Evaluation of five full-text drug databases by pharmacy students, faculty, and librarians: do the groups agree?

PubMed Central

Kupferberg, Natalie; Hartel, Lynda Jones

2004-01-01

Objectives: The purpose of this study is to assess the usefulness of five full-text drug databases as evaluated by medical librarians, pharmacy faculty, and pharmacy students at an academic health center. Study findings and recommendations are offered as guidance to librarians responsible for purchasing decisions. Methods: Four pharmacy students, four pharmacy faculty members, and four medical librarians answered ten drug information questions using the databases AHFS Drug Information (STAT!Ref); DRUGDEX (Micromedex); eFacts (Drug Facts and Comparisons); Lexi-Drugs Online (Lexi-Comp); and the PDR Electronic Library (Micromedex). Participants noted whether each database contained answers to the questions and evaluated each database on ease of navigation, screen readability, overall satisfaction, and product recommendation. Results: While each study group found that DRUGDEX provided the most direct answers to the ten questions, faculty members gave Lexi-Drugs the highest overall rating. Students favored eFacts. The faculty and students found the PDR least useful. Librarians ranked DRUGDEX the highest and AHFS the lowest. The comments of pharmacy faculty and students show that these groups preferred concise, easy-to-use sources; librarians focused on the comprehensiveness, layout, and supporting references of the databases. Conclusion: This study demonstrates the importance of consulting with primary clientele before purchasing databases. Although there are many online drug databases to consider, present findings offer strong support for eFacts, Lexi-Drugs, and DRUGDEX. PMID:14762464

Freely Accessible Chemical Database Resources of Compounds for in Silico Drug Discovery.

PubMed

Yang, JingFang; Wang, Di; Jia, Chenyang; Wang, Mengyao; Hao, GeFei; Yang, GuangFu

2018-05-07

In silico drug discovery has been proved to be a solidly established key component in early drug discovery. However, this task is hampered by the limitation of quantity and quality of compound databases for screening. In order to overcome these obstacles, freely accessible database resources of compounds have bloomed in recent years. Nevertheless, how to choose appropriate tools to treat these freely accessible databases are crucial. To the best of our knowledge, this is the first systematic review on this issue. The existed advantages and drawbacks of chemical databases were analyzed and summarized based on the collected six categories of freely accessible chemical databases from literature in this review. Suggestions on how and in which conditions the usage of these databases could be reasonable were provided. Tools and procedures for building 3D structure chemical libraries were also introduced. In this review, we described the freely accessible chemical database resources for in silico drug discovery. In particular, the chemical information for building chemical database appears as attractive resources for drug design to alleviate experimental pressure. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Application of the 4D Fingerprint Method with a Robust Scoring Function for Scaffold-Hopping and Drug Repurposing Strategies

PubMed Central

2015-01-01

Two factors contribute to the inefficiency associated with screening pharmaceutical library collections as a means of identifying new drugs: [1] the limited success of virtual screening (VS) methods in identifying new scaffolds; [2] the limited accuracy of computational methods in predicting off-target effects. We recently introduced a 3D shape-based similarity algorithm of the SABRE program, which encodes a consensus molecular shape pattern of a set of active ligands into a 4D fingerprint descriptor. Here, we report a mathematical model for shape similarity comparisons and ligand database filtering using this 4D fingerprint method and benchmarked the scoring function HWK (Hamza–Wei–Korotkov), using the 81 targets of the DEKOIS database. Subsequently, we applied our combined 4D fingerprint and HWK scoring function VS approach in scaffold-hopping and drug repurposing using the National Cancer Institute (NCI) and Food and Drug Administration (FDA) databases, and we identified new inhibitors with different scaffolds of MycP1 protease from the mycobacterial ESX-1 secretion system. Experimental evaluation of nine compounds from the NCI database and three from the FDA database displayed IC50 values ranging from 70 to 100 μM against MycP1 and possessed high structural diversity, which provides departure points for further structure–activity relationship (SAR) optimization. In addition, this study demonstrates that the combination of our 4D fingerprint algorithm and the HWK scoring function may provide a means for identifying repurposed drugs for the treatment of infectious diseases and may be used in the drug-target profile strategy. PMID:25229183

Application of the 4D fingerprint method with a robust scoring function for scaffold-hopping and drug repurposing strategies.

PubMed

Hamza, Adel; Wagner, Jonathan M; Wei, Ning-Ning; Kwiatkowski, Stefan; Zhan, Chang-Guo; Watt, David S; Korotkov, Konstantin V

2014-10-27

Two factors contribute to the inefficiency associated with screening pharmaceutical library collections as a means of identifying new drugs: [1] the limited success of virtual screening (VS) methods in identifying new scaffolds; [2] the limited accuracy of computational methods in predicting off-target effects. We recently introduced a 3D shape-based similarity algorithm of the SABRE program, which encodes a consensus molecular shape pattern of a set of active ligands into a 4D fingerprint descriptor. Here, we report a mathematical model for shape similarity comparisons and ligand database filtering using this 4D fingerprint method and benchmarked the scoring function HWK (Hamza-Wei-Korotkov), using the 81 targets of the DEKOIS database. Subsequently, we applied our combined 4D fingerprint and HWK scoring function VS approach in scaffold-hopping and drug repurposing using the National Cancer Institute (NCI) and Food and Drug Administration (FDA) databases, and we identified new inhibitors with different scaffolds of MycP1 protease from the mycobacterial ESX-1 secretion system. Experimental evaluation of nine compounds from the NCI database and three from the FDA database displayed IC50 values ranging from 70 to 100 μM against MycP1 and possessed high structural diversity, which provides departure points for further structure-activity relationship (SAR) optimization. In addition, this study demonstrates that the combination of our 4D fingerprint algorithm and the HWK scoring function may provide a means for identifying repurposed drugs for the treatment of infectious diseases and may be used in the drug-target profile strategy.

Exploring Chemical Space for Drug Discovery Using the Chemical Universe Database

PubMed Central

2012-01-01

Herein we review our recent efforts in searching for bioactive ligands by enumeration and virtual screening of the unknown chemical space of small molecules. Enumeration from first principles shows that almost all small molecules (>99.9%) have never been synthesized and are still available to be prepared and tested. We discuss open access sources of molecules, the classification and representation of chemical space using molecular quantum numbers (MQN), its exhaustive enumeration in form of the chemical universe generated databases (GDB), and examples of using these databases for prospective drug discovery. MQN-searchable GDB, PubChem, and DrugBank are freely accessible at www.gdb.unibe.ch. PMID:23019491

PubChem BioAssay: A Decade's Development toward Open High-Throughput Screening Data Sharing.

PubMed

Wang, Yanli; Cheng, Tiejun; Bryant, Stephen H

2017-07-01

High-throughput screening (HTS) is now routinely conducted for drug discovery by both pharmaceutical companies and screening centers at academic institutions and universities. Rapid advance in assay development, robot automation, and computer technology has led to the generation of terabytes of data in screening laboratories. Despite the technology development toward HTS productivity, fewer efforts were devoted to HTS data integration and sharing. As a result, the huge amount of HTS data was rarely made available to the public. To fill this gap, the PubChem BioAssay database ( https://www.ncbi.nlm.nih.gov/pcassay/ ) was set up in 2004 to provide open access to the screening results tested on chemicals and RNAi reagents. With more than 10 years' development and contributions from the community, PubChem has now become the largest public repository for chemical structures and biological data, which provides an information platform to worldwide researchers supporting drug development, medicinal chemistry study, and chemical biology research. This work presents a review of the HTS data content in the PubChem BioAssay database and the progress of data deposition to stimulate knowledge discovery and data sharing. It also provides a description of the database's data standard and basic utilities facilitating information access and use for new users.

A knowledge-based approach for identification of drugs against vivapain-2 protein of Plasmodium vivax through pharmacophore-based virtual screening with comparative modelling.

PubMed

Yadav, Manoj Kumar; Singh, Amisha; Swati, D

2014-08-01

Malaria is one of the most infectious diseases in the world. Plasmodium vivax, the pathogen causing endemic malaria in humans worldwide, is responsible for extensive disease morbidity. Due to the emergence of resistance to common anti-malarial drugs, there is a continuous need to develop a new class of drugs for this pathogen. P. vivax cysteine protease, also known as vivapain-2, plays an important role in haemoglobin hydrolysis and is considered essential for the survival of the parasite. The three-dimensional (3D) structure of vivapain-2 is not predicted experimentally, so its structure is modelled by using comparative modelling approach and further validated by Qualitative Model Energy Analysis (QMEAN) and RAMPAGE tools. The potential binding site of selected vivapain-2 structure has been detected by grid-based function prediction method. Drug targets and their respective drugs similar to vivapain-2 have been identified using three publicly available databases: STITCH 3.1, DrugBank and Therapeutic Target Database (TTD). The second approach of this work focuses on docking study of selected drug E-64 against vivapain-2 protein. Docking reveals crucial information about key residues (Asn281, Cys283, Val396 and Asp398) that are responsible for holding the ligand in the active site. The similarity-search criterion is used for the preparation of our in-house database of drugs, obtained from filtering the drugs from the DrugBank database. A five-point 3D pharmacophore model is generated for the docked complex of vivapain-2 with E-64. This study of 3D pharmacophore-based virtual screening results in identifying three new drugs, amongst which one is approved and the other two are experimentally proved. The ADMET properties of these drugs are found to be in the desired range. These drugs with novel scaffolds may act as potent drugs for treating malaria caused by P. vivax.

Chemical Space: Big Data Challenge for Molecular Diversity.

PubMed

Awale, Mahendra; Visini, Ricardo; Probst, Daniel; Arús-Pous, Josep; Reymond, Jean-Louis

2017-10-25

Chemical space describes all possible molecules as well as multi-dimensional conceptual spaces representing the structural diversity of these molecules. Part of this chemical space is available in public databases ranging from thousands to billions of compounds. Exploiting these databases for drug discovery represents a typical big data problem limited by computational power, data storage and data access capacity. Here we review recent developments of our laboratory, including progress in the chemical universe databases (GDB) and the fragment subset FDB-17, tools for ligand-based virtual screening by nearest neighbor searches, such as our multi-fingerprint browser for the ZINC database to select purchasable screening compounds, and their application to discover potent and selective inhibitors for calcium channel TRPV6 and Aurora A kinase, the polypharmacology browser (PPB) for predicting off-target effects, and finally interactive 3D-chemical space visualization using our online tools WebDrugCS and WebMolCS. All resources described in this paper are available for public use at www.gdb.unibe.ch.

Efficient method for high-throughput virtual screening based on flexible docking: discovery of novel acetylcholinesterase inhibitors.

PubMed

Mizutani, Miho Yamada; Itai, Akiko

2004-09-23

A method of easily finding ligands, with a variety of core structures, for a given target macromolecule would greatly contribute to the rapid identification of novel lead compounds for drug development. We have developed an efficient method for discovering ligand candidates from a number of flexible compounds included in databases, when the three-dimensional (3D) structure of the drug target is available. The method, named ADAM&EVE, makes use of our automated docking method ADAM, which has already been reported. Like ADAM, ADAM&EVE takes account of the flexibility of each molecule in databases, by exploring the conformational space fully and continuously. Database screening has been made much faster than with ADAM through the tuning of parameters, so that computational screening of several hundred thousand compounds is possible in a practical time. Promising ligand candidates can be selected according to various criteria based on the docking results and characteristics of compounds. Furthermore, we have developed a new tool, EVE-MAKE, for automatically preparing the additional compound data necessary for flexible docking calculation, prior to 3D database screening. Among several successful cases of lead discovery by ADAM&EVE, the finding of novel acetylcholinesterase (AChE) inhibitors is presented here. We performed a virtual screening of about 160 000 commercially available compounds against the X-ray crystallographic structure of AChE. Among 114 compounds that could be purchased and assayed, 35 molecules with various core structures showed inhibitory activities with IC(50) values less than 100 microM. Thirteen compounds had IC(50) values between 0.5 and 10 microM, and almost all their core structures are very different from those of known inhibitors. The results demonstrate the effectiveness and validity of the ADAM&EVE approach and provide a starting point for development of novel drugs to treat Alzheimer's disease.

FilTer BaSe: A web accessible chemical database for small compound libraries.

PubMed

Kolte, Baban S; Londhe, Sanjay R; Solanki, Bhushan R; Gacche, Rajesh N; Meshram, Rohan J

2018-03-01

Finding novel chemical agents for targeting disease associated drug targets often requires screening of large number of new chemical libraries. In silico methods are generally implemented at initial stages for virtual screening. Filtering of such compound libraries on physicochemical and substructure ground is done to ensure elimination of compounds with undesired chemical properties. Filtering procedure, is redundant, time consuming and requires efficient bioinformatics/computer manpower along with high end software involving huge capital investment that forms a major obstacle in drug discovery projects in academic setup. We present an open source resource, FilTer BaSe- a chemoinformatics platform (http://bioinfo.net.in/filterbase/) that host fully filtered, ready to use compound libraries with workable size. The resource also hosts a database that enables efficient searching the chemical space of around 348,000 compounds on the basis of physicochemical and substructure properties. Ready to use compound libraries and database presented here is expected to aid a helping hand for new drug developers and medicinal chemists. Copyright © 2017 Elsevier Inc. All rights reserved.

PDQ® Cancer Information

Cancer.gov

An NCI database that contains the latest information about cancer treatment, screening, prevention, genetics, supportive care, and complementary and alternative medicine, plus drug information and a dictionary of cancer terms.

A high-sensitivity ultra-high performance liquid chromatography/high-resolution time-of-flight mass spectrometry (UHPLC-HR-TOFMS) method for screening synthetic cannabinoids and other drugs of abuse in urine.

PubMed

Sundström, Mira; Pelander, Anna; Angerer, Verena; Hutter, Melanie; Kneisel, Stefan; Ojanperä, Ilkka

2013-10-01

The continuing emergence of designer drugs imposes high demands on the scope and sensitivity of toxicological drug screening procedures. An ultra-high performance liquid chromatography/high-resolution time-of-flight mass spectrometry (UHPLC-HR-TOFMS) method was developed for screening and simultaneous confirmation of both designer drugs and other drugs of abuse in urine samples in a single run. The method covered selected synthetic cannabinoids and cathinones, amphetamines, natural cannabinoids, opioids, cocaine and other important drugs of abuse, together with their main urinary metabolites. The database consisted of 277 compounds with molecular formula and exact monoisotopic mass; retention time was included for 192 compounds, and primary and secondary qualifier ion exact mass for 191 and 95 compounds, respectively. Following a solid-phase extraction, separation was performed by UHPLC and mass analysis by HR-TOFMS. MS, and broad-band collision-induced dissociation data were acquired at m/z range 50-700. Compound identification was based on a reverse database search with acceptance criteria for retention time, precursor ion mass accuracy, isotopic pattern and abundance of qualifier ions. Mass resolving power in spiked urine samples was on average FWHM 23,500 and mass accuracy 0.3 mDa. The mean and median cut-off concentrations determined for 75 compounds were 4.2 and 1 ng/mL, respectively. The range of cut-off concentrations for synthetic cannabinoids was 0.2-60 ng/mL and for cathinones 0.7-15 ng/mL. The method proved to combine high sensitivity and a wide scope in a manner not previously reported in drugs of abuse screening. The method's feasibility was demonstrated with 50 authentic urine samples.

An Automated System Combining Safety Signal Detection and Prioritization from Healthcare Databases: A Pilot Study.

PubMed

Arnaud, Mickael; Bégaud, Bernard; Thiessard, Frantz; Jarrion, Quentin; Bezin, Julien; Pariente, Antoine; Salvo, Francesco

2018-04-01

Signal detection from healthcare databases is possible, but is not yet used for routine surveillance of drug safety. One challenge is to develop methods for selecting signals that should be assessed with priority. The aim of this study was to develop an automated system combining safety signal detection and prioritization from healthcare databases and applicable to drugs used in chronic diseases. Patients present in the French EGB healthcare database for at least 1 year between 2005 and 2015 were considered. Noninsulin glucose-lowering drugs (NIGLDs) were selected as a case study, and hospitalization data were used to select important medical events (IME). Signal detection was performed quarterly from 2008 to 2015 using sequence symmetry analysis. NIGLD/IME associations were screened if one or more exposed case was identified in the quarter, and three or more exposed cases were identified in the population at the date of screening. Detected signals were prioritized using the Longitudinal-SNIP (L-SNIP) algorithm based on strength (S), novelty (N), and potential impact of signal (I), and pattern of drug use (P). Signals scored in the top 10% were identified as of high priority. A reference set was built based on NIGLD summaries of product characteristics (SPCs) to compute the performance of the developed system. A total of 815 associations were screened and 241 (29.6%) were detected as signals; among these, 58 (24.1%) were prioritized. The performance for signal detection was sensitivity = 47%; specificity = 80%; positive predictive value (PPV) 33%; negative predictive value = 82%. The use of the L-SNIP algorithm increased the early identification of positive controls, restricted to those mentioned in the SPCs after 2008: PPV = 100% versus PPV = 14% with its non-use. The system revealed a strong new signal with dipeptidylpeptidase-4 inhibitors and venous thromboembolism. The developed system seems promising for the routine use of healthcare data for safety surveillance of drugs used in chronic diseases.

Discovery of novel human acrosin inhibitors by virtual screening

NASA Astrophysics Data System (ADS)

Liu, Xuefei; Dong, Guoqiang; Zhang, Jue; Qi, Jingjing; Zheng, Canhui; Zhou, Youjun; Zhu, Ju; Sheng, Chunquan; Lü, Jiaguo

2011-10-01

Human acrosin is an attractive target for the discovery of male contraceptive drugs. For the first time, structure-based drug design was applied to discover structurally diverse human acrosin inhibitors. A parallel virtual screening strategy in combination with pharmacophore-based and docking-based techniques was used to screen the SPECS database. From 16 compounds selected by virtual screening, a total of 10 compounds were found to be human acrosin inhibitors. Compound 2 was found to be the most potent hit (IC50 = 14 μM) and its binding mode was investigated by molecular dynamics simulations. The hit interacted with human acrosin mainly through hydrophobic and hydrogen-bonding interactions, which provided a good starting structure for further optimization studies.

Exploration of natural product ingredients as inhibitors of human HMG-CoA reductase through structure-based virtual screening.

PubMed

Lin, Shih-Hung; Huang, Kao-Jean; Weng, Ching-Feng; Shiuan, David

2015-01-01

Cholesterol plays an important role in living cells. However, a very high level of cholesterol may lead to atherosclerosis. HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase is the key enzyme in the cholesterol biosynthesis pathway, and the statin-like drugs are inhibitors of human HMG-CoA reductase (hHMGR). The present study aimed to virtually screen for potential hHMGR inhibitors from natural product to discover hypolipidemic drug candidates with fewer side effects and lesser toxicities. We used the 3D structure 1HWK from the PDB (Protein Data Bank) database of hHMGR as the target to screen for the strongly bound compounds from the traditional Chinese medicine database. Many interesting molecules including polyphenolic compounds, polisubstituted heterocyclics, and linear lipophilic alcohols were identified and their ADMET (absorption, disrtibution, metabolism, excretion, toxicity) properties were predicted. Finally, four compounds were obtained for the in vitro validation experiments. The results indicated that curcumin and salvianolic acid C can effectively inhibit hHMGR, with IC50 (half maximal inhibitory concentration) values of 4.3 µM and 8 µM, respectively. The present study also demonstrated the feasibility of discovering new drug candidates through structure-based virtual screening.

Complete genome-wide screening and subtractive genomic approach revealed new virulence factors, potential drug targets against bio-war pathogen Brucella melitensis 16M

PubMed Central

Pradeepkiran, Jangampalli Adi; Sainath, Sri Bhashyam; Kumar, Konidala Kranthi; Bhaskar, Matcha

2015-01-01

Brucella melitensis 16M is a Gram-negative coccobacillus that infects both animals and humans. It causes a disease known as brucellosis, which is characterized by acute febrile illness in humans and causes abortions in livestock. To prevent and control brucellosis, identification of putative drug targets is crucial. The present study aimed to identify drug targets in B. melitensis 16M by using a subtractive genomic approach. We used available database repositories (Database of Essential Genes, Kyoto Encyclopedia of Genes and Genomes Automatic Annotation Server, and Kyoto Encyclopedia of Genes and Genomes) to identify putative genes that are nonhomologous to humans and essential for pathogen B. melitensis 16M. The results revealed that among 3 Mb genome size of pathogen, 53 putative characterized and 13 uncharacterized hypothetical genes were identified; further, from Basic Local Alignment Search Tool protein analysis, one hypothetical protein showed a close resemblance (50%) to Silicibacter pomeroyi DUF1285 family protein (2RE3). A further homology model of the target was constructed using MODELLER 9.12 and optimized through variable target function method by molecular dynamics optimization with simulating annealing. The stereochemical quality of the restrained model was evaluated by PROCHECK, VERIFY-3D, ERRAT, and WHATIF servers. Furthermore, structure-based virtual screening was carried out against the predicted active site of the respective protein using the glycerol structural analogs from the PubChem database. We identified five best inhibitors with strong affinities, stable interactions, and also with reliable drug-like properties. Hence, these leads might be used as the most effective inhibitors of modeled protein. The outcome of the present work of virtual screening of putative gene targets might facilitate design of potential drugs for better treatment against brucellosis. PMID:25834405

LigandBox: A database for 3D structures of chemical compounds

PubMed Central

Kawabata, Takeshi; Sugihara, Yusuke; Fukunishi, Yoshifumi; Nakamura, Haruki

2013-01-01

A database for the 3D structures of available compounds is essential for the virtual screening by molecular docking. We have developed the LigandBox database (http://ligandbox.protein.osaka-u.ac.jp/ligandbox/) containing four million available compounds, collected from the catalogues of 37 commercial suppliers, and approved drugs and biochemical compounds taken from KEGG_DRUG, KEGG_COMPOUND and PDB databases. Each chemical compound in the database has several 3D conformers with hydrogen atoms and atomic charges, which are ready to be docked into receptors using docking programs. The 3D conformations were generated using our molecular simulation program package, myPresto. Various physical properties, such as aqueous solubility (LogS) and carcinogenicity have also been calculated to characterize the ADME-Tox properties of the compounds. The Web database provides two services for compound searches: a property/chemical ID search and a chemical structure search. The chemical structure search is performed by a descriptor search and a maximum common substructure (MCS) search combination, using our program kcombu. By specifying a query chemical structure, users can find similar compounds among the millions of compounds in the database within a few minutes. Our database is expected to assist a wide range of researchers, in the fields of medical science, chemical biology, and biochemistry, who are seeking to discover active chemical compounds by the virtual screening. PMID:27493549

LigandBox: A database for 3D structures of chemical compounds.

PubMed

Kawabata, Takeshi; Sugihara, Yusuke; Fukunishi, Yoshifumi; Nakamura, Haruki

2013-01-01

A database for the 3D structures of available compounds is essential for the virtual screening by molecular docking. We have developed the LigandBox database (http://ligandbox.protein.osaka-u.ac.jp/ligandbox/) containing four million available compounds, collected from the catalogues of 37 commercial suppliers, and approved drugs and biochemical compounds taken from KEGG_DRUG, KEGG_COMPOUND and PDB databases. Each chemical compound in the database has several 3D conformers with hydrogen atoms and atomic charges, which are ready to be docked into receptors using docking programs. The 3D conformations were generated using our molecular simulation program package, myPresto. Various physical properties, such as aqueous solubility (LogS) and carcinogenicity have also been calculated to characterize the ADME-Tox properties of the compounds. The Web database provides two services for compound searches: a property/chemical ID search and a chemical structure search. The chemical structure search is performed by a descriptor search and a maximum common substructure (MCS) search combination, using our program kcombu. By specifying a query chemical structure, users can find similar compounds among the millions of compounds in the database within a few minutes. Our database is expected to assist a wide range of researchers, in the fields of medical science, chemical biology, and biochemistry, who are seeking to discover active chemical compounds by the virtual screening.

New drug candidates for liposomal delivery identified by computer modeling of liposomes' remote loading and leakage.

PubMed

Cern, Ahuva; Marcus, David; Tropsha, Alexander; Barenholz, Yechezkel; Goldblum, Amiram

2017-04-28

Remote drug loading into nano-liposomes is in most cases the best method for achieving high concentrations of active pharmaceutical ingredients (API) per nano-liposome that enable therapeutically viable API-loaded nano-liposomes, referred to as nano-drugs. This approach also enables controlled drug release. Recently, we constructed computational models to identify APIs that can achieve the desired high concentrations in nano-liposomes by remote loading. While those previous models included a broad spectrum of experimental conditions and dealt only with loading, here we reduced the scope to the molecular characteristics alone. We model and predict API suitability for nano-liposomal delivery by fixing the main experimental conditions: liposome lipid composition and size to be similar to those of Doxil® liposomes. On that basis, we add a prediction of drug leakage from the nano-liposomes during storage. The latter is critical for having pharmaceutically viable nano-drugs. The "load and leak" models were used to screen two large molecular databases in search of candidate APIs for delivery by nano-liposomes. The distribution of positive instances in both loading and leakage models was similar in the two databases screened. The screening process identified 667 molecules that were positives by both loading and leakage models (i.e., both high-loading and stable). Among them, 318 molecules received a high score in both properties and of these, 67 are FDA-approved drugs. This group of molecules, having diverse pharmacological activities, may be the basis for future liposomal drug development. Copyright © 2017 Elsevier B.V. All rights reserved.

Discovery of Novel HIV-1 Integrase Inhibitors Using QSAR-Based Virtual Screening of the NCI Open Database.

PubMed

Ko, Gene M; Garg, Rajni; Bailey, Barbara A; Kumar, Sunil

2016-01-01

Quantitative structure-activity relationship (QSAR) models can be used as a predictive tool for virtual screening of chemical libraries to identify novel drug candidates. The aims of this paper were to report the results of a study performed for descriptor selection, QSAR model development, and virtual screening for identifying novel HIV-1 integrase inhibitor drug candidates. First, three evolutionary algorithms were compared for descriptor selection: differential evolution-binary particle swarm optimization (DE-BPSO), binary particle swarm optimization, and genetic algorithms. Next, three QSAR models were developed from an ensemble of multiple linear regression, partial least squares, and extremely randomized trees models. A comparison of the performances of three evolutionary algorithms showed that DE-BPSO has a significant improvement over the other two algorithms. QSAR models developed in this study were used in consensus as a predictive tool for virtual screening of the NCI Open Database containing 265,242 compounds to identify potential novel HIV-1 integrase inhibitors. Six compounds were predicted to be highly active (plC50 > 6) by each of the three models. The use of a hybrid evolutionary algorithm (DE-BPSO) for descriptor selection and QSAR model development in drug design is a novel approach. Consensus modeling may provide better predictivity by taking into account a broader range of chemical properties within the data set conducive for inhibition that may be missed by an individual model. The six compounds identified provide novel drug candidate leads in the design of next generation HIV- 1 integrase inhibitors targeting drug resistant mutant viruses.

gWEGA: GPU-accelerated WEGA for molecular superposition and shape comparison.

PubMed

Yan, Xin; Li, Jiabo; Gu, Qiong; Xu, Jun

2014-06-05

Virtual screening of a large chemical library for drug lead identification requires searching/superimposing a large number of three-dimensional (3D) chemical structures. This article reports a graphic processing unit (GPU)-accelerated weighted Gaussian algorithm (gWEGA) that expedites shape or shape-feature similarity score-based virtual screening. With 86 GPU nodes (each node has one GPU card), gWEGA can screen 110 million conformations derived from an entire ZINC drug-like database with diverse antidiabetic agents as query structures within 2 s (i.e., screening more than 55 million conformations per second). The rapid screening speed was accomplished through the massive parallelization on multiple GPU nodes and rapid prescreening of 3D structures (based on their shape descriptors and pharmacophore feature compositions). Copyright © 2014 Wiley Periodicals, Inc.

Developing science gateways for drug discovery in a grid environment.

PubMed

Pérez-Sánchez, Horacio; Rezaei, Vahid; Mezhuyev, Vitaliy; Man, Duhu; Peña-García, Jorge; den-Haan, Helena; Gesing, Sandra

2016-01-01

Methods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources. To this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows. Our implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.

Designing Second Generation Anti-Alzheimer Compounds as Inhibitors of Human Acetylcholinesterase: Computational Screening of Synthetic Molecules and Dietary Phytochemicals

PubMed Central

Amat-ur-Rasool, Hafsa; Ahmed, Mehboob

2015-01-01

Alzheimer's disease (AD), a big cause of memory loss, is a progressive neurodegenerative disorder. The disease leads to irreversible loss of neurons that result in reduced level of acetylcholine neurotransmitter (ACh). The reduction of ACh level impairs brain functioning. One aspect of AD therapy is to maintain ACh level up to a safe limit, by blocking acetylcholinesterase (AChE), an enzyme that is naturally responsible for its degradation. This research presents an in-silico screening and designing of hAChE inhibitors as potential anti-Alzheimer drugs. Molecular docking results of the database retrieved (synthetic chemicals and dietary phytochemicals) and self-drawn ligands were compared with Food and Drug Administration (FDA) approved drugs against AD as controls. Furthermore, computational ADME studies were performed on the hits to assess their safety. Human AChE was found to be most approptiate target site as compared to commonly used Torpedo AChE. Among the tested dietry phytochemicals, berberastine, berberine, yohimbine, sanguinarine, elemol and naringenin are the worth mentioning phytochemicals as potential anti-Alzheimer drugs The synthetic leads were mostly dual binding site inhibitors with two binding subunits linked by a carbon chain i.e. second generation AD drugs. Fifteen new heterodimers were designed that were computationally more efficient inhibitors than previously reported compounds. Using computational methods, compounds present in online chemical databases can be screened to design more efficient and safer drugs against cognitive symptoms of AD. PMID:26325402

Designing Second Generation Anti-Alzheimer Compounds as Inhibitors of Human Acetylcholinesterase: Computational Screening of Synthetic Molecules and Dietary Phytochemicals.

PubMed

Amat-Ur-Rasool, Hafsa; Ahmed, Mehboob

2015-01-01

Alzheimer's disease (AD), a big cause of memory loss, is a progressive neurodegenerative disorder. The disease leads to irreversible loss of neurons that result in reduced level of acetylcholine neurotransmitter (ACh). The reduction of ACh level impairs brain functioning. One aspect of AD therapy is to maintain ACh level up to a safe limit, by blocking acetylcholinesterase (AChE), an enzyme that is naturally responsible for its degradation. This research presents an in-silico screening and designing of hAChE inhibitors as potential anti-Alzheimer drugs. Molecular docking results of the database retrieved (synthetic chemicals and dietary phytochemicals) and self-drawn ligands were compared with Food and Drug Administration (FDA) approved drugs against AD as controls. Furthermore, computational ADME studies were performed on the hits to assess their safety. Human AChE was found to be most approptiate target site as compared to commonly used Torpedo AChE. Among the tested dietry phytochemicals, berberastine, berberine, yohimbine, sanguinarine, elemol and naringenin are the worth mentioning phytochemicals as potential anti-Alzheimer drugs The synthetic leads were mostly dual binding site inhibitors with two binding subunits linked by a carbon chain i.e. second generation AD drugs. Fifteen new heterodimers were designed that were computationally more efficient inhibitors than previously reported compounds. Using computational methods, compounds present in online chemical databases can be screened to design more efficient and safer drugs against cognitive symptoms of AD.

Drug search for leishmaniasis: a virtual screening approach by grid computing

NASA Astrophysics Data System (ADS)

Ochoa, Rodrigo; Watowich, Stanley J.; Flórez, Andrés; Mesa, Carol V.; Robledo, Sara M.; Muskus, Carlos

2016-07-01

The trypanosomatid protozoa Leishmania is endemic in 100 countries, with infections causing 2 million new cases of leishmaniasis annually. Disease symptoms can include severe skin and mucosal ulcers, fever, anemia, splenomegaly, and death. Unfortunately, therapeutics approved to treat leishmaniasis are associated with potentially severe side effects, including death. Furthermore, drug-resistant Leishmania parasites have developed in most endemic countries. To address an urgent need for new, safe and inexpensive anti-leishmanial drugs, we utilized the IBM World Community Grid to complete computer-based drug discovery screens (Drug Search for Leishmaniasis) using unique leishmanial proteins and a database of 600,000 drug-like small molecules. Protein structures from different Leishmania species were selected for molecular dynamics (MD) simulations, and a series of conformational "snapshots" were chosen from each MD trajectory to simulate the protein's flexibility. A Relaxed Complex Scheme methodology was used to screen 2000 MD conformations against the small molecule database, producing >1 billion protein-ligand structures. For each protein target, a binding spectrum was calculated to identify compounds predicted to bind with highest average affinity to all protein conformations. Significantly, four different Leishmania protein targets were predicted to strongly bind small molecules, with the strongest binding interactions predicted to occur for dihydroorotate dehydrogenase (LmDHODH; PDB:3MJY). A number of predicted tight-binding LmDHODH inhibitors were tested in vitro and potent selective inhibitors of Leishmania panamensis were identified. These promising small molecules are suitable for further development using iterative structure-based optimization and in vitro/in vivo validation assays.

Drug search for leishmaniasis: a virtual screening approach by grid computing.

PubMed

Ochoa, Rodrigo; Watowich, Stanley J; Flórez, Andrés; Mesa, Carol V; Robledo, Sara M; Muskus, Carlos

2016-07-01

The trypanosomatid protozoa Leishmania is endemic in ~100 countries, with infections causing ~2 million new cases of leishmaniasis annually. Disease symptoms can include severe skin and mucosal ulcers, fever, anemia, splenomegaly, and death. Unfortunately, therapeutics approved to treat leishmaniasis are associated with potentially severe side effects, including death. Furthermore, drug-resistant Leishmania parasites have developed in most endemic countries. To address an urgent need for new, safe and inexpensive anti-leishmanial drugs, we utilized the IBM World Community Grid to complete computer-based drug discovery screens (Drug Search for Leishmaniasis) using unique leishmanial proteins and a database of 600,000 drug-like small molecules. Protein structures from different Leishmania species were selected for molecular dynamics (MD) simulations, and a series of conformational "snapshots" were chosen from each MD trajectory to simulate the protein's flexibility. A Relaxed Complex Scheme methodology was used to screen ~2000 MD conformations against the small molecule database, producing >1 billion protein-ligand structures. For each protein target, a binding spectrum was calculated to identify compounds predicted to bind with highest average affinity to all protein conformations. Significantly, four different Leishmania protein targets were predicted to strongly bind small molecules, with the strongest binding interactions predicted to occur for dihydroorotate dehydrogenase (LmDHODH; PDB:3MJY). A number of predicted tight-binding LmDHODH inhibitors were tested in vitro and potent selective inhibitors of Leishmania panamensis were identified. These promising small molecules are suitable for further development using iterative structure-based optimization and in vitro/in vivo validation assays.

Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database

PubMed Central

Butkiewicz, Mariusz; Lowe, Edward W.; Mueller, Ralf; Mendenhall, Jeffrey L.; Teixeira, Pedro L.; Weaver, C. David; Meiler, Jens

2013-01-01

With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR) models are built using Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Decision Trees (DTs), and Kohonen networks (KNs). Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS) and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed. PMID:23299552

Application of the ToxMiner Database: Network Analysis of ...

EPA Pesticide Factsheets

The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effective alternatives to animal testing. The chemicals selected for Phase I are composed largely by a diverse set of pesticide active ingredients, which had sufficient supporting in vivo data included as part of their registration process with the EPA. Other miscellaneous chemicals of environmental concern were also included. Application of HTS to environmental toxicants is a novel approach to predictive toxicology and health risk assessment, and differs from what is required for drug efficacy screening in that biochemical interaction of environmental chemicals are sometimes weaker than that seen with drugs and their intended targets. Additionally, the chemical space covered by environmental chemicals is much broader compared to that of pharmaceuticals. The ToxMiner database has been created and added to the EPA’s ACToR (Aggregated Computational Toxicology Resource) chemical database. One purpose of the ToxMiner database is to link biological, metabolic and cellular pathway data to genes and in vitro assay data for the initial subset of chemicals screened in the ToxCast Phase I HTS assays. Also included in ToxMiner is human disease information, which correlates with ToxCast assays that tar

Application of the ToxMiner Database: Network Analysis ...

EPA Pesticide Factsheets

The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effective alternatives to animal testing. The chemicals selected for Phase I are composed largely by a diverse set of pesticide active ingredients, which had sufficient supporting in vivo data included as part of their registration process with the EPA. Other miscellaneous chemicals of environmental concern were also included. Application of HTS to environmental toxicants is a novel approach to predictive toxicology and health risk assessment, and differs from what is required for drug efficacy screening in that biochemical interaction of environmental chemicals are sometimes weaker than that seen with drugs and their intended targets. Additionally, the chemical space covered by environmental chemicals is much broader compared to that of pharmaceuticals. The ToxMiner database has been created and added to the EPA’s ACToR (Aggregated Computational Toxicology Resource) chemical database. One purpose of the ToxMiner database is to link biological, metabolic, and cellular pathway data to genes and in vitro assay data for the initial subset of chemicals screened in the ToxCast Phase I HTS assays. Also included in ToxMiner is human disease information, which correlates with ToxCast assays that ta

Molecular Quantum Similarity, Chemical Reactivity and Database Screening of 3D Pharmacophores of the Protein Kinases A, B and G from Mycobacterium tuberculosis.

PubMed

Morales-Bayuelo, Alejandro

2017-06-21

Mycobacterium tuberculosis remains one of the world's most devastating pathogens. For this reason, we developed a study involving 3D pharmacophore searching, selectivity analysis and database screening for a series of anti-tuberculosis compounds, associated with the protein kinases A, B, and G. This theoretical study is expected to shed some light onto some molecular aspects that could contribute to the knowledge of the molecular mechanics behind interactions of these compounds, with anti-tuberculosis activity. Using the Molecular Quantum Similarity field and reactivity descriptors supported in the Density Functional Theory, it was possible to measure the quantification of the steric and electrostatic effects through the Overlap and Coulomb quantitative convergence (alpha and beta) scales. In addition, an analysis of reactivity indices using global and local descriptors was developed, identifying the binding sites and selectivity on these anti-tuberculosis compounds in the active sites. Finally, the reported pharmacophores to PKn A, B and G, were used to carry out database screening, using a database with anti-tuberculosis drugs from the Kelly Chibale research group (http://www.kellychibaleresearch.uct.ac.za/), to find the compounds with affinity for the specific protein targets associated with PKn A, B and G. In this regard, this hybrid methodology (Molecular Mechanic/Quantum Chemistry) shows new insights into drug design that may be useful in the tuberculosis treatment today.

Fragment virtual screening based on Bayesian categorization for discovering novel VEGFR-2 scaffolds.

PubMed

Zhang, Yanmin; Jiao, Yu; Xiong, Xiao; Liu, Haichun; Ran, Ting; Xu, Jinxing; Lu, Shuai; Xu, Anyang; Pan, Jing; Qiao, Xin; Shi, Zhihao; Lu, Tao; Chen, Yadong

2015-11-01

The discovery of novel scaffolds against a specific target has long been one of the most significant but challengeable goals in discovering lead compounds. A scaffold that binds in important regions of the active pocket is more favorable as a starting point because scaffolds generally possess greater optimization possibilities. However, due to the lack of sufficient chemical space diversity of the databases and the ineffectiveness of the screening methods, it still remains a great challenge to discover novel active scaffolds. Since the strengths and weaknesses of both fragment-based drug design and traditional virtual screening (VS), we proposed a fragment VS concept based on Bayesian categorization for the discovery of novel scaffolds. This work investigated the proposal through an application on VEGFR-2 target. Firstly, scaffold and structural diversity of chemical space for 10 compound databases were explicitly evaluated. Simultaneously, a robust Bayesian classification model was constructed for screening not only compound databases but also their corresponding fragment databases. Although analysis of the scaffold diversity demonstrated a very unevenly distribution of scaffolds over molecules, results showed that our Bayesian model behaved better in screening fragments than molecules. Through a literature retrospective research, several generated fragments with relatively high Bayesian scores indeed exhibit VEGFR-2 biological activity, which strongly proved the effectiveness of fragment VS based on Bayesian categorization models. This investigation of Bayesian-based fragment VS can further emphasize the necessity for enrichment of compound databases employed in lead discovery by amplifying the diversity of databases with novel structures.

Building a medical image processing algorithm verification database

NASA Astrophysics Data System (ADS)

Brown, C. Wayne

2000-06-01

The design of a database containing head Computed Tomography (CT) studies is presented, along with a justification for the database's composition. The database will be used to validate software algorithms that screen normal head CT studies from studies that contain pathology. The database is designed to have the following major properties: (1) a size sufficient for statistical viability, (2) inclusion of both normal (no pathology) and abnormal scans, (3) inclusion of scans due to equipment malfunction, technologist error, and uncooperative patients, (4) inclusion of data sets from multiple scanner manufacturers, (5) inclusion of data sets from different gender and age groups, and (6) three independent diagnosis of each data set. Designed correctly, the database will provide a partial basis for FDA (United States Food and Drug Administration) approval of image processing algorithms for clinical use. Our goal for the database is the proof of viability of screening head CT's for normal anatomy using computer algorithms. To put this work into context, a classification scheme for 'computer aided diagnosis' systems is proposed.

[Adverse Effect Predictions Based on Computational Toxicology Techniques and Large-scale Databases].

PubMed

Uesawa, Yoshihiro

2018-01-01

　Understanding the features of chemical structures related to the adverse effects of drugs is useful for identifying potential adverse effects of new drugs. This can be based on the limited information available from post-marketing surveillance, assessment of the potential toxicities of metabolites and illegal drugs with unclear characteristics, screening of lead compounds at the drug discovery stage, and identification of leads for the discovery of new pharmacological mechanisms. This present paper describes techniques used in computational toxicology to investigate the content of large-scale spontaneous report databases of adverse effects, and it is illustrated with examples. Furthermore, volcano plotting, a new visualization method for clarifying the relationships between drugs and adverse effects via comprehensive analyses, will be introduced. These analyses may produce a great amount of data that can be applied to drug repositioning.

When drug discovery meets web search: Learning to Rank for ligand-based virtual screening.

PubMed

Zhang, Wei; Ji, Lijuan; Chen, Yanan; Tang, Kailin; Wang, Haiping; Zhu, Ruixin; Jia, Wei; Cao, Zhiwei; Liu, Qi

2015-01-01

The rapid increase in the emergence of novel chemical substances presents a substantial demands for more sophisticated computational methodologies for drug discovery. In this study, the idea of Learning to Rank in web search was presented in drug virtual screening, which has the following unique capabilities of 1). Applicable of identifying compounds on novel targets when there is not enough training data available for these targets, and 2). Integration of heterogeneous data when compound affinities are measured in different platforms. A standard pipeline was designed to carry out Learning to Rank in virtual screening. Six Learning to Rank algorithms were investigated based on two public datasets collected from Binding Database and the newly-published Community Structure-Activity Resource benchmark dataset. The results have demonstrated that Learning to rank is an efficient computational strategy for drug virtual screening, particularly due to its novel use in cross-target virtual screening and heterogeneous data integration. To the best of our knowledge, we have introduced here the first application of Learning to Rank in virtual screening. The experiment workflow and algorithm assessment designed in this study will provide a standard protocol for other similar studies. All the datasets as well as the implementations of Learning to Rank algorithms are available at http://www.tongji.edu.cn/~qiliu/lor_vs.html. Graphical AbstractThe analogy between web search and ligand-based drug discovery.

Exploiting PubChem for Virtual Screening

PubMed Central

Xie, Xiang-Qun

2011-01-01

Importance of the field PubChem is a public molecular information repository, a scientific showcase of the NIH Roadmap Initiative. The PubChem database holds over 27 million records of unique chemical structures of compounds (CID) derived from nearly 70 million substance depositions (SID), and contains more than 449,000 bioassay records with over thousands of in vitro biochemical and cell-based screening bioassays established, with targeting more than 7000 proteins and genes linking to over 1.8 million of substances. Areas covered in this review This review builds on recent PubChem-related computational chemistry research reported by other authors while providing readers with an overview of the PubChem database, focusing on its increasing role in cheminformatics, virtual screening and toxicity prediction modeling. What the reader will gain These publicly available datasets in PubChem provide great opportunities for scientists to perform cheminformatics and virtual screening research for computer-aided drug design. However, the high volume and complexity of the datasets, in particular the bioassay-associated false positives/negatives and highly imbalanced datasets in PubChem, also creates major challenges. Several approaches regarding the modeling of PubChem datasets and development of virtual screening models for bioactivity and toxicity predictions are also reviewed. Take home message Novel data-mining cheminformatics tools and virtual screening algorithms are being developed and used to retrieve, annotate and analyze the large-scale and highly complex PubChem biological screening data for drug design. PMID:21691435

Toward antituberculosis drugs: in silico screening of synthetic compounds against Mycobacterium tuberculosisl,d-transpeptidase 2.

PubMed

Billones, Junie B; Carrillo, Maria Constancia O; Organo, Voltaire G; Macalino, Stephani Joy Y; Sy, Jamie Bernadette A; Emnacen, Inno A; Clavio, Nina Abigail B; Concepcion, Gisela P

2016-01-01

Mycobacterium tuberculosis (Mtb) the main causative agent of tuberculosis, is the main reason why this disease continues to be a global public health threat. It is therefore imperative to find a novel antitubercular drug target that is unique to the structural machinery or is essential to the growth and survival of the bacterium. One such target is the enzyme l,d-transpeptidase 2, also known as LdtMt2, a protein primarily responsible for the catalysis of 3→3 cross-linkages that make up the mycolyl-arabinogalactan-peptidoglycan complex of Mtb. In this study, structure-based pharmacophore screening, molecular docking, and in silico toxicity evaluations were employed in screening compounds from a database of synthetic compounds. Out of the 4.5 million database compounds, 18 structures were identified as high-scoring, high-binding hits with very satisfactory absorption, distribution, metabolism, excretion, and toxicity properties. Two out of the 18 compounds were further subjected to in vitro bioactivity assays, with one exhibiting a good inhibitory activity against the Mtb H37Ra strain.

Decision support methods for the detection of adverse events in post-marketing data.

PubMed

Hauben, M; Bate, A

2009-04-01

Spontaneous reporting is a crucial component of post-marketing drug safety surveillance despite its significant limitations. The size and complexity of some spontaneous reporting system databases represent a challenge for drug safety professionals who traditionally have relied heavily on the scientific and clinical acumen of the prepared mind. Computer algorithms that calculate statistical measures of reporting frequency for huge numbers of drug-event combinations are increasingly used to support pharamcovigilance analysts screening large spontaneous reporting system databases. After an overview of pharmacovigilance and spontaneous reporting systems, we discuss the theory and application of contemporary computer algorithms in regular use, those under development, and the practical considerations involved in the implementation of computer algorithms within a comprehensive and holistic drug safety signal detection program.

Screening the receptorome to discover the molecular targets for plant-derived psychoactive compounds: a novel approach for CNS drug discovery.

PubMed

Roth, Bryan L; Lopez, Estela; Beischel, Scott; Westkaemper, Richard B; Evans, Jon M

2004-05-01

Because psychoactive plants exert profound effects on human perception, emotion, and cognition, discovering the molecular mechanisms responsible for psychoactive plant actions will likely yield insights into the molecular underpinnings of human consciousness. Additionally, it is likely that elucidation of the molecular targets responsible for psychoactive drug actions will yield validated targets for CNS drug discovery. This review article focuses on an unbiased, discovery-based approach aimed at uncovering the molecular targets responsible for psychoactive drug actions wherein the main active ingredients of psychoactive plants are screened at the "receptorome" (that portion of the proteome encoding receptors). An overview of the receptorome is given and various in silico, public-domain resources are described. Newly developed tools for the in silico mining of data derived from the National Institute of Mental Health Psychoactive Drug Screening Program's (NIMH-PDSP) K(i) Database (K(i) DB) are described in detail. Additionally, three case studies aimed at discovering the molecular targets responsible for Hypericum perforatum, Salvia divinorum, and Ephedra sinica actions are presented. Finally, recommendations are made for future studies.

Development of a chemotherapy regimen interaction database for the mobile internet: detecting interactions with psychotropics through OncoRx-MI.

PubMed

Yap, Kevin Yi-Lwern; Chui, Wai Keung; Chan, Alexandre

2011-09-01

Cancer patients are at high risks of drug-drug interactions (DDIs). Clinicians need to know the magnitude of DDIs so as to better manage their patients' drug therapies. We have previously created a novel interaction database for oncology prescriptions (OncoRx). In this project, we leverage on 3G networks to further develop this database into an iPhone-specific application for the mobile internet (OncoRx-MI). Data on anticancer drugs (ACDs), chemotherapy regimens (CRegs) and DDIs with psychotropics were compiled from various hardcopy and online resources, and published articles from PubMed, Scopus and Science Direct. The database and iPhone web documents were designed using Adobe Dreamweaver CS4 and associated with a combination of open-source programming scripts. OncoRx-MI currently detects over 5000 DDIs (69.3% pharmacokinetic, 30.7% pharmacodynamic) between 256 single-agent and combination CRegs with 51 psychotropic drugs. OncoRx-MI fits the iPhone screen configuration, and displays information regarding the regimen, pharmacokinetics of the drugs and detected DDIs in tabular format for improved usability. OncoRx-MI is the first mobile DDI application of its kind which detects interactions for combination CRegs. Future versions will include DDIs with other drug categories. Usability studies on its impact in clinical practice will also be carried out.

In silico modeling to predict drug-induced phospholipidosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov

2013-06-01

Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the constructionmore » and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.« less

Facilitating high resolution mass spectrometry data processing for screening of environmental water samples: An evaluation of two deconvolution tools.

PubMed

Bade, Richard; Causanilles, Ana; Emke, Erik; Bijlsma, Lubertus; Sancho, Juan V; Hernandez, Felix; de Voogt, Pim

2016-11-01

A screening approach was applied to influent and effluent wastewater samples. After injection in a LC-LTQ-Orbitrap, data analysis was performed using two deconvolution tools, MsXelerator (modules MPeaks and MS Compare) and Sieve 2.1. The outputs were searched incorporating an in-house database of >200 pharmaceuticals and illicit drugs or ChemSpider. This hidden target screening approach led to the detection of numerous compounds including the illicit drug cocaine and its metabolite benzoylecgonine and the pharmaceuticals carbamazepine, gemfibrozil and losartan. The compounds found using both approaches were combined, and isotopic pattern and retention time prediction were used to filter out false positives. The remaining potential positives were reanalysed in MS/MS mode and their product ions were compared with literature and/or mass spectral libraries. The inclusion of the chemical database ChemSpider led to the tentative identification of several metabolites, including paraxanthine, theobromine, theophylline and carboxylosartan, as well as the pharmaceutical phenazone. The first three of these compounds are isomers and they were subsequently distinguished based on their product ions and predicted retention times. This work has shown that the use deconvolution tools facilitates non-target screening and enables the identification of a higher number of compounds. Copyright © 2016 Elsevier B.V. All rights reserved.

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents.

PubMed

Balakumar, Chandrasekaran; Ramesh, Muthusamy; Tham, Chuin Lean; Khathi, Samukelisiwe Pretty; Kozielski, Frank; Srinivasulu, Cherukupalli; Hampannavar, Girish A; Sayyad, Nisar; Soliman, Mahmoud E; Karpoormath, Rajshekhar

2017-11-29

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.

TIPdb: a database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan.

PubMed

Lin, Ying-Chi; Wang, Chia-Chi; Chen, Ih-Sheng; Jheng, Jhao-Liang; Li, Jih-Heng; Tung, Chun-Wei

2013-01-01

The unique geographic features of Taiwan are attributed to the rich indigenous and endemic plant species in Taiwan. These plants serve as resourceful bank for biologically active phytochemicals. Given that these plant-derived chemicals are prototypes of potential drugs for diseases, databases connecting the chemical structures and pharmacological activities may facilitate drug development. To enhance the utility of the data, it is desirable to develop a database of chemical compounds and corresponding activities from indigenous plants in Taiwan. A database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan was constructed. The database, TIPdb, is composed of a standardized format of published anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan. A browse function was implemented for users to browse the database in a taxonomy-based manner. Search functions can be utilized to filter records of interest by botanical name, part, chemical class, or compound name. The structured and searchable database TIPdb was constructed to serve as a comprehensive and standardized resource for anticancer, antiplatelet, and antituberculosis compounds search. The manually curated chemical structures and activities provide a great opportunity to develop quantitative structure-activity relationship models for the high-throughput screening of potential anticancer, antiplatelet, and antituberculosis drugs.

TIPdb: A Database of Anticancer, Antiplatelet, and Antituberculosis Phytochemicals from Indigenous Plants in Taiwan

PubMed Central

Lin, Ying-Chi; Wang, Chia-Chi; Chen, Ih-Sheng; Jheng, Jhao-Liang; Li, Jih-Heng; Tung, Chun-Wei

2013-01-01

The unique geographic features of Taiwan are attributed to the rich indigenous and endemic plant species in Taiwan. These plants serve as resourceful bank for biologically active phytochemicals. Given that these plant-derived chemicals are prototypes of potential drugs for diseases, databases connecting the chemical structures and pharmacological activities may facilitate drug development. To enhance the utility of the data, it is desirable to develop a database of chemical compounds and corresponding activities from indigenous plants in Taiwan. A database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan was constructed. The database, TIPdb, is composed of a standardized format of published anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan. A browse function was implemented for users to browse the database in a taxonomy-based manner. Search functions can be utilized to filter records of interest by botanical name, part, chemical class, or compound name. The structured and searchable database TIPdb was constructed to serve as a comprehensive and standardized resource for anticancer, antiplatelet, and antituberculosis compounds search. The manually curated chemical structures and activities provide a great opportunity to develop quantitative structure-activity relationship models for the high-throughput screening of potential anticancer, antiplatelet, and antituberculosis drugs. PMID:23766708

In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database

NASA Astrophysics Data System (ADS)

Dai, Shao-Xing; Li, Wen-Xing; Han, Fei-Fei; Guo, Yi-Cheng; Zheng, Jun-Juan; Liu, Jia-Qian; Wang, Qian; Gao, Yue-Dong; Li, Gong-Hua; Huang, Jing-Fei

2016-05-01

There is a constant demand to develop new, effective, and affordable anti-cancer drugs. The traditional Chinese medicine (TCM) is a valuable and alternative resource for identifying novel anti-cancer agents. In this study, we aim to identify the anti-cancer compounds and plants from the TCM database by using cheminformatics. We first predicted 5278 anti-cancer compounds from TCM database. The top 346 compounds were highly potent active in the 60 cell lines test. Similarity analysis revealed that 75% of the 5278 compounds are highly similar to the approved anti-cancer drugs. Based on the predicted anti-cancer compounds, we identified 57 anti-cancer plants by activity enrichment. The identified plants are widely distributed in 46 genera and 28 families, which broadens the scope of the anti-cancer drug screening. Finally, we constructed a network of predicted anti-cancer plants and approved drugs based on the above results. The network highlighted the supportive role of the predicted plant in the development of anti-cancer drug and suggested different molecular anti-cancer mechanisms of the plants. Our study suggests that the predicted compounds and plants from TCM database offer an attractive starting point and a broader scope to mine for potential anti-cancer agents.

In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database.

PubMed

Dai, Shao-Xing; Li, Wen-Xing; Han, Fei-Fei; Guo, Yi-Cheng; Zheng, Jun-Juan; Liu, Jia-Qian; Wang, Qian; Gao, Yue-Dong; Li, Gong-Hua; Huang, Jing-Fei

2016-05-05

There is a constant demand to develop new, effective, and affordable anti-cancer drugs. The traditional Chinese medicine (TCM) is a valuable and alternative resource for identifying novel anti-cancer agents. In this study, we aim to identify the anti-cancer compounds and plants from the TCM database by using cheminformatics. We first predicted 5278 anti-cancer compounds from TCM database. The top 346 compounds were highly potent active in the 60 cell lines test. Similarity analysis revealed that 75% of the 5278 compounds are highly similar to the approved anti-cancer drugs. Based on the predicted anti-cancer compounds, we identified 57 anti-cancer plants by activity enrichment. The identified plants are widely distributed in 46 genera and 28 families, which broadens the scope of the anti-cancer drug screening. Finally, we constructed a network of predicted anti-cancer plants and approved drugs based on the above results. The network highlighted the supportive role of the predicted plant in the development of anti-cancer drug and suggested different molecular anti-cancer mechanisms of the plants. Our study suggests that the predicted compounds and plants from TCM database offer an attractive starting point and a broader scope to mine for potential anti-cancer agents.

In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database

PubMed Central

Dai, Shao-Xing; Li, Wen-Xing; Han, Fei-Fei; Guo, Yi-Cheng; Zheng, Jun-Juan; Liu, Jia-Qian; Wang, Qian; Gao, Yue-Dong; Li, Gong-Hua; Huang, Jing-Fei

2016-01-01

There is a constant demand to develop new, effective, and affordable anti-cancer drugs. The traditional Chinese medicine (TCM) is a valuable and alternative resource for identifying novel anti-cancer agents. In this study, we aim to identify the anti-cancer compounds and plants from the TCM database by using cheminformatics. We first predicted 5278 anti-cancer compounds from TCM database. The top 346 compounds were highly potent active in the 60 cell lines test. Similarity analysis revealed that 75% of the 5278 compounds are highly similar to the approved anti-cancer drugs. Based on the predicted anti-cancer compounds, we identified 57 anti-cancer plants by activity enrichment. The identified plants are widely distributed in 46 genera and 28 families, which broadens the scope of the anti-cancer drug screening. Finally, we constructed a network of predicted anti-cancer plants and approved drugs based on the above results. The network highlighted the supportive role of the predicted plant in the development of anti-cancer drug and suggested different molecular anti-cancer mechanisms of the plants. Our study suggests that the predicted compounds and plants from TCM database offer an attractive starting point and a broader scope to mine for potential anti-cancer agents. PMID:27145869

Similarity-based modeling in large-scale prediction of drug-drug interactions.

PubMed

Vilar, Santiago; Uriarte, Eugenio; Santana, Lourdes; Lorberbaum, Tal; Hripcsak, George; Friedman, Carol; Tatonetti, Nicholas P

2014-09-01

Drug-drug interactions (DDIs) are a major cause of adverse drug effects and a public health concern, as they increase hospital care expenses and reduce patients' quality of life. DDI detection is, therefore, an important objective in patient safety, one whose pursuit affects drug development and pharmacovigilance. In this article, we describe a protocol applicable on a large scale to predict novel DDIs based on similarity of drug interaction candidates to drugs involved in established DDIs. The method integrates a reference standard database of known DDIs with drug similarity information extracted from different sources, such as 2D and 3D molecular structure, interaction profile, target and side-effect similarities. The method is interpretable in that it generates drug interaction candidates that are traceable to pharmacological or clinical effects. We describe a protocol with applications in patient safety and preclinical toxicity screening. The time frame to implement this protocol is 5-7 h, with additional time potentially necessary, depending on the complexity of the reference standard DDI database and the similarity measures implemented.

Modeling Liver-Related Adverse Effects of Drugs Using kNN QSAR Method

PubMed Central

Rodgers, Amie D.; Zhu, Hao; Fourches, Dennis; Rusyn, Ivan; Tropsha, Alexander

2010-01-01

Adverse effects of drugs (AEDs) continue to be a major cause of drug withdrawals both in development and post-marketing. While liver-related AEDs are a major concern for drug safety, there are few in silico models for predicting human liver toxicity for drug candidates. We have applied the Quantitative Structure Activity Relationship (QSAR) approach to model liver AEDs. In this study, we aimed to construct a QSAR model capable of binary classification (active vs. inactive) of drugs for liver AEDs based on chemical structure. To build QSAR models, we have employed an FDA spontaneous reporting database of human liver AEDs (elevations in activity of serum liver enzymes), which contains data on approximately 500 approved drugs. Approximately 200 compounds with wide clinical data coverage, structural similarity and balanced (40/60) active/inactive ratio were selected for modeling and divided into multiple training/test and external validation sets. QSAR models were developed using the k nearest neighbor method and validated using external datasets. Models with high sensitivity (>73%) and specificity (>94%) for prediction of liver AEDs in external validation sets were developed. To test applicability of the models, three chemical databases (World Drug Index, Prestwick Chemical Library, and Biowisdom Liver Intelligence Module) were screened in silico and the validity of predictions was determined, where possible, by comparing model-based classification with assertions in publicly available literature. Validated QSAR models of liver AEDs based on the data from the FDA spontaneous reporting system can be employed as sensitive and specific predictors of AEDs in pre-clinical screening of drug candidates for potential hepatotoxicity in humans. PMID:20192250

Identification of novel tyrosine kinase inhibitors for drug resistant T315I mutant BCR-ABL: a virtual screening and molecular dynamics simulations study

NASA Astrophysics Data System (ADS)

Banavath, Hemanth Naick; Sharma, Om Prakash; Kumar, Muthuvel Suresh; Baskaran, R.

2014-11-01

BCR-ABL tyrosine kinase plays a major role in the pathogenesis of chronic myeloid leukemia (CML) and is a proven target for drug development. Currently available drugs in the market are effective against CML; however, side-effects and drug-resistant mutations in BCR-ABL limit their full potential. Using high throughput virtual screening approach, we have screened several small molecule databases and docked against wild-type and drug resistant T315I mutant BCR-ABL. Drugs that are currently available, such as imatinib and ponatinib, were also docked against BCR-ABL protein to set a cutoff value for our screening. Selected lead compounds were further evaluated for chemical reactivity employing density functional theory approach, all selected ligands shows HLG value > 0.09900 and the binding free energy between protein-ligand complex interactions obtained was rescored using MM-GBSA. The selected compounds showed least ΔG score -71.53 KJ/mol to maximum -126.71 KJ/mol in both wild type and drug resistant T315I mutant BCR-ABL. Following which, the stability of the docking complexes were evaluated by molecular dynamics simulation (MD) using GROMACS4.5.5. Results uncovered seven lead molecules, designated with Drug-Bank and PubChem ids as DB07107, DB06977, ST013616, DB04200, ST007180 ST019342, and DB01172, which shows docking scores higher than imatinib and ponatinib.

SuperNatural: a searchable database of available natural compounds

PubMed Central

Dunkel, Mathias; Fullbeck, Melanie; Neumann, Stefanie; Preissner, Robert

2006-01-01

Although tremendous effort has been put into synthetic libraries, most drugs on the market are still natural compounds or derivatives thereof. There are encyclopaedias of natural compounds, but the availability of these compounds is often unclear and catalogues from numerous suppliers have to be checked. To overcome these problems we have compiled a database of ∼50 000 natural compounds from different suppliers. To enable efficient identification of the desired compounds, we have implemented substructure searches with typical templates. Starting points for in silico screenings are about 2500 well-known and classified natural compounds from a compendium that we have added. Possible medical applications can be ascertained via automatic searches for similar drugs in a free conformational drug database containing WHO indications. Furthermore, we have computed about three million conformers, which are deployed to account for the flexibilities of the compounds when the 3D superposition algorithm that we have developed is used. The SuperNatural Database is publicly available at . Viewing requires the free Chime-plugin from MDL (Chime) or Java2 Runtime Environment (MView), which is also necessary for using Marvin application for chemical drawing. PMID:16381957

Wide-range screening of psychoactive substances by FIA-HRMS: identification strategies.

PubMed

Alechaga, Élida; Moyano, Encarnación; Galceran, Maria Teresa

2015-06-01

Recreational drugs (illicit drugs, human and veterinary medicines, legal highs, etc.) often contain lacing agents and adulterants which are not related to the main active ingredient. Serious side effects and even the death of the consumer have been related to the consumption of mixtures of psychoactive substances and/or adulterants, so it is important to know the actual composition of recreational drugs. In this work, a method based on flow injection analysis (FIA) coupled with high-resolution mass spectrometry (HRMS) is proposed for the fast identification of psychoactive substances in recreational drugs and legal highs. The FIA and HRMS working conditions were optimized in order to detect a wide range of psychoactive compounds. As most of the psychoactive substances are acid-base compounds, methanol-0.1 % aqueous formic acid (1:1 v/v) as a carrier solvent and electrospray in both positive ion mode and negative ion mode were used. Two data acquisition modes, full scan at high mass resolution (HRMS) and data-dependent tandem mass spectrometry (ddMS/HRMS) with a quadrupole-Orbitrap mass analyzer were used, resulting in sufficient selectivity for identification of the components of the samples. A custom-made database containing over 450 substances, including psychoactive compounds and common adulterants, was built to perform a high-throughput target and suspect screening. Moreover, online accurate mass databases and mass fragmenter software were used to identify unknowns. Some examples, selected among the analyzed samples of recreational drugs and legal highs using the FIA-HRMS(ddMS/HRMS) method developed, are discussed to illustrate the screening strategy used in this study. The results showed that many of the analyzed samples were adulterated, and in some cases the sample composition did not match that of the supposed marketed substance.

Scrubchem: Building Bioactivity Datasets from Pubchem Bioassay Data (SOT)

EPA Science Inventory

The PubChem Bioassay database is a non-curated public repository with data from 64 sources, including: ChEMBL, BindingDb, DrugBank, EPA Tox21, NIH Molecular Libraries Screening Program, and various other academic, government, and industrial contributors. Methods for extracting th...

Solubility prediction, solvate and cocrystal screening as tools for rational crystal engineering.

PubMed

Loschen, Christoph; Klamt, Andreas

2015-06-01

The fact that novel drug candidates are becoming increasingly insoluble is a major problem of current drug development. Computational tools may address this issue by screening for suitable solvents or by identifying potential novel cocrystal formers that increase bioavailability. In contrast to other more specialized methods, the fluid phase thermodynamics approach COSMO-RS (conductor-like screening model for real solvents) allows for a comprehensive treatment of drug solubility, solvate and cocrystal formation and many other thermodynamics properties in liquids. This article gives an overview of recent COSMO-RS developments that are of interest for drug development and contains several new application examples for solubility prediction and solvate/cocrystal screening. For all property predictions COSMO-RS has been used. The basic concept of COSMO-RS consists of using the screening charge density as computed from first principles calculations in combination with fast statistical thermodynamics to compute the chemical potential of a compound in solution. The fast and accurate assessment of drug solubility and the identification of suitable solvents, solvate or cocrystal formers is nowadays possible and may be used to complement modern drug development. Efficiency is increased by avoiding costly quantum-chemical computations using a database of previously computed molecular fragments. COSMO-RS theory can be applied to a range of physico-chemical properties, which are of interest in rational crystal engineering. Most notably, in combination with experimental reference data, accurate quantitative solubility predictions in any solvent or solvent mixture are possible. Additionally, COSMO-RS can be extended to the prediction of cocrystal formation, which results in considerable predictive accuracy concerning coformer screening. In a recent variant costly quantum chemical calculations are avoided resulting in a significant speed-up and ease-of-use. © 2015 Royal Pharmaceutical Society.

The drug discovery portal: a computational platform for identifying drug leads from academia.

PubMed

Clark, Rachel L; Johnston, Blair F; Mackay, Simon P; Breslin, Catherine J; Robertson, Murray N; Sutcliffe, Oliver B; Dufton, Mark J; Harvey, Alan L

2010-05-01

The Drug Discovery Portal (DDP) is a research initiative based at the University of Strathclyde in Glasgow, Scotland. It was initiated in 2007 by a group of researchers with expertise in virtual screening. Academic research groups in the university working in drug discovery programmes estimated there was a historical collection of physical compounds going back 50 years that had never been adequately catalogued. This invaluable resource has been harnessed to form the basis of the DDP library, and has attracted a high-percentage uptake from the Universities and Research Groups internationally. Its unique attributes include the diversity of the academic database, sourced from synthetic, medicinal and phytochemists working an academic laboratories and the ability to link biologists with appropriate chemical expertise through a target-matching virtual screening approach, and has resulted in seven emerging hit development programmes between international contributors.

DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina.

PubMed

Di Muzio, Elena; Toti, Daniele; Polticelli, Fabio

2017-02-01

Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in.

Getting the Most out of PubChem for Virtual Screening

PubMed Central

Kim, Sunghwan

2016-01-01

Introduction With the emergence of the “big data” era, the biomedical research community has great interest in exploiting publicly available chemical information for drug discovery. PubChem is an example of public databases that provide a large amount of chemical information free of charge. Areas covered This article provides an overview of how PubChem’s data, tools, and services can be used for virtual screening and reviews recent publications that discuss important aspects of exploiting PubChem for drug discovery. Expert opinion PubChem offers comprehensive chemical information useful for drug discovery. It also provides multiple programmatic access routes, which are essential to build automated virtual screening pipelines that exploit PubChem data. In addition, PubChemRDF allows users to download PubChem data and load them into a local computing facility, facilitating data integration between PubChem and other resources. PubChem resources have been used in many studies for developing bioactivity and toxicity prediction models, discovering polypharmacologic (multi-target) ligands, and identifying new macromolecule targets of compounds (for drug-repurposing or off-target side effect prediction). These studies demonstrate the usefulness of PubChem as a key resource for computer-aided drug discovery and related area. PMID:27454129

DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina

NASA Astrophysics Data System (ADS)

Di Muzio, Elena; Toti, Daniele; Polticelli, Fabio

2017-02-01

Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in.

Identification of critical chemical features for Aurora kinase-B inhibitors using Hip-Hop, virtual screening and molecular docking

NASA Astrophysics Data System (ADS)

Sakkiah, Sugunadevi; Thangapandian, Sundarapandian; John, Shalini; Lee, Keun Woo

2011-01-01

This study was performed to find the selective chemical features for Aurora kinase-B inhibitors using the potent methods like Hip-Hop, virtual screening, homology modeling, molecular dynamics and docking. The best hypothesis, Hypo1 was validated toward a wide range of test set containing the selective inhibitors of Aurora kinase-B. Homology modeling and molecular dynamics studies were carried out to perform the molecular docking studies. The best hypothesis Hypo1 was used as a 3D query to screen the chemical databases. The screened molecules from the databases were sorted based on ADME and drug like properties. The selective hit compounds were docked and the hydrogen bond interactions with the critical amino acids present in Aurora kinase-B were compared with the chemical features present in the Hypo1. Finally, we suggest that the chemical features present in the Hypo1 are vital for a molecule to inhibit the Aurora kinase-B activity.

Traditional Medicine Collection Tracking System (TM-CTS): a database for ethnobotanically driven drug-discovery programs.

PubMed

Harris, Eric S J; Erickson, Sean D; Tolopko, Andrew N; Cao, Shugeng; Craycroft, Jane A; Scholten, Robert; Fu, Yanling; Wang, Wenquan; Liu, Yong; Zhao, Zhongzhen; Clardy, Jon; Shamu, Caroline E; Eisenberg, David M

2011-05-17

Ethnobotanically driven drug-discovery programs include data related to many aspects of the preparation of botanical medicines, from initial plant collection to chemical extraction and fractionation. The Traditional Medicine Collection Tracking System (TM-CTS) was created to organize and store data of this type for an international collaborative project involving the systematic evaluation of commonly used Traditional Chinese Medicinal plants. The system was developed using domain-driven design techniques, and is implemented using Java, Hibernate, PostgreSQL, Business Intelligence and Reporting Tools (BIRT), and Apache Tomcat. The TM-CTS relational database schema contains over 70 data types, comprising over 500 data fields. The system incorporates a number of unique features that are useful in the context of ethnobotanical projects such as support for information about botanical collection, method of processing, quality tests for plants with existing pharmacopoeia standards, chemical extraction and fractionation, and historical uses of the plants. The database also accommodates data provided in multiple languages and integration with a database system built to support high throughput screening based drug discovery efforts. It is accessed via a web-based application that provides extensive, multi-format reporting capabilities. This new database system was designed to support a project evaluating the bioactivity of Chinese medicinal plants. The software used to create the database is open source, freely available, and could potentially be applied to other ethnobotanically driven natural product collection and drug-discovery programs. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Traditional Medicine Collection Tracking System (TM-CTS): A Database for Ethnobotanically-Driven Drug-Discovery Programs

PubMed Central

Harris, Eric S. J.; Erickson, Sean D.; Tolopko, Andrew N.; Cao, Shugeng; Craycroft, Jane A.; Scholten, Robert; Fu, Yanling; Wang, Wenquan; Liu, Yong; Zhao, Zhongzhen; Clardy, Jon; Shamu, Caroline E.; Eisenberg, David M.

2011-01-01

Aim of the study. Ethnobotanically-driven drug-discovery programs include data related to many aspects of the preparation of botanical medicines, from initial plant collection to chemical extraction and fractionation. The Traditional Medicine-Collection Tracking System (TM-CTS) was created to organize and store data of this type for an international collaborative project involving the systematic evaluation of commonly used Traditional Chinese Medicinal plants. Materials and Methods. The system was developed using domain-driven design techniques, and is implemented using Java, Hibernate, PostgreSQL, Business Intelligence and Reporting Tools (BIRT), and Apache Tomcat. Results. The TM-CTS relational database schema contains over 70 data types, comprising over 500 data fields. The system incorporates a number of unique features that are useful in the context of ethnobotanical projects such as support for information about botanical collection, method of processing, quality tests for plants with existing pharmacopoeia standards, chemical extraction and fractionation, and historical uses of the plants. The database also accommodates data provided in multiple languages and integration with a database system built to support high throughput screening based drug discovery efforts. It is accessed via a web-based application that provides extensive, multi-format reporting capabilities. Conclusions. This new database system was designed to support a project evaluating the bioactivity of Chinese medicinal plants. The software used to create the database is open source, freely available, and could potentially be applied to other ethnobotanically-driven natural product collection and drug-discovery programs. PMID:21420479

The application of knowledge discovery in databases to post-marketing drug safety: example of the WHO database.

PubMed

Bate, A; Lindquist, M; Edwards, I R

2008-04-01

After market launch, new information on adverse effects of medicinal products is almost exclusively first highlighted by spontaneous reporting. As data sets of spontaneous reports have become larger, and computational capability has increased, quantitative methods have been increasingly applied to such data sets. The screening of such data sets is an application of knowledge discovery in databases (KDD). Effective KDD is an iterative and interactive process made up of the following steps: developing an understanding of an application domain, creating a target data set, data cleaning and pre-processing, data reduction and projection, choosing the data mining task, choosing the data mining algorithm, data mining, interpretation of results and consolidating and using acquired knowledge. The process of KDD as it applies to the analysis of spontaneous reports can be exemplified by its routine use on the 3.5 million suspected adverse drug reaction (ADR) reports in the WHO ADR database. Examples of new adverse effects first highlighted by the KDD process on WHO data include topiramate glaucoma, infliximab vasculitis and the association of selective serotonin reuptake inhibitors (SSRIs) and neonatal convulsions. The KDD process has already improved our ability to highlight previously unsuspected ADRs for clinical review in spontaneous reporting, and we anticipate that such techniques will be increasingly used in the successful screening of other healthcare data sets such as patient records in the future.

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid

PubMed Central

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php PMID:26896846

PhAST: pharmacophore alignment search tool.

PubMed

Hähnke, Volker; Hofmann, Bettina; Grgat, Tomislav; Proschak, Ewgenij; Steinhilber, Dieter; Schneider, Gisbert

2009-04-15

We present a ligand-based virtual screening technique (PhAST) for rapid hit and lead structure searching in large compound databases. Molecules are represented as strings encoding the distribution of pharmacophoric features on the molecular graph. In contrast to other text-based methods using SMILES strings, we introduce a new form of text representation that describes the pharmacophore of molecules. This string representation opens the opportunity for revealing functional similarity between molecules by sequence alignment techniques in analogy to homology searching in protein or nucleic acid sequence databases. We favorably compared PhAST with other current ligand-based virtual screening methods in a retrospective analysis using the BEDROC metric. In a prospective application, PhAST identified two novel inhibitors of 5-lipoxygenase product formation with minimal experimental effort. This outcome demonstrates the applicability of PhAST to drug discovery projects and provides an innovative concept of sequence-based compound screening with substantial scaffold hopping potential. 2008 Wiley Periodicals, Inc.

Large-scale annotation of small-molecule libraries using public databases.

PubMed

Zhou, Yingyao; Zhou, Bin; Chen, Kaisheng; Yan, S Frank; King, Frederick J; Jiang, Shumei; Winzeler, Elizabeth A

2007-01-01

While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.

Modern approaches to accelerate discovery of new antischistosomal drugs.

PubMed

Neves, Bruno Junior; Muratov, Eugene; Machado, Renato Beilner; Andrade, Carolina Horta; Cravo, Pedro Vitor Lemos

2016-06-01

The almost exclusive use of only praziquantel for the treatment of schistosomiasis has raised concerns about the possible emergence of drug-resistant schistosomes. Consequently, there is an urgent need for new antischistosomal drugs. The identification of leads and the generation of high quality data are crucial steps in the early stages of schistosome drug discovery projects. Herein, the authors focus on the current developments in antischistosomal lead discovery, specifically referring to the use of automated in vitro target-based and whole-organism screens and virtual screening of chemical databases. They highlight the strengths and pitfalls of each of the above-mentioned approaches, and suggest possible roadmaps towards the integration of several strategies, which may contribute for optimizing research outputs and led to more successful and cost-effective drug discovery endeavors. Increasing partnerships and access to funding for drug discovery have strengthened the battle against schistosomiasis in recent years. However, the authors believe this battle also includes innovative strategies to overcome scientific challenges. In this context, significant advances of in vitro screening as well as computer-aided drug discovery have contributed to increase the success rate and reduce the costs of drug discovery campaigns. Although some of these approaches were already used in current antischistosomal lead discovery pipelines, the integration of these strategies in a solid workflow should allow the production of new treatments for schistosomiasis in the near future.

Essential proteins and possible therapeutic targets of Wolbachia endosymbiont and development of FiloBase-a comprehensive drug target database for Lymphatic filariasis

NASA Astrophysics Data System (ADS)

Sharma, Om Prakash; Kumar, Muthuvel Suresh

2016-01-01

Lymphatic filariasis (Lf) is one of the oldest and most debilitating tropical diseases. Millions of people are suffering from this prevalent disease. It is estimated to infect over 120 million people in at least 80 nations of the world through the tropical and subtropical regions. More than one billion people are in danger of getting affected with this life-threatening disease. Several studies were suggested its emerging limitations and resistance towards the available drugs and therapeutic targets for Lf. Therefore, better medicine and drug targets are in demand. We took an initiative to identify the essential proteins of Wolbachia endosymbiont of Brugia malayi, which are indispensable for their survival and non-homologous to human host proteins. In this current study, we have used proteome subtractive approach to screen the possible therapeutic targets for wBm. In addition, numerous literatures were mined in the hunt for potential drug targets, drugs, epitopes, crystal structures, and expressed sequence tag (EST) sequences for filarial causing nematodes. Data obtained from our study were presented in a user friendly database named FiloBase. We hope that information stored in this database may be used for further research and drug development process against filariasis. URL: http://filobase.bicpu.edu.in.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics.

PubMed

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics

PubMed Central

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Abstract: Background Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design. PMID:27075578

Virtual Screening Approaches towards the Discovery of Toll-Like Receptor Modulators

PubMed Central

Pérez-Regidor, Lucía; Zarioh, Malik; Ortega, Laura; Martín-Santamaría, Sonsoles

2016-01-01

This review aims to summarize the latest efforts performed in the search for novel chemical entities such as Toll-like receptor (TLR) modulators by means of virtual screening techniques. This is an emergent research field with only very recent (and successful) contributions. Identification of drug-like molecules with potential therapeutic applications for the treatment of a variety of TLR-regulated diseases has attracted considerable interest due to the clinical potential. Additionally, the virtual screening databases and computational tools employed have been overviewed in a descriptive way, widening the scope for researchers interested in the field. PMID:27618029

Internet Database Review: The FDA BBS.

ERIC Educational Resources Information Center

Tomaiuolo, Nicholas G.

1993-01-01

Describes the electronic bulletin board system (BBS) of the Food and Drug Administration (FDA) that is accessible through the Internet. Highlights include how to gain access; the menu-driven software; other electronic sources of FDA information; and adding value. Examples of the FDA BBS menu and the help screen are included. (LRW)

Discovery of Novel Human Epidermal Growth Factor Receptor-2 Inhibitors by Structure-based Virtual Screening.

PubMed

Shi, Zheng; Yu, Tian; Sun, Rong; Wang, Shan; Chen, Xiao-Qian; Cheng, Li-Jia; Liu, Rong

2016-01-01

Human epidermal growth factor receptor-2 (HER2) is a trans-membrane receptor like protein, and aberrant signaling of HER2 is implicated in many human cancers, such as ovarian cancer, gastric cancer, and prostate cancer, most notably breast cancer. Moreover, it has been in the spotlight in the recent years as a promising new target for therapy of breast cancer. Since virtual screening has become an integral part of the drug discovery process, it is of great significant to identify novel HER2 inhibitors by structure-based virtual screening. In this study, we carried out a series of elegant bioinformatics approaches, such as virtual screening and molecular dynamics (MD) simulations to identify HER2 inhibitors from Food and Drug Administration-approved small molecule drug as potential "new use" drugs. Molecular docking identified top 10 potential drugs which showed spectrum affinity to HER2. Moreover, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) might exert potential inhibitory effects against HER2-targeted anti-breast cancer therapeutics. Together, our findings may provide successful application of virtual screening studies in the lead discovery process, and suggest that our discovered small molecules could be effective HER2 inhibitor candidates for further study. A series of elegant bioinformatics approaches, including virtual screening and molecular dynamics (MD) simulations were took advantage to identify human epidermal growth factor receptor-2 (HER2) inhibitors. Molecular docking recognized top 10 candidate compounds, which showed spectrum affinity to HER2. Further, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) in candidate compounds were identified as potential "new use" drugs against HER2-targeted anti-breast cancer therapeutics. Abbreviations used: HER2: Human epidermal growth factor receptor-2, FDA: Food and Drug Administration, PDB: Protein Database Bank, RMSDs: Root mean square deviations, SPC: Single point charge, PME: Particle mesh Ewald, NVT: Constant volume, NPT: Constant pressure, RMSF: Root-mean-square fluctuation.

Performance Studies on Distributed Virtual Screening

PubMed Central

Krüger, Jens; de la Garza, Luis; Kohlbacher, Oliver; Nagel, Wolfgang E.

2014-01-01

Virtual high-throughput screening (vHTS) is an invaluable method in modern drug discovery. It permits screening large datasets or databases of chemical structures for those structures binding possibly to a drug target. Virtual screening is typically performed by docking code, which often runs sequentially. Processing of huge vHTS datasets can be parallelized by chunking the data because individual docking runs are independent of each other. The goal of this work is to find an optimal splitting maximizing the speedup while considering overhead and available cores on Distributed Computing Infrastructures (DCIs). We have conducted thorough performance studies accounting not only for the runtime of the docking itself, but also for structure preparation. Performance studies were conducted via the workflow-enabled science gateway MoSGrid (Molecular Simulation Grid). As input we used benchmark datasets for protein kinases. Our performance studies show that docking workflows can be made to scale almost linearly up to 500 concurrent processes distributed even over large DCIs, thus accelerating vHTS campaigns significantly. PMID:25032219

Stereoselective virtual screening of the ZINC database using atom pair 3D-fingerprints.

PubMed

Awale, Mahendra; Jin, Xian; Reymond, Jean-Louis

2015-01-01

Tools to explore large compound databases in search for analogs of query molecules provide a strategically important support in drug discovery to help identify available analogs of any given reference or hit compound by ligand based virtual screening (LBVS). We recently showed that large databases can be formatted for very fast searching with various 2D-fingerprints using the city-block distance as similarity measure, in particular a 2D-atom pair fingerprint (APfp) and the related category extended atom pair fingerprint (Xfp) which efficiently encode molecular shape and pharmacophores, but do not perceive stereochemistry. Here we investigated related 3D-atom pair fingerprints to enable rapid stereoselective searches in the ZINC database (23.2 million 3D structures). Molecular fingerprints counting atom pairs at increasing through-space distance intervals were designed using either all atoms (16-bit 3DAPfp) or different atom categories (80-bit 3DXfp). These 3D-fingerprints retrieved molecular shape and pharmacophore analogs (defined by OpenEye ROCS scoring functions) of 110,000 compounds from the Cambridge Structural Database with equal or better accuracy than the 2D-fingerprints APfp and Xfp, and showed comparable performance in recovering actives from decoys in the DUD database. LBVS by 3DXfp or 3DAPfp similarity was stereoselective and gave very different analogs when starting from different diastereomers of the same chiral drug. Results were also different from LBVS with the parent 2D-fingerprints Xfp or APfp. 3D- and 2D-fingerprints also gave very different results in LBVS of folded molecules where through-space distances between atom pairs are much shorter than topological distances. 3DAPfp and 3DXfp are suitable for stereoselective searches for shape and pharmacophore analogs of query molecules in large databases. Web-browsers for searching ZINC by 3DAPfp and 3DXfp similarity are accessible at www.gdb.unibe.ch and should provide useful assistance to drug discovery projects. Graphical abstractAtom pair fingerprints based on through-space distances (3DAPfp) provide better shape encoding than atom pair fingerprints based on topological distances (APfp) as measured by the recovery of ROCS shape analogs by fp similarity.

SuperNatural: a searchable database of available natural compounds.

PubMed

Dunkel, Mathias; Fullbeck, Melanie; Neumann, Stefanie; Preissner, Robert

2006-01-01

Although tremendous effort has been put into synthetic libraries, most drugs on the market are still natural compounds or derivatives thereof. There are encyclopaedias of natural compounds, but the availability of these compounds is often unclear and catalogues from numerous suppliers have to be checked. To overcome these problems we have compiled a database of approximately 50,000 natural compounds from different suppliers. To enable efficient identification of the desired compounds, we have implemented substructure searches with typical templates. Starting points for in silico screenings are about 2500 well-known and classified natural compounds from a compendium that we have added. Possible medical applications can be ascertained via automatic searches for similar drugs in a free conformational drug database containing WHO indications. Furthermore, we have computed about three million conformers, which are deployed to account for the flexibilities of the compounds when the 3D superposition algorithm that we have developed is used. The SuperNatural Database is publicly available at http://bioinformatics.charite.de/supernatural. Viewing requires the free Chime-plugin from MDL (Chime) or Java2 Runtime Environment (MView), which is also necessary for using Marvin application for chemical drawing.

Privacy-preserving search for chemical compound databases.

PubMed

Shimizu, Kana; Nuida, Koji; Arai, Hiromi; Mitsunari, Shigeo; Attrapadung, Nuttapong; Hamada, Michiaki; Tsuda, Koji; Hirokawa, Takatsugu; Sakuma, Jun; Hanaoka, Goichiro; Asai, Kiyoshi

2015-01-01

Searching for similar compounds in a database is the most important process for in-silico drug screening. Since a query compound is an important starting point for the new drug, a query holder, who is afraid of the query being monitored by the database server, usually downloads all the records in the database and uses them in a closed network. However, a serious dilemma arises when the database holder also wants to output no information except for the search results, and such a dilemma prevents the use of many important data resources. In order to overcome this dilemma, we developed a novel cryptographic protocol that enables database searching while keeping both the query holder's privacy and database holder's privacy. Generally, the application of cryptographic techniques to practical problems is difficult because versatile techniques are computationally expensive while computationally inexpensive techniques can perform only trivial computation tasks. In this study, our protocol is successfully built only from an additive-homomorphic cryptosystem, which allows only addition performed on encrypted values but is computationally efficient compared with versatile techniques such as general purpose multi-party computation. In an experiment searching ChEMBL, which consists of more than 1,200,000 compounds, the proposed method was 36,900 times faster in CPU time and 12,000 times as efficient in communication size compared with general purpose multi-party computation. We proposed a novel privacy-preserving protocol for searching chemical compound databases. The proposed method, easily scaling for large-scale databases, may help to accelerate drug discovery research by making full use of unused but valuable data that includes sensitive information.

Privacy-preserving search for chemical compound databases

PubMed Central

2015-01-01

Background Searching for similar compounds in a database is the most important process for in-silico drug screening. Since a query compound is an important starting point for the new drug, a query holder, who is afraid of the query being monitored by the database server, usually downloads all the records in the database and uses them in a closed network. However, a serious dilemma arises when the database holder also wants to output no information except for the search results, and such a dilemma prevents the use of many important data resources. Results In order to overcome this dilemma, we developed a novel cryptographic protocol that enables database searching while keeping both the query holder's privacy and database holder's privacy. Generally, the application of cryptographic techniques to practical problems is difficult because versatile techniques are computationally expensive while computationally inexpensive techniques can perform only trivial computation tasks. In this study, our protocol is successfully built only from an additive-homomorphic cryptosystem, which allows only addition performed on encrypted values but is computationally efficient compared with versatile techniques such as general purpose multi-party computation. In an experiment searching ChEMBL, which consists of more than 1,200,000 compounds, the proposed method was 36,900 times faster in CPU time and 12,000 times as efficient in communication size compared with general purpose multi-party computation. Conclusion We proposed a novel privacy-preserving protocol for searching chemical compound databases. The proposed method, easily scaling for large-scale databases, may help to accelerate drug discovery research by making full use of unused but valuable data that includes sensitive information. PMID:26678650

A strategy to find novel candidate anti-Alzheimer's disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants.

PubMed

Chen, Bi-Wen; Li, Wen-Xing; Wang, Guang-Hui; Li, Gong-Hua; Liu, Jia-Qian; Zheng, Jun-Juan; Wang, Qian; Li, Hui-Juan; Dai, Shao-Xing; Huang, Jing-Fei

2018-01-01

Alzheimer' disease (AD) is an ultimately fatal degenerative brain disorder that has an increasingly large burden on health and social care systems. There are only five drugs for AD on the market, and no new effective medicines have been discovered for many years. Chinese medicinal plants have been used to treat diseases for thousands of years, and screening herbal remedies is a way to develop new drugs. We used molecular docking to screen 30,438 compounds from Traditional Chinese Medicine (TCM) against a comprehensive list of AD target proteins. TCM compounds in the top 0.5% of binding affinity scores for each target protein were selected as our research objects. Structural similarities between existing drugs from DrugBank database and selected TCM compounds as well as the druggability of our candidate compounds were studied. Finally, we searched the CNKI database to obtain studies on anti-AD Chinese plants from 2007 to 2017, and only clinical studies were included. A total of 1,476 compounds (top 0.5%) were selected as drug candidates. Most of these compounds are abundantly found in plants used for treating AD in China, especially the plants from two genera Panax and Morus. We classified the compounds by single target and multiple targets and analyzed the interactions between target proteins and compounds. Analysis of structural similarity revealed that 17 candidate anti-AD compounds were structurally identical to 14 existing approved drugs. Most of them have been reported to have a positive effect in AD. After filtering for compound druggability, we identified 11 anti-AD compounds with favorable properties, seven of which are found in anti-AD Chinese plants. Of 11 anti-AD compounds, four compounds 5,862, 5,863, 5,868, 5,869 have anti-inflammatory activity. The compound 28,814 mainly has immunoregulatory activity. The other six compounds have not yet been reported for any biology activity at present. Natural compounds from TCM provide a broad prospect for the screening of anti-AD drugs. In this work, we established networks to systematically study the connections among natural compounds, approved drugs, TCM plants and AD target proteins with the goal of identifying promising drug candidates. We hope that our study will facilitate in-depth research for the treatment of AD in Chinese medicine.

Identification of antipsychotic drug fluspirilene as a potential p53-MDM2 inhibitor: a combined computational and experimental study

NASA Astrophysics Data System (ADS)

Patil, Sachin P.; Pacitti, Michael F.; Gilroy, Kevin S.; Ruggiero, John C.; Griffin, Jonathan D.; Butera, Joseph J.; Notarfrancesco, Joseph M.; Tran, Shawn; Stoddart, John W.

2015-02-01

The inhibition of tumor suppressor p53 protein due to its direct interaction with oncogenic murine double minute 2 (MDM2) protein, plays a central role in almost 50 % of all human tumor cells. Therefore, pharmacological inhibition of the p53-binding pocket on MDM2, leading to p53 activation, presents an important therapeutic target against these cancers expressing wild-type p53. In this context, the present study utilized an integrated virtual and experimental screening approach to screen a database of approved drugs for potential p53-MDM2 interaction inhibitors. Specifically, using an ensemble rigid-receptor docking approach with four MDM2 protein crystal structures, six drug molecules were identified as possible p53-MDM2 inhibitors. These drug molecules were then subjected to further molecular modeling investigation through flexible-receptor docking followed by Prime/MM-GBSA binding energy analysis. These studies identified fluspirilene, an approved antipsychotic drug, as a top hit with MDM2 binding mode and energy similar to that of a native MDM2 crystal ligand. The molecular dynamics simulations suggested stable binding of fluspirilene to the p53-binding pocket on MDM2 protein. The experimental testing of fluspirilene showed significant growth inhibition of human colon tumor cells in a p53-dependent manner. Fluspirilene also inhibited growth of several other human tumor cell lines in the NCI60 cell line panel. Taken together, these computational and experimental data suggest a potentially novel role of fluspirilene in inhibiting the p53-MDM2 interaction. It is noteworthy here that fluspirilene has a long history of safe human use, thus presenting immediate clinical potential as a cancer therapeutic. Furthermore, fluspirilene could also serve as a structurally-novel lead molecule for the development of more potent, small-molecule p53-MDM2 inhibitors against several types of cancer. Importantly, the combined computational and experimental screening protocol presented in this study may also prove useful for screening other commercially-available compound databases for identification of novel, small molecule p53-MDM2 inhibitors.

Contributions of computational chemistry and biophysical techniques to fragment-based drug discovery.

PubMed

Gozalbes, Rafael; Carbajo, Rodrigo J; Pineda-Lucena, Antonio

2010-01-01

In the last decade, fragment-based drug discovery (FBDD) has evolved from a novel approach in the search of new hits to a valuable alternative to the high-throughput screening (HTS) campaigns of many pharmaceutical companies. The increasing relevance of FBDD in the drug discovery universe has been concomitant with an implementation of the biophysical techniques used for the detection of weak inhibitors, e.g. NMR, X-ray crystallography or surface plasmon resonance (SPR). At the same time, computational approaches have also been progressively incorporated into the FBDD process and nowadays several computational tools are available. These stretch from the filtering of huge chemical databases in order to build fragment-focused libraries comprising compounds with adequate physicochemical properties, to more evolved models based on different in silico methods such as docking, pharmacophore modelling, QSAR and virtual screening. In this paper we will review the parallel evolution and complementarities of biophysical techniques and computational methods, providing some representative examples of drug discovery success stories by using FBDD.

Pharmit: interactive exploration of chemical space.

PubMed

Sunseri, Jocelyn; Koes, David Ryan

2016-07-08

Pharmit (http://pharmit.csb.pitt.edu) provides an online, interactive environment for the virtual screening of large compound databases using pharmacophores, molecular shape and energy minimization. Users can import, create and edit virtual screening queries in an interactive browser-based interface. Queries are specified in terms of a pharmacophore, a spatial arrangement of the essential features of an interaction, and molecular shape. Search results can be further ranked and filtered using energy minimization. In addition to a number of pre-built databases of popular compound libraries, users may submit their own compound libraries for screening. Pharmit uses state-of-the-art sub-linear algorithms to provide interactive screening of millions of compounds. Queries typically take a few seconds to a few minutes depending on their complexity. This allows users to iteratively refine their search during a single session. The easy access to large chemical datasets provided by Pharmit simplifies and accelerates structure-based drug design. Pharmit is available under a dual BSD/GPL open-source license. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Role of Open Source Tools and Resources in Virtual Screening for Drug Discovery.

PubMed

Karthikeyan, Muthukumarasamy; Vyas, Renu

2015-01-01

Advancement in chemoinformatics research in parallel with availability of high performance computing platform has made handling of large scale multi-dimensional scientific data for high throughput drug discovery easier. In this study we have explored publicly available molecular databases with the help of open-source based integrated in-house molecular informatics tools for virtual screening. The virtual screening literature for past decade has been extensively investigated and thoroughly analyzed to reveal interesting patterns with respect to the drug, target, scaffold and disease space. The review also focuses on the integrated chemoinformatics tools that are capable of harvesting chemical data from textual literature information and transform them into truly computable chemical structures, identification of unique fragments and scaffolds from a class of compounds, automatic generation of focused virtual libraries, computation of molecular descriptors for structure-activity relationship studies, application of conventional filters used in lead discovery along with in-house developed exhaustive PTC (Pharmacophore, Toxicophores and Chemophores) filters and machine learning tools for the design of potential disease specific inhibitors. A case study on kinase inhibitors is provided as an example.

Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Choi, Inhee; Sarker, Malabika; Talcott, Carolyn

2010-01-01

We are witnessing the growing menace of both increasing cases of drug-sensitive and drug-resistant Mycobacterium tuberculosis strains and the challenge to produce the first new tuberculosis (TB) drug in well over 40 years. The TB community, having invested in extensive high-throughput screening efforts, is faced with the question of how to optimally leverage this data in order to move from a hit to a lead to a clinical candidate and potentially a new drug. Complementing this approach, yet conducted on a much smaller scale, cheminformatic techniques have been leveraged and are herein reviewed. We suggest these computational approaches should be more optimally integrated in a workflow with experimental approaches to accelerate TB drug discovery. PMID:21129975

Screening of cardiovascular risk factors in patients with schizophrenia and patients treated with antipsychotic drugs: are we equally exhaustive as with the general population?

PubMed

Castillo-Sánchez, Miguel; Fàbregas-Escurriola, Mireia; Bergè-Baquero, Daniel; Fernández-SanMartín, MªIsabel; Goday-Arno, Albert

2017-01-01

Many studies have previously shown increased cardiovascular risk factors related to schizophrenia independently from the use of antipsychotic drugs. However, a poorer effort in clinical detection and management of cardiovascular risk in patients with severe mental illness could also explain these results. To test this hypothesis, we analyzed the differences in screening and incidence of cardiovascular risk factors between schizophrenia, non-schizophrenic patients on treatment with antipsychotic drugs (NS-TAD) and the general population. Data from adult subjects assessed by high-quality register general practitioners from 2006 to 2011 were extracted from the Catalonian SIDIAP database. The schizophrenia, NS-TAD, and control groups were compared in terms of measurements and incidence of diabetes, dyslipidemia, obesity, hypertension, and smoking. A total of 4911 patients in the schizophrenia group, 4157 in NS-TAD group, and 98644 in the control group were included. Schizophrenia patients were screened for dyslipidemia and diabetes more frequently than the control group, while for obesity or hypertension, they were screened equal to controls. Also, as compared to the control group, the NS-TAD group was more frequently screened for obesity with no differences in dyslipidemia and diabetes and less frequently for hypertension. Smoking was less frequently screened in both study groups. The incidence of all risk factors studied in both study groups was higher than or equal to the control group, except for hypertension, which had lower incidence. The lack of screening of risk factors does not appear decisive in the increased cardiovascular risk of patients diagnosed with schizophrenia seen in primary care. Studies evaluating the possible under diagnosis of the risk factors are required. Schizophrenia (SZ); Treatment with antipsychotic drugs (TAD); Cardiovascular risk factor/s (CVRF); Without schizophrenia but on therapy with antipsychotic drugs (NS-TAD); Defined Daily Dose (DDD).

MLViS: A Web Tool for Machine Learning-Based Virtual Screening in Early-Phase of Drug Discovery and Development

PubMed Central

Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

2015-01-01

Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/. PMID:25928885

Screening emergency department patients for opioid drug use: A qualitative systematic review.

PubMed

Sahota, Preet Kaur; Shastry, Siri; Mukamel, Dana B; Murphy, Linda; Yang, Narisu; Lotfipour, Shahram; Chakravarthy, Bharath

2018-05-24

The opioid drug epidemic is a major public health concern and an economic burden in the United States. The purpose of this systematic review is to assess the reliability and validity of screening instruments used in emergency medicine settings to detect opioid use in patients and to assess psychometric data for each screening instrument. PubMed/MEDLINE, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Web of Science, Cumulative Index to Nursing and Allied Health Literature and ClinicalTrials.gov were searched for articles published up to May 2018. The extracted articles were independently screened for eligibility by two reviewers. We extracted 1555 articles for initial screening and 95 articles were assessed for full-text eligibility. Six articles were extracted from the full-text assessment. Six instruments were identified from the final article list: Screener and Opioid Assessment for Patients with Pain - Revised; Drug Abuse Screening Test; Opioid Risk Tool; Current Opioid Misuse Measure; an Emergency Medicine Providers Clinician Assessment Questionnaire; and an Emergency Provider Impression Data Collection Form. Screening instrument characteristics, and reliability and validity data were extracted from the six studies. A meta-analysis was not conducted due to heterogeneity between the studies. There is a lack of validity and reliability evidence in all six articles; and sensitivity, specificity and predictive values varied between the different instruments. These instruments cannot be validated for use in emergency medicine settings. There is no clear evidence to state which screening instruments are appropriate for use in detecting opioid use disorders in emergency medicine patients. There is a need for brief, reliable, valid and feasible opioid use screening instruments in the emergency medicine setting. Copyright © 2018 Elsevier Ltd. All rights reserved.

Combinatorial phenotypic screen uncovers unrecognized family of extended thiourea inhibitors with copper-dependent anti-staphylococcal activity.

PubMed

Dalecki, Alex G; Malalasekera, Aruni P; Schaaf, Kaitlyn; Kutsch, Olaf; Bossmann, Stefan H; Wolschendorf, Frank

2016-04-01

The continuous rise of multi-drug resistant pathogenic bacteria has become a significant challenge for the health care system. In particular, novel drugs to treat infections of methicillin-resistant Staphylococcus aureus strains (MRSA) are needed, but traditional drug discovery campaigns have largely failed to deliver clinically suitable antibiotics. More than simply new drugs, new drug discovery approaches are needed to combat bacterial resistance. The recently described phenomenon of copper-dependent inhibitors has galvanized research exploring the use of metal-coordinating molecules to harness copper's natural antibacterial properties for therapeutic purposes. Here, we describe the results of the first concerted screening effort to identify copper-dependent inhibitors of Staphylococcus aureus. A standard library of 10 000 compounds was assayed for anti-staphylococcal activity, with hits defined as those compounds with a strict copper-dependent inhibitory activity. A total of 53 copper-dependent hit molecules were uncovered, similar to the copper independent hit rate of a traditionally executed campaign conducted in parallel on the same library. Most prominent was a hit family with an extended thiourea core structure, termed the NNSN motif. This motif resulted in copper-dependent and copper-specific S. aureus inhibition, while simultaneously being well tolerated by eukaryotic cells. Importantly, we could demonstrate that copper binding by the NNSN motif is highly unusual and likely responsible for the promising biological qualities of these compounds. A subsequent chemoinformatic meta-analysis of the ChEMBL chemical database confirmed the NNSNs as an unrecognized staphylococcal inhibitor, despite the family's presence in many chemical screening libraries. Thus, our copper-biased screen has proven able to discover inhibitors within previously screened libraries, offering a mechanism to reinvigorate exhausted molecular collections.

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid.

PubMed

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php. © The Author(s) 2016. Published by Oxford University Press.

ScrubChem: Cleaning of PubChem Bioassay Data to Create Diverse and Massive Bioactivity Datasets for Use in Modeling Applications (SOT)

EPA Science Inventory

The PubChem Bioassay database is a non-curated public repository with bioactivity data from 64 sources, including: ChEMBL, BindingDb, DrugBank, Tox21, NIH Molecular Libraries Screening Program, and various academic, government, and industrial contributors. However, this data is d...

Novel Mycosin Protease MycP1 Inhibitors Identified by Virtual Screening and 4D Fingerprints

PubMed Central

2015-01-01

The rise of drug-resistant Mycobacterium tuberculosis lends urgency to the need for new drugs for the treatment of tuberculosis (TB). The identification of a serine protease, mycosin protease-1 (MycP1), as the crucial agent in hydrolyzing the virulence factor, ESX-secretion-associated protein B (EspB), potentially opens the door to new tuberculosis treatment options. Using the crystal structure of mycobacterial MycP1 in the apo form, we performed an iterative ligand- and structure-based virtual screening (VS) strategy to identify novel, nonpeptide, small-molecule inhibitors against MycP1 protease. Screening of ∼485 000 ligands from databases at the Genomics Research Institute (GRI) at the University of Cincinnati and the National Cancer Institute (NCI) using our VS approach, which integrated a pharmacophore model and consensus molecular shape patterns of active ligands (4D fingerprints), identified 81 putative inhibitors, and in vitro testing subsequently confirmed two of them as active inhibitors. Thereafter, the lead structures of each VS round were used to generate a new 4D fingerprint that enabled virtual rescreening of the chemical libraries. Finally, the iterative process identified a number of diverse scaffolds as lead compounds that were tested and found to have micromolar IC50 values against the MycP1 target. This study validated the efficiency of the SABRE 4D fingerprints as a means of identifying novel lead compounds in each screening round of the databases. Together, these results underscored the value of using a combination of in silico iterative ligand- and structure-based virtual screening of chemical libraries with experimental validation for the identification of promising structural scaffolds, such as the MycP1 inhibitors. PMID:24628123

Congestion game scheduling for virtual drug screening optimization

NASA Astrophysics Data System (ADS)

Nikitina, Natalia; Ivashko, Evgeny; Tchernykh, Andrei

2018-02-01

In virtual drug screening, the chemical diversity of hits is an important factor, along with their predicted activity. Moreover, interim results are of interest for directing the further research, and their diversity is also desirable. In this paper, we consider a problem of obtaining a diverse set of virtual screening hits in a short time. To this end, we propose a mathematical model of task scheduling for virtual drug screening in high-performance computational systems as a congestion game between computational nodes to find the equilibrium solutions for best balancing the number of interim hits with their chemical diversity. The model considers the heterogeneous environment with workload uncertainty, processing time uncertainty, and limited knowledge about the input dataset structure. We perform computational experiments and evaluate the performance of the developed approach considering organic molecules database GDB-9. The used set of molecules is rich enough to demonstrate the feasibility and practicability of proposed solutions. We compare the algorithm with two known heuristics used in practice and observe that game-based scheduling outperforms them by the hit discovery rate and chemical diversity at earlier steps. Based on these results, we use a social utility metric for assessing the efficiency of our equilibrium solutions and show that they reach greatest values.

Shape based virtual screening and molecular docking towards designing novel pancreatic lipase inhibitors

PubMed Central

Veeramachaneni, Ganesh Kumar; Raj, K Kranthi; Chalasani, Leela Madhuri; Annamraju, Sai Krishna; JS, Bondili; Talluri, Venkateswara Rao

2015-01-01

Increase in obesity rates and obesity associated health issues became one of the greatest health concerns in the present world population. With alarming increase in obese percentage there is a need to design new drugs related to the obesity targets. Among the various targets linked to obesity, pancreatic lipase was one of the promising targets for obesity treatment. Using the in silico methods like structure based virtual screening, QikProp, docking studies and binding energy calculations three molecules namely zinc85531017, zinc95919096 and zinc33963788 from the natural database were reported as the potential inhibitors for the pancreatic lipase. Among them zinc95919096 presented all the interactions matching to both standard and crystal ligand and hence it can be further proceeded to drug discovery process. PMID:26770027

In Silico Repositioning-Chemogenomics Strategy Identifies New Drugs with Potential Activity against Multiple Life Stages of Schistosoma mansoni

PubMed Central

Neves, Bruno J.; Braga, Rodolpho C.; Bezerra, José C. B.; Cravo, Pedro V. L.; Andrade, Carolina H.

2015-01-01

Morbidity and mortality caused by schistosomiasis are serious public health problems in developing countries. Because praziquantel is the only drug in therapeutic use, the risk of drug resistance is a concern. In the search for new schistosomicidal drugs, we performed a target-based chemogenomics screen of a dataset of 2,114 proteins to identify drugs that are approved for clinical use in humans that may be active against multiple life stages of Schistosoma mansoni. Each of these proteins was treated as a potential drug target, and its amino acid sequence was used to interrogate three databases: Therapeutic Target Database (TTD), DrugBank and STITCH. Predicted drug-target interactions were refined using a combination of approaches, including pairwise alignment, conservation state of functional regions and chemical space analysis. To validate our strategy, several drugs previously shown to be active against Schistosoma species were correctly predicted, such as clonazepam, auranofin, nifedipine, and artesunate. We were also able to identify 115 drugs that have not yet been experimentally tested against schistosomes and that require further assessment. Some examples are aprindine, gentamicin, clotrimazole, tetrabenazine, griseofulvin, and cinnarizine. In conclusion, we have developed a systematic and focused computer-aided approach to propose approved drugs that may warrant testing and/or serve as lead compounds for the design of new drugs against schistosomes. PMID:25569258

Successful adaption of a forensic toxicological screening workflow employing nontargeted liquid chromatography-tandem mass spectrometry to water analysis.

PubMed

Steger, Julia; Arnhard, Kathrin; Haslacher, Sandra; Geiger, Klemens; Singer, Klaus; Schlapp, Michael; Pitterl, Florian; Oberacher, Herbert

2016-04-01

Forensic toxicology and environmental water analysis share the common interest and responsibility in ensuring comprehensive and reliable confirmation of drugs and pharmaceutical compounds in samples analyzed. Dealing with similar analytes, detection and identification techniques should be exchangeable between scientific disciplines. Herein, we demonstrate the successful adaption of a forensic toxicological screening workflow employing nontargeted LC/MS/MS under data-dependent acquisition control and subsequent database search to water analysis. The main modification involved processing of an increased sample volume with SPE (500 mL vs. 1-10 mL) to reach LODs in the low ng/L range. Tandem mass spectra acquired with a qTOF instrument were submitted to database search. The targeted data mining strategy was found to be sensitive and specific; automated search produced hardly any false results. To demonstrate the applicability of the adapted workflow to complex samples, 14 wastewater effluent samples collected on seven consecutive days at the local wastewater-treatment plant were analyzed. Of the 88,970 fragment ion mass spectra produced, 8.8% of spectra were successfully assigned to one of the 1040 reference compounds included in the database, and this enabled the identification of 51 compounds representing important illegal drugs, members of various pharmaceutical compound classes, and metabolites thereof. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of Quantitative Structure–Activity Relationship Models of 5-HT1A Receptor Binding to Virtual Screening Identifies Novel and Potent 5-HT1A Ligands

PubMed Central

2015-01-01

The 5-hydroxytryptamine 1A (5-HT1A) serotonin receptor has been an attractive target for treating mood and anxiety disorders such as schizophrenia. We have developed binary classification quantitative structure–activity relationship (QSAR) models of 5-HT1A receptor binding activity using data retrieved from the PDSP Ki database. The prediction accuracy of these models was estimated by external 5-fold cross-validation as well as using an additional validation set comprising 66 structurally distinct compounds from the World of Molecular Bioactivity database. These validated models were then used to mine three major types of chemical screening libraries, i.e., drug-like libraries, GPCR targeted libraries, and diversity libraries, to identify novel computational hits. The five best hits from each class of libraries were chosen for further experimental testing in radioligand binding assays, and nine of the 15 hits were confirmed to be active experimentally with binding affinity better than 10 μM. The most active compound, Lysergol, from the diversity library showed very high binding affinity (Ki) of 2.3 nM against 5-HT1A receptor. The novel 5-HT1A actives identified with the QSAR-based virtual screening approach could be potentially developed as novel anxiolytics or potential antischizophrenic drugs. PMID:24410373

Large-Scale Chemical Similarity Networks for Target Profiling of Compounds Identified in Cell-Based Chemical Screens

PubMed Central

Lo, Yu-Chen; Senese, Silvia; Li, Chien-Ming; Hu, Qiyang; Huang, Yong; Damoiseaux, Robert; Torres, Jorge Z.

2015-01-01

Target identification is one of the most critical steps following cell-based phenotypic chemical screens aimed at identifying compounds with potential uses in cell biology and for developing novel disease therapies. Current in silico target identification methods, including chemical similarity database searches, are limited to single or sequential ligand analysis that have limited capabilities for accurate deconvolution of a large number of compounds with diverse chemical structures. Here, we present CSNAP (Chemical Similarity Network Analysis Pulldown), a new computational target identification method that utilizes chemical similarity networks for large-scale chemotype (consensus chemical pattern) recognition and drug target profiling. Our benchmark study showed that CSNAP can achieve an overall higher accuracy (>80%) of target prediction with respect to representative chemotypes in large (>200) compound sets, in comparison to the SEA approach (60–70%). Additionally, CSNAP is capable of integrating with biological knowledge-based databases (Uniprot, GO) and high-throughput biology platforms (proteomic, genetic, etc) for system-wise drug target validation. To demonstrate the utility of the CSNAP approach, we combined CSNAP's target prediction with experimental ligand evaluation to identify the major mitotic targets of hit compounds from a cell-based chemical screen and we highlight novel compounds targeting microtubules, an important cancer therapeutic target. The CSNAP method is freely available and can be accessed from the CSNAP web server (http://services.mbi.ucla.edu/CSNAP/). PMID:25826798

Quantum probability ranking principle for ligand-based virtual screening.

PubMed

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Quantum probability ranking principle for ligand-based virtual screening

NASA Astrophysics Data System (ADS)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Building a virtual ligand screening pipeline using free software: a survey.

PubMed

Glaab, Enrico

2016-03-01

Virtual screening, the search for bioactive compounds via computational methods, provides a wide range of opportunities to speed up drug development and reduce the associated risks and costs. While virtual screening is already a standard practice in pharmaceutical companies, its applications in preclinical academic research still remain under-exploited, in spite of an increasing availability of dedicated free databases and software tools. In this survey, an overview of recent developments in this field is presented, focusing on free software and data repositories for screening as alternatives to their commercial counterparts, and outlining how available resources can be interlinked into a comprehensive virtual screening pipeline using typical academic computing facilities. Finally, to facilitate the set-up of corresponding pipelines, a downloadable software system is provided, using platform virtualization to integrate pre-installed screening tools and scripts for reproducible application across different operating systems. © The Author 2015. Published by Oxford University Press.

Building a virtual ligand screening pipeline using free software: a survey

PubMed Central

2016-01-01

Virtual screening, the search for bioactive compounds via computational methods, provides a wide range of opportunities to speed up drug development and reduce the associated risks and costs. While virtual screening is already a standard practice in pharmaceutical companies, its applications in preclinical academic research still remain under-exploited, in spite of an increasing availability of dedicated free databases and software tools. In this survey, an overview of recent developments in this field is presented, focusing on free software and data repositories for screening as alternatives to their commercial counterparts, and outlining how available resources can be interlinked into a comprehensive virtual screening pipeline using typical academic computing facilities. Finally, to facilitate the set-up of corresponding pipelines, a downloadable software system is provided, using platform virtualization to integrate pre-installed screening tools and scripts for reproducible application across different operating systems. PMID:26094053

[Screen potential CYP450 2E1 inhibitors from Chinese herbal medicine based on support vector regression and molecular docking method].

PubMed

Chen, Xi; Lu, Fang; Jiang, Lu-di; Cai, Yi-Lian; Li, Gong-Yu; Zhang, Yan-Ling

2016-07-01

Inhibition of cytochrome P450 (CYP450) enzymes is the most common reasons for drug interactions, so the study on early prediction of CYPs inhibitors can help to decrease the incidence of adverse reactions caused by drug interactions.CYP450 2E1(CYP2E1), as a key role in drug metabolism process, has broad spectrum of drug metabolism substrate. In this study, 32 CYP2E1 inhibitors were collected for the construction of support vector regression (SVR) model. The test set data were used to verify CYP2E1 quantitative models and obtain the optimal prediction model of CYP2E1 inhibitor. Meanwhile, one molecular docking program, CDOCKER, was utilized to analyze the interaction pattern between positive compounds and active pocket to establish the optimal screening model of CYP2E1 inhibitors.SVR model and molecular docking prediction model were combined to screen traditional Chinese medicine database (TCMD), which could improve the calculation efficiency and prediction accuracy. 6 376 traditional Chinese medicine (TCM) compounds predicted by SVR model were obtained, and in further verification by using molecular docking model, 247 TCM compounds with potential inhibitory activities against CYP2E1 were finally retained. Some of them have been verified by experiments. The results demonstrated that this study could provide guidance for the virtual screening of CYP450 inhibitors and the prediction of CYPs-mediated DDIs, and also provide references for clinical rational drug use. Copyright© by the Chinese Pharmaceutical Association.

Intrathecal Drug Delivery Systems for Cancer Pain: A Health Technology Assessment

PubMed Central

2016-01-01

Background Intrathecal drug delivery systems can be used to manage refractory or persistent cancer pain. We investigated the benefits, harms, cost-effectiveness, and budget impact of these systems compared with current standards of care for adult patients with chronic pain due owing to cancer. Methods We searched Ovid MEDLINE, Ovid Embase, the Cochrane Library databases, National Health Service's Economic Evaluation Database, and Tufts Cost-Effectiveness Analysis Registry from January 1994 to April 2014 for evidence of effectiveness, harms, and cost-effectiveness. We used existing systematic reviews that had employed reliable search and screen methods and searched for studies published after the search date reported in the latest systematic review to identify studies. Two reviewers screened records and assessed study validity. The cost burden of publicly funding intrathecal drug delivery systems for cancer pain was estimated for a 5-year timeframe using a combination of published literature, information from the device manufacturer, administrative data, and expert opinion for the inputs. Results We included one randomized trial that examined effectiveness and harms, and one case series that reported an eligible economic evaluation. We found very low quality evidence that intrathecal drug delivery systems added to comprehensive pain management reduce overall drug toxicity; no significant reduction in pain scores was observed. Weak conclusions from economic evidence suggested that intrathecal drug delivery systems had the potential to be more cost-effective than high-cost oral therapy if administered for 7 months or longer. The cost burden of publicly funding this therapy is estimated to be $100,000 in the first year, increasing to $500,000 by the fifth year. Conclusions Current evidence could not establish the benefit, harm, or cost-effectiveness of intrathecal drug delivery systems compared with current standards of care for managing refractory cancer pain in adults. Publicly funding intrathecal drug delivery systems for cancer pain would result in a budget impact of several hundred thousand dollars per year. PMID:27026796

Intrathecal Drug Delivery Systems for Cancer Pain: A Health Technology Assessment.

PubMed

2016-01-01

Intrathecal drug delivery systems can be used to manage refractory or persistent cancer pain. We investigated the benefits, harms, cost-effectiveness, and budget impact of these systems compared with current standards of care for adult patients with chronic pain due owing to cancer. We searched Ovid MEDLINE, Ovid Embase, the Cochrane Library databases, National Health Service's Economic Evaluation Database, and Tufts Cost-Effectiveness Analysis Registry from January 1994 to April 2014 for evidence of effectiveness, harms, and cost-effectiveness. We used existing systematic reviews that had employed reliable search and screen methods and searched for studies published after the search date reported in the latest systematic review to identify studies. Two reviewers screened records and assessed study validity. The cost burden of publicly funding intrathecal drug delivery systems for cancer pain was estimated for a 5-year timeframe using a combination of published literature, information from the device manufacturer, administrative data, and expert opinion for the inputs. We included one randomized trial that examined effectiveness and harms, and one case series that reported an eligible economic evaluation. We found very low quality evidence that intrathecal drug delivery systems added to comprehensive pain management reduce overall drug toxicity; no significant reduction in pain scores was observed. Weak conclusions from economic evidence suggested that intrathecal drug delivery systems had the potential to be more cost-effective than high-cost oral therapy if administered for 7 months or longer. The cost burden of publicly funding this therapy is estimated to be $100,000 in the first year, increasing to $500,000 by the fifth year. Current evidence could not establish the benefit, harm, or cost-effectiveness of intrathecal drug delivery systems compared with current standards of care for managing refractory cancer pain in adults. Publicly funding intrathecal drug delivery systems for cancer pain would result in a budget impact of several hundred thousand dollars per year.

Quantitative NTCP Pharmacophore and Lack of Association between DILI and NTCP Inhibition

PubMed Central

Dong, Zhongqi; Ekins, Sean; Polli, James E.

2014-01-01

The human sodium taurocholate cotransporting polypeptide (NTCP) is a hepatic bile acid transporter. Inhibition of NTCP uptake may potentially also prevent hepatitis B virus (HBV) infection. The first objective was to develop a quantitative pharmacophore for NTCP inhibition. Recent studies showed that hepatotoxic drugs could inhibit bile acid uptake into hepatocytes, without inhibiting canalicular efflux, and cause bile acid elevation in plasma. Hence, a second objective was to examine whether NTCP inhibition is associated with drug induced liver injury (DILI). Twenty-seven drugs from our previous study were used as the training set to develop a quantitative pharmacophore. From secondary screening from a drug database, six retrieved drugs and three drugs not retrieved by the model were tested for NTCP inhibition. Tertiary screening involved drugs known to cause DILI and not cause DILI. Overall, ninety-four drugs were assessed for hepatotoxicity and were assessed relative to NTCP inhibition. The quantitative pharmacophore possessed one hydrogen bond acceptor, one hydrogen bond donor, a hydrophobic feature, and excluded volumes. From 94 drugs, NTCP inhibitors and non-inhibitors were approximately equally distributed across the drugs of most DILI concern, less DILI concern, and no DILI concern, indicating no relationship between NTCP inhibition and DILI risk. Hence, an approach to treat HBV via NTCP inhibition is not expected to be associated with DILI. PMID:25220493

Quantitative NTCP pharmacophore and lack of association between DILI and NTCP Inhibition.

PubMed

Dong, Zhongqi; Ekins, Sean; Polli, James E

2015-01-23

The human sodium taurocholate cotransporting polypeptide (NTCP) is a hepatic bile acid transporter. Inhibition of NTCP uptake may potentially also prevent hepatitis B virus (HBV) infection. The first objective was to develop a quantitative pharmacophore for NTCP inhibition. Recent studies showed that hepatotoxic drugs could inhibit bile acid uptake into hepatocytes, without inhibiting canalicular efflux, and cause bile acid elevation in plasma. Hence, a second objective was to examine whether NTCP inhibition is associated with drug induced liver injury (DILI). Twenty-seven drugs from our previous study were used as the training set to develop a quantitative pharmacophore. From secondary screening from a drug database, six retrieved drugs and three drugs not retrieved by the model were tested for NTCP inhibition. Tertiary screening involved drugs known to cause DILI and not cause DILI. Overall, ninety-four drugs were assessed for hepatotoxicity and were assessed relative to NTCP inhibition. The quantitative pharmacophore possessed one hydrogen bond acceptor, one hydrogen bond donor, a hydrophobic feature, and excluded volumes. From 94 drugs, NTCP inhibitors and non-inhibitors were approximately equally distributed across the drugs of most DILI concern, less DILI concern, and no DILI concern, indicating no relationship between NTCP inhibition and DILI risk. Hence, an approach to treat HBV via NTCP inhibition is not expected to be associated with DILI. Copyright © 2014 Elsevier B.V. All rights reserved.

The Tropical Biominer Project: mining old sources for new drugs.

PubMed

Artiguenave, François; Lins, André; Maciel, Wesley Dias; Junior, Antonio Celso Caldeira; Nacif-Coelho, Carla; de Souza Linhares, Maria Margarida Ribeiro; de Oliveira, Guilherme Correa; Barbosa, Luis Humberto Rezende; Lopes, Júlio César Dias; Junior, Claudionor Nunes Coelho

2005-01-01

The Tropical Biominer Project is a recent initiative from the Federal University of Minas Gerais (UFMG) and the Oswaldo Cruz foundation, with the participation of the Biominas Foundation (Belo Horizonte, Minas Gerais, Brazil) and the start-up Homologix. The main objective of the project is to build a new resource for the chemogenomics research, on chemical compounds, with a strong emphasis on natural molecules. Adopted technologies include the search of information from structured, semi-structured, and non-structured documents (the last two from the web) and datamining tools in order to gather information from different sources. The database is the support for developing applications to find new potential treatments for parasitic infections by using virtual screening tools. We present here the midpoint of the project: the conception and implementation of the Tropical Biominer Database. This is a Federated Database designed to store data from different resources. Connected to the database, a web crawler is able to gather information from distinct, patented web sites and store them after automatic classification using datamining tools. Finally, we demonstrate the interest of the approach, by formulating new hypotheses on specific targets of a natural compound, violacein, using inferences from a Virtual Screening procedure.

Comparative analyses of structural features and scaffold diversity for purchasable compound libraries.

PubMed

Shang, Jun; Sun, Huiyong; Liu, Hui; Chen, Fu; Tian, Sheng; Pan, Peichen; Li, Dan; Kong, Dexin; Hou, Tingjun

2017-04-21

Large purchasable screening libraries of small molecules afforded by commercial vendors are indispensable sources for virtual screening (VS). Selecting an optimal screening library for a specific VS campaign is quite important to improve the success rates and avoid wasting resources in later experimental phases. Analysis of the structural features and molecular diversity for different screening libraries can provide valuable information to the decision making process when selecting screening libraries for VS. In this study, the structural features and scaffold diversity of eleven purchasable screening libraries and Traditional Chinese Medicine Compound Database (TCMCD) were analyzed and compared. Their scaffold diversity represented by the Murcko frameworks and Level 1 scaffolds was characterized by the scaffold counts and cumulative scaffold frequency plots, and visualized by Tree Maps and SAR Maps. The analysis demonstrates that, based on the standardized subsets with similar molecular weight distributions, Chembridge, ChemicalBlock, Mucle, TCMCD and VitasM are more structurally diverse than the others. Compared with all purchasable screening libraries, TCMCD has the highest structural complexity indeed but more conservative molecular scaffolds. Moreover, we found that some representative scaffolds were important components of drug candidates against different drug targets, such as kinases and guanosine-binding protein coupled receptors, and therefore the molecules containing pharmacologically important scaffolds found in screening libraries might be potential inhibitors against the relevant targets. This study may provide valuable perspective on which purchasable compound libraries are better for you to screen. Graphical abstract Selecting diverse compound libraries with scaffold analyses.

Mining collections of compounds with Screening Assistant 2

PubMed Central

2012-01-01

Background High-throughput screening assays have become the starting point of many drug discovery programs for large pharmaceutical companies as well as academic organisations. Despite the increasing throughput of screening technologies, the almost infinite chemical space remains out of reach, calling for tools dedicated to the analysis and selection of the compound collections intended to be screened. Results We present Screening Assistant 2 (SA2), an open-source JAVA software dedicated to the storage and analysis of small to very large chemical libraries. SA2 stores unique molecules in a MySQL database, and encapsulates several chemoinformatics methods, among which: providers management, interactive visualisation, scaffold analysis, diverse subset creation, descriptors calculation, sub-structure / SMART search, similarity search and filtering. We illustrate the use of SA2 by analysing the composition of a database of 15 million compounds collected from 73 providers, in terms of scaffolds, frameworks, and undesired properties as defined by recently proposed HTS SMARTS filters. We also show how the software can be used to create diverse libraries based on existing ones. Conclusions Screening Assistant 2 is a user-friendly, open-source software that can be used to manage collections of compounds and perform simple to advanced chemoinformatics analyses. Its modular design and growing documentation facilitate the addition of new functionalities, calling for contributions from the community. The software can be downloaded at http://sa2.sourceforge.net/. PMID:23327565

Mining collections of compounds with Screening Assistant 2.

PubMed

Guilloux, Vincent Le; Arrault, Alban; Colliandre, Lionel; Bourg, Stéphane; Vayer, Philippe; Morin-Allory, Luc

2012-08-31

High-throughput screening assays have become the starting point of many drug discovery programs for large pharmaceutical companies as well as academic organisations. Despite the increasing throughput of screening technologies, the almost infinite chemical space remains out of reach, calling for tools dedicated to the analysis and selection of the compound collections intended to be screened. We present Screening Assistant 2 (SA2), an open-source JAVA software dedicated to the storage and analysis of small to very large chemical libraries. SA2 stores unique molecules in a MySQL database, and encapsulates several chemoinformatics methods, among which: providers management, interactive visualisation, scaffold analysis, diverse subset creation, descriptors calculation, sub-structure / SMART search, similarity search and filtering. We illustrate the use of SA2 by analysing the composition of a database of 15 million compounds collected from 73 providers, in terms of scaffolds, frameworks, and undesired properties as defined by recently proposed HTS SMARTS filters. We also show how the software can be used to create diverse libraries based on existing ones. Screening Assistant 2 is a user-friendly, open-source software that can be used to manage collections of compounds and perform simple to advanced chemoinformatics analyses. Its modular design and growing documentation facilitate the addition of new functionalities, calling for contributions from the community. The software can be downloaded at http://sa2.sourceforge.net/.

In silico discovery and in vitro activity of inhibitors against Mycobacterium tuberculosis 7,8-diaminopelargonic acid synthase (Mtb BioA).

PubMed

Billones, Junie B; Carrillo, Maria Constancia O; Organo, Voltaire G; Sy, Jamie Bernadette A; Clavio, Nina Abigail B; Macalino, Stephani Joy Y; Emnacen, Inno A; Lee, Alexandra P; Ko, Paul Kenny L; Concepcion, Gisela P

2017-01-01

Computer-aided drug discovery and development approaches such as virtual screening, molecular docking, and in silico drug property calculations have been utilized in this effort to discover new lead compounds against tuberculosis. The enzyme 7,8-diaminopelargonic acid aminotransferase (BioA) in Mycobacterium tuberculosis ( Mtb ), primarily involved in the lipid biosynthesis pathway, was chosen as the drug target due to the fact that humans are not capable of synthesizing biotin endogenously. The computational screening of 4.5 million compounds from the Enamine REAL database has ultimately yielded 45 high-scoring, high-affinity compounds with desirable in silico absorption, distribution, metabolism, excretion, and toxicity properties. Seventeen of the 45 compounds were subjected to bioactivity validation using the resazurin microtiter assay. Among the 4 actives, compound 7 (( Z )- N -(2-isopropoxyphenyl)-2-oxo-2-((3-(trifluoromethyl)cyclohexyl)amino)acetimidic acid) displayed inhibitory activity up to 83% at 10 μg/mL concentration against the growth of the Mtb H37Ra strain.

In silico discovery and in vitro activity of inhibitors against Mycobacterium tuberculosis 7,8-diaminopelargonic acid synthase (Mtb BioA)

PubMed Central

Billones, Junie B; Carrillo, Maria Constancia O; Organo, Voltaire G; Sy, Jamie Bernadette A; Clavio, Nina Abigail B; Macalino, Stephani Joy Y; Emnacen, Inno A; Lee, Alexandra P; Ko, Paul Kenny L; Concepcion, Gisela P

2017-01-01

Computer-aided drug discovery and development approaches such as virtual screening, molecular docking, and in silico drug property calculations have been utilized in this effort to discover new lead compounds against tuberculosis. The enzyme 7,8-diaminopelargonic acid aminotransferase (BioA) in Mycobacterium tuberculosis (Mtb), primarily involved in the lipid biosynthesis pathway, was chosen as the drug target due to the fact that humans are not capable of synthesizing biotin endogenously. The computational screening of 4.5 million compounds from the Enamine REAL database has ultimately yielded 45 high-scoring, high-affinity compounds with desirable in silico absorption, distribution, metabolism, excretion, and toxicity properties. Seventeen of the 45 compounds were subjected to bioactivity validation using the resazurin microtiter assay. Among the 4 actives, compound 7 ((Z)-N-(2-isopropoxyphenyl)-2-oxo-2-((3-(trifluoromethyl)cyclohexyl)amino)acetimidic acid) displayed inhibitory activity up to 83% at 10 μg/mL concentration against the growth of the Mtb H37Ra strain. PMID:28280303

Predictors of therapeutic engagement in prison-based drug treatment.

PubMed

Welsh, Wayne N; McGrain, Patrick N

2008-08-01

Few studies to date have examined predictors of therapeutic engagement (TE) or other indicators of responsiveness to prison drug treatment. Subjects were 347 inmates participating in a 12-month modified therapeutic community (TC) drug treatment program at a specialized treatment prison for convicted, drug-involved offenders. Data were obtained through correctional databases and the administration of the TCU Drug Screen II, the Resident Evaluation of Self and Treatment (REST), and the Counselor Rating of Client (CRC) form. Three main hypotheses were supported: (1) baseline motivation predicted therapeutic engagement net of other inmate characteristics; (2) critical dimensions of the treatment experience (e.g., peer support, counselor rapport) also predicted therapeutic engagement; and (3) dynamic predictors and programmatic characteristics became more important over time. Implications for research, theory and policy are discussed.

Large-scale exploration and analysis of drug combinations.

PubMed

Li, Peng; Huang, Chao; Fu, Yingxue; Wang, Jinan; Wu, Ziyin; Ru, Jinlong; Zheng, Chunli; Guo, Zihu; Chen, Xuetong; Zhou, Wei; Zhang, Wenjuan; Li, Yan; Chen, Jianxin; Lu, Aiping; Wang, Yonghua

2015-06-15

Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered. We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications. The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Human intestinal transporter database: QSAR modeling and virtual profiling of drug uptake, efflux and interactions.

PubMed

Sedykh, Alexander; Fourches, Denis; Duan, Jianmin; Hucke, Oliver; Garneau, Michel; Zhu, Hao; Bonneau, Pierre; Tropsha, Alexander

2013-04-01

Membrane transporters mediate many biological effects of chemicals and play a major role in pharmacokinetics and drug resistance. The selection of viable drug candidates among biologically active compounds requires the assessment of their transporter interaction profiles. Using public sources, we have assembled and curated the largest, to our knowledge, human intestinal transporter database (>5,000 interaction entries for >3,700 molecules). This data was used to develop thoroughly validated classification Quantitative Structure-Activity Relationship (QSAR) models of transport and/or inhibition of several major transporters including MDR1, BCRP, MRP1-4, PEPT1, ASBT, OATP2B1, OCT1, and MCT1. QSAR models have been developed with advanced machine learning techniques such as Support Vector Machines, Random Forest, and k Nearest Neighbors using Dragon and MOE chemical descriptors. These models afforded high external prediction accuracies of 71-100% estimated by 5-fold external validation, and showed hit retrieval rates with up to 20-fold enrichment in the virtual screening of DrugBank compounds. The compendium of predictive QSAR models developed in this study can be used for virtual profiling of drug candidates and/or environmental agents with the optimal transporter profiles.

Nature is the best source of anti-inflammatory drugs: indexing natural products for their anti-inflammatory bioactivity.

PubMed

Aswad, Miran; Rayan, Mahmoud; Abu-Lafi, Saleh; Falah, Mizied; Raiyn, Jamal; Abdallah, Ziyad; Rayan, Anwar

2018-01-01

The aim was to index natural products for less expensive preventive or curative anti-inflammatory therapeutic drugs. A set of 441 anti-inflammatory drugs representing the active domain and 2892 natural products representing the inactive domain was used to construct a predictive model for bioactivity-indexing purposes. The model for indexing the natural products for potential anti-inflammatory activity was constructed using the iterative stochastic elimination algorithm (ISE). ISE is capable of differentiating between active and inactive anti-inflammatory molecules. By applying the prediction model to a mix set of (active/inactive) substances, we managed to capture 38% of the anti-inflammatory drugs in the top 1% of the screened set of chemicals, yielding enrichment factor of 38. Ten natural products that scored highly as potential anti-inflammatory drug candidates are disclosed. Searching the PubMed revealed that only three molecules (Moupinamide, Capsaicin, and Hypaphorine) out of the ten were tested and reported as anti-inflammatory. The other seven phytochemicals await evaluation for their anti-inflammatory activity in wet lab. The proposed anti-inflammatory model can be utilized for the virtual screening of large chemical databases and for indexing natural products for potential anti-inflammatory activity.

Screening_mgmt: a Python module for managing screening data.

PubMed

Helfenstein, Andreas; Tammela, Päivi

2015-02-01

High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers. © 2014 Society for Laboratory Automation and Screening.

Multiple target drug cocktail design for attacking the core network markers of four cancers using ligand-based and structure-based virtual screening methods

PubMed Central

2015-01-01

Background Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology. Methods In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins. Results We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy. Conclusions Combination of systems biology with computer-aided drug design could help us develop novel drug cocktails with multiple targets. We believe this will enhance the efficiency of therapeutic practice and lead to new directions for cancer therapy. PMID:26680552

Bipolar postpartum depression: An update and recommendations.

PubMed

Sharma, Verinder; Doobay, Minakshi; Baczynski, Christine

2017-09-01

Over the past few years there has been a surge of interest in the study of bipolar postpartum depression (PPD); however, questions remain about its prevalence, screening, clinical features, and treatment. Three electronic databases, MEDLINE/PubMed (1966-2016), PsycINFO (1806-2016), and the Cochrane Database of Systematic Reviews, were searched using a combination of the keywords bipolar, depression, postpartum, peripartum, prevalence, screening, diagnosis, treatment, drugs, and psychotherapy. The reference lists of articles identified were also searched. All relevant articles published in English were included. Depending on the population studied, 21.4-54% of women with PPD have a diagnosis of bipolar disorder (BD). Characteristic clinical features include younger age at illness onset, first onset of depression after childbirth, onset immediately after delivery, atypical depressive symptoms, psychotic features, mixed features, and history of BD in first-degree family members. Treatment should be guided by symptom acuity, safety concerns, the patient's response to past treatments, drug tolerability, and breastfeeding preference. In the absence of controlled treatment data, preference should be given to drugs normally indicated for bipolar depression including lithium, quetiapine and lamotrigine. Although antidepressants have been studied in combination with mood stabilizers in bipolar depression, these drugs should be avoided due to likelihood of elevated risk of induction of manic symptoms in the postpartum period. In the postpartum period, bipolar PPD is common, can be differentiated from unipolar PPD, and needs to be identified promptly in order to expedite appropriate treatment. Future studies on pharmacotherapy and psychotherapy should focus on the acute and preventative treatment of bipolar PPD. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of a novel multiple kinase inhibitor with potent antiviral activity against influenza virus by reducing viral polymerase activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sasaki, Yutaka; Kakisaka, Michinori; Chutiwitoonchai, Nopporn

Highlights: • Screening of 50,000 compounds and subsequent lead optimization identified WV970. • WV970 has antiviral effects against influenza A, B and highly pathogenic viral strains. • WV970 inhibits viral genome replication and transcription. • A target database search suggests that WV970 may bind to a number of kinases. • KINOMEscan screening revealed that WV970 has inhibitory effects on 15 kinases. - Abstract: Neuraminidase inhibitors are the only currently available influenza treatment, although resistant viruses to these drugs have already been reported. Thus, new antiviral drugs with novel mechanisms of action are urgently required. In this study, we identified amore » novel antiviral compound, WV970, through cell-based screening of a 50,000 compound library and subsequent lead optimization. This compound exhibited potent antiviral activity with nanomolar IC{sub 50} values against both influenza A and B viruses but not non-influenza RNA viruses. Time-of-addition and indirect immunofluorescence assays indicated that WV970 acted at an early stage of the influenza life cycle, but likely after nuclear entry of viral ribonucleoprotein (vRNP). Further analyses of viral RNA expression and viral polymerase activity indicated that WV970 inhibited vRNP-mediated viral genome replication and transcription. Finally, structure-based virtual screening and comprehensive human kinome screening were used to demonstrate that WV970 acts as a multiple kinase inhibitor, many of which are associated with influenza virus replication. Collectively, these results strongly suggest that WV970 is a promising anti-influenza drug candidate and that several kinases associated with viral replication are promising drug targets.« less

Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer's disease.

PubMed

Patel, Chirag N; Georrge, John J; Modi, Krunal M; Narechania, Moksha B; Patel, Daxesh P; Gonzalez, Frank J; Pandya, Himanshu A

2017-12-27

Alzheimer's disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering by using FAF-Drug-3 and 36 molecules were considered for molecular docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the molecular dynamics simulation analysis having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of molecular-level interactions.

Structure-based virtual screening and characterization of a novel IL-6 antagonistic compound from synthetic compound database.

PubMed

Wang, Jing; Qiao, Chunxia; Xiao, He; Lin, Zhou; Li, Yan; Zhang, Jiyan; Shen, Beifen; Fu, Tinghuan; Feng, Jiannan

2016-01-01

According to the three-dimensional (3D) complex structure of (hIL-6⋅hIL-6R⋅gp 130) 2 and the binding orientation of hIL-6, three compounds with high affinity to hIL-6R and bioactivity to block hIL-6 in vitro were screened theoretically from the chemical databases, including 3D-Available Chemicals Directory (ACD) and MDL Drug Data Report (MDDR), by means of the computer-guided virtual screening method. Using distance geometry, molecular modeling and molecular dynamics trajectory analysis methods, the binding mode and binding energy of the three compounds were evaluated theoretically. Enzyme-linked immunosorbent assay analysis demonstrated that all the three compounds could block IL-6 binding to IL-6R specifically. However, only compound 1 could effectively antagonize the function of hIL-6 and inhibit the proliferation of XG-7 cells in a dose-dependent manner, whereas it showed no cytotoxicity to SP2/0 or L929 cells. These data demonstrated that the compound 1 could be a promising candidate of hIL-6 antagonist.

In silico prediction of cytochrome P450-mediated drug metabolism.

PubMed

Zhang, Tao; Chen, Qi; Li, Li; Liu, Limin Angela; Wei, Dong-Qing

2011-06-01

The application of combinatorial chemistry and high-throughput screening technique enables the large number of chemicals to be generated and tested simultaneously, which will facilitate the drug development and discovery. At the same time, it brings about a challenge of how to efficiently identify the potential drug candidates from thousands of compounds. A way used to deal with the challenge is to consider the drug pharmacokinetic properties, such as absorption, distribution, metabolism and excretion (ADME), in the early stage of drug development. Among ADME properties, metabolism is of importance due to the strong association with efficacy and safety of drug. The review will focus on in silico approaches for prediction of Cytochrome P450-mediated drug metabolism. We will describe these predictive methods from two aspects, structure-based and data-based. Moreover, the applications and limitations of various methods will be discussed. Finally, we provide further direction toward improving the predictive accuracy of these in silico methods.

PubChem BioAssay: 2017 update

PubMed Central

Wang, Yanli; Bryant, Stephen H.; Cheng, Tiejun; Wang, Jiyao; Gindulyte, Asta; Shoemaker, Benjamin A.; Thiessen, Paul A.; He, Siqian; Zhang, Jian

2017-01-01

PubChem's BioAssay database (https://pubchem.ncbi.nlm.nih.gov) has served as a public repository for small-molecule and RNAi screening data since 2004 providing open access of its data content to the community. PubChem accepts data submission from worldwide researchers at academia, industry and government agencies. PubChem also collaborates with other chemical biology database stakeholders with data exchange. With over a decade's development effort, it becomes an important information resource supporting drug discovery and chemical biology research. To facilitate data discovery, PubChem is integrated with all other databases at NCBI. In this work, we provide an update for the PubChem BioAssay database describing several recent development including added sources of research data, redesigned BioAssay record page, new BioAssay classification browser and new features in the Upload system facilitating data sharing. PMID:27899599

Multinomial modeling and an evaluation of common data-mining algorithms for identifying signals of disproportionate reporting in pharmacovigilance databases.

PubMed

Johnson, Kjell; Guo, Cen; Gosink, Mark; Wang, Vicky; Hauben, Manfred

2012-12-01

A principal objective of pharmacovigilance is to detect adverse drug reactions that are unknown or novel in terms of their clinical severity or frequency. One method is through inspection of spontaneous reporting system databases, which consist of millions of reports of patients experiencing adverse effects while taking one or more drugs. For such large databases, there is an increasing need for quantitative and automated screening tools to assist drug safety professionals in identifying drug-event combinations (DECs) worthy of further investigation. Existing algorithms can effectively identify problematic DECs when the frequencies are high. However these algorithms perform differently for low-frequency DECs. In this work, we provide a method based on the multinomial distribution that identifies signals of disproportionate reporting, especially for low-frequency combinations. In addition, we comprehensively compare the performance of commonly used algorithms with the new approach. Simulation results demonstrate the advantages of the proposed method, and analysis of the Adverse Event Reporting System data shows that the proposed method can help detect interesting signals. Furthermore, we suggest that these methods be used to identify DECs that occur significantly less frequently than expected, thus identifying potential alternative indications for these drugs. We provide an empirical example that demonstrates the importance of exploring underexpected DECs. Code to implement the proposed method is available in R on request from the corresponding authors. kjell@arboranalytics.com or Mark.M.Gosink@Pfizer.com Supplementary data are available at Bioinformatics online.

Identification and evaluation of drug-supplement interactions in Hungarian hospital patients.

PubMed

Végh, Anna; Lankó, Erzsébet; Fittler, András; Vida, Róbert György; Miseta, Ildikó; Takács, Gábor; Botz, Lajos

2014-04-01

The increasing number of patients taking supplementary products together with prescribed medicines has become a new challenge for health care systems. These products may influence therapy outcomes by inducing unwanted effects. Particularly concerning is the potential for harmful interactions between prescribed medicines and supplementary products. The aims of the study were to evaluate supplement use, to identify and analyse potential interactions, and to assess the efficiency of computerised interaction screening. Participants of the study were inpatients and outpatients of a Hungarian university hospital. A cross-sectional point-of-care survey of 200 patients was carried out. Data was collected through personal interviews and a review of the medical records. Drug-drug, drug-supplement and supplement-supplement interactions were analysed with three interaction databases (Lexi-Interact Online, Medscape Drug Interaction Checker and Mediris). Prevalence of supplementary product use, number of medicines and supplementary products per patient, procurement sources of products, number of potentially severe interactions. There was a marked difference between data obtained from patient interviews and the medical records. 85.5 % of the surveyed patients took supplementary products during the 2 weeks prior to the interview. The average number of prescribed medicines and supplementary products were 7.8 and 2.5, respectively. Women were more likely to take supplements than men. There was no significant difference in supplement use between patients under or over 60 years, between inpatients and outpatients and among patients in various wards. 39.4 % of supplementary products were purchased outside a regulated pharmacy environment. Potentially severe drug-supplement interactions were detected with 45.2 % of supplement users; however the majority of interactions were not included in one or the other of the three databases. In addition to that the risk ratings of the same interactions varied greatly between databases. A significant number of patients are exposed to potential drug interactions with supplementary products; however interagreement among interaction databases is poor. Our data suggest that a full medication history should specifically address the intake of supplements.

tcpl: the ToxCast pipeline for high-throughput screening data.

PubMed

Filer, Dayne L; Kothiya, Parth; Setzer, R Woodrow; Judson, Richard S; Martin, Matthew T

2017-02-15

Large high-throughput screening (HTS) efforts are widely used in drug development and chemical toxicity screening. Wide use and integration of these data can benefit from an efficient, transparent and reproducible data pipeline. Summary: The tcpl R package and its associated MySQL database provide a generalized platform for efficiently storing, normalizing and dose-response modeling of large high-throughput and high-content chemical screening data. The novel dose-response modeling algorithm has been tested against millions of diverse dose-response series, and robustly fits data with outliers and cytotoxicity-related signal loss. tcpl is freely available on the Comprehensive R Archive Network under the GPL-2 license. martin.matt@epa.gov. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

Applications of computer-aided approaches in the development of hepatitis C antiviral agents.

PubMed

Ganesan, Aravindhan; Barakat, Khaled

2017-04-01

Hepatitis C virus (HCV) is a global health problem that causes several chronic life-threatening liver diseases. The numbers of people affected by HCV are rising annually. Since 2011, the FDA has approved several anti-HCV drugs; while many other promising HCV drugs are currently in late clinical trials. Areas covered: This review discusses the applications of different computational approaches in HCV drug design. Expert opinion: Molecular docking and virtual screening approaches have emerged as a low-cost tool to screen large databases and identify potential small-molecule hits against HCV targets. Ligand-based approaches are useful for filtering-out compounds with rich physicochemical properties to inhibit HCV targets. Molecular dynamics (MD) remains a useful tool in optimizing the ligand-protein complexes and understand the ligand binding modes and drug resistance mechanisms in HCV. Despite their varied roles, the application of in-silico approaches in HCV drug design is still in its infancy. A more mature application should aim at modelling the whole HCV replicon in its active form and help to identify new effective druggable sites within the replicon system. With more technological advancements, the roles of computer-aided methods are only going to increase several folds in the development of next-generation HCV drugs.

Study on the Mechanisms of Active Compounds in Traditional Chinese Medicine for the Treatment of Influenza Virus by Virtual Screening.

PubMed

Ai, Haixin; Wu, Xuewei; Qi, Mengyuan; Zhang, Li; Hu, Huan; Zhao, Qi; Zhao, Jian; Liu, Hongsheng

2018-06-01

In recent years, new strains of influenza virus such as H7N9, H10N8, H5N6 and H5N8 had continued to emerge. There was an urgent need for discovery of new anti-influenza virus drugs as well as accurate and efficient large-scale inhibitor screening methods. In this study, we focused on six influenza virus proteins that could be anti-influenza drug targets, including neuraminidase (NA), hemagglutinin (HA), matrix protein 1 (M1), M2 proton channel (M2), nucleoprotein (NP) and non-structural protein 1 (NS1). Structure-based molecular docking was utilized to identify potential inhibitors for these drug targets from 13144 compounds in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The results showed that 56 compounds could inhibit more than two drug targets simultaneously. Further, we utilized reverse docking to study the interaction of these compounds with host targets. Finally, the 22 compound inhibitors could stably bind to host targets with high binding free energy. The results showed that the Chinese herbal medicines had a multi-target effect, which could directly inhibit influenza virus by the target viral protein and indirectly inhibit virus by the human target protein. This method was of great value for large-scale virtual screening of new anti-influenza virus compounds.

Screening of pharmaceuticals and illicit drugs in wastewater and surface waters of Spain and Italy by high resolution mass spectrometry using UHPLC-QTOF MS and LC-LTQ-Orbitrap MS.

PubMed

Bade, Richard; Rousis, Nikolaos I; Bijlsma, Lubertus; Gracia-Lor, Emma; Castiglioni, Sara; Sancho, Juan V; Hernandez, Felix

2015-12-01

The existence of pharmaceuticals and illicit drugs (PIDs) in environmental waters has led many analytical chemists to develop screening methods for monitoring purposes. Water samples can contain a huge number of possible contaminants, commonly at low concentrations, which makes their detection and identification problematic. Liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) has proven itself effective in the screening of environmental contaminants. The present work investigates the use of the most popular HRMS instruments, quadrupole time-of-flight and linear trap quadrupole-Orbitrap, from two different laboratories. A suspect screening for PIDs was carried out on wastewater (influent and effluent) and surface water samples from Castellón, Eastern Spain, and Cremona, Northern Italy, incorporating a database of 107 PIDs (including 220 fragment ions). A comparison between the findings of both instruments and of the samples was made which highlights the advantages and drawbacks of the strategies applied in each case. In total, 28 compounds were detected and/or identified by either/both instruments with irbesartan, valsartan, benzoylecgonine and caffeine being the most commonly found compounds across all samples.

[Implementation of a computerized pharmacological database for pediatric use].

PubMed

Currò, V; Grimaldi, V; Polidori, G; Cascioli, E; Lanni, R; De Luca, F; D'Atri, A; Bernabei, A

1990-01-01

The authors present a pharmacological database to support teaching and care activity carried out in the Divisional Paediatric Ambulatory of the Catholic University of Rome. This database is included in a integrated system, ARPIA (Ambulatory and Research in Pediatric by Information Assistance), devoted to manage ambulatory paediatric data. ARPIA has been implemented by using a relational DBMS, very cheap and highly diffused on personal computers. The database specifies: active ingredient and code number related to it, clinical uses, doses, contra-indications and precautions, adverse effects, besides the possible wrapping available on the market. All this is showed on a single for that appears on the screen and allows a fast reading of the most important elements characterizing every drug. The search of the included drugs can be made on the basis of three different detailed lists: active ingredient, proprietary preparation and clinical use. It is, besides, possible to have a complete report about the drugs requested by the user. This system allows the user, without modifying the program, to interact with the included data modifying each element of the form. In the system there is also a fast consultation handbook containing for every active ingredient, the complete list of italian proprietary medicines. This system aims to give a better knowledge of the most commonly used drugs, not only limited to the paediatrician but also to the ambulatory health staff; an improvement of the therapy furthering, a more effective use of several pharmacological agents and first of all a training device not only to specialists but also to students.

[Computational chemistry in structure-based drug design].

PubMed

Cao, Ran; Li, Wei; Sun, Han-Zi; Zhou, Yu; Huang, Niu

2013-07-01

Today, the understanding of the sequence and structure of biologically relevant targets is growing rapidly and researchers from many disciplines, physics and computational science in particular, are making significant contributions to modern biology and drug discovery. However, it remains challenging to rationally design small molecular ligands with desired biological characteristics based on the structural information of the drug targets, which demands more accurate calculation of ligand binding free-energy. With the rapid advances in computer power and extensive efforts in algorithm development, physics-based computational chemistry approaches have played more important roles in structure-based drug design. Here we reviewed the newly developed computational chemistry methods in structure-based drug design as well as the elegant applications, including binding-site druggability assessment, large scale virtual screening of chemical database, and lead compound optimization. Importantly, here we address the current bottlenecks and propose practical solutions.

Machine Learning-based Virtual Screening and Its Applications to Alzheimer's Drug Discovery: A Review.

PubMed

Carpenter, Kristy A; Huang, Xudong

2018-06-07

Virtual Screening (VS) has emerged as an important tool in the drug development process, as it conducts efficient in silico searches over millions of compounds, ultimately increasing yields of potential drug leads. As a subset of Artificial Intelligence (AI), Machine Learning (ML) is a powerful way of conducting VS for drug leads. ML for VS generally involves assembling a filtered training set of compounds, comprised of known actives and inactives. After training the model, it is validated and, if sufficiently accurate, used on previously unseen databases to screen for novel compounds with desired drug target binding activity. The study aims to review ML-based methods used for VS and applications to Alzheimer's disease (AD) drug discovery. To update the current knowledge on ML for VS, we review thorough backgrounds, explanations, and VS applications of the following ML techniques: Naïve Bayes (NB), k-Nearest Neighbors (kNN), Support Vector Machines (SVM), Random Forests (RF), and Artificial Neural Networks (ANN). All techniques have found success in VS, but the future of VS is likely to lean more heavily toward the use of neural networks - and more specifically, Convolutional Neural Networks (CNN), which are a subset of ANN that utilize convolution. We additionally conceptualize a work flow for conducting ML-based VS for potential therapeutics of for AD, a complex neurodegenerative disease with no known cure and prevention. This both serves as an example of how to apply the concepts introduced earlier in the review and as a potential workflow for future implementation. Different ML techniques are powerful tools for VS, and they have advantages and disadvantages albeit. ML-based VS can be applied to AD drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Improving compound-protein interaction prediction by building up highly credible negative samples.

PubMed

Liu, Hui; Sun, Jianjiang; Guan, Jihong; Zheng, Jie; Zhou, Shuigeng

2015-06-15

Computational prediction of compound-protein interactions (CPIs) is of great importance for drug design and development, as genome-scale experimental validation of CPIs is not only time-consuming but also prohibitively expensive. With the availability of an increasing number of validated interactions, the performance of computational prediction approaches is severely impended by the lack of reliable negative CPI samples. A systematic method of screening reliable negative sample becomes critical to improving the performance of in silico prediction methods. This article aims at building up a set of highly credible negative samples of CPIs via an in silico screening method. As most existing computational models assume that similar compounds are likely to interact with similar target proteins and achieve remarkable performance, it is rational to identify potential negative samples based on the converse negative proposition that the proteins dissimilar to every known/predicted target of a compound are not much likely to be targeted by the compound and vice versa. We integrated various resources, including chemical structures, chemical expression profiles and side effects of compounds, amino acid sequences, protein-protein interaction network and functional annotations of proteins, into a systematic screening framework. We first tested the screened negative samples on six classical classifiers, and all these classifiers achieved remarkably higher performance on our negative samples than on randomly generated negative samples for both human and Caenorhabditis elegans. We then verified the negative samples on three existing prediction models, including bipartite local model, Gaussian kernel profile and Bayesian matrix factorization, and found that the performances of these models are also significantly improved on the screened negative samples. Moreover, we validated the screened negative samples on a drug bioactivity dataset. Finally, we derived two sets of new interactions by training an support vector machine classifier on the positive interactions annotated in DrugBank and our screened negative interactions. The screened negative samples and the predicted interactions provide the research community with a useful resource for identifying new drug targets and a helpful supplement to the current curated compound-protein databases. Supplementary files are available at: http://admis.fudan.edu.cn/negative-cpi/. © The Author 2015. Published by Oxford University Press.

[Artificial Intelligence in Drug Discovery].

PubMed

Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

2018-04-01

According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

An infrastructure to mine molecular descriptors for ligand selection on virtual screening.

PubMed

Seus, Vinicius Rosa; Perazzo, Giovanni Xavier; Winck, Ana T; Werhli, Adriano V; Machado, Karina S

2014-01-01

The receptor-ligand interaction evaluation is one important step in rational drug design. The databases that provide the structures of the ligands are growing on a daily basis. This makes it impossible to test all the ligands for a target receptor. Hence, a ligand selection before testing the ligands is needed. One possible approach is to evaluate a set of molecular descriptors. With the aim of describing the characteristics of promising compounds for a specific receptor we introduce a data warehouse-based infrastructure to mine molecular descriptors for virtual screening (VS). We performed experiments that consider as target the receptor HIV-1 protease and different compounds for this protein. A set of 9 molecular descriptors are taken as the predictive attributes and the free energy of binding is taken as a target attribute. By applying the J48 algorithm over the data we obtain decision tree models that achieved up to 84% of accuracy. The models indicate which molecular descriptors and their respective values are relevant to influence good FEB results. Using their rules we performed ligand selection on ZINC database. Our results show important reduction in ligands selection to be applied in VS experiments; for instance, the best selection model picked only 0.21% of the total amount of drug-like ligands.

Discovery and study of novel protein tyrosine phosphatase 1B inhibitors

NASA Astrophysics Data System (ADS)

Zhang, Qian; Chen, Xi; Feng, Changgen

2017-10-01

Protein tyrosine phosphatase 1B (PTP1B) is considered to be a target for therapy of type II diabetes and obesity. So it is of great significance to take advantage of a computer aided drug design protocol involving the structured-based virtual screening with docking simulations for fast searching small molecule PTP1B inhibitors. Based on optimized complex structure of PTP1B bound with specific inhibitor of IX1, structured-based virtual screening against a library of natural products containing 35308 molecules, which was constructed based on Traditional Chinese Medicine database@ Taiwan (TCM database@ Taiwan), was conducted to determine the occurrence of PTP1B inhibitors using the Lubbock module and CDOCKER module from Discovery Studio 3.1 software package. The results were further filtered by predictive ADME simulation and predictive toxic simulation. As a result, 2 good drug-like molecules, namely para-benzoquinone compound 1 and Clavepictine analogue 2 were identified ultimately with the dock score of original inhibitor (IX1) and the receptor as a threshold. Binding model analyses revealed that these two candidate compounds have good interactions with PTP1B. The PTP1B inhibitory activity of compound 2 hasn't been reported before. The optimized compound 2 has higher scores and deserves further study.

Small molecule inhibitors of mesotrypsin from a structure-based docking screen

DOE PAGES

Kayode, Olumide; Huang, Zunnan; Soares, Alexei S.; ...

2017-05-02

PRSS3/mesotrypsin is an atypical isoform of trypsin, the upregulation of which has been implicated in promoting tumor progression. To date there are no mesotrypsin-selective pharmacological inhibitors which could serve as tools for deciphering the pathological role of this enzyme, and could potentially form the basis for novel therapeutic strategies targeting mesotrypsin. A virtual screen of the Natural Product Database (NPD) and Food and Drug Administration (FDA) approved Drug Database was conducted by high-throughput molecular docking utilizing crystal structures of mesotrypsin. Twelve high-scoring compounds were selected for testing based on lowest free energy docking scores, interaction with key mesotrypsin active sitemore » residues, and commercial availability. Diminazene (C1D22956468), along with two similar compounds presenting the bis-benzamidine substructure, was validated as a competitive inhibitor of mesotrypsin and other human trypsin isoforms. Diminazene is the most potent small molecule inhibitor of mesotrypsin reported to date with an inhibitory constant (K i) of 3.6±0.3 pM. Diminazene was subsequently co-crystalized with mesotrypsin and the crystal structure was solved and refined to 1.25 Å resolution. This high resolution crystal structure can now offer a foundation for structure-guided efforts to develop novel and potentially more selective mesotrypsin inhibitors based on similar molecular substructures.« less

Small molecule inhibitors of mesotrypsin from a structure-based docking screen

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kayode, Olumide; Huang, Zunnan; Soares, Alexei S.

PRSS3/mesotrypsin is an atypical isoform of trypsin, the upregulation of which has been implicated in promoting tumor progression. To date there are no mesotrypsin-selective pharmacological inhibitors which could serve as tools for deciphering the pathological role of this enzyme, and could potentially form the basis for novel therapeutic strategies targeting mesotrypsin. A virtual screen of the Natural Product Database (NPD) and Food and Drug Administration (FDA) approved Drug Database was conducted by high-throughput molecular docking utilizing crystal structures of mesotrypsin. Twelve high-scoring compounds were selected for testing based on lowest free energy docking scores, interaction with key mesotrypsin active sitemore » residues, and commercial availability. Diminazene (C1D22956468), along with two similar compounds presenting the bis-benzamidine substructure, was validated as a competitive inhibitor of mesotrypsin and other human trypsin isoforms. Diminazene is the most potent small molecule inhibitor of mesotrypsin reported to date with an inhibitory constant (K i) of 3.6±0.3 pM. Diminazene was subsequently co-crystalized with mesotrypsin and the crystal structure was solved and refined to 1.25 Å resolution. This high resolution crystal structure can now offer a foundation for structure-guided efforts to develop novel and potentially more selective mesotrypsin inhibitors based on similar molecular substructures.« less

Development of predictive pharmacophore model for in silico screening, and 3D QSAR CoMFA and CoMSIA studies for lead optimization, for designing of potent tumor necrosis factor alpha converting enzyme inhibitors

NASA Astrophysics Data System (ADS)

Murumkar, Prashant Revan; Zambre, Vishal Prakash; Yadav, Mange Ram

2010-02-01

A chemical feature-based pharmacophore model was developed for Tumor Necrosis Factor-α converting enzyme (TACE) inhibitors. A five point pharmacophore model having two hydrogen bond acceptors (A), one hydrogen bond donor (D) and two aromatic rings (R) with discrete geometries as pharmacophoric features was developed. The pharmacophore model so generated was then utilized for in silico screening of a database. The pharmacophore model so developed was validated by using four compounds having proven TACE inhibitory activity which were grafted into the database. These compounds mapped well onto the five listed pharmacophoric features. This validated pharmacophore model was also used for alignment of molecules in CoMFA and CoMSIA analysis. The contour maps of the CoMFA/CoMSIA models were utilized to provide structural insight for activity improvement of potential novel TACE inhibitors. The pharmacophore model so developed could be used for in silico screening of any commercial/in house database for identification of TACE inhibiting lead compounds, and the leads so identified could be optimized using the developed CoMSIA model. The present work highlights the tremendous potential of the two mutually complementary ligand-based drug designing techniques (i.e. pharmacophore mapping and 3D-QSAR analysis) using TACE inhibitors as prototype biologically active molecules.

Analysis on composition rules of Chinese patent drugs treating pain-related diseases based on data mining method.

PubMed

Tang, Shi-Huan; Shen, Dan; Yang, Hong-Jun

2017-08-24

To analyze the composition rules of oral prescriptions in the treatment of headache, stomachache and dysmenorrhea recorded in National Standard for Chinese Patent Drugs (NSCPD) enacted by Ministry of Public Health of China and then make comparison between them to better understand pain treatment in different regions of human body. Constructed NSCPD database had been constructed in 2014. Prescriptions treating the three pain-related diseases were searched and screened from the database. Then data mining method such as association rules analysis and complex system entropy method integrated in the data mining software Traditional Chinese Medicine Inheritance Support System (TCMISS) were applied to process the data. Top 25 drugs with high frequency in the treatment of each disease were selected, and 51, 33 and 22 core combinations treating headache, stomachache and dysmenorrhea respectively were mined out as well. The composition rules of the oral prescriptions for treating headache, stomachache and dysmenorrhea recorded in NSCPD has been summarized. Although there were similarities between them, formula varied according to different locations of pain. It can serve as an evidence and reference for clinical treatment and new drug development.

Computer-aided identification of potential TYK2 inhibitors from drug database

NASA Astrophysics Data System (ADS)

Zhang, Wei; Li, Jianzong; Huang, Zhixin; Wang, Haiyang; Luo, Hao; Wang, Xin; Zhou, Nan; Wu, Chuanfang; Bao, Jinku

2016-10-01

TYK2 is a member of JAKs family protein tyrosine kinase activated in response to various cytokines. It plays a crucial role in transducing signals downstream of various cytokine receptors, which are involved in proinflammatory responses associated with immunological diseases. Thus, the study of selective TYK2 inhibitors is one of the most popular fields in anti-inflammation drug development. Herein, we adopted molecular docking, molecular dynamics simulation and MM-PBSA binding free energy calculation to screen potential TYK2-selective inhibitors from ZINC Drug Database. Finally, three small molecule drugs ZINC12503271 (Gemifloxacin), ZINC05844792 (Nebivolol) and ZINC00537805 (Glyburide) were selected as potential TYK2-selective inhibitors. Compared to known inhibitor 2,6-dichloro-N-{2-[(cyclopropylcarbonyl)amino]pyridin-4-yl}benzamide, these three candidates had better Grid score and Amber score from molecular docking and preferable results from binding free energy calculation as well. What's more, the ATP-binding site and A-loop motif had been identified to play key roles in TYK2-targeted inhibitor discovery. It is expected that our study will pave the way for the design of potent TYK2 inhibitors of new drugs to treat a wide variety of immunological diseases such as inflammatory diseases, multiple sclerosis, psoriasis inflammatory bowel disease (IBD) and so on.

iDrug: a web-accessible and interactive drug discovery and design platform

PubMed Central

2014-01-01

Background The progress in computer-aided drug design (CADD) approaches over the past decades accelerated the early-stage pharmaceutical research. Many powerful standalone tools for CADD have been developed in academia. As programs are developed by various research groups, a consistent user-friendly online graphical working environment, combining computational techniques such as pharmacophore mapping, similarity calculation, scoring, and target identification is needed. Results We presented a versatile, user-friendly, and efficient online tool for computer-aided drug design based on pharmacophore and 3D molecular similarity searching. The web interface enables binding sites detection, virtual screening hits identification, and drug targets prediction in an interactive manner through a seamless interface to all adapted packages (e.g., Cavity, PocketV.2, PharmMapper, SHAFTS). Several commercially available compound databases for hit identification and a well-annotated pharmacophore database for drug targets prediction were integrated in iDrug as well. The web interface provides tools for real-time molecular building/editing, converting, displaying, and analyzing. All the customized configurations of the functional modules can be accessed through featured session files provided, which can be saved to the local disk and uploaded to resume or update the history work. Conclusions iDrug is easy to use, and provides a novel, fast and reliable tool for conducting drug design experiments. By using iDrug, various molecular design processing tasks can be submitted and visualized simply in one browser without installing locally any standalone modeling softwares. iDrug is accessible free of charge at http://lilab.ecust.edu.cn/idrug. PMID:24955134

A graph-based approach to construct target-focused libraries for virtual screening.

PubMed

Naderi, Misagh; Alvin, Chris; Ding, Yun; Mukhopadhyay, Supratik; Brylinski, Michal

2016-01-01

Due to exorbitant costs of high-throughput screening, many drug discovery projects commonly employ inexpensive virtual screening to support experimental efforts. However, the vast majority of compounds in widely used screening libraries, such as the ZINC database, will have a very low probability to exhibit the desired bioactivity for a given protein. Although combinatorial chemistry methods can be used to augment existing compound libraries with novel drug-like compounds, the broad chemical space is often too large to be explored. Consequently, the trend in library design has shifted to produce screening collections specifically tailored to modulate the function of a particular target or a protein family. Assuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. On this account, we developed eSynth, an exhaustive graph-based search algorithm to computationally synthesize new compounds by reconnecting these building blocks following their connectivity patterns. We conducted a series of benchmarking calculations against the Directory of Useful Decoys, Enhanced database. First, in a self-benchmarking test, the correctness of the algorithm is validated with the objective to recover a molecule from its building blocks. Encouragingly, eSynth can efficiently rebuild more than 80 % of active molecules from their fragment components. Next, the capability to discover novel scaffolds is assessed in a cross-benchmarking test, where eSynth successfully reconstructed 40 % of the target molecules using fragments extracted from chemically distinct compounds. Despite an enormous chemical space to be explored, eSynth is computationally efficient; half of the molecules are rebuilt in less than a second, whereas 90 % take only about a minute to be generated. eSynth can successfully reconstruct chemically feasible molecules from molecular fragments. Furthermore, in a procedure mimicking the real application, where one expects to discover novel compounds based on a small set of already developed bioactives, eSynth is capable of generating diverse collections of molecules with the desired activity profiles. Thus, we are very optimistic that our effort will contribute to targeted drug discovery. eSynth is freely available to the academic community at www.brylinski.org/content/molecular-synthesis.Graphical abstractAssuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. Here, we developed eSynth, an automated method to synthesize new compounds by reconnecting these building blocks following the connectivity patterns via an exhaustive graph-based search algorithm. eSynth opens up a possibility to rapidly construct virtual screening libraries for targeted drug discovery.

Discovery of Anthelmintic Drug Targets and Drugs Using Chokepoints in Nematode Metabolic Pathways

PubMed Central

Taylor, Christina M.; Wang, Qi; Rosa, Bruce A.; Huang, Stanley Ching-Cheng; Powell, Kerrie; Schedl, Tim; Pearce, Edward J.; Abubucker, Sahar; Mitreva, Makedonka

2013-01-01

Parasitic roundworm infections plague more than 2 billion people (1/3 of humanity) and cause drastic losses in crops and livestock. New anthelmintic drugs are urgently needed as new drug resistance and environmental concerns arise. A “chokepoint reaction” is defined as a reaction that either consumes a unique substrate or produces a unique product. A chokepoint analysis provides a systematic method of identifying novel potential drug targets. Chokepoint enzymes were identified in the genomes of 10 nematode species, and the intersection and union of all chokepoint enzymes were found. By studying and experimentally testing available compounds known to target proteins orthologous to nematode chokepoint proteins in public databases, this study uncovers features of chokepoints that make them successful drug targets. Chemogenomic screening was performed on drug-like compounds from public drug databases to find existing compounds that target homologs of nematode chokepoints. The compounds were prioritized based on chemical properties frequently found in successful drugs and were experimentally tested using Caenorhabditis elegans. Several drugs that are already known anthelmintic drugs and novel candidate targets were identified. Seven of the compounds were tested in Caenorhabditis elegans and three yielded a detrimental phenotype. One of these three drug-like compounds, Perhexiline, also yielded a deleterious effect in Haemonchus contortus and Onchocerca lienalis, two nematodes with divergent forms of parasitism. Perhexiline, known to affect the fatty acid oxidation pathway in mammals, caused a reduction in oxygen consumption rates in C. elegans and genome-wide gene expression profiles provided an additional confirmation of its mode of action. Computational modeling of Perhexiline and its target provided structural insights regarding its binding mode and specificity. Our lists of prioritized drug targets and drug-like compounds have potential to expedite the discovery of new anthelmintic drugs with broad-spectrum efficacy. PMID:23935495

Structure-based virtual screening efforts against HIV-1 reverse transcriptase to introduce the new potent non-nucleoside reverse transcriptase inhibitor

NASA Astrophysics Data System (ADS)

Hosseini, Yaser; Mollica, Adriano; Mirzaie, Sako

2016-12-01

The human immunodeficiency virus (HIV) which is strictly related to the development of AIDS, is treated by a cocktail of drugs, but due its high propensity gain drug resistance, the rational development of new medicine is highly desired. Among the different mechanism of action we selected the reverse transcriptase (RT) inhibition, for our studies. With the aim to identify new chemical entities to be used for further rational drug design, a set of 3000 molecules from the Zinc Database have been screened by docking experiments using AutoDock Vina software. The best ranked compounds with respect of the crystallographic inhibitor MK-4965 resulted to be five compounds, and the best among them was further tested by molecular dynamics (MD) simulation. Our results indicate that comp1 has a stronger interaction with the subsite p66 of RT than MK-4965 and that both are able to stabilize specific conformational changes of the RT 3D structure, which may explain their activity as inhibitors. Therefore comp1 could be a good candidate for biological tests and further development.

Property distribution of drug-related chemical databases*

NASA Astrophysics Data System (ADS)

Oprea, Tudor I.

2000-04-01

The process of compound selection and prioritization is crucial for both combinatorial chemistry (CBC) and high throughput screening (HTS). Compound libraries have to be screened for unwanted chemical structures, as well as for unwanted chemical properties. Property extrema can be eliminated by using property filters, in accordance with their actual distribution. Property distribution was examined in the following compound databases: MACCS-II Drug Data Report (MDDR), Current Patents Fast-alert, Comprehensive Medicinal Chemistry, Physician Desk Reference, New Chemical Entities, and the Available Chemical Directory (ACD). The ACDF and MDDRF subsets were created by removing reactive functionalities from the ACD and MDDR databases, respectively. The ACDF subset was further filtered by keeping only molecules with a `drug-like' score [Ajay et al., J. Med. Chem., 41 (1998) 3314; Sadowski and Kubinyi, J. Med. Chem., 41 (1998) 3325] below 0.8. The following properties were examined: molecular weight (MW), the calculated octanol/water partition coefficient (CLOGP), the number of rotatable (RTB) and rigid bonds (RGB), the number of rings (RNG), and the number of hydrogen bond donors (HDO) and acceptors (HAC). Of these, MW and CLOGP follow a Gaussian distribution, whereas all other descriptors have an asymmetric (truncated Gaussian) distribution. Four out of five compounds in ACDF and MDDRF pass the `rule of 5' test, a probability scheme that estimates oral absorption proposed by Lipinski et al. [Adv. Drug Deliv. Rev., 23 (1997) 3]. Because property distributions of HDO, HAC, MW and CLOGP (used in the `rule of 5' test) do not differ significantly between these datasets, the `rule of 5' does not distinguish `drugs' from `nondrugs'. Therefore, Pareto analyses were performed to examine skewed distributions in all compound collections. Seventy percent of the `drug-like' compounds were found between the following limits: 0 ≤ HDO ≤ 2, 2 ≤ HAC ≤ 9, 2 ≤ RTB ≤ 8, and 1 ≤ RNG ≤ 4, respectively. The number of launched drugs in MDDR having 0 ≤ HDO ≤ 2 is 4.8 times higher than the number of drugs having 3 ≤ HDO ≤ 5. Skewed distributions can be exploited to focus on the `drug-like space': 62.68% of ACDF (`nondrug-like') compounds have 0 ≤ RNG ≤ 2, and RGB ≤ 17, while 28.88% of ACDF compounds have 3 ≤ RNG ≤ 13, and 18 ≤ RGB ≤ 56. By contrast, 61.22% of MDDRF compounds have RNG ≥ 3, and RGB ≥ 18, and only 24.73% of MDDRF compounds have 0 ≤ RNG ≤ 2 rings, and RGB ≤ 17. The probability of identifying `drug-like' structures increases with molecular complexity.

[Activity of NTDs Drug-discovery Research Consortium].

PubMed

Namatame, Ichiji

2016-01-01

Neglected tropical diseases (NTDs) are an extremely important issue facing global health care. To improve "access to health" where people are unable to access adequate medical care due to poverty and weak healthcare systems, we have established two consortiums: the NTD drug discovery research consortium, and the pediatric praziquantel consortium. The NTD drug discovery research consortium, which involves six institutions from industry, government, and academia, as well as an international non-profit organization, is committed to developing anti-protozoan active compounds for three NTDs (Leishmaniasis, Chagas disease, and African sleeping sickness). Each participating institute will contribute their efforts to accomplish the following: selection of drug targets based on information technology, and drug discovery by three different approaches (in silico drug discovery, "fragment evolution" which is a unique drug designing method of Astellas Pharma, and phenotypic screening with Astellas' compound library). The consortium has established a brand new database (Integrated Neglected Tropical Disease Database; iNTRODB), and has selected target proteins for the in silico and fragment evolution drug discovery approaches. Thus far, we have identified a number of promising compounds that inhibit the target protein, and we are currently trying to improve the anti-protozoan activity of these compounds. The pediatric praziquantel consortium was founded in July 2012 to develop and register a new praziquantel pediatric formulation for the treatment of schistosomiasis. Astellas Pharma has been a core member in this consortium since its establishment, and has provided expertise and technology in the area of pediatric formulation development and clinical development.

QSAR of phytochemicals for the design of better drugs.

PubMed

Kar, Supratik; Roy, Kunal

2012-10-01

Phytochemicals have been the single most prolific source of leads for the development of new drug entities from the dawn of the drug discovery. They cover a wide range of therapeutic indications with a great diversity of chemical structures. The research fraternity still believes in exploring the phytochemicals for new drug discovery. Application of molecular biological techniques has increased the availability of novel compounds that can be conveniently isolated from natural sources. Combinatorial chemistry approaches are being applied based on phytochemical scaffolds to create screening libraries that closely resemble drug-like compounds. In silico techniques like quantitative structure-activity relationships (QSAR), pharmacophore and virtual screening are playing crucial and rate accelerating steps for the better drug design in modern era. QSAR models of different classes of phytochemicals covering different therapeutic areas are thoroughly discussed in the review. Further, the authors have enlisted all the available phytochemical databases for the convenience of researchers working in the area. This review justifies the need to develop more QSAR models for the design of better drugs from phytochemicals. Technical drawbacks associated with phytochemical research have been lessened, and there are better opportunities to explore the biological activity of previously inaccessible sources of phytochemicals although there is still the need to reduce the time and cost involvement in such exercise. The future possibilities for the integration of ethnopharmacology with QSAR, place us at an exciting stage that will allow us to explore plant sources worldwide and design better drugs.

Qualitative screening for new psychoactive substances in wastewater collected during a city festival using liquid chromatography coupled to high-resolution mass spectrometry.

PubMed

Causanilles, Ana; Kinyua, Juliet; Ruttkies, Christoph; van Nuijs, Alexander L N; Emke, Erik; Covaci, Adrian; de Voogt, Pim

2017-10-01

The inclusion of new psychoactive substances (NPS) in the wastewater-based epidemiology approach presents challenges, such as the reduced number of users that translates into low concentrations of residues and the limited pharmacokinetics information available, which renders the choice of target biomarker difficult. The sampling during special social settings, the analysis with improved analytical techniques, and data processing with specific workflow to narrow the search, are required approaches for a successful monitoring. This work presents the application of a qualitative screening technique to wastewater samples collected during a city festival, where likely users of recreational substances gather and consequently higher residual concentrations of used NPS are expected. The analysis was performed using liquid chromatography coupled to high-resolution mass spectrometry. Data were processed using an algorithm that involves the extraction of accurate masses (calculated based on molecular formula) of expected m/z from an in-house database containing about 2,000 entries, including NPS and transformation products. We positively identified eight NPS belonging to the classes of synthetic cathinones, phenethylamines and opioids. In addition, the presence of benzodiazepine analogues, classical drugs and other licit substances with potential for abuse was confirmed. The screening workflow based on a database search was useful in the identification of NPS biomarkers in wastewater. The findings highlight the specific classical drugs and low NPS use in the Netherlands. Additionally, meta-chlorophenylpiperazine (mCPP), 2,5-dimethoxy-4-bromophenethylamine (2C-B), and 4-fluoroamphetamine (FA) were identified in wastewater for the first time. Copyright © 2017 Elsevier Ltd. All rights reserved.

The relationship between target-class and the physicochemical properties of antibacterial drugs

PubMed Central

Mugumbate, Grace; Overington, John P.

2015-01-01

The discovery of novel mechanism of action (MOA) antibacterials has been associated with the concept that antibacterial drugs occupy a differentiated region of physicochemical space compared to human-targeted drugs. With, in broad terms, antibacterials having higher molecular weight, lower log P and higher polar surface area (PSA). By analysing the physicochemical properties of about 1700 approved drugs listed in the ChEMBL database, we show, that antibacterials for whose targets are riboproteins (i.e., composed of a complex of RNA and protein) fall outside the conventional human ‘drug-like’ chemical space; whereas antibacterials that modulate bacterial protein targets, generally comply with the ‘rule-of-five’ guidelines for classical oral human drugs. Our analysis suggests a strong target-class association for antibacterials—either protein-targeted or riboprotein-targeted. There is much discussion in the literature on the failure of screening approaches to deliver novel antibacterial lead series, and linkage of this poor success rate for antibacterials with the chemical space properties of screening collections. Our analysis suggests that consideration of target-class may be an underappreciated factor in antibacterial lead discovery, and that in fact bacterial protein-targets may well have similar binding site characteristics to human protein targets, and questions the assumption that larger, more polar compounds are a key part of successful future antibacterial discovery. PMID:25975639

Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification

PubMed Central

Ballester, Pedro J.; Mangold, Martina; Howard, Nigel I.; Robinson, Richard L. Marchese; Abell, Chris; Blumberger, Jochen; Mitchell, John B. O.

2012-01-01

One of the initial steps of modern drug discovery is the identification of small organic molecules able to inhibit a target macromolecule of therapeutic interest. A small proportion of these hits are further developed into lead compounds, which in turn may ultimately lead to a marketed drug. A commonly used screening protocol used for this task is high-throughput screening (HTS). However, the performance of HTS against antibacterial targets has generally been unsatisfactory, with high costs and low rates of hit identification. Here, we present a novel computational methodology that is able to identify a high proportion of structurally diverse inhibitors by searching unusually large molecular databases in a time-, cost- and resource-efficient manner. This virtual screening methodology was tested prospectively on two versions of an antibacterial target (type II dehydroquinase from Mycobacterium tuberculosis and Streptomyces coelicolor), for which HTS has not provided satisfactory results and consequently practically all known inhibitors are derivatives of the same core scaffold. Overall, our protocols identified 100 new inhibitors, with calculated Ki ranging from 4 to 250 μM (confirmed hit rates are 60% and 62% against each version of the target). Most importantly, over 50 new active molecular scaffolds were discovered that underscore the benefits that a wide application of prospectively validated in silico screening tools is likely to bring to antibacterial hit identification. PMID:22933186

Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification.

PubMed

Ballester, Pedro J; Mangold, Martina; Howard, Nigel I; Robinson, Richard L Marchese; Abell, Chris; Blumberger, Jochen; Mitchell, John B O

2012-12-07

One of the initial steps of modern drug discovery is the identification of small organic molecules able to inhibit a target macromolecule of therapeutic interest. A small proportion of these hits are further developed into lead compounds, which in turn may ultimately lead to a marketed drug. A commonly used screening protocol used for this task is high-throughput screening (HTS). However, the performance of HTS against antibacterial targets has generally been unsatisfactory, with high costs and low rates of hit identification. Here, we present a novel computational methodology that is able to identify a high proportion of structurally diverse inhibitors by searching unusually large molecular databases in a time-, cost- and resource-efficient manner. This virtual screening methodology was tested prospectively on two versions of an antibacterial target (type II dehydroquinase from Mycobacterium tuberculosis and Streptomyces coelicolor), for which HTS has not provided satisfactory results and consequently practically all known inhibitors are derivatives of the same core scaffold. Overall, our protocols identified 100 new inhibitors, with calculated K(i) ranging from 4 to 250 μM (confirmed hit rates are 60% and 62% against each version of the target). Most importantly, over 50 new active molecular scaffolds were discovered that underscore the benefits that a wide application of prospectively validated in silico screening tools is likely to bring to antibacterial hit identification.

Evolving BioAssay Ontology (BAO): modularization, integration and applications

PubMed Central

2014-01-01

The lack of established standards to describe and annotate biological assays and screening outcomes in the domain of drug and chemical probe discovery is a severe limitation to utilize public and proprietary drug screening data to their maximum potential. We have created the BioAssay Ontology (BAO) project (http://bioassayontology.org) to develop common reference metadata terms and definitions required for describing relevant information of low-and high-throughput drug and probe screening assays and results. The main objectives of BAO are to enable effective integration, aggregation, retrieval, and analyses of drug screening data. Since we first released BAO on the BioPortal in 2010 we have considerably expanded and enhanced BAO and we have applied the ontology in several internal and external collaborative projects, for example the BioAssay Research Database (BARD). We describe the evolution of BAO with a design that enables modeling complex assays including profile and panel assays such as those in the Library of Integrated Network-based Cellular Signatures (LINCS). One of the critical questions in evolving BAO is the following: how can we provide a way to efficiently reuse and share among various research projects specific parts of our ontologies without violating the integrity of the ontology and without creating redundancies. This paper provides a comprehensive answer to this question with a description of a methodology for ontology modularization using a layered architecture. Our modularization approach defines several distinct BAO components and separates internal from external modules and domain-level from structural components. This approach facilitates the generation/extraction of derived ontologies (or perspectives) that can suit particular use cases or software applications. We describe the evolution of BAO related to its formal structures, engineering approaches, and content to enable modeling of complex assays and integration with other ontologies and datasets. PMID:25093074

Evolving BioAssay Ontology (BAO): modularization, integration and applications.

PubMed

Abeyruwan, Saminda; Vempati, Uma D; Küçük-McGinty, Hande; Visser, Ubbo; Koleti, Amar; Mir, Ahsan; Sakurai, Kunie; Chung, Caty; Bittker, Joshua A; Clemons, Paul A; Brudz, Steve; Siripala, Anosha; Morales, Arturo J; Romacker, Martin; Twomey, David; Bureeva, Svetlana; Lemmon, Vance; Schürer, Stephan C

2014-01-01

The lack of established standards to describe and annotate biological assays and screening outcomes in the domain of drug and chemical probe discovery is a severe limitation to utilize public and proprietary drug screening data to their maximum potential. We have created the BioAssay Ontology (BAO) project (http://bioassayontology.org) to develop common reference metadata terms and definitions required for describing relevant information of low-and high-throughput drug and probe screening assays and results. The main objectives of BAO are to enable effective integration, aggregation, retrieval, and analyses of drug screening data. Since we first released BAO on the BioPortal in 2010 we have considerably expanded and enhanced BAO and we have applied the ontology in several internal and external collaborative projects, for example the BioAssay Research Database (BARD). We describe the evolution of BAO with a design that enables modeling complex assays including profile and panel assays such as those in the Library of Integrated Network-based Cellular Signatures (LINCS). One of the critical questions in evolving BAO is the following: how can we provide a way to efficiently reuse and share among various research projects specific parts of our ontologies without violating the integrity of the ontology and without creating redundancies. This paper provides a comprehensive answer to this question with a description of a methodology for ontology modularization using a layered architecture. Our modularization approach defines several distinct BAO components and separates internal from external modules and domain-level from structural components. This approach facilitates the generation/extraction of derived ontologies (or perspectives) that can suit particular use cases or software applications. We describe the evolution of BAO related to its formal structures, engineering approaches, and content to enable modeling of complex assays and integration with other ontologies and datasets.

Avalanche for shape and feature-based virtual screening with 3D alignment

NASA Astrophysics Data System (ADS)

Diller, David J.; Connell, Nancy D.; Welsh, William J.

2015-11-01

This report introduces a new ligand-based virtual screening tool called Avalanche that incorporates both shape- and feature-based comparison with three-dimensional (3D) alignment between the query molecule and test compounds residing in a chemical database. Avalanche proceeds in two steps. The first step is an extremely rapid shape/feature based comparison which is used to narrow the focus from potentially millions or billions of candidate molecules and conformations to a more manageable number that are then passed to the second step. The second step is a detailed yet still rapid 3D alignment of the remaining candidate conformations to the query conformation. Using the 3D alignment, these remaining candidate conformations are scored, re-ranked and presented to the user as the top hits for further visualization and evaluation. To provide further insight into the method, the results from two prospective virtual screens are presented which show the ability of Avalanche to identify hits from chemical databases that would likely be missed by common substructure-based or fingerprint-based search methods. The Avalanche method is extended to enable patent landscaping, i.e., structural refinements to improve the patentability of hits for deployment in drug discovery campaigns.

A new retrospective, multi-evidence veterinary drug screening method using drift tube ion mobility mass spectrometry.

PubMed

Xu, Zhenzhen; Li, Jianzhong; Chen, Ailiang; Ma, Xin; Yang, Shuming

2018-05-03

The retrospectivity (the ability to retrospect to a previously unknown compound in raw data) is very meaningful for food safety and risk assessment when facing new emerging drugs. Accurate mass and retention time based screening may lead false positive and false negative results so new retrospective, reliable platform is desirable. Different concentration levels of standards with and without matrix were analyzed using ion mobility (IM)-quadrupole-time-of-flight (Q-TOF) for collecting retrospective accurate mass, retention time, drift time and tandem MS evidence for identification in a single experiment. The isomer separation ability of IM and the four-dimensional (4D) feature abundance quantification abilities were evaluated for veterinary drugs for the first time. The sensitivity of the IM-Q-TOF workflow was obviously higher than that of the traditional database searching algorithm [find by formula (FbF) function] for Q-TOF. In addition, the IM-Q-TOF workflow contained most of the results from FbF and removed the false positive results. Some isomers were separated by IM and the 4D feature abundance quantitation removed interference with similar accurate mass and showed good linearity. A new retrospective, multi-evidence platform was built for veterinary drug screening in a single experiment. The sensitivity was significantly improved and the data can be used for quantification. The platform showed its potential to be used for food safety and risk assessment. This article is protected by copyright. All rights reserved.

A Drug Discovery Partnership for Personalized Breast Cancer Therapy

DTIC Science & Technology

2013-09-01

structures of ER alpha and beta (with bound agonists or antagonists) and then virtually screen the USDA Phytochemical, Chinese Herbal Medicine , and the FDA...ER agonists and antagonists that are in the registered pharmaceuticals and herbal medicine databases. The 29 analogs obtained have been...Drew, T. Wang, J. Antoon, T. Nguyen, P. Dupart, Y. Wang, M. Zhao, Y.Y. Liu, M. Foroozesh, and B. Beckman, submitted to the Journal of Medicinal

Bioinformatics: Cheap and robust method to explore biomaterial from Indonesia biodiversity

NASA Astrophysics Data System (ADS)

Widodo

2015-02-01

Indonesia has a huge amount of biodiversity, which may contain many biomaterials for pharmaceutical application. These resources potency should be explored to discover new drugs for human wealth. However, the bioactive screening using conventional methods is very expensive and time-consuming. Therefore, we developed a methodology for screening the potential of natural resources based on bioinformatics. The method is developed based on the fact that organisms in the same taxon will have similar genes, metabolism and secondary metabolites product. Then we employ bioinformatics to explore the potency of biomaterial from Indonesia biodiversity by comparing species with the well-known taxon containing the active compound through published paper or chemical database. Then we analyze drug-likeness, bioactivity and the target proteins of the active compound based on their molecular structure. The target protein was examined their interaction with other proteins in the cell to determine action mechanism of the active compounds in the cellular level, as well as to predict its side effects and toxicity. By using this method, we succeeded to screen anti-cancer, immunomodulators and anti-inflammation from Indonesia biodiversity. For example, we found anticancer from marine invertebrate by employing the method. The anti-cancer was explore based on the isolated compounds of marine invertebrate from published article and database, and then identified the protein target, followed by molecular pathway analysis. The data suggested that the active compound of the invertebrate able to kill cancer cell. Further, we collect and extract the active compound from the invertebrate, and then examined the activity on cancer cell (MCF7). The MTT result showed that the methanol extract of marine invertebrate was highly potent in killing MCF7 cells. Therefore, we concluded that bioinformatics is cheap and robust way to explore bioactive from Indonesia biodiversity for source of drug and another pharmaceutical material.

Practical application of in silico fragmentation based residue screening with ion mobility high-resolution mass spectrometry.

PubMed

Kaufmann, Anton; Butcher, Patrick; Maden, Kathry; Walker, Stephan; Widmer, Mirjam

2017-07-15

A screening concept for residues in complex matrices based on liquid chromatography coupled to ion mobility high-resolution mass spectrometry LC/IMS-HRMS is presented. The comprehensive four-dimensional data (chromatographic retention time, drift time, mass-to-charge and ion abundance) obtained in data-independent acquisition (DIA) mode was used for data mining. An in silico fragmenter utilizing a molecular structure database was used for suspect screening, instead of targeted screening with reference substances. The utilized data-independent acquisition mode relies on the MS E concept; where two constantly alternating HRMS scans (low and high fragmentation energy) are acquired. Peak deconvolution and drift time alignment of ions from the low (precursor ion) and high (product ion) energy scan result in relatively clean product ion spectra. A bond dissociation in silico fragmenter (MassFragment) supplied with mol files of compounds of interest was used to explain the observed product ions of each extracted candidate component (chromatographic peak). Two complex matrices (fish and bovine liver extract) were fortified with 98 veterinary drugs. Out of 98 screened compounds 94 could be detected with the in silico based screening approach. The high correlation among drift time and m/z value of equally charged ions was utilized for an orthogonal filtration (ranking). Such an orthogonal ion mobility based filter removes multiply charged ions (e.g. peptides and proteins from the matrix) as well as noise and artefacts. Most significantly, this filtration dramatically reduces false positive findings but hardly increases false negative findings. The proposed screening approach may offer new possibilities for applications where reference compounds are hardly or not at all commercially available. Such areas may be the analysis of metabolites of drugs, pyrrolizidine alkaloids, marine toxins, derivatives of sildenafil or novel designer drugs (new psychoactive substances). Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Contaminant screening of wastewater with HPLC-IM-qTOF-MS and LC+LC-IM-qTOF-MS using a CCS database.

PubMed

Stephan, Susanne; Hippler, Joerg; Köhler, Timo; Deeb, Ahmad A; Schmidt, Torsten C; Schmitz, Oliver J

2016-09-01

Non-target analysis has become an important tool in the field of water analysis since a broad variety of pollutants from different sources are released to the water cycle. For identification of compounds in such complex samples, liquid chromatography coupled to high resolution mass spectrometry are often used. The introduction of ion mobility spectrometry provides an additional separation dimension and allows determining collision cross sections (CCS) of the analytes as a further physicochemical constant supporting the identification. A CCS database with more than 500 standard substances including drug-like compounds and pesticides was used for CCS data base search in this work. A non-target analysis of a wastewater sample was initially performed with high performance liquid chromatography (HPLC) coupled to an ion mobility-quadrupole-time of flight mass spectrometer (IM-qTOF-MS). A database search including exact mass (±5 ppm) and CCS (±1 %) delivered 22 different compounds. Furthermore, the same sample was analyzed with a two-dimensional LC method, called LC+LC, developed in our group for the coupling to IM-qTOF-MS. This four dimensional separation platform revealed 53 different compounds, identified over exact mass and CCS, in the examined wastewater sample. It is demonstrated that the CCS database can also help to distinguish between isobaric structures exemplified for cyclophosphamide and ifosfamide. Graphical Abstract Scheme of sample analysis and database screening.

Reliability and validity assessment of administrative databases in measuring the quality of rectal cancer management.

PubMed

Corbellini, Carlo; Andreoni, Bruno; Ansaloni, Luca; Sgroi, Giovanni; Martinotti, Mario; Scandroglio, Ildo; Carzaniga, Pierluigi; Longoni, Mauro; Foschi, Diego; Dionigi, Paolo; Morandi, Eugenio; Agnello, Mauro

2018-01-01

Measurement and monitoring of the quality of care using a core set of quality measures are increasing in health service research. Although administrative databases include limited clinical data, they offer an attractive source for quality measurement. The purpose of this study, therefore, was to evaluate the completeness of different administrative data sources compared to a clinical survey in evaluating rectal cancer cases. Between May 2012 and November 2014, a clinical survey was done on 498 Lombardy patients who had rectal cancer and underwent surgical resection. These collected data were compared with the information extracted from administrative sources including Hospital Discharge Dataset, drug database, daycare activity data, fee-exemption database, and regional screening program database. The agreement evaluation was performed using a set of 12 quality indicators. Patient complexity was a difficult indicator to measure for lack of clinical data. Preoperative staging was another suboptimal indicator due to the frequent missing administrative registration of tests performed. The agreement between the 2 data sources regarding chemoradiotherapy treatments was high. Screening detection, minimally invasive techniques, length of stay, and unpreventable readmissions were detected as reliable quality indicators. Postoperative morbidity could be a useful indicator but its agreement was lower, as expected. Healthcare administrative databases are large and real-time collected repositories of data useful in measuring quality in a healthcare system. Our investigation reveals that the reliability of indicators varies between them. Ideally, a combination of data from both sources could be used in order to improve usefulness of less reliable indicators.

TCMSP: a database of systems pharmacology for drug discovery from herbal medicines.

PubMed

Ru, Jinlong; Li, Peng; Wang, Jinan; Zhou, Wei; Li, Bohui; Huang, Chao; Li, Pidong; Guo, Zihu; Tao, Weiyang; Yang, Yinfeng; Xu, Xue; Li, Yan; Wang, Yonghua; Yang, Ling

2014-01-01

Modern medicine often clashes with traditional medicine such as Chinese herbal medicine because of the little understanding of the underlying mechanisms of action of the herbs. In an effort to promote integration of both sides and to accelerate the drug discovery from herbal medicines, an efficient systems pharmacology platform that represents ideal information convergence of pharmacochemistry, ADME properties, drug-likeness, drug targets, associated diseases and interaction networks, are urgently needed. The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 Chinese herbs registered in the Chinese pharmacopoeia with 29,384 ingredients, 3,311 targets and 837 associated diseases. Twelve important ADME-related properties like human oral bioavailability, half-life, drug-likeness, Caco-2 permeability, blood-brain barrier and Lipinski's rule of five are provided for drug screening and evaluation. TCMSP also provides drug targets and diseases of each active compound, which can automatically establish the compound-target and target-disease networks that let users view and analyze the drug action mechanisms. It is designed to fuel the development of herbal medicines and to promote integration of modern medicine and traditional medicine for drug discovery and development. The particular strengths of TCMSP are the composition of the large number of herbal entries, and the ability to identify drug-target networks and drug-disease networks, which will help revealing the mechanisms of action of Chinese herbs, uncovering the nature of TCM theory and developing new herb-oriented drugs. TCMSP is freely available at http://sm.nwsuaf.edu.cn/lsp/tcmsp.php.

Management of Psychotropic Drug-Induced DRESS Syndrome: A Systematic Review.

PubMed

Bommersbach, Tanner J; Lapid, Maria I; Leung, Jonathan G; Cunningham, Julie L; Rummans, Teresa A; Kung, Simon

2016-06-01

Drug rash with eosinophilia and systemic symptoms (DRESS) is a severe cutaneous eruption that has been linked to several common drugs and drug categories, including antiepileptics, allopurinol, sulfonamides, and various antibiotics; however, because of a number of recent case reports linking psychotropic medications to this condition, DRESS is increasingly recognized among psychiatrists. We systematically reviewed all psychotropic drugs linked to DRESS syndrome, and this article summarizes the clinical management relevant to psychiatric professionals. A comprehensive search was performed using Ovid MEDLINE, Ovid EMBASE, Ovid Cochrane Database of Systematic Reviews, Web of Science, Scopus, and Litt's Drug Eruption and Reaction Database for articles published in English during the past 20 years (1996-2015) using the search terms (1) psychotropic drugs OR serotonin uptake inhibitors AND DRESS or (2) psychotropic drugs AND drug reaction (or rash) eosinophilia systemic syndrome, and all article abstracts were screened for inclusion and exclusion criteria by 3 reviewers. Two independent reviewers examined the full text of 163 articles, of which 96 (25 original articles, 12 review articles, 55 case reports, and 4 letters to the editor) were included in the systematic review. We identified 1072 cases of psychotropic drug-induced DRESS, with carbamazepine, lamotrigine, phenytoin, valproate, and phenobarbital being the most implicated drugs. Based on our review of the literature, we outline management principles that include prompt withdrawal of the causative drug, hospitalization, corticosteroid therapy, and novel treatments, including intravenous immunoglobulin, cyclophosphamide, and cyclosporine, for corticosteroid-resistant DRESS. Finally, we outline strategies for treating comorbid psychiatric illness after a DRESS reaction to the psychotropic medication. Copyright © 2016 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

Virtual Screening of compounds to 1-deoxy-Dxylulose 5-phosphate reductoisomerase (DXR) from Plasmodium falciparum.

PubMed

Chaudhary, Kamal Kumar; Prasad, C V S Siva

2014-01-01

The 1-deoxy-D-xylulose 5-phosphate reductoisomerase (DXR) protein (Gen Bank ID AAN37254.1) from Plasmodium falciparum is a potential drug target. Therefore, it is of interest to screen DXR against a virtual library of compounds (at the ZINC database) for potential binders as possible inhibitors. This exercise helped to choose 10 top ranking molecules with ZINC00200163 [N-(2,2di methoxy ethyl)-6-methyl-2, 3, 4, 9-tetrahydro-1H-carbazol-1-amine] a having good fit (-6.43 KJ/mol binding energy) with the target protein. Thus, ZINC00200163 is identified as a potential molecule for further comprehensive characterization and in-depth analysis.

Lattice energy calculation - A quick tool for screening of cocrystals and estimation of relative solubility. Case of flavonoids

NASA Astrophysics Data System (ADS)

Kuleshova, L. N.; Hofmann, D. W. M.; Boese, R.

2013-03-01

Cocrystals (or multicomponent crystals) have physico-chemical properties that are different from crystals of pure components. This is significant in drug development, since the desired properties, e.g. solubility, stability and bioavailability, can be tailored by binding two substances into a single crystal without chemical modification of an active component. Here, the FLEXCRYST program suite, implemented with a data mining force field, was used to estimate the relative stability and, consequently, the relative solubility of cocrystals of flavonoids vs their pure crystals, stored in the Cambridge Structural Database. The considerable potency of this approach for in silico screening of cocrystals, as well as their relative solubility, was demonstrated.

Using Chemoinformatics, Bioinformatics, and Bioassay to Predict and Explain the Antibacterial Activity of Nonantibiotic Food and Drug Administration Drugs.

PubMed

Kahlous, Nour Aldin; Bawarish, Muhammad Al Mohdi; Sarhan, Muhammad Arabi; Küpper, Manfred; Hasaba, Ali; Rajab, Mazen

2017-04-01

Discovering of new and effective antibiotics is a major issue facing scientists today. Luckily, the development of computer science offers new methods to overcome this issue. In this study, a set of computer software was used to predict the antibacterial activity of nonantibiotic Food and Drug Administration (FDA)-approved drugs, and to explain their action by possible binding to well-known bacterial protein targets, along with testing their antibacterial activity against Gram-positive and Gram-negative bacteria. A three-dimensional virtual screening method that relies on chemical and shape similarity was applied using rapid overlay of chemical structures (ROCS) software to select candidate compounds from the FDA-approved drugs database that share similarity with 17 known antibiotics. Then, to check their antibacterial activity, disk diffusion test was applied on Staphylococcus aureus and Escherichia coli. Finally, a protein docking method was applied using HYBRID software to predict the binding of the active candidate to the target receptor of its similar antibiotic. Of the 1,991 drugs that were screened, 34 had been selected and among them 10 drugs showed antibacterial activity, whereby drotaverine and metoclopramide activities were without precedent reports. Furthermore, the docking process predicted that diclofenac, drotaverine, (S)-flurbiprofen, (S)-ibuprofen, and indomethacin could bind to the protein target of their similar antibiotics. Nevertheless, their antibacterial activities are weak compared with those of their similar antibiotics, which can be potentiated further by performing chemical modifications on their structure.

An exploratory study of mental health and HIV risk behavior among drug-using rural women in jail.

PubMed

Staton-Tindall, Michele; Harp, Kathi L H; Minieri, Alexandra; Oser, Carrie; Webster, J Matthew; Havens, Jennifer; Leukefeld, Carl

2015-03-01

Rural women, particularly those in the criminal justice system, are at risk for HIV related to the increasing prevalence of injection drug use as well as limited services. Research on HIV risk correlates, including drug use and mental health, has primarily focused on urban women incarcerated in prisons. The purpose of this exploratory study is to examine dual HIV risk by 3 different mental health problems (depression, anxiety, and posttraumatic stress disorder [PTSD]) among drug-using women in rural jails. This study involved random selection, screening, and face-to-face interviews with 136 women in 1 Appalachian state. Analyses focused on the relationship between mental health and HIV risk. Nearly 80% of women self-reported symptoms of depression, and more than 60% endorsed symptoms consistent with anxiety and PTSD symptoms. Mental health significantly correlated with severity of certain types of drug use, as well as risky sexual activity. In addition, for women experiencing anxiety and PTSD, injection drug use moderated the relationship between mental health and risky sexual activity. Based on these rates of drug use, mental health problems, and the emergence of injection drug use in rural Appalachia, the need to explore the relationships between these issues among vulnerable and understudied populations, such as rural women, is critical. Because of service limitations in rural communities, criminal justice venues such as jails provide opportune settings for screening, assessment, and intervention for drug use, mental health, and HIV education and prevention. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Novel inhibitors to Taenia solium Cu/Zn superoxide dismutase identified by virtual screening

NASA Astrophysics Data System (ADS)

García-Gutiérrez, P.; Landa-Piedra, A.; Rodríguez-Romero, A.; Parra-Unda, R.; Rojo-Domínguez, A.

2011-12-01

We describe in this work a successful virtual screening and experimental testing aimed to the identification of novel inhibitors of superoxide dismutase of the worm Taenia solium ( TsCu/Zn-SOD), a human parasite. Conformers from LeadQuest® database of drug-like compounds were selected and then docked on the surface of TsCu/Zn-SOD. Results were screened looking for ligand contacts with receptor side-chains not conserved in the human homologue, with a subsequent development of a score optimization by a set of energy minimization steps, aimed to identify lead compounds for in vitro experiments. Six out of fifty experimentally tested compounds showed μM inhibitory activity toward TsCu/Zn-SOD. Two of them showed species selectivity since did not inhibit the homologous human enzyme when assayed in vitro.

TB Mobile: a mobile app for anti-tuberculosis molecules with known targets

PubMed Central

2013-01-01

Background An increasing number of researchers are focused on strategies for developing inhibitors of Mycobacterium tuberculosis (Mtb) as tuberculosis (TB) drugs. Results In order to learn from prior work we have collated information on molecules screened versus Mtb and their targets which has been made available in the Collaborative Drug Discovery (CDD) database. This dataset contains published data on target, essentiality, links to PubMed, TBDB, TBCyc (which provides a pathway-based visualization of the entire cellular biochemical network) and human homolog information. The development of mobile cheminformatics apps could lower the barrier to drug discovery and promote collaboration. Therefore we have used this set of over 700 molecules screened versus Mtb and their targets to create a free mobile app (TB Mobile) that displays molecule structures and links to the bioinformatics data. By input of a molecular structures and performing a similarity search within the app we can infer potential targets or search by targets to retrieve compounds known to be active. Conclusions TB Mobile may assist researchers as part of their workflow in identifying potential targets for hits generated from phenotypic screening and in prioritizing them for further follow-up. The app is designed to lower the barriers to accessing this information, so that all researchers with an interest in combatting this deadly disease can use it freely to the benefit of their own efforts. PMID:23497706

Application of 3D Zernike descriptors to shape-based ligand similarity searching.

PubMed

Venkatraman, Vishwesh; Chakravarthy, Padmasini Ramji; Kihara, Daisuke

2009-12-17

The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD.

Application of 3D Zernike descriptors to shape-based ligand similarity searching

PubMed Central

2009-01-01

Background The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability. Conclusion The 3DZD has unique ability for fast comparison of three-dimensional shape of compounds. Examples analyzed illustrate the advantages and the room for improvements for the 3DZD. PMID:20150998

Testing the effects of brief intervention in primary care for problem drug use in a randomized controlled trial: rationale, design, and methods.

PubMed

Krupski, Antoinette; Joesch, Jutta M; Dunn, Chris; Donovan, Dennis; Bumgardner, Kristin; Lord, Sarah Peregrine; Ries, Richard; Roy-Byrne, Peter

2012-12-14

A substantial body of research has established the effectiveness of brief interventions for problem alcohol use. Following these studies, national dissemination projects of screening, brief intervention (BI), and referral to treatment (SBIRT) for alcohol and drugs have been implemented on a widespread scale in multiple states despite little existing evidence for the impact of BI on drug use for non-treatment seekers. This article describes the design of a study testing the impact of SBIRT on individuals with drug problems, its contributions to the existing literature, and its potential to inform drug policy. The study is a randomized controlled trial of an SBIRT intervention carried out in a primary care setting within a safety net system of care. Approximately 1,000 individuals presenting for scheduled medical care at one of seven designated primary care clinics who endorse problematic drug use when screened are randomized in a 1:1 ratio to BI versus enhanced care as usual (ECAU). Individuals in both groups are reassessed at 3, 6, 9, and 12 months after baseline. Self-reported drug use and other psychosocial measures collected at each data point are supplemented by urine analysis and public health-related data from administrative databases. This study will contribute to the existing literature by providing evidence for the impact of BI on problem drug use based on a broad range of measures including self-reported drug use, urine analysis, admission to drug abuse treatment, and changes in utilization and costs of health care services, arrests, and death with the intent of informing policy and program planning for problem drug use at the local, state, and national levels. ClinicalTrials.gov NCT00877331.

Using computer-aided drug design and medicinal chemistry strategies in the fight against diabetes.

PubMed

Semighini, Evandro P; Resende, Jonathan A; de Andrade, Peterson; Morais, Pedro A B; Carvalho, Ivone; Taft, Carlton A; Silva, Carlos H T P

2011-04-01

The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics, ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.

DrugBank: a knowledgebase for drugs, drug actions and drug targets

PubMed Central

Wishart, David S.; Knox, Craig; Guo, An Chi; Cheng, Dean; Shrivastava, Savita; Tzur, Dan; Gautam, Bijaya; Hassanali, Murtaza

2008-01-01

DrugBank is a richly annotated resource that combines detailed drug data with comprehensive drug target and drug action information. Since its first release in 2006, DrugBank has been widely used to facilitate in silico drug target discovery, drug design, drug docking or screening, drug metabolism prediction, drug interaction prediction and general pharmaceutical education. The latest version of DrugBank (release 2.0) has been expanded significantly over the previous release. With ∼4900 drug entries, it now contains 60% more FDA-approved small molecule and biotech drugs including 10% more ‘experimental’ drugs. Significantly, more protein target data has also been added to the database, with the latest version of DrugBank containing three times as many non-redundant protein or drug target sequences as before (1565 versus 524). Each DrugCard entry now contains more than 100 data fields with half of the information being devoted to drug/chemical data and the other half devoted to pharmacological, pharmacogenomic and molecular biological data. A number of new data fields, including food–drug interactions, drug–drug interactions and experimental ADME data have been added in response to numerous user requests. DrugBank has also significantly improved the power and simplicity of its structure query and text query searches. DrugBank is available at http://www.drugbank.ca PMID:18048412

A comprehensive review of the psychometric properties of the Drug Abuse Screening Test.

PubMed

Yudko, Errol; Lozhkina, Olga; Fouts, Adriana

2007-03-01

This article reviews the reliability and the validity of the (10-, 20-, and 28-item) Drug Abuse Screening Test (DAST). The reliability and the validity of the adolescent version of the DAST are also reviewed. An extensive literature review was conducted using the Medline and Psychinfo databases from the years 1982 to 2005. All articles that addressed the reliability and the validity of the DAST were examined. Publications in which the DAST was used as a screening tool but had no data on its psychometric properties were not included. Descriptive information about each version of the test, as well as discussion of the empirical literature that has explored measures of the reliability and the validity of the DAST, has been included. The DAST tended to have moderate to high levels of test-retest, interitem, and item-total reliabilities. The DAST also tended to have moderate to high levels of validity, sensitivity, and specificity. In general, all versions of the DAST yield satisfactory measures of reliability and validity for use as clinical or research tools. Furthermore, these tests are easy to administer and have been used in a variety of populations.

Analysis and hit filtering of a very large library of compounds screened against Mycobacterium tuberculosis.

PubMed

Ekins, Sean; Kaneko, Takushi; Lipinski, Christopher A; Bradford, Justin; Dole, Krishna; Spektor, Anna; Gregory, Kellan; Blondeau, David; Ernst, Sylvia; Yang, Jeremy; Goncharoff, Nicko; Hohman, Moses M; Bunin, Barry A

2010-11-01

There is an urgent need for new drugs against tuberculosis which annually claims 1.7-1.8 million lives. One approach to identify potential leads is to screen in vitro small molecules against Mycobacterium tuberculosis (Mtb). Until recently there was no central repository to collect information on compounds screened. Consequently, it has been difficult to analyze molecular properties of compounds that inhibit the growth of Mtb in vitro. We have collected data from publically available sources on over 300 000 small molecules deposited in the Collaborative Drug Discovery TB Database. A cheminformatics analysis on these compounds indicates that inhibitors of the growth of Mtb have statistically higher mean logP, rule of 5 alerts, while also having lower HBD count, atom count and lower PSA (ChemAxon descriptors), compared to compounds that are classed as inactive. Additionally, Bayesian models for selecting Mtb active compounds were evaluated with over 100 000 compounds and, they demonstrated 10 fold enrichment over random for the top ranked 600 compounds. This represents a promising approach for finding compounds active against Mtb in whole cells screened under the same in vitro conditions. Various sets of Mtb hit molecules were also examined by various filtering rules used widely in the pharmaceutical industry to identify compounds with potentially reactive moieties. We found differences between the number of compounds flagged by these rules in Mtb datasets, malaria hits, FDA approved drugs and antibiotics. Combining these approaches may enable selection of compounds with increased probability of inhibition of whole cell Mtb activity.

Identifying depression severity risk factors in persons with traumatic spinal cord injury.

PubMed

Williams, Ryan T; Wilson, Catherine S; Heinemann, Allen W; Lazowski, Linda E; Fann, Jesse R; Bombardier, Charles H

2014-02-01

Examine the relationship between demographic characteristics, health-, and injury-related characteristics, and substance misuse across multiple levels of depression severity. 204 persons with traumatic spinal cord injury (SCI) volunteered as part of screening efforts for a randomized controlled trial of venlafaxine extended release for major depressive disorder (MDD). Instruments included the Patient Health Questionnaire-9 (PHQ-9) depression scale, the Alcohol Use Disorders Identification Test (AUDIT), and the Substance Abuse in Vocational Rehabilitation-Screener (SAVR-S), which contains 3 subscales: drug misuse, alcohol misuse, and a subtle items scale. Each of the SAVR-S subscales contributes to an overall substance use disorder (SUD) outcome. Three proportional odds models were specified, varying the substance misuse measure included in each model. 44% individuals had no depression symptoms, 31% had mild symptoms, 16% had moderate symptoms, 6% had moderately severe symptoms, and 3% had severe depression symptoms. Alcohol misuse, as indicated by the AUDIT and the SAVR-S drug misuse subscale scores were significant predictors of depression symptom severity. The SAVR-S substance use disorder (SUD) screening outcome was the most predictive variable. Level of education was only significantly predictive of depression severity in the model using the AUDIT alcohol misuse indicator. Likely SUD as measured by the SAVR-S was most predictive of depression symptom severity in this sample of persons with traumatic SCI. Drug and alcohol screening are important for identifying individuals at risk for depression, but screening for both may be optimal. Further research is needed on risk and protective factors for depression, including psychosocial characteristics. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Detection and identification of drugs and toxicants in human body fluids by liquid chromatography-tandem mass spectrometry under data-dependent acquisition control and automated database search.

PubMed

Oberacher, Herbert; Schubert, Birthe; Libiseller, Kathrin; Schweissgut, Anna

2013-04-03

Systematic toxicological analysis (STA) is aimed at detecting and identifying all substances of toxicological relevance (i.e. drugs, drugs of abuse, poisons and/or their metabolites) in biological material. Particularly, gas chromatography-mass spectrometry (GC/MS) represents a competent and commonly applied screening and confirmation tool. Herein, we present an untargeted liquid chromatography-tandem mass spectrometry (LC/MS/MS) assay aimed to complement existing GC/MS screening for the detection and identification of drugs in blood, plasma and urine samples. Solid-phase extraction was accomplished on mixed-mode cartridges. LC was based on gradient elution in a miniaturized C18 column. High resolution electrospray ionization-MS/MS in positive ion mode with data-dependent acquisition control was used to generate tandem mass spectral information that enabled compound identification via automated library search in the "Wiley Registry of Tandem Mass Spectral Data, MSforID". Fitness of the developed LC/MS/MS method for application in STA in terms of selectivity, detection capability and reliability of identification (sensitivity/specificity) was demonstrated with blank samples, certified reference materials, proficiency test samples, and authentic casework samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Mitochondrial Targets for Pharmacological Intervention in Human Disease

PubMed Central

2015-01-01

Over the past several years, mitochondrial dysfunction has been linked to an increasing number of human illnesses, making mitochondrial proteins (MPs) an ever more appealing target for therapeutic intervention. With 20% of the mitochondrial proteome (312 of an estimated 1500 MPs) having known interactions with small molecules, MPs appear to be highly targetable. Yet, despite these targeted proteins functioning in a range of biological processes (including induction of apoptosis, calcium homeostasis, and metabolism), very few of the compounds targeting MPs find clinical use. Recent work has greatly expanded the number of proteins known to localize to the mitochondria and has generated a considerable increase in MP 3D structures available in public databases, allowing experimental screening and in silico prediction of mitochondrial drug targets on an unprecedented scale. Here, we summarize the current literature on clinically active drugs that target MPs, with a focus on how existing drug targets are distributed across biochemical pathways and organelle substructures. Also, we examine current strategies for mitochondrial drug discovery, focusing on genetic, proteomic, and chemogenomic assays, and relevant model systems. As cell models and screening techniques improve, MPs appear poised to emerge as relevant targets for a wide range of complex human diseases, an eventuality that can be expedited through systematic analysis of MP function. PMID:25367773

Indexing Natural Products for Their Potential Anti-Diabetic Activity: Filtering and Mapping Discriminative Physicochemical Properties.

PubMed

Zeidan, Mouhammad; Rayan, Mahmoud; Zeidan, Nuha; Falah, Mizied; Rayan, Anwar

2017-09-17

Diabetes mellitus (DM) poses a major health problem, for which there is an unmet need to develop novel drugs. The application of in silico techniques and optimization algorithms is instrumental to achieving this goal. A set of 97 approved anti-diabetic drugs, representing the active domain, and a set of 2892 natural products, representing the inactive domain, were used to construct predictive models and to index anti-diabetic bioactivity. Our recently-developed approach of 'iterative stochastic elimination' was utilized. This article describes a highly discriminative and robust model, with an area under the curve above 0.96. Using the indexing model and a mix ratio of 1:1000 (active/inactive), 65% of the anti-diabetic drugs in the sample were captured in the top 1% of the screened compounds, compared to 1% in the random model. Some of the natural products that scored highly as potential anti-diabetic drug candidates are disclosed. One of those natural products is caffeine, which is noted in the scientific literature as having the capability to decrease blood glucose levels. The other nine phytochemicals await evaluation in a wet lab for their anti-diabetic activity. The indexing model proposed herein is useful for the virtual screening of large chemical databases and for the construction of anti-diabetes focused libraries.

Screening of phytochemicals against protease activated receptor 1 (PAR1), a promising target for cancer.

PubMed

Kakarala, Kavita Kumari; Jamil, Kaiser

2015-02-01

Drug resistance and drug-associated toxicity are the primary causes for withdrawal of many drugs, although patient recovery is satisfactory in many instances. Interestingly, the use of phytochemicals in the treatment of cancer as an alternative to synthetic drugs comes with a host of advantages; minimum side effects, good human absorption and low toxicity to normal cells. Protease activated receptor 1 (PAR1) has been established as a promising target in many diseases including various cancers. Strong evidences suggest its role in metastasis also. There are no natural compounds known to inhibit its activity, so we aimed to identify phytochemicals with antagonist activity against PAR1. We screened phytochemicals from Naturally Occurring Plant-based Anticancer Compound-Activity-Target database (NPACT, http://crdd.osdd.net/raghava/npact/ ) against PAR1 using virtual screening workflow of Schrödinger software. It analyzes pharmaceutically relevant properties using Qikprop and calculates binding energy using Glide at three accuracy levels (high-throughput virtual screening, standard precision and extra precision). Our study led to the identification of phytochemicals, which showed interaction with at least one experimentally determined active site residue of PAR1, showed no violations to Lipinski's rule of five along with predicted high human absorption. Furthermore, structural interaction fingerprint analysis indicated that the residues H255, D256, E260, S344, V257, L258, L262, Y337 and S344 may play an important role in the hydrogen bond interactions of the phytochemicals screened. Of these residues, H255 and L258 residues were experimentally proved to be important for antagonist binding. The residues Y183, L237, L258, L262, F271, L332, L333, Y337, L340, A349, Y350, A352, and Y353 showed maximum hydrophobic interactions with the phytochemicals screened. The results of this work suggest that phytochemicals Reissantins D, 24,25-dihydro-27-desoxywithaferin A, Isoguaiacin, 20-hydroxy-12-deoxyphorbol angelate, etc. could be potential antagonist of PAR1. However, further experimental studies are necessary to validate their antagonistic activity against PAR1.

Terahertz absorption spectra of commonly used antimalarial drugs

NASA Astrophysics Data System (ADS)

Bawuah, Prince; Zeitler, J. Axel; Ketolainen, Jarkko; Peiponen, Kai-Erik

2018-06-01

Terahertz (THz) spectra from the pure forms [i.e. the active pharmaceutical ingredients (APIs)] of four commonly used antimalarial drugs are reported. The well-defined spectral fingerprints obtained for these APIs in the spectral range of 0.1 THz-3 THz show the sensitivity of the THz time-domain spectroscopic (THz-TDS) method for screening antimalarial drugs. For identification purpose, two commercially available antimalarial tablets were detected. Clear spectral fingerprints of the APIs in the antimalarial tablets were obtained even amidst the several types of excipients present in the tablets. This observation further proves the high sensitivity of the THz techniques in tracking the presence or absence of API in a pharmaceutical tablet. We envisage that the spectral data obtained for these drugs can contribute to a spectroscopic database in the far infrared spectral region and hence support the modelling of THz sensing to differentiate between genuine and counterfeit antimalarial tablets.

Terahertz absorption spectra of commonly used antimalarial drugs

NASA Astrophysics Data System (ADS)

Bawuah, Prince; Zeitler, J. Axel; Ketolainen, Jarkko; Peiponen, Kai-Erik

2018-03-01

Terahertz (THz) spectra from the pure forms [i.e. the active pharmaceutical ingredients (APIs)] of four commonly used antimalarial drugs are reported. The well-defined spectral fingerprints obtained for these APIs in the spectral range of 0.1 THz-3 THz show the sensitivity of the THz time-domain spectroscopic (THz-TDS) method for screening antimalarial drugs. For identification purpose, two commercially available antimalarial tablets were detected. Clear spectral fingerprints of the APIs in the antimalarial tablets were obtained even amidst the several types of excipients present in the tablets. This observation further proves the high sensitivity of the THz techniques in tracking the presence or absence of API in a pharmaceutical tablet. We envisage that the spectral data obtained for these drugs can contribute to a spectroscopic database in the far infrared spectral region and hence support the modelling of THz sensing to differentiate between genuine and counterfeit antimalarial tablets.

[Study on lipid-lowering traditional Chinese medicines based on pharmacophore technology and patent retrieval].

PubMed

Huo, Xiao-qian; He, Yu-su; Qiao, Lian-sheng; Sun, Zhi-yi; Zhang, Yan-ling

2014-12-01

The combined application of statins that inhibit HMG-CoA reductase and fibrates that activate PPAR-α can produce a better lipid-lowering effect than the simple application, but with stronger adverse reactions at the same time. In the treatment of hyperlipidemia, the combined administration of TCMs and HMG-CoA reductase inhibitor in treating hyperlipidemia shows stable efficacy and less adverse reactions, and provides a new option for the combined application of drugs. In this article, the pharmacophore technology was used to search chemical components of TCMs, trace their source herbs, and determine the potential common TCMs that could activate PPAR-α. Because there is no hyperlipidemia-related medication reference in modern TCM classics, to ensure the high safety and efficacy of all selected TCMs, we selected TCMs that are proved to be combined with statins in the World Traditional/Natural Medicine Patent Database, analyzed corresponding drugs in pharmacophore results based on that, and finally obtained common TCMs that can be applied in PPAR-α and combined with statins. Specifically, the pharmacophore model was based on eight receptor-ligand complexes of PPAR-α. The Receptor-Ligand Pharmacophore Generation module in the DS program was used to build the model, optimize with the Screen Library module, and get the best sub-pharmacophore, which consisted of two hydrogen bond acceptor, three hydrophobic groups and 19 excluded volumes, with the identification effectiveness index value N of 2. 82 and the comprehensive evaluation index CAI value of 1. 84. The model was used to screen the TCMD database, hit 5,235 kinds of chemical components and 1 193 natural animals and plants, and finally determine 62 TCMs. Through patent retrieval, we found 38 TCMs; After comparing with the virtual screening results, we finally got seven TCMs.

Analysis of psychoactive substances in water by information dependent acquisition on a hybrid quadrupole time-of-flight mass spectrometer.

PubMed

Andrés-Costa, María Jesús; Andreu, Vicente; Picó, Yolanda

2016-08-26

Emerging drugs of abuse, belonging to many different chemical classes, are attracting users with promises of "legal" highs and easy access via internet. Prevalence of their consumption and abuse through wastewater-based epidemiology can only be realized if a suitable analytical screening procedure exists to detect and quantify them in water. Solid-phase extraction and ultra-high performance liquid chromatography quadrupole time-of-flight-mass spectrometry (UHPLC-QqTOF-MS/MS) was applied for rapid suspect screening as well as for the quantitative determination of 42 illicit drugs and metabolites in water. Using this platform, we were able to identify amphetamines, tryptamines, piperazines, pyrrolidinophenones, arylcyclohexylamines, cocainics, opioids and cannabinoids. Additionally, paracetamol, carbamazepine, ibersartan, valsartan, sulfamethoxazole, terbumeton, diuron, etc. (including degradation products as 3-hydroxy carbamazepine or deethylterbuthylazine) were detected. This method encompasses easy sample preparation and rapid identification of psychoactive drugs against a database that cover more than 2000 compounds that ionized in positive mode, and possibility to identify metabolites and degradation products as well as unknown compounds. The method for river water, influent and effluents samples was fully validated for the target psychoactive substances including assessment of matrix effects (-88-67.8%), recovery (42-115%), precision (<19%) and limits of quantification (1-100ngL(-1)). Method efficiency was thoroughly investigated for a wide range of waste and surface waters. Robust and repeatable functioning of this platform in the screening, identification and quantification of traditional and new psychoactive drugs biomarkers and other water contaminants is demonstrated. Copyright © 2016 Elsevier B.V. All rights reserved.

Comprehensive Urine Drug Screen by Gas Chromatography/Mass Spectrometry (GC/MS).

PubMed

Ramoo, Bheemraj; Funke, Melissa; Frazee, Clint; Garg, Uttam

2016-01-01

Drug screening is an essential component of clinical toxicology laboratory service. Some laboratories use only automated chemistry analyzers for limited screening of drugs of abuse and few other drugs. Other laboratories use a combination of various techniques such as immunoassays, colorimetric tests, and mass spectrometry to provide more detailed comprehensive drug screening. Mass spectrometry, gas or liquid, can screen for hundreds of drugs and is often considered the gold standard for comprehensive drug screening. We describe an efficient and rapid gas chromatography/mass spectrometry (GC/MS) method for comprehensive drug screening in urine which utilizes a liquid-liquid extraction, sample concentration, and analysis by GC/MS.

Novel Design Strategy for Checkpoint Kinase 2 Inhibitors Using Pharmacophore Modeling, Combinatorial Fusion, and Virtual Screening

PubMed Central

Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the BesttrainBesttest and FasttrainFasttest prediction results. The potential inhibitors were selected from NCI database by screening according to BesttrainBesttest + FasttrainFasttest prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study. PMID:24864236

SuperTarget and Matador: resources for exploring drug-target relationships.

PubMed

Günther, Stefan; Kuhn, Michael; Dunkel, Mathias; Campillos, Monica; Senger, Christian; Petsalaki, Evangelia; Ahmed, Jessica; Urdiales, Eduardo Garcia; Gewiess, Andreas; Jensen, Lars Juhl; Schneider, Reinhard; Skoblo, Roman; Russell, Robert B; Bourne, Philip E; Bork, Peer; Preissner, Robert

2008-01-01

The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use query interface enables the user to pose complex queries, for example to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador. SuperTarget and Matador are available at http://insilico.charite.de/supertarget and http://matador.embl.de.

Route to three-dimensional fragments using diversity-oriented synthesis

PubMed Central

Hung, Alvin W.; Ramek, Alex; Wang, Yikai; Kaya, Taner; Wilson, J. Anthony; Clemons, Paul A.; Young, Damian W.

2011-01-01

Fragment-based drug discovery (FBDD) has proven to be an effective means of producing high-quality chemical ligands as starting points for drug-discovery pursuits. The increasing number of clinical candidate drugs developed using FBDD approaches is a testament of the efficacy of this approach. The success of fragment-based methods is highly dependent on the identity of the fragment library used for screening. The vast majority of FBDD has centered on the use of sp2-rich aromatic compounds. An expanded set of fragments that possess more 3D character would provide access to a larger chemical space of fragments than those currently used. Diversity-oriented synthesis (DOS) aims to efficiently generate a set of molecules diverse in skeletal and stereochemical properties. Molecules derived from DOS have also displayed significant success in the modulation of function of various “difficult” targets. Herein, we describe the application of DOS toward the construction of a unique set of fragments containing highly sp3-rich skeletons for fragment-based screening. Using cheminformatic analysis, we quantified the shapes and physical properties of the new 3D fragments and compared them with a database containing known fragment-like molecules. PMID:21482811

Route to three-dimensional fragments using diversity-oriented synthesis.

PubMed

Hung, Alvin W; Ramek, Alex; Wang, Yikai; Kaya, Taner; Wilson, J Anthony; Clemons, Paul A; Young, Damian W

2011-04-26

Fragment-based drug discovery (FBDD) has proven to be an effective means of producing high-quality chemical ligands as starting points for drug-discovery pursuits. The increasing number of clinical candidate drugs developed using FBDD approaches is a testament of the efficacy of this approach. The success of fragment-based methods is highly dependent on the identity of the fragment library used for screening. The vast majority of FBDD has centered on the use of sp(2)-rich aromatic compounds. An expanded set of fragments that possess more 3D character would provide access to a larger chemical space of fragments than those currently used. Diversity-oriented synthesis (DOS) aims to efficiently generate a set of molecules diverse in skeletal and stereochemical properties. Molecules derived from DOS have also displayed significant success in the modulation of function of various "difficult" targets. Herein, we describe the application of DOS toward the construction of a unique set of fragments containing highly sp(3)-rich skeletons for fragment-based screening. Using cheminformatic analysis, we quantified the shapes and physical properties of the new 3D fragments and compared them with a database containing known fragment-like molecules.

Identification of potential hit compounds for Dengue virus NS2B/NS3 protease inhibitors by combining virtual screening and binding free energy calculations.

PubMed

Wichapong, K; Nueangaudom, A; Pianwanit, S; Sippl, W; Kokpol, S

2013-09-01

Dengue virus (DV) infections are a serious public health problem and there is currently no vaccine or drug treatment. NS2B/NS3 protease, an essential enzyme for viral replication, is one of the promising targets in the search for drugs against DV. In this research work, virtual screening (VS) was carried out on four multi-conformational databases using several criteria. Firstly, molecular dynamics simulations of the NS2B/NS3 protease and four known inhibitors, which reveal an importance of both electrostatic and van der Waals interactions in stabilizing the ligand-enzyme interaction, were used to generate three different pharmacophore models (a structure-based, a static and a dynamic). Subsequently, these three models were employed for pharmacophore search in the VS. Secondly, compounds passing the first criterion were further reduced using the Lipinski's rule of five to keep only compounds with drug-like properties. Thirdly, molecular docking calculations were performed to remove compounds with unsuitable ligand-enzyme interactions. Finally, binding free energy of each compound was calculated. Compounds having better energy than the known inhibitors were selected and thus 20 potential hits were obtained.

Virtual screening of potential inhibitors from TCM for the CPSF30 binding site on the NS1A protein of influenza A virus.

PubMed

Ai, Haixin; Zhang, Li; Chang, Alan K; Wei, Hongyun; Che, Yuchen; Liu, Hongsheng

2014-03-01

Inhibition of CPSF30 function by the effector domain of influenza A virus of non-structural protein 1 (NS1A) protein plays a critical role in the suppression of host key antiviral response. The CPSF30-binding site of NS1A appears to be a very attractive target for the development of new drugs against influenza A virus. In this study, structure-based molecular docking was utilized to screen more than 30,000 compounds from a Traditional Chinese Medicine (TCM) database. Four drug-like compounds were selected as potential inhibitors for the CPSF30-binding site of NS1A. Docking conformation analysis results showed that these potential inhibitors could bind to the CPSF30-binding site with strong hydrophobic interactions and weak hydrogen bonds. Molecular dynamics simulations and MM-PBSA calculations suggested that two of the inhibitors, compounds 32056 and 31674, could stably bind to the CPSF30-binding site with high binding free energy. These two compounds could be modified to achieve higher binding affinity, so that they may be used as potential leads in the development of new anti-influenza drugs.

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2011-07-06

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Version 1.00 programmer`s tools used in constructing the INEL RML/analytical radiochemistry sample tracking database and its user interface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Femec, D.A.

This report describes two code-generating tools used to speed design and implementation of relational databases and user interfaces: CREATE-SCHEMA and BUILD-SCREEN. CREATE-SCHEMA produces the SQL commands that actually create and define the database. BUILD-SCREEN takes templates for data entry screens and generates the screen management system routine calls to display the desired screen. Both tools also generate the related FORTRAN declaration statements and precompiled SQL calls. Included with this report is the source code for a number of FORTRAN routines and functions used by the user interface. This code is broadly applicable to a number of different databases.

[Method of traditional Chinese medicine formula design based on 3D-database pharmacophore search and patent retrieval].

PubMed

He, Yu-su; Sun, Zhi-yi; Zhang, Yan-ling

2014-11-01

By using the pharmacophore model of mineralocorticoid receptor antagonists as a starting point, the experiment stud- ies the method of traditional Chinese medicine formula design for anti-hypertensive. Pharmacophore models were generated by 3D-QSAR pharmacophore (Hypogen) program of the DS3.5, based on the training set composed of 33 mineralocorticoid receptor antagonists. The best pharmacophore model consisted of two Hydrogen-bond acceptors, three Hydrophobic and four excluded volumes. Its correlation coefficient of training set and test set, N, and CAI value were 0.9534, 0.6748, 2.878, and 1.119. According to the database screening, 1700 active compounds from 86 source plant were obtained. Because of lacking of available anti-hypertensive medi cation strategy in traditional theory, this article takes advantage of patent retrieval in world traditional medicine patent database, in order to design drug formula. Finally, two formulae was obtained for antihypertensive.

Identification of DNA primase inhibitors via a combined fragment-based and virtual screening

NASA Astrophysics Data System (ADS)

Ilic, Stefan; Akabayov, Sabine R.; Arthanari, Haribabu; Wagner, Gerhard; Richardson, Charles C.; Akabayov, Barak

2016-11-01

The structural differences between bacterial and human primases render the former an excellent target for drug design. Here we describe a technique for selecting small molecule inhibitors of the activity of T7 DNA primase, an ideal model for bacterial primases due to their common structural and functional features. Using NMR screening, fragment molecules that bind T7 primase were identified and then exploited in virtual filtration to select larger molecules from the ZINC database. The molecules were docked to the primase active site using the available primase crystal structure and ranked based on their predicted binding energies to identify the best candidates for functional and structural investigations. Biochemical assays revealed that some of the molecules inhibit T7 primase-dependent DNA replication. The binding mechanism was delineated via NMR spectroscopy. Our approach, which combines fragment based and virtual screening, is rapid and cost effective and can be applied to other targets.

Target-similarity search using Plasmodium falciparum proteome identifies approved drugs with anti-malarial activity and their possible targets

PubMed Central

Akala, Hoseah M.; Macharia, Rosaline W.; Juma, Dennis W.; Cheruiyot, Agnes C.; Andagalu, Ben; Brown, Mathew L.; El-Shemy, Hany A.; Nyanjom, Steven G.

2017-01-01

Malaria causes about half a million deaths annually, with Plasmodium falciparum being responsible for 90% of all the cases. Recent reports on artemisinin resistance in Southeast Asia warrant urgent discovery of novel drugs for the treatment of malaria. However, most bioactive compounds fail to progress to treatments due to safety concerns. Drug repositioning offers an alternative strategy where drugs that have already been approved as safe for other diseases could be used to treat malaria. This study screened approved drugs for antimalarial activity using an in silico chemogenomics approach prior to in vitro verification. All the P. falciparum proteins sequences available in NCBI RefSeq were mined and used to perform a similarity search against DrugBank, TTD and STITCH databases to identify similar putative drug targets. Druggability indices of the potential P. falciparum drug targets were obtained from TDR targets database. Functional amino acid residues of the drug targets were determined using ConSurf server which was used to fine tune the similarity search. This study predicted 133 approved drugs that could target 34 P. falciparum proteins. A literature search done at PubMed and Google Scholar showed 105 out of the 133 drugs to have been previously tested against malaria, with most showing activity. For further validation, drug susceptibility assays using SYBR Green I method were done on a representative group of 10 predicted drugs, eight of which did show activity against P. falciparum 3D7 clone. Seven had IC50 values ranging from 1 μM to 50 μM. This study also suggests drug-target association and hence possible mechanisms of action of drugs that did show antiplasmodial activity. The study results validate the use of proteome-wide target similarity approach in identifying approved drugs with activity against P. falciparum and could be adapted for other pathogens. PMID:29088219

Improving database enrichment through ensemble docking

NASA Astrophysics Data System (ADS)

Rao, Shashidhar; Sanschagrin, Paul C.; Greenwood, Jeremy R.; Repasky, Matthew P.; Sherman, Woody; Farid, Ramy

2008-09-01

While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.

DG-AMMOS: a new tool to generate 3d conformation of small molecules using distance geometry and automated molecular mechanics optimization for in silico screening.

PubMed

Lagorce, David; Pencheva, Tania; Villoutreix, Bruno O; Miteva, Maria A

2009-11-13

Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats. Here, we describe the new open source program DG-AMMOS which allows the generation of the 3D conformation of small molecules using Distance Geometry and their energy minimization via Automated Molecular Mechanics Optimization. The program is validated on the Astex dataset, the ChemBridge Diversity database and on a number of small molecules with known crystal structures extracted from the Cambridge Structural Database. A comparison with the free program Balloon and the well-known commercial program Omega generating the 3D of small molecules is carried out. The results show that the new free program DG-AMMOS is a very efficient 3D structure generator engine. DG-AMMOS provides fast, automated and reliable access to the generation of 3D conformation of small molecules and facilitates the preparation of a compound collection prior to high-throughput virtual screening computations. The validation of DG-AMMOS on several different datasets proves that generated structures are generally of equal quality or sometimes better than structures obtained by other tested methods.

Identification of novel malarial cysteine protease inhibitors using structure-based virtual screening of a focused cysteine protease inhibitor library.

PubMed

Shah, Falgun; Mukherjee, Prasenjit; Gut, Jiri; Legac, Jennifer; Rosenthal, Philip J; Tekwani, Babu L; Avery, Mitchell A

2011-04-25

Malaria, in particular that caused by Plasmodium falciparum , is prevalent across the tropics, and its medicinal control is limited by widespread drug resistance. Cysteine proteases of P. falciparum , falcipain-2 (FP-2) and falcipain-3 (FP-3), are major hemoglobinases, validated as potential antimalarial drug targets. Structure-based virtual screening of a focused cysteine protease inhibitor library built with soft rather than hard electrophiles was performed against an X-ray crystal structure of FP-2 using the Glide docking program. An enrichment study was performed to select a suitable scoring function and to retrieve potential candidates against FP-2 from a large chemical database. Biological evaluation of 50 selected compounds identified 21 diverse nonpeptidic inhibitors of FP-2 with a hit rate of 42%. Atomic Fukui indices were used to predict the most electrophilic center and its electrophilicity in the identified hits. Comparison of predicted electrophilicity of electrophiles in identified hits with those in known irreversible inhibitors suggested the soft-nature of electrophiles in the selected target compounds. The present study highlights the importance of focused libraries and enrichment studies in structure-based virtual screening. In addition, few compounds were screened against homologous human cysteine proteases for selectivity analysis. Further evaluation of structure-activity relationships around these nonpeptidic scaffolds could help in the development of selective leads for antimalarial chemotherapy.

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Prediction of anti-cancer drug response by kernelized multi-task learning.

PubMed

Tan, Mehmet

2016-10-01

Chemotherapy or targeted therapy are two of the main treatment options for many types of cancer. Due to the heterogeneous nature of cancer, the success of the therapeutic agents differs among patients. In this sense, determination of chemotherapeutic response of the malign cells is essential for establishing a personalized treatment protocol and designing new drugs. With the recent technological advances in producing large amounts of pharmacogenomic data, in silico methods have become important tools to achieve this aim. Data produced by using cancer cell lines provide a test bed for machine learning algorithms that try to predict the response of cancer cells to different agents. The potential use of these algorithms in drug discovery/repositioning and personalized treatments motivated us in this study to work on predicting drug response by exploiting the recent pharmacogenomic databases. We aim to improve the prediction of drug response of cancer cell lines. We propose to use a method that employs multi-task learning to improve learning by transfer, and kernels to extract non-linear relationships to predict drug response. The method outperforms three state-of-the-art algorithms on three anti-cancer drug screen datasets. We achieved a mean squared error of 3.305 and 0.501 on two different large scale screen data sets. On a recent challenge dataset, we obtained an error of 0.556. We report the methodological comparison results as well as the performance of the proposed algorithm on each single drug. The results show that the proposed method is a strong candidate to predict drug response of cancer cell lines in silico for pre-clinical studies. The source code of the algorithm and data used can be obtained from http://mtan.etu.edu.tr/Supplementary/kMTrace/. Copyright © 2016 Elsevier B.V. All rights reserved.

ChemoPy: freely available python package for computational biology and chemoinformatics.

PubMed

Cao, Dong-Sheng; Xu, Qing-Song; Hu, Qian-Nan; Liang, Yi-Zeng

2013-04-15

Molecular representation for small molecules has been routinely used in QSAR/SAR, virtual screening, database search, ranking, drug ADME/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently. The python package, ChemoPy, is freely available via http://code.google.com/p/pychem/downloads/list, and it runs on Linux and MS-Windows. Supplementary data are available at Bioinformatics online.

Short tandem repeat DNA typing provides an international reference standard for authentication of human cell lines.

PubMed

Dirks, Wilhelm Gerhard; Faehnrich, Silke; Estella, Isabelle Annick Janine; Drexler, Hans Guenter

2005-01-01

Cell lines have wide applications as model systems in the medical and pharmaceutical industry. Much drug and chemical testing is now first carried out exhaustively on in vitro systems, reducing the need for complicated and invasive animal experiments. The basis for any research, development or production program involving cell lines is the choice of an authentic cell line. Microsatellites in the human genome that harbour short tandem repeat (STR) DNA markers allow individualisation of established cell lines at the DNA level. Fluorescence polymerase chain reaction amplification of eight highly polymorphic microsatellite STR loci plus gender determination was found to be the best tool to screen the uniqueness of DNA profiles in a fingerprint database. Our results demonstrate that cross-contamination and misidentification remain chronic problems in the use of human continuous cell lines. The combination of rapidly generated DNA types based on single-locus STR and their authentication or individualisation by screening the fingerprint database constitutes a highly reliable and robust method for the identification and verification of cell lines.

vSDC: a method to improve early recognition in virtual screening when limited experimental resources are available.

PubMed

Chaput, Ludovic; Martinez-Sanz, Juan; Quiniou, Eric; Rigolet, Pascal; Saettel, Nicolas; Mouawad, Liliane

2016-01-01

In drug design, one may be confronted to the problem of finding hits for targets for which no small inhibiting molecules are known and only low-throughput experiments are available (like ITC or NMR studies), two common difficulties encountered in a typical academic setting. Using a virtual screening strategy like docking can alleviate some of the problems and save a considerable amount of time by selecting only top-ranking molecules, but only if the method is very efficient, i.e. when a good proportion of actives are found in the 1-10 % best ranked molecules. The use of several programs (in our study, Gold, Surflex, FlexX and Glide were considered) shows a divergence of the results, which presents a difficulty in guiding the experiments. To overcome this divergence and increase the yield of the virtual screening, we created the standard deviation consensus (SDC) and variable SDC (vSDC) methods, consisting of the intersection of molecule sets from several virtual screening programs, based on the standard deviations of their ranking distributions. SDC allowed us to find hits for two new protein targets by testing only 9 and 11 small molecules from a chemical library of circa 15,000 compounds. Furthermore, vSDC, when applied to the 102 proteins of the DUD-E benchmarking database, succeeded in finding more hits than any of the four isolated programs for 13-60 % of the targets. In addition, when only 10 molecules of each of the 102 chemical libraries were considered, vSDC performed better in the number of hits found, with an improvement of 6-24 % over the 10 best-ranked molecules given by the individual docking programs.Graphical abstractIn drug design, for a given target and a given chemical library, the results obtained with different virtual screening programs are divergent. So how to rationally guide the experimental tests, especially when only a few number of experiments can be made? The variable Standard Deviation Consensus (vSDC) method was developed to answer this issue. Left panel the vSDC principle consists of intersecting molecule sets, chosen on the basis of the standard deviations of their ranking distributions, obtained from various virtual screening programs. In this study Glide, Gold, FlexX and Surflex were used and tested on the 102 targets of the DUD-E database. Right panel Comparison of the average percentage of hits found with vSDC and each of the four programs, when only 10 molecules from each of the 102 chemical libraries of the DUD-E database were considered. On average, vSDC was capable of finding 38 % of the findable hits, against 34 % for Glide, 32 % for Gold, 16 % for FlexX and 14 % for Surflex, showing that with vSDC, it was possible to overcome the unpredictability of the virtual screening results and to improve them.

Searching for new leads to treat epilepsy. Target-based virtual screening for the discovery of anticonvulsant agents.

PubMed

Palestro, Pablo; Enrique, Nicolas; Goicoechea, Sofia; Villalba, María Luisa; Sabatier, Laureano Leonel; Martin, Pedro; Milesi, Veronica; Bruno-Blanch, Luis E; Gavernet, Luciana

2018-06-05

The purpose of this investigation is to contribute to the development of new anticonvulsant drugs to treat patients with refractory epilepsy. We applied a virtual screening protocol that involved the search into molecular databases of new compounds and known drugs to find small molecules that interact with the open conformation of the Nav1.2 pore. As the 3D structure of human Nav1.2 is not available, we first assembled 3D models of the target, in closed and open conformations. After the virtual screening, the resulting candidates were submitted to a second virtual filter, to find compounds with better chances of being effective for the treatment of P-glycoprotein (P-gp) mediated resistant epilepsy. Again, we built a model of the 3D structure of human P-gp and we validated the docking methodology selected to propose the best candidates, which were experimentally tested on Nav1.2 channels by patch clamp techniques and in vivo by MES-test. Patch clamp studies allowed us to corroborate that our candidates, drugs used for the treatment of other pathologies like Ciprofloxacin, Losartan and Valsartan, exhibit inhibitory effects on Nav1.2 channel activity. Additionally, a compound synthesized in our lab, N,N´-diphenethylsulfamide, interacts with the target and also triggers significant Na1.2 channel inhibitory action. Finally, in-vivo studies confirmed the anticonvulsant action of Valsartan, Ciprofloxacin and N.N´-diphenethylsulfamide.

Drug-Path: a database for drug-induced pathways

PubMed Central

Zeng, Hui; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. Database URL: http://www.cuilab.cn/drugpath PMID:26130661

Identification of repaglinide as a therapeutic drug for glioblastoma multiforme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, Zui Xuan; Chen, Ruo Qiao; Hu, Dian Xing

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with a median survival time of only 14 months after treatment. It is urgent to find new therapeutic drugs that increase survival time of GBM patients. To achieve this goal, we screened differentially expressed genes between long-term and short-term survived GBM patients from Gene Expression Omnibus database and found gene expression signature for the long-term survived GBM patients. The signaling networks of all those differentially expressed genes converged to protein binding, extracellular matrix and tissue development as revealed in BiNGO and Cytoscape. Drug repositioning in Connectivity Map by using the genemore » expression signature identified repaglinide, a first-line drug for diabetes mellitus, as the most promising novel drug for GBM. In vitro experiments demonstrated that repaglinide significantly inhibited the proliferation and migration of human GBM cells. In vivo experiments demonstrated that repaglinide prominently prolonged the median survival time of mice bearing orthotopic glioma. Mechanistically, repaglinide significantly reduced Bcl-2, Beclin-1 and PD-L1 expression in glioma tissues, indicating that repaglinide may exert its anti-cancer effects via apoptotic, autophagic and immune checkpoint signaling. Taken together, repaglinide is likely to be an effective drug to prolong life span of GBM patients. - Highlights: • Gene expression signarue in long-term survived GBM patients are identified from Gene Expression Omnibus database. • Repaglinide is identified as a survival-related drug for GBM via drug repositioning in CMap. • Repaglinide effectively kills GBM cells, inhibits GBM cell migration and increases survival of mice bearing orthotopic glioma. • Repaglinide reduces Bcl-2, Beclin-1 and PD-L1 in GBM tissues.« less

Active drug safety surveillance: a tool to improve public health.

PubMed

Platt, Richard; Madre, Leanne; Reynolds, Robert; Tilson, Hugh

2008-12-01

Ensuring that drugs have an acceptable safety profile and are used safely is a major public health priority. The Centers for Education and Research on Therapeutics (CERTs) convened experts from academia, government, and industry to assess strategies to increase the speed and predictive value of generating and evaluating safety signals, and to identify next steps to improve the US system for identifying and evaluating potential safety signals. The CERTs convened a think tank comprising representatives of the groups noted above to address these goals. Participants observed that, with the increasing availability of electronic health data, opportunities have emerged to more accurately characterize and confirm potential safety issues. The gain for public health from a highly coordinated network of population-based databases for active surveillance is great and within reach, although operational questions remain. A collaborative network must create a working definition of a safety signal, screening algorithms, and criteria and strategies to confirm or refute a signal once identified through screening. Guidelines are needed for when and how to communicate a signal exists and is being evaluated, as well as the outcome of that evaluation. A public-private partnership to create a network of government and private databases to routinely evaluate and prioritize safety questions is in the public interest. Better methods are needed, and a knowledgeable workforce is required to conduct the surveillance and understand how to interpret the results. The international community will benefit from the availability of better methods and more experts. Copyright (c) 2008 John Wiley & Sons, Ltd.

Evaluation of the Triage TOX Drug Screen Assay for Detection of 11 Drugs of Abuse and Therapeutic Drugs.

PubMed

Bang, Hae In; Jang, Mi Ae; Lee, Yong Wha

2017-11-01

The demand for rapid and broad clinical toxicology screens is on the rise. Recently, a new rapid toxicology screening test, the Triage TOX Drug Screen (Alere Inc., USA), which can simultaneously detect 11 drugs of abuse and therapeutic drugs with an instrument-read cartridge, was developed. In the present study, we evaluated the efficacy of this new on-site immunoassay using 105 urine specimens; the results were compared with those obtained by using ultra-performance liquid chromatography with tandem mass spectrometry (UPLC-TMS). Precision was evaluated according to the CLSI EP12-A2 for analyte concentrations near the cutoff, including C₅₀ and±30% of C₅₀, for each drug using standard materials. The C₅₀ specimens yielded 35-65% positive results and the±30% concentration range of all evaluated drugs encompassed the C₅-C₉₅ interval. The overall percent agreement of the Triage TOX Drug Screen was 92.4-100% compared with UPLC-TMS; however, the Triage TOX Drug Screen results showed some discordant cases including acetaminophen, amphetamine, benzodiazepine, opiates, and tricyclic antidepressants. The overall performance of the Triage TOX Drug Screen assay was comparable to that of UPLC-TMS for screening of drug intoxication in hospitals. This assay could constitute a useful screening method for drugs of abuse and therapeutic drugs in urine. © The Korean Society for Laboratory Medicine.

Evaluation of consumer drug information databases.

PubMed

Choi, J A; Sullivan, J; Pankaskie, M; Brufsky, J

1999-01-01

To evaluate prescription drug information contained in six consumer drug information databases available on CD-ROM, and to make health care professionals aware of the information provided, so that they may appropriately recommend these databases for use by their patients. Observational study of six consumer drug information databases: The Corner Drug Store, Home Medical Advisor, Mayo Clinic Family Pharmacist, Medical Drug Reference, Mosby's Medical Encyclopedia, and PharmAssist. Not applicable. Not applicable. Information on 20 frequently prescribed drugs was evaluated in each database. The databases were ranked using a point-scale system based on primary and secondary assessment criteria. For the primary assessment, 20 categories of information based on those included in the 1998 edition of the USP DI Volume II, Advice for the Patient: Drug Information in Lay Language were evaluated for each of the 20 drugs, and each database could earn up to 400 points (for example, 1 point was awarded if the database mentioned a drug's mechanism of action). For the secondary assessment, the inclusion of 8 additional features that could enhance the utility of the databases was evaluated (for example, 1 point was awarded if the database contained a picture of the drug), and each database could earn up to 8 points. The results of the primary and secondary assessments, listed in order of highest to lowest number of points earned, are as follows: Primary assessment--Mayo Clinic Family Pharmacist (379), Medical Drug Reference (251), PharmAssist (176), Home Medical Advisor (113.5), The Corner Drug Store (98), and Mosby's Medical Encyclopedia (18.5); secondary assessment--The Mayo Clinic Family Pharmacist (8), The Corner Drug Store (5), Mosby's Medical Encyclopedia (5), Home Medical Advisor (4), Medical Drug Reference (4), and PharmAssist (3). The Mayo Clinic Family Pharmacist was the most accurate and complete source of prescription drug information based on the USP DI Volume II and would be an appropriate database for health care professionals to recommend to patients.

Tuning hERG out: Antitarget QSAR Models for Drug Development

PubMed Central

Braga, Rodolpho C.; Alves, Vinícius M.; Silva, Meryck F. B.; Muratov, Eugene; Fourches, Denis; Tropsha, Alexander; Andrade, Carolina H.

2015-01-01

Several non-cardiovascular drugs have been withdrawn from the market due to their inhibition of hERG K+ channels that can potentially lead to severe heart arrhythmia and death. As hERG safety testing is a mandatory FDA-required procedure, there is a considerable interest for developing predictive computational tools to identify and filter out potential hERG blockers early in the drug discovery process. In this study, we aimed to generate predictive and well-characterized quantitative structure–activity relationship (QSAR) models for hERG blockage using the largest publicly available dataset of 11,958 compounds from the ChEMBL database. The models have been developed and validated according to OECD guidelines using four types of descriptors and four different machine-learning techniques. The classification accuracies discriminating blockers from non-blockers were as high as 0.83–0.93 on external set. Model interpretation revealed several SAR rules, which can guide structural optimization of some hERG blockers into non-blockers. We have also applied the generated models for screening the World Drug Index (WDI) database and identify putative hERG blockers and non-blockers among currently marketed drugs. The developed models can reliably identify blockers and non-blockers, which could be useful for the scientific community. A freely accessible web server has been developed allowing users to identify putative hERG blockers and non-blockers in chemical libraries of their interest (http://labmol.farmacia.ufg.br/predherg). PMID:24805060

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials

PubMed Central

Federer, Callie; Yoo, Minjae

2016-01-01

Abstract Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov (https://clinicaltrials.gov/), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov. Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs. PMID:27631620

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.

PubMed

Federer, Callie; Yoo, Minjae; Tan, Aik Choon

2016-12-01

Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov ( https://clinicaltrials.gov/ ), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov . Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs.

A Methodology for Cancer Therapeutics by Systems Pharmacology-Based Analysis: A Case Study on Breast Cancer-Related Traditional Chinese Medicines.

PubMed

Li, Yan; Wang, Jinghui; Lin, Feng; Yang, Yinfeng; Chen, Su-Shing

2017-01-01

Breast cancer is the most common carcinoma in women. Comprehensive therapy on breast cancer including surgical operation, chemotherapy, radiotherapy, endocrinotherapy, etc. could help, but still has serious side effect and resistance against anticancer drugs. Complementary and alternative medicine (CAM) may avoid these problems, in which traditional Chinese medicine (TCM) has been highlighted. In this section, to analyze the mechanism through which TCM act on breast cancer, we have built a virtual model consisting of the construction of database, oral bioavailability prediction, drug-likeness evaluation, target prediction, network construction. The 20 commonly employed herbs for the treatment of breast cancer were used as a database to carry out research. As a result, 150 ingredient compounds were screened out as active molecules for the herbs, with 33 target proteins predicted. Our analysis indicates that these herbs 1) takes a 'Jun-Chen-Zuo-Shi" as rule of prescription, 2) which function mainly through perturbing three pathways involving the epidermal growth factor receptor, estrogen receptor, and inflammatory pathways, to 3) display the breast cancer-related anti-estrogen, anti-inflammatory, regulation of cell metabolism and proliferation activities. To sum it up, by providing a novel in silico strategy for investigation of the botanical drugs, this work may be of some help for understanding the action mechanisms of herbal medicines and for discovery of new drugs from plants.

Digoxin and prostate cancer survival in the Finnish Randomized Study of Screening for Prostate Cancer.

PubMed

Kaapu, Kalle J; Murtola, Teemu J; Talala, Kirsi; Taari, Kimmo; Tammela, Teuvo Lj; Auvinen, Anssi

2016-11-22

Protective effects have been suggested for digoxin against prostate cancer risk. However, few studies have evaluated the possible effects on prostate cancer-specific survival. We studied the association between use of digoxin or beta-blocker sotalol and prostate cancer-specific survival as compared with users of other antiarrhythmic drugs in a retrospective cohort study. Our study population consisted of 6537 prostate cancer cases from the Finnish Randomized Study of Screening for Prostate Cancer diagnosed during 1996-2009 (485 digoxin users). The median exposure for digoxin was 480 DDDs (interquartile range 100-1400 DDDs). During a median follow-up of 7.5 years after diagnosis, 617 men (48 digoxin users) died of prostate cancer. We collected information on antiarrhythmic drug purchases from the national prescription database. Both prediagnostic and postdiagnostic drug usages were analysed using the Cox regression method. No association was found for prostate cancer death with digoxin usage before (HR 1.00, 95% CI 0.56-1.80) or after (HR 0.81, 95% CI 0.43-1.51) prostate cancer diagnosis. The results were also comparable for sotalol and antiarrhythmic drugs in general. Among men not receiving hormonal therapy, prediagnostic digoxin usage was associated with prolonged prostate cancer survival (HR 0.20, 95% CI 0.05-0.86). No general protective effects against prostate cancer were observed for digoxin or sotalol usage.

Discovery of agents that eradicate leukemia stem cells using an in silico screen of public gene expression data

PubMed Central

Hassane, Duane C.; Guzman, Monica L.; Corbett, Cheryl; Li, Xiaojie; Abboud, Ramzi; Young, Fay; Liesveld, Jane L.; Carroll, Martin

2008-01-01

Increasing evidence indicates that malignant stem cells are important for the pathogenesis of acute myelogenous leukemia (AML) and represent a reservoir of cells that drive the development of AML and relapse. Therefore, new treatment regimens are necessary to prevent relapse and improve therapeutic outcomes. Previous studies have shown that the sesquiterpene lactone, parthenolide (PTL), ablates bulk, progenitor, and stem AML cells while causing no appreciable toxicity to normal hematopoietic cells. Thus, PTL must evoke cellular responses capable of mediating AML selective cell death. Given recent advances in chemical genomics such as gene expression-based high-throughput screening (GE-HTS) and the Connectivity Map, we hypothesized that the gene expression signature resulting from treatment of primary AML with PTL could be used to search for similar signatures in publicly available gene expression profiles deposited into the Gene Expression Omnibus (GEO). We therefore devised a broad in silico screen of the GEO database using the PTL gene expression signature as a template and discovered 2 new agents, celastrol and 4-hydroxy-2-nonenal, that effectively eradicate AML at the bulk, progenitor, and stem cell level. These findings suggest the use of multicenter collections of high-throughput data to facilitate discovery of leukemia drugs and drug targets. PMID:18305216

Risk factors and prevalence of newborn hearing loss in a private health care system of Porto Velho, Northern Brazil

PubMed Central

de Oliveira, Juliana Santos; Rodrigues, Liliane Barbosa; Aurélio, Fernanda Soares; da Silva, Virgínia Braz

2013-01-01

OBJECTIVE: To determine the prevalence of hearing loss and to analyze the results of newborn hearing screening and audiological diagnosis in private health care systems. METHODS Cross-sectional and retrospective study in a database of newborn hearing screening performed by a private clinic in neonates born in private hospitals of Porto Velho, Rondônia, Northern Brazil. The screening results, the risk for hearing loss, the risk indicators for hearing loss and the diagnosis were descriptively analyzed. Newborns cared in rooming in with their mothers were compared to those admitted to the Intensive Care Unit regarding risk factors for hearing loss. RESULTS: Among 1,146 (100%) enrolled newborns, 1,064 (92.8%) passed and 82 (7.2%) failed the hearing screening. Among all screened neonates, 1,063 (92.8%) were cared in rooming and 83 (7.2%) needed intensive care; 986 (86.0%) were considered at low risk and 160 (14.0%) at high risk for hearing problems. Of the 160 patients identified as having high risk for hearing loss, 83 (37.7%) were admitted to an hospitalized in the Intensive Care Unit, 76 (34.5%) used ototoxic drugs and 38 (17.2%) had a family history of hearing loss in childhood. Hearing loss was diagnosed in two patients (0.2% of the screened sample). CONCLUSIONS: The prevalence of hearing loss in newborns from private hospitals was two cases per 1,000 evaluated patients. The use of ototoxic drugs, admission to Intensive Care Unit and family history of hearing loss were the most common risk factors for hearing loss in the studied population. PMID:24142311

A PATO-compliant zebrafish screening database (MODB): management of morpholino knockdown screen information.

PubMed

Knowlton, Michelle N; Li, Tongbin; Ren, Yongliang; Bill, Brent R; Ellis, Lynda Bm; Ekker, Stephen C

2008-01-07

The zebrafish is a powerful model vertebrate amenable to high throughput in vivo genetic analyses. Examples include reverse genetic screens using morpholino knockdown, expression-based screening using enhancer trapping and forward genetic screening using transposon insertional mutagenesis. We have created a database to facilitate web-based distribution of data from such genetic studies. The MOrpholino DataBase is a MySQL relational database with an online, PHP interface. Multiple quality control levels allow differential access to data in raw and finished formats. MODBv1 includes sequence information relating to almost 800 morpholinos and their targets and phenotypic data regarding the dose effect of each morpholino (mortality, toxicity and defects). To improve the searchability of this database, we have incorporated a fixed-vocabulary defect ontology that allows for the organization of morpholino affects based on anatomical structure affected and defect produced. This also allows comparison between species utilizing Phenotypic Attribute Trait Ontology (PATO) designated terminology. MODB is also cross-linked with ZFIN, allowing full searches between the two databases. MODB offers users the ability to retrieve morpholino data by sequence of morpholino or target, name of target, anatomical structure affected and defect produced. MODB data can be used for functional genomic analysis of morpholino design to maximize efficacy and minimize toxicity. MODB also serves as a template for future sequence-based functional genetic screen databases, and it is currently being used as a model for the creation of a mutagenic insertional transposon database.

Evaluation of personal digital assistant drug information databases for the managed care pharmacist.

PubMed

Lowry, Colleen M; Kostka-Rokosz, Maria D; McCloskey, William W

2003-01-01

Personal digital assistants (PDAs) are becoming a necessity for practicing pharmacists. They offer a time-saving and convenient way to obtain current drug information. Several software companies now offer general drug information databases for use on hand held computers. PDAs priced less than 200 US dollars often have limited memory capacity; therefore, the user must choose from a growing list of general drug information database options in order to maximize utility without exceeding memory capacity. This paper reviews the attributes of available general drug information software databases for the PDA. It provides information on the content, advantages, limitations, pricing, memory requirements, and accessibility of drug information software databases. Ten drug information databases were subjectively analyzed and evaluated based on information from the product.s Web site, vendor Web sites, and from our experience. Some of these databases have attractive auxiliary features such as kinetics calculators, disease references, drug-drug and drug-herb interaction tools, and clinical guidelines, which may make them more useful to the PDA user. Not all drug information databases are equal with regard to content, author credentials, frequency of updates, and memory requirements. The user must therefore evaluate databases for completeness, currency, and cost effectiveness before purchase. In addition, consideration should be given to the ease of use and flexibility of individual programs.

[Validation of interaction databases in psychopharmacotherapy].

PubMed

Hahn, M; Roll, S C

2018-03-01

Drug-drug interaction databases are an important tool to increase drug safety in polypharmacy. There are several drug interaction databases available but it is unclear which one shows the best results and therefore increases safety for the user of the databases and the patients. So far, there has been no validation of German drug interaction databases. Validation of German drug interaction databases regarding the number of hits, mechanisms of drug interaction, references, clinical advice, and severity of the interaction. A total of 36 drug interactions which were published in the last 3-5 years were checked in 5 different databases. Besides the number of hits, it was also documented if the mechanism was correct, clinical advice was given, primary literature was cited, and the severity level of the drug-drug interaction was given. All databases showed weaknesses regarding the hit rate of the tested drug interactions, with a maximum of 67.7% hits. The highest score in this validation was achieved by MediQ with 104 out of 180 points. PsiacOnline achieved 83 points, arznei-telegramm® 58, ifap index® 54 and the ABDA-database 49 points. Based on this validation MediQ seems to be the most suitable databank for the field of psychopharmacotherapy. The best results in this comparison were achieved by MediQ but this database also needs improvement with respect to the hit rate so that the users can rely on the results and therefore increase drug therapy safety.

ACToR-Aggregated Computational Resource | Science ...

EPA Pesticide Factsheets

ACToR (Aggregated Computational Toxicology Resource) is a database and set of software applications that bring into one central location many types and sources of data on environmental chemicals. Currently, the ACToR chemical database contains information on chemical structure, in vitro bioassays and in vivo toxicology assays derived from more than 150 sources including the U.S. Environmental Protection Agency (EPA), Centers for Disease Control (CDC), U.S. Food & Drug Administration (FDA), National Institutes of Health (NIH), state agencies, corresponding government agencies in Canada, Europe and Japan, universities, the World Health Organization (WHO) and non-governmental organizations (NGOs). At the EPA National Center for Computational Toxicology, ACToR helps manage large data sets being used in a high throughput environmental chemical screening and prioritization program called ToxCast(TM).

ACToR - Aggregated Computational Toxicology Resource

DOE Office of Scientific and Technical Information (OSTI.GOV)

Judson, Richard; Richard, Ann; Dix, David

2008-11-15

ACToR (Aggregated Computational Toxicology Resource) is a database and set of software applications that bring into one central location many types and sources of data on environmental chemicals. Currently, the ACToR chemical database contains information on chemical structure, in vitro bioassays and in vivo toxicology assays derived from more than 150 sources including the U.S. Environmental Protection Agency (EPA), Centers for Disease Control (CDC), U.S. Food and Drug Administration (FDA), National Institutes of Health (NIH), state agencies, corresponding government agencies in Canada, Europe and Japan, universities, the World Health Organization (WHO) and non-governmental organizations (NGOs). At the EPA National Centermore » for Computational Toxicology, ACToR helps manage large data sets being used in a high-throughput environmental chemical screening and prioritization program called ToxCast{sup TM}.« less

Image-based drug screen identifies HDAC inhibitors as novel Golgi disruptors synergizing with JQ1

PubMed Central

Gendarme, Mathieu; Baumann, Jan; Ignashkova, Tatiana I.; Lindemann, Ralph K.; Reiling, Jan H.

2017-01-01

The Golgi apparatus is increasingly recognized as a major hub for cellular signaling and is involved in numerous pathologies, including neurodegenerative diseases and cancer. The study of Golgi stress-induced signaling pathways relies on the selectivity of the available tool compounds of which currently only a few are known. To discover novel Golgi-fragmenting agents, transcriptomic profiles of cells treated with brefeldin A, golgicide A, or monensin were generated and compared with a database of gene expression profiles from cells treated with other bioactive small molecules. In parallel, a phenotypic screen was performed for compounds that alter normal Golgi structure. Histone deacetylase (HDAC) inhibitors and DNA-damaging agents were identified as novel Golgi disruptors. Further analysis identified HDAC1/HDAC9 as well as BRD8 and DNA-PK as important regulators of Golgi breakdown mediated by HDAC inhibition. We provide evidence that combinatorial HDACi/(+)-JQ1 treatment spurs synergistic Golgi dispersal in several cancer cell lines, pinpointing a possible link between drug-induced toxicity and Golgi morphology alterations. PMID:29074567

Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening

NASA Astrophysics Data System (ADS)

Halim, Sobia A.; Khan, Shanza; Khan, Ajmal; Wadood, Abdul; Mabood, Fazal; Hussain, Javid; Al-Harrasi, Ahmed

2017-10-01

Dengue fever is an emerging public health concern, with several million viral infections occur annually, for which no effective therapy currently exist. Non-structural protein 3 (NS-3) Helicase encoded by the dengue virus (DENV) is considered as a potential drug target to design new and effective drugs against dengue. Helicase is involved in unwinding of dengue RNA. This study was conducted to design new NS-3 Helicase inhibitor by in silico ligand- and structure based approaches. Initially ligand-based pharmacophore model was generated that was used to screen a set of 1201474 compounds collected from ZINC Database. The compounds matched with the pharmacophore model were docked into the active site of NS-3 helicase. Based on docking scores and binding interactions, twenty five compounds are suggested to be potential inhibitors of NS3 Helicase. The pharmacokinetic properties of these hits were predicted. The selected hits revealed acceptable ADMET properties. This study identified potential inhibitors of NS-3 Helicase in silico, and can be helpful in the treatment of Dengue.

PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach

PubMed Central

Liu, Xiaofeng; Ouyang, Sisheng; Yu, Biao; Liu, Yabo; Huang, Kai; Gong, Jiayu; Zheng, Siyuan; Li, Zhihua; Li, Honglin; Jiang, Hualiang

2010-01-01

In silico drug target identification, which includes many distinct algorithms for finding disease genes and proteins, is the first step in the drug discovery pipeline. When the 3D structures of the targets are available, the problem of target identification is usually converted to finding the best interaction mode between the potential target candidates and small molecule probes. Pharmacophore, which is the spatial arrangement of features essential for a molecule to interact with a specific target receptor, is an alternative method for achieving this goal apart from molecular docking method. PharmMapper server is a freely accessed web server designed to identify potential target candidates for the given small molecules (drugs, natural products or other newly discovered compounds with unidentified binding targets) using pharmacophore mapping approach. PharmMapper hosts a large, in-house repertoire of pharmacophore database (namely PharmTargetDB) annotated from all the targets information in TargetBank, BindingDB, DrugBank and potential drug target database, including over 7000 receptor-based pharmacophore models (covering over 1500 drug targets information). PharmMapper automatically finds the best mapping poses of the query molecule against all the pharmacophore models in PharmTargetDB and lists the top N best-fitted hits with appropriate target annotations, as well as respective molecule’s aligned poses are presented. Benefited from the highly efficient and robust triangle hashing mapping method, PharmMapper bears high throughput ability and only costs 1 h averagely to screen the whole PharmTargetDB. The protocol was successful in finding the proper targets among the top 300 pharmacophore candidates in the retrospective benchmarking test of tamoxifen. PharmMapper is available at http://59.78.96.61/pharmmapper. PMID:20430828

Identification of Novel Potential β-N-Acetyl-D-Hexosaminidase Inhibitors by Virtual Screening, Molecular Dynamics Simulation and MM-PBSA Calculations

PubMed Central

Liu, Jianling; Liu, Mengmeng; Yao, Yao; Wang, Jinan; Li, Yan; Li, Guohui; Wang, Yonghua

2012-01-01

Chitinolytic β-N-acetyl-d-hexosaminidases, as a class of chitin hydrolysis enzyme in insects, are a potential species-specific target for developing environmentally-friendly pesticides. Until now, pesticides targeting chitinolytic β-N-acetyl-d-hexosaminidase have not been developed. This study demonstrates a combination of different theoretical methods for investigating the key structural features of this enzyme responsible for pesticide inhibition, thus allowing for the discovery of novel small molecule inhibitors. Firstly, based on the currently reported crystal structure of this protein (OfHex1.pdb), we conducted a pre-screening of a drug-like compound database with 8 × 106 compounds by using the expanded pesticide-likeness criteria, followed by docking-based screening, obtaining 5 top-ranked compounds with favorable docking conformation into OfHex1. Secondly, molecular docking and molecular dynamics simulations are performed for the five complexes and demonstrate that one main hydrophobic pocket formed by residues Trp424, Trp448 and Trp524, which is significant for stabilization of the ligand–receptor complex, and key residues Asp477 and Trp490, are respectively responsible for forming hydrogen-bonding and π–π stacking interactions with the ligands. Finally, the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) analysis indicates that van der Waals interactions are the main driving force for the inhibitor binding that agrees with the fact that the binding pocket of OfHex1 is mainly composed of hydrophobic residues. These results suggest that screening the ZINC database can maximize the identification of potential OfHex1 inhibitors and the computational protocol will be valuable for screening potential inhibitors of the binding mode, which is useful for the future rational design of novel, potent OfHex1-specific pesticides. PMID:22605995

Multi-component identification and target cell-based screening of potential bioactive compounds in toad venom by UPLC coupled with high-resolution LTQ-Orbitrap MS and high-sensitivity Qtrap MS.

PubMed

Ren, Wei; Han, Lingyu; Luo, Mengyi; Bian, Baolin; Guan, Ming; Yang, Hui; Han, Chao; Li, Na; Li, Tuo; Li, Shilei; Zhang, Yangyang; Zhao, Zhenwen; Zhao, Haiyu

2018-04-28

Traditional Chinese medicines (TCMs) are undoubtedly treasured natural resources for discovering effective medicines in treating and preventing various diseases. However, it is still extremely difficult for screening the bioactive compounds due to the tremendous constituents in TCMs. In this work, the chemical composition of toad venom was comprehensively analyzed using ultra-high performance liquid chromatography (UPLC) coupled with high-resolution LTQ-Orbitrap mass spectrometry and 93 compounds were detected. Among them, 17 constituents were confirmed by standard substances and 8 constituents were detected in toad venom for the first time. Further, a compound database of toad venom containing the fullest compounds was further constructed using UPLC coupled with high-sensitivity Qtrap MS. Then a target cell-based approach for screening potential bioactive compounds from toad venom was developed by analyzing the target cell extracts. The reliability of this method was validated by negative controls and positive controls. In total, 17 components in toad venom were discovered to interact with the target cancer cells. Further, in vitro pharmacological trials were performed to confirm the anti-cancer activity of four of them. The results showed that the six bufogenins and seven bufotoxins detected in our research represented a promising resource to explore bufogenins/bufotoxins-based anticancer agents with low cardiotoxic effect. The target cell-based screening method coupled with the compound database of toad venom constructed by UPLC-Qtrap-MS with high sensitivity provide us a new strategy to rapidly screen and identify the potential bioactive constituents with low content in natural products, which was beneficial for drug discovery from other TCMs. ᅟ Graphical abstract.

Is Human-induced Pluripotent Stem Cell the Best Optimal?

PubMed

Wang, Feng; Kong, Jie; Cui, Yi-Yao; Liu, Peng; Wen, Jian-Yan

2018-04-05

Since the advent of induced pluripotent stem cell (iPSC) technology a decade ago, enormous progress has been made in stem cell biology and regenerative medicine. Human iPSCs have been widely used for disease modeling, drug discovery, and cell therapy development. In this review, we discuss the progress in applications of iPSC technology that are particularly relevant to drug discovery and regenerative medicine, and consider the remaining challenges and the emerging opportunities in the field. Articles in this review were searched from PubMed database from January 2014 to December 2017. Original articles about iPSCs and cardiovascular diseases were included and analyzed. iPSC holds great promises for human disease modeling, drug discovery, and stem cell-based therapy, and this potential is only beginning to be realized. However, several important issues remain to be addressed. The recent availability of human cardiomyocytes derived from iPSCs opens new opportunities to build in vitro models of cardiac disease, screening for new drugs and patient-specific cardiac therapy.

Repositioning Proton Pump Inhibitors as Anticancer Drugs by Targeting the Thioesterase Domain of Human Fatty Acid Synthase

PubMed Central

2015-01-01

Fatty acid synthase (FASN), the enzyme responsible for de novo synthesis of free fatty acids, is up-regulated in many cancers. FASN is essential for cancer cell survival and contributes to drug resistance and poor prognosis. However, it is not expressed in most nonlipogenic normal tissues. Thus, FASN is a desirable target for drug discovery. Although different FASN inhibitors have been identified, none has successfully moved into clinical use. In this study, using in silico screening of an FDA-approved drug database, we identified proton pump inhibitors (PPIs) as effective inhibitors of the thioesterase activity of human FASN. Further investigation showed that PPIs inhibited proliferation and induced apoptosis of cancer cells. Supplementation of palmitate, the end product of FASN catalysis, rescued cancer cells from PPI-induced cell death. These findings provide new evidence for the mechanism by which this FDA-approved class of compounds may be acting on cancer cells. PMID:25513712

SuperTarget goes quantitative: update on drug–target interactions

PubMed Central

Hecker, Nikolai; Ahmed, Jessica; von Eichborn, Joachim; Dunkel, Mathias; Macha, Karel; Eckert, Andreas; Gilson, Michael K.; Bourne, Philip E.; Preissner, Robert

2012-01-01

There are at least two good reasons for the on-going interest in drug–target interactions: first, drug-effects can only be fully understood by considering a complex network of interactions to multiple targets (so-called off-target effects) including metabolic and signaling pathways; second, it is crucial to consider drug-target-pathway relations for the identification of novel targets for drug development. To address this on-going need, we have developed a web-based data warehouse named SuperTarget, which integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins. At present, the updated database contains >6000 target proteins, which are annotated with >330 000 relations to 196 000 compounds (including approved drugs); the vast majority of interactions include binding affinities and pointers to the respective literature sources. The user interface provides tools for drug screening and target similarity inclusion. A query interface enables the user to pose complex queries, for example, to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target proteins within a certain affinity range. SuperTarget is available at http://bioinformatics.charite.de/supertarget. PMID:22067455

Ocular toxicities associated with targeted anticancer agents: an analysis of clinical data with management suggestions

PubMed Central

Fu, Chen; Gombos, Dan S; Lee, Jared; George, Goldy C; Hess, Kenneth; Whyte, Andrew; Hong, David S

2017-01-01

Ocular toxicities are among the most common adverse events resulting from targeted anticancer agents and are becoming increasingly relevant in the management of patients on these agents. The purpose of this study is to provide a framework for management of these challenging toxicities based on objective data from FDA labels and from analysis of the literature. All oncologic drugs approved by the FDA up to March 14, 2015, were screened for inclusion. A total of 16 drugs (12 small-molecule drugs and 4 monoclonal antibodies) were analyzed for ocular toxicity profiles based on evidence of ocular toxicity. Trials cited by FDA labels were retrieved, and a combination search in Medline, Google Scholar, the Cochrane database, and the NIH Clinical Trials Database was conducted. The majority of ocular toxicities reported were low severity, and the most common were conjunctivitis and “visual disturbances.” However, severe events including incidents of blindness, retinal vascular occlusion, and corneal ulceration occurred. The frequency and severity at which ocular toxicities occur merits a more multidisciplinary approach to managing patients with agents that are known to cause ocular issues. We suggest a standardized methodology for referral and surveillance of patients who are potentially at risk of severe ocular toxicity. PMID:28938590

Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors.

PubMed

Xue, Xin; Wei, Jin-Lian; Xu, Li-Li; Xi, Mei-Yang; Xu, Xiao-Li; Liu, Fang; Guo, Xiao-Ke; Wang, Lei; Zhang, Xiao-Jin; Zhang, Ming-Ye; Lu, Meng-Chen; Sun, Hao-Peng; You, Qi-Dong

2013-10-28

Protein-protein interactions (PPIs) play a crucial role in cellular function and form the backbone of almost all biochemical processes. In recent years, protein-protein interaction inhibitors (PPIIs) have represented a treasure trove of potential new drug targets. Unfortunately, there are few successful drugs of PPIIs on the market. Structure-based pharmacophore (SBP) combined with docking has been demonstrated as a useful Virtual Screening (VS) strategy in drug development projects. However, the combination of target complexity and poor binding affinity prediction has thwarted the application of this strategy in the discovery of PPIIs. Here we report an effective VS strategy on p53-MDM2 PPI. First, we built a SBP model based on p53-MDM2 complex cocrystal structures. The model was then simplified by using a Receptor-Ligand complex-based pharmacophore model considering the critical binding features between MDM2 and its small molecular inhibitors. Cascade docking was subsequently applied to improve the hit rate. Based on this strategy, we performed VS on NCI and SPECS databases and successfully discovered 6 novel compounds from 15 hits with the best, compound 1 (NSC 5359), K(i) = 180 ± 50 nM. These compounds can serve as lead compounds for further optimization.

Drug-Path: a database for drug-induced pathways.

PubMed

Zeng, Hui; Qiu, Chengxiang; Cui, Qinghua

2015-01-01

Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. © The Author(s) 2015. Published by Oxford University Press.

Trainable structure-activity relationship model for virtual screening of CYP3A4 inhibition.

PubMed

Didziapetris, Remigijus; Dapkunas, Justas; Sazonovas, Andrius; Japertas, Pranas

2010-11-01

A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for >800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. For compounds within this domain the statistical results of the final model approach the data consistency between experimental data from literature and PubChem datasets with the overall accuracy of 89%. However, the original model is applicable only for less than a half of PubChem database. Since the similarity correction procedure of GALAS modeling method allows straightforward model training, the possibility to expand the applicability domain has been investigated. Experimental data from PubChem dataset served as an example of in-house high-throughput screening data. The model successfully adapted itself to both data classified using the same and different IC₅₀ threshold compared with the training set. In addition, adjustment of the CYP3A4 inhibition model to compounds with a novel chemical scaffold has been demonstrated. The reported GALAS model is proposed as a useful tool for virtual screening of compounds for possible drug-drug interactions even prior to the actual synthesis.

DockScreen: A database of in silico biomolecular interactions to support computational toxicology

EPA Science Inventory

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...

Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening.

PubMed

Lin, Chun-Yuan; Wang, Yen-Ling

2014-01-01

Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.

High-throughput screening of a diversity collection using biodefense category A and B priority pathogens.

PubMed

Barrow, Esther W; Clinkenbeard, Patricia A; Duncan-Decocq, Rebecca A; Perteet, Rachel F; Hill, Kimberly D; Bourne, Philip C; Valderas, Michelle W; Bourne, Christina R; Clarkson, Nicole L; Clinkenbeard, Kenneth D; Barrow, William W

2012-08-01

One of the objectives of the National Institutes of Allergy and Infectious Diseases (NIAID) Biodefense Program is to identify or develop broad-spectrum antimicrobials for use against bioterrorism pathogens and emerging infectious agents. As a part of that program, our institution has screened the 10 000-compound MyriaScreen Diversity Collection of high-purity druglike compounds against three NIAID category A and one category B priority pathogens in an effort to identify potential compound classes for further drug development. The effective use of a Clinical and Laboratory Standards Institute-based high-throughput screening (HTS) 96-well-based format allowed for the identification of 49 compounds that had in vitro activity against all four pathogens with minimum inhibitory concentration values of ≤16 µg/mL. Adaptation of the HTS process was necessary to conduct the work in higher-level containment, in this case, biosafety level 3. Examination of chemical scaffolds shared by some of the 49 compounds and assessment of available chemical databases indicates that several may represent broad-spectrum antimicrobials whose activity is based on novel mechanisms of action.

Identification of the Beer Component Hordenine as Food-Derived Dopamine D2 Receptor Agonist by Virtual Screening a 3D Compound Database

NASA Astrophysics Data System (ADS)

Sommer, Thomas; Hübner, Harald; El Kerdawy, Ahmed; Gmeiner, Peter; Pischetsrieder, Monika; Clark, Timothy

2017-03-01

The dopamine D2 receptor (D2R) is involved in food reward and compulsive food intake. The present study developed a virtual screening (VS) method to identify food components, which may modulate D2R signalling. In contrast to their common applications in drug discovery, VS methods are rarely applied for the discovery of bioactive food compounds. Here, databases were created that exclusively contain substances occurring in food and natural sources (about 13,000 different compounds in total) as the basis for combined pharmacophore searching, hit-list clustering and molecular docking into D2R homology models. From 17 compounds finally tested in radioligand assays to determine their binding affinities, seven were classified as hits (hit rate = 41%). Functional properties of the five most active compounds were further examined in β-arrestin recruitment and cAMP inhibition experiments. D2R-promoted G-protein activation was observed for hordenine, a constituent of barley and beer, with approximately identical ligand efficacy as dopamine (76%) and a Ki value of 13 μM. Moreover, hordenine antagonised D2-mediated β-arrestin recruitment indicating functional selectivity. Application of our databases provides new perspectives for the discovery of bioactive food constituents using VS methods. Based on its presence in beer, we suggest that hordenine significantly contributes to mood-elevating effects of beer.

Identification of Potent Chloride Intracellular Channel Protein 1 Inhibitors from Traditional Chinese Medicine through Structure-Based Virtual Screening and Molecular Dynamics Analysis

PubMed Central

Wan, Minghui; Liao, Dongjiang; Peng, Guilin; Xu, Xin; Yin, Weiqiang; Guo, Guixin; Jiang, Funeng; Zhong, Weide

2017-01-01

Chloride intracellular channel 1 (CLIC1) is involved in the development of most aggressive human tumors, including gastric, colon, lung, liver, and glioblastoma cancers. It has become an attractive new therapeutic target for several types of cancer. In this work, we aim to identify natural products as potent CLIC1 inhibitors from Traditional Chinese Medicine (TCM) database using structure-based virtual screening and molecular dynamics (MD) simulation. First, structure-based docking was employed to screen the refined TCM database and the top 500 TCM compounds were obtained and reranked by X-Score. Then, 30 potent hits were achieved from the top 500 TCM compounds using cluster and ligand-protein interaction analysis. Finally, MD simulation was employed to validate the stability of interactions between each hit and CLIC1 protein from docking simulation, and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) analysis was used to refine the virtual hits. Six TCM compounds with top MM-GBSA scores and ideal-binding models were confirmed as the final hits. Our study provides information about the interaction between TCM compounds and CLIC1 protein, which may be helpful for further experimental investigations. In addition, the top 6 natural products structural scaffolds could serve as building blocks in designing drug-like molecules for CLIC1 inhibition. PMID:29147652

Thailand mutation and variation database (ThaiMUT).

PubMed

Ruangrit, Uttapong; Srikummool, Metawee; Assawamakin, Anunchai; Ngamphiw, Chumpol; Chuechote, Suparat; Thaiprasarnsup, Vilasinee; Agavatpanitch, Gallissara; Pasomsab, Ekawat; Yenchitsomanus, Pa-Thai; Mahasirimongkol, Surakameth; Chantratita, Wasun; Palittapongarnpim, Prasit; Uyyanonvara, Bunyarit; Limwongse, Chanin; Tongsima, Sissades

2008-08-01

With the completion of the human genome project, novel sequencing and genotyping technologies had been utilized to detect mutations. Such mutations have continually been produced at exponential rate by researchers in various communities. Based on the population's mutation spectra, occurrences of Mendelian diseases are different across ethnic groups. A proportion of Mendelian diseases can be observed in some countries at higher rates than others. Recognizing the importance of mutation effects in Thailand, we established a National and Ethnic Mutation Database (NEMDB) for Thai people. This database, named Thailand Mutation and Variation database (ThaiMUT), offers a web-based access to genetic mutation and variation information in Thai population. This NEMDB initiative is an important informatics tool for both research and clinical purposes to retrieve and deposit human variation data. The mutation data cataloged in ThaiMUT database were derived from journal articles available in PubMed and local publications. In addition to collected mutation data, ThaiMUT also records genetic polymorphisms located in drug related genes. ThaiMUT could then provide useful information for clinical mutation screening services for Mendelian diseases and pharmacogenomic researches. ThaiMUT can be publicly accessed from http://gi.biotec.or.th/thaimut.

A review of drug-induced liver injury databases.

PubMed

Luo, Guangwen; Shen, Yiting; Yang, Lizhu; Lu, Aiping; Xiang, Zheng

2017-09-01

Drug-induced liver injuries have been a major focus of current research in drug development, and are also one of the major reasons for the failure and withdrawal of drugs in development. Drug-induced liver injuries have been systematically recorded in many public databases, which have become valuable resources in this field. In this study, we provide an overview of these databases, including the liver injury-specific databases LiverTox, LTKB, Open TG-GATEs, LTMap and Hepatox, and the general databases, T3DB, DrugBank, DITOP, DART, CTD and HSDB. The features and limitations of these databases are summarized and discussed in detail. Apart from their powerful functions, we believe that these databases can be improved in several ways: by providing the data about the molecular targets involved in liver toxicity, by incorporating information regarding liver injuries caused by drug interactions, and by regularly updating the data.

High impact technologies for natural products screening.

PubMed

Koehn, Frank E

2008-01-01

Natural products have historically been a rich source of lead molecules in drug discovery. However, natural products have been de-emphasized as high throughput screening resources in the recent past, in part because of difficulties in obtaining high quality natural products screening libraries, or in applying modern screening assays to these libraries. In addition, natural products programs based on screening of extract libraries, bioassay-guided isolation, structure elucidation and subsequent production scale-up are challenged to meet the rapid cycle times that are characteristic of the modern HTS approach. Fortunately, new technologies in mass spectrometry, NMR and other spectroscopic techniques can greatly facilitate the first components of the process - namely the efficient creation of high-quality natural products libraries, bimolecular target or cell-based screening, and early hit characterization. The success of any high throughput screening campaign is dependent on the quality of the chemical library. The construction and maintenance of a high quality natural products library, whether based on microbial, plant, marine or other sources is a costly endeavor. The library itself may be composed of samples that are themselves mixtures - such as crude extracts, semi-pure mixtures or single purified natural products. Each of these library designs carries with it distinctive advantages and disadvantages. Crude extract libraries have lower resource requirements for sample preparation, but high requirements for identification of the bioactive constituents. Pre-fractionated libraries can be an effective strategy to alleviate interferences encountered with crude libraries, and may shorten the time needed to identify the active principle. Purified natural product libraries require substantial resources for preparation, but offer the advantage that the hit detection process is reduced to that of synthetic single component libraries. Whether the natural products library consists of crude or partially fractionated mixtures, the library contents should be profiled to identify the known components present - a process known as dereplication. The use of mass spectrometry and HPLC-mass spectrometry together with spectral databases is a powerful tool in the chemometric profiling of bio-sources for natural product production. High throughput, high sensitivity flow NMR is an emerging tool in this area as well. Whether by cell based or biomolecular target based assays, screening of natural product extract libraries continues to furnish novel lead molecules for further drug development, despite challenges in the analysis and prioritization of natural products hits. Spectroscopic techniques are now being used to directly screen natural product and synthetic libraries. Mass spectrometry in the form of methods such as ESI-ICRFTMS, and FACS-MS as well as NMR methods such as SAR by NMR and STD-NMR have been utilized to effectively screen molecular libraries. Overall, emerging advances in mass spectrometry, NMR and other technologies are making it possible to overcome the challenges encountered in screening natural products libraries in today's drug discovery environment. As we apply these technologies and develop them even further, we can look forward to increased impact of natural products in the HTS based drug discovery.

Virtual screening using the ligand ZINC database for novel lipoxygenase-3 inhibitors.

PubMed

Monika; Kour, Janmeet; Singh, Kulwinder

2013-01-01

The leukotrienes constitute a group of arachidonic acid-derived compounds with biologic activities suggesting important roles in inflammation and immediate hypersensitivity. Epidermis-type lipoxygenase-3 (ALOXE3), a distinct subclass within the multigene family of mammalian lipoxygenases, is a novel isoenzyme involved in the metabolism of leukotrienes and plays a very important role in skin barrier functions. Lipoxygenase selective inhibitors such as azelastine and zileuton are currently used to reduce inflammatory response. Nausea, pharyngolaryngeal pain, headache, nasal burning and somnolence are the most frequently reported adverse effects of these drugs. Therefore, there is still a need to develop more potent lipoxygenase inhibitors. In this paper, we report the screening of various compounds from the ZINC database (contains over 21 million compounds) using the Molegro Virtual Docker software against the ALOXE3 protein. Screening was performed using molecular constraints tool to filter compounds with physico-chemical properties similar to the 1N8Q bound ligand protocatechuic acid. The analysis resulted in 4319 Lipinski compliant hits which are docked and scored to identify structurally novel ligands that make similar interactions to those of known ligands or may have different interactions with other parts of the binding site. Our screening approach identified four molecules ZINC84299674; ZINC76643455; ZINC84299122 & ZINC75626957 with MolDock score of -128.901, -120.22, -116.873 & - 102.116 kcal/mol, respectively. Their energy scores were better than the 1N8Q bound co-crystallized ligand protocatechuic acid (with MolDock score of -77.225 kcal/mol). All the ligands were docked within the binding pocket forming interactions with amino acid residues.

Evaluation of thromboembolic events in cancer patients receiving bevacizumab according to the Japanese Adverse Drug Event Report database.

PubMed

Matsumura, Chikako; Chisaki, Yugo; Sakimoto, Satoko; Sakae, Honoka; Yano, Yoshitaka

2018-01-01

Purpose We aimed to examine the risk factors, time of onset, incidence rates, and outcomes of thromboembolic events induced by bevacizumab in patients with cancer using the Japanese Adverse Drug Event Report (JADER) database of the Pharmaceuticals and Medical Devices Agency. Methods Adverse event data recorded in the JADER database between January 2004 and January 2015 were used. After screening the data using the generic drug name bevacizumab, patient data were classified into two groups by age and five groups by cancer type. The histories of disorders were also categorized. Arterial thromboembolic event and venous thromboembolic event were classified as "favorable" or "unfavorable" outcomes. Results In total, 6076 patients were reported to have developed adverse events during the sample period, of which 233 and 453 developed arterial thromboembolic event and venous thromboembolic event, respectively. Logistic analysis suggested that the presence of cancer was a significant risk factor for both arterial thromboembolic event and venous thromboembolic event. Age (≥70 years), histories of either hypertension or diabetes mellitus were also risk factors for arterial thromboembolic event. Median cumulative times of onset for arterial thromboembolic event and venous thromboembolic event were 60 and 80 days, respectively, and were not significantly different by the log-rank test. By the chi-square test, the rate of unfavorable outcomes was found to be higher after developing arterial thromboembolic event than after venous thromboembolic event. Conclusion Thromboembolism is a leading cause of mortality in patients with cancer. Patients should be monitored for the symptoms of thromboembolic events right from the initial stages of bevacizumab treatment.

Novel Phenotypic Outcomes Identified for a Public Collection of Approved Drugs from a Publicly Accessible Panel of Assays

PubMed Central

Oliver, Sarah; Willard, Francis S.; Heidler, Steven; Peery, Robert B.; Oler, Jennifer; Chu, Shaoyou; Southall, Noel; Dexheimer, Thomas S.; Smallwood, Jeffrey; Huang, Ruili; Guha, Rajarshi; Jadhav, Ajit; Cox, Karen; Austin, Christopher P.; Simeonov, Anton; Sittampalam, G. Sitta; Husain, Saba; Franklin, Natalie; Wild, David J.; Yang, Jeremy J.; Sutherland, Jeffrey J.; Thomas, Craig J.

2015-01-01

Phenotypic assays have a proven track record for generating leads that become first-in-class therapies. Whole cell assays that inform on a phenotype or mechanism also possess great potential in drug repositioning studies by illuminating new activities for the existing pharmacopeia. The National Center for Advancing Translational Sciences (NCATS) pharmaceutical collection (NPC) is the largest reported collection of approved small molecule therapeutics that is available for screening in a high-throughput setting. Via a wide-ranging collaborative effort, this library was analyzed in the Open Innovation Drug Discovery (OIDD) phenotypic assay modules publicly offered by Lilly. The results of these tests are publically available online at www.ncats.nih.gov/expertise/preclinical/pd2 and via the PubChem Database (https://pubchem.ncbi.nlm.nih.gov/) (AID 1117321). Phenotypic outcomes for numerous drugs were confirmed, including sulfonylureas as insulin secretagogues and the anti-angiogenesis actions of multikinase inhibitors sorafenib, axitinib and pazopanib. Several novel outcomes were also noted including the Wnt potentiating activities of rotenone and the antifolate class of drugs, and the anti-angiogenic activity of cetaben. PMID:26177200

Novel Phenotypic Outcomes Identified for a Public Collection of Approved Drugs from a Publicly Accessible Panel of Assays.

PubMed

Lee, Jonathan A; Shinn, Paul; Jaken, Susan; Oliver, Sarah; Willard, Francis S; Heidler, Steven; Peery, Robert B; Oler, Jennifer; Chu, Shaoyou; Southall, Noel; Dexheimer, Thomas S; Smallwood, Jeffrey; Huang, Ruili; Guha, Rajarshi; Jadhav, Ajit; Cox, Karen; Austin, Christopher P; Simeonov, Anton; Sittampalam, G Sitta; Husain, Saba; Franklin, Natalie; Wild, David J; Yang, Jeremy J; Sutherland, Jeffrey J; Thomas, Craig J

2015-01-01

Phenotypic assays have a proven track record for generating leads that become first-in-class therapies. Whole cell assays that inform on a phenotype or mechanism also possess great potential in drug repositioning studies by illuminating new activities for the existing pharmacopeia. The National Center for Advancing Translational Sciences (NCATS) pharmaceutical collection (NPC) is the largest reported collection of approved small molecule therapeutics that is available for screening in a high-throughput setting. Via a wide-ranging collaborative effort, this library was analyzed in the Open Innovation Drug Discovery (OIDD) phenotypic assay modules publicly offered by Lilly. The results of these tests are publically available online at www.ncats.nih.gov/expertise/preclinical/pd2 and via the PubChem Database (https://pubchem.ncbi.nlm.nih.gov/) (AID 1117321). Phenotypic outcomes for numerous drugs were confirmed, including sulfonylureas as insulin secretagogues and the anti-angiogenesis actions of multikinase inhibitors sorafenib, axitinib and pazopanib. Several novel outcomes were also noted including the Wnt potentiating activities of rotenone and the antifolate class of drugs, and the anti-angiogenic activity of cetaben.

EDCs DataBank: 3D-Structure database of endocrine disrupting chemicals.

PubMed

Montes-Grajales, Diana; Olivero-Verbel, Jesus

2015-01-02

Endocrine disrupting chemicals (EDCs) are a group of compounds that affect the endocrine system, frequently found in everyday products and epidemiologically associated with several diseases. The purpose of this work was to develop EDCs DataBank, the only database of EDCs with three-dimensional structures. This database was built on MySQL using the EU list of potential endocrine disruptors and TEDX list. It contains the three-dimensional structures available on PubChem, as well as a wide variety of information from different databases and text mining tools, useful for almost any kind of research regarding EDCs. The web platform was developed employing HTML, CSS and PHP languages, with dynamic contents in a graphic environment, facilitating information analysis. Currently EDCs DataBank has 615 molecules, including pesticides, natural and industrial products, cosmetics, drugs and food additives, among other low molecular weight xenobiotics. Therefore, this database can be used to study the toxicological effects of these molecules, or to develop pharmaceuticals targeting hormone receptors, through docking studies, high-throughput virtual screening and ligand-protein interaction analysis. EDCs DataBank is totally user-friendly and the 3D-structures of the molecules can be downloaded in several formats. This database is freely available at http://edcs.unicartagena.edu.co. Copyright © 2014. Published by Elsevier Ireland Ltd.

Towards the comprehensive, rapid, and accurate prediction of the favorable tautomeric states of drug-like molecules in aqueous solution

NASA Astrophysics Data System (ADS)

Greenwood, Jeremy R.; Calkins, David; Sullivan, Arron P.; Shelley, John C.

2010-06-01

Generating the appropriate protonation states of drug-like molecules in solution is important for success in both ligand- and structure-based virtual screening. Screening collections of millions of compounds requires a method for determining tautomers and their energies that is sufficiently rapid, accurate, and comprehensive. To maximise enrichment, the lowest energy tautomers must be determined from heterogeneous input, without over-enumerating unfavourable states. While computationally expensive, the density functional theory (DFT) method M06-2X/aug-cc-pVTZ(-f) [PB-SCRF] provides accurate energies for enumerated model tautomeric systems. The empirical Hammett-Taft methodology can very rapidly extrapolate substituent effects from model systems to drug-like molecules via the relationship between pKT and pKa. Combining the two complementary approaches transforms the tautomer problem from a scientific challenge to one of engineering scale-up, and avoids issues that arise due to the very limited number of measured pKT values, especially for the complicated heterocycles often favoured by medicinal chemists for their novelty and versatility. Several hundreds of pre-calculated tautomer energies and substituent pKa effects are tabulated in databases for use in structural adjustment by the program Epik, which treats tautomers as a subset of the larger problem of the protonation states in aqueous ensembles and their energy penalties. Accuracy and coverage is continually improved and expanded by parameterizing new systems of interest using DFT and experimental data. Recommendations are made for how to best incorporate tautomers in molecular design and virtual screening workflows.

Current situation and future usage of anticancer drug databases.

PubMed

Wang, Hongzhi; Yin, Yuanyuan; Wang, Peiqi; Xiong, Chenyu; Huang, Lingyu; Li, Sijia; Li, Xinyi; Fu, Leilei

2016-07-01

Cancer is a deadly disease with increasing incidence and mortality rates and affects the life quality of millions of people per year. The past 15 years have witnessed the rapid development of targeted therapy for cancer treatment, with numerous anticancer drugs, drug targets and related gene mutations been identified. The demand for better anticancer drugs and the advances in database technologies have propelled the development of databases related to anticancer drugs. These databases provide systematic collections of integrative information either directly on anticancer drugs or on a specific type of anticancer drugs with their own emphases on different aspects, such as drug-target interactions, the relationship between mutations in drug targets and drug resistance/sensitivity, drug-drug interactions, natural products with anticancer activity, anticancer peptides, synthetic lethality pairs and histone deacetylase inhibitors. We focus on a holistic view of the current situation and future usage of databases related to anticancer drugs and further discuss their strengths and weaknesses, in the hope of facilitating the discovery of new anticancer drugs with better clinical outcomes.

The CSB Incident Screening Database: description, summary statistics and uses.

PubMed

Gomez, Manuel R; Casper, Susan; Smith, E Allen

2008-11-15

This paper briefly describes the Chemical Incident Screening Database currently used by the CSB to identify and evaluate chemical incidents for possible investigations, and summarizes descriptive statistics from this database that can potentially help to estimate the number, character, and consequences of chemical incidents in the US. The report compares some of the information in the CSB database to roughly similar information available from databases operated by EPA and the Agency for Toxic Substances and Disease Registry (ATSDR), and explores the possible implications of these comparisons with regard to the dimension of the chemical incident problem. Finally, the report explores in a preliminary way whether a system modeled after the existing CSB screening database could be developed to serve as a national surveillance tool for chemical incidents.

CrossCheck: an open-source web tool for high-throughput screen data analysis.

PubMed

Najafov, Jamil; Najafov, Ayaz

2017-07-19

Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

The prescribable drugs with efficacy in experimental epilepsies (PDE3) database for drug repurposing research in epilepsy.

PubMed

Sivapalarajah, Shayeeshan; Krishnakumar, Mathangi; Bickerstaffe, Harry; Chan, YikYing; Clarkson, Joseph; Hampden-Martin, Alistair; Mirza, Ahmad; Tanti, Matthew; Marson, Anthony; Pirmohamed, Munir; Mirza, Nasir

2018-02-01

Current antiepileptic drugs (AEDs) have several shortcomings. For example, they fail to control seizures in 30% of patients. Hence, there is a need to identify new AEDs. Drug repurposing is the discovery of new indications for approved drugs. This drug "recycling" offers the potential of significant savings in the time and cost of drug development. Many drugs licensed for other indications exhibit antiepileptic efficacy in animal models. Our aim was to create a database of "prescribable" drugs, approved for other conditions, with published evidence of efficacy in animal models of epilepsy, and to collate data that would assist in choosing the most promising candidates for drug repurposing. The database was created by the following: (1) computational literature-mining using novel software that identifies Medline abstracts containing the name of a prescribable drug, a rodent model of epilepsy, and a phrase indicating seizure reduction; then (2) crowdsourced manual curation of the identified abstracts. The final database includes 173 drugs and 500 abstracts. It is made freely available at www.liverpool.ac.uk/D3RE/PDE3. The database is reliable: 94% of the included drugs have corroborative evidence of efficacy in animal models (for example, evidence from multiple independent studies). The database includes many drugs that are appealing candidates for repurposing, as they are widely accepted by prescribers and patients-the database includes half of the 20 most commonly prescribed drugs in England-and they target many proteins involved in epilepsy but not targeted by current AEDs. It is important to note that the drugs are of potential relevance to human epilepsy-the database is highly enriched with drugs that target proteins of known causal human epilepsy genes (Fisher's exact test P-value < 3 × 10 -5 ). We present data to help prioritize the most promising candidates for repurposing from the database. The PDE3 database is an important new resource for drug repurposing research in epilepsy. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Clinical evaluation and use of urine screening for drug abuse.

PubMed Central

Saxon, A J; Calsyn, D A; Haver, V M; Delaney, C J

1988-01-01

Urine drug screening is indicated to evaluate patients who show mental status or behavioral changes and to monitor the abstinence of drug abusers. The appropriate timing for collecting urine specimens may vary depending on the suspected drug of abuse and on laboratory factors. Laboratories use a variety of techniques to do urine screens, and these must be understood by clinicians ordering the screens to interpret results correctly. In treating drug-abusing patients, clinicians must apply structured reinforcement in conjunction with urine screen results to aid patients in achieving abstinence. PMID:3176489

In silico strategies for the selection of chelating compounds with potential application in metal-promoted neurodegenerative diseases

NASA Astrophysics Data System (ADS)

Rodríguez-Rodríguez, Cristina; Rimola, Albert; Alí-Torres, Jorge; Sodupe, Mariona; González-Duarte, Pilar

2011-01-01

The development of new strategies to find commercial molecules with promising biochemical features is a main target in the field of biomedicine chemistry. In this work we present an in silico-based protocol that allows identifying commercial compounds with suitable metal coordinating and pharmacokinetic properties to act as metal-ion chelators in metal-promoted neurodegenerative diseases (MpND). Selection of the chelating ligands is done by combining quantum chemical calculations with the search of commercial compounds on different databases via virtual screening. Starting from different designed molecular frameworks, which mainly constitute the binding site, the virtual screening on databases facilitates the identification of different commercial molecules that enclose such scaffolds and, by imposing a set of chemical and pharmacokinetic filters, obey some drug-like requirements mandatory to deal with MpND. The quantum mechanical calculations are useful to gauge the chelating properties of the selected candidate molecules by determining the structure of metal complexes and evaluating their stability constants. With the proposed strategy, commercial compounds containing N and S donor atoms in the binding sites and capable to cross the BBB have been identified and their chelating properties analyzed.

RigFit: a new approach to superimposing ligand molecules.

PubMed

Lemmen, C; Hiller, C; Lengauer, T

1998-09-01

If structural knowledge of a receptor under consideration is lacking, drug design approaches focus on similarity or dissimilarity analysis of putative ligands. In this context the mutual ligand superposition is of utmost importance. Methods that are rapid enough to facilitate interactive usage, that allow to process sets of conformers and that enable database screening are of special interest here. The ability to superpose molecular fragments instead of entire molecules has proven to be helpful too. The RIGFIT approach meets these requirements and has several additional advantages. In three distinct test applications, we evaluated how closely we can approximate the observed relative orientation for a set of known crystal structures, we employed RIGFIT as a fragment placement procedure, and we performed a fragment-based database screening. The run time of RIGFIT can be traded off against its accuracy. To be competitive in accuracy with another state-of-the-art alignment tool, with which we compare our method explicitly, computing times of about 6 s per superposition on a common day workstation are required. If longer run times can be afforded the accuracy increases significantly. RIGFIT is part of the flexible superposition software FLEXS which can be accessed on the WWW [http:/(/)cartan.gmd.de/FlexS].

Headache (chronic tension-type)

PubMed Central

2016-01-01

Introduction Chronic tension-type headache (CTTH) is a disorder that evolves from episodic tension-type headache, with daily, or very frequent, episodes of headache lasting hours or they may be continuous. It affects up to 4% of the general population, and is more prevalent in women (up to 65% of cases). Methods and outcomes We conducted a systematic overview, aiming to answer the following clinical questions: What are the effects of drug treatments for CTTH? What are the effects of non-drug treatments for CTTH? We searched: Medline, Embase, The Cochrane Library, and other important databases up to December 2013 (BMJ Clinical Evidence overviews are updated periodically; please check our website for the most up-to-date version of this overview). Results At this update, searching of electronic databases retrieved 125 studies. After deduplication, 77 records were screened for inclusion in the overview. Appraisal of titles and abstracts led to the exclusion of 56 studies and the further review of 21 full publications. Of the 21 full articles evaluated, three systematic reviews and one RCT were included at this update. We performed a GRADE evaluation for 15 PICO combinations. Conclusions In this systematic overview, we categorised the efficacy for 12 interventions based on information about the effectiveness and safety of non-drug treatments acupuncture and cognitive behavioural therapy (CBT), as well as the drug treatments amitriptyline, anticonvulsant drugs (sodium valproate, topiramate, or gabapentin), benzodiazepines, botulinum toxin, noradrenergic and specific serotonergic antidepressants (mirtazapine), NSAIDs (e.g. ibuprofen); opioid analgesics (e.g. codeine), paracetamol, serotonin re-uptake inhibitor antidepressants (SSRIs, SNRIs), and tricyclic antidepressants (other than amitriptyline). PMID:26859719

Drug sales data analysis for outbreak detection of infectious diseases: a systematic literature review.

PubMed

Pivette, Mathilde; Mueller, Judith E; Crépey, Pascal; Bar-Hen, Avner

2014-11-18

This systematic literature review aimed to summarize evidence for the added value of drug sales data analysis for the surveillance of infectious diseases. A search for relevant publications was conducted in Pubmed, Embase, Scopus, Cochrane Library, African Index Medicus and Lilacs databases. Retrieved studies were evaluated in terms of objectives, diseases studied, data sources, methodologies and performance for real-time surveillance. Most studies compared drug sales data to reference surveillance data using correlation measurements or indicators of outbreak detection performance (sensitivity, specificity, timeliness of the detection). We screened 3266 articles and included 27 in the review. Most studies focused on acute respiratory and gastroenteritis infections. Nineteen studies retrospectively compared drug sales data to reference clinical data, and significant correlations were observed in 17 of them. Four studies found that over-the-counter drug sales preceded clinical data in terms of incidence increase. Five studies developed and evaluated statistical algorithms for selecting drug groups to monitor specific diseases. Another three studies developed models to predict incidence increase from drug sales. Drug sales data analyses appear to be a useful tool for surveillance of gastrointestinal and respiratory disease, and OTC drugs have the potential for early outbreak detection. Their utility remains to be investigated for other diseases, in particular those poorly surveyed.

The impact of substance abuse on mortality in patients with severe traumatic brain injury.

PubMed

O'Phelan, Kristine; McArthur, David L; Chang, Cherylee W J; Green, Deborah; Hovda, David A

2008-09-01

Drug and alcohol use are common in neurotrauma patients. Despite growing methamphetamine use there are few studies of the impact of methamphetamine use on outcome after traumatic brain injury (TBI). We conducted a retrospective review of 5-years of data from a trauma database. Inclusion criteria included severe TBI and diagnosis codes indicating head injury. The entire database was analyzed and then a subset of patients with complete toxicology data were examined separately. Primary outcome was mortality. Four hundred eighty-three patients were included. Toxicology results were available for 52.6% of patients. Alcohol, amphetamines, and cannabis were the most commonly detected substances. Overall mortality was 50.9%. When the group with complete tox screen data were analyzed, a toxicology screen that was positive for alcohol or amphetamine was associated with decreased mortality with an odds ratio of 0.23 (CI: 0.10-0.56, p = 0.001) and 0.25 (CI: 0.08-0.79, p = 0.02), respectively. When the subset of patients for whom toxicology data were available was analyzed the amphetamine-positive group was more likely to use cannabis and less likely to use alcohol. We unexpectedly found alcohol and methamphetamine use to be associated with decreased mortality. Neurotoxic and possible neuroprotective mechanisms of these substances are discussed as well as possible interactions between cannabis and methamphetamine. The potential influence of psycho-social factors are also considered. Prospective studies are needed to further investigate the effects of drug and alcohol use on outcome after severe TBI.

3D pharmacophore-based virtual screening, docking and density functional theory approach towards the discovery of novel human epidermal growth factor receptor-2 (HER2) inhibitors.

PubMed

Gogoi, Dhrubajyoti; Baruah, Vishwa Jyoti; Chaliha, Amrita Kashyap; Kakoti, Bibhuti Bhushan; Sarma, Diganta; Buragohain, Alak Kumar

2016-12-21

Human epidermal growth factor receptor 2 (HER2) is one of the four members of the epidermal growth factor receptor (EGFR) family and is expressed to facilitate cellular proliferation across various tissue types. Therapies targeting HER2, which is a transmembrane glycoprotein with tyrosine kinase activity, offer promising prospects especially in breast and gastric/gastroesophageal cancer patients. Persistence of both primary and acquired resistance to various routine drugs/antibodies is a disappointing outcome in the treatment of many HER2 positive cancer patients and is a challenge that requires formulation of new and improved strategies to overcome the same. Identification of novel HER2 inhibitors with improved therapeutics index was performed with a highly correlating (r=0.975) ligand-based pharmacophore model (Hypo1) in this study. Hypo1 was generated from a training set of 22 compounds with HER2 inhibitory activity and this well-validated hypothesis was subsequently used as a 3D query to screen compounds in a total of four databases of which two were natural product databases. Further, these compounds were analyzed for compliance with Veber's drug-likeness rule and optimum ADMET parameters. The selected compounds were then subjected to molecular docking and Density Functional Theory (DFT) analysis to discern their molecular interactions at the active site of HER2. The findings thus presented would be an important starting point towards the development of novel HER2 inhibitors using well-validated computational techniques. Copyright © 2016 Elsevier Ltd. All rights reserved.

A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.

PubMed

Davis, Allan Peter; Wiegers, Thomas C; Roberts, Phoebe M; King, Benjamin L; Lay, Jean M; Lennon-Hopkins, Kelley; Sciaky, Daniela; Johnson, Robin; Keating, Heather; Greene, Nigel; Hernandez, Robert; McConnell, Kevin J; Enayetallah, Ahmed E; Mattingly, Carolyn J

2013-01-01

Improving the prediction of chemical toxicity is a goal common to both environmental health research and pharmaceutical drug development. To improve safety detection assays, it is critical to have a reference set of molecules with well-defined toxicity annotations for training and validation purposes. Here, we describe a collaboration between safety researchers at Pfizer and the research team at the Comparative Toxicogenomics Database (CTD) to text mine and manually review a collection of 88,629 articles relating over 1,200 pharmaceutical drugs to their potential involvement in cardiovascular, neurological, renal and hepatic toxicity. In 1 year, CTD biocurators curated 254,173 toxicogenomic interactions (152,173 chemical-disease, 58,572 chemical-gene, 5,345 gene-disease and 38,083 phenotype interactions). All chemical-gene-disease interactions are fully integrated with public CTD, and phenotype interactions can be downloaded. We describe Pfizer's text-mining process to collate the articles, and CTD's curation strategy, performance metrics, enhanced data content and new module to curate phenotype information. As well, we show how data integration can connect phenotypes to diseases. This curation can be leveraged for information about toxic endpoints important to drug safety and help develop testable hypotheses for drug-disease events. The availability of these detailed, contextualized, high-quality annotations curated from seven decades' worth of the scientific literature should help facilitate new mechanistic screening assays for pharmaceutical compound survival. This unique partnership demonstrates the importance of resource sharing and collaboration between public and private entities and underscores the complementary needs of the environmental health science and pharmaceutical communities. Database URL: http://ctdbase.org/

Intrathecal Drug Delivery Systems for Noncancer Pain: A Health Technology Assessment.

PubMed

2016-01-01

Intrathecal drug delivery systems can be used to manage refractory or persistent chronic nonmalignant (noncancer) pain. We investigated the benefits, harms, cost-effectiveness, and budget impact of these systems compared with current standards of care for adult patients with chronic pain owing to nonmalignant conditions. We searched Ovid MEDLINE, Ovid Embase, the Cochrane Library, and the National Health Service's Economic Evaluation Database and Tufts Cost-Effectiveness Analysis Registry from January 1994 to April 2014 for evidence of effectiveness, harms, and cost-effectiveness. We used existing systematic reviews that had employed reliable search and screen methods and also searched for studies published after the search date reported in the latest systematic review to identify studies. Two reviewers screened records and assessed study validity. We found comparative evidence of effectiveness and harms in one cohort study at high risk of bias (≥ 3-year follow-up, N = 130). Four economic evaluations of low to very low quality were also included. Compared with oral opioid analgesia alone or a program of analgesia plus rehabilitation, intrathecal drug delivery systems significantly reduced pain (27% additional improvement) and morphine consumption. Despite these reductions, intrathecal drug delivery systems were not superior in patient-reported well-being or quality of life. There is no evidence of superiority of intrathecal drug delivery systems over oral opioids in global pain improvement and global treatment satisfaction. Comparative evidence of harms was not found. Cost-effectiveness evidence is of insufficient quality to assess the appropriateness of funding intrathecal drug delivery systems. Evidence comparing intrathecal drug delivery systems with standard care was of very low quality. Current evidence does not establish (or rule out) superiority or cost-effectiveness of intrathecal drug delivery systems for managing chronic refractory nonmalignant pain. The budget impact of funding intrathecal drug delivery systems would be between $1.5 and $5.0 million per year.

In silico design of fragment-based drug targeting host processing α-glucosidase i for dengue fever

NASA Astrophysics Data System (ADS)

Toepak, E. P.; Tambunan, U. S. F.

2017-02-01

Dengue is a major health problem in the tropical and sub-tropical regions. The development of antiviral that targeting dengue’s host enzyme can be more effective and efficient treatment than the viral enzyme. Host enzyme processing α-glucosidase I has an important role in the maturation process of dengue virus envelope glycoprotein. The inhibition of processing α-glucosidase I can become a promising target for dengue fever treatment. The antiviral approach using in silico fragment-based drug design can generate drug candidates with high binding affinity. In this research, 198.621 compounds were obtained from ZINC15 Biogenic Database. These compounds were screened to find the favorable fragments according to Rules of Three and pharmacological properties. The screening fragments were docked into the active site of processing α-glucosidase I. The potential fragment candidates from the molecular docking simulation were linked with castanospermine (CAST) to generate ligands with a better binding affinity. The Analysis of ligand - enzyme interaction showed ligands with code LRS 22, 28, and 47 have the better binding free energy than the standard ligand. Ligand LRS 28 (N-2-4-methyl-5-((1S,3S,6S,7R,8R,8aR)-1,6,7,8-tetrahydroxyoctahydroindolizin-3-yl) pentyl) indolin-1-yl) propionamide) itself among the other ligands has the lowest binding free energy. Pharmacological properties prediction also showed the ligands LRS 22, 28, and 47 can be promising as the dengue fever drug candidates.

Development of a replicated database of DHCP data for evaluation of drug use.

PubMed Central

Graber, S E; Seneker, J A; Stahl, A A; Franklin, K O; Neel, T E; Miller, R A

1996-01-01

This case report describes development and testing of a method to extract clinical information stored in the Veterans Affairs (VA) Decentralized Hospital Computer System (DHCP) for the purpose of analyzing data about groups of patients. The authors used a microcomputer-based, structured query language (SQL)-compatible, relational database system to replicate a subset of the Nashville VA Hospital's DHCP patient database. This replicated database contained the complete current Nashville DHCP prescription, provider, patient, and drug data sets, and a subset of the laboratory data. A pilot project employed this replicated database to answer questions that might arise in drug-use evaluation, such as identification of cases of polypharmacy, suboptimal drug regimens, and inadequate laboratory monitoring of drug therapy. These database queries included as candidates for review all prescriptions for all outpatients. The queries demonstrated that specific drug-use events could be identified for any time interval represented in the replicated database. PMID:8653451

Development of a replicated database of DHCP data for evaluation of drug use.

PubMed

Graber, S E; Seneker, J A; Stahl, A A; Franklin, K O; Neel, T E; Miller, R A

1996-01-01

This case report describes development and testing of a method to extract clinical information stored in the Veterans Affairs (VA) Decentralized Hospital Computer System (DHCP) for the purpose of analyzing data about groups of patients. The authors used a microcomputer-based, structured query language (SQL)-compatible, relational database system to replicate a subset of the Nashville VA Hospital's DHCP patient database. This replicated database contained the complete current Nashville DHCP prescription, provider, patient, and drug data sets, and a subset of the laboratory data. A pilot project employed this replicated database to answer questions that might arise in drug-use evaluation, such as identification of cases of polypharmacy, suboptimal drug regimens, and inadequate laboratory monitoring of drug therapy. These database queries included as candidates for review all prescriptions for all outpatients. The queries demonstrated that specific drug-use events could be identified for any time interval represented in the replicated database.

A single-question screening test for drug use in primary care.

PubMed

Smith, Peter C; Schmidt, Susan M; Allensworth-Davies, Donald; Saitz, Richard

2010-07-12

Drug use (illicit drug use and nonmedical use of prescription drugs) is common but underrecognized in primary care settings. We validated a single-question screening test for drug use and drug use disorders in primary care. Adult patients recruited from primary care waiting rooms were asked the single screening question, "How many times in the past year have you used an illegal drug or used a prescription medication for nonmedical reasons?" A response of at least 1 time was considered positive for drug use. They were also asked the 10-item Drug Abuse Screening Test (DAST-10). The reference standard was the presence or absence of current (past year) drug use or a drug use disorder (abuse or dependence) as determined by a standardized diagnostic interview. Drug use was also determined by oral fluid testing for common drugs of abuse. Of 394 eligible primary care patients, 286 (73%) completed the interview. The single screening question was 100% sensitive (95% confidence interval [CI], 90.6%-100%) and 73.5% specific (95% CI, 67.7%-78.6%) for the detection of a drug use disorder. It was less sensitive for the detection of self-reported current drug use (92.9%; 95% CI, 86.1%-96.5%) and drug use detected by oral fluid testing or self-report (81.8%; 95% CI, 72.5%-88.5%). Test characteristics were similar to those of the DAST-10 and were affected very little by participant demographic characteristics. The single screening question accurately identified drug use in this sample of primary care patients, supporting the usefulness of this brief screen in primary care.

Efficient discovery of responses of proteins to compounds using active learning

PubMed Central

2014-01-01

Background Drug discovery and development has been aided by high throughput screening methods that detect compound effects on a single target. However, when using focused initial screening, undesirable secondary effects are often detected late in the development process after significant investment has been made. An alternative approach would be to screen against undesired effects early in the process, but the number of possible secondary targets makes this prohibitively expensive. Results This paper describes methods for making this global approach practical by constructing predictive models for many target responses to many compounds and using them to guide experimentation. We demonstrate for the first time that by jointly modeling targets and compounds using descriptive features and using active machine learning methods, accurate models can be built by doing only a small fraction of possible experiments. The methods were evaluated by computational experiments using a dataset of 177 assays and 20,000 compounds constructed from the PubChem database. Conclusions An average of nearly 60% of all hits in the dataset were found after exploring only 3% of the experimental space which suggests that active learning can be used to enable more complete characterization of compound effects than otherwise affordable. The methods described are also likely to find widespread application outside drug discovery, such as for characterizing the effects of a large number of compounds or inhibitory RNAs on a large number of cell or tissue phenotypes. PMID:24884564

Diagnostic accuracy of a two-item screen for drug use developed from the alcohol, smoking and substance involvement screening test (ASSIST).

PubMed

Tiet, Quyen Q; Leyva, Yani; Moos, Rudolf H; Smith, Brandy

2016-07-01

The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) is a screening instrument to detect substance use in primary care (PC). To screen for illicit substances (excluding tobacco and alcohol), the ASSIST consists of 8-57 questions and requires complicated scoring. To improve the efficiency of screening of drug misuse in PC, this study constructed and validated a two-item screen for drug use from the ASSIST. Guided by previous reviews, the ASSIST was revised. Patients were recruited in VA primary care clinics (N=1283). Half of the sample was used to develop the ASSIST-Drug; the other half was used to validate it. The Mini International Neuropsychiatric Interview (MINI) and the Inventory of Drug Use Consequences were the criterion measures. A brief, two-item ASSIST-Drug was constructed. Based on the development sample, the ASSIST-Drug was 94.1% sensitive and 89.6% specific for drug use disorders. Based on the validation sample, it was 95.4% sensitive and 87.8% specific. The ASSIST-Drug also had comparable sensitivity and specificity to identify drug use negative consequences, as well as for diverse subgroups of patients in terms of gender, age, race/ethnicity, marital status, educational levels, and post traumatic stress disorder status. The ASSIST-Drug may be a useful screening tool for PC settings. It is reliable, brief, and easy to remember, administer and score. It is sensitive and specific for drug use disorders and drug use negative consequences, and the predictive properties are consistent across subgroup of patients. Published by Elsevier Ireland Ltd.

A Public-Use, Full-Screen Interface for SPIRES Databases.

ERIC Educational Resources Information Center

Kriz, Harry M.

This paper describes the techniques for implementing a full-screen, custom SPIRES interface for a public-use library database. The database-independent protocol that controls the system is described in detail. Source code for an entire working application using this interface is included. The protocol, with less than 170 lines of procedural code,…

Screening the Medicines for Malaria Venture Pathogen Box across Multiple Pathogens Reclassifies Starting Points for Open-Source Drug Discovery

PubMed Central

Sykes, Melissa L.; Jones, Amy J.; Shelper, Todd B.; Simpson, Moana; Lang, Rebecca; Poulsen, Sally-Ann; Sleebs, Brad E.

2017-01-01

ABSTRACT Open-access drug discovery provides a substantial resource for diseases primarily affecting the poor and disadvantaged. The open-access Pathogen Box collection is comprised of compounds with demonstrated biological activity against specific pathogenic organisms. The supply of this resource by the Medicines for Malaria Venture has the potential to provide new chemical starting points for a number of tropical and neglected diseases, through repurposing of these compounds for use in drug discovery campaigns for these additional pathogens. We tested the Pathogen Box against kinetoplastid parasites and malaria life cycle stages in vitro. Consequently, chemical starting points for malaria, human African trypanosomiasis, Chagas disease, and leishmaniasis drug discovery efforts have been identified. Inclusive of this in vitro biological evaluation, outcomes from extensive literature reviews and database searches are provided. This information encompasses commercial availability, literature reference citations, other aliases and ChEMBL number with associated biological activity, where available. The release of this new data for the Pathogen Box collection into the public domain will aid the open-source model of drug discovery. Importantly, this will provide novel chemical starting points for drug discovery and target identification in tropical disease research. PMID:28674055

Screening the Medicines for Malaria Venture Pathogen Box across Multiple Pathogens Reclassifies Starting Points for Open-Source Drug Discovery.

PubMed

Duffy, Sandra; Sykes, Melissa L; Jones, Amy J; Shelper, Todd B; Simpson, Moana; Lang, Rebecca; Poulsen, Sally-Ann; Sleebs, Brad E; Avery, Vicky M

2017-09-01

Open-access drug discovery provides a substantial resource for diseases primarily affecting the poor and disadvantaged. The open-access Pathogen Box collection is comprised of compounds with demonstrated biological activity against specific pathogenic organisms. The supply of this resource by the Medicines for Malaria Venture has the potential to provide new chemical starting points for a number of tropical and neglected diseases, through repurposing of these compounds for use in drug discovery campaigns for these additional pathogens. We tested the Pathogen Box against kinetoplastid parasites and malaria life cycle stages in vitro Consequently, chemical starting points for malaria, human African trypanosomiasis, Chagas disease, and leishmaniasis drug discovery efforts have been identified. Inclusive of this in vitro biological evaluation, outcomes from extensive literature reviews and database searches are provided. This information encompasses commercial availability, literature reference citations, other aliases and ChEMBL number with associated biological activity, where available. The release of this new data for the Pathogen Box collection into the public domain will aid the open-source model of drug discovery. Importantly, this will provide novel chemical starting points for drug discovery and target identification in tropical disease research. Copyright © 2017 Duffy et al.

A reliable computational workflow for the selection of optimal screening libraries.

PubMed

Gilad, Yocheved; Nadassy, Katalin; Senderowitz, Hanoch

2015-01-01

The experimental screening of compound collections is a common starting point in many drug discovery projects. Successes of such screening campaigns critically depend on the quality of the screened library. Many libraries are currently available from different vendors yet the selection of the optimal screening library for a specific project is challenging. We have devised a novel workflow for the rational selection of project-specific screening libraries. The workflow accepts as input a set of virtual candidate libraries and applies the following steps to each library: (1) data curation; (2) assessment of ADME/T profile; (3) assessment of the number of promiscuous binders/frequent HTS hitters; (4) assessment of internal diversity; (5) assessment of similarity to known active compound(s) (optional); (6) assessment of similarity to in-house or otherwise accessible compound collections (optional). For ADME/T profiling, Lipinski's and Veber's rule-based filters were implemented and a new blood brain barrier permeation model was developed and validated (85 and 74 % success rate for training set and test set, respectively). Diversity and similarity descriptors which demonstrated best performances in terms of their ability to select either diverse or focused sets of compounds from three databases (Drug Bank, CMC and CHEMBL) were identified and used for diversity and similarity assessments. The workflow was used to analyze nine common screening libraries available from six vendors. The results of this analysis are reported for each library providing an assessment of its quality. Furthermore, a consensus approach was developed to combine the results of these analyses into a single score for selecting the optimal library under different scenarios. We have devised and tested a new workflow for the rational selection of screening libraries under different scenarios. The current workflow was implemented using the Pipeline Pilot software yet due to the usage of generic components, it can be easily adapted and reproduced by computational groups interested in rational selection of screening libraries. Furthermore, the workflow could be readily modified to include additional components. This workflow has been routinely used in our laboratory for the selection of libraries in multiple projects and consistently selects libraries which are well balanced across multiple parameters.Graphical abstract.

AHCODA-DB: a data repository with web-based mining tools for the analysis of automated high-content mouse phenomics data.

PubMed

Koopmans, Bastijn; Smit, August B; Verhage, Matthijs; Loos, Maarten

2017-04-04

Systematic, standardized and in-depth phenotyping and data analyses of rodent behaviour empowers gene-function studies, drug testing and therapy design. However, no data repositories are currently available for standardized quality control, data analysis and mining at the resolution of individual mice. Here, we present AHCODA-DB, a public data repository with standardized quality control and exclusion criteria aimed to enhance robustness of data, enabled with web-based mining tools for the analysis of individually and group-wise collected mouse phenotypic data. AHCODA-DB allows monitoring in vivo effects of compounds collected from conventional behavioural tests and from automated home-cage experiments assessing spontaneous behaviour, anxiety and cognition without human interference. AHCODA-DB includes such data from mutant mice (transgenics, knock-out, knock-in), (recombinant) inbred strains, and compound effects in wildtype mice and disease models. AHCODA-DB provides real time statistical analyses with single mouse resolution and versatile suite of data presentation tools. On March 9th, 2017 AHCODA-DB contained 650 k data points on 2419 parameters from 1563 mice. AHCODA-DB provides users with tools to systematically explore mouse behavioural data, both with positive and negative outcome, published and unpublished, across time and experiments with single mouse resolution. The standardized (automated) experimental settings and the large current dataset (1563 mice) in AHCODA-DB provide a unique framework for the interpretation of behavioural data and drug effects. The use of common ontologies allows data export to other databases such as the Mouse Phenome Database. Unbiased presentation of positive and negative data obtained under the highly standardized screening conditions increase cost efficiency of publicly funded mouse screening projects and help to reach consensus conclusions on drug responses and mouse behavioural phenotypes. The website is publicly accessible through https://public.sylics.com and can be viewed in every recent version of all commonly used browsers.

Sequential Application of Ligand and Structure Based Modeling Approaches to Index Chemicals for Their hH4R Antagonism

PubMed Central

Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

2014-01-01

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner. PMID:25330207

Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

PubMed

Pappalardo, Matteo; Shachaf, Nir; Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

2014-01-01

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.

WISDOM-II: screening against multiple targets implicated in malaria using computational grid infrastructures.

PubMed

Kasam, Vinod; Salzemann, Jean; Botha, Marli; Dacosta, Ana; Degliesposti, Gianluca; Isea, Raul; Kim, Doman; Maass, Astrid; Kenyon, Colin; Rastelli, Giulio; Hofmann-Apitius, Martin; Breton, Vincent

2009-05-01

Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery. Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase. In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures. On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed. The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.

In Vitro Drug-Induced Liver Injury Prediction: Criteria Optimization of Efflux Transporter IC50 and Physicochemical Properties.

PubMed

Yucha, Robert W; He, Kan; Shi, Qin; Cai, Lining; Nakashita, Yukie; Xia, Cindy Q; Liao, Mingxiang

2017-06-01

Drug-induced liver injury (DILI) is a severe drug adverse response, which cannot always be reliably predicted in preclinical or clinical studies. Lack of observation of DILI during preclinical and clinical drug development has led to DILI being a leading cause of drug withdrawal from the market. As DILI is potentially fatal, pharmaceutical companies have been developing in vitro tools to screen for potential liver injury. Screens for physicochemical properties, mitochondrial function, and transport protein inhibition have all been employed to varying degrees of success. In vitro inhibition of the bile salt export pump (BSEP) has become a major risk factor for in vivo DILI predictions, yet discrepancies exist in which methods to use and the extent to which BSEP inhibition predicts clinical DILI. The presented work focuses on optimizing DILI predictions by comparing BSEP inhibition via the membrane vesicle assay and the hepatocyte-based BSEPcyte assay, as well as dual and triple liabilities. BSEP transport inhibition of taurcholic acids and glycocholic acids were similar for up to 29 drugs tested, in both the vesicle and hepatocyte-based assays. Positive and negative DILI predictions were optimized at a 50-µM cutoff value for 50 drugs using both NIH Livertox and PharmaPendium databases. Additionally, dual inhibition of BSEP and other efflux transporters (multidrug resistance-associated protein [MRP]2, MRP3, or MRP4) provided no observable predictive benefit compared with BSEP inhibition alone. Eighty-five percent of drugs with high molecular weight (>600 Da), high cLogP (>3), or a daily dose >100 mg and BSEP inhibition were associated with DILI. Triple liability of BSEP inhibition, high molecular weight, and high cLogP attained a 100% positive prediction rate. © The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Urine drug screen

MedlinePlus

Drug screen - urine ... detect the presence of illegal and some prescription drugs in your urine. Their presence may indicate that you recently used these drugs. Some drugs may remain in your system for ...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gragg, Evan James; Middleton, Richard Stephen

This report describes the benefits of the BECCUS screening tools. The goals of this project are to utilize NATCARB database for site screening; enhance NATCARB database; run CO 2-EOR simulations and economic models using updated reservoir data sets (SCO 2T-EOR).

Pharmacophore modeling for identification of anti-IGF-1R drugs and in-vitro validation of fulvestrant as a potential inhibitor

PubMed Central

Hanif, Rumeza; Jabeen, Ishrat; Mansoor, Qaisar; Ismail, Muhammad

2018-01-01

Insulin-like growth factor 1 receptor (IGF-1R) is an important therapeutic target for breast cancer treatment. The alteration in the IGF-1R associated signaling network due to various genetic and environmental factors leads the system towards metastasis. The pharmacophore modeling and logical approaches have been applied to analyze the behaviour of complex regulatory network involved in breast cancer. A total of 23 inhibitors were selected to generate ligand based pharmacophore using the tool, Molecular Operating Environment (MOE). The best model consisted of three pharmacophore features: aromatic hydrophobic (HyD/Aro), hydrophobic (HyD) and hydrogen bond acceptor (HBA). This model was validated against World drug bank (WDB) database screening to identify 189 hits with the required pharmacophore features and was further screened by using Lipinski positive compounds. Finally, the most effective drug, fulvestrant, was selected. Fulvestrant is a selective estrogen receptor down regulator (SERD). This inhibitor was further studied by using both in-silico and in-vitro approaches that showed the targeted effect of fulvestrant in ER+ MCF-7 cells. Results suggested that fulvestrant has selective cytotoxic effect and a dose dependent response on IRS-1, IGF-1R, PDZK1 and ER-α in MCF-7 cells. PDZK1 can be an important inhibitory target using fulvestrant because it directly regulates IGF-1R. PMID:29787591

Prevention of IcaA regulated poly N-acetyl glucosamine formation in Staphylococcus aureus biofilm through new-drug like inhibitors: In silico approach and MD simulation study.

PubMed

Gupta, Ayushi; Mishra, Swechha; Singh, Sangeeta; Mishra, Sonali

2017-09-01

The effectiveness of various ligands against the protein structure of IcaA of the IcaABCD gene locus of Staphylococcus aureus were examined using the approach of structure based drug designing in reference with the protein's efficiency to form biofilms. Four compounds CID42738592, CID90468752, CID24277882, and CID6435208 were secluded from a database of 31,242 inhibitory ligands on the justification of the evaluated values falling under the four - tier structure based virtual screening. Under this principle value of least binding energy, human oral absorption and ADME properties were taken into consideration. Using the Glide module of Schrödinger, the above mentioned ligands showed an effective action against the protein IcaA which showed reduced activity as a glucosaminyl transferase. The complex of protein and ligand with best docking score was chosen for simulation studies. Structure based drug designing for the protein IcaA has given us potential leads as anti - biofilm agents. These screened out ligands might enable the development of new therapeutic strategies aimed at disrupting Staphylococcus aureus biofilms. The complex was showing stability towards the end of time for which it has been put for simulation. Thus molecule could be considered for making of biofilms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Experimentally Validated Novel Inhibitors of Helicobacter pylori Phosphopantetheine Adenylyltransferase Discovered by Virtual High-Throughput Screening

PubMed Central

Cheng, Chao-Sheng; Jia, Kai-Fan; Chen, Ting; Chang, Shun-Ya; Lin, Ming-Shen; Yin, Hsien-Sheng

2013-01-01

Helicobacter pylori is a major etiologic agent associated with the development and maintenance of human gastritis. The goal of this study was to develop novel antibiotics against H. pylori, and we thus targeted H. pylori phosphopantetheine adenylyltransferase (HpPPAT). PPAT catalyzes the penultimate step in coenzyme A biosynthesis. Its inactivation effectively prevents bacterial viability, making it an attractive target for antibacterial drug discovery. We employed virtual high-throughput screening and the HpPPAT crystal structure to identify compounds in the PubChem database that might act as inhibitors of HpPPAT. d-amethopterin is a potential inhibitor for blocking HpPPAT activity and suppressing H. pylori viability. Following treatment with d-amethopterin, H. pylori exhibited morphological characteristics associated with cell death. d-amethopterin is a mixed inhibitor of HpPPAT activity; it simultaneously occupies the HpPPAT 4'-phosphopantetheine- and ATP-binding sites. Its binding affinity is in the micromolar range, implying that it is sufficiently potent to serve as a lead compound in subsequent drug development. Characterization of the d-amethopterin and HpPPAT interaction network in a docked model will allow us to initiate rational drug optimization to improve the inhibitory efficacy of d-amethopterin. We anticipate that novel, potent, and selective HpPPAT inhibitors will emerge for the treatment of H. pylori infection. PMID:24040220

Pharmacophore modeling for identification of anti-IGF-1R drugs and in-vitro validation of fulvestrant as a potential inhibitor.

PubMed

Khalid, Samra; Hanif, Rumeza; Jabeen, Ishrat; Mansoor, Qaisar; Ismail, Muhammad

2018-01-01

Insulin-like growth factor 1 receptor (IGF-1R) is an important therapeutic target for breast cancer treatment. The alteration in the IGF-1R associated signaling network due to various genetic and environmental factors leads the system towards metastasis. The pharmacophore modeling and logical approaches have been applied to analyze the behaviour of complex regulatory network involved in breast cancer. A total of 23 inhibitors were selected to generate ligand based pharmacophore using the tool, Molecular Operating Environment (MOE). The best model consisted of three pharmacophore features: aromatic hydrophobic (HyD/Aro), hydrophobic (HyD) and hydrogen bond acceptor (HBA). This model was validated against World drug bank (WDB) database screening to identify 189 hits with the required pharmacophore features and was further screened by using Lipinski positive compounds. Finally, the most effective drug, fulvestrant, was selected. Fulvestrant is a selective estrogen receptor down regulator (SERD). This inhibitor was further studied by using both in-silico and in-vitro approaches that showed the targeted effect of fulvestrant in ER+ MCF-7 cells. Results suggested that fulvestrant has selective cytotoxic effect and a dose dependent response on IRS-1, IGF-1R, PDZK1 and ER-α in MCF-7 cells. PDZK1 can be an important inhibitory target using fulvestrant because it directly regulates IGF-1R.

Use of HLA-B*58:01 genotyping to prevent allopurinol induced severe cutaneous adverse reactions in Taiwan: national prospective cohort study

PubMed Central

Ko, Tai-Ming; Tsai, Chang-Youh; Chen, Shih-Yang; Chen, Kuo-Shu; Yu, Kuang-Hui; Chu, Chih-Sheng; Huang, Chung-Ming; Wang, Chrong-Reen; Weng, Chia-Tse; Yu, Chia-Li; Hsieh, Song-Chou; Tsai, Jer-Chia; Lai, Wen-Ter; Tsai, Wen-Chan; Yin, Guang-Dar; Ou, Tsan-Teng; Cheng, Kai-Hung; Yen, Jeng-Hsien; Liou, Teh-Ling; Lin, Tsung-Hsien; Chen, Der-Yuan; Hsiao, Pi-Jung; Weng, Meng-Yu; Chen, Yi-Ming; Chen, Chen-Hung; Liu, Ming-Fei; Yen, Hsueh-Wei; Lee, Jia-Jung; Kuo, Mei-Chuan; Wu, Chen-Ching; Hung, Shih-Yuan; Luo, Shue-Fen; Yang, Ya-Hui; Chuang, Hui-Ping; Chou, Yi-Chun; Liao, Hung-Ting; Wang, Chia-Wen; Huang, Chun-Lin; Chang, Chia-Shuo; Lee, Ming-Ta Michael; Chen, Pei; Wong, Chih-Shung; Chen, Chien-Hsiun; Wu, Jer-Yuarn; Chen, Yuan-Tsong

2015-01-01

Objective To evaluate the use of prospective screening for the HLA-B*58:01 allele to identify Taiwanese individuals at risk of severe cutaneous adverse reactions (SCARs) induced by allopurinol treatment. Design National prospective cohort study. Setting 15 medical centres in different regions of Taiwan, from July 2009 to August 2014. Participants 2926 people who had an indication for allopurinol treatment but had not taken allopurinol previously. Participants were excluded if they had undergone a bone marrow transplant, were not of Han Chinese descent, and had a history of allopurinol induced hypersensitivity. DNA purified from 2910 participants’ peripheral blood was used to assess the presence of HLA-B*58:01. Main outcome measures Incidence of allopurinol induced SCARs with and without screening. Results Participants who tested positive for HLA-B*58:01 (19.6%, n=571) were advised to avoid allopurinol, and were referred to an alternate drug treatment or advised to continue with their prestudy treatment. Participants who tested negative (80.4%, n=2339) were given allopurinol. Participants were interviewed once a week for two months to monitor symptoms. The historical incidence of allopurinol induced SCARs, estimated by the National Health Insurance research database of Taiwan, was used for comparison. Mild, transient rash without blisters developed in 97 (3%) participants during follow-up. None of the participants was admitted to hospital owing to adverse drug reactions. SCARs did not develop in any of the participants receiving allopurinol who screened negative for HLA-B*58:01. By contrast, seven cases of SCARs were expected, based on the estimated historical incidence of allopurinol induced SCARs nationwide (0.30% per year, 95% confidence interval 0.28% to 0.31%; P=0.0026; two side one sample binomial test). Conclusions Prospective screening of the HLA-B*58:01 allele, coupled with an alternative drug treatment for carriers, significantly decreased the incidence of allopurinol induced SCARs in Taiwanese medical centres. PMID:26399967

Identification of the active compounds and significant pathways of yinchenhao decoction based on network pharmacology

PubMed Central

Huang, Jihan; Cheung, Fan; Tan, Hor-Yue; Hong, Ming; Wang, Ning; Yang, Juan; Feng, Yibin; Zheng, Qingshan

2017-01-01

Yinchenhao decoction (YCHD) is a traditional Chinese medicine formulation, which has been widely used for the treatment of jaundice for 2,000 years. Currently, YCHD is used to treat various liver disorders and metabolic diseases, however its chemical/pharmacologic profiles remain to be elucidated. The present study identified the active compounds and significant pathways of YCHD based on network pharmacology. All of the chemical ingredients of YCHD were retrieved from the Traditional Chinese Medicine Systems Pharmacology database. Absorption, distribution, metabolism and excretion screening with oral bioavailability (OB) screening, drug-likeness (DL) and intestinal epithelial permeability (Caco-2) evaluation were applied to discover the bioactive compounds in YCHD. Following this, target prediction, pathway identification and network construction were employed to clarify the mechanism of action of YCHD. Following OB screening, and evaluation of DL and Caco-2, 34 compounds in YCHD were identified as potential active ingredients, of which 30 compounds were associated with 217 protein targets. A total of 31 significant pathways were obtained by performing enrichment analyses of 217 proteins using the JEPETTO 3.x plugin, and 16 classes of gene-associated diseases were revealed by performing enrichment analyses using Database for Annotation, Visualization and Integrated Discovery v6.7. The present study identified potential active compounds and significant pathways in YCHD. In addition, the mechanism of action of YCHD in the treatment of various diseases through multiple pathways was clarified. PMID:28791364

Discovery of novel InhA reductase inhibitors: application of pharmacophore- and shape-based screening approach.

PubMed

Kumar, Uday Chandra; Bvs, Suneel Kumar; Mahmood, Shaik; D, Sriram; Kumar-Sahu, Prashanta; Pulakanam, Sridevi; Ballell, Lluís; Alvarez-Gomez, Daniel; Malik, Siddharth; Jarp, Sarma

2013-03-01

InhA is a promising and attractive target in antimycobacterial drug development. InhA is involved in the reduction of long-chain trans-2-enoyl-ACP in the type II fatty acid biosynthesis pathway of Mycobacterium tuberculosis. Recent studies have demonstrated that InhA is one of the targets for the second line antitubercular drug ethionamide. In the current study, we have generated quantitative pharmacophore models using known InhA inhibitors and validated using a large test set. The validated pharmacophore model was used as a query to screen an in-house database of 400,000 compounds and retrieved 25,000 hits. These hits were further ranked based on its shape and feature similarity with potent InhA inhibitor using rapid overlay of chemical structures (OpenEye™) and subsequent hits were subjected for docking. Based on the pharmacophore, rapid overlay of chemical structures model and docking interactions, 32 compounds with more than eight chemotypes were selected, purchased and assayed for InhA inhibitory activity. Out of the 32 compounds, 28 demonstrated 10-38% inhibition against InhA at 10 µM. Further optimization of these analogues is in progress and will update in due course.

LactMed: New NLM Database on Drugs and Lactation

MedlinePlus

... Issues Research News From NIH LactMed: New NLM Database on Drugs and Lactation Past Issues / Summer 2006 ... Javascript on. Photo: Comstock LactMed, a free online database with information on drugs and lactation, is one ...

A population-based study of chronic hepatitis C in immigrants and non-immigrants in Quebec, Canada.

PubMed

Greenaway, Christina; Azoulay, Laurent; Allard, Robert; Cox, Joseph; Tran, Viet Anh; Abou Chakra, Claire Nour; Steele, Russ; Klein, Marina

2017-02-13

Immigrants originating from intermediate and high HCV prevalence countries may be at increased risk of exposure to hepatitis C infection (HCV) in their countries of origin, however they are not routinely screened after arrival in most low HCV prevalence host countries. We aimed to describe the epidemiology of HCV in immigrants compared to the Canadian born population. Using the reportable infectious disease database linked to the landed immigration database and several provincial administrative databases, we assembled a cohort of all reported cases of HCV in Quebec, Canada (1998-2008). Underlying co-morbidities were identified in the health services databases. Stratum specific rates of reported cases/100,000, rate ratios (RRs) and trends over the study period were estimated. A total of 20,862 patients with HCV were identified, among whom 1922 (9.2%) were immigrants. Immigrants were older and diagnosed a mean of 9.8 ± 7 years after arrival. The Canadian born population was more likely to have behavior co-morbidities (problematic alcohol or drug use) and HIV co-infection. Immigrants from Sub-Saharan Africa, Asia and Eastern Europe had the highest HCV reported rates with RRs compared to non-immigrants ranging from 1.5 to 1.7. The age and sex adjusted rates decreased by 4.9% per year in non-immigrants but remained unchanged in immigrants. The proportion of HCV occurring in immigrants doubled over the study period from 5 to 11%. Immigrants from intermediate and high HCV prevalence countries are at increased risk for HCV and had a mean delay in diagnosis of almost 10 years after arrival suggesting that they may benefit from targeted HCV screening and earlier linkage to care.

Discovery of Novel ROCK1 Inhibitors via Integrated Virtual Screening Strategy and Bioassays

PubMed Central

Shen, Mingyun; Tian, Sheng; Pan, Peichen; Sun, Huiyong; Li, Dan; Li, Youyong; Zhou, Hefeng; Li, Chuwen; Lee, Simon Ming-Yuen; Hou, Tingjun

2015-01-01

Rho-associated kinases (ROCKs) have been regarded as promising drug targets for the treatment of cardiovascular diseases, nervous system diseases and cancers. In this study, a novel integrated virtual screening protocol by combining molecular docking and pharmacophore mapping based on multiple ROCK1 crystal structures was utilized to screen the ChemBridge database for discovering potential inhibitors of ROCK1. Among the 38 tested compounds, seven of them exhibited significant inhibitory activities of ROCK1 (IC50 < 10 μM) and the most potent one (compound TS-f22) with the novel scaffold of 4-Phenyl-1H-pyrrolo [2,3-b] pyridine had an IC50 of 480 nM. Then, the structure-activity relationships of 41 analogues of TS-f22 were examined. Two potent inhibitors were proven effective in inhibiting the phosphorylation of the downstream target in the ROCK signaling pathway in vitro and protecting atorvastatin-induced cerebral hemorrhage in vivo. The high hit rate (28.95%) suggested that the integrated virtual screening strategy was quite reliable and could be used as a powerful tool for identifying promising active compounds for targets of interest. PMID:26568382

Discovery of Novel ROCK1 Inhibitors via Integrated Virtual Screening Strategy and Bioassays.

PubMed

Shen, Mingyun; Tian, Sheng; Pan, Peichen; Sun, Huiyong; Li, Dan; Li, Youyong; Zhou, Hefeng; Li, Chuwen; Lee, Simon Ming-Yuen; Hou, Tingjun

2015-11-16

Rho-associated kinases (ROCKs) have been regarded as promising drug targets for the treatment of cardiovascular diseases, nervous system diseases and cancers. In this study, a novel integrated virtual screening protocol by combining molecular docking and pharmacophore mapping based on multiple ROCK1 crystal structures was utilized to screen the ChemBridge database for discovering potential inhibitors of ROCK1. Among the 38 tested compounds, seven of them exhibited significant inhibitory activities of ROCK1 (IC50 < 10 μM) and the most potent one (compound TS-f22) with the novel scaffold of 4-Phenyl-1H-pyrrolo [2,3-b] pyridine had an IC50 of 480 nM. Then, the structure-activity relationships of 41 analogues of TS-f22 were examined. Two potent inhibitors were proven effective in inhibiting the phosphorylation of the downstream target in the ROCK signaling pathway in vitro and protecting atorvastatin-induced cerebral hemorrhage in vivo. The high hit rate (28.95%) suggested that the integrated virtual screening strategy was quite reliable and could be used as a powerful tool for identifying promising active compounds for targets of interest.

Databases in the Area of Pharmacogenetics

PubMed Central

Sim, Sarah C.; Altman, Russ B.; Ingelman-Sundberg, Magnus

2012-01-01

In the area of pharmacogenetics and personalized health care it is obvious that databases, providing important information of the occurrence and consequences of variant genes encoding drug metabolizing enzymes, drug transporters, drug targets, and other proteins of importance for drug response or toxicity, are of critical value for scientists, physicians, and industry. The primary outcome of the pharmacogenomic field is the identification of biomarkers that can predict drug toxicity and drug response, thereby individualizing and improving drug treatment of patients. The drug in question and the polymorphic gene exerting the impact are the main issues to be searched for in the databases. Here, we review the databases that provide useful information in this respect, of benefit for the development of the pharmacogenomic field. PMID:21309040

Analysis for identification in amnesty bin samples from dance venues.

PubMed

Kenyon, Susannah L; Ramsey, John D; Lee, Terry; Johnston, Atholl; Holt, David W

2005-12-01

The analysis of unknown substances discarded in amnesty bins, first described by Ramsey et al, from a large central London club and 7 smaller clubs in Manchester, UK are described. The contents of the bins were collected between July 2003 and March 2004. Solid dosage formulations were identified using the TICTAC database, chemical tests, and GC-MS screening. Drugs that could not be readily identified were subjected to other analytical techniques. The goal was to document the current range of drugs available on the dance scene and compare the findings between the London club, which had been the subject of a previous survey, and Manchester clubs. More than 1000 tablets, capsules, and powder doses were discarded in the amnesty bins. Tablets containing only MDMA (ecstasy) were found to be >94% and >84% of the total in London and Manchester, respectively. Although the quantities of tablets and powders recovered were different between London and Manchester, the proportions of the drugs were remarkably similar. The most common drugs found in powders in London and Manchester respectively were cocaine (29%, 40%), amphetamine (25%, 26%), ketamine (19%, 20%), and MDMA (19%, 11%).

A literature review: polypharmacy protocol for primary care.

PubMed

Skinner, Mary

2015-01-01

The purpose of this literature review is to critically evaluate published protocols on polypharmacy in adults ages 65 and older that are currently used in primary care settings that may potentially lead to fewer adverse drug events. A review of OVID, CINAHL, EBSCO, Cochrane Library, Medline, and PubMed databases was completed using the following key words: protocol, guideline, geriatrics, elderly, older adult, polypharmacy, and primary care. Inclusion criteria were: articles in medical, nursing, and pharmacology journals with an intervention, protocol, or guideline addressing polypharmacy that lead to fewer adverse drug events. Qualitative and quantitative studies were included. Exclusion criteria were: publications prior to the year 1992. A gap exists in the literature. No standardized protocol for addressing polypharmacy in the primary care setting was found. Mnemonics, algorithms, clinical practice guidelines, and clinical strategies for addressing polypharmacy in a variety of health care settings were found throughout the literature. Several screening instruments for use in primary care to assess potentially inappropriate prescription of medications in the elderly, such as the Beers Criteria and the STOPP screening tool, were identified. However, these screening instruments were not included in a standardized protocol to manage polypharmacy in primary care. Polypharmacy in the elderly is a critical problem that may result in adverse drug events such as falls, hospitalizations, and increased expenditures for both the patient and the health care system. No standardized protocols to address polypharmacy specific to the primary care setting were identified in this review of the literature. Given the growing population of elderly in this country and the high number of medications they consume, it is critical to focus on the utilization of a standardized protocol to address the potential harm of polypharmacy in the primary care setting and evaluate its effects on patient outcomes. Copyright © 2015 Elsevier Inc. All rights reserved.

Work-related injuries in a state trauma registry: relationship between industry and drug screening.

PubMed

Bunn, Terry L; Slavova, Svetla; Bernard, Andrew C

2014-08-01

Work-related injuries exert a great financial and economic burden on the US population. The study objectives were to identify the industries and occupations associated with worker injuries and to determine the predictors for injured worker drug screening in trauma centers. Work-related injury cases were selected using three criteria (expected payer source of workers' compensation, industry-related e-codes, and work-related indicator) from the Kentucky Trauma Registry data set for years 2008 to 2012. Descriptive analyses and multiple logistic regression were performed on the work-related injury cases. The "other services" and construction industry sectors accounted for the highest number of work-related cases. Drugs were detected in 55% of all drug-screened work-related trauma cases. Higher percentages of injured workers tested positive for drugs in the natural resources and mining, transportation and public utilities, and construction industries. In comparison, higher percentages of injured workers in the other services as well as transportation and public utilities industries were drug screened. Treatment at Level I trauma centers and Glasgow Coma Scale (GCS) scores indicating a coma or severe brain injury were both significant independent predictors for being screened for drugs; industry was not a significant predictor for being drug screened. The injured worker was more likely to be drug screened if the worker had a greater than mild injury, regardless of whether the worker was an interfacility transfer. These findings indicate that there may be elevated drug use or abuse in natural resources and mining, transportation and public utilities, as well as construction industry workers; improved identification of the specific drug types in positive drug screen results of injured workers is needed to better target prevention efforts. Epidemiologic study, level III.

Computer-aided design of liposomal drugs: In silico prediction and experimental validation of drug candidates for liposomal remote loading.

PubMed

Cern, Ahuva; Barenholz, Yechezkel; Tropsha, Alexander; Goldblum, Amiram

2014-01-10

Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs' structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al., J. Control. Release 160 (2012) 147-157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-Nearest Neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used by us in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs. © 2013.

Use of a single alcohol screening question to identify other drug use.

PubMed

Smith, Peter C; Cheng, Debbie M; Allensworth-Davies, Donald; Winter, Michael R; Saitz, Richard

2014-06-01

People who consume unhealthy amounts of alcohol are more likely to use illicit drugs. We tested the ability of a screening test for unhealthy alcohol use to simultaneously detect drug use. Adult English speaking patients (n=286) were enrolled from a primary care waiting room. They were asked the screening question for unhealthy alcohol use "How many times in the past year have you had X or more drinks in a day?", where X is 5 for men and 4 for women, and a response of one or more is considered positive. A standard diagnostic interview was used to determine current (past year) drug use or a drug use disorder (abuse or dependence). Oral fluid testing was also used to detect recent use of common drugs of abuse. The single screening question for unhealthy alcohol use was 67.6% sensitive (95% confidence interval [CI], 50.2-82.0%) and 64.7% specific (95% CI, 58.4-70.6%) for the detection of a drug use disorder. It was similarly insensitive for drug use detected by oral fluid testing and/or self-report. Although a patient with a drug use disorder has twice the odds of screening positive for unhealthy alcohol use compared to one without a drug use disorder, suggesting patients who screen positive for alcohol should be asked about drug use, a single screening question for unhealthy alcohol use was not sensitive or specific for the detection of other drug use or drug use disorders in a sample of primary care patients. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Data integration and warehousing: coordination between newborn screening and related public health programs.

PubMed

Therrell, Bradford L

2003-01-01

At birth, patient demographic and health information begin to accumulate in varied databases. There are often multiple sources of the same or similar data. New public health programs are often created without considering data linkages. Recently, newborn hearing screening (NHS) programs and immunization programs have virtually ignored the existence of newborn dried blood spot (DBS) newborn screening databases containing similar demographic data, creating data duplication in their 'new' systems. Some progressive public health departments are developing data warehouses of basic, recurrent patient information, and linking these databases to other health program databases where programs and services can benefit from such linkages. Demographic data warehousing saves time (and money) by eliminating duplicative data entry and reducing the chances of data errors. While newborn screening data are usually the first data available, they should not be the only data source considered for early data linkage or for populating a data warehouse. Birth certificate information should also be considered along with other data sources for infants that may not have received newborn screening or who may have been born outside of the jurisdiction and not have birth certificate information locally available. This newborn screening serial number provides a convenient identification number for use in the DBS program and for linking with other systems. As a minimum, data linkages should exist between newborn dried blood spot screening, newborn hearing screening, immunizations, birth certificates and birth defect registries.

Microfluidics-assisted in vitro drug screening and carrier production

PubMed Central

Tsui, Jonathan H.; Lee, Woohyuk; Pun, Suzie H.; Kim, Jungkyu; Kim, Deok-Ho

2013-01-01

Microfluidic platforms provide several unique advantages for drug development. In the production of drug carriers, physical properties such as size and shape, and chemical properties such as drug composition and pharmacokinetic parameters, can be modified simply and effectively by tuning the flow rate and geometries. Large numbers of carriers can then be fabricated with minimal effort and with little to no batch-to-batch variation. Additionally, cell or tissue culture models in microfluidic systems can be used as in vitro drug screening tools. Compared to in vivo animal models, microfluidic drug screening platforms allow for high-throughput and reproducible screening at a significantly lower cost, and when combined with current advances in tissue engineering, are also capable of mimicking native tissues. In this review, various microfluidic platforms for drug and gene carrier fabrication are reviewed to provide guidelines for designing appropriate carriers. In vitro microfluidic drug screening platforms designed for high-throughput analysis and replication of in vivo conditions are also reviewed to highlight future directions for drug research and development. PMID:23856409

Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches.

PubMed

Luo, Yao; Wang, Ling

2017-11-16

The mammalian target of rapamycin (mTOR) is a central controller of cell growth, proliferation, metabolism, and angiogenesis. This protein is an attractive target for new anticancer drug development. Significant progress has been made in hit discovery, lead optimization, drug candidate development and determination of the three-dimensional (3D) structure of mTOR. Computational methods have been applied to accelerate the discovery and development of mTOR inhibitors helping to model the structure of mTOR, screen compound databases, uncover structure-activity relationship (SAR) and optimize the hits, mine the privileged fragments and design focused libraries. Besides, computational approaches were also applied to study protein-ligand interactions mechanisms and in natural product-driven drug discovery. Herein, we survey the most recent progress on the application of computational approaches to advance the discovery and development of compounds targeting mTOR. Future directions in the discovery of new mTOR inhibitors using computational methods are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Access to digital library databases in higher education: design problems and infrastructural gaps.

PubMed

Oswal, Sushil K

2014-01-01

After defining accessibility and usability, the author offers a broad survey of the research studies on digital content databases which have thus far primarily depended on data drawn from studies conducted by sighted researchers with non-disabled users employing screen readers and low vision devices. This article aims at producing a detailed description of the difficulties confronted by blind screen reader users with online library databases which now hold most of the academic, peer-reviewed journal and periodical content essential for research and teaching in higher education. The approach taken here is borrowed from descriptive ethnography which allows the author to create a complete picture of the accessibility and usability problems faced by an experienced academic user of digital library databases and screen readers. The author provides a detailed analysis of the different aspects of accessibility issues in digital databases under several headers with a special focus on full-text PDF files. The author emphasizes that long-term studies with actual, blind screen reader users employing both qualitative and computerized research tools can yield meaningful data for the designers and developers to improve these databases to a level that they begin to provide an equal access to the blind.

Clinical decision support tools: performance of personal digital assistant versus online drug information databases.

PubMed

Clauson, Kevin A; Polen, Hyla H; Marsh, Wallace A

2007-12-01

To evaluate personal digital assistant (PDA) drug information databases used to support clinical decision-making, and to compare the performance of PDA databases with their online versions. Prospective evaluation with descriptive analysis. Five drug information databases available for PDAs and online were evaluated according to their scope (inclusion of correct answers), completeness (on a 3-point scale), and ease of use; 158 question-answer pairs across 15 weighted categories of drug information essential to health care professionals were used to evaluate these databases. An overall composite score integrating these three measures was then calculated. Scores for the PDA databases and for each PDA-online pair were compared. Among the PDA databases, composite rankings, from highest to lowest, were as follows: Lexi-Drugs, Clinical Pharmacology OnHand, Epocrates Rx Pro, mobileMicromedex (now called Thomson Clinical Xpert), and Epocrates Rx free version. When we compared database pairs, online databases that had greater scope than their PDA counterparts were Clinical Pharmacology (137 vs 100 answers, p<0.001), Micromedex (132 vs 96 answers, p<0.001), Lexi-Comp Online (131 vs 119 answers, p<0.001), and Epocrates Online Premium (103 vs 98 answers, p=0.001). Only Micromedex online was more complete than its PDA version (p=0.008). Regarding ease of use, the Lexi-Drugs PDA database was superior to Lexi-Comp Online (p<0.001); however, Epocrates Online Premium, Epocrates Online Free, and Micromedex online were easier to use than their PDA counterparts (p<0.001). In terms of composite scores, only the online versions of Clinical Pharmacology and Micromedex demonstrated superiority over their PDA versions (p>0.01). Online and PDA drug information databases assist practitioners in improving their clinical decision-making. Lexi-Drugs performed significantly better than all of the other PDA databases evaluated. No PDA database demonstrated superiority to its online counterpart; however, the online versions of Clinical Pharmacology and Micromedex were superior to their PDA versions in answering questions.

Creating and virtually screening databases of fluorescently-labelled compounds for the discovery of target-specific molecular probes

NASA Astrophysics Data System (ADS)

Kamstra, Rhiannon L.; Dadgar, Saedeh; Wigg, John; Chowdhury, Morshed A.; Phenix, Christopher P.; Floriano, Wely B.

2014-11-01

Our group has recently demonstrated that virtual screening is a useful technique for the identification of target-specific molecular probes. In this paper, we discuss some of our proof-of-concept results involving two biologically relevant target proteins, and report the development of a computational script to generate large databases of fluorescence-labelled compounds for computer-assisted molecular design. The virtual screening of a small library of 1,153 fluorescently-labelled compounds against two targets, and the experimental testing of selected hits reveal that this approach is efficient at identifying molecular probes, and that the screening of a labelled library is preferred over the screening of base compounds followed by conjugation of confirmed hits. The automated script for library generation explores the known reactivity of commercially available dyes, such as NHS-esters, to create large virtual databases of fluorescence-tagged small molecules that can be easily synthesized in a laboratory. A database of 14,862 compounds, each tagged with the ATTO680 fluorophore was generated with the automated script reported here. This library is available for downloading and it is suitable for virtual ligand screening aiming at the identification of target-specific fluorescent molecular probes.

Comparing the outcomes of two strategies for colorectal tumor detection: policy-promoted screening program versus health promotion service.

PubMed

Wu, Ping-Hsiu; Lin, Yu-Min; Liao, Chao-Sheng; Chang, Hung-Chuen; Chen, Yu-Hung; Yang, Kuo-Ching; Shih, Chia-Hui

2013-06-01

The Taiwanese government has proposed a population-based colorectal tumor detection program for the average-risk population. This study's objectives were to understand the outcomes of these screening policies and to evaluate the effectiveness of the program. We compared two databases compiled in one medical center. The "policy-promoted cancer screening" (PPS) database was built on the basis of the policy of the Taiwan Bureau of National Health Insurance for cancer screening. The "health promotion service" (HPS) database was built to provide health check-ups for self-paid volunteers. Both the PPS and HPS databases employ the immunochemical fecal occult blood test (iFOBT) and colonoscopy for colorectal tumor screening using different strategies. A comparison of outcomes between the PPS and HPS included: (1) quality indicators-compliance rate, cecum reaching rate, and tumor detection rate; and (2) validity indicators-sensitivity, specificity, positive, and negative predictive values for detecting colorectal neoplasms. A total of 10,563 and 1481 individuals were enrolled in PPS and HPS, respectively. Among quality indicators, there was no statistically significant difference in the cecum reaching rate between PPS and HPS. The compliance rates were 56.1% for PPS and 91.8% for HPS (p < 0.001). The advanced adenoma detection rates of PPS and HPS were 1.0% and 3.6%, respectively (p < 0.01). The carcinoma detection rates were 0.3% and 0.4%, respectively (p = 0.59). For validity indicators, PPS provides only a positive predictive value for colorectal tumor detection. HPS provides additional validity indicators, including sensitivity, specificity, positive predictive value, and negative predictive value, for colorectal tumor screening. In comparison with the outcomes of the HPS database, the screening efficacy of the PPS database is even for detecting colorectal carcinoma but is limited in detecting advanced adenoma. HPS may provide comprehensive validity indicators and will be helpful in adjusting current policies for improving screening performance. Copyright © 2013. Published by Elsevier B.V.

Discovery of novel polyamine analogs with anti-protozoal activity by computer guided drug repositioning

NASA Astrophysics Data System (ADS)

Alberca, Lucas N.; Sbaraglini, María L.; Balcazar, Darío; Fraccaroli, Laura; Carrillo, Carolina; Medeiros, Andrea; Benitez, Diego; Comini, Marcelo; Talevi, Alan

2016-04-01

Chagas disease is a parasitic infection caused by the protozoa Trypanosoma cruzi that affects about 6 million people in Latin America. Despite its sanitary importance, there are currently only two drugs available for treatment: benznidazole and nifurtimox, both exhibiting serious adverse effects and limited efficacy in the chronic stage of the disease. Polyamines are ubiquitous to all living organisms where they participate in multiple basic functions such as biosynthesis of nucleic acids and proteins, proliferation and cell differentiation. T. cruzi is auxotroph for polyamines, which are taken up from the extracellular medium by efficient transporters and, to a large extent, incorporated into trypanothione (bis-glutathionylspermidine), the major redox cosubstrate of trypanosomatids. From a 268-compound database containing polyamine analogs with and without inhibitory effect on T. cruzi we have inferred classificatory models that were later applied in a virtual screening campaign to identify anti-trypanosomal compounds among drugs already used for other therapeutic indications (i.e. computer-guided drug repositioning) compiled in the DrugBank and Sweetlead databases. Five of the candidates identified with this strategy were evaluated in cellular models from different pathogenic trypanosomatids ( T. cruzi wt, T. cruzi PAT12, T. brucei and Leishmania infantum), and in vitro models of aminoacid/polyamine transport assays and trypanothione synthetase inhibition assay. Triclabendazole, sertaconazole and paroxetine displayed inhibitory effects on the proliferation of T. cruzi (epimastigotes) and the uptake of putrescine by the parasite. They also interfered with the uptake of others aminoacids and the proliferation of infective T. brucei and L. infantum (promastigotes). Trypanothione synthetase was ruled out as molecular target for the anti-parasitic activity of these compounds.

Identification of new benzamide inhibitor against α-subunit of tryptophan synthase from Mycobacterium tuberculosis through structure-based virtual screening, anti-tuberculosis activity and molecular dynamics simulations.

PubMed

Naz, Sadia; Farooq, Umar; Ali, Sajid; Sarwar, Rizwana; Khan, Sara; Abagyan, Ruben

2018-03-13

Multi-drug-resistant tuberculosis and extensively drug-resistant tuberculosis has emerged as global health threat, causing millions of deaths worldwide. Identification of new drug candidates for tuberculosis (TB) by targeting novel and less explored protein targets will be invaluable for antituberculosis drug discovery. We performed structure-based virtual screening of eMolecules database against a homology model of relatively unexplored protein target: the α-subunit of tryptophan synthase (α-TRPS) from Mycobacterium tuberculosis essential for bacterial survival. Based on physiochemical properties analysis and molecular docking, the seven candidate compounds were selected and evaluated through whole cell-based activity against the H37Rv strain of M. tuberculosis. A new Benzamide inhibitor against α-subunit of tryptophan synthase (α-TRPS) from M. tuberculosis has been identified causing 100% growth inhibition at 25 μg/ml and visible bactericidal activity at 6 μg/ml. This benzamide inhibitor displayed a good predicted binding score (-48.24 kcal/mol) with the α-TRPS binding pocket and has logP value (2.95) comparable to Rifampicin. Further refinement of docking results and evaluation of inhibitor-protein complex stability were investigated through Molecular dynamic (MD) simulations studies. Following MD simulations, Root mean square deviation, Root mean square fluctuation and secondary structure analysis confirmed that protein did not unfold and ligand stayed inside the active pocket of protein during the explored time scale. This identified benzamide inhibitor against the α-subunit of TRPS from M. tuberculosis could be considered as candidate for drug discovery against TB and will be further evaluated for enzyme-based inhibition in future studies.

Computational modeling-based discovery of novel classes of anti-inflammatory drugs that target lanthionine synthetase C-like protein 2.

PubMed

Lu, Pinyi; Hontecillas, Raquel; Horne, William T; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R; Lewis, Stephanie N; Bassaganya-Riera, Josep

2012-01-01

Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates.

Computational Modeling-Based Discovery of Novel Classes of Anti-Inflammatory Drugs That Target Lanthionine Synthetase C-Like Protein 2

PubMed Central

Lu, Pinyi; Hontecillas, Raquel; Horne, William T.; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R.; Lewis, Stephanie N.; Bassaganya-Riera, Josep

2012-01-01

Background Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. Methodology/Principal Findings The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. Conclusions/Significance LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates. PMID:22509338

Is electroconvulsive therapy effective as augmentation in clozapine-resistant schizophrenia?

PubMed

Kittsteiner Manubens, Lucas; Lobos Urbina, Diego; Aceituno, David

2016-10-14

Clozapine is considered to be the most effective antipsychotic drug for patients with treatment resistant schizophrenia, but up to a third of the patients do not respond to this treatment. Various strategies have been tried to augment the effect of clozapine in non-responders, one of these strategies being electroconvulsive therapy. However, its efficacy and safety are not yet clear. Searching in Epistemonikos database, which is maintained by screening 30 databases, we identified six systematic reviews including 55 studies, among them six randomized controlled trials addressing clozapine-resistant schizophrenia. We combined the evidence using meta-analysis and generated a summary of findings following the GRADE approach. We concluded electroconvulsive therapy probably augments response to clozapine in patients with treatment resistant schizophrenia, but it is not possible to determine if it leads to cognitive adverse effects because the certainty of the evidence is very low.

A Virtual Screening Approach For Identifying Plants with Anti H5N1 Neuraminidase Activity

PubMed Central

2016-01-01

Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here, we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were selected for experimental evaluation. Twelve specific compounds isolated from these five plants were shown to inhibit neuraminidase, including two compounds with IC50 values less than 92 μM. Furthermore, four of the 12 isolated compounds had also been identified in the top 100 compounds from the virtual screen. Together, these results suggest an effective new approach for identifying bioactive plant species that will further the identification of new pharmacologically active compounds from diverse natural-product resources. PMID:25555059

Discovery of a quorum-sensing inhibitor of drug-resistant staphylococcal infections by structure-based virtual screening.

PubMed

Kiran, Madanahally D; Adikesavan, Nallini Vijayarangan; Cirioni, Oscar; Giacometti, Andrea; Silvestri, Carmela; Scalise, Giorgio; Ghiselli, Roberto; Saba, Vittorio; Orlando, Fiorenza; Shoham, Menachem; Balaban, Naomi

2008-05-01

Staphylococci are a major health threat because of increasing resistance to antibiotics. An alternative to antibiotic treatment is preventing virulence by inhibition of bacterial cell-to-cell communication using the quorum-sensing inhibitor RNAIII-inhibiting peptide (RIP). In this work, we identified 2',5-di-O-galloyl-d-hamamelose (hamamelitannin) as a nonpeptide analog of RIP by virtual screening of a RIP-based pharmacophore against a database of commercially available small-molecule compounds. Hamamelitannin is a natural product found in the bark of Hamamelis virginiana (witch hazel), and it has no effect on staphylococcal growth in vitro; but like RIP, it does inhibit the quorum-sensing regulator RNAIII. In a rat graft model, hamamelitannin prevented device-associated infections in vivo, including infections caused by methicillin-resistant Staphylococcus aureus and Staphylococcus epidermidis strains. These findings suggest that hamamelitannin may be used as a suppressor to staphylococcal infections.

Molecular modeling, simulation and virtual screening of MurD ligase protein from Salmonella typhimurium LT2.

PubMed

Samal, Himanshu Bhusan; Das, Jugal Kishore; Mahapatra, Rajani Kanta; Suar, Mrutyunjay

2015-01-01

The Mur enzymes of the peptidoglycan biosynthesis pathway constitute ideal targets for the design of new classes of antimicrobial inhibitors in Gram-negative bacteria. We built a homology model of MurD of Salmonella typhimurium LT2 using MODELLER (9v12) software. 'The homology model was subjected to energy minimization by molecular dynamics (MD) simulation study with GROMACS software for a simulation time of 20 ns in water environment. The model was subjected for virtual screening study from the Zinc Database using Dockblaster software. Inhibition assay for the best inhibitor, 3-(amino methyl)-n-(4-methoxyphenyl) aniline, by flow cytometric analysis revealed the effective inhibition of peptidoglycan biosynthesis. Results from this study provide new insights for the molecular understanding and development of new antibacterial drugs against the pathogen. Copyright © 2015 Elsevier Inc. All rights reserved.

The Development of a Korean Drug Dosing Database

PubMed Central

Kim, Sun Ah; Kim, Jung Hoon; Jang, Yoo Jin; Jeon, Man Ho; Hwang, Joong Un; Jeong, Young Mi; Choi, Kyung Suk; Lee, Iyn Hyang; Jeon, Jin Ok; Lee, Eun Sook; Lee, Eun Kyung; Kim, Hong Bin; Chin, Ho Jun; Ha, Ji Hye; Kim, Young Hoon

2011-01-01

Objectives This report describes the development process of a drug dosing database for ethical drugs approved by the Korea Food & Drug Administration (KFDA). The goal of this study was to develop a computerized system that supports physicians' prescribing decisions, particularly in regards to medication dosing. Methods The advisory committee, comprised of doctors, pharmacists, and nurses from the Seoul National University Bundang Hospital, pharmacists familiar with drug databases, KFDA officials, and software developers from the BIT Computer Co. Ltd. analyzed approved KFDA drug dosing information, defined the fields and properties of the information structure, and designed a management program used to enter dosing information. The management program was developed using a web based system that allows multiple researchers to input drug dosing information in an organized manner. The whole process was improved by adding additional input fields and eliminating the unnecessary existing fields used when the dosing information was entered, resulting in an improved field structure. Results A total of 16,994 drugs sold in the Korean market in July 2009, excluding the exclusion criteria (e.g., radioactivity drugs, X-ray contrast medium), usage and dosing information were made into a database. Conclusions The drug dosing database was successfully developed and the dosing information for new drugs can be continually maintained through the management mode. This database will be used to develop the drug utilization review standards and to provide appropriate dosing information. PMID:22259729

Drug and bioactive molecule screening based on a bioelectrical impedance cell culture platform

PubMed Central

Ramasamy, Sakthivel; Bennet, Devasier; Kim, Sanghyo

2014-01-01

This review will present a brief discussion on the recent advancements of bioelectrical impedance cell-based biosensors, especially the electric cell-substrate impedance sensing (ECIS) system for screening of various bioactive molecules. The different technical integrations of various chip types, working principles, measurement systems, and applications for drug targeting of molecules in cells are highlighted in this paper. Screening of bioactive molecules based on electric cell-substrate impedance sensing is a trial-and-error process toward the development of therapeutically active agents for drug discovery and therapeutics. In general, bioactive molecule screening can be used to identify active molecular targets for various diseases and toxicity at the cellular level with nanoscale resolution. In the innovation and screening of new drugs or bioactive molecules, the activeness, the efficacy of the compound, and safety in biological systems are the main concerns on which determination of drug candidates is based. Further, drug discovery and screening of compounds are often performed in cell-based test systems in order to reduce costs and save time. Moreover, this system can provide more relevant results in in vivo studies, as well as high-throughput drug screening for various diseases during the early stages of drug discovery. Recently, MEMS technologies and integration with image detection techniques have been employed successfully. These new technologies and their possible ongoing transformations are addressed. Select reports are outlined, and not all the work that has been performed in the field of drug screening and development is covered. PMID:25525360

Prevalence of Different Combinations of Antiepileptic Drugs and CNS Drugs in Elderly Home Care Service and Nursing Home Patients in Norway.

PubMed

Halvorsen, Kjell H; Johannessen Landmark, Cecilie; Granas, Anne Gerd

2016-01-01

Introduction. Antiepileptic drugs (AEDs) are used to treat different conditions in elderly patients and are among the drug classes most susceptible to be involved in drug-drug interactions (DDI). The aim of the study was to describe and compare use of AEDs between home care service and nursing home patients, as these patients are not included in nationwide databases of drug utilization. In the combined population, we investigate DDI of AEDs with other central nervous system- (CNS-) active drugs and DDIs involving AEDs in general. Materials and Methods. Point-prevalence study of Norwegian patients in home care services and nursing homes in 2009. At the patient level, we screened for different DDIs involving AEDs. Results. In total, 882 patients (7.8%) of 11,254 patients used AEDs and number of users did not differ between home care services and nursing homes (8.2% versus 7.7%). In the combined population, we identified 436 potential DDIs in 45% of the patients. Conclusions. In a large population of elderly, home care service and nursing home patients do not differ with respect to exposure of AEDs but use more AEDs as compared to the general population of similar age. The risk of DDIs with AEDs and other CNS-active drugs should be taken into consideration and individual clinical evaluations are assessed in this population.

Campania preventability assessment committee: a focus on the preventability of the contrast media adverse drug reactions.

PubMed

Sessa, Maurizio; Rossi, Claudia; Rafaniello, Concetta; Mascolo, Annamaria; Cimmaruta, Daniela; Scavone, Cristina; Fiorentino, Sonia; Grassi, Enrico; Reginelli, Alfonso; Rotondo, Antonio; Sportiello, Liberata

2016-12-01

The current study aims to assess the preventability of the contrast media adverse drug reactions reported through the Campania spontaneous reporting system, identifying the possible limitations emerged in this type of evaluation. All the individual case safety reports validated by the Campania Pharmacovigilance Regional Centre from July 2012 to September 2015 were screened to select those that reported contrast media as suspected drug. Campania Preventability Assessment Committee, in collaboration with clinicians specialized in Radiology, assessed the preventability according to the P-Method, through a case-by-case approach. From July 2012 to September 2015, 13798 cases were inserted by pharmacovigilance managers in the Italian Pharmacovigilance Network database (in the geographical contest of the Campania Region), of which 67 reported contrast media as suspected drug. Five preventable cases were found. The most reported causes for preventability were the inappropriate drug use for the case clinical conditions and the absence of the preventive measure administrated prior to the contrast media administration. Several limitations were found in the evaluation of the critical criteria for the preventability assessment. Educational initiatives will be organized directly to the healthcare professionals involved in the contrast media administration, to promote an appropriate use of the contrast media.

Can Disproportionality Analysis of Post-marketing Case Reports be Used for Comparison of Drug Safety Profiles?

PubMed

Michel, Christiane; Scosyrev, Emil; Petrin, Michael; Schmouder, Robert

2017-05-01

Clinical trials usually do not have the power to detect rare adverse drug reactions. Spontaneous adverse reaction reports as for example available in post-marketing safety databases such as the FDA Adverse Event Reporting System (FAERS) are therefore a valuable source of information to detect new safety signals early. To screen such large data-volumes for safety signals, data-mining algorithms based on the concept of disproportionality have been developed. Because disproportionality analysis is based on spontaneous reports submitted for a large number of drugs and adverse event types, one might consider using these data to compare safety profiles across drugs. In fact, recent publications have promoted this practice, claiming to provide guidance on treatment decisions to healthcare decision makers. In this article we investigate the validity of this approach. We argue that disproportionality cannot be used for comparative drug safety analysis beyond basic hypothesis generation because measures of disproportionality are: (1) missing the incidence denominators, (2) subject to severe reporting bias, and (3) not adjusted for confounding. Hypotheses generated by disproportionality analyses must be investigated by more robust methods before they can be allowed to influence clinical decisions.

A Small-molecule Inhibitor, 5′-O-Tritylthymidine, targets FAK and Mdm-2 Interaction, and Blocks Breast and Colon Tumorigenesis in vivo

PubMed Central

Golubovskaya, Vita; Palma, Nadia L.; Zheng, Min; Ho, Baotran; Magis, Andrew; Ostrov, David; Cance, William G.

2013-01-01

Focal Adhesion Kinase (FAK) is overexpressed in many types of tumors and plays an important role in survival. We developed a novel approach, targeting FAK-protein interactions by computer modeling and screening of NCI small molecule drug database. In this report we targeted FAK and Mdm-2 protein interaction to decrease tumor growth. By macromolecular modeling we found a model of FAK and Mdm-2 interaction and performed screening of >200,000 small molecule compounds from NCI database with drug-like characteristics, targeting the FAK-Mdm-2 interaction. We identified 5′-O-Tritylthymidine, called M13 compound that significantly decreased viability in different cancer cells. M13 was docked into the pocket of FAK and Mdm-2 interaction and was directly bound to the FAK-N terminal domain by ForteBio Octet assay. In addition, M13 compound affected FAK and Mdm-2 levels and decreased complex of FAK and Mdm-2 proteins in breast and colon cancer cells. M13 re-activated p53 activity inhibited by FAK with Mdm-2 promoter. M13 decreased viability, clonogenicity, increased detachment and apoptosis in a dose-dependent manner in BT474 breast and in HCT116 colon cancer cells in vitro. M13 decreased FAK, activated p53 and caspase-8 in both cell lines. In addition, M13 decreased breast and colon tumor growth in vivo. M13 activated p53 and decreased FAK in tumor samples consistent with decreased tumor growth. The data demonstrate a novel approach for targeting FAK and Mdm-2 protein interaction, provide a model of FAK and Mdm-2 interaction, identify M13 compound targeting this interaction and decreasing tumor growth that is critical for future targeted therapeutics. PMID:22292771

Biomimetic three-dimensional tissue models for advanced high-throughput drug screening

PubMed Central

Nam, Ki-Hwan; Smith, Alec S.T.; Lone, Saifullah; Kwon, Sunghoon; Kim, Deok-Ho

2015-01-01

Most current drug screening assays used to identify new drug candidates are 2D cell-based systems, even though such in vitro assays do not adequately recreate the in vivo complexity of 3D tissues. Inadequate representation of the human tissue environment during a preclinical test can result in inaccurate predictions of compound effects on overall tissue functionality. Screening for compound efficacy by focusing on a single pathway or protein target, coupled with difficulties in maintaining long-term 2D monolayers, can serve to exacerbate these issues when utilizing such simplistic model systems for physiological drug screening applications. Numerous studies have shown that cell responses to drugs in 3D culture are improved from those in 2D, with respect to modeling in vivo tissue functionality, which highlights the advantages of using 3D-based models for preclinical drug screens. In this review, we discuss the development of microengineered 3D tissue models which accurately mimic the physiological properties of native tissue samples, and highlight the advantages of using such 3D micro-tissue models over conventional cell-based assays for future drug screening applications. We also discuss biomimetic 3D environments, based-on engineered tissues as potential preclinical models for the development of more predictive drug screening assays for specific disease models. PMID:25385716

Structure based virtual screening of the Ebola virus trimeric glycoprotein using consensus scoring.

PubMed

Onawole, Abdulmujeeb T; Kolapo, Temitope U; Sulaiman, Kazeem O; Adegoke, Rukayat O

2018-02-01

Ebola virus (EBOV) causes zoonotic viral infection with a potential risk of global spread and a highly fatal effect on humans. Till date, no drug has gotten market approval for the treatment of Ebola virus disease (EVD), and this perhaps allows the use of both experimental and computational approaches in the antiviral drug discovery process. The main target of potential vaccines that are recently undergoing clinical trials is trimeric glycoprotein (GP) of the EBOV and its exact crystal structure was used in this structure based virtual screening study, with the aid of consensus scoring to select three possible hit compounds from about 36 million compounds in MCULE's database. Amongst these three compounds, (5R)-5-[[5-(4-chlorophenyl)-1,2,4-oxadiazol-3-yl]methyl]-N-[(4-methoxyphenyl)methyl]-4,5-dihydroisoxazole-3-carboxamide (SC-2, C 21 H 19 ClN 4 O 4 ) showed good features with respect to drug likeness, ligand efficiency metrics, solubility, absorption and distribution properties and non-carcinogenicity to emerge as the most promising compound that can be optimized to lead compound against the GP EBOV. The binding mode showed that SC-2 is well embedded within the trimeric chains of the GP EBOV with molecular interactions with some amino acids. The SC-2 hit compound, upon its optimization to lead, might be a good potential candidate with efficacy against the EBOV pathogen and subsequently receive necessary approval to be used as antiviral drug for the treatment of EVD. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Prospective Virtual Screening Study: Enriching Hit Rates and Designing Focus Libraries To Find Inhibitors of PI3Kδ and PI3Kγ.

PubMed

Damm-Ganamet, Kelly L; Bembenek, Scott D; Venable, Jennifer W; Castro, Glenda G; Mangelschots, Lieve; Peeters, Daniëlle C G; Mcallister, Heather M; Edwards, James P; Disepio, Daniel; Mirzadegan, Taraneh

2016-05-12

Here, we report a high-throughput virtual screening (HTVS) study using phosphoinositide 3-kinase (both PI3Kγ and PI3Kδ). Our initial HTVS results of the Janssen corporate database identified small focused libraries with hit rates at 50% inhibition showing a 50-fold increase over those from a HTS (high-throughput screen). Further, applying constraints based on "chemically intuitive" hydrogen bonds and/or positional requirements resulted in a substantial improvement in the hit rates (versus no constraints) and reduced docking time. While we find that docking scoring functions are not capable of providing a reliable relative ranking of a set of compounds, a prioritization of groups of compounds (e.g., low, medium, and high) does emerge, which allows for the chemistry efforts to be quickly focused on the most viable candidates. Thus, this illustrates that it is not always necessary to have a high correlation between a computational score and the experimental data to impact the drug discovery process.

Virtual Screening Approach of Bacterial Peptide Deformylase Inhibitors Results in New Antibiotics.

PubMed

Merzoug, Amina; Chikhi, Abdelouahab; Bensegueni, Abderrahmane; Boucherit, Hanane; Okay, Sezer

2018-03-01

The increasing resistance of bacteria to antibacterial therapy poses an enormous health problem, it renders the development of new antibacterial agents with novel mechanism of action an urgent need. Peptide deformylase, a metalloenzyme which catalytically removes N-formyl group from N-terminal methionine of newly synthesized polypeptides, is an important target in antibacterial drug discovery. In this study, we report the structure-based virtual screening of ZINC database in order to discover potential hits as bacterial peptide deformylase enzyme inhibitors with more affinity as compared to GSK1322322, previously known inhibitor. After virtual screening, fifteen compounds of the top hits predicted were purchased and evaluated in vitro for their antibacterial activities against one Gram positive (Staphylococcus aureus) and three Gram negative (Escherichia coli, Pseudomonas aeruginosa and Klebsiella. pneumoniae) bacteria in different concentrations by disc diffusion method. Out of these, three compounds, ZINC00039650, ZINC03872971 and ZINC00126407, exhibited significant zone of inhibition. The results obtained were confirmed using the dilution method. Thus, these proposed compounds may aid the development of more efficient antibacterial agents. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

PubMed Central

Zhao, Mingzhu; Wei, Dong-Qing

2013-01-01

The traditional Chinese medicine (TCM), which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM. PMID:23818932

Computational Exploration for Lead Compounds That Can Reverse the Nuclear Morphology in Progeria

PubMed Central

Baek, Ayoung; Son, Minky; Zeb, Amir; Park, Chanin; Kumar, Raj; Lee, Gihwan; Kim, Donghwan; Choi, Yeonuk; Cho, Yeongrae; Park, Yohan

2017-01-01

Progeria is a rare genetic disorder characterized by premature aging that eventually leads to death and is noticed globally. Despite alarming conditions, this disease lacks effective medications; however, the farnesyltransferase inhibitors (FTIs) are a hope in the dark. Therefore, the objective of the present article is to identify new compounds from the databases employing pharmacophore based virtual screening. Utilizing nine training set compounds along with lonafarnib, a common feature pharmacophore was constructed consisting of four features. The validated Hypo1 was subsequently allowed to screen Maybridge, Chembridge, and Asinex databases to retrieve the novel lead candidates, which were then subjected to Lipinski's rule of 5 and ADMET for drug-like assessment. The obtained 3,372 compounds were forwarded to docking simulations and were manually examined for the key interactions with the crucial residues. Two compounds that have demonstrated a higher dock score than the reference compounds and showed interactions with the crucial residues were subjected to MD simulations and binding free energy calculations to assess the stability of docked conformation and to investigate the binding interactions in detail. Furthermore, this study suggests that the Hits may be more effective against progeria and further the DFT studies were executed to understand their orbital energies. PMID:29226142

Drug screening using model systems: some basics

PubMed Central

2016-01-01

ABSTRACT An increasing number of laboratories that focus on model systems are considering drug screening. Executing a drug screen is complicated enough. But the path for moving initial hits towards the clinic requires a different knowledge base and even a different mindset. In this Editorial I discuss the importance of doing some homework before you start screening. 'Lead hits', 'patentable chemical space' and 'druggability' are all concepts worth exploring when deciding which screening path to take. I discuss some of the lessons I learned that may be useful as you navigate the screening matrix. PMID:27821602

[Progresses in screening active compounds from herbal medicine by affinity chromatography].

PubMed

Feng, Ying-shu; Tong, Shan-shan; Xu, Xi-ming; Yu, Jiang-nan

2015-03-01

Affinity chromatography is a chromatographic method for separating molecules using the binding characteristics of the stationary phase with potential drug molecules. This method can be performed as a high throughput screening method and a chromatographic separation method to screen a variety of active drugs. This paper summarizes the history of affinity chromatography, screening technology of affinity chromatography, and application of affinity chromatography in screening bio-active compounds in herbal medicines, and then discusses its application prospects, in order to broaden applications of the affinity chromatography in drug screening.

The "GeneTrustee": a universal identification system that ensures privacy and confidentiality for human genetic databases.

PubMed

Burnett, Leslie; Barlow-Stewart, Kris; Proos, Anné L; Aizenberg, Harry

2003-05-01

This article describes a generic model for access to samples and information in human genetic databases. The model utilises a "GeneTrustee", a third-party intermediary independent of the subjects and of the investigators or database custodians. The GeneTrustee model has been implemented successfully in various community genetics screening programs and has facilitated research access to genetic databases while protecting the privacy and confidentiality of research subjects. The GeneTrustee model could also be applied to various types of non-conventional genetic databases, including neonatal screening Guthrie card collections, and to forensic DNA samples.

Novel Hybrid Virtual Screening Protocol Based on Molecular Docking and Structure-Based Pharmacophore for Discovery of Methionyl-tRNA Synthetase Inhibitors as Antibacterial Agents

PubMed Central

Liu, Chi; He, Gu; Jiang, Qinglin; Han, Bo; Peng, Cheng

2013-01-01

Methione tRNA synthetase (MetRS) is an essential enzyme involved in protein biosynthesis in all living organisms and is a potential antibacterial target. In the current study, the structure-based pharmacophore (SBP)-guided method has been suggested to generate a comprehensive pharmacophore of MetRS based on fourteen crystal structures of MetRS-inhibitor complexes. In this investigation, a hybrid protocol of a virtual screening method, comprised of pharmacophore model-based virtual screening (PBVS), rigid and flexible docking-based virtual screenings (DBVS), is used for retrieving new MetRS inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen the Specs (202,408 compounds) database, a structurally diverse chemical database. Fifteen hit compounds were selected from the final hits and shifted to experimental studies. These results may provide important information for further research of novel MetRS inhibitors as antibacterial agents. PMID:23839093

21 CFR 892.1960 - Radiographic intensifying screen.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Radiographic intensifying screen. 892.1960 Section 892.1960 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES RADIOLOGY DEVICES Diagnostic Devices § 892.1960 Radiographic intensifying screen...

Science Undergraduate Laboratory Internship Program at NREL | NREL

Science.gov Websites

domestic travel to and from NREL. By Car Travel by car and you'll be reimbursed up to $250, one way. Drug Screening and Background Check Drug Screening NREL coordinates a one-time background investigation and drug appointment for the drug screening, they have 72 hours to complete the required urine test. Work Hours NREL

Drug-induced Brugada syndrome: Clinical characteristics and risk factors.

PubMed

Konigstein, Maayan; Rosso, Raphael; Topaz, Guy; Postema, Pieter G; Friedensohn, Limor; Heller, Karin; Zeltser, David; Belhassen, Bernard; Adler, Arnon; Viskin, Sami

2016-05-01

Cardiac arrest may result from seemingly innocuous medications that do not necessarily have cardiac indications. The best-known example is the drug-induced long QT syndrome. A less known but not necessarily less important form of drug-induced proarrhythmia is the drug-induced Brugada syndrome. The purpose of this study was to identify clinical and ECG risk markers for drug-induced Brugada syndrome. Reports of drug-induced Brugada syndrome recounted by an international database (http://www.brugadadrugs.org) were reviewed to define characteristics that identify patients prone to developing this complication. For each patient with drug-induced Brugada syndrome who had an ECG recorded in the absence of drugs, we included 5 healthy controls matched by gender and age. All ECGs were evaluated for Brugada-like abnormalities. Seventy-four cases of drug-induced Brugada syndrome from noncardiac medications were identified: 77% were male, and drug toxicity was involved in 46%. Drug-induced Brugada syndrome from oral medications generally occurred weeks after the initiation of therapy. Mortality was 13%. By definition, all cases had a type I Brugada pattern during drug therapy. Nevertheless, their ECG in the absence of drugs was more frequently abnormal than the ECG of controls (56% vs 33%, P = .04). Drug-induced Brugada syndrome from noncardiac drugs occurs predominantly in adult males, is frequently due to drug toxicity, and occurs late after the onset of therapy. Minor changes are frequently noticeable on baseline ECG, but screening is impractical because of a prohibitive false-positive rate. Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Elucidation of the binding mechanism of renin using a wide array of computational techniques and biological assays.

PubMed

Tzoupis, Haralambos; Leonis, Georgios; Avramopoulos, Aggelos; Reis, Heribert; Czyżnikowska, Żaneta; Zerva, Sofia; Vergadou, Niki; Peristeras, Loukas D; Papavasileiou, Konstantinos D; Alexis, Michael N; Mavromoustakos, Thomas; Papadopoulos, Manthos G

2015-11-01

We investigate the binding mechanism in renin complexes, involving three drugs (remikiren, zankiren and enalkiren) and one lead compound, which was selected after screening the ZINC database. For this purpose, we used ab initio methods (the effective fragment potential, the variational perturbation theory, the energy decomposition analysis, the atoms-in-molecules), docking, molecular dynamics, and the MM-PBSA method. A biological assay for the lead compound has been performed to validate the theoretical findings. Importantly, binding free energy calculations for the three drug complexes are within 3 kcal/mol of the experimental values, thus further justifying our computational protocol, which has been validated through previous studies on 11 drug-protein systems. The main elements of the discovered mechanism are: (i) minor changes are induced to renin upon drug binding, (ii) the three drugs form an extensive network of hydrogen bonds with renin, whilst the lead compound presented diminished interactions, (iii) ligand binding in all complexes is driven by favorable van der Waals interactions and the nonpolar contribution to solvation, while the lead compound is associated with diminished van der Waals interactions compared to the drug-bound forms of renin, and (iv) the environment (H2O/Na(+)) has a small effect on the renin-remikiren interaction. Copyright © 2015 Elsevier Inc. All rights reserved.

Identification of repaglinide as a therapeutic drug for glioblastoma multiforme.

PubMed

Xiao, Zui Xuan; Chen, Ruo Qiao; Hu, Dian Xing; Xie, Xiao Qiang; Yu, Shang Bin; Chen, Xiao Qian

2017-06-17

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with a median survival time of only 14 months after treatment. It is urgent to find new therapeutic drugs that increase survival time of GBM patients. To achieve this goal, we screened differentially expressed genes between long-term and short-term survived GBM patients from Gene Expression Omnibus database and found gene expression signature for the long-term survived GBM patients. The signaling networks of all those differentially expressed genes converged to protein binding, extracellular matrix and tissue development as revealed in BiNGO and Cytoscape. Drug repositioning in Connectivity Map by using the gene expression signature identified repaglinide, a first-line drug for diabetes mellitus, as the most promising novel drug for GBM. In vitro experiments demonstrated that repaglinide significantly inhibited the proliferation and migration of human GBM cells. In vivo experiments demonstrated that repaglinide prominently prolonged the median survival time of mice bearing orthotopic glioma. Mechanistically, repaglinide significantly reduced Bcl-2, Beclin-1 and PD-L1 expression in glioma tissues, indicating that repaglinide may exert its anti-cancer effects via apoptotic, autophagic and immune checkpoint signaling. Taken together, repaglinide is likely to be an effective drug to prolong life span of GBM patients. Copyright © 2017. Published by Elsevier Inc.

Computer-aided design of liposomal drugs: in silico prediction and experimental validation of drug candidates for liposomal remote loading

PubMed Central

Cern, Ahuva; Barenholz, Yechezkel; Tropsha, Alexander; Goldblum, Amiram

2014-01-01

Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs’ structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al, Journal of Controlled Release, 160(2012) 14–157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-nearest neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs. PMID:24184343

Application of kernel functions for accurate similarity search in large chemical databases.

PubMed

Wang, Xiaohong; Huan, Jun; Smalter, Aaron; Lushington, Gerald H

2010-04-29

Similarity search in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screening among others. It is widely believed that structure based methods provide an efficient way to do the query. Recently various graph kernel functions have been designed to capture the intrinsic similarity of graphs. Though successful in constructing accurate predictive and classification models, graph kernel functions can not be applied to large chemical compound database due to the high computational complexity and the difficulties in indexing similarity search for large databases. To bridge graph kernel function and similarity search in chemical databases, we applied a novel kernel-based similarity measurement, developed in our team, to measure similarity of graph represented chemicals. In our method, we utilize a hash table to support new graph kernel function definition, efficient storage and fast search. We have applied our method, named G-hash, to large chemical databases. Our results show that the G-hash method achieves state-of-the-art performance for k-nearest neighbor (k-NN) classification. Moreover, the similarity measurement and the index structure is scalable to large chemical databases with smaller indexing size, and faster query processing time as compared to state-of-the-art indexing methods such as Daylight fingerprints, C-tree and GraphGrep. Efficient similarity query processing method for large chemical databases is challenging since we need to balance running time efficiency and similarity search accuracy. Our previous similarity search method, G-hash, provides a new way to perform similarity search in chemical databases. Experimental study validates the utility of G-hash in chemical databases.

21 CFR 886.1810 - Tangent screen (campimeter).

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Tangent screen (campimeter). 886.1810 Section 886.1810 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED... a patient's visual field. This generic type of device includes projection tangent screens, target...

Trends and Disparities in Osteoporosis Screening Among Women in the United States, 2008-2014.

PubMed

Gillespie, Catherine W; Morin, Pamela E

2017-03-01

The United States Preventive Services Task Force recommends universal osteoporosis screening among women ages 65+ and targeted screening of younger women, but historically, adherence to these evidence-based recommendations has been suboptimal. To describe contemporary patterns of osteoporosis screening, we conducted a retrospective analysis using the OptumLabs ™ Data Warehouse, a database of de-identified administrative claims, which includes medical and eligibility information for over 100 million Medicare Advantage and commercial enrollees. Study participants included 1,638,454 women ages 50+ with no prior history of osteoporosis diagnosis, osteoporosis drug use, or hip fracture. Osteoporosis screening during the most recent 2-year period of continuous enrollment was assessed via medical claims. Patient sociodemographics, comorbidities, and utilization of other services were also determined using health insurance files. Overall screening rates were low: 21.1%, 26.5%, and 12.8% among women ages 50-64, 65-79, and 80+ years, respectively. Secular trends differed significantly by age (P <.001). Between 2008 and 2014, utilization among women ages 50-64 years declined 31.4%, changed little among women 65-79, and increased 37.7% among women 80+ years. Even after accounting for socioeconomic status, health status, and health care utilization patterns, non-Hispanic black women were least likely to be screened, whereas non-Hispanic Asian and Hispanic women were most likely to undergo screening. Marked socioeconomic gradients in screening probabilities narrowed substantially over time, decreasing by 44.5%, 71.9%, and 59.7% among women ages 50-64, 65-79 and 80+ years, respectively. Despite significant changes in utilization of osteoporosis screening among women ages 50-64 and 80+, in line with national recommendations, tremendous deficiencies among women 65+ remain. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

[Use of urine drug screening in the emergency department of a paediatric hospital].

PubMed

Ferrer Bosch, Núria; Martínez Sánchez, Lidia; Trenchs Sainz de la Maza, Victoria; Velasco Rodríguez, Jesús; García González, Elsa; Luaces Cubells, Carles

2018-01-01

To describe the situations in which urine drug screening is used in a Paediatric Emergency Department (ED). An analysis is also made on its potential usefulness on whether it changes the patient management, and if the results are confirmed by using specific techniques. A retrospective study was conducted on patients under the age of 18 attended in the ED during 2014 and in whom urine drug screening was requested. Depending on the potential capacity of the screening result to change patient management, two groups were defined (potentially useful and not potentially useful). Urine drug screening was performed on a total of 161 patients. The screening was considered not to be potentially useful in 87 (54.0%). This was because the clinical history already explained the symptoms the patient had in 55 (34.1%) patients, in 29 (18.0%) because the patient was asymptomatic, and in 3 (1.9%) because the suspected drug was not detectable in the screening. The drug screening results changed the patient management in 5 (3.1%) cases. A toxic substance was detected in 44 (27.3%). Two out of the 44 that were positive (2.1%) were re-tested by specific techniques, and presence of the toxic substance was ruled out in both of them (false positives). Most of the drug screening tests are not justified, and it is very infrequent that they change patient management. It is very rare that the results are confirmed using more specific methods. Urine drug screening tests should be restricted to particular cases and if the result has legal implications, or if the patient denies using the drug, it should be followed by a specific toxicological study to provide a conclusive result. Copyright © 2016 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

Hierarchical virtual screening approaches in small molecule drug discovery.

PubMed

Kumar, Ashutosh; Zhang, Kam Y J

2015-01-01

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

Generation of human pluripotent stem cell-derived hepatocyte-like cells for drug toxicity screening.

PubMed

Takayama, Kazuo; Mizuguchi, Hiroyuki

2017-02-01

Because drug-induced liver injury is one of the main reasons for drug development failures, it is important to perform drug toxicity screening in the early phase of pharmaceutical development. Currently, primary human hepatocytes are most widely used for the prediction of drug-induced liver injury. However, the sources of primary human hepatocytes are limited, making it difficult to supply the abundant quantities required for large-scale drug toxicity screening. Therefore, there is an urgent need for a novel unlimited, efficient, inexpensive, and predictive model which can be applied for large-scale drug toxicity screening. Human embryonic stem (ES) cells and induced pluripotent stem (iPS) cells are able to replicate indefinitely and differentiate into most of the body's cell types, including hepatocytes. It is expected that hepatocyte-like cells generated from human ES/iPS cells (human ES/iPS-HLCs) will be a useful tool for drug toxicity screening. To apply human ES/iPS-HLCs to various applications including drug toxicity screening, homogenous and functional HLCs must be differentiated from human ES/iPS cells. In this review, we will introduce the current status of hepatocyte differentiation technology from human ES/iPS cells and a novel method to predict drug-induced liver injury using human ES/iPS-HLCs. Copyright © 2016 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

High-throughput screening with nanoimprinting 3D culture for efficient drug development by mimicking the tumor environment.

PubMed

Yoshii, Yukie; Furukawa, Takako; Waki, Atsuo; Okuyama, Hiroaki; Inoue, Masahiro; Itoh, Manabu; Zhang, Ming-Rong; Wakizaka, Hidekatsu; Sogawa, Chizuru; Kiyono, Yasushi; Yoshii, Hiroshi; Fujibayashi, Yasuhisa; Saga, Tsuneo

2015-05-01

Anti-cancer drug development typically utilizes high-throughput screening with two-dimensional (2D) cell culture. However, 2D culture induces cellular characteristics different from tumors in vivo, resulting in inefficient drug development. Here, we report an innovative high-throughput screening system using nanoimprinting 3D culture to simulate in vivo conditions, thereby facilitating efficient drug development. We demonstrated that cell line-based nanoimprinting 3D screening can more efficiently select drugs that effectively inhibit cancer growth in vivo as compared to 2D culture. Metabolic responses after treatment were assessed using positron emission tomography (PET) probes, and revealed similar characteristics between the 3D spheroids and in vivo tumors. Further, we developed an advanced method to adopt cancer cells from patient tumor tissues for high-throughput drug screening with nanoimprinting 3D culture, which we termed Cancer tissue-Originated Uniformed Spheroid Assay (COUSA). This system identified drugs that were effective in xenografts of the original patient tumors. Nanoimprinting 3D spheroids showed low permeability and formation of hypoxic regions inside, similar to in vivo tumors. Collectively, the nanoimprinting 3D culture provides easy-handling high-throughput drug screening system, which allows for efficient drug development by mimicking the tumor environment. The COUSA system could be a useful platform for drug development with patient cancer cells. Copyright © 2015 Elsevier Ltd. All rights reserved.

Alternative to the soft-agar assay that permits high-throughput drug and genetic screens for cellular transformation

PubMed Central

Rotem, Asaf; Janzer, Andreas; Izar, Benjamin; Ji, Zhe; Doench, John G.; Garraway, Levi A.; Struhl, Kevin

2015-01-01

Colony formation in soft agar is the gold-standard assay for cellular transformation in vitro, but it is unsuited for high-throughput screening. Here, we describe an assay for cellular transformation that involves growth in low attachment (GILA) conditions and is strongly correlated with the soft-agar assay. Using GILA, we describe high-throughput screens for drugs and genes that selectively inhibit or increase transformation, but not proliferation. Such molecules are unlikely to be found through conventional drug screening, and they include kinase inhibitors and drugs for noncancer diseases. In addition to known oncogenes, the genetic screen identifies genes that contribute to cellular transformation. Lastly, we demonstrate the ability of Food and Drug Administration-approved noncancer drugs to selectively kill ovarian cancer cells derived from patients with chemotherapy-resistant disease, suggesting this approach may provide useful information for personalized cancer treatment. PMID:25902495

Alternative to the soft-agar assay that permits high-throughput drug and genetic screens for cellular transformation.

PubMed

Rotem, Asaf; Janzer, Andreas; Izar, Benjamin; Ji, Zhe; Doench, John G; Garraway, Levi A; Struhl, Kevin

2015-05-05

Colony formation in soft agar is the gold-standard assay for cellular transformation in vitro, but it is unsuited for high-throughput screening. Here, we describe an assay for cellular transformation that involves growth in low attachment (GILA) conditions and is strongly correlated with the soft-agar assay. Using GILA, we describe high-throughput screens for drugs and genes that selectively inhibit or increase transformation, but not proliferation. Such molecules are unlikely to be found through conventional drug screening, and they include kinase inhibitors and drugs for noncancer diseases. In addition to known oncogenes, the genetic screen identifies genes that contribute to cellular transformation. Lastly, we demonstrate the ability of Food and Drug Administration-approved noncancer drugs to selectively kill ovarian cancer cells derived from patients with chemotherapy-resistant disease, suggesting this approach may provide useful information for personalized cancer treatment.

Optically Based Rapid Screening Method for Proven Optimal Treatment Strategies Before Treatment Begins

DTIC Science & Technology

to rapidly test /screen breast cancer therapeutics as a strategy to streamline drug development and provide individualized treatment. The results...system can therefore be used to streamline pre-clinical drug development, by reducing the number of animals , cost, and time required to screen new drugs

Microfluidic cell chips for high-throughput drug screening

PubMed Central

Chi, Chun-Wei; Ahmed, AH Rezwanuddin; Dereli-Korkut, Zeynep; Wang, Sihong

2016-01-01

The current state of screening methods for drug discovery is still riddled with several inefficiencies. Although some widely used high-throughput screening platforms may enhance the drug screening process, their cost and oversimplification of cell–drug interactions pose a translational difficulty. Microfluidic cell-chips resolve many issues found in conventional HTS technology, providing benefits such as reduced sample quantity and integration of 3D cell culture physically more representative of the physiological/pathological microenvironment. In this review, we introduce the advantages of microfluidic devices in drug screening, and outline the critical factors which influence device design, highlighting recent innovations and advances in the field including a summary of commercialization efforts on microfluidic cell chips. Future perspectives of microfluidic cell devices are also provided based on considerations of present technological limitations and translational barriers. PMID:27071838

Cough Due to TB and Other Chronic Infections: CHEST Guideline and Expert Panel Report.

PubMed

Field, Stephen K; Escalante, Patricio; Fisher, Dina A; Ireland, Belinda; Irwin, Richard S

2018-02-01

Cough is common in pulmonary TB and other chronic respiratory infections. Identifying features that predict whether pulmonary TB is the cause would help target appropriate individuals for rapid and cost-effective screening, potentially limiting disease progression and preventing transmission to others. A systematic literature search for individual studies to answer eight key questions (KQs) was conducted according to established Chest Organization methods by using the following databases: MEDLINE via PubMed, Embase, Scopus, and the Cochrane Database of Systematic Reviews from January 1, 1984, to April 2014. Searches for KQ 1 and KQ 3 were updated in February 2016. An updated KQ 2 search was undertaken in March 2017. Even where TB prevalence is greatest, most individuals with cough do not have pulmonary TB. There was no evidence that 1, 3, or 4 weeks' duration were better predictors than cough lasting ≥ 2 weeks to screen for pulmonary TB. In people living with HIV (PLWHIV), screening for fever, night sweats, hemoptysis, and/or weight loss in addition to cough (any World Health Organization [WHO]-endorsed symptom) increases the diagnostic sensitivity for TB. Although the diagnostic accuracy of symptom-based screening remains low, the negative predictive value of the WHO-endorsed symptom screen in PLWHIV may help to risk-stratify individuals who are not close TB contacts and who do not require further testing for pulmonary TB in resource-limited settings. However, pregnant PLWHIV are more likely to be asymptomatic, and the WHO-endorsed symptom screen is not sensitive enough to be reliable. Combined with passive case finding (PCF), active case finding (ACF) identifies pulmonary TB cases earlier and possibly when less advanced. Whether outcomes are improved or transmission is reduced is unclear. Screening asymptomatic patients is cost-effective only in populations with a very high TB prevalence. The Xpert MTB/RIF assay on sputum is more cost-effective than clinical diagnosis. To our knowledge, no published comparative studies addressed whether the rate of cough resolution is a reliable determinant of the response to treatment or whether the rate of cough resolution was faster in the absence of cavitary lung disease. All studies on cough prevalence in Mycobacterium avium complex (MAC) lung disease, other nontuberculous mycobacterial infections, fungal lung disease, and paragonimiasis were of poor quality and were excluded from the evidence review. On the basis of relatively few studies of fair to good quality, we conclude that most individuals at high risk and household contacts with cough ≥ 2 weeks do not have pulmonary TB, but we suggest screening them regardless of cough duration. In PLWHIV, the addition of the other WHO-endorsed symptoms increases the diagnostic sensitivity of cough. Earlier screening of patients with cough will help diagnose pulmonary TB sooner but will increase the cost of screening. The addition of ACF to PCF will increase the number of pulmonary TB cases identified. Screening asymptomatic individuals is cost-effective only in groups with a very high TB prevalence. Data are insufficient to determine whether cough resolution is delayed in individuals with cavitary lung disease or in those for whom treatment fails because of drug resistance, poor adherence, and/or drug malabsorption compared with results in other individuals with pulmonary TB. Cough is common in patients with lung infections due to MAC, other nontuberculous mycobacteria, fungal diseases, and paragonimiasis. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Antiprotozoan lead discovery by aligning dry and wet screening: prediction, synthesis, and biological assay of novel quinoxalinones.

PubMed

Martins Alho, Miriam A; Marrero-Ponce, Yovani; Barigye, Stephen J; Meneses-Marcel, Alfredo; Machado Tugores, Yanetsy; Montero-Torres, Alina; Gómez-Barrio, Alicia; Nogal, Juan J; García-Sánchez, Rory N; Vega, María Celeste; Rolón, Miriam; Martínez-Fernández, Antonio R; Escario, José A; Pérez-Giménez, Facundo; Garcia-Domenech, Ramón; Rivera, Norma; Mondragón, Ricardo; Mondragón, Mónica; Ibarra-Velarde, Froylán; Lopez-Arencibia, Atteneri; Martín-Navarro, Carmen; Lorenzo-Morales, Jacob; Cabrera-Serra, Maria Gabriela; Piñero, Jose; Tytgat, Jan; Chicharro, Roberto; Arán, Vicente J

2014-03-01

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In an effort to overcome this problem, the main purpose of this study is to develop a QSARs-based ensemble classifier for antiprotozoan drug-like entities from a heterogeneous compounds collection. Here, we use some of the TOMOCOMD-CARDD molecular descriptors and linear discriminant analysis (LDA) to derive individual linear classification functions in order to discriminate between antiprotozoan and non-antiprotozoan compounds as a way to enable the computational screening of virtual combinatorial datasets and/or drugs already approved. Firstly, we construct a wide-spectrum benchmark database comprising of 680 organic chemicals with great structural variability (254 of them antiprotozoan agents and 426 to drugs having other clinical uses). This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. In total, seven discriminant functions were obtained, by using the whole set of atom-based linear indices. All the LDA-based QSAR models show accuracies above 85% in the training set and values of Matthews correlation coefficients (C) vary from 0.70 to 0.86. The external validation set shows rather-good global classifications of around 80% (92.05% for best equation). Later, we developed a multi-agent QSAR classification system, in which the individual QSAR outputs are the inputs of the aforementioned fusion approach. Finally, the fusion model was used for the identification of a novel generation of lead-like antiprotozoan compounds by using ligand-based virtual screening of 'available' small molecules (with synthetic feasibility) in our 'in-house' library. A new molecular subsystem (quinoxalinones) was then theoretically selected as a promising lead series, and its derivatives subsequently synthesized, structurally characterized, and experimentally assayed by using in vitro screening that took into consideration a battery of five parasite-based assays. The chemicals 11(12) and 16 are the most active (hits) against apicomplexa (sporozoa) and mastigophora (flagellata) subphylum parasites, respectively. Both compounds depicted good activity in every protozoan in vitro panel and they did not show unspecific cytotoxicity on the host cells. The described technical framework seems to be a promising QSAR-classifier tool for the molecular discovery and development of novel classes of broad-antiprotozoan-spectrum drugs, which may meet the dual challenges posed by drug-resistant parasites and the rapid progression of protozoan illnesses. Copyright © 2014 Elsevier Ltd. All rights reserved.

QSAR modeling of GPCR ligands: methodologies and examples of applications.

PubMed

Tropsha, A; Wang, S X

2006-01-01

GPCR ligands represent not only one of the major classes of current drugs but the major continuing source of novel potent pharmaceutical agents. Because 3D structures of GPCRs as determined by experimental techniques are still unavailable, ligand-based drug discovery methods remain the major computational molecular modeling approaches to the analysis of growing data sets of tested GPCR ligands. This paper presents an overview of modern Quantitative Structure Activity Relationship (QSAR) modeling. We discuss the critical issue of model validation and the strategy for applying the successfully validated QSAR models to virtual screening of available chemical databases. We present several examples of applications of validated QSAR modeling approaches to GPCR ligands. We conclude with the comments on exciting developments in the QSAR modeling of GPCR ligands that focus on the study of emerging data sets of compounds with dual or even multiple activities against two or more of GPCRs.

Adverse interactions between herbal and dietary substances and prescription medications: a clinical survey.

PubMed

Bush, Thomas M; Rayburn, Keith S; Holloway, Sandra W; Sanchez-Yamamoto, Deanna S; Allen, Blaine L; Lam, Tiffany; So, Brian K; Tran, De H; Greyber, Elizabeth R; Kantor, Sophia; Roth, Larry W

2007-01-01

Patients often combine prescription medications with herbal and dietary substances (herein referred to as herbal medicines). A variety of potential adverse herb-drug interactions exist based on the pharmacological properties of herbal and prescription medications. To determine the incidence of potential and observed adverse herb-drug interactions in patients using herbal medicines with prescription medications. Consecutive patients were questioned about their use of herbal medicines in 6 outpatient clinics. Patients reporting use of these products provided a list of their prescription medications, which were reviewed for any potential adverse herb-drug interactions using a comprehensive natural medicine database. Any potential adverse herb-drug interactions prompted a review of the patient's chart for evidence of an observed adverse herb-drug interaction. The rate of potential and observed adverse herb-drug interactions. Eight hundred four patients were surveyed, and 122 (15%) used herbal medicines. Eighty-five potential adverse herb-drug interactions were found in 49 patients (40% of herbal medicine users). Twelve possible adverse herb-drug interactions in 8 patients (7% of herbal medicine users) were observed. In all 12 cases, the severity scores were rated as mild, including 8 cases of hypoglycemia in diabetics taking nopal (prickly pear cactus). A substantial number of potential adverse herb-drug interactions were detected and a small number of adverse herb-drug interactions observed, particularly in diabetics taking nopal. Screening for herbal medicine usage in 804 patients did not uncover any serious adverse interactions with prescription medications.

IDAAPM: integrated database of ADMET and adverse effects of predictive modeling based on FDA approved drug data.

PubMed

Legehar, Ashenafi; Xhaard, Henri; Ghemtio, Leo

2016-01-01

The disposition of a pharmaceutical compound within an organism, i.e. its Absorption, Distribution, Metabolism, Excretion, Toxicity (ADMET) properties and adverse effects, critically affects late stage failure of drug candidates and has led to the withdrawal of approved drugs. Computational methods are effective approaches to reduce the number of safety issues by analyzing possible links between chemical structures and ADMET or adverse effects, but this is limited by the size, quality, and heterogeneity of the data available from individual sources. Thus, large, clean and integrated databases of approved drug data, associated with fast and efficient predictive tools are desirable early in the drug discovery process. We have built a relational database (IDAAPM) to integrate available approved drug data such as drug approval information, ADMET and adverse effects, chemical structures and molecular descriptors, targets, bioactivity and related references. The database has been coupled with a searchable web interface and modern data analytics platform (KNIME) to allow data access, data transformation, initial analysis and further predictive modeling. Data were extracted from FDA resources and supplemented from other publicly available databases. Currently, the database contains information regarding about 19,226 FDA approval applications for 31,815 products (small molecules and biologics) with their approval history, 2505 active ingredients, together with as many ADMET properties, 1629 molecular structures, 2.5 million adverse effects and 36,963 experimental drug-target bioactivity data. IDAAPM is a unique resource that, in a single relational database, provides detailed information on FDA approved drugs including their ADMET properties and adverse effects, the corresponding targets with bioactivity data, coupled with a data analytics platform. It can be used to perform basic to complex drug-target ADMET or adverse effects analysis and predictive modeling. IDAAPM is freely accessible at http://idaapm.helsinki.fi and can be exploited through a KNIME workflow connected to the database.Graphical abstractFDA approved drug data integration for predictive modeling.

Pharmacogenomic biomarker information in drug labels approved by the United States food and drug administration: prevalence of related drug use.

PubMed

Frueh, Felix W; Amur, Shashi; Mummaneni, Padmaja; Epstein, Robert S; Aubert, Ronald E; DeLuca, Teresa M; Verbrugge, Robert R; Burckart, Gilbert J; Lesko, Lawrence J

2008-08-01

To review the labels of United States Food and Drug Administration (FDA)-approved drugs to identify those that contain pharmacogenomic biomarker information, and to collect prevalence information on the use of those drugs for which pharmacogenomic information is included in the drug labeling. Retrospective analysis. The Physicians' Desk Reference Web site, Drugs@FDA Web site, and manufacturers' Web sites were used to identify drug labels containing pharmacogenomic information, and the prescription claims database of a large pharmacy benefits manager (insuring > 55 million individuals in the United States) was used to obtain drug utilization data. Pharmacogenomic biomarkers were defined, FDA-approved drug labels containing this information were identified, and utilization of these drugs was determined. Of 1200 drug labels reviewed for the years 1945-2005, 121 drug labels contained pharmacogenomic information based on a key word search and follow-up screening. Of those, 69 labels referred to human genomic biomarkers, and 52 referred to microbial genomic biomarkers. Of the labels referring to human biomarkers, 43 (62%) pertained to polymorphisms in cytochrome P450 (CYP) enzyme metabolism, with CYP2D6 being most common. Of 36.1 million patients whose prescriptions were processed by a large pharmacy benefits manager in 2006, about 8.8 million (24.3%) received one or more drugs with human genomic biomarker information in the drug label. Nearly one fourth of all outpatients received one or more drugs that have pharmacogenomic information in the label for that drug. The incorporation and appropriate use of pharmacogenomic information in drug labels should be tested for its ability to improve drug use and safety in the United States.

Timing of specimen collection is crucial in urine screening of drug dependent mothers and newborns.

PubMed

Halstead, A C; Godolphin, W; Lockitch, G; Segal, S

1988-01-01

We compared results of urine drug analysis with clinical data and history to test the usefulness of peripartum drug screening and to establish guidelines for optimal testing. Urine from 28 mothers and 52 babies was analysed. Drugs not suspected by history were found in 10 mothers and six babies. Results assisted in the management of neonatal withdrawal in three babies. Drugs suspected by history were not found in 11/22 mothers and 23/35 babies. About half of these results were associated with delayed urine collection. In 12/28 mothers, drugs administered in hospital could have confused interpretation of screen results. We conclude that urine drug screening without strict protocols for specimen collection is of limited usefulness for management of drug abuse in pregnancy and neonatal drug withdrawal. We favour testing of maternal urine obtained before drugs are administered in hospital. Neonatal urine, if used, should be collected in the first day of life.

Discovery of novel drugs for promising targets.

PubMed

Martell, Robert E; Brooks, David G; Wang, Yan; Wilcoxen, Keith

2013-09-01

Once a promising drug target is identified, the steps to actually discover and optimize a drug are diverse and challenging. The goal of this study was to provide a road map to navigate drug discovery. Review general steps for drug discovery and provide illustrating references. A number of approaches are available to enhance and accelerate target identification and validation. Consideration of a variety of potential mechanisms of action of potential drugs can guide discovery efforts. The hit to lead stage may involve techniques such as high-throughput screening, fragment-based screening, and structure-based design, with informatics playing an ever-increasing role. Biologically relevant screening models are discussed, including cell lines, 3-dimensional culture, and in vivo screening. The process of enabling human studies for an investigational drug is also discussed. Drug discovery is a complex process that has significantly evolved in recent years. © 2013 Elsevier HS Journals, Inc. All rights reserved.

Identification of multi-targeted anti-migraine potential of nystatin and development of its brain targeted chitosan nanoformulation.

PubMed

Girotra, Priti; Thakur, Aman; Kumar, Ajay; Singh, Shailendra Kumar

2017-03-01

The complex pathophysiology involved in migraine necessitates the drug treatment to act on several receptors simultaneously. The present investigation was an attempt to discover the unidentified anti-migraine activity of the already marketed drugs. Shared featured pharmacophore modeling was employed for this purpose on six target receptors (β 2 adrenoceptor, Dopamine D 3 , 5HT 1B , TRPV1, iGluR5 kainate and CGRP), resulting in the generation of five shared featured pharmacophores, which were further subjected to virtual screening of the ligands obtained from Drugbank database. Molecular docking, performed on the obtained hit compounds from virtual screening, indicated nystatin to be the only active lead against the receptors iGluR5 kainate receptor (1VSO), CGRP (3N7R), β 2 adrenoceptor (3NYA) and Dopamine D 3 (3PBL) with a high binding energy of -11.1, -10.9, -10.2 and -12kcal/mole respectively. The anti-migraine activity of nystatin was then adjudged by fabricating its brain targeted chitosan nanoparticles. Its brain targeting efficacy, analyzed qualitatively by confocal laser scanning microscopy, demonstrated a significant amount of drug reaching the brain. The pharmacodynamic models on Swiss male albino mice revealed significant anti-migraine activity of the nanoformulation. The present study reports for the first time the therapeutic potential of nystatin in migraine management, hence opening avenues for its future exploration. Copyright © 2016 Elsevier B.V. All rights reserved.

Identification of Novel Compounds against an R294K Substitution of Influenza A (H7N9) Virus Using Ensemble Based Drug Virtual Screening

PubMed Central

Tran, Nhut; Van, Thanh; Nguyen, Hieu; Le, Ly

2015-01-01

Influenza virus H7N9 foremost emerged in China in 2013 and killed hundreds of people in Asia since they possessed all mutations that enable them to resist to all existing influenza drugs, resulting in high mortality to human. In the effort to identify novel inhibitors combat resistant strains of influenza virus H7N9; we performed virtual screening targeting the Neuraminidase (NA) protein against natural compounds of traditional Chinese medicine database (TCM) and ZINC natural products. Compounds expressed high binding affinity to the target protein was then evaluated for molecular properties to determine drug-like molecules. 4 compounds showed their binding energy less than -11Kcal/mol were selected for molecular dynamics (MD) simulation to capture intermolecular interactions of ligand-protein complexes. The molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method was utilized to estimate binding free energy of the complex. In term of stability, NA-7181 (IUPAC namely {9-Hydroxy-10-[3-(trifluoromrthyl) cyclohexyl]-4.8-diazatricyclo [6.4.0.02,6]dodec-4-yl}(perhydro-1H-inden-5-yl)formaldehyde) achieved stable conformation after 20ns and 27ns for ligand and protein root mean square deviation, respectively. In term of binding free energy, 7181 gave the negative value of -30.031 (KJ/mol) indicating the compound obtained a favourable state in the active site of the protein. PMID:25589893

Applications of chemogenomic library screening in drug discovery.

PubMed

Jones, Lyn H; Bunnage, Mark E

2017-04-01

The allure of phenotypic screening, combined with the industry preference for target-based approaches, has prompted the development of innovative chemical biology technologies that facilitate the identification of new therapeutic targets for accelerated drug discovery. A chemogenomic library is a collection of selective small-molecule pharmacological agents, and a hit from such a set in a phenotypic screen suggests that the annotated target or targets of that pharmacological agent may be involved in perturbing the observable phenotype. In this Review, we describe opportunities for chemogenomic screening to considerably expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications are explored, including drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.

DoD Identity Matching Engine for Security and Analysis (IMESA) Access to Criminal Justice Information (CJI) and Terrorist Screening Databases (TSDB)

DTIC Science & Technology

2016-05-04

IMESA) Access to Criminal Justice Information (CJI) and Terrorist Screening Databases (TSDB) References: See Enclosure 1 1. PURPOSE. In...CJI database mirror image files. (3) Memorandums of understanding with the FBI CJIS as the data broker for DoD organizations that need access ...not for access determinations. (3) Legal restrictions established by the Sex Offender Registration and Notification Act (SORNA) jurisdictions on

Propofol versus thiopental sodium for the treatment of refractory status epilepticus.

PubMed

Prabhakar, Hemanshu; Bindra, Ashish; Singh, Gyaninder Pal; Kalaivani, Mani

2012-08-15

Failure to respond to antiepileptic drugs in uncontrolled seizure activity such as refractory status epilepticus (RSE) has led to the use of anaesthetic drugs. Coma is induced with anaesthetic drugs to achieve complete control of seizure activity. Thiopental sodium and propofol are popularly used for this purpose. Both agents have been found to be effective. However, there is substantial lack of evidence as to which of the two drugs is better in terms of clinical outcome. To compare the efficacy, adverse effects, and short- and long-term outcomes of RSE treated with one of the two anaesthetic agents, thiopental sodium or propofol. We searched the Cochrane Epilepsy Group Specialized Register (10 May 2012), the Cochrane Central Register of Controlled Trials (CENTRAL Issue 4 of 12, The Cochrane Library 2012), and MEDLINE (1946 to May week 1, 2012). We also searched (10 May 2012) ClinicalTrials.gov, The South Asian Database of Controlled Clinical Trials, and IndMED (a bibliographic database of Indian Medical Journals). All randomised or quasi-randomised controlled studies (regardless of blinding) of control of RSE using either thiopental sodium or propofol. Two review authors screened the search results and reviewed abstracts of relevant and eligible trials before retrieving the full text publications. One study was available for review. This study was a small, single-blind, multicentre trial studying adults with RSE and receiving either propofol or thiopental sodium for the control of seizure activity (Rossetti 2011). This study showed a wide confidence interval suggesting that the drugs may differ in efficacy up to more than two-fold. There was no evidence of a difference between the drugs with respect to the outcome measures such as control of seizure activity and functional outcome at three months. There is lack of robust and randomised controlled evidence that can clarify the efficacy of propofol and thiopental sodium over each other in the treatment of RSE. There is a need for large, randomised controlled trials for this serious condition.

Effect of a Hypocretin/Orexin Antagonist on Neurocognitive Performance

DTIC Science & Technology

2011-09-01

physical exam, urine drug and pregnancy screen, and blood draw for hematology and serum chemistry panels. Eligible Participants: 21 participants have...20 5.5 Drug Storage and Accountability...amphetamines, cocaine, cannabis, or any other illicit drugs within 30 days of screening by self report or a urine toxicology screen; 20.) Known

DITOP: drug-induced toxicity related protein database.

PubMed

Zhang, Jing-Xian; Huang, Wei-Juan; Zeng, Jing-Hua; Huang, Wen-Hui; Wang, Yi; Zhao, Rui; Han, Bu-Cong; Liu, Qing-Feng; Chen, Yu-Zong; Ji, Zhi-Liang

2007-07-01

Drug-induced toxicity related proteins (DITRPs) are proteins that mediate adverse drug reactions (ADRs) or toxicities through their binding to drugs or reactive metabolites. Collection of these proteins facilitates better understanding of the molecular mechanisms of drug-induced toxicity and the rational drug discovery. Drug-induced toxicity related protein database (DITOP) is such a database that is intending to provide comprehensive information of DITRPs. Currently, DITOP contains 1501 records, covering 618 distinct literature-reported DITRPs, 529 drugs/ligands and 418 distinct toxicity terms. These proteins were confirmed experimentally to interact with drugs or their reactive metabolites, thus directly or indirectly cause adverse effects or toxicities. Five major types of drug-induced toxicities or ADRs are included in DITOP, which are the idiosyncratic adverse drug reactions, the dose-dependent toxicities, the drug-drug interactions, the immune-mediated adverse drug effects (IMADEs) and the toxicities caused by genetic susceptibility. Molecular mechanisms underlying the toxicity and cross-links to related resources are also provided while available. Moreover, a series of user-friendly interfaces were designed for flexible retrieval of DITRPs-related information. The DITOP can be accessed freely at http://bioinf.xmu.edu.cn/databases/ADR/index.html. Supplementary data are available at Bioinformatics online.

A national database for essential drugs in South Africa.

PubMed

Zweygarth, M; Summers, R S

2000-06-01

In the process of drafting standard treatment guidelines for adults and children at hospital level, the Secretariat of the National Essential Drugs List Committee made use of a database designed with technical support from the School of Pharmacy, MEDUNSA. The database links the current 697 drugs on the Essential Drugs List with Standard Treatment Guidelines for over 400 conditions. It served to streamline the inclusion of different drugs and dosage forms in the various guidelines, and provided concise, updated information to other departments involved in drug procurement. From information on drug prices and morbidity, it can also be used to calculate drug consumption and cost estimates and compare them with actual figures.

Magnetic Resonance Imaging as an Adjunct to Mammography for Breast Cancer Screening in Women at Less Than High Risk for Breast Cancer: A Health Technology Assessment

PubMed Central

Nikitovic-Jokic, Milica; Holubowich, Corinne

2016-01-01

Background Screening with mammography can detect breast cancer early, before clinical symptoms appear. Some cancers, however, are not captured with mammography screening alone. Among women at high risk for breast cancer, magnetic resonance imaging (MRI) has been suggested as a safe adjunct (supplemental) screening tool that can detect breast cancers missed on screening mammography, potentially reducing the number of deaths associated with the disease. However, the use of adjunct screening tests may also increase the number of false-positive test results, which may lead to unnecessary follow-up testing, as well as patient stress and anxiety. We investigated the benefits and harms of MRI as an adjunct to mammography compared with mammography alone for screening women at less than high risk (average or higher than average risk) for breast cancer. Methods We searched Ovid MEDLINE, Ovid Embase, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects (DARE), Centre for Reviews and Dissemination (CRD) Health Technology Assessment Database, and National Health Service (NHS) Economic Evaluation Database, from January 2002 to January 2016, for evidence of effectiveness, harms, and diagnostic accuracy. Only studies evaluating the use of screening breast MRI as an adjunct to mammography in the specified populations were included. Results No studies in women at less than high risk for breast cancer met our inclusion criteria. Conclusions It remains uncertain if the use of adjunct screening breast MRI in women at less than high risk (average or higher than average risk) for breast cancer will reduce breast cancer–related mortality without significant increases in unnecessary follow-up testing and treatment. PMID:27990198

Scrubchem: Building Bioactivity Datasets from Pubchem ...

EPA Pesticide Factsheets

The PubChem Bioassay database is a non-curated public repository with data from 64 sources, including: ChEMBL, BindingDb, DrugBank, EPA Tox21, NIH Molecular Libraries Screening Program, and various other academic, government, and industrial contributors. Methods for extracting this public data into quality datasets, useable for analytical research, presents several big-data challenges for which we have designed manageable solutions. According to our preliminary work, there are approximately 549 million bioactivity values and related meta-data within PubChem that can be mapped to over 10,000 biological targets. However, this data is not ready for use in data-driven research, mainly due to lack of structured annotations.We used a pragmatic approach that provides increasing access to bioactivity values in the PubChem Bioassay database. This included restructuring of individual PubChem Bioassay files into a relational database (ScrubChem). ScrubChem contains all primary PubChem Bioassay data that was: reparsed; error-corrected (when applicable); enriched with additional data links from other NCBI databases; and improved by adding key biological and assay annotations derived from logic-based language processing rules. The utility of ScrubChem and the curation process were illustrated using an example bioactivity dataset for the androgen receptor protein. This initial work serves as a trial ground for establishing the technical framework for accessing, integrating, cu

A Retrospective Analysis of Urine Drugs of Abuse Immunoassay True Positive Rates at a National Reference Laboratory.

PubMed

Johnson-Davis, Kamisha L; Sadler, Aaron J; Genzen, Jonathan R

2016-03-01

Urine drug screens are commonly performed to identify drug use or monitor adherence to drug therapy. The purpose of this retrospective study was to evaluate the true positive and false positive rates of one of our in-house urine drug screen panels. The urine drugs of abuse panel studied consists of screening by immunoassay then positive immunoassay results were confirmed by mass spectrometry. Reagents from Syva and Microgenics were used for the immunoassay screen. The screen was performed on a Beckman AU5810 random access automated clinical analyzer. The percent of true positives for each immunoassay was determined. Agreement with previously validated GC-MS or LC-MS-MS confirmatory methods was also evaluated. There were 8,825 de-identified screening results for each of the drugs in the panel, except for alcohol (N = 2,296). The percent of samples that screened positive were: 10.0% for amphetamine/methamphetamine/3,4-methylenedioxy-methamphetamine (MDMA), 12.8% for benzodiazepines, 43.7% for opiates (including oxycodone) and 20.3% for tetrahydrocannabinol (THC). The false positive rate for amphetamine/methamphetamine was ∼14%, ∼34% for opiates (excluding oxycodone), 25% for propoxyphene and 100% for phencyclidine and MDMA immunoassays. Based on the results from this retrospective study, the true positive rate for THC drug use among adults were similar to the rate of illicit drug use in young adults from the 2013 National Survey; however, our positivity rate for cocaine was higher than the National Survey. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Database-Centric Method for Automated High-Throughput Deconvolution and Analysis of Kinetic Antibody Screening Data.

PubMed

Nobrega, R Paul; Brown, Michael; Williams, Cody; Sumner, Chris; Estep, Patricia; Caffry, Isabelle; Yu, Yao; Lynaugh, Heather; Burnina, Irina; Lilov, Asparouh; Desroches, Jordan; Bukowski, John; Sun, Tingwan; Belk, Jonathan P; Johnson, Kirt; Xu, Yingda

2017-10-01

The state-of-the-art industrial drug discovery approach is the empirical interrogation of a library of drug candidates against a target molecule. The advantage of high-throughput kinetic measurements over equilibrium assessments is the ability to measure each of the kinetic components of binding affinity. Although high-throughput capabilities have improved with advances in instrument hardware, three bottlenecks in data processing remain: (1) intrinsic molecular properties that lead to poor biophysical quality in vitro are not accounted for in commercially available analysis models, (2) processing data through a user interface is time-consuming and not amenable to parallelized data collection, and (3) a commercial solution that includes historical kinetic data in the analysis of kinetic competition data does not exist. Herein, we describe a generally applicable method for the automated analysis, storage, and retrieval of kinetic binding data. This analysis can deconvolve poor quality data on-the-fly and store and organize historical data in a queryable format for use in future analyses. Such database-centric strategies afford greater insight into the molecular mechanisms of kinetic competition, allowing for the rapid identification of allosteric effectors and the presentation of kinetic competition data in absolute terms of percent bound to antigen on the biosensor.

Screening for small molecule inhibitors of Toxoplasma gondii.

PubMed

Kortagere, Sandhya

2012-12-01

Toxoplasma gondii, the agent that causes toxoplasmosis, is an opportunistic parasite that infects many mammalian species. It is an obligate intracellular parasite that causes severe congenital neurological and ocular disease mostly in immunocompromised humans. The current regimen of therapy includes only a few medications that often lead to hypersensitivity and toxicity. In addition, there are no vaccines available to prevent the transmission of this agent. Therefore, safer and more effective medicines to treat toxoplasmosis are urgently needed. The author presents in silico and in vitro strategies that are currently used to screen for novel targets and unique chemotypes against T. gondii. Furthermore, this review highlights the screening technologies and characterization of some novel targets and new chemical entities that could be developed into highly efficacious treatments for toxoplasmosis. A number of diverse methods are being used to design inhibitors against T. gondii. These include ligand-based methods, in which drugs that have been shown to be efficacious against other Apicomplexa parasites can be repurposed to identify lead molecules against T. gondii. In addition, structure-based methods use currently available repertoire of structural information in various databases to rationally design small-molecule inhibitors of T. gondii. Whereas the screening methods have their advantages and limitations, a combination of methods is ideally suited to design small-molecule inhibitors of complex parasites such as T. gondii.

Virtual screening for novel Staphylococcus Aureus NorA efflux pump inhibitors from natural products.

PubMed

Thai, Khac-Minh; Ngo, Trieu-Du; Phan, Thien-Vy; Tran, Thanh-Dao; Nguyen, Ngoc-Vinh; Nguyen, Thien-Hai; Le, Minh-Tri

2015-01-01

NorA is a member of the Major Facilitator Superfamily (MFS) drug efflux pumps that have been shown to mediate antibiotic resistance in Staphylococcus aureus (SA). In this study, QSAR analysis, virtual screening and molecular docking were implemented in an effort to discover novel SA NorA efflux pump inhibitors. Originally, a set of 47 structurally diverse compounds compiled from the literature was used to develop linear QSAR models and another set of 15 different compounds were chosen for extra validation. The final model which was estimated by statistical values for the full data set (n = 45, Q(2) = 0.80, RMSE = 0.20) and for the external test set (n = 15, R(2) = 0.60, |res|max = 0.75, |res|min = 0.02) was applied on the collection of 182 flavonoides and the traditional Chinese medicine (TCM) database to screen for novel NorA inhibitors. Finally, 33 lead compounds that met the Lipinski's rules of five/three and had good predicted pIC50 values from in silico screening process were employed to analyze the binding ability by docking studies on NorA homology model in place of its unavailable crystal structures at two active sites, the central channel and the Walker B.

Discovery of Dual ETA/ETB Receptor Antagonists from Traditional Chinese Herbs through in Silico and in Vitro Screening

PubMed Central

Wang, Xing; Zhang, Yuxin; Liu, Qing; Ai, Zhixin; Zhang, Yanling; Xiang, Yuhong; Qiao, Yanjiang

2016-01-01

Endothelin-1 receptors (ETAR and ETBR) act as a pivotal regulator in the biological effects of ET-1 and represent a potential drug target for the treatment of multiple cardiovascular diseases. The purpose of the study is to discover dual ETA/ETB receptor antagonists from traditional Chinese herbs. Ligand- and structure-based virtual screening was performed to screen an in-house database of traditional Chinese herbs, followed by a series of in vitro bioassay evaluation. Aristolochic acid A (AAA) was first confirmed to be a dual ETA/ETB receptor antagonist based intracellular calcium influx assay and impedance-based assay. Dose-response curves showed that AAA can block both ETAR and ETBR with IC50 of 7.91 and 7.40 μM, respectively. Target specificity and cytotoxicity bioassay proved that AAA is a selective dual ETA/ETB receptor antagonist and has no significant cytotoxicity on HEK293/ETAR and HEK293/ETBR cells within 24 h. It is a feasible and effective approach to discover bioactive compounds from traditional Chinese herbs using in silico screening combined with in vitro bioassay evaluation. The structural characteristic of AAA for its activity was especially interpreted, which could provide valuable reference for the further structural modification of AAA. PMID:26999111

Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies

PubMed Central

Son, Minky; Park, Chanin; Kim, Hyong-Ha; Suh, Jung-Keun

2017-01-01

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1. PMID:29312992

Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies.

PubMed

Rampogu, Shailima; Son, Minky; Park, Chanin; Kim, Hyong-Ha; Suh, Jung-Keun; Lee, Keun Woo

2017-01-01

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1.

Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus.

PubMed

Karthick, V; Nagasundaram, N; Doss, C George Priya; Chakraborty, Chiranjib; Siva, R; Lu, Aiping; Zhang, Ge; Zhu, Hailong

2016-02-17

The Ebola virus is highly pathogenic and destructive to humans and other primates. The Ebola virus encodes viral protein 40 (VP40), which is highly expressed and regulates the assembly and release of viral particles in the host cell. Because VP40 plays a prominent role in the life cycle of the Ebola virus, it is considered as a key target for antiviral treatment. However, there is currently no FDA-approved drug for treating Ebola virus infection, resulting in an urgent need to develop effective antiviral inhibitors that display good safety profiles in a short duration. This study aimed to screen the effective lead candidate against Ebola infection. First, the lead molecules were filtered based on the docking score. Second, Lipinski rule of five and the other drug likeliness properties are predicted to assess the safety profile of the lead candidates. Finally, molecular dynamics simulations was performed to validate the lead compound. Our results revealed that emodin-8-beta-D-glucoside from the Traditional Chinese Medicine Database (TCMD) represents an active lead candidate that targets the Ebola virus by inhibiting the activity of VP40, and displays good pharmacokinetic properties. This report will considerably assist in the development of the competitive and robust antiviral agents against Ebola infection.

In silico investigation of potential mTOR inhibitors from traditional Chinese medicine for treatment of Leigh syndrome.

PubMed

Chen, Kuan-Chung; Lee, Wen-Yuan; Chen, Hsin-Yi; Chen, Calvin Yu-Chian

2014-01-01

A recent research demonstrates that the inhibition of mammalian target of rapamycin (mTOR) improves survival and health for patients with Leigh syndrome. mTOR proteins can be treated as drug target proteins against Leigh syndrome and other mitochondrial disorders. In this study, we aim to identify potent TCM compounds from the TCM Database@Taiwan as lead compounds of mTOR inhibitors. PONDR-Fit protocol was employed to predict the disordered disposition in mTOR protein before virtual screening. After virtual screening, the MD simulation was employed to validate the stability of interactions between each ligand and mTOR protein in the docking poses from docking simulation. The top TCM compounds, picrasidine M and acerosin, have higher binding affinities with target protein in docking simulation than control. There have H-bonds with residues Val2240 and π interactions with common residue Trp2239. After MD simulation, the top TCM compounds maintain similar docking poses under dynamic conditions. The top two TCM compounds, picrasidine M and acerosin, were extracted from Picrasma quassioides (D. Don) Benn. and Vitex negundo L. Hence, we propose the TCM compounds, picrasidine M and acerosin, as potential candidates as lead compounds for further study in drug development process with the mTOR protein against Leigh syndrome and other mitochondrial disorders.

Potential human cholesterol esterase inhibitor design: benefits from the molecular dynamics simulations and pharmacophore modeling studies.

PubMed

John, Shalini; Thangapandian, Sundarapandian; Lee, Keun Woo

2012-01-01

Human pancreatic cholesterol esterase (hCEase) is one of the lipases found to involve in the digestion of large and broad spectrum of substrates including triglycerides, phospholipids, cholesteryl esters, etc. The presence of bile salts is found to be very important for the activation of hCEase. Molecular dynamic simulations were performed for the apoform and bile salt complexed form of hCEase using the co-ordinates of two bile salts from bovine CEase. The stability of the systems throughout the simulation time was checked and two representative structures from the highly populated regions were selected using cluster analysis. These two representative structures were used in pharmacophore model generation. The generated pharmacophore models were validated and used in database screening. The screened hits were refined for their drug-like properties based on Lipinski's rule of five and ADMET properties. The drug-like compounds were further refined by molecular docking simulation using GOLD program based on the GOLD fitness score, mode of binding, and molecular interactions with the active site amino acids. Finally, three hits of novel scaffolds were selected as potential leads to be used in novel and potent hCEase inhibitor design. The stability of binding modes and molecular interactions of these final hits were re-assured by molecular dynamics simulations.

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Kejian, E-mail: kejian.wang.bio@gmail.com; Weng, Zuquan; Sun, Liya

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. Inmore » the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.« less

Hepatitis C screening trends in a large integrated health system

PubMed Central

Linas, Benjamin P.; Hu, Haihong; Barter, Devra M.; Horberg, Michael

2014-01-01

Background As new hepatitis C virus (HCV) therapies emerge, only 1–12% of individuals are screened in the U.S. for HCV infection. Presently, HCV screening trends are unknown. Methods We utilized the Kaiser Permanente Mid-Atlantic States’ (KPMAS) data repository to investigate HCV antibody screening between 1/1/2003 and 12/31/2012. We identified the proportion screened for HCV and 5-year cumulative incidence of screening, the screening positivity rate, the provider types performing HCV screening, patient-level factors associated with being screened, and trends in screening over time. Results 444,594 patients met the inclusion criteria. Overall, 15.8% of the cohort was ever screened for HCV. Adult primary care and obstetrics and gynecology providers performed 75.9% of all screening. The overall test positivity rate was 3.8%. Screening was more frequent in younger age groups (p<0.0001) and those with a documented history of illicit drug use (p<0.0001). Patients with missing drug use history (46.7%) were least likely to be screened (p<0.0001). While the rate of HCV screening increased in the later years of the study, among those enrolled in KPMAS 2009–2012, only 11.8% were screened by the end of follow-up. Conclusion Screening for HCV is increasing, but remains incomplete. Targeting screening to those with a history of injection drug will not likely expand screening, as nearly half of patients have no documented drug use history. Routine screening is likely the most effective approach to expand HCV screening. PMID:24486288

Hepatitis C screening trends in a large integrated health system.

PubMed

Linas, Benjamin P; Hu, Haihong; Barter, Devra M; Horberg, Michael

2014-05-01

As new hepatitis C virus (HCV) therapies emerge, only 1%-12% of individuals are screened in the US for HCV infection. Presently, HCV screening trends are unknown. We utilized the Kaiser Permanente Mid-Atlantic States' (KPMAS) data repository to investigate HCV antibody screening between January 1, 2003 and December 31, 2012. We identified the proportion screened for HCV and 5-year cumulative incidence of screening, the screening positivity rate, the provider types performing HCV screening, patient-level factors associated with being screened, and trends in screening over time. There were 444,594 patients who met the inclusion criteria. Overall, 15.8% of the cohort was ever screened for HCV. Adult primary care and obstetrics and gynecology providers performed 75.9% of all screening. The overall test positivity rate was 3.8%. Screening was more frequent in younger age groups (P <.0001) and those with a documented history of illicit drug use (P <.0001). Patients with missing drug use history (46.7%) were least likely to be screened (P <.0001). While the rate of HCV screening increased in the later years of the study among those enrolled in KPMAS 2009-2012, only 11.8% were screened by the end of follow-up. Screening for HCV is increasing but remains incomplete. Targeting screening to those with a history of injection drug will not likely expand screening, as nearly half of patients have no documented drug use history. Routine screening is likely the most effective approach to expand HCV screening. Copyright © 2014. Published by Elsevier Inc.

Importance of Urinary Drug Screening in the Multiple Sleep Latency Test and Maintenance of Wakefulness Test.

PubMed

Anniss, Angela M; Young, Alan; O'Driscoll, Denise M

2016-12-15

Multiple sleep latency testing (MSLT) and the maintenance of wakefulness test (MWT) are gold-standard objective tests of daytime sleepiness and alertness; however, there is marked variability in their interpretation and practice. This study aimed to determine the incidence of positive drug screens and their influence on MSLT, MWT, and polysomnographic variables. All patients attending Eastern Health Sleep Laboratory for MSLT or MWT over a 21-mo period were included in the study. Urinary drug screening for amphetamines, barbiturates, benzodiazepines, cannabinoids, cocaine, methadone, and opiates was performed following overnight polysomnography (PSG). Demographics and PSG variables were compared. Of 69 studies, MSLT (43) and MWT (26), 16% of patients had positive urinary drug screening (7 MSLT; 4 MWT). Drugs detected included amphetamines, cannabinoids, opiates, and benzodiazepines. No patient self-reported use of these medications prior to testing. No demographic, MSLT or MWT PSG data or overnight PSG data showed any statistical differences between positive and negative drug screen groups. Of seven MSLT patients testing positive for drug use, one met criteria for the diagnosis of narcolepsy and five for idiopathic hypersomnia. On MWT, three of the four drug-positive patients had a history of a motor vehicle accident and two patients were occupational drivers. These findings indicate drug use is present in patients attending for daytime testing of objective sleepiness and wakefulness. These data support routine urinary drug screening in all patients undergoing MSLT or MWT studies to ensure accurate interpretation in the context of illicit and prescription drug use. © 2016 American Academy of Sleep Medicine

S2RSLDB: a comprehensive manually curated, internet-accessible database of the sigma-2 receptor selective ligands.

PubMed

Nastasi, Giovanni; Miceli, Carla; Pittalà, Valeria; Modica, Maria N; Prezzavento, Orazio; Romeo, Giuseppe; Rescifina, Antonio; Marrazzo, Agostino; Amata, Emanuele

2017-01-01

Sigma (σ) receptors are accepted as a particular receptor class consisting of two subtypes: sigma-1 (σ 1 ) and sigma-2 (σ 2 ). The two receptor subtypes have specific drug actions, pharmacological profiles and molecular characteristics. The σ 2 receptor is overexpressed in several tumor cell lines, and its ligands are currently under investigation for their role in tumor diagnosis and treatment. The σ 2 receptor structure has not been disclosed, and researchers rely on σ 2 receptor radioligand binding assay to understand the receptor's pharmacological behavior and design new lead compounds. Here we present the sigma-2 Receptor Selective Ligands Database (S2RSLDB) a manually curated database of the σ 2 receptor selective ligands containing more than 650 compounds. The database is built with chemical structure information, radioligand binding affinity data, computed physicochemical properties, and experimental radioligand binding procedures. The S2RSLDB is freely available online without account login and having a powerful search engine the user may build complex queries, sort tabulated results, generate color coded 2D and 3D graphs and download the data for additional screening. The collection here reported is extremely useful for the development of new ligands endowed of σ 2 receptor affinity, selectivity, and appropriate physicochemical properties. The database will be updated yearly and in the near future, an online submission form will be available to help with keeping the database widely spread in the research community and continually updated. The database is available at http://www.researchdsf.unict.it/S2RSLDB.

Development and Validation of a Qualitative Method for Target Screening of 448 Pesticide Residues in Fruits and Vegetables Using UHPLC/ESI Q-Orbitrap Based on Data-Independent Acquisition and Compound Database.

PubMed

Wang, Jian; Chow, Willis; Chang, James; Wong, Jon W

2017-01-18

A semiautomated qualitative method for target screening of 448 pesticide residues in fruits and vegetables was developed and validated using ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole Orbitrap high-resolution mass spectrometry (UHPLC/ESI Q-Orbitrap). The Q-Orbitrap Full MS/dd-MS 2 (data dependent acquisition) was used to acquire product-ion spectra of individual pesticides to build a compound database or an MS library, while its Full MS/DIA (data independent acquisition) was utilized for sample data acquisition from fruit and vegetable matrices fortified with pesticides at 10 and 100 μg/kg for target screening purpose. Accurate mass, retention time and response threshold were three key parameters in a compound database that were used to detect incurred pesticide residues in samples. The concepts and practical aspects of in-spectrum mass correction or solvent background lock-mass correction, retention time alignment and response threshold adjustment are discussed while building a functional and working compound database for target screening. The validated target screening method is capable of screening at least 94% and 99% of 448 pesticides at 10 and 100 μg/kg, respectively, in fruits and vegetables without having to evaluate every compound manually during data processing, which significantly reduced the workload in routine practice.

Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase.

PubMed

Shukla, Rohit; Shukla, Harish; Sonkar, Amit; Pandey, Tripti; Tripathi, Timir

2018-06-01

Mycobacterium tuberculosis is the etiological agent of tuberculosis in humans and is responsible for more than two million deaths annually. M. tuberculosis isocitrate lyase (MtbICL) catalyzes the first step in the glyoxylate cycle, plays a pivotal role in the persistence of M. tuberculosis, which acts as a potential target for an anti-tubercular drug. To identify the potential anti-tuberculosis compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,748) against the MtbICL structure. The ligands were docked against MtbICL in three sequential docking modes that resulted in 340 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 27 compounds were found to fit well with re-docking studies. After refinement by molecular docking and drug-likeness analyses, three potential inhibitors (ZINC1306071, ZINC2111081, and ZINC2134917) were identified. These three ligands and the reference compounds were further subjected to molecular dynamics simulation and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the MtbICL and bound complexes. The binding free energy analyses were calculated to validate and capture the intermolecular interactions. The results suggested that the three compounds had a negative binding energy with -96.462, -143.549, and -122.526 kJ mol -1 for compounds with IDs ZINC1306071, ZINC2111081, and ZINC2134917, respectively. These lead compounds displayed substantial pharmacological and structural properties to be drug candidates. We concluded that ZINC2111081 has a great potential to inhibit MtbICL and would add to the drug discovery process against tuberculosis.

Predicting Rat and Human Pregnane X Receptor Activators Using Bayesian Classification Models.

PubMed

AbdulHameed, Mohamed Diwan M; Ippolito, Danielle L; Wallqvist, Anders

2016-10-17

The pregnane X receptor (PXR) is a ligand-activated transcription factor that acts as a master regulator of metabolizing enzymes and transporters. To avoid adverse drug-drug interactions and diseases such as steatosis and cancers associated with PXR activation, identifying drugs and chemicals that activate PXR is of crucial importance. In this work, we developed ligand-based predictive computational models for both rat and human PXR activation, which allowed us to identify potentially harmful chemicals and evaluate species-specific effects of a given compound. We utilized a large publicly available data set of nearly 2000 compounds screened in cell-based reporter gene assays to develop Bayesian quantitative structure-activity relationship models using physicochemical properties and structural descriptors. Our analysis showed that PXR activators tend to be hydrophobic and significantly different from nonactivators in terms of their physicochemical properties such as molecular weight, logP, number of rings, and solubility. Our Bayesian models, evaluated by using 5-fold cross-validation, displayed a sensitivity of 75% (76%), specificity of 76% (75%), and accuracy of 89% (89%) for human (rat) PXR activation. We identified structural features shared by rat and human PXR activators as well as those unique to each species. We compared rat in vitro PXR activation data to in vivo data by using DrugMatrix, a large toxicogenomics database with gene expression data obtained from rats after exposure to diverse chemicals. Although in vivo gene expression data pointed to cross-talk between nuclear receptor activators that is captured only by in vivo assays, overall we found broad agreement between in vitro and in vivo PXR activation. Thus, the models developed here serve primarily as efficient initial high-throughput in silico screens of in vitro activity.

A Systematic Review of Economic Evaluations of Pharmacogenetic Testing for Prevention of Adverse Drug Reactions.

PubMed

Plumpton, Catrin O; Roberts, Daniel; Pirmohamed, Munir; Hughes, Dyfrig A

2016-08-01

Pharmacogenetics offers the potential to improve health outcomes by identifying individuals who are at greater risk of harm from certain medicines. Routine adoption of pharmacogenetic tests requires evidence of their cost effectiveness. The present review aims to systematically review published economic evaluations of pharmacogenetic tests that aim to prevent or reduce the incidence of ADRs. We conducted a systematic literature review of economic evaluations of pharmacogenetic tests aimed to reduce the incidence of adverse drug reactions. Literature was searched using Embase, MEDLINE and the NHS Economic Evaluation Database with search terms relating to pharmacogenetic testing, adverse drug reactions, economic evaluations and pharmaceuticals. Titles were screened independently by two reviewers. Articles deemed to meet the inclusion criteria were screened independently on abstract, and full texts reviewed. We identified 852 articles, of which 47 met the inclusion criteria. There was evidence supporting the cost effectiveness of testing for HLA-B*57:01 (prior to abacavir), HLA-B*15:02 and HLA-A*31:01 (prior to carbamazepine), HLA-B*58:01 (prior to allopurinol) and CYP2C19 (prior to clopidogrel treatment). Economic evidence was inconclusive with respect to TPMT (prior to 6-mercaptoputine, azathioprine and cisplatin therapy), CYP2C9 and VKORC1 (to inform genotype-guided dosing of coumarin derivatives), MTHFR (prior to methotrexate treatment) and factor V Leiden testing (prior to oral contraception). Testing for A1555G is not cost effective before prescribing aminoglycosides. Our systematic review identified robust evidence of the cost effectiveness of genotyping prior to treatment with a number of common drugs. However, further analyses and (or) availability of robust clinical evidence is necessary to make recommendations for others.

Automated Fast Screening Method for Cocaine Identification in Seized Drug Samples Using a Portable Fourier Transform Infrared (FT-IR) Instrument.

PubMed

Mainali, Dipak; Seelenbinder, John

2016-05-01

Quick and presumptive identification of seized drug samples without destroying evidence is necessary for law enforcement officials to control the trafficking and abuse of drugs. This work reports an automated screening method to detect the presence of cocaine in seized samples using portable Fourier transform infrared (FT-IR) spectrometers. The method is based on the identification of well-defined characteristic vibrational frequencies related to the functional group of the cocaine molecule and is fully automated through the use of an expert system. Traditionally, analysts look for key functional group bands in the infrared spectra and characterization of the molecules present is dependent on user interpretation. This implies the need for user expertise, especially in samples that likely are mixtures. As such, this approach is biased and also not suitable for non-experts. The method proposed in this work uses the well-established "center of gravity" peak picking mathematical algorithm and combines it with the conditional reporting feature in MicroLab software to provide an automated method that can be successfully employed by users with varied experience levels. The method reports the confidence level of cocaine present only when a certain number of cocaine related peaks are identified by the automated method. Unlike library search and chemometric methods that are dependent on the library database or the training set samples used to build the calibration model, the proposed method is relatively independent of adulterants and diluents present in the seized mixture. This automated method in combination with a portable FT-IR spectrometer provides law enforcement officials, criminal investigators, or forensic experts a quick field-based prescreening capability for the presence of cocaine in seized drug samples. © The Author(s) 2016.

Field test of on-site drug detection devices

DOT National Transportation Integrated Search

2000-10-01

This NHTSA-sponsored study reports the findings of a field evaluation of five on-site drug screening devices used by law enforcement to screen for illicit drugs among drivers suspected of driving under the influence (DUI) of alcohol or other drugs. I...

Logistics or patient care: which features do independent Finnish pharmacy owners prioritize in a strategic plan for future information technology systems?

PubMed

Westerling, Anna M; Haikala, Veikko E; Bell, J Simon; Airaksinen, Marja S

2010-01-01

To determine Finnish community pharmacy owners' requirements for the next generation of software systems. Descriptive, nonexperimental, cross-sectional study. Finland during December 2006. 308 independent pharmacy owners. Survey listing 126 features that could potentially be included in the new information technology (IT) system. The list was grouped into five categories: (1) drug information and patient counseling, (2) medication safety, (3) interprofessional collaboration, (4) pharmacy services, and (5) pharmacy internal processes. Perceived value of potential features for a new IT system. The survey was mailed to all independent pharmacy owners in Finland (n = 580; response rate 53% [n = 308]). Respondents gave priority to logistical functions and functions related to drug information and patient care. The highest rated individual features were tracking product expiry (rated as very or quite important by 100% of respondents), computerized drug-drug interaction screening (99%), an electronic version of the national pharmaceutical reference book (97%), and a checklist-type drug information database to assist patient counseling (95%). In addition to the high ranking for logistical features, Finnish pharmacy owners put a priority on support for cognitive pharmaceutical services in the next IT system. Although the importance of logistical functions is understandable, the owners demonstrated a commitment to strategic health policy goals when planning their business IT system.

A web-based platform for virtual screening.

PubMed

Watson, Paul; Verdonk, Marcel; Hartshorn, Michael J

2003-09-01

A fully integrated, web-based, virtual screening platform has been developed to allow rapid virtual screening of large numbers of compounds. ORACLE is used to store information at all stages of the process. The system includes a large database of historical compounds from high throughput screenings (HTS) chemical suppliers, ATLAS, containing over 3.1 million unique compounds with their associated physiochemical properties (ClogP, MW, etc.). The database can be screened using a web-based interface to produce compound subsets for virtual screening or virtual library (VL) enumeration. In order to carry out the latter task within ORACLE a reaction data cartridge has been developed. Virtual libraries can be enumerated rapidly using the web-based interface to the cartridge. The compound subsets can be seamlessly submitted for virtual screening experiments, and the results can be viewed via another web-based interface allowing ad hoc querying of the virtual screening data stored in ORACLE.

GPCR ontology: development and application of a G protein-coupled receptor pharmacology knowledge framework.

PubMed

Przydzial, Magdalena J; Bhhatarai, Barun; Koleti, Amar; Vempati, Uma; Schürer, Stephan C

2013-12-15

Novel tools need to be developed to help scientists analyze large amounts of available screening data with the goal to identify entry points for the development of novel chemical probes and drugs. As the largest class of drug targets, G protein-coupled receptors (GPCRs) remain of particular interest and are pursued by numerous academic and industrial research projects. We report the first GPCR ontology to facilitate integration and aggregation of GPCR-targeting drugs and demonstrate its application to classify and analyze a large subset of the PubChem database. The GPCR ontology, based on previously reported BioAssay Ontology, depicts available pharmacological, biochemical and physiological profiles of GPCRs and their ligands. The novelty of the GPCR ontology lies in the use of diverse experimental datasets linked by a model to formally define these concepts. Using a reasoning system, GPCR ontology offers potential for knowledge-based classification of individuals (such as small molecules) as a function of the data. The GPCR ontology is available at http://www.bioassayontology.org/bao_gpcr and the National Center for Biomedical Ontologies Web site.

Bigger data, collaborative tools and the future of predictive drug discovery

NASA Astrophysics Data System (ADS)

Ekins, Sean; Clark, Alex M.; Swamidass, S. Joshua; Litterman, Nadia; Williams, Antony J.

2014-10-01

Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas.

Mapping small molecule binding data to structural domains

PubMed Central

2012-01-01

Background Large-scale bioactivity/SAR Open Data has recently become available, and this has allowed new analyses and approaches to be developed to help address the productivity and translational gaps of current drug discovery. One of the current limitations of these data is the relative sparsity of reported interactions per protein target, and complexities in establishing clear relationships between bioactivity and targets using bioinformatics tools. We detail in this paper the indexing of targets by the structural domains that bind (or are likely to bind) the ligand within a full-length protein. Specifically, we present a simple heuristic to map small molecule binding to Pfam domains. This profiling can be applied to all proteins within a genome to give some indications of the potential pharmacological modulation and regulation of all proteins. Results In this implementation of our heuristic, ligand binding to protein targets from the ChEMBL database was mapped to structural domains as defined by profiles contained within the Pfam-A database. Our mapping suggests that the majority of assay targets within the current version of the ChEMBL database bind ligands through a small number of highly prevalent domains, and conversely the majority of Pfam domains sampled by our data play no currently established role in ligand binding. Validation studies, carried out firstly against Uniprot entries with expert binding-site annotation and secondly against entries in the wwPDB repository of crystallographic protein structures, demonstrate that our simple heuristic maps ligand binding to the correct domain in about 90 percent of all assessed cases. Using the mappings obtained with our heuristic, we have assembled ligand sets associated with each Pfam domain. Conclusions Small molecule binding has been mapped to Pfam-A domains of protein targets in the ChEMBL bioactivity database. The result of this mapping is an enriched annotation of small molecule bioactivity data and a grouping of activity classes following the Pfam-A specifications of protein domains. This is valuable for data-focused approaches in drug discovery, for example when extrapolating potential targets of a small molecule with known activity against one or few targets, or in the assessment of a potential target for drug discovery or screening studies. PMID:23282026

Construction of a database for published phase II/III drug intervention clinical trials for the period 2009-2014 comprising 2,326 records, 90 disease categories, and 939 drug entities.

PubMed

Jeong, Sohyun; Han, Nayoung; Choi, Boyoon; Sohn, Minji; Song, Yun-Kyoung; Chung, Myeon-Woo; Na, Han-Sung; Ji, Eunhee; Kim, Hyunah; Rhew, Ki Yon; Kim, Therasa; Kim, In-Wha; Oh, Jung Mi

2016-06-01

To construct a database of published clinical drug trials suitable for use 1) as a research tool in accessing clinical trial information and 2) in evidence-based decision-making by regulatory professionals, clinical research investigators, and medical practitioners. Comprehensive information obtained from a search of design elements and results of clinical trials in peer reviewed journals using PubMed (http://www.ncbi.nlm.ih.gov/pubmed). The methodology to develop a structured database was devised by a panel composed of experts in medical, pharmaceutical, information technology, and members of Ministry of Food and Drug Safety (MFDS) using a step by step approach. A double-sided system consisting of user mode and manager mode served as the framework for the database; elements of interest from each trial were entered via secure manager mode enabling the input information to be accessed in a user-friendly manner (user mode). Information regarding methodology used and results of drug treatment were extracted as detail elements of each data set and then inputted into the web-based database system. Comprehensive information comprising 2,326 clinical trial records, 90 disease states, and 939 drugs entities and concerning study objectives, background, methods used, results, and conclusion could be extracted from published information on phase II/III drug intervention clinical trials appearing in SCI journals within the last 10 years. The extracted data was successfully assembled into a clinical drug trial database with easy access suitable for use as a research tool. The clinically most important therapeutic categories, i.e., cancer, cardiovascular, respiratory, neurological, metabolic, urogenital, gastrointestinal, psychological, and infectious diseases were covered by the database. Names of test and control drugs, details on primary and secondary outcomes and indexed keywords could also be retrieved and built into the database. The construction used in the database enables the user to sort and download targeted information as a Microsoft Excel spreadsheet. Because of the comprehensive and standardized nature of the clinical drug trial database and its ease of access it should serve as valuable information repository and research tool for accessing clinical trial information and making evidence-based decisions by regulatory professionals, clinical research investigators, and medical practitioners.

Alcoholism, Psychopathology and Sensation-Seeking: Differences Between Male Dui First Offenders and Recidivists

DTIC Science & Technology

1994-01-01

scales from the Drug Use Screening Inventory: Behavior Pattern Domain and Psychiatric Disorder Domain. The following scales from the Zuckerman ...1992). Validation of the adolescent Drug Use Screening Inventory: Preliminary findings. -Py hogyof Addictive Behaviors.6(4), 233-36. Tennen, H... Drug Use Screening Inventory - Revised (Behavior and Psychiatry Scales) ..................................... 58 Measures of Sensation-seeking and

76 FR 53912 - FDA's Public Database of Products With Orphan-Drug Designation: Replacing Non-Informative Code...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-30

...] FDA's Public Database of Products With Orphan-Drug Designation: Replacing Non-Informative Code Names... replaced non- informative code names with descriptive identifiers on its public database of products that... on our public database with non-informative code names. After careful consideration of this matter...

21 CFR 830.350 - Correction of information submitted to the Global Unique Device Identification Database.

Code of Federal Regulations, 2014 CFR

2014-04-01

... Unique Device Identification Database. 830.350 Section 830.350 Food and Drugs FOOD AND DRUG... Global Unique Device Identification Database § 830.350 Correction of information submitted to the Global Unique Device Identification Database. (a) If FDA becomes aware that any information submitted to the...

SM-TF: A structural database of small molecule-transcription factor complexes.

PubMed

Xu, Xianjin; Ma, Zhiwei; Sun, Hongmin; Zou, Xiaoqin

2016-06-30

Transcription factors (TFs) are the proteins involved in the transcription process, ensuring the correct expression of specific genes. Numerous diseases arise from the dysfunction of specific TFs. In fact, over 30 TFs have been identified as therapeutic targets of about 9% of the approved drugs. In this study, we created a structural database of small molecule-transcription factor (SM-TF) complexes, available online at http://zoulab.dalton.missouri.edu/SM-TF. The 3D structures of the co-bound small molecule and the corresponding binding sites on TFs are provided in the database, serving as a valuable resource to assist structure-based drug design related to TFs. Currently, the SM-TF database contains 934 entries covering 176 TFs from a variety of species. The database is further classified into several subsets by species and organisms. The entries in the SM-TF database are linked to the UniProt database and other sequence-based TF databases. Furthermore, the druggable TFs from human and the corresponding approved drugs are linked to the DrugBank. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Using glycome databases for drug discovery.

PubMed

Aoki-Kinoshita, Kiyoko F

2008-08-01

The glycomics field has made great advancements in the last decade due to technologies for their synthesis and analysis including carbohydrate microarrays. Accordingly, databases for glycomics research have also emerged and been made publicly available by many major institutions worldwide. This review introduces these and other useful databases on which new methods for drug discovery can be developed. The scope of this review covers current documented and accessible databases and resources pertaining to glycomics. These were selected with the expectation that they may be useful for drug discovery research. There is a plethora of glycomics databases that have much potential for drug discovery. This may seem daunting at first but this review helps to put some of these resources into perspective. Additionally, some thoughts on how to integrate these resources to allow more efficient research are presented.

[Benefits of large healthcare databases for drug risk research].

PubMed

Garbe, Edeltraut; Pigeot, Iris

2015-08-01

Large electronic healthcare databases have become an important worldwide data resource for drug safety research after approval. Signal generation methods and drug safety studies based on these data facilitate the prospective monitoring of drug safety after approval, as has been recently required by EU law and the German Medicines Act. Despite its large size, a single healthcare database may include insufficient patients for the study of a very small number of drug-exposed patients or the investigation of very rare drug risks. For that reason, in the United States, efforts have been made to work on models that provide the linkage of data from different electronic healthcare databases for monitoring the safety of medicines after authorization in (i) the Sentinel Initiative and (ii) the Observational Medical Outcomes Partnership (OMOP). In July 2014, the pilot project Mini-Sentinel included a total of 178 million people from 18 different US databases. The merging of the data is based on a distributed data network with a common data model. In the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCEPP) there has been no comparable merging of data from different databases; however, first experiences have been gained in various EU drug safety projects. In Germany, the data of the statutory health insurance providers constitute the most important resource for establishing a large healthcare database. Their use for this purpose has so far been severely restricted by the Code of Social Law (Section 75, Book 10). Therefore, a reform of this section is absolutely necessary.

FlyRNAi.org—the database of the Drosophila RNAi screening center and transgenic RNAi project: 2017 update

PubMed Central

Hu, Yanhui; Comjean, Aram; Roesel, Charles; Vinayagam, Arunachalam; Flockhart, Ian; Zirin, Jonathan; Perkins, Lizabeth; Perrimon, Norbert; Mohr, Stephanie E.

2017-01-01

The FlyRNAi database of the Drosophila RNAi Screening Center (DRSC) and Transgenic RNAi Project (TRiP) at Harvard Medical School and associated DRSC/TRiP Functional Genomics Resources website (http://fgr.hms.harvard.edu) serve as a reagent production tracking system, screen data repository, and portal to the community. Through this portal, we make available protocols, online tools, and other resources useful to researchers at all stages of high-throughput functional genomics screening, from assay design and reagent identification to data analysis and interpretation. In this update, we describe recent changes and additions to our website, database and suite of online tools. Recent changes reflect a shift in our focus from a single technology (RNAi) and model species (Drosophila) to the application of additional technologies (e.g. CRISPR) and support of integrated, cross-species approaches to uncovering gene function using functional genomics and other approaches. PMID:27924039

Development of a Sigma-2 Receptor affinity filter through a Monte Carlo based QSAR analysis.

PubMed

Rescifina, Antonio; Floresta, Giuseppe; Marrazzo, Agostino; Parenti, Carmela; Prezzavento, Orazio; Nastasi, Giovanni; Dichiara, Maria; Amata, Emanuele

2017-08-30

For the first time in sigma-2 (σ 2 ) receptor field, a quantitative structure-activity relationship (QSAR) model has been built using pK i values of the whole set of known selective σ 2 receptor ligands (548 compounds), taken from the Sigma-2 Receptor Selective Ligands Database (S2RSLDB) (http://www.researchdsf.unict.it/S2RSLDB/), through the Monte Carlo technique and employing the software CORAL. The model has been developed by using a large and structurally diverse set of compounds, allowing for a prediction of different populations of chemical compounds endpoint (σ 2 receptor pK i ). The statistical quality reached, suggested that model for pK i determination is robust and possesses a satisfactory predictive potential. The statistical quality is high for both visible and invisible sets. The screening of the FDA approved drugs, external to our dataset, suggested that sixteen compounds might be repositioned as σ 2 receptor ligands (predicted pK i ≥8). A literature check showed that six of these compounds have already been tested for affinity at σ 2 receptor and, of these, two (Flunarizine and Terbinafine) have shown an experimental σ 2 receptor pK i >7. This suggests that this QSAR model may be used as focusing screening filter in order to prospectively find or repurpose new drugs with high affinity for the σ 2 receptor, and overall allowing for an enhanced hit rate respect to a random screening. Copyright © 2017 Elsevier B.V. All rights reserved.

21 CFR 1301.90 - Employee screening procedures.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 9 2011-04-01 2011-04-01 false Employee screening procedures. 1301.90 Section 1301.90 Food and Drugs DRUG ENFORCEMENT ADMINISTRATION, DEPARTMENT OF JUSTICE REGISTRATION OF... by non-practitioners is vital to fairly assess the likelihood of an employee committing a drug...

RAS - Screens & Assays - Drug Discovery

Cancer.gov

The RAS Drug Discovery group aims to develop assays that will reveal aspects of RAS biology upon which cancer cells depend. Successful assay formats are made available for high-throughput screening programs to yield potentially effective drug compounds.

Mammography usage with relevant factors among women with mental disabilities in Taiwan: a nationwide population-based study.

PubMed

Yen, Suh-May; Kung, Pei-Tseng; Tsai, Wen-Chen

2015-02-01

Women with mental illness are at increased risk of developing and dying from breast cancer and are thus in urgent need of breast cancer preventive care. This study examined the use of screening mammography by Taiwanese women with mental disabilities and analyzed factors affecting this use. 17,243 Taiwanese women with mental disabilities aged 50-69 years were retrospectively included as study subjects. Linked patient data were obtained from three national databases in Taiwan (the 2008 database of physically and mentally disabled persons, the Health Promotion Administration's 2007-2008 mammography screening data, and claims data from the National Health Insurance Research Database). Besides descriptive statistics and bivariate analysis, logistic regression analysis was also performed to examine factors affecting screening mammography use. The 2007-2008 mammography screening rate for Taiwanese women with mental disabilities was 8.79% (n=1515). Variables that significantly influenced screening use were income, education, presence of catastrophic illness/injury, severity of mental disability, and usage of other preventive care services. Screening was positively correlated with income and education. Those with catastrophic illness/injury were more likely to be screened (odds ratio [OR], 1.40; 95% CI=1.15-1.72). Severity of disability was negatively correlated with screening, with very severe, severe, and moderate disability being associated with 0.34-0.69 times the odds of screening as mild disability. In Taiwan, women with mental disabilities receive far less mammography screening than women in general. Copyright © 2014 Elsevier Ltd. All rights reserved.

Presence and Accuracy of Drug Dosage Recommendations for Continuous Renal Replacement Therapy in Tertiary Drug Information References

PubMed Central

Gorman, Sean K; Slavik, Richard S; Lam, Stefanie

2012-01-01

Background: Clinicians commonly rely on tertiary drug information references to guide drug dosages for patients who are receiving continuous renal replacement therapy (CRRT). It is unknown whether the dosage recommendations in these frequently used references reflect the most current evidence. Objective: To determine the presence and accuracy of drug dosage recommendations for patients undergoing CRRT in 4 drug information references. Methods: Medications commonly prescribed during CRRT were identified from an institutional medication inventory database, and evidence-based dosage recommendations for this setting were developed from the primary and secondary literature. The American Hospital Formulary System—Drug Information (AHFS–DI), Micromedex 2.0 (specifically the DRUGDEX and Martindale databases), and the 5th edition of Drug Prescribing in Renal Failure (DPRF5) were assessed for the presence of drug dosage recommendations in the CRRT setting. The dosage recommendations in these tertiary references were compared with the recommendations derived from the primary and secondary literature to determine concordance. Results: Evidence-based drug dosage recommendations were developed for 33 medications administered in patients undergoing CRRT. The AHFS–DI provided no dosage recommendations specific to CRRT, whereas the DPRF5 provided recommendations for 27 (82%) of the medications and the Micromedex 2.0 application for 20 (61%) (13 [39%] in the DRUGDEX database and 16 [48%] in the Martindale database, with 9 medications covered by both). The dosage recommendations were in concordance with evidence-based recommendations for 12 (92%) of the 13 medications in the DRUGDEX database, 26 (96%) of the 27 in the DPRF5, and all 16 (100%) of those in the Martindale database. Conclusions: One prominent tertiary drug information resource provided no drug dosage recommendations for patients undergoing CRRT. However, 2 of the databases in an Internet-based medical information application and the latest edition of a renal specialty drug information resource provided recommendations for a majority of the medications investigated. Most dosage recommendations were similar to those derived from the primary and secondary literature. The most recent edition of the DPRF is the preferred source of information when prescribing dosage regimens for patients receiving CRRT. PMID:22783029

Prevalence of illicit drug use in pregnant women in a Wisconsin private practice setting.

PubMed

Schauberger, Charles W; Newbury, Emily J; Colburn, Jean M; Al-Hamadani, Mohammed

2014-09-01

We sought to measure the prevalence of illicit drug use in our obstetric population, to identify the drugs being used, and to determine whether a modified version of the 4Ps Plus screening tool could serve as an initial screen. In this prospective study, urine samples of 200 unselected patients presenting for initiation of prenatal care in a Wisconsin private practice were analyzed for evidence of the use of illicit drugs. Of 200 patients, 26 (13%) had evidence of drugs of abuse in their urine samples. Marijuana (7%) and opioids (6.5%) were the most commonly identified drugs. Adding 5 questions about drug or alcohol use to the obstetric intake questionnaire proved sensitive in identifying patients with high risks of having a positive drug screen. The rate of drug use in our low-risk population was higher than expected and may reflect increasing rates of drug use across the United States. Enhanced screening should be performed to identify patients using illicit drugs in pregnancy to improve their care. Medical centers and communities may benefit from periodic testing of their community prevalence rates to aid in appropriate care planning. Copyright © 2014 Mosby, Inc. All rights reserved.

Drug target identification in protozoan parasites.

PubMed

Müller, Joachim; Hemphill, Andrew

2016-08-01

Despite the fact that diseases caused by protozoan parasites represent serious challenges for public health, animal production and welfare, only a limited panel of drugs has been marketed for clinical applications. Herein, the authors investigate two strategies, namely whole organism screening and target-based drug design. The present pharmacopoeia has resulted from whole organism screening, and the mode of action and targets of selected drugs are discussed. However, the more recent extensive genome sequencing efforts and the development of dry and wet lab genomics and proteomics that allow high-throughput screening of interactions between micromolecules and recombinant proteins has resulted in target-based drug design as the predominant focus in anti-parasitic drug development. Selected examples of target-based drug design studies are presented, and calcium-dependent protein kinases, important drug targets in apicomplexan parasites, are discussed in more detail. Despite the enormous efforts in target-based drug development, this approach has not yet generated market-ready antiprotozoal drugs. However, whole-organism screening approaches, comprising of both in vitro and in vivo investigations, should not be disregarded. The repurposing of already approved and marketed drugs could be a suitable strategy to avoid fastidious approval procedures, especially in the case of neglected or veterinary parasitoses.

Phenotypic screening in cancer drug discovery - past, present and future.

PubMed

Moffat, John G; Rudolph, Joachim; Bailey, David

2014-08-01

There has been a resurgence of interest in the use of phenotypic screens in drug discovery as an alternative to target-focused approaches. Given that oncology is currently the most active therapeutic area, and also one in which target-focused approaches have been particularly prominent in the past two decades, we investigated the contribution of phenotypic assays to oncology drug discovery by analysing the origins of all new small-molecule cancer drugs approved by the US Food and Drug Administration (FDA) over the past 15 years and those currently in clinical development. Although the majority of these drugs originated from target-based discovery, we identified a significant number whose discovery depended on phenotypic screening approaches. We postulate that the contribution of phenotypic screening to cancer drug discovery has been hampered by a reliance on 'classical' nonspecific drug effects such as cytotoxicity and mitotic arrest, exacerbated by a paucity of mechanistically defined cellular models for therapeutically translatable cancer phenotypes. However, technical and biological advances that enable such mechanistically informed phenotypic models have the potential to empower phenotypic drug discovery in oncology.

Nosocomial spontaneous bacterial peritonitis antibiotic treatment in the era of multi-drug resistance pathogens: A systematic review.

PubMed

Fiore, Marco; Maraolo, Alberto Enrico; Gentile, Ivan; Borgia, Guglielmo; Leone, Sebastiano; Sansone, Pasquale; Passavanti, Maria Beatrice; Aurilio, Caterina; Pace, Maria Caterina

2017-07-07

To systematically review literature upon aetiology of nosocomial spontaneous bacterial peritonitis (N-SBP) given the rising importance of multidrug-resistant (MDR) bacteria. A literature search was performed on MEDLINE and Google Scholar databases from 2000 to 15 th of November 2016, using the following search strategy: "spontaneous" AND "peritonitis". The initial search through electronic databases retrieved 2556 records. After removing duplicates, 1958 records remained. One thousand seven hundred and thirty-five of them were excluded on the basis of the screening of titles and abstract, and the ensuing number of remaining articles was 223. Of these records, after careful evaluation, only 9 were included in the qualitative analysis. The overall proportion of MDR bacteria turned out to be from 22% to 73% of cases across the studies. N-SBP is caused, in a remarkable proportion, by MDR pathogens. This should prompt a careful re-assessment of guidelines addressing the treatment of this clinical entity.

Identification of some novel pyrazolo[1,5-a]pyrimidine derivatives as InhA inhibitors through pharmacophore-based virtual screening and molecular docking.

PubMed

Modi, Palmi; Patel, Shivani; Chhabria, Mahesh T

2018-05-04

The InhA inhibitors play key role in mycolic acid synthesis by preventing the fatty acid biosynthesis pathway. In this present article, Pharmacophore modelling and molecular docking study followed by in silico virtual screening could be considered as effective strategy to identify newer enoyl-ACP reductase inhibitors. Pyrrolidine carboxamide derivatives were opted to generate pharmacophore models using HypoGen algorithm in Discovery studio 2.1. Further it was employed to screen Zinc and Minimaybridge databases to identify and design newer potent hit molecules. The retrieved newer hits were further evaluated for their drug likeliness and docked against enoyl acyl carrier protein reductase. Here, novel pyrazolo[1,5-a]pyrimidine analogues were designed and synthesized with good yields. Structural elucidation of synthesized final molecules was perform through IR, MASS, 1 H-NMR, 13 C-NMR spectroscopy and further tested for its in vitro anti-tubercular activity against H37Rv strain using Microplate Alamar blue assay (MABA) method. Most of the synthesized compounds displayed strong anti-tubercular activities. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study.

Discovery of Novel New Delhi Metallo-β-Lactamases-1 Inhibitors by Multistep Virtual Screening

PubMed Central

Wang, Xuequan; Lu, Meiling; Shi, Yang; Ou, Yu; Cheng, Xiaodong

2015-01-01

The emergence of NDM-1 containing multi-antibiotic resistant "Superbugs" necessitates the needs of developing of novel NDM-1inhibitors. In this study, we report the discovery of novel NDM-1 inhibitors by multi-step virtual screening. From a 2,800,000 virtual drug-like compound library selected from the ZINC database, we generated a focused NDM-1 inhibitor library containing 298 compounds of which 44 chemical compounds were purchased and evaluated experimentally for their ability to inhibit NDM-1 in vitro. Three novel NDM-1 inhibitors with micromolar IC50 values were validated. The most potent inhibitor, VNI-41, inhibited NDM-1 with an IC50 of 29.6 ± 1.3 μM. Molecular dynamic simulation revealed that VNI-41 interacted extensively with the active site. In particular, the sulfonamide group of VNI-41 interacts directly with the metal ion Zn1 that is critical for the catalysis. These results demonstrate the feasibility of applying virtual screening methodologies in identifying novel inhibitors for NDM-1, a metallo-β-lactamase with a malleable active site and provide a mechanism base for rational design of NDM-1 inhibitors using sulfonamide as a functional scaffold. PMID:25734558

Renal cell carcinoma: Review of etiology, pathophysiology and risk factors.

PubMed

Petejova, Nadezda; Martinek, Arnost

2016-06-01

The global incidence of renal cell cancer is increasing annually and the causes are multifactorial. Early diagnosis and successful urological procedures with partial or total nephrectomy can be life-saving. However, only up to 10% of RCC patients present with characteristic clinical symptoms. Over 60% are detected incidentally in routine ultrasound examination. The question of screening and preventive measures greatly depends on the cause of the tumor development. For the latter reason, this review focuses on etiology, pathophysiology and risk factors for renal neoplasm. A literature search using the databases Medscape, Pubmed, UpToDate and EBSCO from 1945 to 2015. Genetic predisposition/hereditary disorders, obesity, smoking, various nephrotoxic industrial chemicals, drugs and natural/manmade radioactivity all contribute and enviromental risks are a serious concern in terms of prevention and the need to screen populations at risk. Apropos treatment, current oncological research is directed to blocking cancer cell division and inhibiting angiogenesis based on a knowledge of molecular pathways.

Extensive characterization of peptides from Panax ginseng C. A. Meyer using mass spectrometric approach.

PubMed

Ye, Xueting; Zhao, Nan; Yu, Xi; Han, Xiaoli; Gao, Huiyuan; Zhang, Xiaozhe

2016-11-01

Panax ginseng is an important herb that has clear effects on the treatment of diverse diseases. Until now, the natural peptide constitution of this herb remains unclear. Here, we conduct an extensive characterization of Ginseng peptidome using MS-based data mining and sequencing. The screen on the charge states of precursor ions indicated that Ginseng is a peptide-rich herb in comparison of a number of commonly used herbs. The Ginseng peptides were then extracted and submitted to nano-LC-MS/MS analysis using different fragmentation modes, including CID, high-energy collisional dissociation, and electron transfer dissociation. Further database search and de novo sequencing allowed the identification of total 308 peptides, some of which might have important biological activities. This study illustrates the abundance and sequences of endogenous Ginseng peptides, thus providing the information of more candidates for the screening of active compounds for future biological research and drug discovery studies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discovery of Novel Anti-prion Compounds Using In Silico and In Vitro Approaches

PubMed Central

Hyeon, Jae Wook; Choi, Jiwon; Kim, Su Yeon; Govindaraj, Rajiv Gandhi; Jam Hwang, Kyu; Lee, Yeong Seon; An, Seong Soo A.; Lee, Myung Koo; Joung, Jong Young; No, Kyoung Tai; Lee, Jeongmin

2015-01-01

Prion diseases are associated with the conformational conversion of the physiological form of cellular prion protein (PrPC) to the pathogenic form, PrPSc. Compounds that inhibit this process by blocking conversion to the PrPSc could provide useful anti-prion therapies. However, no suitable drugs have been identified to date. To identify novel anti-prion compounds, we developed a combined structure- and ligand-based virtual screening system in silico. Virtual screening of a 700,000-compound database, followed by cluster analysis, identified 37 compounds with strong interactions with essential hotspot PrP residues identified in a previous study of PrPC interaction with a known anti-prion compound (GN8). These compounds were tested in vitro using a multimer detection system, cell-based assays, and surface plasmon resonance. Some compounds effectively reduced PrPSc levels and one of these compounds also showed a high binding affinity for PrPC. These results provide a promising starting point for the development of anti-prion compounds. PMID:26449325

Computational Study on New Natural Compound Inhibitors of Pyruvate Dehydrogenase Kinases

PubMed Central

Zhou, Xiaoli; Yu, Shanshan; Su, Jing; Sun, Liankun

2016-01-01

Pyruvate dehydrogenase kinases (PDKs) are key enzymes in glucose metabolism, negatively regulating pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibiting PDKs could upregulate PDC activity and drive cells into more aerobic metabolism. Therefore, PDKs are potential targets for metabolism related diseases, such as cancers and diabetes. In this study, a series of computer-aided virtual screening techniques were utilized to discover potential inhibitors of PDKs. Structure-based screening using Libdock was carried out following by ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was used to analyze the binding mechanism between these compounds and PDKs. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. From the computational results, two novel natural coumarins compounds (ZINC12296427 and ZINC12389251) from the ZINC database were found binding to PDKs with favorable interaction energy and predicted to be non-toxic. Our study provide valuable information of PDK-coumarins binding mechanisms in PDK inhibitor-based drug discovery. PMID:26959013

Computational Study on New Natural Compound Inhibitors of Pyruvate Dehydrogenase Kinases.

PubMed

Zhou, Xiaoli; Yu, Shanshan; Su, Jing; Sun, Liankun

2016-03-04

Pyruvate dehydrogenase kinases (PDKs) are key enzymes in glucose metabolism, negatively regulating pyruvate dehyrogenase complex (PDC) activity through phosphorylation. Inhibiting PDKs could upregulate PDC activity and drive cells into more aerobic metabolism. Therefore, PDKs are potential targets for metabolism related diseases, such as cancers and diabetes. In this study, a series of computer-aided virtual screening techniques were utilized to discover potential inhibitors of PDKs. Structure-based screening using Libdock was carried out following by ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction. Molecular docking was used to analyze the binding mechanism between these compounds and PDKs. Molecular dynamic simulation was utilized to confirm the stability of potential compound binding. From the computational results, two novel natural coumarins compounds (ZINC12296427 and ZINC12389251) from the ZINC database were found binding to PDKs with favorable interaction energy and predicted to be non-toxic. Our study provide valuable information of PDK-coumarins binding mechanisms in PDK inhibitor-based drug discovery.

In silico toxicology for the pharmaceutical sciences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valerio, Luis G., E-mail: Luis.Valerio@fda.hhs.go

2009-12-15

The applied use of in silico technologies (a.k.a. computational toxicology, in silico toxicology, computer-assisted tox, e-tox, i-drug discovery, predictive ADME, etc.) for predicting preclinical toxicological endpoints, clinical adverse effects, and metabolism of pharmaceutical substances has become of high interest to the scientific community and the public. The increased accessibility of these technologies for scientists and recent regulations permitting their use for chemical risk assessment supports this notion. The scientific community is interested in the appropriate use of such technologies as a tool to enhance product development and safety of pharmaceuticals and other xenobiotics, while ensuring the reliability and accuracy ofmore » in silico approaches for the toxicological and pharmacological sciences. For pharmaceutical substances, this means active and impurity chemicals in the drug product may be screened using specialized software and databases designed to cover these substances through a chemical structure-based screening process and algorithm specific to a given software program. A major goal for use of these software programs is to enable industry scientists not only to enhance the discovery process but also to ensure the judicious use of in silico tools to support risk assessments of drug-induced toxicities and in safety evaluations. However, a great amount of applied research is still needed, and there are many limitations with these approaches which are described in this review. Currently, there is a wide range of endpoints available from predictive quantitative structure-activity relationship models driven by many different computational software programs and data sources, and this is only expected to grow. For example, there are models based on non-proprietary and/or proprietary information specific to assessing potential rodent carcinogenicity, in silico screens for ICH genetic toxicity assays, reproductive and developmental toxicity, theoretical prediction of human drug metabolism, mechanisms of action for pharmaceuticals, and newer models for predicting human adverse effects. How accurate are these approaches is both a statistical issue and challenge in toxicology. In this review, fundamental concepts and the current capabilities and limitations of this technology will be critically addressed.« less

Transition to injecting drug use in Iran: a systematic review of qualitative and quantitative evidence

PubMed Central

Rahimi-Movaghar, Afarin; Amin-Esmaeili, Masoumeh; Shadloo, Behrang; Malekinejad, Mohsen

2015-01-01

Background Injection drug use has been increasing over the past decade in Iran. This study aims to review the epidemiological and qualitative evidence on factors that facilitate or protect against transition to injection in Iran. Methods Five international (Medline, Web of Science, EMBASE, CINAHL, PsycINFO), one regional (IMEMR) and three Iranian (Iranmedex, Iranpsych, IranDoc) databases were searched and key experts were contacted. Two trained researchers screened documents to identify relevant studies and independently extracted data using a pre-specified protocol. A thematic analysis was applied to the qualitative data and a random effect meta-analysis model was used to determine age of first injection. Results A total of 39 documents from 31 studies met the eligibility criteria; more than 50% were conducted between 2006 and 2008. The weighted mean age of first injection was 25.8 years (95% Confidence Interval: 25.3–26.2). Overall, drug users had used drugs for 6 to 7 years before starting to inject. Heroin was the first drug of injection in the majority of cases. Factors influencing transition to injection included 1) individual (pleasure-seeking behavior and development of drug dependency), 2) social network (role of peer drug users in first injection use), and 3) environmental (the economic efficiency associated with injection and the wide availability of injectable form of drugs in the market). Conclusion Harm reduction policies in Iran have almost exclusively focused on drug injectors. However, given the extent of non-injection drug use, evidence from this study can provide insight on points of interventions for preventing transition to injection use. PMID:26210009

Comprehensive List of Cancer-Related Genetic Variations of the NCI-60 Panel | Center for Cancer Research

Cancer.gov

The NCI-60 cell lines are the most frequently studied human tumor cell lines in cancer research. The panel of cell lines represents nine different types of cancer: breast, ovary, prostate, colon, lung, kidney, brain, leukemia, and melanoma. Originally developed to screen anticancer compounds by the NCI Developmental Therapeutics Program (DTP), the NCI-60 panel has generated the most extensive cancer pharmacology database worldwide. The 60 cell lines have also been extensively analyzed for their gene and microRNA expression levels, DNA mutation status, and DNA copy number variations. These findings have provided the groundwork for research centered on increasing our understanding of tumor biology and drug activity.

LS-align: an atom-level, flexible ligand structural alignment algorithm for high-throughput virtual screening.

PubMed

Hu, Jun; Liu, Zi; Yu, Dong-Jun; Zhang, Yang

2018-02-15

Sequence-order independent structural comparison, also called structural alignment, of small ligand molecules is often needed for computer-aided virtual drug screening. Although many ligand structure alignment programs are proposed, most of them build the alignments based on rigid-body shape comparison which cannot provide atom-specific alignment information nor allow structural variation; both abilities are critical to efficient high-throughput virtual screening. We propose a novel ligand comparison algorithm, LS-align, to generate fast and accurate atom-level structural alignments of ligand molecules, through an iterative heuristic search of the target function that combines inter-atom distance with mass and chemical bond comparisons. LS-align contains two modules of Rigid-LS-align and Flexi-LS-align, designed for rigid-body and flexible alignments, respectively, where a ligand-size independent, statistics-based scoring function is developed to evaluate the similarity of ligand molecules relative to random ligand pairs. Large-scale benchmark tests are performed on prioritizing chemical ligands of 102 protein targets involving 1,415,871 candidate compounds from the DUD-E (Database of Useful Decoys: Enhanced) database, where LS-align achieves an average enrichment factor (EF) of 22.0 at the 1% cutoff and the AUC score of 0.75, which are significantly higher than other state-of-the-art methods. Detailed data analyses show that the advanced performance is mainly attributed to the design of the target function that combines structural and chemical information to enhance the sensitivity of recognizing subtle difference of ligand molecules and the introduces of structural flexibility that help capture the conformational changes induced by the ligand-receptor binding interactions. These data demonstrate a new avenue to improve the virtual screening efficiency through the development of sensitive ligand structural alignments. http://zhanglab.ccmb.med.umich.edu/LS-align/. njyudj@njust.edu.cn or zhng@umich.edu. Supplementary data are available at Bioinformatics online.

Profiling the NIH Small Molecule Repository for Compounds That Generate H2O2 by Redox Cycling in Reducing Environments

PubMed Central

2010-01-01

We have screened the Library of Pharmacologically Active Compounds (LOPAC) and the National Institutes of Health (NIH) Small Molecule Repository (SMR) libraries in a horseradish peroxidase–phenol red (HRP-PR) H2O2 detection assay to identify redox cycling compounds (RCCs) capable of generating H2O2 in buffers containing dithiothreitol (DTT). Two RCCs were identified in the LOPAC set, the ortho-naphthoquinone β-lapachone and the para-naphthoquinone NSC 95397. Thirty-seven (0.02%) concentration-dependent RCCs were identified from 195,826 compounds in the NIH SMR library; 3 singleton structures, 9 ortho-quinones, 2 para-quinones, 4 pyrimidotriazinediones, 15 arylsulfonamides, 2 nitrothiophene-2-carboxylates, and 2 tolyl hydrazides. Sixty percent of the ortho-quinones and 80% of the pyrimidotriazinediones in the library were confirmed as RCCs. In contrast, only 3.9% of the para-quinones were confirmed as RCCs. Fifteen of the 251 arylsulfonamides in the library were confirmed as RCCs, and since we screened 17,868 compounds with a sulfonamide functional group we conclude that the redox cycling activity of the arylsulfonamide RCCs is due to peripheral reactive enone, aromatic, or heterocyclic functions. Cross-target queries of the University of Pittsburgh Drug Discovery Institute (UPDDI) and PubChem databases revealed that the RCCs exhibited promiscuous bioactivity profiles and have populated both screening databases with significantly higher numbers of active flags than non-RCCs. RCCs were promiscuously active against protein targets known to be susceptible to oxidation, but were also active in cell growth inhibition assays, and against other targets thought to be insensitive to oxidation. Profiling compound libraries or the hits from screening campaigns in the HRP-PR H2O2 detection assay significantly reduce the timelines and resources required to identify and eliminate promiscuous nuisance RCCs from the candidates for lead optimization. PMID:20070233

Drugged Driving in Wisconsin: Oral Fluid Versus Blood.

PubMed

Edwards, Lorrine D; Smith, Katherine L; Savage, Theodore

2017-07-01

A pilot project was conducted in Dane County, Wisconsin, to evaluate the frequency of individuals driving under the influence of drugs (DUID). Evidentiary blood specimens, collected from subjects arrested for Operating While Intoxicated (OWI), were compared to oral fluid (OF) results obtained with the Alere DDS2®, a handheld screening device. The project objectives were to evaluate (i) the Alere DDS2® for use by police officers in the field, (ii) the frequency of individuals DUID and drugs combined with alcohol among OWI cases, (iii) the differences between detecting drugs in OF and in blood, and (iv) the effect of the laboratory drug testing cancellation policy (LCP) when the blood alcohol concentration (BAC) exceeds 0.100 g/100 mL. Following the arrest and collection of blood, subjects were asked to voluntarily participate in the project and provide an OF specimen. The OF was presumptively screened with the Alere DDS2® for six drug categories including (ng/mL) amphetamine (50), benzodiazepines (temazepam, 20), cocaine (benzoylecgonine, 30), methamphetamine (50), opioids (morphine, 40) and THC (delta-9-THC, 25). Results obtained with the OF screening instrument were not confirmed. A total of 104 subjects (22 female, 82 male), ages 18-72, were included in the project. Blood specimens were tested by gas chromatography-headspace (GCHS-FID) for volatiles, enzyme immunoassay (Siemens Viva-E Drug Testing System), and an alkaline basic drug screen with gas chromatography-mass spectrometry (GCMS) analysis. To compensate for differences between the EIA and the Alere DDS2® drug categories, results from the enzyme immunoassay and the alkaline basic drug screen were combined for purposes of comparing OF to blood. Seventy-six of 104 (73%) subjects arrested for OWI were driving under the influence of alcohol; 71 of the 76 had a BAC exceeding 0.10 g/100 mL. Subjects with a BAC exceeding the LCP, screened positive for drugs in both OF (n = 29) and blood (n = 28). Overall, one or more positive drug screening result was observed in 57 (55%) and 50 (48%) subjects for OF and blood specimens, respectively. THC was the most frequently detected drug category in both OF (n = 46) and whole blood (n = 44). Drug Recognition Expert (DRE) evaluations were performed on 18 subjects. In general, the Alere DDS2® results were consistent with the combined screening results observed in evidentiary blood specimens. This project was limited in scope as a second OF specimen was not collected for confirmation of drugs, however it did demonstrate that nearly 40% of the subjects with concentrations of alcohol exceeding 0.10 g/100 mL, screened positive for one or more drug categories in both OF and blood. The Alere DDS2® portable OF screening instrument may be useful in assisting law enforcement with identifying individuals driving under the influence of drugs and establishing probable cause at roadside for making DUID arrests. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Performance of Machine Learning Algorithms for Qualitative and Quantitative Prediction Drug Blockade of hERG1 channel.

PubMed

Wacker, Soren; Noskov, Sergei Yu

2018-05-01

Drug-induced abnormal heart rhythm known as Torsades de Pointes (TdP) is a potential lethal ventricular tachycardia found in many patients. Even newly released anti-arrhythmic drugs, like ivabradine with HCN channel as a primary target, block the hERG potassium current in overlapping concentration interval. Promiscuous drug block to hERG channel may potentially lead to perturbation of the action potential duration (APD) and TdP, especially when with combined with polypharmacy and/or electrolyte disturbances. The example of novel anti-arrhythmic ivabradine illustrates clinically important and ongoing deficit in drug design and warrants for better screening methods. There is an urgent need to develop new approaches for rapid and accurate assessment of how drugs with complex interactions and multiple subcellular targets can predispose or protect from drug-induced TdP. One of the unexpected outcomes of compulsory hERG screening implemented in USA and European Union resulted in large datasets of IC 50 values for various molecules entering the market. The abundant data allows now to construct predictive machine-learning (ML) models. Novel ML algorithms and techniques promise better accuracy in determining IC 50 values of hERG blockade that is comparable or surpassing that of the earlier QSAR or molecular modeling technique. To test the performance of modern ML techniques, we have developed a computational platform integrating various workflows for quantitative structure activity relationship (QSAR) models using data from the ChEMBL database. To establish predictive powers of ML-based algorithms we computed IC 50 values for large dataset of molecules and compared it to automated patch clamp system for a large dataset of hERG blocking and non-blocking drugs, an industry gold standard in studies of cardiotoxicity. The optimal protocol with high sensitivity and predictive power is based on the novel eXtreme gradient boosting (XGBoost) algorithm. The ML-platform with XGBoost displays excellent performance with a coefficient of determination of up to R 2 ~0.8 for pIC 50 values in evaluation datasets, surpassing other metrics and approaches available in literature. Ultimately, the ML-based platform developed in our work is a scalable framework with automation potential to interact with other developing technologies in cardiotoxicity field, including high-throughput electrophysiology measurements delivering large datasets of profiled drugs, rapid synthesis and drug development via progress in synthetic biology.

Machine learning plus optical flow: a simple and sensitive method to detect cardioactive drugs

NASA Astrophysics Data System (ADS)

Lee, Eugene K.; Kurokawa, Yosuke K.; Tu, Robin; George, Steven C.; Khine, Michelle

2015-07-01

Current preclinical screening methods do not adequately detect cardiotoxicity. Using human induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs), more physiologically relevant preclinical or patient-specific screening to detect potential cardiotoxic effects of drug candidates may be possible. However, one of the persistent challenges for developing a high-throughput drug screening platform using iPS-CMs is the need to develop a simple and reliable method to measure key electrophysiological and contractile parameters. To address this need, we have developed a platform that combines machine learning paired with brightfield optical flow as a simple and robust tool that can automate the detection of cardiomyocyte drug effects. Using three cardioactive drugs of different mechanisms, including those with primarily electrophysiological effects, we demonstrate the general applicability of this screening method to detect subtle changes in cardiomyocyte contraction. Requiring only brightfield images of cardiomyocyte contractions, we detect changes in cardiomyocyte contraction comparable to - and even superior to - fluorescence readouts. This automated method serves as a widely applicable screening tool to characterize the effects of drugs on cardiomyocyte function.

Rationale and uses of a public HIV drug-resistance database.

PubMed

Shafer, Robert W

2006-09-15

Knowledge regarding the drug resistance of human immunodeficiency virus (HIV) is critical for surveillance of drug resistance, development of antiretroviral drugs, and management of infections with drug-resistant viruses. Such knowledge is derived from studies that correlate genetic variation in the targets of therapy with the antiretroviral treatments received by persons from whom the variant was obtained (genotype-treatment), with drug-susceptibility data on genetic variants (genotype-phenotype), and with virological and clinical response to a new treatment regimen (genotype-outcome). An HIV drug-resistance database is required to represent, store, and analyze the diverse forms of data underlying our knowledge of drug resistance and to make these data available to the broad community of researchers studying drug resistance in HIV and clinicians using HIV drug-resistance tests. Such genotype-treatment, genotype-phenotype, and genotype-outcome correlations are contained in the Stanford HIV RT and Protease Sequence Database and have specific usefulness.

GEAR: A database of Genomic Elements Associated with drug Resistance.

PubMed

Wang, Yin-Ying; Chen, Wei-Hua; Xiao, Pei-Pei; Xie, Wen-Bin; Luo, Qibin; Bork, Peer; Zhao, Xing-Ming

2017-03-15

Drug resistance is becoming a serious problem that leads to the failure of standard treatments, which is generally developed because of genetic mutations of certain molecules. Here, we present GEAR (A database of Genomic Elements Associated with drug Resistance) that aims to provide comprehensive information about genomic elements (including genes, single-nucleotide polymorphisms and microRNAs) that are responsible for drug resistance. Right now, GEAR contains 1631 associations between 201 human drugs and 758 genes, 106 associations between 29 human drugs and 66 miRNAs, and 44 associations between 17 human drugs and 22 SNPs. These relationships are firstly extracted from primary literature with text mining and then manually curated. The drug resistome deposited in GEAR provides insights into the genetic factors underlying drug resistance. In addition, new indications and potential drug combinations can be identified based on the resistome. The GEAR database can be freely accessed through http://gear.comp-sysbio.org.

GEAR: A database of Genomic Elements Associated with drug Resistance

PubMed Central

Wang, Yin-Ying; Chen, Wei-Hua; Xiao, Pei-Pei; Xie, Wen-Bin; Luo, Qibin; Bork, Peer; Zhao, Xing-Ming

2017-01-01

Drug resistance is becoming a serious problem that leads to the failure of standard treatments, which is generally developed because of genetic mutations of certain molecules. Here, we present GEAR (A database of Genomic Elements Associated with drug Resistance) that aims to provide comprehensive information about genomic elements (including genes, single-nucleotide polymorphisms and microRNAs) that are responsible for drug resistance. Right now, GEAR contains 1631 associations between 201 human drugs and 758 genes, 106 associations between 29 human drugs and 66 miRNAs, and 44 associations between 17 human drugs and 22 SNPs. These relationships are firstly extracted from primary literature with text mining and then manually curated. The drug resistome deposited in GEAR provides insights into the genetic factors underlying drug resistance. In addition, new indications and potential drug combinations can be identified based on the resistome. The GEAR database can be freely accessed through http://gear.comp-sysbio.org. PMID:28294141

Analysis of 44 drugs of abuse and metabolites in wastewater and river water using a hybrid quadrupole time-of-flight tandem mass spectrometry

NASA Astrophysics Data System (ADS)

Andres-Costa, M. Jesus; Andreu, Vicente; Picó, Yolanda

2016-04-01

The presence of drugs of abuse in the aquatic environment has been recognized as an important issue for the ecosystem due their possible negative effect on it (Richardson, 2011). Incomplete removal of these substances during wastewater treatment could be one of the causes of their release in the environment (Zuccato and Castiglioni, 2009). Pollution by illicit drug residues at very low concentrations is generalized in populated areas, with potential risks for human health and the environment (Zuccato, 2008; Castiglioni et al 2007).The aim of this study was to screen and quantify 44 drugs of abuse and metabolites of wastewater samples using a hybrid quadrupole time-of-flight tandem mass spectrometry and furthermore carry out a post-target screening to identify additional compounds present in the water samples. Wastewater samples were collected from the influent and effluent of three wastewater treatment plants (WWTPs) in Valencia and river water samples form Turia River Basin. Illicit drugs were extracted by solid-phase extraction (SPE). The chromatography was performed with an Agilent 1260 Infinity ultra high performance liquid chromatography (UHPLC). The UHPLC system was coupled to a hybrid quadrupole time-of-flight ABSciex Triple TOFTM 5600. All analytes were analyzed in positive mode. Acquiring full scan MS data was employed for quantification of drugs of abuse, and automatic data dependent information product ion spectra (IDA-MS/MS) was checked for identifying emerging illicit drugs and other compounds in water samples. The use of a database containing 1212 compounds achieved high confidence results for a wide number of contaminants. In the present study, the presence of compounds that belong to amphetamines group (amphetamine, methamphetamine, ephedrine, MDMA, MDA and MDEA), tryptamines (bufotenine), pirrolidinophenone group (α-PVP and 4'-MePHP), arylcyclohexylamines (ketamine), cocainics (cocaine, benzoylecgonine, cocaethylene and ecgonine methyl ester) and morphine derivatives (codeine, EDDP, morphine and methadone) and cannabinoids (THC) were detected in the influent, effluent or river water samples. These compounds were quantified, reaching cocainics and morphine derivates the highest values. Regarding post-target screening approach, more than 120 contaminants, mostly pharmaceuticals, but also mycotoxins and polyphenols were unambiguously identified. This new approach to data evaluation by non-target screening analyses opens the possibility of various other applications, for example in open and groundwater or for monitoring natural attenuation. Acknowledgements This work has been supported by the Spanish Ministry of Economy and Competitiveness trough the project CGL 2011-29703-C02-02. MJ Andrés Costa also acknowledges to this Ministry the FPI grant to perform her PhD. References Castiglioni S, Zuccato E. Chiabrando C., Faneli R., Bagnati R. Spectroscopy Europe (2007), 19, 7-9. Richardson SD. Anal Chem (2011), 84, 747-778. Zuccato E., Castiglioni S. Philos Trans R Soc A (2009), 367, 3965-3978. Zuccato E., Castiglioni S., Bagnati, R., Chiabrando C., Grassi P., Fanelli R. Water Res (2008), 42, 961-968.

An update on the use of C. elegans for preclinical drug discovery: screening and identifying anti-infective drugs.

PubMed

Kim, Wooseong; Hendricks, Gabriel Lambert; Lee, Kiho; Mylonakis, Eleftherios

2017-06-01

The emergence of antibiotic-resistant and -tolerant bacteria is a major threat to human health. Although efforts for drug discovery are ongoing, conventional bacteria-centered screening strategies have thus far failed to yield new classes of effective antibiotics. Therefore, new paradigms for discovering novel antibiotics are of critical importance. Caenorhabditis elegans, a model organism used for in vivo, offers a promising solution for identification of anti-infective compounds. Areas covered: This review examines the advantages of C. elegans-based high-throughput screening over conventional, bacteria-centered in vitro screens. It discusses major anti-infective compounds identified from large-scale C. elegans-based screens and presents the first clinically-approved drugs, then known bioactive compounds, and finally novel small molecules. Expert opinion: There are clear advantages of using a C. elegans-infection based screening method. A C. elegans-based screen produces an enriched pool of non-toxic, efficacious, potential anti-infectives, covering: conventional antimicrobial agents, immunomodulators, and anti-virulence agents. Although C. elegans-based screens do not denote the mode of action of hit compounds, this can be elucidated in secondary studies by comparing the results to target-based screens, or conducting subsequent target-based screens, including the genetic knock-down of host or bacterial genes.

Database for High Throughput Screening Hits (dHITS): a simple tool to retrieve gene specific phenotypes from systematic screens done in yeast.

PubMed

Chuartzman, Silvia G; Schuldiner, Maya

2018-03-25

In the last decade several collections of Saccharomyces cerevisiae yeast strains have been created. In these collections every gene is modified in a similar manner such as by a deletion or the addition of a protein tag. Such libraries have enabled a diversity of systematic screens, giving rise to large amounts of information regarding gene functions. However, often papers describing such screens focus on a single gene or a small set of genes and all other loci affecting the phenotype of choice ('hits') are only mentioned in tables that are provided as supplementary material and are often hard to retrieve or search. To help unify and make such data accessible, we have created a Database of High Throughput Screening Hits (dHITS). The dHITS database enables information to be obtained about screens in which genes of interest were found as well as the other genes that came up in that screen - all in a readily accessible and downloadable format. The ability to query large lists of genes at the same time provides a platform to easily analyse hits obtained from transcriptional analyses or other screens. We hope that this platform will serve as a tool to facilitate investigation of protein functions to the yeast community. © 2018 The Authors Yeast Published by John Wiley & Sons Ltd.

Network pharmacology-based prediction of active compounds and molecular targets in Yijin-Tang acting on hyperlipidaemia and atherosclerosis.

PubMed

Lee, A Yeong; Park, Won; Kang, Tae-Wook; Cha, Min Ho; Chun, Jin Mi

2018-07-15

Yijin-Tang (YJT) is a traditional prescription for the treatment of hyperlipidaemia, atherosclerosis and other ailments related to dampness phlegm, a typical pathological symptom of abnormal body fluid metabolism in Traditional Korean Medicine. However, a holistic network pharmacology approach to understanding the therapeutic mechanisms underlying hyperlipidaemia and atherosclerosis has not been pursued. To examine the network pharmacological potential effects of YJT on hyperlipidaemia and atherosclerosis, we analysed components, performed target prediction and network analysis, and investigated interacting pathways using a network pharmacology approach. Information on compounds in herbal medicines was obtained from public databases, and oral bioavailability and drug-likeness was screened using absorption, distribution, metabolism, and excretion (ADME) criteria. Correlations between compounds and genes were linked using the STITCH database, and genes related to hyperlipidaemia and atherosclerosis were gathered using the GeneCards database. Human genes were identified and subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Network analysis identified 447 compounds in five herbal medicines that were subjected to ADME screening, and 21 compounds and 57 genes formed the main pathways linked to hyperlipidaemia and atherosclerosis. Among them, 10 compounds (naringenin, nobiletin, hesperidin, galangin, glycyrrhizin, homogentisic acid, stigmasterol, 6-gingerol, quercetin and glabridin) were linked to more than four genes, and are bioactive compounds and key chemicals. Core genes in this network were CASP3, CYP1A1, CYP1A2, MMP2 and MMP9. The compound-target gene network revealed close interactions between multiple components and multiple targets, and facilitates a better understanding of the potential therapeutic effects of YJT. Pharmacological network analysis can help to explain the potential effects of YJT for treating dampness phlegm-related diseases such as hyperlipidaemia and atherosclerosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Domestic trends in malaria research and development in China and its global influence.

PubMed

Huang, Yang-Mu; Shi, Lu-Wen; She, Rui; Bai, Jing; Jiao, Shi-Yong; Guo, Yan

2017-01-10

Though many countries, including China, are moving towards malaria elimination, malaria remains a major global health threat. Due to the spread of antimalarial drug resistance and the need for innovative medical products during the elimination phase, further research and development (R&D) of innovative tools in both epidemic and elimination areas is needed. This study aims to identify the trends and gaps in malaria R&D in China, and aims to offer suggestions on how China can be more effectively involved in global malaria R&D. Quantitative analysis was carried out by collecting data on Chinese malaria-related research programmes between 1985 and 2014, invention patents in China from 1985 to 2014, and articles published by Chinese researchers in PubMed and Chinese databases from 2005 to 2014. All data were screened and extracted for numerical analysis and were categorized into basic sciences, drug/drug resistance, immunology/vaccines, or diagnostics/detection for chronological and subgroup comparisons. The number of malaria R&D activities have shown a trend of increase during the past 30 years, however these activities have fluctuated within the past few years. During the past 10 years, R&D on drug/drug resistance accounted for the highest percentages of research programmes (32.4%), articles (55.0% in PubMed and 50.6% in Chinese databases) and patents (45.5%). However, these R&D activities were mainly related to artemisinin. R&D on immunology/vaccines has been a continuous interest for China's public entities, but the focus remains on basic science. R&D in the area of high-efficiency diagnostics has been rarely seen or reported in China. China has long been devoted to malaria R&D in multiple areas, including drugs, drug resistance, immunology and vaccines. R&D on diagnostics has received significantly less attention, however, it should also be an area where China can make a contribution. More focus on malaria R&D is needed, especially in the area of diagnostics, if China would like to contribute in a more significant way to global malaria control and elimination.

Network-based drug discovery by integrating systems biology and computational technologies

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768

Patterns of use and impact of standardised MedDRA query analyses on the safety evaluation and review of new drug and biologics license applications.

PubMed

Chang, Lin-Chau; Mahmood, Riaz; Qureshi, Samina; Breder, Christopher D

2017-01-01

Standardised MedDRA Queries (SMQs) have been developed since the early 2000's and used by academia, industry, public health, and government sectors for detecting safety signals in adverse event safety databases. The purpose of the present study is to characterize how SMQs are used and the impact in safety analyses for New Drug Application (NDA) and Biologics License Application (BLA) submissions to the United States Food and Drug Administration (USFDA). We used the PharmaPendium database to capture SMQ use in Summary Basis of Approvals (SBoAs) of drugs and biologics approved by the USFDA. Characteristics of the drugs and the SMQ use were employed to evaluate the role of SMQ safety analyses in regulatory decisions and the veracity of signals they revealed. A comprehensive search of the SBoAs yielded 184 regulatory submissions approved from 2006 to 2015. Search strategies more frequently utilized restrictive searches with "narrow terms" to enhance specificity over strategies using "broad terms" to increase sensitivity, while some involved modification of search terms. A majority (59%) of 1290 searches used descriptive statistics, however inferential statistics were utilized in 35% of them. Commentary from reviewers and supervisory staff suggested that a small, yet notable percentage (18%) of 1290 searches supported regulatory decisions. The searches with regulatory impact were found in 73 submissions (40% of the submissions investigated). Most searches (75% of 227 searches) with regulatory implications described how the searches were confirmed, indicating prudence in the decision-making process. SMQs have an increasing role in the presentation and review of safety analysis for NDAs/BLAs and their regulatory reviews. This study suggests that SMQs are best used for screening process, with descriptive statistics, description of SMQ modifications, and systematic verification of cases which is crucial for drawing regulatory conclusions.

Patterns of use and impact of standardised MedDRA query analyses on the safety evaluation and review of new drug and biologics license applications

PubMed Central

Chang, Lin-Chau; Mahmood, Riaz; Qureshi, Samina

2017-01-01

Purpose Standardised MedDRA Queries (SMQs) have been developed since the early 2000’s and used by academia, industry, public health, and government sectors for detecting safety signals in adverse event safety databases. The purpose of the present study is to characterize how SMQs are used and the impact in safety analyses for New Drug Application (NDA) and Biologics License Application (BLA) submissions to the United States Food and Drug Administration (USFDA). Methods We used the PharmaPendium database to capture SMQ use in Summary Basis of Approvals (SBoAs) of drugs and biologics approved by the USFDA. Characteristics of the drugs and the SMQ use were employed to evaluate the role of SMQ safety analyses in regulatory decisions and the veracity of signals they revealed. Results A comprehensive search of the SBoAs yielded 184 regulatory submissions approved from 2006 to 2015. Search strategies more frequently utilized restrictive searches with “narrow terms” to enhance specificity over strategies using “broad terms” to increase sensitivity, while some involved modification of search terms. A majority (59%) of 1290 searches used descriptive statistics, however inferential statistics were utilized in 35% of them. Commentary from reviewers and supervisory staff suggested that a small, yet notable percentage (18%) of 1290 searches supported regulatory decisions. The searches with regulatory impact were found in 73 submissions (40% of the submissions investigated). Most searches (75% of 227 searches) with regulatory implications described how the searches were confirmed, indicating prudence in the decision-making process. Conclusions SMQs have an increasing role in the presentation and review of safety analysis for NDAs/BLAs and their regulatory reviews. This study suggests that SMQs are best used for screening process, with descriptive statistics, description of SMQ modifications, and systematic verification of cases which is crucial for drawing regulatory conclusions. PMID:28570569

High-throughput matrix screening identifies synergistic and antagonistic antimalarial drug combinations

PubMed Central

Mott, Bryan T.; Eastman, Richard T.; Guha, Rajarshi; Sherlach, Katy S.; Siriwardana, Amila; Shinn, Paul; McKnight, Crystal; Michael, Sam; Lacerda-Queiroz, Norinne; Patel, Paresma R.; Khine, Pwint; Sun, Hongmao; Kasbekar, Monica; Aghdam, Nima; Fontaine, Shaun D.; Liu, Dongbo; Mierzwa, Tim; Mathews-Griner, Lesley A.; Ferrer, Marc; Renslo, Adam R.; Inglese, James; Yuan, Jing; Roepe, Paul D.; Su, Xin-zhuan; Thomas, Craig J.

2015-01-01

Drug resistance in Plasmodium parasites is a constant threat. Novel therapeutics, especially new drug combinations, must be identified at a faster rate. In response to the urgent need for new antimalarial drug combinations we screened a large collection of approved and investigational drugs, tested 13,910 drug pairs, and identified many promising antimalarial drug combinations. The activity of known antimalarial drug regimens was confirmed and a myriad of new classes of positively interacting drug pairings were discovered. Network and clustering analyses reinforced established mechanistic relationships for known drug combinations and identified several novel mechanistic hypotheses. From eleven screens comprising >4,600 combinations per parasite strain (including duplicates) we further investigated interactions between approved antimalarials, calcium homeostasis modulators, and inhibitors of phosphatidylinositide 3-kinases (PI3K) and the mammalian target of rapamycin (mTOR). These studies highlight important targets and pathways and provide promising leads for clinically actionable antimalarial therapy. PMID:26403635

The Community College Internship Program at NREL | NREL

Science.gov Websites

lower. Drug Screening and Background Check NREL coordinates a one-time background investigation and drug the drug screening, they have 72 hours to complete the required urine test. Work Hours NREL encourages

Drugs and Drug-Like Compounds: Discriminating Approved Pharmaceuticals from Screening-Library Compounds

NASA Astrophysics Data System (ADS)

Schierz, Amanda C.; King, Ross D.

Compounds in drug screening-libraries should resemble pharmaceuticals. To operationally test this, we analysed the compounds in terms of known drug-like filters and developed a novel machine learning method to discriminate approved pharmaceuticals from “drug-like” compounds. This method uses both structural features and molecular properties for discrimination. The method has an estimated accuracy of 91% in discriminating between the Maybridge HitFinder library and approved pharmaceuticals, and 99% between the NATDiverse collection (from Analyticon Discovery) and approved pharmaceuticals. These results show that Lipinski’s Rule of 5 for oral absorption is not sufficient to describe “drug-likeness” and be the main basis of screening-library design.

A Chemogenomic Analysis of Ionization Constants - Implications for Drug Discovery

PubMed Central

Manallack, David T.; Prankerd, Richard J.; Nassta, Gemma C.; Ursu, Oleg; Oprea, Tudor I.; Chalmers, David K.

2013-01-01

Chemogenomics methods seek to characterize the interaction between drugs and biological systems and are an important guide for the selection of screening compounds. The acid/base character of drugs has a profound influence on their affinity for the receptor, on their absorption, distribution, metabolism, excretion and toxicity (ADMET) profile and the way the drug can be formulated. In particular, the charge state of a molecule greatly influences its lipophilicity and biopharmaceutical characteristics. This study investigates the acid/base profile of human small molecule drugs, chemogenomics datasets and screening compounds including a natural products set. We estimate the ionization constants (pKa values) of these compounds and determine the identity of the ionizable functional groups in each set. We find substantial differences in acid/base profiles of the chemogenomic classes. In many cases, these differences can be linked to the nature of the target binding site and the corresponding functional groups needed for recognition of the ligand. Clear differences are also observed between the acid/base characteristics of drugs and screening compounds. For example, the proportion of drugs containing a carboxylic acid was 20%, in stark contrast to a value of 2.4% for the screening set sample. The proportion of aliphatic amines was 27% for drugs and only 3.4% for screening compounds. This suggests that there is a mismatch between commercially available screening compounds and the compounds that are likely to interact with a given chemogenomic target family. Our analysis provides a guide for the selection of screening compounds to better target specific chemogenomic families with regard to the overall balance of acids, bases and pKa distributions. PMID:23303535

Retrieving Online Information on Drugs: An Analysis of Four Databases.

ERIC Educational Resources Information Center

Lavengood, Kathryn A.

This study examines the indexing of drugs in the literature and compares actual drug indexing to stated indexing policies in selected databases. The goal is to aid health science information specialists, end-users, and/or non-subject experts to improve recall and comprehensiveness when searching for drug information by identifying the most useful…

Building a structured monitoring and evaluating system of postmarketing drug use in Shanghai.

PubMed

Du, Wenmin; Levine, Mitchell; Wang, Longxing; Zhang, Yaohua; Yi, Chengdong; Wang, Hongmin; Wang, Xiaoyu; Xie, Hongjuan; Xu, Jianglong; Jin, Huilin; Wang, Tongchun; Huang, Gan; Wu, Ye

2007-01-01

In order to understand a drug's full profile in the post-marketing environment, information is needed regarding utilization patterns, beneficial effects, ADRs and economic value. China, the most populated country in the world, has the largest number of people who are taking medications. To begin to appreciate the impact of these medications, a multifunctional evaluation and surveillance system was developed, the Shanghai Drug Monitoring and Evaluative System (SDMES). Set up by the Shanghai Center for Adverse Drug Reaction Monitoring in 2001, the SDMES contains three databases: a population health data base of middle aged and elderly persons; hospital patient medical records; and a spontaneous ADR reporting database. Each person has a unique identification and Medicare number, which permits record-linkage within and between these three databases. After more than three years in development, the population health database has comprehensive data for more than 320,000 residents. The hospital database has two years of inpatient medical records from five major hospitals, and will be increasing to 10 hospitals in 2007. The spontaneous reporting ADR database has collected 20,205 cases since 2001 from approximately 295 sources, including hospitals, pharmaceutical companies, drug wholesalers and pharmacies. The SDMES has the potential to become an important national and international pharmacoepidemiology resource for drug evaluation.

Parallel shRNA and CRISPR-Cas9 screens enable antiviral drug target identification.

PubMed

Deans, Richard M; Morgens, David W; Ökesli, Ayşe; Pillay, Sirika; Horlbeck, Max A; Kampmann, Martin; Gilbert, Luke A; Li, Amy; Mateo, Roberto; Smith, Mark; Glenn, Jeffrey S; Carette, Jan E; Khosla, Chaitan; Bassik, Michael C

2016-05-01

Broad-spectrum antiviral drugs targeting host processes could potentially treat a wide range of viruses while reducing the likelihood of emergent resistance. Despite great promise as therapeutics, such drugs remain largely elusive. Here we used parallel genome-wide high-coverage short hairpin RNA (shRNA) and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 screens to identify the cellular target and mechanism of action of GSK983, a potent broad-spectrum antiviral with unexplained cytotoxicity. We found that GSK983 blocked cell proliferation and dengue virus replication by inhibiting the pyrimidine biosynthesis enzyme dihydroorotate dehydrogenase (DHODH). Guided by mechanistic insights from both genomic screens, we found that exogenous deoxycytidine markedly reduced GSK983 cytotoxicity but not antiviral activity, providing an attractive new approach to improve the therapeutic window of DHODH inhibitors against RNA viruses. Our results highlight the distinct advantages and limitations of each screening method for identifying drug targets, and demonstrate the utility of parallel knockdown and knockout screens for comprehensive probing of drug activity.

Toxicology screen

MedlinePlus

... Analgesics - screen; Antidepressants - screen; Narcotics - screen; Phenothiazines - screen; Drug abuse screen; Blood alcohol test ... poisoning) Complicated alcohol abstinence (delirium tremens) Delirium ... Fetal alcohol syndrome Intentional overdose Seizures Stroke ...

Genome-wide identification of genetic determinants for the cytotoxicity of perifosine

PubMed Central

2008-01-01

Perifosine belongs to the class of alkylphospholipid analogues, which act primarily at the cell membrane, thereby targeting signal transduction pathways. In phase I/II clinical trials, perifosine has induced tumour regression and caused disease stabilisation in a variety of tumour types. The genetic determinants responsible for its cytotoxicity have not been comprehensively studied, however. We performed a genome-wide analysis to identify genes whose expression levels or genotypic variation were correlated with the cytotoxicity of perifosine, using public databases on the US National Cancer Institute (NCI)-60 human cancer cell lines. For demonstrating drug specificity, the NCI Standard Agent Database (including 171 drugs acting through a variety of mechanisms) was used as a control. We identified agents with similar cytotoxicity profiles to that of perifosine in compounds used in the NCI drug screen. Furthermore, Gene Ontology and pathway analyses were carried out on genes more likely to be perifosine specific. The results suggested that genes correlated with perifosine cytotoxicity are connected by certain known pathways that lead to the mitogen-activated protein kinase signalling pathway and apoptosis. Biological processes such as 'response to stress', 'inflammatory response' and 'ubiquitin cycle' were enriched among these genes. Three single nucleotide polymorphisms (SNPs) located in CACNA2DI and EXOC4 were found to be correlated with perifosine cytotoxicity. Our results provided a manageable list of genes whose expression levels or genotypic variation were strongly correlated with the cytotoxcity of perifosine. These genes could be targets for further studies using candidate-gene approaches. The results also provided insights into the pharmacodynamics of perifosine. PMID:19129090

An Approach for Identification of Novel Drug Targets in Streptococcus pyogenes SF370 Through Pathway Analysis.

PubMed

Singh, Satendra; Singh, Dev Bukhsh; Singh, Anamika; Gautam, Budhayash; Ram, Gurudayal; Dwivedi, Seema; Ramteke, Pramod W

2016-12-01

Streptococcus pyogenes is one of the most important pathogens as it is involved in various infections affecting upper respiratory tract and skin. Due to the emergence of multidrug resistance and cross-resistance, S. Pyogenes is becoming more pathogenic and dangerous. In the present study, an in silico comparative analysis of total 65 metabolic pathways of the host (Homo sapiens) and the pathogen was performed. Initially, 486 paralogous enzymes were identified so that they can be removed from possible drug target list. The 105 enzymes of the biochemical pathways of S. pyogenes from the KEGG metabolic pathway database were compared with the proteins from the Homo sapiens by performing a BLASTP search against the non-redundant database restricted to the Homo sapiens subset. Out of these, 83 enzymes were identified as non-human homologous while 30 enzymes of inadequate amino acid length were removed for further processing. Essential enzymes were finally mined from remaining 53 enzymes. Finally, 28 essential enzymes were identified in S. pyogenes SF370 (serotype M1). In subcellular localization study, 18 enzymes were predicted with cytoplasmic localization and ten enzymes with the membrane localization. These ten enzymes with putative membrane localization should be of particular interest. Acyl-carrier-protein S-malonyltransferase, DNA polymerase III subunit beta and dihydropteroate synthase are novel drug targets and thus can be used to design potential inhibitors against S. pyogenes infection. 3D structure of dihydropteroate synthase was modeled and validated that can be used for virtual screening and interaction study of potential inhibitors with the target enzyme.

Collaborative Core Research Program for Chemical-Biological Warfare Defense

DTIC Science & Technology

2015-01-04

Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD...Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD) Current pharmaceutical approaches involving drug discovery...structural analysis and docking program generally known as fragment based drug design (FBDD). The main advantage of using these approaches is that

The QDREC web server: determining dose-response characteristics of complex macroparasites in phenotypic drug screens.

PubMed

Asarnow, Daniel; Rojo-Arreola, Liliana; Suzuki, Brian M; Caffrey, Conor R; Singh, Rahul

2015-05-01

Neglected tropical diseases (NTDs) caused by helminths constitute some of the most common infections of the world's poorest people. The etiological agents are complex and recalcitrant to standard techniques of molecular biology. Drug screening against helminths has often been phenotypic and typically involves manual description of drug effect and efficacy. A key challenge is to develop automated, quantitative approaches to drug screening against helminth diseases. The quantal dose-response calculator (QDREC) constitutes a significant step in this direction. It can be used to automatically determine quantitative dose-response characteristics and half-maximal effective concentration (EC50) values using image-based readouts from phenotypic screens, thereby allowing rigorous comparisons of the efficacies of drug compounds. QDREC has been developed and validated in the context of drug screening for schistosomiasis, one of the most important NTDs. However, it is equally applicable to general phenotypic screening involving helminths and other complex parasites. QDREC is publically available at: http://haddock4.sfsu.edu/qdrec2/. Source code and datasets are at: http://tintin.sfsu.edu/projects/phenotypicAssays.html. rahul@sfsu.edu. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

In silico identification of anthropogenic chemicals as ligands of zebrafish sex hormone binding globulin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorsteinson, Nels; Ban, Fuqiang; Santos-Filho, Osvaldo

2009-01-01

Anthropogenic compounds with the capacity to interact with the steroid-binding site of sex hormone binding globulin (SHBG) pose health risks to humans and other vertebrates including fish. Building on studies of human SHBG, we have applied in silico drug discovery methods to identify potential binders for SHBG in zebrafish (Danio rerio) as a model aquatic organism. Computational methods, including; homology modeling, molecular dynamics simulations, virtual screening, and 3D QSAR analysis, successfully identified 6 non-steroidal substances from the ZINC chemical database that bind to zebrafish SHBG (zfSHBG) with low-micromolar to nanomolar affinities, as determined by a competitive ligand-binding assay. We alsomore » screened 80,000 commercial substances listed by the European Chemicals Bureau and Environment Canada, and 6 non-steroidal hits from this in silico screen were tested experimentally for zfSHBG binding. All 6 of these compounds displaced the [{sup 3}H]5{alpha}-dihydrotestosterone used as labeled ligand in the zfSHBG screening assay when tested at a 33 {mu}M concentration, and 3 of them (hexestrol, 4-tert-octylcatechol, and dihydrobenzo(a)pyren-7(8H)-one) bind to zfSHBG in the micromolar range. The study demonstrates the feasibility of large-scale in silico screening of anthropogenic compounds that may disrupt or highjack functionally important protein:ligand interactions. Such studies could increase the awareness of hazards posed by existing commercial chemicals at relatively low cost.« less

Record linkage for pharmacoepidemiological studies in cancer patients.

PubMed

Herk-Sukel, Myrthe P P van; Lemmens, Valery E P P; Poll-Franse, Lonneke V van de; Herings, Ron M C; Coebergh, Jan Willem W

2012-01-01

An increasing need has developed for the post-approval surveillance of (new) anti-cancer drugs by means of pharmacoepidemiology and outcomes research in the area of oncology. To create an overview that makes researchers aware of the available database linkages in Northern America and Europe which facilitate pharmacoepidemiology and outcomes research in cancer patients. In addition to our own database, i.e. the Eindhoven Cancer Registry (ECR) linked to the PHARMO Record Linkage System, we considered database linkages between a population-based cancer registry and an administrative healthcare database that at least contains information on drug use and offers a longitudinal perspective on healthcare utilization. Eligible database linkages were limited to those that had been used in multiple published articles in English language included in Pubmed. The HMO Cancer Research Network (CRN) in the US was excluded from this review, as an overview of the linked databases participating in the CRN is already provided elsewhere. Researchers who had worked with the data resources included in our review were contacted for additional information and verification of the data presented in the overview. The following database linkages were included: the Surveillance, Epidemiology, and End-Results-Medicare; cancer registry data linked to Medicaid; Canadian cancer registries linked to population-based drug databases; the Scottish cancer registry linked to the Tayside drug dispensing data; linked databases in the Nordic Countries of Europe: Norway, Sweden, Finland and Denmark; and the ECR-PHARMO linkage in the Netherlands. Descriptives of the included database linkages comprise population size, generalizability of the population, year of first data availability, contents of the cancer registry, contents of the administrative healthcare database, the possibility to select a cancer-free control cohort, and linkage to other healthcare databases. The linked databases offer a longitudinal perspective, allowing for observations of health care utilization before, during, and after cancer diagnosis. They create new powerful data resources for the monitoring of post-approval drug utilization, as well as a framework to explore the (cost-)effectiveness of new, often expensive, anti-cancer drugs as used in everyday practice. Copyright © 2011 John Wiley & Sons, Ltd.

MPD3: a useful medicinal plants database for drug designing.

PubMed

Mumtaz, Arooj; Ashfaq, Usman Ali; Ul Qamar, Muhammad Tahir; Anwar, Farooq; Gulzar, Faisal; Ali, Muhammad Amjad; Saari, Nazamid; Pervez, Muhammad Tariq

2017-06-01

Medicinal plants are the main natural pools for the discovery and development of new drugs. In the modern era of computer-aided drug designing (CADD), there is need of prompt efforts to design and construct useful database management system that allows proper data storage, retrieval and management with user-friendly interface. An inclusive database having information about classification, activity and ready-to-dock library of medicinal plant's phytochemicals is therefore required to assist the researchers in the field of CADD. The present work was designed to merge activities of phytochemicals from medicinal plants, their targets and literature references into a single comprehensive database named as Medicinal Plants Database for Drug Designing (MPD3). The newly designed online and downloadable MPD3 contains information about more than 5000 phytochemicals from around 1000 medicinal plants with 80 different activities, more than 900 literature references and 200 plus targets. The designed database is deemed to be very useful for the researchers who are engaged in medicinal plants research, CADD and drug discovery/development with ease of operation and increased efficiency. The designed MPD3 is a comprehensive database which provides most of the information related to the medicinal plants at a single platform. MPD3 is freely available at: http://bioinform.info .

Strategy for Identifying Repurposed Drugs for the Treatment of Cerebral Cavernous Malformation

PubMed Central

Gibson, Christopher C.; Zhu, Weiquan; Davis, Chadwick T.; Bowman-Kirigin, Jay A.; Chan, Aubrey C.; Ling, Jing; Walker, Ashley E.; Goitre, Luca; Monache, Simona Delle; Retta, Saverio Francesco; Shiu, Yan-Ting E.; Grossmann, Allie H.; Thomas, Kirk R.; Donato, Anthony J.; Lesniewski, Lisa A.; Whitehead, Kevin J.; Li, Dean Y.

2014-01-01

Background Cerebral cavernous malformation (CCM) is a hemorrhagic stroke disease affecting up to 0.5% of North Americans with no approved non-surgical treatment. A subset of patients have a hereditary form of the disease due primarily to loss-of-function mutations in KRIT1, CCM2, or PDCD10. We sought to identify known drugs that could be repurposed to treat CCM. Methods and Results We developed an unbiased screening platform based on both cellular and animal models of loss-of-function of CCM2. Our discovery strategy consisted of four steps: an automated immunofluorescence and machine-learning-based primary screen of structural phenotypes in human endothelial cells deficient in CCM2; a secondary screen of functional changes in endothelial stability in these same cells; a rapid in vivo tertiary screen of dermal microvascular leak in mice lacking endothelial Ccm2; and finally a quaternary screen of CCM lesion burden in these same mice. We screened 2,100 known drugs and bioactive compounds, and identified two candidates for further study, cholecalciferol (Vitamin D3) and tempol (a scavenger of superoxide). Each drug decreased lesion burden in a mouse model of CCM vascular disease by approximately 50%. Conclusions By identifying known drugs as potential therapeutics for CCM, we have decreased the time, cost, and risk of bringing treatments to patients. Each drug also prompts additional exploration of biomarkers of CCM disease. We further suggest that the structure-function screening platform presented here may be adapted and scaled to facilitate drug discovery for diverse loss-of-function genetic vascular disease. PMID:25486933

Substance use in remand prisoners: a consecutive case study.

PubMed Central

Mason, D.; Birmingham, L.; Grubin, D.

1997-01-01

OBJECTIVES: To determine the prevalence of drug and alcohol use among newly remanded prisoners, assess the effectiveness of prison reception screening, and examine the clinical management of substance misusers among remand prisoners. DESIGN: A consecutive case study of remand prisoners screened at reception for substance misuse and treatment needs and comparison of findings with those of prison reception screening and treatment provision. SETTING: A large adult male remand prison (Durham). SUBJECTS: 548 men aged 21 and over awaiting trial. MAIN OUTCOME MEASURES: Prevalence of substance misuse; treatment needs of substance misusers; effectiveness of prison reception screening for substance misuse; provision of detoxification programmes. RESULTS: Before remand 312 (57%) men were using illicit drugs and 181 (33%) met DSM-IV drug misuse or dependence criteria; 177 (32%) men met misuse or dependence criteria for alcohol. 391 (71%) men were judged to require help directed at their drug or alcohol use and 197 (36%) were judged to require a detoxification programme. The prison reception screen identified recent illicit drug use in 131 (24%) of 536 men and problem drinking in 103 (19%). Drug use was more likely to be identified by prison screening if an inmate was using multiple substances, using opiates, or had a diagnosis of abuse or dependence. 47 (9%) of 536 inmates were prescribed treatment to ease the symptoms of substance withdrawal. CONCLUSIONS: The prevalence of substance misuse in newly remanded prisoners is high. Prison reception health screening consistently underestimated drug and alcohol use. In many cases in which substance use is identified the quantities and numbers of different substances being used are underestimated. Initial management of inmates identified by prison screening as having problems with dependence producing substances is poor. Few receive a detoxification programme, so that many are left with the option of continuing to use drugs in prison or facing untreated withdrawal. PMID:9233320

MouseNet database: digital management of a large-scale mutagenesis project.

PubMed

Pargent, W; Heffner, S; Schäble, K F; Soewarto, D; Fuchs, H; Hrabé de Angelis, M

2000-07-01

The Munich ENU Mouse Mutagenesis Screen is a large-scale mutant production, phenotyping, and mapping project. It encompasses two animal breeding facilities and a number of screening groups located in the general area of Munich. A central database is required to manage and process the immense amount of data generated by the mutagenesis project. This database, which we named MouseNet(c), runs on a Sybase platform and will finally store and process all data from the entire project. In addition, the system comprises a portfolio of functions needed to support the workflow management of the core facility and the screening groups. MouseNet(c) will make all of the data available to the participating screening groups, and later to the international scientific community. MouseNet(c) will consist of three major software components:* Animal Management System (AMS)* Sample Tracking System (STS)* Result Documentation System (RDS)MouseNet(c) provides the following major advantages:* being accessible from different client platforms via the Internet* being a full-featured multi-user system (including access restriction and data locking mechanisms)* relying on a professional RDBMS (relational database management system) which runs on a UNIX server platform* supplying workflow functions and a variety of plausibility checks.

Drug target identification in protozoan parasites

PubMed Central

Müller, Joachim; Hemphill, Andrew

2016-01-01

Introduction Despite the fact that diseases caused by protozoan parasites represent serious challenges for public health, animal production and welfare, only a limited panel of drugs has been marketed for clinical applications. Areas covered Herein, the authors investigate two strategies, namely whole organism screening and target-based drug design. The present pharmacopoeia has resulted from whole organism screening, and the mode of action and targets of selected drugs are discussed. However, the more recent extensive genome sequencing efforts and the development of dry and wet lab genomics and proteomics that allow high-throughput screening of interactions between micromolecules and recombinant proteins has resulted in target-based drug design as the predominant focus in anti-parasitic drug development. Selected examples of target-based drug design studies are presented, and calcium-dependent protein kinases, important drug targets in apicomplexan parasites, are discussed in more detail. Expert opinion Despite the enormous efforts in target-based drug development, this approach has not yet generated market-ready antiprotozoal drugs. However, whole-organism screening approaches, comprising of both in vitro and in vivo investigations, should not be disregarded. The repurposing of already approved and marketed drugs could be a suitable strategy to avoid fastidious approval procedures, especially in the case of neglected or veterinary parasitoses. PMID:27238605

A Novel Approach for Efficient Pharmacophore-based Virtual Screening: Method and Applications

PubMed Central

Dror, Oranit; Schneidman-Duhovny, Dina; Inbar, Yuval; Nussinov, Ruth; Wolfson, Haim J.

2009-01-01

Virtual screening is emerging as a productive and cost-effective technology in rational drug design for the identification of novel lead compounds. An important model for virtual screening is the pharmacophore. Pharmacophore is the spatial configuration of essential features that enable a ligand molecule to interact with a specific target receptor. In the absence of a known receptor structure, a pharmacophore can be identified from a set of ligands that have been observed to interact with the target receptor. Here, we present a novel computational method for pharmacophore detection and virtual screening. The pharmacophore detection module is able to: (i) align multiple flexible ligands in a deterministic manner without exhaustive enumeration of the conformational space, (ii) detect subsets of input ligands that may bind to different binding sites or have different binding modes, (iii) address cases where the input ligands have different affinities by defining weighted pharmacophores based on the number of ligands that share them, and (iv) automatically select the most appropriate pharmacophore candidates for virtual screening. The algorithm is highly efficient, allowing a fast exploration of the chemical space by virtual screening of huge compound databases. The performance of PharmaGist was successfully evaluated on a commonly used dataset of G-Protein Coupled Receptor alpha1A. Additionally, a large-scale evaluation using the DUD (directory of useful decoys) dataset was performed. DUD contains 2950 active ligands for 40 different receptors, with 36 decoy compounds for each active ligand. PharmaGist enrichment rates are comparable with other state-of-the-art tools for virtual screening. Availability The software is available for download. A user-friendly web interface for pharmacophore detection is available at http://bioinfo3d.cs.tau.ac.il/PharmaGist. PMID:19803502

Computation-based virtual screening for designing novel antimalarial drugs by targeting falcipain-III: a structure-based drug designing approach.

PubMed

Kesharwani, Rajesh Kumar; Singh, Durg Vijay; Misra, Krishna

2013-01-01

Cysteine proteases (falcipains), a papain-family of enzymes of Plasmodium falciparum, are responsible for haemoglobin degradation and thus necessary for its survival during asexual life cycle phase inside the human red blood cells while remaining non-functional for the human body. Therefore, these can act as potential targets for designing antimalarial drugs. The P. falciparum cysteine proteases, falcipain-II and falcipain- III are the enzymes which initiate the haemoglobin degradation, therefore, have been selected as targets. In the present study, we have designed new leupeptin analogues and subjected to virtual screening using Glide at the active site cavity of falcipain-II and falcipain-III to select the best docked analogues on the basis of Glide score and also compare with the result of AutoDock. The proposed analogues can be synthesized and tested in vivo as future potent antimalarial drugs. Protein falcipain-II and falcipain-III together with bounds inhibitors epoxysuccinate E64 (E64) and leupeptin respectively were retrieved from protein data bank (PDB) and latter leupeptin was used as lead molecule to design new analogues by using Ligbuilder software and refined the molecules on the basis of Lipinski rule of five and fitness score parameters. All the designed leupeptin analogues were screened via docking simulation at the active site cavity of falcipain-II and falcipain-III by using Glide software and AutoDock. The 104 new leupeptin-based antimalarial ligands were designed using structure-based drug designing approach with the help of Ligbuilder and subjected for virtual screening via docking simulation method against falcipain-II and falcipain-III receptor proteins. The Glide docking results suggest that the ligands namely result_037 shows good binding and other two, result_044 and result_042 show nearly similar binding than naturally occurring PDB bound ligand E64 against falcipain-II and in case of falcipain-III, 15 designed leupeptin analogues having better binding affinity compared to the PDB bound inhibitor of falcipain-III. The docking simulation results of falcipain-III with designed leupeptin analogues using Glide compared with AutoDock and find 80% similarity as better binder than leupeptin. These results further highlight new leupeptin analogues as promising future inhibitors for chemotherapeutic prevention of malaria. The result of Glide for falcipain-III has been compared with the result of AutoDock and finds very less differences in their order of binding affinity. Although there are no extra hydrogen bonds, however, equal number of hydrogen bonds with variable strength as compared to leupeptin along with the enhanced hydrophobic and electrostatic interactions in case of analogues supports our study that it holds the ligand molecules strongly within the receptor. The comparative e-pharmacophoric study also suggests and supports our predictions regarding the minimum features required in ligand molecule to behave as falcipain- III inhibitors and is also helpful in screening the large database as future antimalarial inhibitors.

Online drug databases: a new method to assess and compare inclusion of clinically relevant information.

PubMed

Silva, Cristina; Fresco, Paula; Monteiro, Joaquim; Rama, Ana Cristina Ribeiro

2013-08-01

Evidence-Based Practice requires health care decisions to be based on the best available evidence. The model "Information Mastery" proposes that clinicians should use sources of information that have previously evaluated relevance and validity, provided at the point of care. Drug databases (DB) allow easy and fast access to information and have the benefit of more frequent content updates. Relevant information, in the context of drug therapy, is that which supports safe and effective use of medicines. Accordingly, the European Guideline on the Summary of Product Characteristics (EG-SmPC) was used as a standard to evaluate the inclusion of relevant information contents in DB. To develop and test a method to evaluate relevancy of DB contents, by assessing the inclusion of information items deemed relevant for effective and safe drug use. Hierarchical organisation and selection of the principles defined in the EGSmPC; definition of criteria to assess inclusion of selected information items; creation of a categorisation and quantification system that allows score calculation; calculation of relative differences (RD) of scores for comparison with an "ideal" database, defined as the one that achieves the best quantification possible for each of the information items; pilot test on a sample of 9 drug databases, using 10 drugs frequently associated in literature with morbidity-mortality and also being widely consumed in Portugal. Main outcome measure Calculate individual and global scores for clinically relevant information items of drug monographs in databases, using the categorisation and quantification system created. A--Method development: selection of sections, subsections, relevant information items and corresponding requisites; system to categorise and quantify their inclusion; score and RD calculation procedure. B--Pilot test: calculated scores for the 9 databases; globally, all databases evaluated significantly differed from the "ideal" database; some DB performed better but performance was inconsistent at subsections level, within the same DB. The method developed allows quantification of the inclusion of relevant information items in DB and comparison with an "ideal database". It is necessary to consult diverse DB in order to find all the relevant information needed to support clinical drug use.

Personalized drug discovery: HCA approach optimized for rare diseases at Tel Aviv University.

PubMed

Solmesky, Leonardo J; Weil, Miguel

2014-03-01

The Cell screening facility for personalized medicine (CSFPM) at Tel Aviv University in Israel is devoted to screening small molecules libraries for finding new drugs for rare diseases using human cell based models. The main strategy of the facility is based on smartly reducing the size of the compounds collection in similarity clusters and at the same time keeping high diversity of pharmacophores. This strategy allows parallel screening of several patient derived - cells in a personalized screening approach. The tested compounds are repositioned drugs derived from collections of phase III and FDA approved small molecules. In addition, the facility carries screenings using other chemical libraries and toxicological characterizations of nanomaterials.

A trial with IgY chicken antibodies to eradicate faecal carriage of Klebsiella pneumoniae and Escherichia coli producing extended-spectrum beta-lactamases

PubMed Central

Jonsson, Anna-Karin; Larsson, Anders; Tängdén, Thomas; Melhus, Åsa; Lannergård, Anders

2015-01-01

Background Extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae is an emerging therapeutic challenge, especially in the treatment of urinary tract infections. Following an outbreak of CTX-M-15 Klebsiella pneumoniae in Uppsala, Sweden, an orphan drug trial on IgY chicken antibodies was undertaken in an attempt to eradicate faecal carriage of ESBL-producing K. pneumoniae and Escherichia coli. Methods Hens were immunised with epitopes from freeze-dried, whole-cell bacteria (ESBL-producing K. pneumoniae and E. coli) and recombinant proteins of two K. pneumoniae fimbriae subunits (fimH and mrkD). The egg yolks were processed according to good manufacturing practice and the product was stored at−20°C until used. Using an internal database from the outbreak and the regular laboratory database, faecal carriers were identified and recruited from May 2005 to December 2013. The participants were randomised in a placebo-controlled 1:1 manner. Results From 749 eligible patients, 327 (44%) had deceased, and only 91 (12%) were recruited and signed the informed consent. In the initial screening performed using the polymerase chain reaction, 24 participants were ESBL positive and subsequently randomised and treated with either the study drug or a placebo. The study was powered for 124 participants. Because of a very high dropout rate, the study was prematurely terminated. From the outbreak cohort (n=247), only eight patients were screened, and only one was positive with the outbreak strain in faeces. Conclusions The present study design, using IgY chicken antibodies for the eradication of ESBL-producing K. pneumonia and E. coli, was ineffective in reaching its goal due to high mortality and other factors resulting in a low inclusion rate. Spontaneous eradication of ESBL-producing bacteria was frequently observed in recruited participants, which is consistent with previous reports. PMID:26560861

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

PubMed

Joslin, John; Gilligan, James; Anderson, Paul; Garcia, Catherine; Sharif, Orzala; Hampton, Janice; Cohen, Steven; King, Miranda; Zhou, Bin; Jiang, Shumei; Trussell, Christopher; Dunn, Robert; Fathman, John W; Snead, Jennifer L; Boitano, Anthony E; Nguyen, Tommy; Conner, Michael; Cooke, Mike; Harris, Jennifer; Ainscow, Ed; Zhou, Yingyao; Shaw, Chris; Sipes, Dan; Mainquist, James; Lesley, Scott

2018-05-01

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Drug screening of cancer cell lines and human primary tumors using droplet microfluidics.

PubMed

Wong, Ada Hang-Heng; Li, Haoran; Jia, Yanwei; Mak, Pui-In; Martins, Rui Paulo da Silva; Liu, Yan; Vong, Chi Man; Wong, Hang Cheong; Wong, Pak Kin; Wang, Haitao; Sun, Heng; Deng, Chu-Xia

2017-08-22

Precision Medicine in Oncology requires tailoring of therapeutic strategies to individual cancer patients. Due to the limited quantity of tumor samples, this proves to be difficult, especially for early stage cancer patients whose tumors are small. In this study, we exploited a 2.4 × 2.4 centimeters polydimethylsiloxane (PDMS) based microfluidic chip which employed droplet microfluidics to conduct drug screens against suspended and adherent cancer cell lines, as well as cells dissociated from primary tumor of human patients. Single cells were dispersed in aqueous droplets and imaged within 24 hours of drug treatment to assess cell viability by ethidium homodimer 1 staining. Our results showed that 5 conditions could be screened for every 80,000 cells in one channel on our chip under current circumstances. Additionally, screening conditions have been adapted to both suspended and adherent cancer cells, giving versatility to potentially all types of cancers. Hence, this study provides a powerful tool for rapid, low-input drug screening of primary cancers within 24 hours after tumor resection from cancer patients. This paves the way for further technological advancement to cutting down sample size and increasing drug screening throughput in advent to personalized cancer therapy.

Network-assisted target identification for haploinsufficiency and homozygous profiling screens

PubMed Central

Wang, Sheng

2017-01-01

Chemical genomic screens have recently emerged as a systematic approach to drug discovery on a genome-wide scale. Drug target identification and elucidation of the mechanism of action (MoA) of hits from these noisy high-throughput screens remain difficult. Here, we present GIT (Genetic Interaction Network-Assisted Target Identification), a network analysis method for drug target identification in haploinsufficiency profiling (HIP) and homozygous profiling (HOP) screens. With the drug-induced phenotypic fitness defect of the deletion of a gene, GIT also incorporates the fitness defects of the gene’s neighbors in the genetic interaction network. On three genome-scale yeast chemical genomic screens, GIT substantially outperforms previous scoring methods on target identification on HIP and HOP assays, respectively. Finally, we showed that by combining HIP and HOP assays, GIT further boosts target identification and reveals potential drug’s mechanism of action. PMID:28574983

A review of human pluripotent stem cell-derived cardiomyocytes for high-throughput drug discovery, cardiotoxicity screening, and publication standards.

PubMed

Mordwinkin, Nicholas M; Burridge, Paul W; Wu, Joseph C

2013-02-01

Drug attrition rates have increased in past years, resulting in growing costs for the pharmaceutical industry and consumers. The reasons for this include the lack of in vitro models that correlate with clinical results and poor preclinical toxicity screening assays. The in vitro production of human cardiac progenitor cells and cardiomyocytes from human pluripotent stem cells provides an amenable source of cells for applications in drug discovery, disease modeling, regenerative medicine, and cardiotoxicity screening. In addition, the ability to derive human-induced pluripotent stem cells from somatic tissues, combined with current high-throughput screening and pharmacogenomics, may help realize the use of these cells to fulfill the potential of personalized medicine. In this review, we discuss the use of pluripotent stem cell-derived cardiomyocytes for drug discovery and cardiotoxicity screening, as well as current hurdles that must be overcome for wider clinical applications of this promising approach.

DrugBank 5.0: a major update to the DrugBank database for 2018.

PubMed

Wishart, David S; Feunang, Yannick D; Guo, An C; Lo, Elvis J; Marcu, Ana; Grant, Jason R; Sajed, Tanvir; Johnson, Daniel; Li, Carin; Sayeeda, Zinat; Assempour, Nazanin; Iynkkaran, Ithayavani; Liu, Yifeng; Maciejewski, Adam; Gale, Nicola; Wilson, Alex; Chin, Lucy; Cummings, Ryan; Le, Diana; Pon, Allison; Knox, Craig; Wilson, Michael

2018-01-04

DrugBank (www.drugbank.ca) is a web-enabled database containing comprehensive molecular information about drugs, their mechanisms, their interactions and their targets. First described in 2006, DrugBank has continued to evolve over the past 12 years in response to marked improvements to web standards and changing needs for drug research and development. This year's update, DrugBank 5.0, represents the most significant upgrade to the database in more than 10 years. In many cases, existing data content has grown by 100% or more over the last update. For instance, the total number of investigational drugs in the database has grown by almost 300%, the number of drug-drug interactions has grown by nearly 600% and the number of SNP-associated drug effects has grown more than 3000%. Significant improvements have been made to the quantity, quality and consistency of drug indications, drug binding data as well as drug-drug and drug-food interactions. A great deal of brand new data have also been added to DrugBank 5.0. This includes information on the influence of hundreds of drugs on metabolite levels (pharmacometabolomics), gene expression levels (pharmacotranscriptomics) and protein expression levels (pharmacoprotoemics). New data have also been added on the status of hundreds of new drug clinical trials and existing drug repurposing trials. Many other important improvements in the content, interface and performance of the DrugBank website have been made and these should greatly enhance its ease of use, utility and potential applications in many areas of pharmacological research, pharmaceutical science and drug education. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The identification of goat peroxiredoxin-5 and the evaluation and enhancement of its stability by nanoparticle formation

PubMed Central

Feng, Xiaozhou; Liu, Juanjuan; Fan, Shuai; Liu, Fan; Li, Yadong; Jin, Yuanyuan; Bai, Liping; Yang, Zhaoyong

2016-01-01

An anticancer bioactive peptide (ACBP), goat peroxiredoxin-5 (gPRDX5), was identified from goat-spleen extract after immunizing the goat with gastric cancer-cell lysate. Its amino acid sequence was determined by employing 2D nano-LC-ESI-LTQ-Orbitrap MS/MS combined with Mascot database search in the goat subset of the Uniprot database. The recombinant gPRDX5 protein was acquired by heterogeneous expression in Escherichia coli. Subsequently, the anti-cancer bioactivity of the peptide was measured by several kinds of tumor cells. The results indicated that the gPRDX5 was a good anti-cancer candidate, especially for killing B16 cells. However, the peptide was found to be unstable without modification with pharmaceutical excipients, which would be a hurdle for future medicinal application. In order to overcome this problem and find an effective way to evaluate the gPRDX5, nanoparticle formation, which has been widely used in drug delivery because of its steadiness in application, less side-effects and enhancement of drug accumulation in target issues, was used here to address the issues. In this work, the gPRDX5 was dispersed into nanoparticles before delivered to B16 cells. By the nanotechnological method, the gPRDX5 was stabilized by a fast and accurate procedure, which suggests a promising way for screening the peptide for further possible medicinal applications. PMID:27074889

The identification of goat peroxiredoxin-5 and the evaluation and enhancement of its stability by nanoparticle formation.

PubMed

Feng, Xiaozhou; Liu, Juanjuan; Fan, Shuai; Liu, Fan; Li, Yadong; Jin, Yuanyuan; Bai, Liping; Yang, Zhaoyong

2016-04-14

An anticancer bioactive peptide (ACBP), goat peroxiredoxin-5 (gPRDX5), was identified from goat-spleen extract after immunizing the goat with gastric cancer-cell lysate. Its amino acid sequence was determined by employing 2D nano-LC-ESI-LTQ-Orbitrap MS/MS combined with Mascot database search in the goat subset of the Uniprot database. The recombinant gPRDX5 protein was acquired by heterogeneous expression in Escherichia coli. Subsequently, the anti-cancer bioactivity of the peptide was measured by several kinds of tumor cells. The results indicated that the gPRDX5 was a good anti-cancer candidate, especially for killing B16 cells. However, the peptide was found to be unstable without modification with pharmaceutical excipients, which would be a hurdle for future medicinal application. In order to overcome this problem and find an effective way to evaluate the gPRDX5, nanoparticle formation, which has been widely used in drug delivery because of its steadiness in application, less side-effects and enhancement of drug accumulation in target issues, was used here to address the issues. In this work, the gPRDX5 was dispersed into nanoparticles before delivered to B16 cells. By the nanotechnological method, the gPRDX5 was stabilized by a fast and accurate procedure, which suggests a promising way for screening the peptide for further possible medicinal applications.

The identification of goat peroxiredoxin-5 and the evaluation and enhancement of its stability by nanoparticle formation

NASA Astrophysics Data System (ADS)

Feng, Xiaozhou; Liu, Juanjuan; Fan, Shuai; Liu, Fan; Li, Yadong; Jin, Yuanyuan; Bai, Liping; Yang, Zhaoyong

2016-04-01

An anticancer bioactive peptide (ACBP), goat peroxiredoxin-5 (gPRDX5), was identified from goat-spleen extract after immunizing the goat with gastric cancer-cell lysate. Its amino acid sequence was determined by employing 2D nano-LC-ESI-LTQ-Orbitrap MS/MS combined with Mascot database search in the goat subset of the Uniprot database. The recombinant gPRDX5 protein was acquired by heterogeneous expression in Escherichia coli. Subsequently, the anti-cancer bioactivity of the peptide was measured by several kinds of tumor cells. The results indicated that the gPRDX5 was a good anti-cancer candidate, especially for killing B16 cells. However, the peptide was found to be unstable without modification with pharmaceutical excipients, which would be a hurdle for future medicinal application. In order to overcome this problem and find an effective way to evaluate the gPRDX5, nanoparticle formation, which has been widely used in drug delivery because of its steadiness in application, less side-effects and enhancement of drug accumulation in target issues, was used here to address the issues. In this work, the gPRDX5 was dispersed into nanoparticles before delivered to B16 cells. By the nanotechnological method, the gPRDX5 was stabilized by a fast and accurate procedure, which suggests a promising way for screening the peptide for further possible medicinal applications.

Molecular diversity management strategies for building and enhancement of diverse and focused lead discovery compound screening collections.

PubMed

Schuffenhauer, A; Popov, M; Schopfer, U; Acklin, P; Stanek, J; Jacoby, E

2004-12-01

This publication describes processes for the selection of chemical compounds for the building of a high-throughput screening (HTS) collection for drug discovery, using the currently implemented process in the Discovery Technologies Unit of the Novartis Institute for Biomedical Research, Basel Switzerland as reference. More generally, the currently existing compound acquisition models and practices are discussed. Our informatics, chemistry and biology-driven compound selection consists of two steps: 1) The individual compounds are filtered and grouped into three priority classes on the basis of their individual structural properties. Substructure filters are used to eliminate or penalize compounds based on unwanted structural properties. The similarity of the structures to reference ligands of the main proven druggable target families is computed, and drug-similar compounds are prioritized for the following diversity analysis. 2) The compounds are compared to the archive compounds and a diversity analysis is performed. This is done separately for the prioritized, regular and penalized compounds with increasingly stringent dissimilarity criterion. The process includes collecting vendor catalogues and monitoring the availability of samples together with the selection and purchase decision points. The development of a corporate vendor catalogue database is described. In addition to the selection methods on a per single molecule basis, selection criteria for scaffold and combinatorial chemistry projects in collaboration with compound vendors are discussed.

Stem cells: a model for screening, discovery and development of drugs.

PubMed

Kitambi, Satish Srinivas; Chandrasekar, Gayathri

2011-01-01

The identification of normal and cancerous stem cells and the recent advances made in isolation and culture of stem cells have rapidly gained attention in the field of drug discovery and regenerative medicine. The prospect of performing screens aimed at proliferation, directed differentiation, and toxicity and efficacy studies using stem cells offers a reliable platform for the drug discovery process. Advances made in the generation of induced pluripotent stem cells from normal or diseased tissue serves as a platform to perform drug screens aimed at developing cell-based therapies against conditions like Parkinson's disease and diabetes. This review discusses the application of stem cells and cancer stem cells in drug screening and their role in complementing, reducing, and replacing animal testing. In addition to this, target identification and major advances in the field of personalized medicine using induced pluripotent cells are also discussed.

Cell and small animal models for phenotypic drug discovery.

PubMed

Szabo, Mihaly; Svensson Akusjärvi, Sara; Saxena, Ankur; Liu, Jianping; Chandrasekar, Gayathri; Kitambi, Satish S

2017-01-01

The phenotype-based drug discovery (PDD) approach is re-emerging as an alternative platform for drug discovery. This review provides an overview of the various model systems and technical advances in imaging and image analyses that strengthen the PDD platform. In PDD screens, compounds of therapeutic value are identified based on the phenotypic perturbations produced irrespective of target(s) or mechanism of action. In this article, examples of phenotypic changes that can be detected and quantified with relative ease in a cell-based setup are discussed. In addition, a higher order of PDD screening setup using small animal models is also explored. As PDD screens integrate physiology and multiple signaling mechanisms during the screening process, the identified hits have higher biomedical applicability. Taken together, this review highlights the advantages gained by adopting a PDD approach in drug discovery. Such a PDD platform can complement target-based systems that are currently in practice to accelerate drug discovery.

Web-Based Alcohol, Smoking, and Substance Involvement Screening Test Results for the General Spanish Population: Cross-Sectional Study

PubMed Central

2018-01-01

Background Information technology in health sciences could be a screening tool of great potential and has been shown to be effective in identifying single-drug users at risk. Although there are many published tests for single-drug screening, there is a gap for concomitant drug use screening in general population. The ASSIST (Alcohol, Smoking and Substance Involvement Screening Test) website was launched on February 2015 in Madrid, Spain, as a tool to identify those at risk. Objective The aim of this study was to describe the use of a tool and to analyze profiles of drug users, their consumption patterns, and associated factors. Methods Government- and press-released launching of a Spanish-validated ASSIST test from the World Health Organization (WHO) was used for voluntary Web-based screening of people with drug-related problems. The tests completed in the first 6 months were analyzed . Results A total of 1657 visitors of the 15,867 visits (1657/15,867, 10.44%) completed the whole Web-based screening over a 6-month period. The users had an average age of 37.4 years, and 78.87% (1307/1657) screened positive for at least one of the 9 drugs tested. The drugs with higher prevalence were tobacco (840/1657, 50.69%), alcohol (437/1657, 26.37%), cannabis (361/1657, 21.79%), and sedatives or hypnotics (192/1657, 11.59%). Polyconsumption or concomitant drug use was stated by 31.80% (527/1657) of the users. Male respondents had a higher risk of having alcohol problems (odds ratio, OR 1.55, 95% CI 1.18-2.04; P=.002) and double the risk for cannabis problems (OR 2.07, 95% CI 1.46-2.92; P<.001). Growing age increased by 3 times the risk of developing alcohol problems for people aged between 45 and 65 years (OR 3.01, 95% CI 1.89-4.79; P<.001). Conclusions A Web-based screening test could be useful to detect people at risk. The drug-related problem rates detected by the study are consistent with the current literature. This tool could be useful for users, who use information technology on a daily basis, not seeking medical attention. PMID:29453188

Coupling computer-interpretable guidelines with a drug-database through a web-based system – The PRESGUID project

PubMed Central

Dufour, Jean-Charles; Fieschi, Dominique; Fieschi, Marius

2004-01-01

Background Clinical Practice Guidelines (CPGs) available today are not extensively used due to lack of proper integration into clinical settings, knowledge-related information resources, and lack of decision support at the point of care in a particular clinical context. Objective The PRESGUID project (PREScription and GUIDelines) aims to improve the assistance provided by guidelines. The project proposes an online service enabling physicians to consult computerized CPGs linked to drug databases for easier integration into the healthcare process. Methods Computable CPGs are structured as decision trees and coded in XML format. Recommendations related to drug classes are tagged with ATC codes. We use a mapping module to enhance computerized guidelines coupling with a drug database, which contains detailed information about each usable specific medication. In this way, therapeutic recommendations are backed up with current and up-to-date information from the database. Results Two authoritative CPGs, originally diffused as static textual documents, have been implemented to validate the computerization process and to illustrate the usefulness of the resulting automated CPGs and their coupling with a drug database. We discuss the advantages of this approach for practitioners and the implications for both guideline developers and drug database providers. Other CPGs will be implemented and evaluated in real conditions by clinicians working in different health institutions. PMID:15053828

The role of targeted chemical proteomics in pharmacology

PubMed Central

Sutton, Chris W

2012-01-01

Traditionally, proteomics is the high-throughput characterization of the global complement of proteins in a biological system using cutting-edge technologies (robotics and mass spectrometry) and bioinformatics tools (Internet-based search engines and databases). As the field of proteomics has matured, a diverse range of strategies have evolved to answer specific problems. Chemical proteomics is one such direction that provides the means to enrich and detect less abundant proteins (the ‘hidden’ proteome) from complex mixtures of wide dynamic range (the ‘deep’ proteome). In pharmacology, chemical proteomics has been utilized to determine the specificity of drugs and their analogues, for anticipated known targets, only to discover other proteins that bind and could account for side effects observed in preclinical and clinical trials. As a consequence, chemical proteomics provides a valuable accessory in refinement of second- and third-generation drug design for treatment of many diseases. However, determining definitive affinity capture of proteins by a drug immobilized on soft gel chromatography matrices has highlighted some of the challenges that remain to be addressed. Examples of the different strategies that have emerged using well-established drugs against pharmaceutically important enzymes, such as protein kinases, metalloproteases, PDEs, cytochrome P450s, etc., indicate the potential opportunity to employ chemical proteomics as an early-stage screening approach in the identification of new targets. PMID:22074351

Cancer stem cell drugs target K-ras signaling in a stemness context

PubMed Central

Najumudeen, A K; Jaiswal, A; Lectez, B; Oetken-Lindholm, C; Guzmán, C; Siljamäki, E; Posada, I M D; Lacey, E; Aittokallio, T; Abankwa, D

2016-01-01

Cancer stem cells (CSCs) are considered to be responsible for treatment relapse and have therefore become a major target in cancer research. Salinomycin is the most established CSC inhibitor. However, its primary mechanistic target is still unclear, impeding the discovery of compounds with similar anti-CSC activity. Here, we show that salinomycin very specifically interferes with the activity of K-ras4B, but not H-ras, by disrupting its nanoscale membrane organization. We found that caveolae negatively regulate the sensitivity to this drug. On the basis of this novel mechanistic insight, we defined a K-ras-associated and stem cell-derived gene expression signature that predicts the drug response of cancer cells to salinomycin. Consistent with therapy resistance of CSC, 8% of tumor samples in the TCGA-database displayed our signature and were associated with a significantly higher mortality. Using our K-ras-specific screening platform, we identified several new candidate CSC drugs. Two of these, ophiobolin A and conglobatin A, possessed a similar or higher potency than salinomycin. Finally, we established that the most potent compound, ophiobolin A, exerts its K-ras4B-specific activity through inactivation of calmodulin. Our data suggest that specific interference with the K-ras4B/calmodulin interaction selectively inhibits CSC. PMID:26973241

Database Dictionary for Ethiopian National Ground-Water DAtabase (ENGDA) Data Fields

USGS Publications Warehouse

Kuniansky, Eve L.; Litke, David W.; Tucci, Patrick

2007-01-01

Introduction This document describes the data fields that are used for both field forms and the Ethiopian National Ground-water Database (ENGDA) tables associated with information stored about production wells, springs, test holes, test wells, and water level or water-quality observation wells. Several different words are used in this database dictionary and in the ENGDA database to describe a narrow shaft constructed in the ground. The most general term is borehole, which is applicable to any type of hole. A well is a borehole specifically constructed to extract water from the ground; however, for this data dictionary and for the ENGDA database, the words well and borehole are used interchangeably. A production well is defined as any well used for water supply and includes hand-dug wells, small-diameter bored wells equipped with hand pumps, or large-diameter bored wells equipped with large-capacity motorized pumps. Test holes are borings made to collect information about the subsurface with continuous core or non-continuous core and/or where geophysical logs are collected. Test holes are not converted into wells. A test well is a well constructed for hydraulic testing of an aquifer in order to plan a larger ground-water production system. A water-level or water-quality observation well is a well that is used to collect information about an aquifer and not used for water supply. A spring is any naturally flowing, local, ground-water discharge site. The database dictionary is designed to help define all fields on both field data collection forms (provided in attachment 2 of this report) and for the ENGDA software screen entry forms (described in Litke, 2007). The data entered into each screen entry field are stored in relational database tables within the computer database. The organization of the database dictionary is designed based on field data collection and the field forms, because this is what the majority of people will use. After each field, however, the ENGDA database field name and relational database table is designated; along with the ENGDA screen entry form(s) and the ENGDA field form (attachment 2). The database dictionary is separated into sections. The first section, Basic Site Data Fields, describes the basic site information that is similar for all of the different types of sites. The remaining sections may be applicable for only one type of site; for example, the Well Drilling and Construction Data Fields and Lithologic Description Data Fields are applicable to boreholes and not to springs. Attachment 1 contains a table for conversion from English to metric units. Attachment 2 contains selected field forms used in conjunction with ENGDA. A separate document, 'Users Reference Manual for the Ethiopian National Ground-Water DAtabase (ENGDA),' by David W. Litke was developed as a users guide for the computer database and screen entry. This database dictionary serves as a reference for both the field forms and the computer database. Every effort has been made to have identical field names between the field forms and the screen entry forms in order to avoid confusion.

Drug use in pregnant women-a pilot study of the coherence between reported use of drugs and presence of drugs in plasma.

PubMed

Wolgast, Emelie; Josefsson, Ann; Josefsson, Martin; Lilliecreutz, Caroline; Reis, Margareta

2018-04-01

In Sweden, information on drug use during pregnancy is obtained through an interview and recorded in a standardized medical record at every visit to the antenatal care clinic throughout the pregnancy. Antenatal, delivery, and neonatal records constitute the basis for the Swedish Medical Birth Register (MBR). The purpose of this exploratory study was to investigate the reliability of reported drug use by simultaneous screening for drug substances in the blood stream of the pregnant woman and thereby validate self-reported data in the MBR. Plasma samples from 200 women were obtained at gestational weeks 10-12 and 25 and screened for drugs by using ultra-high performance liquid chromatography with time of flight mass spectrometry (UHPLC-TOF-MS). The results from the analysis were then compared to medical records. At the first sampling occasion, the drugs found by screening had been reported by 86% of the women and on the second sampling, 85.5%. Missed reported information was clearly associated with drugs for occasional use. The most common drugs in plasma taken in early and mid-pregnancy were meclizine and paracetamol. Two types of continuously used drugs, selective serotonin reuptake inhibitors and propranolol, were used. All women using them reported it and the drug screening revealed a 100% coherence. This study shows good coherence between reported drug intake and the drugs found in plasma samples, which in turn positively validates the MBR.

Non-opioid anesthetic drug abuse among anesthesia care providers: a narrative review.

PubMed

Zuleta-Alarcón, Alix; Coffman, John C; Soghomonyan, Suren; Papadimos, Thomas J; Bergese, Sergio D; Moran, Kenneth R

2017-02-01

The objective of this narrative review is to provide an overview of the problem of non-opioid anesthetic drug abuse among anesthesia care providers (ACPs) and to describe current approaches to screening, therapy, and rehabilitation of ACPs suffering from non-opioid anesthetic drug abuse. We first performed a search of all literature available on PubMed prior to April 11, 2016. The search was limited to articles published in Spanish and English, and the following key words were used: anesthesiology, anesthesia personnel, AND substance-related disorders. We also searched Ovid MEDLINE ® databases from 1946-April 11, 2016 using the following search terms: anesthesiology OR anesthesia, OR nurse anesthetist OR anesthesia care provider OR perioperative nursing AND substance-related disorders. Despite an increased awareness of drug abuse among ACPs and improvements in preventive measures, the problem of non-opioid anesthetic drug abuse remains significant. While opioids are the most commonly abused anesthesia medications among ACPs, the abuse of non-opioid anesthetics is a significant cause of morbidity, mortality, and professional demise. Early detection, effective therapy, and long-term follow-up help ACPs cope more effectively with the problem and, when possible, resume their professional activities. There is insufficient evidence to determine the ability of ACPs to return safely to anesthesia practice after rehabilitation, though awareness of the issue and ongoing treatment are necessary to minimize patient risk from potentially related clinical errors.

Prospective virtual screening for novel p53-MDM2 inhibitors using ultrafast shape recognition

NASA Astrophysics Data System (ADS)

Patil, Sachin P.; Ballester, Pedro J.; Kerezsi, Cassidy R.

2014-02-01

The p53 protein, known as the guardian of genome, is mutated or deleted in approximately 50 % of human tumors. In the rest of the cancers, p53 is expressed in its wild-type form, but its function is inhibited by direct binding with the murine double minute 2 (MDM2) protein. Therefore, inhibition of the p53-MDM2 interaction, leading to the activation of tumor suppressor p53 protein presents a fundamentally novel therapeutic strategy against several types of cancers. The present study utilized ultrafast shape recognition (USR), a virtual screening technique based on ligand-receptor 3D shape complementarity, to screen DrugBank database for novel p53-MDM2 inhibitors. Specifically, using 3D shape of one of the most potent crystal ligands of MDM2, MI-63, as the query molecule, six compounds were identified as potential p53-MDM2 inhibitors. These six USR hits were then subjected to molecular modeling investigations through flexible receptor docking followed by comparative binding energy analysis. These studies suggested a potential role of the USR-selected molecules as p53-MDM2 inhibitors. This was further supported by experimental tests showing that the treatment of human colon tumor cells with the top USR hit, telmisartan, led to a dose-dependent cell growth inhibition in a p53-dependent manner. It is noteworthy that telmisartan has a long history of safe human use as an approved anti-hypertension drug and thus may present an immediate clinical potential as a cancer therapeutic. Furthermore, it could also serve as a structurally-novel lead molecule for the development of more potent, small-molecule p53-MDM2 inhibitors against variety of cancers. Importantly, the present study demonstrates that the adopted USR-based virtual screening protocol is a useful tool for hit identification in the domain of small molecule p53-MDM2 inhibitors.

DR HAGIS-a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients.

PubMed

Holm, Sven; Russell, Greg; Nourrit, Vincent; McLoughlin, Niall

2017-01-01

A database of retinal fundus images, the DR HAGIS database, is presented. This database consists of 39 high-resolution color fundus images obtained from a diabetic retinopathy screening program in the UK. The NHS screening program uses service providers that employ different fundus and digital cameras. This results in a range of different image sizes and resolutions. Furthermore, patients enrolled in such programs often display other comorbidities in addition to diabetes. Therefore, in an effort to replicate the normal range of images examined by grading experts during screening, the DR HAGIS database consists of images of varying image sizes and resolutions and four comorbidity subgroups: collectively defined as the diabetic retinopathy, hypertension, age-related macular degeneration, and Glaucoma image set (DR HAGIS). For each image, the vasculature has been manually segmented to provide a realistic set of images on which to test automatic vessel extraction algorithms. Modified versions of two previously published vessel extraction algorithms were applied to this database to provide some baseline measurements. A method based purely on the intensity of images pixels resulted in a mean segmentation accuracy of 95.83% ([Formula: see text]), whereas an algorithm based on Gabor filters generated an accuracy of 95.71% ([Formula: see text]).

Diagnostic accuracy of a two-item Drug Abuse Screening Test (DAST-2).

PubMed

Tiet, Quyen Q; Leyva, Yani E; Moos, Rudolf H; Smith, Brandy

2017-11-01

Drug use is prevalent and costly to society, but individuals with drug use disorders (DUDs) are under-diagnosed and under-treated, particularly in primary care (PC) settings. Drug screening instruments have been developed to identify patients with DUDs and facilitate treatment. The Drug Abuse Screening Test (DAST) is one of the most well-known drug screening instruments. However, similar to many such instruments, it is too long for routine use in busy PC settings. This study developed and validated a briefer and more practical DAST for busy PC settings. We recruited 1300 PC patients in two Department of Veterans Affairs (VA) clinics. Participants responded to a structured diagnostic interview. We randomly selected half of the sample to develop and the other half to validate the new instrument. We employed signal detection techniques to select the best DAST items to identify DUDs (based on the MINI) and negative consequences of drug use (measured by the Inventory of Drug Use Consequences). Performance indicators were calculated. The two-item DAST (DAST-2) was 97% sensitive and 91% specific for DUDs in the development sample and 95% sensitive and 89% specific in the validation sample. It was highly sensitive and specific for DUD and negative consequences of drug use in subgroups of patients, including gender, age, race/ethnicity, marital status, educational level, and posttraumatic stress disorder status. The DAST-2 is an appropriate drug screening instrument for routine use in PC settings in the VA and may be applicable in broader range of PC clinics. Published by Elsevier Ltd.

Screening for alcohol and drug use in pregnancy.

PubMed

Seib, Charrlotte A; Daglish, Mark; Heath, Renée; Booker, Catriona; Reid, Carol; Fraser, Jennifer

2012-12-01

this study examined the clinical utility and precision of routine screening for alcohol and other drug use among women attending a public antenatal service. a survey of clients and audit of clinical charts. clients attending an antenatal clinic of a large tertiary hospital in Queensland, Australia, from October to December 2009. data were collected from two sources. First, 32 women who reported use of alcohol or other drugs during pregnancy at initial screening were then asked to complete a full substance use survey. Second, data were collected from charts of 349 new clients who attended the antenatal clinic during the study period. Both sensitivity (86%, 67%) and positive predictive value (100%, 92%) for alcohol and other drug use respectively, were high. Only 15% of surveyed women were uncomfortable about being screened for substance use in pregnancy, yet the chart audit revealed poor staff compliance. During the study period, 25% of clients were either not screened adequately or not at all. KEY CONCLUSIONS AND IMPLICATIONS FOR PRACTISE: despite recommended universal screening in pregnancy and the apparent acceptance by our participants, alcohol and other drug (A&OD) screening in the antenatal setting remains problematic. Investigation into the reasons behind, and ways to overcome, the low screening rate could improve health outcomes for mothers and children in this at-risk group. Targeted education and training for midwives may form part of the solution as these clinicians have a key role in implementing prevention and early intervention strategies. Copyright © 2011 Elsevier Ltd. All rights reserved.

Drug Testing Park Law Enforcement Officers.

ERIC Educational Resources Information Center

Murrell, Dan S.; And Others

1991-01-01

Discusses drug testing for park law enforcement officers, presenting drug screening guidelines for park managers. The article examines how to establish programs, whether to screen, legal aspects, and implications of the Handicap Act (which makes it difficult to dismiss employees claiming the handicap of substance abuse without providing…

Screening for mental illness: the merger of eugenics and the drug industry.

PubMed

Sharav, Vera Hassner

2005-01-01

The implementation of a recommendation by the President's New Freedom Commission (NFC) to screen the entire United States population--children first--for presumed, undetected, mental illness is an ill-conceived policy destined for disastrous consequences. The "pseudoscientific" methods used to screen for mental and behavioral abnormalities are a legacy from the discredited ideology of eugenics. Both eugenics and psychiatry suffer from a common philosophical fallacy that undermines the validity of their theories and prescriptions. Both are wed to a faith-based ideological assumption that mental and behavioral manifestations are biologically determined, and are, therefore, ameliorated by biological interventions. NFC promoted the Texas Medication Algorithm Project (TMAP) as a "model" medication treatment plan. The impact of TMAP is evident in the skyrocketing increase in psychotropic drug prescriptions for children and adults, and in the disproportionate expenditure for psychotropic drugs. The New Freedom Commission's screening for mental illness initiative is, therefore, but the first step toward prescribing drugs. The escalating expenditure for psychotropic drugs since TMAP leaves little doubt about who the beneficiaries of TMAP are. Screening for mental illness will increase their use.

First quantitative high-throughput screen in zebrafish identifies novel pathways for increasing pancreatic β-cell mass

PubMed Central

Wang, Guangliang; Rajpurohit, Surendra K; Delaspre, Fabien; Walker, Steven L; White, David T; Ceasrine, Alexis; Kuruvilla, Rejji; Li, Ruo-jing; Shim, Joong S; Liu, Jun O; Parsons, Michael J; Mumm, Jeff S

2015-01-01

Whole-organism chemical screening can circumvent bottlenecks that impede drug discovery. However, in vivo screens have not attained throughput capacities possible with in vitro assays. We therefore developed a method enabling in vivo high-throughput screening (HTS) in zebrafish, termed automated reporter quantification in vivo (ARQiv). In this study, ARQiv was combined with robotics to fully actualize whole-organism HTS (ARQiv-HTS). In a primary screen, this platform quantified cell-specific fluorescent reporters in >500,000 transgenic zebrafish larvae to identify FDA-approved (Federal Drug Administration) drugs that increased the number of insulin-producing β cells in the pancreas. 24 drugs were confirmed as inducers of endocrine differentiation and/or stimulators of β-cell proliferation. Further, we discovered novel roles for NF-κB signaling in regulating endocrine differentiation and for serotonergic signaling in selectively stimulating β-cell proliferation. These studies demonstrate the power of ARQiv-HTS for drug discovery and provide unique insights into signaling pathways controlling β-cell mass, potential therapeutic targets for treating diabetes. DOI: http://dx.doi.org/10.7554/eLife.08261.001 PMID:26218223