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

Identification of novel drug scaffolds for inhibition of SARS-CoV 3-Chymotrypsin-like protease using virtual and high-throughput screenings.

PubMed

Lee, Hyun; Mittal, Anuradha; Patel, Kavankumar; Gatuz, Joseph L; Truong, Lena; Torres, Jaime; Mulhearn, Debbie C; Johnson, Michael E

2014-01-01

We have used a combination of virtual screening (VS) and high-throughput screening (HTS) techniques to identify novel, non-peptidic small molecule inhibitors against human SARS-CoV 3CLpro. A structure-based VS approach integrating docking and pharmacophore based methods was employed to computationally screen 621,000 compounds from the ZINC library. The screening protocol was validated using known 3CLpro inhibitors and was optimized for speed, improved selectivity, and for accommodating receptor flexibility. Subsequently, a fluorescence-based enzymatic HTS assay was developed and optimized to experimentally screen approximately 41,000 compounds from four structurally diverse libraries chosen mainly based on the VS results. False positives from initial HTS hits were eliminated by a secondary orthogonal binding analysis using surface plasmon resonance (SPR). The campaign identified a reversible small molecule inhibitor exhibiting mixed-type inhibition with a K(i) value of 11.1 μM. Together, these results validate our protocols as suitable approaches to screen virtual and chemical libraries, and the newly identified compound reported in our study represents a promising structural scaffold to pursue for further SARS-CoV 3CLpro inhibitor development. Copyright © 2013. Published by Elsevier Ltd.

[Selection of a melanine concentrating hormone receptor-1 (MCHR1) antagonists' focused library and its biological screening with AequoScreen].

PubMed

Flachner, Beáta; Hajdú, István; Dobi, Krisztina; Lorincz, Zsolt; Cseh, Sándor; Dormán, György

2013-01-01

Target focused libraries can be rapidly selected by 2D virtual screening methods from multimillion compounds' repositories if structures of active compounds are available. In the present study a multi-step virtual and in vitro screening cascade is reported to select Melanin Concentrating Hormone Receptor-1 (MCHR1) antagonists. The 2D similarity search combined with physicochemical parameter filtering is suitable for selecting candidates from multimillion compounds' repository. The seeds of the first round virtual screening were collected from the literature and commercial databases, while the seeds of the second round were the hits of the first round. In vitro screening underlined the efficiency of our approach, as in the second screening round the hit rate (8.6 %) significantly improved compared to the first round (1.9%), reaching the antagonist activity even below 10 nM.

Library fingerprints: a novel approach to the screening of virtual libraries.

PubMed

Klon, Anthony E; Diller, David J

2007-01-01

We propose a novel method to prioritize libraries for combinatorial synthesis and high-throughput screening that assesses the viability of a particular library on the basis of the aggregate physical-chemical properties of the compounds using a naïve Bayesian classifier. This approach prioritizes collections of related compounds according to the aggregate values of their physical-chemical parameters in contrast to single-compound screening. The method is also shown to be useful in screening existing noncombinatorial libraries when the compounds in these libraries have been previously clustered according to their molecular graphs. We show that the method used here is comparable or superior to the single-compound virtual screening of combinatorial libraries and noncombinatorial libraries and is superior to the pairwise Tanimoto similarity searching of a collection of combinatorial libraries.

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.

Spherical harmonics coefficients for ligand-based virtual screening of cyclooxygenase inhibitors.

PubMed

Wang, Quan; Birod, Kerstin; Angioni, Carlo; Grösch, Sabine; Geppert, Tim; Schneider, Petra; Rupp, Matthias; Schneider, Gisbert

2011-01-01

Molecular descriptors are essential for many applications in computational chemistry, such as ligand-based similarity searching. Spherical harmonics have previously been suggested as comprehensive descriptors of molecular structure and properties. We investigate a spherical harmonics descriptor for shape-based virtual screening. We introduce and validate a partially rotation-invariant three-dimensional molecular shape descriptor based on the norm of spherical harmonics expansion coefficients. Using this molecular representation, we parameterize molecular surfaces, i.e., isosurfaces of spatial molecular property distributions. We validate the shape descriptor in a comprehensive retrospective virtual screening experiment. In a prospective study, we virtually screen a large compound library for cyclooxygenase inhibitors, using a self-organizing map as a pre-filter and the shape descriptor for candidate prioritization. 12 compounds were tested in vitro for direct enzyme inhibition and in a whole blood assay. Active compounds containing a triazole scaffold were identified as direct cyclooxygenase-1 inhibitors. This outcome corroborates the usefulness of spherical harmonics for representation of molecular shape in virtual screening of large compound collections. The combination of pharmacophore and shape-based filtering of screening candidates proved to be a straightforward approach to finding novel bioactive chemotypes with minimal experimental effort.

PyGOLD: a python based API for docking based virtual screening workflow generation.

PubMed

Patel, Hitesh; Brinkjost, Tobias; Koch, Oliver

2017-08-15

Molecular docking is one of the successful approaches in structure based discovery and development of bioactive molecules in chemical biology and medicinal chemistry. Due to the huge amount of computational time that is still required, docking is often the last step in a virtual screening approach. Such screenings are set as workflows spanned over many steps, each aiming at different filtering task. These workflows can be automatized in large parts using python based toolkits except for docking using the docking software GOLD. However, within an automated virtual screening workflow it is not feasible to use the GUI in between every step to change the GOLD configuration file. Thus, a python module called PyGOLD was developed, to parse, edit and write the GOLD configuration file and to automate docking based virtual screening workflows. The latest version of PyGOLD, its documentation and example scripts are available at: http://www.ccb.tu-dortmund.de/koch or http://www.agkoch.de. PyGOLD is implemented in Python and can be imported as a standard python module without any further dependencies. oliver.koch@agkoch.de, oliver.koch@tu-dortmund.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Quantitative structure-activity relationship analysis and virtual screening studies for identifying HDAC2 inhibitors from known HDAC bioactive chemical libraries.

PubMed

Pham-The, H; Casañola-Martin, G; Diéguez-Santana, K; Nguyen-Hai, N; Ngoc, N T; Vu-Duc, L; Le-Thi-Thu, H

2017-03-01

Histone deacetylases (HDAC) are emerging as promising targets in cancer, neuronal diseases and immune disorders. Computational modelling approaches have been widely applied for the virtual screening and rational design of novel HDAC inhibitors. In this study, different machine learning (ML) techniques were applied for the development of models that accurately discriminate HDAC2 inhibitors form non-inhibitors. The obtained models showed encouraging results, with the global accuracy in the external set ranging from 0.83 to 0.90. Various aspects related to the comparison of modelling techniques, applicability domain and descriptor interpretations were discussed. Finally, consensus predictions of these models were used for screening HDAC2 inhibitors from four chemical libraries whose bioactivities against HDAC1, HDAC3, HDAC6 and HDAC8 have been known. According to the results of virtual screening assays, structures of some hits with pair-isoform-selective activity (between HDAC2 and other HDACs) were revealed. This study illustrates the power of ML-based QSAR approaches for the screening and discovery of potent, isoform-selective HDACIs.

Spectrophores as one-dimensional descriptors calculated from three-dimensional atomic properties: applications ranging from scaffold hopping to multi-target virtual screening.

PubMed

Gladysz, Rafaela; Dos Santos, Fabio Mendes; Langenaeker, Wilfried; Thijs, Gert; Augustyns, Koen; De Winter, Hans

2018-03-07

Spectrophores are novel descriptors that are calculated from the three-dimensional atomic properties of molecules. In our current implementation, the atomic properties that were used to calculate spectrophores include atomic partial charges, atomic lipophilicity indices, atomic shape deviations and atomic softness properties. This approach can easily be widened to also include additional atomic properties. Our novel methodology finds its roots in the experimental affinity fingerprinting technology developed in the 1990's by Terrapin Technologies. Here we have translated it into a purely virtual approach using artificial affinity cages and a simplified metric to calculate the interaction between these cages and the atomic properties. A typical spectrophore consists of a vector of 48 real numbers. This makes it highly suitable for the calculation of a wide range of similarity measures for use in virtual screening and for the investigation of quantitative structure-activity relationships in combination with advanced statistical approaches such as self-organizing maps, support vector machines and neural networks. In our present report we demonstrate the applicability of our novel methodology for scaffold hopping as well as virtual screening.

SABRE: ligand/structure-based virtual screening approach using consensus molecular-shape pattern recognition.

PubMed

Wei, Ning-Ning; Hamza, Adel

2014-01-27

We present an efficient and rational ligand/structure shape-based virtual screening approach combining our previous ligand shape-based similarity SABRE (shape-approach-based routines enhanced) and the 3D shape of the receptor binding site. Our approach exploits the pharmacological preferences of a number of known active ligands to take advantage of the structural diversities and chemical similarities, using a linear combination of weighted molecular shape density. Furthermore, the algorithm generates a consensus molecular-shape pattern recognition that is used to filter and place the candidate structure into the binding pocket. The descriptor pool used to construct the consensus molecular-shape pattern consists of four dimensional (4D) fingerprints generated from the distribution of conformer states available to a molecule and the 3D shapes of a set of active ligands computed using SABRE software. The virtual screening efficiency of SABRE was validated using the Database of Useful Decoys (DUD) and the filtered version (WOMBAT) of 10 DUD targets. The ligand/structure shape-based similarity SABRE algorithm outperforms several other widely used virtual screening methods which uses the data fusion of multiscreening tools (2D and 3D fingerprints) and demonstrates a superior early retrieval rate of active compounds (EF(0.1%) = 69.0% and EF(1%) = 98.7%) from a large size of ligand database (∼95,000 structures). Therefore, our developed similarity approach can be of particular use for identifying active compounds that are similar to reference molecules and predicting activity against other targets (chemogenomics). An academic license of the SABRE program is available on request.

Consensus Induced Fit Docking (cIFD): methodology, validation, and application to the discovery of novel Crm1 inhibitors

NASA Astrophysics Data System (ADS)

Kalid, Ori; Toledo Warshaviak, Dora; Shechter, Sharon; Sherman, Woody; Shacham, Sharon

2012-11-01

We present the Consensus Induced Fit Docking (cIFD) approach for adapting a protein binding site to accommodate multiple diverse ligands for virtual screening. This novel approach results in a single binding site structure that can bind diverse chemotypes and is thus highly useful for efficient structure-based virtual screening. We first describe the cIFD method and its validation on three targets that were previously shown to be challenging for docking programs (COX-2, estrogen receptor, and HIV reverse transcriptase). We then demonstrate the application of cIFD to the challenging discovery of irreversible Crm1 inhibitors. We report the identification of 33 novel Crm1 inhibitors, which resulted from the testing of 402 purchased compounds selected from a screening set containing 261,680 compounds. This corresponds to a hit rate of 8.2 %. The novel Crm1 inhibitors reveal diverse chemical structures, validating the utility of the cIFD method in a real-world drug discovery project. This approach offers a pragmatic way to implicitly account for protein flexibility without the additional computational costs of ensemble docking or including full protein flexibility during virtual screening.

Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2012-05-01

SAMPL3 fragment based virtual screening challenge provides a valuable opportunity for researchers to test their programs, methods and screening protocols in a blind testing environment. We participated in SAMPL3 challenge and evaluated our virtual fragment screening protocol, which involves RosettaLigand as the core component by screening a 500 fragments Maybridge library against bovine pancreatic trypsin. Our study reaffirmed that the real test for any virtual screening approach would be in a blind testing environment. The analyses presented in this paper also showed that virtual screening performance can be improved, if a set of known active compounds is available and parameters and methods that yield better enrichment are selected. Our study also highlighted that to achieve accurate orientation and conformation of ligands within a binding site, selecting an appropriate method to calculate partial charges is important. Another finding is that using multiple receptor ensembles in docking does not always yield better enrichment than individual receptors. On the basis of our results and retrospective analyses from SAMPL3 fragment screening challenge we anticipate that chances of success in a fragment screening process could be increased significantly with careful selection of receptor structures, protein flexibility, sufficient conformational sampling within binding pocket and accurate assignment of ligand and protein partial charges.

Graph-based similarity concepts in virtual screening.

PubMed

Hutter, Michael C

2011-03-01

Applying similarity for finding new promising compounds is a key issue in drug design. Conversely, quantifying similarity between molecules has remained a difficult task despite the numerous approaches. Here, some general aspects along with recent developments regarding similarity criteria are collected. For the purpose of virtual screening, the compounds have to be encoded into a computer-readable format that permits a comparison, according to given similarity criteria, comprising the use of the 3D structure, fingerprints, graph-based and alignment-based approaches. Whereas finding the most common substructures is the most obvious method, more recent approaches take into account chemical modifications that appear throughout existing drugs, from various therapeutic categories and targets.

ChemScreener: A Distributed Computing Tool for Scaffold based Virtual Screening.

PubMed

Karthikeyan, Muthukumarasamy; Pandit, Deepak; Vyas, Renu

2015-01-01

In this work we present ChemScreener, a Java-based application to perform virtual library generation combined with virtual screening in a platform-independent distributed computing environment. ChemScreener comprises a scaffold identifier, a distinct scaffold extractor, an interactive virtual library generator as well as a virtual screening module for subsequently selecting putative bioactive molecules. The virtual libraries are annotated with chemophore-, pharmacophore- and toxicophore-based information for compound prioritization. The hits selected can then be further processed using QSAR, docking and other in silico approaches which can all be interfaced within the ChemScreener framework. As a sample application, in this work scaffold selectivity, diversity, connectivity and promiscuity towards six important therapeutic classes have been studied. In order to illustrate the computational power of the application, 55 scaffolds extracted from 161 anti-psychotic compounds were enumerated to produce a virtual library comprising 118 million compounds (17 GB) and annotated with chemophore, pharmacophore and toxicophore based features in a single step which would be non-trivial to perform with many standard software tools today on libraries of this size.

Combining structure-based pharmacophore modeling, virtual screening, and in silico ADMET analysis to discover novel tetrahydro-quinoline based pyruvate kinase isozyme M2 activators with antitumor activity

PubMed Central

Chen, Can; Wang, Ting; Wu, Fengbo; Huang, Wei; He, Gu; Ouyang, Liang; Xiang, Mingli; Peng, Cheng; Jiang, Qinglin

2014-01-01

Compared with normal differentiated cells, cancer cells upregulate the expression of pyruvate kinase isozyme M2 (PKM2) to support glycolytic intermediates for anabolic processes, including the synthesis of nucleic acids, amino acids, and lipids. In this study, a combination of the structure-based pharmacophore modeling and a hybrid protocol of virtual screening methods comprised of pharmacophore model-based virtual screening, docking-based virtual screening, and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis were used to retrieve novel PKM2 activators from commercially available chemical databases. Tetrahydroquinoline derivatives were identified as potential scaffolds of PKM2 activators. Thus, the hybrid virtual screening approach was applied to screen the focused tetrahydroquinoline derivatives embedded in the ZINC database. Six hit compounds were selected from the final hits and experimental studies were then performed. Compound 8 displayed a potent inhibitory effect on human lung cancer cells. Following treatment with Compound 8, cell viability, apoptosis, and reactive oxygen species (ROS) production were examined in A549 cells. Finally, we evaluated the effects of Compound 8 on mice xenograft tumor models in vivo. These results may provide important information for further research on novel PKM2 activators as antitumor agents. PMID:25214764

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.

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

A Pipeline To Enhance Ligand Virtual Screening: Integrating Molecular Dynamics and Fingerprints for Ligand and Proteins.

PubMed

Spyrakis, Francesca; Benedetti, Paolo; Decherchi, Sergio; Rocchia, Walter; Cavalli, Andrea; Alcaro, Stefano; Ortuso, Francesco; Baroni, Massimo; Cruciani, Gabriele

2015-10-26

The importance of taking into account protein flexibility in drug design and virtual ligand screening (VS) has been widely debated in the literature, and molecular dynamics (MD) has been recognized as one of the most powerful tools for investigating intrinsic protein dynamics. Nevertheless, deciphering the amount of information hidden in MD simulations and recognizing a significant minimal set of states to be used in virtual screening experiments can be quite complicated. Here we present an integrated MD-FLAP (molecular dynamics-fingerprints for ligand and proteins) approach, comprising a pipeline of molecular dynamics, clustering and linear discriminant analysis, for enhancing accuracy and efficacy in VS campaigns. We first extracted a limited number of representative structures from tens of nanoseconds of MD trajectories by means of the k-medoids clustering algorithm as implemented in the BiKi Life Science Suite ( http://www.bikitech.com [accessed July 21, 2015]). Then, instead of applying arbitrary selection criteria, that is, RMSD, pharmacophore properties, or enrichment performances, we allowed the linear discriminant analysis algorithm implemented in FLAP ( http://www.moldiscovery.com [accessed July 21, 2015]) to automatically choose the best performing conformational states among medoids and X-ray structures. Retrospective virtual screenings confirmed that ensemble receptor protocols outperform single rigid receptor approaches, proved that computationally generated conformations comprise the same quantity/quality of information included in X-ray structures, and pointed to the MD-FLAP approach as a valuable tool for improving VS performances.

Condorcet and borda count fusion method for ligand-based virtual screening.

PubMed

Ahmed, Ali; Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2014-01-01

It is known that any individual similarity measure will not always give the best recall of active molecule structure for all types of activity classes. Recently, the effectiveness of ligand-based virtual screening approaches can be enhanced by using data fusion. Data fusion can be implemented using two different approaches: group fusion and similarity fusion. Similarity fusion involves searching using multiple similarity measures. The similarity scores, or ranking, for each similarity measure are combined to obtain the final ranking of the compounds in the database. The Condorcet fusion method was examined. This approach combines the outputs of similarity searches from eleven association and distance similarity coefficients, and then the winner measure for each class of molecules, based on Condorcet fusion, was chosen to be the best method of searching. The recall of retrieved active molecules at top 5% and significant test are used to evaluate our proposed method. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints. Simulated virtual screening experiments with the standard two data sets show that the use of Condorcet fusion provides a very simple way of improving the ligand-based virtual screening, especially when the active molecules being sought have a lowest degree of structural heterogeneity. However, the effectiveness of the Condorcet fusion was increased slightly when structural sets of high diversity activities were being sought.

Condorcet and borda count fusion method for ligand-based virtual screening

PubMed Central

2014-01-01

Background It is known that any individual similarity measure will not always give the best recall of active molecule structure for all types of activity classes. Recently, the effectiveness of ligand-based virtual screening approaches can be enhanced by using data fusion. Data fusion can be implemented using two different approaches: group fusion and similarity fusion. Similarity fusion involves searching using multiple similarity measures. The similarity scores, or ranking, for each similarity measure are combined to obtain the final ranking of the compounds in the database. Results The Condorcet fusion method was examined. This approach combines the outputs of similarity searches from eleven association and distance similarity coefficients, and then the winner measure for each class of molecules, based on Condorcet fusion, was chosen to be the best method of searching. The recall of retrieved active molecules at top 5% and significant test are used to evaluate our proposed method. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints. Conclusions Simulated virtual screening experiments with the standard two data sets show that the use of Condorcet fusion provides a very simple way of improving the ligand-based virtual screening, especially when the active molecules being sought have a lowest degree of structural heterogeneity. However, the effectiveness of the Condorcet fusion was increased slightly when structural sets of high diversity activities were being sought. PMID:24883114

Discovery of novel mGluR1 antagonists: a multistep virtual screening approach based on an SVM model and a pharmacophore hypothesis significantly increases the hit rate and enrichment factor.

PubMed

Li, Guo-Bo; Yang, Ling-Ling; Feng, Shan; Zhou, Jian-Ping; Huang, Qi; Xie, Huan-Zhang; Li, Lin-Li; Yang, Sheng-Yong

2011-03-15

Development of glutamate non-competitive antagonists of mGluR1 (Metabotropic glutamate receptor subtype 1) has increasingly attracted much attention in recent years due to their potential therapeutic application for various nervous disorders. Since there is no crystal structure reported for mGluR1, ligand-based virtual screening (VS) methods, typically pharmacophore-based VS (PB-VS), are often used for the discovery of mGluR1 antagonists. Nevertheless, PB-VS usually suffers a lower hit rate and enrichment factor. In this investigation, we established a multistep ligand-based VS approach that is based on a support vector machine (SVM) classification model and a pharmacophore model. Performance evaluation of these methods in virtual screening against a large independent test set, M-MDDR, show that the multistep VS approach significantly increases the hit rate and enrichment factor compared with the individual SB-VS and PB-VS methods. The multistep VS approach was then used to screen several large chemical libraries including PubChem, Specs, and Enamine. Finally a total of 20 compounds were selected from the top ranking compounds, and shifted to the subsequent in vitro and in vivo studies, which results will be reported in the near future. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer.

PubMed

Ren, Ji-Xia; Li, Cheng-Ping; Zhou, Xiu-Ling; Cao, Xue-Song; Xie, Yong

2017-08-22

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using 'Receptor-Ligand Pharmacophore Generation' method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r 2 of 0.996; for the test set, the correlation coefficient r 2 was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.

Discovery of new inhibitors of the bacterial peptidoglycan biosynthesis enzymes MurD and MurF by structure-based virtual screening.

PubMed

Turk, Samo; Kovac, Andreja; Boniface, Audrey; Bostock, Julieanne M; Chopra, Ian; Blanot, Didier; Gobec, Stanislav

2009-03-01

The ATP-dependent Mur ligases (MurC, MurD, MurE and MurF) successively add L-Ala, D-Glu, meso-A(2)pm or L-Lys, and D-Ala-D-Ala to the nucleotide precursor UDP-MurNAc, and they represent promising targets for antibacterial drug discovery. We have used the molecular docking programme eHiTS for the virtual screening of 1990 compounds from the National Cancer Institute 'Diversity Set' on MurD and MurF. The 50 top-scoring compounds from screening on each enzyme were selected for experimental biochemical evaluation. Our approach of virtual screening and subsequent in vitro biochemical evaluation of the best ranked compounds has provided four novel MurD inhibitors (best IC(50)=10 microM) and one novel MurF inhibitor (IC(50)=63 microM).

Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore-based virtual screening, molecular docking and molecular dynamics studies.

PubMed

Islam, Md Ataul; Pillay, Tahir S

2017-08-01

In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB. © 2017 John Wiley & Sons A/S.

Modeling and Deorphanization of Orphan GPCRs.

PubMed

Diaz, Constantino; Angelloz-Nicoud, Patricia; Pihan, Emilie

2018-01-01

Despite tremendous efforts, approximately 120 GPCRs remain orphan. Their physiological functions and their potential roles in diseases are poorly understood. Orphan GPCRs are extremely important because they may provide novel therapeutic targets for unmet medical needs. As a complement to experimental approaches, molecular modeling and virtual screening are efficient techniques to discover synthetic surrogate ligands which can help to elucidate the role of oGPCRs. Constitutively activated mutants and recently published active structures of GPCRs provide stimulating opportunities for building active molecular models for oGPCRs and identifying activators using virtual screening of compound libraries. We describe the molecular modeling and virtual screening process we have applied in the discovery of surrogate ligands, and provide examples for CCKA, a simulated oGPCR, and for two oGPCRs, GPR52 and GPR34.

Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

PubMed

Tropsha, Alexander; Golbraikh, Alexander

2007-01-01

Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data. Model extrapolation was considered if only in hypothetical sense in terms of potential modifications of known biologically active chemicals that could improve compounds' activity. This critical review re-examines the strategy and the output of the modern QSAR modeling approaches. We provide examples and arguments suggesting that current methodologies may afford robust and validated models capable of accurate prediction of compound properties for molecules not included in the training sets. We discuss a data-analytical modeling workflow developed in our laboratory that incorporates modules for combinatorial QSAR model development (i.e., using all possible binary combinations of available descriptor sets and statistical data modeling techniques), rigorous model validation, and virtual screening of available chemical databases to identify novel biologically active compounds. Our approach places particular emphasis on model validation as well as the need to define model applicability domains in the chemistry space. We present examples of studies where the application of rigorously validated QSAR models to virtual screening identified computational hits that were confirmed by subsequent experimental investigations. The emerging focus of QSAR modeling on target property forecasting brings it forward as predictive, as opposed to evaluative, modeling approach.

Virtual daily living test to screen for mild cognitive impairment using kinematic movement analysis

PubMed Central

Seo, Kyoungwon; Kim, Jae-kwan; Oh, Dong Hoon

2017-01-01

Questionnaires or computer-based tests for assessing activities of daily living are well-known approaches to screen for mild cognitive impairment (MCI). However, questionnaires are subjective and computerized tests only collect simple performance data with conventional input devices such as a mouse and keyboard. This study explored the validity and discriminative power of a virtual daily living test as a new diagnostic approach to assess MCI. Twenty-two healthy controls and 20 patients with MCI were recruited. The virtual daily living test presents two complex daily living tasks in an immersive virtual reality environment. The tasks were conducted based on subject body movements and detailed behavioral data (i.e., kinematic measures) were collected. Performance in both the proposed virtual daily living test and conventional neuropsychological tests for patients with MCI was compared to healthy controls. Kinematic measures considered in this study, such as body movement trajectory, time to completion, and speed, classified patients with MCI from healthy controls, F(8, 33) = 5.648, p < 0.001, η2 = 0.578. When both hand and head speed were employed in conjunction with the immediate free-recall test, a conventional neuropsychological test, the discrimination power for screening MCI was significantly improved to 90% sensitivity and 95.5% specificity (cf. the immediate free-recall test alone has 80% sensitivity and 77.3% specificity). Inclusion of the kinematic measures in screening for MCI significantly improved the classification of patients with MCI compared to the healthy control group, Wilks’ Lambda = 0.451, p < 0.001. PMID:28738088

Homology modeling and virtual screening of inhibitors against TEM- and SHV-type-resistant mutants: A multilayer filtering approach.

PubMed

Baig, Mohammad H; Balaramnavar, Vishal M; Wadhwa, Gulshan; Khan, Asad U

2015-01-01

TEM and SHV are class-A-type β-lactamases commonly found in Escherichia coli and Klebsiella pneumoniae. Previous studies reported S130G and K234R mutations in SHVs to be 41- and 10-fold more resistant toward clavulanic acid than SHV-1, respectively, whereas TEM S130G and R244S also showed the same level of resistance. These selected mutants confer higher level of resistance against clavulanic acid. They also show little susceptibility against other commercially available β-lactamase inhibitors. In this study, we have used docking-based virtual screening approach in order to screen potential inhibitors against some of the major resistant mutants of SHV and TEM types β-lactamase. Two different inhibitor-resistant mutants from SHV and TEM were selected. Moreover, we have retained the active site water molecules within each enzyme. Active site water molecules were placed within modeled structure of the mutant whose structure was unavailable with protein databank. The novelty of this work lies in the use of multilayer virtual screening approach for the prediction of best and accurate results. We are reporting five inhibitors on the basis of their efficacy against all the selected resistant mutants. These inhibitors were selected on the basis of their binding efficacies and pharmacophore features. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

Pharmacophore screening of the protein data bank for specific binding site chemistry.

PubMed

Campagna-Slater, Valérie; Arrowsmith, Andrew G; Zhao, Yong; Schapira, Matthieu

2010-03-22

A simple computational approach was developed to screen the Protein Data Bank (PDB) for putative pockets possessing a specific binding site chemistry and geometry. The method employs two commonly used 3D screening technologies, namely identification of cavities in protein structures and pharmacophore screening of chemical libraries. For each protein structure, a pocket finding algorithm is used to extract potential binding sites containing the correct types of residues, which are then stored in a large SDF-formatted virtual library; pharmacophore filters describing the desired binding site chemistry and geometry are then applied to screen this virtual library and identify pockets matching the specified structural chemistry. As an example, this approach was used to screen all human protein structures in the PDB and identify sites having chemistry similar to that of known methyl-lysine binding domains that recognize chromatin methylation marks. The selected genes include known readers of the histone code as well as novel binding pockets that may be involved in epigenetic signaling. Putative allosteric sites were identified on the structures of TP53BP1, L3MBTL3, CHEK1, KDM4A, and CREBBP.

Fragment-based virtual screening approach and molecular dynamics simulation studies for identification of BACE1 inhibitor leads.

PubMed

Manoharan, Prabu; Ghoshal, Nanda

2018-05-01

Traditional structure-based virtual screening method to identify drug-like small molecules for BACE1 is so far unsuccessful. Location of BACE1, poor Blood Brain Barrier permeability and P-glycoprotein (Pgp) susceptibility of the inhibitors make it even more difficult. Fragment-based drug design method is suitable for efficient optimization of initial hit molecules for target like BACE1. We have developed a fragment-based virtual screening approach to identify/optimize the fragment molecules as a starting point. This method combines the shape, electrostatic, and pharmacophoric features of known fragment molecules, bound to protein conjugate crystal structure, and aims to identify both chemically and energetically feasible small fragment ligands that bind to BACE1 active site. The two top-ranked fragment hits were subjected for a 53 ns MD simulation. Principle component analysis and free energy landscape analysis reveal that the new ligands show the characteristic features of established BACE1 inhibitors. The potent method employed in this study may serve for the development of potential lead molecules for BACE1-directed Alzheimer's disease therapeutics.

An enantiomer-based virtual screening approach: Discovery of chiral organophosphates as acetyl cholinesterase inhibitors.

PubMed

Zhang, Aiqian; Mu, Yunsong; Wu, Fengchang

2017-04-01

Chiral organophosphates (OPs) have been used widely around the world, very little is known about binding mechanisms with biological macromolecules. An in-depth understanding of the stereo selectivity of human AChE and discovering bioactive enantiomers of OPs can decrease health risks of these chiral chemicals. In the present study, a flexible molecular docking approach was conducted to investigate different binding modes of twelve phosphorus enantiomers. A pharmacophore model was then developed on basis of the bioactive conformations of these compounds. After virtual screening, twenty-four potential bioactive compounds were found, of which three compounds (Ethyl p-nitrophenyl phenylphosphonate (EPN), 1-naphthaleneacetic anhydride and N,4-dimethyl-N-phenyl-benzenesulfonamide) were tested by use of different in vitro assays. S-isomer of EPN was also found to exhibit greater inhibitory activity towards human AChE than the corresponding R-isomer. These findings affirm that stereochemistry plays a crucial role in virtual screening, and provide a new insight into designing safer organ phosphorus pesticides on human health. Copyright © 2017 Elsevier Inc. All rights reserved.

Identifying potential selective fluorescent probes for cancer-associated protein carbonic anhydrase IX using a computational approach.

PubMed

Kamstra, Rhiannon L; Floriano, Wely B

2014-11-01

Carbonic anhydrase IX (CAIX) is a biomarker for tumor hypoxia. Fluorescent inhibitors of CAIX have been used to study hypoxic tumor cell lines. However, these inhibitor-based fluorescent probes may have a therapeutic effect that is not appropriate for monitoring treatment efficacy. In the search for novel fluorescent probes that are not based on known inhibitors, a database of 20,860 fluorescent compounds was virtually screened against CAIX using hierarchical virtual ligand screening (HierVLS). The screening database contained 14,862 compounds tagged with the ATTO680 fluorophore plus an additional 5998 intrinsically fluorescent compounds. Overall ranking of compounds to identify hit molecular probe candidates utilized a principal component analysis (PCA) approach. Four potential binding sites, including the catalytic site, were identified within the structure of the protein and targeted for virtual screening. Available sequence information for 23 carbonic anhydrase isoforms was used to prioritize the four sites based on the estimated "uniqueness" of each site in CAIX relative to the other isoforms. A database of 32 known inhibitors and 478 decoy compounds was used to validate the methodology. A receiver-operating characteristic (ROC) analysis using the first principal component (PC1) as predictive score for the validation database yielded an area under the curve (AUC) of 0.92. AUC is interpreted as the probability that a binder will have a better score than a non-binder. The use of first component analysis of binding energies for multiple sites is a novel approach for hit selection. The very high prediction power for this approach increases confidence in the outcome from the fluorescent library screening. Ten of the top scoring candidates for isoform-selective putative binding sites are suggested for future testing as fluorescent molecular probe candidates. Copyright © 2014 Elsevier Inc. All rights reserved.

An investigation of the efficacy of collaborative virtual reality systems for moderated remote usability testing.

PubMed

Chalil Madathil, Kapil; Greenstein, Joel S

2017-11-01

Collaborative virtual reality-based systems have integrated high fidelity voice-based communication, immersive audio and screen-sharing tools into virtual environments. Such three-dimensional collaborative virtual environments can mirror the collaboration among usability test participants and facilitators when they are physically collocated, potentially enabling moderated usability tests to be conducted effectively when the facilitator and participant are located in different places. We developed a virtual collaborative three-dimensional remote moderated usability testing laboratory and employed it in a controlled study to evaluate the effectiveness of moderated usability testing in a collaborative virtual reality-based environment with two other moderated usability testing methods: the traditional lab approach and Cisco WebEx, a web-based conferencing and screen sharing approach. Using a mixed methods experimental design, 36 test participants and 12 test facilitators were asked to complete representative tasks on a simulated online shopping website. The dependent variables included the time taken to complete the tasks; the usability defects identified and their severity; and the subjective ratings on the workload index, presence and satisfaction questionnaires. Remote moderated usability testing methodology using a collaborative virtual reality system performed similarly in terms of the total number of defects identified, the number of high severity defects identified and the time taken to complete the tasks with the other two methodologies. The overall workload experienced by the test participants and facilitators was the least with the traditional lab condition. No significant differences were identified for the workload experienced with the virtual reality and the WebEx conditions. However, test participants experienced greater involvement and a more immersive experience in the virtual environment than in the WebEx condition. The ratings for the virtual environment condition were not significantly different from those for the traditional lab condition. The results of this study suggest that participants were productive and enjoyed the virtual lab condition, indicating the potential of a virtual world based approach as an alternative to conventional approaches for synchronous usability testing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of a focused virtual library of heterobifunctional ligands for Clostridium difficile toxins.

PubMed

Sanhueza, Carlos A; Cartmell, Jonathan; El-Hawiet, Amr; Szpacenko, Adam; Kitova, Elena N; Daneshfar, Rambod; Klassen, John S; Lang, Dean E; Eugenio, Luiz; Ng, Kenneth K-S; Kitov, Pavel I; Bundle, David R

2015-01-07

A focused library of virtual heterobifunctional ligands was generated in silico and a set of ligands with recombined fragments was synthesized and evaluated for binding to Clostridium difficile toxins. The position of the trisaccharide fragment was used as a reference for filtering docked poses during virtual screening to match the trisaccharide ligand in a crystal structure. The peptoid, a diversity fragment probing the protein surface area adjacent to a known binding site, was generated by a multi-component Ugi reaction. Our approach combines modular fragment-based design with in silico screening of synthetically feasible compounds and lays the groundwork for future efforts in development of composite bifunctional ligands for large clostridial toxins.

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

Large-scale virtual screening on public cloud resources with Apache Spark.

PubMed

Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola

2017-01-01

Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.

Discovery of novel Pim-1 kinase inhibitors by a hierarchical multistage virtual screening approach based on SVM model, pharmacophore, and molecular docking.

PubMed

Ren, Ji-Xia; Li, Lin-Li; Zheng, Ren-Lin; Xie, Huan-Zhang; Cao, Zhi-Xing; Feng, Shan; Pan, You-Li; Chen, Xin; Wei, Yu-Quan; Yang, Sheng-Yong

2011-06-27

In this investigation, we describe the discovery of novel potent Pim-1 inhibitors by employing a proposed hierarchical multistage virtual screening (VS) approach, which is based on support vector machine-based (SVM-based VS or SB-VS), pharmacophore-based VS (PB-VS), and docking-based VS (DB-VS) methods. In this approach, the three VS methods are applied in an increasing order of complexity so that the first filter (SB-VS) is fast and simple, while successive ones (PB-VS and DB-VS) are more time-consuming but are applied only to a small subset of the entire database. Evaluation of this approach indicates that it can be used to screen a large chemical library rapidly with a high hit rate and a high enrichment factor. This approach was then applied to screen several large chemical libraries, including PubChem, Specs, and Enamine as well as an in-house database. From the final hits, 47 compounds were selected for further in vitro Pim-1 inhibitory assay, and 15 compounds show nanomolar level or low micromolar inhibition potency against Pim-1. In particular, four of them were found to have new scaffolds which have potential for the chemical development of Pim-1 inhibitors.

Validation of virtual learning object to support the teaching of nursing care systematization.

PubMed

Salvador, Pétala Tuani Candido de Oliveira; Mariz, Camila Maria Dos Santos; Vítor, Allyne Fortes; Ferreira Júnior, Marcos Antônio; Fernandes, Maria Isabel Domingues; Martins, José Carlos Amado; Santos, Viviane Euzébia Pereira

2018-01-01

to describe the content validation process of a Virtual Learning Object to support the teaching of nursing care systematization to nursing professionals. methodological study, with quantitative approach, developed according to the methodological reference of Pasquali's psychometry and conducted from March to July 2016, from two-stage Delphi procedure. in the Delphi 1 stage, eight judges evaluated the Virtual Object; in Delphi 2 stage, seven judges evaluated it. The seven screens of the Virtual Object were analyzed as to the suitability of its contents. The Virtual Learning Object to support the teaching of nursing care systematization was considered valid in its content, with a Total Content Validity Coefficient of 0.96. it is expected that the Virtual Object can support the teaching of nursing care systematization in light of appropriate and effective pedagogical approaches.

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.

Virtual Screening with AutoDock: Theory and Practice

PubMed Central

Cosconati, Sandro; Forli, Stefano; Perryman, Alex L.; Harris, Rodney; Goodsell, David S.; Olson, Arthur J.

2011-01-01

Importance to the field Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules. Areas covered in this review We describe virtual screening methods that are available in the AutoDock suite of programs, and several of our successes in using AutoDock virtual screening in pharmaceutical lead discovery. What the reader will gain A general overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges. Take home message Virtual screening is an effective tool for the discovery of compounds for use as leads in drug discovery, and the free, open source program AutoDock is an effective tool for virtual screening. PMID:21532931

Ultra-High-Throughput Structure-Based Virtual Screening for Small-Molecule Inhibitors of Protein-Protein Interactions

PubMed Central

Johnson, David K.; Karanicolas, John

2016-01-01

Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased “pocket optimization” simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its “exemplar”: a perfect, but non-physical, pseudo-ligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 minutes on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a “pocket-optimized” ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target. PMID:26726827

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.

Virtual Environment TBI Screen (VETS)

DTIC Science & Technology

2014-10-01

balance challenges performed on a modified Wii Balance Board . Implementation of this device will enhance current approaches in TBI and mild TBI (i.e...TBI) screen (VETS) device in measuring standing balance . This system consists of software, a Wii balance board , and a large screen television that...Validate Wii ™ Balance Board relative to NeuroCom forceplate ! Running Wii Balance Board validation protocol. ! Milestone Achieved:

Efficient hit-finding approaches for histone methyltransferases: the key parameters.

PubMed

Ahrens, Thomas; Bergner, Andreas; Sheppard, David; Hafenbradl, Doris

2012-01-01

For many novel epigenetics targets the chemical ligand space and structural information were limited until recently and are still largely unknown for some targets. Hit-finding campaigns are therefore dependent on large and chemically diverse libraries. In the specific case of the histone methyltransferase G9a, the authors have been able to apply an efficient process of intelligent selection of compounds for primary screening, rather than screening the full diverse deck of 900 000 compounds to identify hit compounds. A number of different virtual screening methods have been applied for the compound selection, and the results have been analyzed in the context of their individual success rates. For the primary screening of 2112 compounds, a FlashPlate assay format and full-length histone H3.1 substrate were employed. Validation of hit compounds was performed using the orthogonal fluorescence lifetime technology. Rated by purity and IC(50) value, 18 compounds (0.9% of compound screening deck) were finally considered validated primary G9a hits. The hit-finding approach has led to novel chemotypes being identified, which can facilitate hit-to-lead projects. This study demonstrates the power of virtual screening technologies for novel, therapeutically relevant epigenetics protein targets.

Applying DEKOIS 2.0 in structure-based virtual screening to probe the impact of preparation procedures and score normalization.

PubMed

Ibrahim, Tamer M; Bauer, Matthias R; Boeckler, Frank M

2015-01-01

Structure-based virtual screening techniques can help to identify new lead structures and complement other screening approaches in drug discovery. Prior to docking, the data (protein crystal structures and ligands) should be prepared with great attention to molecular and chemical details. Using a subset of 18 diverse targets from the recently introduced DEKOIS 2.0 benchmark set library, we found differences in the virtual screening performance of two popular docking tools (GOLD and Glide) when employing two different commercial packages (e.g. MOE and Maestro) for preparing input data. We systematically investigated the possible factors that can be responsible for the found differences in selected sets. For the Angiotensin-I-converting enzyme dataset, preparation of the bioactive molecules clearly exerted the highest influence on VS performance compared to preparation of the decoys or the target structure. The major contributing factors were different protonation states, molecular flexibility, and differences in the input conformation (particularly for cyclic moieties) of bioactives. In addition, score normalization strategies eliminated the biased docking scores shown by GOLD (ChemPLP) for the larger bioactives and produced a better performance. Generalizing these normalization strategies on the 18 DEKOIS 2.0 sets, improved the performances for the majority of GOLD (ChemPLP) docking, while it showed detrimental performances for the majority of Glide (SP) docking. In conclusion, we exemplify herein possible issues particularly during the preparation stage of molecular data and demonstrate to which extent these issues can cause perturbations in the virtual screening performance. We provide insights into what problems can occur and should be avoided, when generating benchmarks to characterize the virtual screening performance. Particularly, careful selection of an appropriate molecular preparation setup for the bioactive set and the use of score normalization for docking with GOLD (ChemPLP) appear to have a great importance for the screening performance. For virtual screening campaigns, we recommend to invest time and effort into including alternative preparation workflows into the generation of the master library, even at the cost of including multiple representations of each molecule. Graphical AbstractUsing DEKOIS 2.0 benchmark sets in structure-based virtual screening to probe the impact of molecular preparation and score normalization.

Discovery of new erbB4 inhibitors: Repositioning an orphan chemical library by inverse virtual screening.

PubMed

Giordano, Assunta; Forte, Giovanni; Massimo, Luigia; Riccio, Raffaele; Bifulco, Giuseppe; Di Micco, Simone

2018-04-12

Inverse Virtual Screening (IVS) is a docking based approach aimed to the evaluation of the virtual ability of a single compound to interact with a library of proteins. For the first time, we applied this methodology to a library of synthetic compounds, which proved to be inactive towards the target they were initially designed for. Trifluoromethyl-benzenesulfonamides 3-21 were repositioned by means of IVS identifying new lead compounds (14-16, 19 and 20) for the inhibition of erbB4 in the low micromolar range. Among these, compound 20 exhibited an interesting value of IC 50 on MCF7 cell lines, thus validating IVS in lead repurposing. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Simultaneous virtual prediction of anti-Escherichia coli activities and ADMET profiles: A chemoinformatic complementary approach for high-throughput screening.

PubMed

Speck-Planche, Alejandro; Cordeiro, M N D S

2014-02-10

Escherichia coli remains one of the principal pathogens that cause nosocomial infections, medical conditions that are increasingly common in healthcare facilities. E. coli is intrinsically resistant to many antibiotics, and multidrug-resistant strains have emerged recently. Chemoinformatics has been a great ally of experimental methodologies such as high-throughput screening, playing an important role in the discovery of effective antibacterial agents. However, there is no approach that can design safer anti-E. coli agents, because of the multifactorial nature and complexity of bacterial diseases and the lack of desirable ADMET (absorption, distribution, metabolism, elimination, and toxicity) profiles as a major cause of disapproval of drugs. In this work, we introduce the first multitasking model based on quantitative-structure biological effect relationships (mtk-QSBER) for simultaneous virtual prediction of anti-E. coli activities and ADMET properties of drugs and/or chemicals under many experimental conditions. The mtk-QSBER model was developed from a large and heterogeneous data set of more than 37800 cases, exhibiting overall accuracies of >95% in both training and prediction (validation) sets. The utility of our mtk-QSBER model was demonstrated by performing virtual prediction of properties for the investigational drug avarofloxacin (AVX) under 260 different experimental conditions. Results converged with the experimental evidence, confirming the remarkable anti-E. coli activities and safety of AVX. Predictions also showed that our mtk-QSBER model can be a promising computational tool for virtual screening of desirable anti-E. coli agents, and this chemoinformatic approach could be extended to the search for safer drugs with defined pharmacological activities.

Seamless 3D interaction for virtual tables, projection planes, and CAVEs

NASA Astrophysics Data System (ADS)

Encarnacao, L. M.; Bimber, Oliver; Schmalstieg, Dieter; Barton, Robert J., III

2000-08-01

The Virtual Table presents stereoscopic graphics to a user in a workbench-like setting. This device shares with other large- screen display technologies (such as data walls and surround- screen projection systems) the lack of human-centered unencumbered user interfaces and 3D interaction technologies. Such shortcomings present severe limitations to the application of virtual reality (VR) technology to time- critical applications as well as employment scenarios that involve heterogeneous groups of end-users without high levels of computer familiarity and expertise. Traditionally such employment scenarios are common in planning-related application areas such as mission rehearsal and command and control. For these applications, a high grade of flexibility with respect to the system requirements (display and I/O devices) as well as to the ability to seamlessly and intuitively switch between different interaction modalities and interaction are sought. Conventional VR techniques may be insufficient to meet this challenge. This paper presents novel approaches for human-centered interfaces to Virtual Environments focusing on the Virtual Table visual input device. It introduces new paradigms for 3D interaction in virtual environments (VE) for a variety of application areas based on pen-and-clipboard, mirror-in-hand, and magic-lens metaphors, and introduces new concepts for combining VR and augmented reality (AR) techniques. It finally describes approaches toward hybrid and distributed multi-user interaction environments and concludes by hypothesizing on possible use cases for defense applications.

Application of Shape Similarity in Pose Selection and Virtual Screening in CSARdock2014 Exercise.

PubMed

Kumar, Ashutosh; Zhang, Kam Y J

2016-06-27

To evaluate the applicability of shape similarity in docking-based pose selection and virtual screening, we participated in the CSARdock2014 benchmark exercise for identifying the correct docking pose of inhibitors targeting factor XA, spleen tyrosine kinase, and tRNA methyltransferase. This exercise provides a valuable opportunity for researchers to test their docking programs, methods, and protocols in a blind testing environment. In the CSARdock2014 benchmark exercise, we have implemented an approach that uses ligand 3D shape similarity to facilitate docking-based pose selection and virtual screening. We showed here that ligand 3D shape similarity between bound poses could be used to identify the native-like pose from an ensemble of docking-generated poses. Our method correctly identified the native pose as the top-ranking pose for 73% of test cases in a blind testing environment. Moreover, the pose selection results also revealed an excellent correlation between ligand 3D shape similarity scores and RMSD to X-ray crystal structure ligand. In the virtual screening exercise, the average RMSD for our pose prediction was found to be 1.02 Å, and it was one of the top performances achieved in CSARdock2014 benchmark exercise. Furthermore, the inclusion of shape similarity improved virtual screening performance of docking-based scoring and ranking. The coefficient of determination (r(2)) between experimental activities and docking scores for 276 spleen tyrosine kinase inhibitors was found to be 0.365 but reached 0.614 when the ligand 3D shape similarity was included.

Structure Based Virtual Screening Studies to Identify Novel Potential Compounds for GPR142 and Their Relative Dynamic Analysis for Study of Type 2 Diabetes

NASA Astrophysics Data System (ADS)

Kaushik, Aman C.; Kumar, Sanjay; Wei, Dong Q.; Sahi, Shakti

2018-02-01

GPR142 (G protein receptor 142) is a novel orphan GPCR (G protein coupled receptor) belonging to ‘Class A’ of GPCR family and expressed in beta cells of pancreas. In this study, we reported the structure based virtual screening to identify the hit compounds which can be developed as leads for potential agonists. The results were validated through induced fit docking, pharmacophore modeling and system biology approaches. Since, there is no solved crystal structure of GPR142, we attempted to predict the 3D structure followed by validation and then identification of active site using threading and ab initio methods. Also, structure based virtual screening was performed against a total of 1171519 compounds from different libraries and only top 20 best hit compounds were screened and analyzed. Moreover, the biochemical pathway of GPR142 complex with screened compound2 was also designed and compared with experimental data. Interestingly, compound2 showed an increase in insulin production via Gq mediated signaling pathway suggesting the possible role of novel GPR142 agonists in therapy against type 2 diabetes.

ILP-2 modeling and virtual screening of an FDA-approved library:a possible anticancer therapy.

PubMed

Khalili, Saeed; Mohammadpour, Hemn; Shokrollahi Barough, Mahideh; Kokhaei, Parviz

2016-06-23

The members of the inhibitors of apoptosis protein (IAP) family inhibit diverse components of the caspase signaling pathway, notably caspase 3, 7, and 9. ILP-2 (BIRC-8) is the most recently identified member of the IAPs, mainly interacting with caspase 9. This interaction would eventually lead to death resistance in the case of cancerous cells. Therefore, structural modeling of ILP-2 and finding applicable inhibitors of its interaction with caspase 9 are a compelling challenge. Three main protein modeling approaches along with various model refinement measures were harnessed to achieve a reliable 3D model, using state-of-the-art software. Thereafter, the selected model was employed to perform virtual screening of an FDA approved library. A model built by a combinatorial approach (homology and ab initio approaches) was chosen as the best model. Model refinement processes successfully bolstered the model quality. Virtual screening of the compound library introduced several high affinity inhibitor candidates that interact with functional residues of ILP2. Given the 3D structure of the ILP2 molecule, we found promising inhibitory molecules. In addition to high affinity towards the ILP2 molecule, these molecules interact with residues that play pivotal rules in ILP2-caspase interaction. These molecules would inhibit ILP2-caspase interaction and consequently would lead to reactivated cell apoptosis through the caspases pathway.

Virtual gastrointestinal colonoscopy in combination with large bowel endoscopy: Clinical application

PubMed Central

He, Qing; Rao, Ting; Guan, Yong-Song

2014-01-01

Although colorectal cancer (CRC) has no longer been the leading cancer killer worldwide for years with the exponential development in computed tomography (CT) or magnetic resonance imaging, and positron emission tomography/CT as well as virtual colonoscopy for early detection, the CRC related mortality is still high. The objective of CRC screening is to reduce the burden of CRC and thereby the morbidity and mortality rates of the disease. It is believed that this goal can be achieved by regularly screening the average-risk population, enabling the detection of cancer at early, curable stages, and polyps before they become cancerous. Large-scale screening with multimodality imaging approaches plays an important role in reaching that goal to detect polyps, Crohn’s disease, ulcerative colitis and CRC in early stage. This article reviews kinds of presentative imaging procedures for various screening options and updates detecting, staging and re-staging of CRC patients for determining the optimal therapeutic method and forecasting the risk of CRC recurrence and the overall prognosis. The combination use of virtual colonoscopy and conventional endoscopy, advantages and limitations of these modalities are also discussed. PMID:25320519

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.

Free Energy-Based Virtual Screening and Optimization of RNase H Inhibitors of HIV-1 Reverse Transcriptase.

PubMed

Zhang, Baofeng; D'Erasmo, Michael P; Murelli, Ryan P; Gallicchio, Emilio

2016-09-30

We report the results of a binding free energy-based virtual screening campaign of a library of 77 α-hydroxytropolone derivatives against the challenging RNase H active site of the reverse transcriptase (RT) enzyme of human immunodeficiency virus-1. Multiple protonation states, rotamer states, and binding modalities of each compound were individually evaluated. The work involved more than 300 individual absolute alchemical binding free energy parallel molecular dynamics calculations and over 1 million CPU hours on national computing clusters and a local campus computational grid. The thermodynamic and structural measures obtained in this work rationalize a series of characteristics of this system useful for guiding future synthetic and biochemical efforts. The free energy model identified key ligand-dependent entropic and conformational reorganization processes difficult to capture using standard docking and scoring approaches. Binding free energy-based optimization of the lead compounds emerging from the virtual screen has yielded four compounds with very favorable binding properties, which will be the subject of further experimental investigations. This work is one of the few reported applications of advanced-binding free energy models to large-scale virtual screening and optimization projects. It further demonstrates that, with suitable algorithms and automation, advanced-binding free energy models can have a useful role in early-stage drug-discovery programs.

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.

Dockres: a computer program that analyzes the output of virtual screening of small molecules

PubMed Central

2010-01-01

Background This paper describes a computer program named Dockres that is designed to analyze and summarize results of virtual screening of small molecules. The program is supplemented with utilities that support the screening process. Foremost among these utilities are scripts that run the virtual screening of a chemical library on a large number of processors in parallel. Methods Dockres and some of its supporting utilities are written Fortran-77; other utilities are written as C-shell scripts. They support the parallel execution of the screening. The current implementation of the program handles virtual screening with Autodock-3 and Autodock-4, but can be extended to work with the output of other programs. Results Analysis of virtual screening by Dockres led to both active and selective lead compounds. Conclusions Analysis of virtual screening was facilitated and enhanced by Dockres in both the authors' laboratories as well as laboratories elsewhere. PMID:20205801

Screening strategies to identify new chemical diversity for drug development to treat kinetoplastid infections.

PubMed

Don, Rob; Ioset, Jean-Robert

2014-01-01

The Drugs for Neglected Diseases initiative (DNDi) has defined and implemented an early discovery strategy over the last few years, in fitting with its virtual R&D business model. This strategy relies on a medium- to high-throughput phenotypic assay platform to expedite the screening of compound libraries accessed through its collaborations with partners from the pharmaceutical industry. We review the pragmatic approaches used to select compound libraries for screening against kinetoplastids, taking into account screening capacity. The advantages, limitations and current achievements in identifying new quality series for further development into preclinical candidates are critically discussed, together with attractive new approaches currently under investigation.

Discovery of novel inhibitors for DHODH via virtual screening and X-ray crystallographic structures

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

McLean, Larry R.; Zhang, Ying; Degnen, William

2010-10-28

Amino-benzoic acid derivatives 1-4 were found to be inhibitors for DHODH by virtual screening, biochemical, and X-ray crystallographic studies. X-ray structures showed that 1 and 2 bind to DHODH as predicted by virtual screening, but 3 and 4 were found to be structurally different from the corresponding compounds initially identified by virtual screening.

An Unbiased Method To Build Benchmarking Sets for Ligand-Based Virtual Screening and its Application To GPCRs

PubMed Central

2015-01-01

Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods for important drug targets such as G protein-coupled receptors (GPCRs). To date these ready-to-apply data sets for LBVS are fairly limited, and the direct usage of benchmarking sets designed for SBVS could bring the biases to the evaluation of LBVS. Herein, we propose an unbiased method to build benchmarking sets for LBVS and validate it on a multitude of GPCRs targets. To be more specific, our methods can (1) ensure chemical diversity of ligands, (2) maintain the physicochemical similarity between ligands and decoys, (3) make the decoys dissimilar in chemical topology to all ligands to avoid false negatives, and (4) maximize spatial random distribution of ligands and decoys. We evaluated the quality of our Unbiased Ligand Set (ULS) and Unbiased Decoy Set (UDS) using three common LBVS approaches, with Leave-One-Out (LOO) Cross-Validation (CV) and a metric of average AUC of the ROC curves. Our method has greatly reduced the “artificial enrichment” and “analogue bias” of a published GPCRs benchmarking set, i.e., GPCR Ligand Library (GLL)/GPCR Decoy Database (GDD). In addition, we addressed an important issue about the ratio of decoys per ligand and found that for a range of 30 to 100 it does not affect the quality of the benchmarking set, so we kept the original ratio of 39 from the GLL/GDD. PMID:24749745

An unbiased method to build benchmarking sets for ligand-based virtual screening and its application to GPCRs.

PubMed

Xia, Jie; Jin, Hongwei; Liu, Zhenming; Zhang, Liangren; Wang, Xiang Simon

2014-05-27

Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods for important drug targets such as G protein-coupled receptors (GPCRs). To date these ready-to-apply data sets for LBVS are fairly limited, and the direct usage of benchmarking sets designed for SBVS could bring the biases to the evaluation of LBVS. Herein, we propose an unbiased method to build benchmarking sets for LBVS and validate it on a multitude of GPCRs targets. To be more specific, our methods can (1) ensure chemical diversity of ligands, (2) maintain the physicochemical similarity between ligands and decoys, (3) make the decoys dissimilar in chemical topology to all ligands to avoid false negatives, and (4) maximize spatial random distribution of ligands and decoys. We evaluated the quality of our Unbiased Ligand Set (ULS) and Unbiased Decoy Set (UDS) using three common LBVS approaches, with Leave-One-Out (LOO) Cross-Validation (CV) and a metric of average AUC of the ROC curves. Our method has greatly reduced the "artificial enrichment" and "analogue bias" of a published GPCRs benchmarking set, i.e., GPCR Ligand Library (GLL)/GPCR Decoy Database (GDD). In addition, we addressed an important issue about the ratio of decoys per ligand and found that for a range of 30 to 100 it does not affect the quality of the benchmarking set, so we kept the original ratio of 39 from the GLL/GDD.

Structural insights into pharmacophore-assisted in silico identification of protein-protein interaction inhibitors for inhibition of human toll-like receptor 4 - myeloid differentiation factor-2 (hTLR4-MD-2) complex.

PubMed

Mishra, Vinita; Pathak, Chandramani

2018-05-29

Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS-TLR4-MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein-protein interaction (PPI) in TLR4-MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4-MD-2) and dimerization (MD-2-TLR4*) protein-protein interaction interfaces in TLR4-MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4-MD-2 protein-protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4-MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.

Benchmarking methods and data sets for ligand enrichment assessment in virtual screening.

PubMed

Xia, Jie; Tilahun, Ermias Lemma; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon

2015-01-01

Retrospective small-scale virtual screening (VS) based on benchmarking data sets has been widely used to estimate ligand enrichments of VS approaches in the prospective (i.e. real-world) efforts. However, the intrinsic differences of benchmarking sets to the real screening chemical libraries can cause biased assessment. Herein, we summarize the history of benchmarking methods as well as data sets and highlight three main types of biases found in benchmarking sets, i.e. "analogue bias", "artificial enrichment" and "false negative". In addition, we introduce our recent algorithm to build maximum-unbiased benchmarking sets applicable to both ligand-based and structure-based VS approaches, and its implementations to three important human histone deacetylases (HDACs) isoforms, i.e. HDAC1, HDAC6 and HDAC8. The leave-one-out cross-validation (LOO CV) demonstrates that the benchmarking sets built by our algorithm are maximum-unbiased as measured by property matching, ROC curves and AUCs. Copyright © 2014 Elsevier Inc. All rights reserved.

Benchmarking Methods and Data Sets for Ligand Enrichment Assessment in Virtual Screening

PubMed Central

Xia, Jie; Tilahun, Ermias Lemma; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon

2014-01-01

Retrospective small-scale virtual screening (VS) based on benchmarking data sets has been widely used to estimate ligand enrichments of VS approaches in the prospective (i.e. real-world) efforts. However, the intrinsic differences of benchmarking sets to the real screening chemical libraries can cause biased assessment. Herein, we summarize the history of benchmarking methods as well as data sets and highlight three main types of biases found in benchmarking sets, i.e. “analogue bias”, “artificial enrichment” and “false negative”. In addition, we introduced our recent algorithm to build maximum-unbiased benchmarking sets applicable to both ligand-based and structure-based VS approaches, and its implementations to three important human histone deacetylase (HDAC) isoforms, i.e. HDAC1, HDAC6 and HDAC8. The Leave-One-Out Cross-Validation (LOO CV) demonstrates that the benchmarking sets built by our algorithm are maximum-unbiased in terms of property matching, ROC curves and AUCs. PMID:25481478

Virtual screening filters for the design of type II p38 MAP kinase inhibitors: a fragment based library generation approach.

PubMed

Badrinarayan, Preethi; Sastry, G Narahari

2012-04-01

In this work, we introduce the development and application of a three-step scoring and filtering procedure for the design of type II p38 MAP kinase leads using allosteric fragments extracted from virtual screening hits. The design of the virtual screening filters is based on a thorough evaluation of docking methods, DFG-loop conformation, binding interactions and chemotype specificity of the 138 p38 MAP kinase inhibitors from Protein Data Bank bound to DFG-in and DFG-out conformations using Glide, GOLD and CDOCKER. A 40 ns molecular dynamics simulation with the apo, type I with DFG-in and type II with DFG-out forms was carried out to delineate the effects of structural variations on inhibitor binding. The designed docking-score and sub-structure filters were first tested on a dataset of 249 potent p38 MAP kinase inhibitors from seven diverse series and 18,842 kinase inhibitors from PDB, to gauge their capacity to discriminate between kinase and non-kinase inhibitors and likewise to selectively filter-in target-specific inhibitors. The designed filters were then applied in the virtual screening of a database of ten million (10⁷) compounds resulting in the identification of 100 hits. Based on their binding modes, 98 allosteric fragments were extracted from the hits and a fragment library was generated. New type II p38 MAP kinase leads were designed by tailoring the existing type I ATP site binders with allosteric fragments using a common urea linker. Target specific virtual screening filters can thus be easily developed for other kinases based on this strategy to retrieve target selective compounds. Copyright © 2012 Elsevier Inc. All rights reserved.

Automated recycling of chemistry for virtual screening and library design.

PubMed

Vainio, Mikko J; Kogej, Thierry; Raubacher, Florian

2012-07-23

An early stage drug discovery project needs to identify a number of chemically diverse and attractive compounds. These hit compounds are typically found through high-throughput screening campaigns. The diversity of the chemical libraries used in screening is therefore important. In this study, we describe a virtual high-throughput screening system called Virtual Library. The system automatically "recycles" validated synthetic protocols and available starting materials to generate a large number of virtual compound libraries, and allows for fast searches in the generated libraries using a 2D fingerprint based screening method. Virtual Library links the returned virtual hit compounds back to experimental protocols to quickly assess the synthetic accessibility of the hits. The system can be used as an idea generator for library design to enrich the screening collection and to explore the structure-activity landscape around a specific active compound.

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach.

PubMed

Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D; Duvenaud, David; Maclaurin, Dougal; Blood-Forsythe, Martin A; Chae, Hyun Sik; Einzinger, Markus; Ha, Dong-Gwang; Wu, Tony; Markopoulos, Georgios; Jeon, Soonok; Kang, Hosuk; Miyazaki, Hiroshi; Numata, Masaki; Kim, Sunghan; Huang, Wenliang; Hong, Seong Ik; Baldo, Marc; Adams, Ryan P; Aspuru-Guzik, Alán

2016-10-01

Virtual screening is becoming a ground-breaking tool for molecular discovery due to the exponential growth of available computer time and constant improvement of simulation and machine learning techniques. We report an integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing. After exploring a search space of 1.6 million molecules and screening over 400,000 of them using time-dependent density functional theory, we identified thousands of promising novel organic light-emitting diode molecules across the visible spectrum. Our team collaboratively selected the best candidates from this set. The experimentally determined external quantum efficiencies for these synthesized candidates were as large as 22%.

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

NASA Astrophysics Data System (ADS)

Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D.; Duvenaud, David; MacLaurin, Dougal; Blood-Forsythe, Martin A.; Chae, Hyun Sik; Einzinger, Markus; Ha, Dong-Gwang; Wu, Tony; Markopoulos, Georgios; Jeon, Soonok; Kang, Hosuk; Miyazaki, Hiroshi; Numata, Masaki; Kim, Sunghan; Huang, Wenliang; Hong, Seong Ik; Baldo, Marc; Adams, Ryan P.; Aspuru-Guzik, Alán

2016-10-01

Virtual screening is becoming a ground-breaking tool for molecular discovery due to the exponential growth of available computer time and constant improvement of simulation and machine learning techniques. We report an integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing. After exploring a search space of 1.6 million molecules and screening over 400,000 of them using time-dependent density functional theory, we identified thousands of promising novel organic light-emitting diode molecules across the visible spectrum. Our team collaboratively selected the best candidates from this set. The experimentally determined external quantum efficiencies for these synthesized candidates were as large as 22%.

4D Flexible Atom-Pairs: An efficient probabilistic conformational space comparison for ligand-based virtual screening

PubMed Central

2011-01-01

Background The performance of 3D-based virtual screening similarity functions is affected by the applied conformations of compounds. Therefore, the results of 3D approaches are often less robust than 2D approaches. The application of 3D methods on multiple conformer data sets normally reduces this weakness, but entails a significant computational overhead. Therefore, we developed a special conformational space encoding by means of Gaussian mixture models and a similarity function that operates on these models. The application of a model-based encoding allows an efficient comparison of the conformational space of compounds. Results Comparisons of our 4D flexible atom-pair approach with over 15 state-of-the-art 2D- and 3D-based virtual screening similarity functions on the 40 data sets of the Directory of Useful Decoys show a robust performance of our approach. Even 3D-based approaches that operate on multiple conformers yield inferior results. The 4D flexible atom-pair method achieves an averaged AUC value of 0.78 on the filtered Directory of Useful Decoys data sets. The best 2D- and 3D-based approaches of this study yield an AUC value of 0.74 and 0.72, respectively. As a result, the 4D flexible atom-pair approach achieves an average rank of 1.25 with respect to 15 other state-of-the-art similarity functions and four different evaluation metrics. Conclusions Our 4D method yields a robust performance on 40 pharmaceutically relevant targets. The conformational space encoding enables an efficient comparison of the conformational space. Therefore, the weakness of the 3D-based approaches on single conformations is circumvented. With over 100,000 similarity calculations on a single desktop CPU, the utilization of the 4D flexible atom-pair in real-world applications is feasible. PMID:21733172

A ranking method for the concurrent learning of compounds with various activity profiles.

PubMed

Dörr, Alexander; Rosenbaum, Lars; Zell, Andreas

2015-01-01

In this study, we present a SVM-based ranking algorithm for the concurrent learning of compounds with different activity profiles and their varying prioritization. To this end, a specific labeling of each compound was elaborated in order to infer virtual screening models against multiple targets. We compared the method with several state-of-the-art SVM classification techniques that are capable of inferring multi-target screening models on three chemical data sets (cytochrome P450s, dehydrogenases, and a trypsin-like protease data set) containing three different biological targets each. The experiments show that ranking-based algorithms show an increased performance for single- and multi-target virtual screening. Moreover, compounds that do not completely fulfill the desired activity profile are still ranked higher than decoys or compounds with an entirely undesired profile, compared to other multi-target SVM methods. SVM-based ranking methods constitute a valuable approach for virtual screening in multi-target drug design. The utilization of such methods is most helpful when dealing with compounds with various activity profiles and the finding of many ligands with an already perfectly matching activity profile is not to be expected.

GPURFSCREEN: a GPU based virtual screening tool using random forest classifier.

PubMed

Jayaraj, P B; Ajay, Mathias K; Nufail, M; Gopakumar, G; Jaleel, U C A

2016-01-01

In-silico methods are an integral part of modern drug discovery paradigm. Virtual screening, an in-silico method, is used to refine data models and reduce the chemical space on which wet lab experiments need to be performed. Virtual screening of a ligand data model requires large scale computations, making it a highly time consuming task. This process can be speeded up by implementing parallelized algorithms on a Graphical Processing Unit (GPU). Random Forest is a robust classification algorithm that can be employed in the virtual screening. A ligand based virtual screening tool (GPURFSCREEN) that uses random forests on GPU systems has been proposed and evaluated in this paper. This tool produces optimized results at a lower execution time for large bioassay data sets. The quality of results produced by our tool on GPU is same as that on a regular serial environment. Considering the magnitude of data to be screened, the parallelized virtual screening has a significantly lower running time at high throughput. The proposed parallel tool outperforms its serial counterpart by successfully screening billions of molecules in training and prediction phases.

Bayesian Models Leveraging Bioactivity and Cytotoxicity Information for Drug Discovery

PubMed Central

Ekins, Sean; Reynolds, Robert C.; Kim, Hiyun; Koo, Mi-Sun; Ekonomidis, Marilyn; Talaue, Meliza; Paget, Steve D.; Woolhiser, Lisa K.; Lenaerts, Anne J.; Bunin, Barry A.; Connell, Nancy; Freundlich, Joel S.

2013-01-01

SUMMARY Identification of unique leads represents a significant challenge in drug discovery. This hurdle is magnified in neglected diseases such as tuberculosis. We have leveraged public high-throughput screening (HTS) data, to experimentally validate virtual screening approach employing Bayesian models built with bioactivity information (single-event model) as well as bioactivity and cytotoxicity information (dual-event model). We virtually screen a commercial library and experimentally confirm actives with hit rates exceeding typical HTS results by 1-2 orders of magnitude. The first dual-event Bayesian model identified compounds with antitubercular whole-cell activity and low mammalian cell cytotoxicity from a published set of antimalarials. The most potent hit exhibits the in vitro activity and in vitro/in vivo safety profile of a drug lead. These Bayesian models offer significant economies in time and cost to drug discovery. PMID:23521795

Docking and Virtual Screening Strategies for GPCR Drug Discovery.

PubMed

Beuming, Thijs; Lenselink, Bart; Pala, Daniele; McRobb, Fiona; Repasky, Matt; Sherman, Woody

2015-01-01

Progress in structure determination of G protein-coupled receptors (GPCRs) has made it possible to apply structure-based drug design (SBDD) methods to this pharmaceutically important target class. The quality of GPCR structures available for SBDD projects fall on a spectrum ranging from high resolution crystal structures (<2 Å), where all water molecules in the binding pocket are resolved, to lower resolution (>3 Å) where some protein residues are not resolved, and finally to homology models that are built using distantly related templates. Each GPCR project involves a distinct set of opportunities and challenges, and requires different approaches to model the interaction between the receptor and the ligands. In this review we will discuss docking and virtual screening to GPCRs, and highlight several refinement and post-processing steps that can be used to improve the accuracy of these calculations. Several examples are discussed that illustrate specific steps that can be taken to improve upon the docking and virtual screening accuracy. While GPCRs are a unique target class, many of the methods and strategies outlined in this review are general and therefore applicable to other protein families.

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.

Bioturbo similarity searching: combining chemical and biological similarity to discover structurally diverse bioactive molecules.

PubMed

Wassermann, Anne Mai; Lounkine, Eugen; Glick, Meir

2013-03-25

Virtual screening using bioactivity profiles has become an integral part of currently applied hit finding methods in pharmaceutical industry. However, a significant drawback of this approach is that it is only applicable to compounds that have been biologically tested in the past and have sufficient activity annotations for meaningful profile comparisons. Although bioactivity data generated in pharmaceutical institutions are growing on an unprecedented scale, the number of biologically annotated compounds still covers only a minuscule fraction of chemical space. For a newly synthesized compound or an isolated natural product to be biologically characterized across multiple assays, it may take a considerable amount of time. Consequently, this chemical matter will not be included in virtual screening campaigns based on bioactivity profiles. To overcome this problem, we herein introduce bioturbo similarity searching that uses chemical similarity to map molecules without biological annotations into bioactivity space and then searches for biologically similar compounds in this reference system. In benchmark calculations on primary screening data, we demonstrate that our approach generally achieves higher hit rates and identifies structurally more diverse compounds than approaches using chemical information only. Furthermore, our method is able to discover hits with novel modes of inhibition that traditional 2D and 3D similarity approaches are unlikely to discover. Test calculations on a set of natural products reveal the practical utility of the approach for identifying novel and synthetically more accessible chemical matter.

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

Optical engineering challenges of the virtual retinal display

NASA Astrophysics Data System (ADS)

Kollin, Joel S.; Tidwell, Michael R.

1995-08-01

The Virtual Retinal Display (VRD) is a unique approach to developing a high-resolution head- mounted display currently under development at the University of Washington's Human Interface Technology (HIT) Laboratory. Rather than looking at a screen though a magnifier or optical relay system, the viewer of the VRD has a scanned beam of light enter the pupil of the eye and focused to a spot on the retina. This type of optical system is subject to different design constraints than a typical HMD. With the VRD it may be possible to realize higher resolution, greater color saturation, higher brightness and larger field-of-view than a traditional LCD or CRT screen-based system. In this paper the author will present the VRD approach and how it can provide these advantages. Issues to be resolved for the VRD to reach its full potential and some of the solutions developed at the HIT lab will also be discussed.

Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem

PubMed Central

Lim, Hansaim; Gray, Paul; Xie, Lei; Poleksic, Aleksandar

2016-01-01

Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design. PMID:27958331

Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.

PubMed

Lim, Hansaim; Gray, Paul; Xie, Lei; Poleksic, Aleksandar

2016-12-13

Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design.

Shape-Based Virtual Screening with Volumetric Aligned Molecular Shapes

PubMed Central

Koes, David Ryan; Camacho, Carlos J.

2014-01-01

Shape-based virtual screening is an established and effective method for identifying small molecules that are similar in shape and function to a reference ligand. We describe a new method of shape-based virtual screening, volumetric aligned molecular shapes (VAMS). VAMS uses efficient data structures to encode and search molecular shapes. We demonstrate that VAMS is an effective method for shape-based virtual screening and that it can be successfully used as a pre-filter to accelerate more computationally demanding search algorithms. Unique to VAMS is a novel minimum/maximum shape constraint query for precisely specifying the desired molecular shape. Shape constraint searches in VAMS are particularly efficient and millions of shapes can be searched in a fraction of a second. We compare the performance of VAMS with two other shape-based virtual screening algorithms a benchmark of 102 protein targets consisting of more than 32 million molecular shapes and find that VAMS provides a competitive trade-off between run-time performance and virtual screening performance. PMID:25049193

[Chemical databases and virtual screening].

PubMed

Rognan, Didier; Bonnet, Pascal

2014-12-01

A prerequisite to any virtual screening is the definition of compound libraries to be screened. As we describe here, various sources are available. The selection of the proper library is usually project-dependent but at least as important as the screening method itself. This review details the main compound libraries that are available for virtual screening and guide the reader to the best possible selection according to its needs. © 2014 médecine/sciences – Inserm.

Human recombinant beta-secretase immobilized enzyme reactor for fast hits' selection and characterization from a virtual screening library.

PubMed

De Simone, Angela; Mancini, Francesca; Cosconati, Sandro; Marinelli, Luciana; La Pietra, Valeria; Novellino, Ettore; Andrisano, Vincenza

2013-01-25

In the present work, a human recombinant BACE1 immobilized enzyme reactor (hrBACE1-IMER) has been applied for the sensitive fast screening of 38 compounds selected through a virtual screening approach. HrBACE1-IMER was inserted into a liquid chromatograph coupled with a fluorescent detector. A fluorogenic peptide substrate (M-2420), containing the β-secretase site of the Swedish mutation of APP, was injected and cleaved in the on-line HPLC-hrBACE1-IMER system, giving rise to the fluorescent product. The compounds of the library were tested for their ability to inhibit BACE1 in the immobilized format and to reduce the area related to the chromatographic peak of the fluorescent enzymatic product. The results were validated in solution by using two different FRET methods. Due to the efficient virtual screening methodology, more than fifty percent of the selected compounds showed a measurable inhibitory activity. One of the most active compound (a bis-indanone derivative) was characterized in terms of IC(50) and K(i) determination on the hrBACE1-IMER. Thus, the hrBACE1-IMER has been confirmed as a valid tool for the throughput screening of different chemical entities with potency lower than 30μM for the fast hits' selection and for mode of action determination. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Ranking targets in structure-based virtual screening of three-dimensional protein libraries: methods and problems.

PubMed

Kellenberger, Esther; Foata, Nicolas; Rognan, Didier

2008-05-01

Structure-based virtual screening is a promising tool to identify putative targets for a specific ligand. Instead of docking multiple ligands into a single protein cavity, a single ligand is docked in a collection of binding sites. In inverse screening, hits are in fact targets which have been prioritized within the pool of best ranked proteins. The target rate depends on specificity and promiscuity in protein-ligand interactions and, to a considerable extent, on the effectiveness of the scoring function, which still is the Achilles' heel of molecular docking. In the present retrospective study, virtual screening of the sc-PDB target library by GOLD docking was carried out for four compounds (biotin, 4-hydroxy-tamoxifen, 6-hydroxy-1,6-dihydropurine ribonucleoside, and methotrexate) of known sc-PDB targets and, several ranking protocols based on GOLD fitness score and topological molecular interaction fingerprint (IFP) comparison were evaluated. For the four investigated ligands, the fusion of GOLD fitness and two IFP scores allowed the recovery of most targets, including the rare proteins which are not readily suitable for statistical analysis, while significantly filtering out most false positive entries. The current survey suggests that selecting a small number of targets (<20) for experimental evaluation is achievable with a pure structure-based approach.

A combination of 2D similarity search, pharmacophore, and molecular docking techniques for the identification of vascular endothelial growth factor receptor-2 inhibitors.

PubMed

Ai, Guanhua; Tian, Caiping; Deng, Dawei; Fida, Guissi; Chen, Haiyan; Ma, Yuxiang; Ding, Li; Gu, Yueqing

2015-04-01

The human vascular endothelial growth factor receptor-2 (VEGFR-2) has been an attractive target for the inhibition of angiogenesis. In the current study, we used a hybrid protocol of virtual screening methods to retrieve new VEGFR-2 inhibitors from the Zinc-Specs Database (441 574 compounds). The hybrid protocol included the initial screening of candidates by comparing the 2D similarity to five reported top active inhibitors of 13 VEGFR-2 X-ray crystallography structures, followed by the pharmacophore modeling of virtual screening on the basis of receptor-ligand interactions and further narrowing by LibDOCK to obtain the final hits. Two compounds (AN-919/41439526 and AK-968/40939851) with a high libscore were selected as the final hits for a subsequent cell cytotoxicity study. The two compounds screened exerted significant inhibitory effects on the proliferation of cancer cells (U87 and MCF-7). The results indicated that the hybrid procedure is an effective approach for screening specific receptor inhibitors.

DOCKTITE-a highly versatile step-by-step workflow for covalent docking and virtual screening in the molecular operating environment.

PubMed

Scholz, Christoph; Knorr, Sabine; Hamacher, Kay; Schmidt, Boris

2015-02-23

The formation of a covalent bond with the target is essential for a number of successful drugs, yet tools for covalent docking without significant restrictions regarding warhead or receptor classes are rare and limited in use. In this work we present DOCKTITE, a highly versatile workflow for covalent docking in the Molecular Operating Environment (MOE) combining automated warhead screening, nucleophilic side chain attachment, pharmacophore-based docking, and a novel consensus scoring approach. The comprehensive validation study includes pose predictions of 35 protein/ligand complexes which resulted in a mean RMSD of 1.74 Å and a prediction rate of 71.4% with an RMSD below 2 Å, a virtual screening with an area under the curve (AUC) for the receiver operating characteristics (ROC) of 0.81, and a significant correlation between predicted and experimental binding affinities (ρ = 0.806, R(2) = 0.649, p < 0.005).

Improving the accuracy of ultrafast ligand-based screening: incorporating lipophilicity into ElectroShape as an extra dimension.

PubMed

Armstrong, M Stuart; Finn, Paul W; Morris, Garrett M; Richards, W Graham

2011-08-01

In a previous paper, we presented the ElectroShape method, which we used to achieve successful ligand-based virtual screening. It extended classical shape-based methods by applying them to the four-dimensional shape of the molecule where partial charge was used as the fourth dimension to capture electrostatic information. This paper extends the approach by using atomic lipophilicity (alogP) as an additional molecular property and validates it using the improved release 2 of the Directory of Useful Decoys (DUD). When alogP replaced partial charge, the enrichment results were slightly below those of ElectroShape, though still far better than purely shape-based methods. However, when alogP was added as a complement to partial charge, the resulting five-dimensional enrichments shows a clear improvement in performance. This demonstrates the utility of extending the ElectroShape virtual screening method by adding other atom-based descriptors.

SPOT-ligand 2: improving structure-based virtual screening by binding-homology search on an expanded structural template library.

PubMed

Litfin, Thomas; Zhou, Yaoqi; Yang, Yuedong

2017-04-15

The high cost of drug discovery motivates the development of accurate virtual screening tools. Binding-homology, which takes advantage of known protein-ligand binding pairs, has emerged as a powerful discrimination technique. In order to exploit all available binding data, modelled structures of ligand-binding sequences may be used to create an expanded structural binding template library. SPOT-Ligand 2 has demonstrated significantly improved screening performance over its previous version by expanding the template library 15 times over the previous one. It also performed better than or similar to other binding-homology approaches on the DUD and DUD-E benchmarks. The server is available online at http://sparks-lab.org . yaoqi.zhou@griffith.edu.au or yuedong.yang@griffith.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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

Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads

PubMed Central

Reynolds, Christopher R; Muggleton, Stephen H; Sternberg, Michael J E

2015-01-01

The use of virtual screening has become increasingly central to the drug development pipeline, with ligand-based virtual screening used to screen databases of compounds to predict their bioactivity against a target. These databases can only represent a small fraction of chemical space, and this paper describes a method of exploring synthetic space by applying virtual reactions to promising compounds within a database, and generating focussed libraries of predicted derivatives. A ligand-based virtual screening tool Investigational Novel Drug Discovery by Example (INDDEx) is used as the basis for a system of virtual reactions. The use of virtual reactions is estimated to open up a potential space of 1.21×1012 potential molecules. A de novo design algorithm known as Partial Logical-Rule Reactant Selection (PLoRRS) is introduced and incorporated into the INDDEx methodology. PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products. The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016. Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs. PMID:26583052

DEC Ada interface to Screen Management Guidelines (SMG)

NASA Technical Reports Server (NTRS)

Laomanachareon, Somsak; Lekkos, Anthony A.

1986-01-01

DEC's Screen Management Guidelines are the Run-Time Library procedures that perform terminal-independent screen management functions on a VT100-class terminal. These procedures assist users in designing, composing, and keeping track of complex images on a video screen. There are three fundamental elements in the screen management model: the pasteboard, the virtual display, and the virtual keyboard. The pasteboard is like a two-dimensional area on which a user places and manipulates screen displays. The virtual display is a rectangular part of the terminal screen to which a program writes data with procedure calls. The virtual keyboard is a logical structure for input operation associated with a physical keyboard. SMG can be called by all major VAX languages. Through Ada, predefined language Pragmas are used to interface with SMG. These features and elements of SMG are briefly discussed.

Docking and scoring in virtual screening for drug discovery: methods and applications.

PubMed

Kitchen, Douglas B; Decornez, Hélène; Furr, John R; Bajorath, Jürgen

2004-11-01

Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization. Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors. Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches.

Identification of novel antitubulin agents by using a virtual screening approach based on a 7-point pharmacophore model of the tubulin colchi-site.

PubMed

Massarotti, Alberto; Theeramunkong, Sewan; Mesenzani, Ornella; Caldarelli, Antonio; Genazzani, Armando A; Tron, Gian Cesare

2011-12-01

Tubulin inhibition represents an established target in the field of anticancer research, and over the last 20 years, an intensive search for new antimicrotubule agents has occurred. Indeed, in silico models have been presented that might aid the discovery of novel agents. Among these, a 7-point pharmacophore model has been recently proposed. As a formal proof of this model, we carried out a ligand-based virtual screening on the colchicine-binding site. In vitro testing demonstrated that two compounds displayed a cytotoxic profile on neuroblastoma cancer cells (SH-SY5H) and one had an antitubulinic profile. © 2011 John Wiley & Sons A/S.

MOLA: a bootable, self-configuring system for virtual screening using AutoDock4/Vina on computer clusters.

PubMed

Abreu, Rui Mv; Froufe, Hugo Jc; Queiroz, Maria João Rp; Ferreira, Isabel Cfr

2010-10-28

Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters. MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections. MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a potential maximum speed-up of 10x, the parallel algorithm of MOLA performed with a speed-up of 8,64× using AutoDock4 and 8,60× using Vina.

A high-throughput screening approach for the optoelectronic properties of conjugated polymers.

PubMed

Wilbraham, Liam; Berardo, Enrico; Turcani, Lukas; Jelfs, Kim E; Zwijnenburg, Martijn A

2018-06-25

We propose a general high-throughput virtual screening approach for the optical and electronic properties of conjugated polymers. This approach makes use of the recently developed xTB family of low-computational-cost density functional tight-binding methods from Grimme and co-workers, calibrated here to (TD-)DFT data computed for a representative diverse set of (co-)polymers. Parameters drawn from the resulting calibration using a linear model can then be applied to the xTB derived results for new polymers, thus generating near DFT-quality data with orders of magnitude reduction in computational cost. As a result, after an initial computational investment for calibration, this approach can be used to quickly and accurately screen on the order of thousands of polymers for target applications. We also demonstrate that the (opto)electronic properties of the conjugated polymers show only a very minor variation when considering different conformers and that the results of high-throughput screening are therefore expected to be relatively insensitive with respect to the conformer search methodology applied.

PoLi: A Virtual Screening Pipeline Based On Template Pocket And Ligand Similarity

PubMed Central

Roy, Ambrish; Srinivasan, Bharath; Skolnick, Jeffrey

2015-01-01

Often in pharmaceutical research, the goal is to identify small molecules that can interact with and appropriately modify the biological behavior of a new protein target. Unfortunately, most proteins lack both known structures and small molecule binders, prerequisites of many virtual screening, VS, approaches. For such proteins, ligand homology modeling, LHM, that copies ligands from homologous and perhaps evolutionarily distant template proteins, has been shown to be a powerful VS approach to identify possible binding ligands. However, if we want to target a specific pocket for which there is no homologous holo template protein structure, then LHM will not work. To address this issue, in a new pocket based approach, PoLi, we generalize LHM by exploiting the fact that the number of distinct small molecule ligand binding pockets in proteins is small. PoLi identifies similar ligand binding pockets in a holo-template protein library, selectively copies relevant parts of template ligands and uses them for VS. In practice, PoLi is a hybrid structure and ligand based VS algorithm that integrates 2D fingerprint-based and 3D shape-based similarity metrics for improved virtual screening performance. On standard DUD and DUD-E benchmark databases, using modeled receptor structures, PoLi achieves an average enrichment factor of 13.4 and 9.6 respectively, in the top 1% of the screened library. In contrast, traditional docking based VS using AutoDock Vina and homology-based VS using FINDSITEfilt have an average enrichment of 1.6 (3.0) and 9.0 (7.9) on the DUD (DUD-E) sets respectively. Experimental validation of PoLi predictions on dihydrofolate reductase, DHFR, using differential scanning fluorimetry, DSF, identifies multiple ligands with diverse molecular scaffolds, thus demonstrating the advantage of PoLi over current state-of-the-art VS methods. PMID:26225536

Ligand-guided optimization of CXCR4 homology models for virtual screening using a multiple chemotype approach

NASA Astrophysics Data System (ADS)

Neves, Marco A. C.; Simões, Sérgio; Sá e Melo, M. Luisa

2010-12-01

CXCR4 is a G-protein coupled receptor for CXCL12 that plays an important role in human immunodeficiency virus infection, cancer growth and metastasization, immune cell trafficking and WHIM syndrome. In the absence of an X-ray crystal structure, theoretical modeling of the CXCR4 receptor remains an important tool for structure-function analysis and to guide the discovery of new antagonists with potential clinical use. In this study, the combination of experimental data and molecular modeling approaches allowed the development of optimized ligand-receptor models useful for elucidation of the molecular determinants of small molecule binding and functional antagonism. The ligand-guided homology modeling approach used in this study explicitly re-shaped the CXCR4 binding pocket in order to improve discrimination between known CXCR4 antagonists and random decoys. Refinement based on multiple test-sets with small compounds from single chemotypes provided the best early enrichment performance. These results provide an important tool for structure-based drug design and virtual ligand screening of new CXCR4 antagonists.

Discovery of a Small-Molecule Inhibitor of Interleukin 15: Pharmacophore-Based Virtual Screening and Hit Optimization.

PubMed

Quéméner, Agnès; Maillasson, Mike; Arzel, Laurence; Sicard, Benoit; Vomiandry, Romy; Mortier, Erwan; Dubreuil, Didier; Jacques, Yannick; Lebreton, Jacques; Mathé-Allainmat, Monique

2017-07-27

Interleukin (IL)-15 is a pleiotropic cytokine, which is structurally close to IL-2 and shares with it the IL-2 β and γ receptor (R) subunits. By promoting the activation and proliferation of NK, NK-T, and CD8+ T cells, IL-15 plays important roles in innate and adaptative immunity. Moreover, the association of high levels of IL-15 expression with inflammatory and autoimmune diseases has led to the development of various antagonistic approaches targeting IL-15. This study is an original approach aimed at discovering small-molecule inhibitors impeding IL-15/IL-15R interaction. A pharmacophore and docking-based virtual screening of compound libraries led to the selection of 240 high-scoring compounds, 36 of which were found to bind IL-15, to inhibit the binding of IL-15 to the IL-2Rβ chain or the proliferation of IL-15-dependent cells or both. One of them was selected as a hit and optimized by a structure-activity relationship approach, leading to the first small-molecule IL-15 inhibitor with sub-micromolar activity.

A Quantum-Based Similarity Method in Virtual Screening.

PubMed

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

2015-10-02

One of the most widely-used techniques for ligand-based virtual screening is similarity searching. This study adopted the concepts of quantum mechanics to present as state-of-the-art similarity method of molecules inspired from quantum theory. The representation of molecular compounds in mathematical quantum space plays a vital role in the development of quantum-based similarity approach. One of the key concepts of quantum theory is the use of complex numbers. Hence, this study proposed three various techniques to embed and to re-represent the molecular compounds to correspond with complex numbers format. The quantum-based similarity method that developed in this study depending on complex pure Hilbert space of molecules called Standard Quantum-Based (SQB). The recall of retrieved active molecules were at top 1% and top 5%, and significant test is used to evaluate our proposed methods. The MDL drug data report (MDDR), maximum unbiased validation (MUV) and Directory of Useful Decoys (DUD) data sets were used for experiments and were represented by 2D fingerprints. Simulated virtual screening experiment show that the effectiveness of SQB method was significantly increased due to the role of representational power of molecular compounds in complex numbers forms compared to Tanimoto benchmark similarity measure.

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.

Virtual environments for scene of crime reconstruction and analysis

NASA Astrophysics Data System (ADS)

Howard, Toby L. J.; Murta, Alan D.; Gibson, Simon

2000-02-01

This paper describes research conducted in collaboration with Greater Manchester Police (UK), to evalute the utility of Virtual Environments for scene of crime analysis, forensic investigation, and law enforcement briefing and training. We present an illustrated case study of the construction of a high-fidelity virtual environment, intended to match a particular real-life crime scene as closely as possible. We describe and evaluate the combination of several approaches including: the use of the Manchester Scene Description Language for constructing complex geometrical models; the application of a radiosity rendering algorithm with several novel features based on human perceptual consideration; texture extraction from forensic photography; and experiments with interactive walkthroughs and large-screen stereoscopic display of the virtual environment implemented using the MAVERIK system. We also discuss the potential applications of Virtual Environment techniques in the Law Enforcement and Forensic communities.

Protein tyrosine phosphatases: Ligand interaction analysis and optimisation of virtual screening.

PubMed

Ghattas, Mohammad A; Atatreh, Noor; Bichenkova, Elena V; Bryce, Richard A

2014-07-01

Docking-based virtual screening is an established component of structure-based drug discovery. Nevertheless, scoring and ranking of computationally docked ligand libraries still suffer from many false positives. Identifying optimal docking parameters for a target protein prior to virtual screening can improve experimental hit rates. Here, we examine protocols for virtual screening against the important but challenging class of drug target, protein tyrosine phosphatases. In this study, common interaction features were identified from analysis of protein-ligand binding geometries of more than 50 complexed phosphatase crystal structures. It was found that two interactions were consistently formed across all phosphatase inhibitors: (1) a polar contact with the conserved arginine residue, and (2) at least one interaction with the P-loop backbone amide. In order to investigate the significance of these features on phosphatase-ligand binding, a series of seeded virtual screening experiments were conducted on three phosphatase enzymes, PTP1B, Cdc25b and IF2. It was observed that when the conserved arginine and P-loop amide interactions were used as pharmacophoric constraints during docking, enrichment of the virtual screen significantly increased in the three studied phosphatases, by up to a factor of two in some cases. Additionally, the use of such pharmacophoric constraints considerably improved the ability of docking to predict the inhibitor's bound pose, decreasing RMSD to the crystallographic geometry by 43% on average. Constrained docking improved enrichment of screens against both open and closed conformations of PTP1B. Incorporation of an ordered water molecule in PTP1B screening was also found to generally improve enrichment. The knowledge-based computational strategies explored here can potentially inform structure-based design of new phosphatase inhibitors using docking-based virtual screening. Copyright © 2014 Elsevier Inc. All rights reserved.

Low-Cost, Portable, Multi-Wall Virtual Reality

NASA Technical Reports Server (NTRS)

Miller, Samuel A.; Misch, Noah J.; Dalton, Aaron J.

2005-01-01

Virtual reality systems make compelling outreach displays, but some such systems, like the CAVE, have design features that make their use for that purpose inconvenient. In the case of the CAVE, the equipment is difficult to disassemble, transport, and reassemble, and typically CAVEs can only be afforded by large-budget research facilities. We implemented a system like the CAVE that costs less than $30,000, weighs about 500 pounds, and fits into a fifteen-passenger van. A team of six people have unpacked, assembled, and calibrated the system in less than two hours. This cost reduction versus similar virtual-reality systems stems from the unique approach we took to stereoscopic projection. We used an assembly of optical chopper wheels and commodity LCD projectors to create true active stereo at less than a fifth of the cost of comparable active-stereo technologies. The screen and frame design also optimized portability; the frame assembles in minutes with only two fasteners, and both it and the screen pack into small bundles for easy and secure shipment.

Virtual screening methods as tools for drug lead discovery from large chemical libraries.

PubMed

Ma, X H; Zhu, F; Liu, X; Shi, Z; Zhang, J X; Yang, S Y; Wei, Y Q; Chen, Y Z

2012-01-01

Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ~ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.

The BRIGHTEN program: implementation and evaluation of a program to bridge resources of an interdisciplinary geriatric health team via electronic networking.

PubMed

Emery, Erin E; Lapidos, Stan; Eisenstein, Amy R; Ivan, Iulia I; Golden, Robyn L

2012-12-01

To demonstrate the feasibility of the BRIGHTEN Program (Bridging Resources of an Interdisciplinary Geriatric Health Team via Electronic Networking), an interdisciplinary team intervention for assessing and treating older adults for depression in outpatient primary and specialty medical clinics. The BRIGHTEN team collaborates "virtually" to review patient assessment results, develop a treatment plan, and refer to appropriate team members for follow-up care. Older adults in 9 academic medical center clinics and 2 community-based clinics completed screening forms for symptoms of depression and anxiety. Those with positive screens engaged in comprehensive assessment with the BRIGHTEN Program Coordinator; the BRIGHTEN virtual team provided treatment recommendations based on the results of assessment. A collaborative treatment plan was developed with each participant, who was then connected to appropriate services. Two thousand four hundred twenty-two older adults were screened in participating clinics over a 40-month period. Eight hundred fifty-nine older adults screened positive, and 150 elected to enroll in BRIGHTEN. From baseline to 6 months, significant improvements were found in depression symptoms (Geriatric Depression Scale, p < .01) and general mental health (SF-12 Mental Component, p < .01). The BRIGHTEN Program demonstrated that an interdisciplinary virtual team linked with outpatient medical clinics can be an effective, nonthreatening, and seamless approach to enable older adults to access treatment for depression.

3D Pharmacophore-Based Virtual Screening and Docking Approaches toward the Discovery of Novel HPPD Inhibitors.

PubMed

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2017-06-09

p -Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking-based virtual screening were performed to identify novel potential HPPD inhibitors. The complex-based pharmacophore model (CBP) with 0.721 of ROC used for screening compounds showed remarkable ability to retrieve known active ligands from among decoy molecules. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5 (DS 2.5) to discern interactions with key residues at the active site of HPPD. Four compounds with top rankings in the HipHop model and well-known binding model were finally chosen as lead compounds with potential inhibitory effects on the active site of target. The results provided powerful insight into the development of novel HPPD inhibitors herbicides using computational techniques.

A virtual screening method for inhibitory peptides of Angiotensin I-converting enzyme.

PubMed

Wu, Hongxi; Liu, Yalan; Guo, Mingrong; Xie, Jingli; Jiang, XiaMin

2014-09-01

Natural small peptides from foods have been proven to be efficient inhibitors of Angiotensin I-converting enzyme (ACE) for the regulation of blood pressure. The traditional ACE inhibitory peptides screening method is both time consuming and money costing, to the contrary, virtual screening method by computation can break these limitations. We establish a virtual screening method to obtain ACE inhibitory peptides with the help of Libdock module of Discovery Studio 3.5 software. A significant relationship between Libdock score and experimental IC(50) was found, Libdock score = 10.063 log(1/IC(50)) + 68.08 (R(2) = 0.62). The credibility of the relationship was confirmed by testing the coincidence of the estimated log(1/IC(50)) and measured log(1/IC(50)) (IC(50) is 50% inhibitory concentration toward ACE, in μmol/L) of 5 synthetic ACE inhibitory peptides, which was virtual hydrolyzed and screened from a kind of seafood, Phascolosoma esculenta. Accordingly, Libdock method is a valid IC(50) estimation tool and virtual screening method for small ACE inhibitory peptides. © 2014 Institute of Food Technologists®

Guided exploration in virtual environments

NASA Astrophysics Data System (ADS)

Beckhaus, Steffi; Eckel, Gerhard; Strothotte, Thomas

2001-06-01

We describe an application supporting alternating interaction and animation for the purpose of exploration in a surround- screen projection-based virtual reality system. The exploration of an environment is a highly interactive and dynamic process in which the presentation of objects of interest can give the user guidance while exploring the scene. Previous systems for automatic presentation of models or scenes need either cinematographic rules, direct human interaction, framesets or precalculation (e.g. precalculation of paths to a predefined goal). We report on the development of a system that can deal with rapidly changing user interest in objects of a scene or model as well as with dynamic models and changes of the camera position introduced interactively by the user. It is implemented as a potential-field based camera data generating system. In this paper we describe the implementation of our approach in a virtual art museum on the CyberStage, our surround-screen projection-based stereoscopic display. The paradigm of guided exploration is introduced describing the freedom of the user to explore the museum autonomously. At the same time, if requested by the user, guided exploration provides just-in-time navigational support. The user controls this support by specifying the current field of interest in high-level search criteria. We also present an informal user study evaluating this approach.

Adapting Document Similarity Measures for Ligand-Based Virtual Screening.

PubMed

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

2016-04-13

Quantifying the similarity of molecules is considered one of the major tasks in virtual screening. There are many similarity measures that have been proposed for this purpose, some of which have been derived from document and text retrieving areas as most often these similarity methods give good results in document retrieval and can achieve good results in virtual screening. In this work, we propose a similarity measure for ligand-based virtual screening, which has been derived from a text processing similarity measure. It has been adopted to be suitable for virtual screening; we called this proposed measure the Adapted Similarity Measure of Text Processing (ASMTP). For evaluating and testing the proposed ASMTP we conducted several experiments on two different benchmark datasets: the Maximum Unbiased Validation (MUV) and the MDL Drug Data Report (MDDR). The experiments have been conducted by choosing 10 reference structures from each class randomly as queries and evaluate them in the recall of cut-offs at 1% and 5%. The overall obtained results are compared with some similarity methods including the Tanimoto coefficient, which are considered to be the conventional and standard similarity coefficients for fingerprint-based similarity calculations. The achieved results show that the performance of ligand-based virtual screening is better and outperforms the Tanimoto coefficients and other methods.

Teaching Basic Field Skills Using Screen-Based Virtual Reality Landscapes

NASA Astrophysics Data System (ADS)

Houghton, J.; Robinson, A.; Gordon, C.; Lloyd, G. E. E.; Morgan, D. J.

2016-12-01

We are using screen-based virtual reality landscapes, created using the Unity 3D game engine, to augment the training geoscience students receive in preparing for fieldwork. Students explore these landscapes as they would real ones, interacting with virtual outcrops to collect data, determine location, and map the geology. Skills for conducting field geological surveys - collecting, plotting and interpreting data; time management and decision making - are introduced interactively and intuitively. As with real landscapes, the virtual landscapes are open-ended terrains with embedded data. This means the game does not structure student interaction with the information as it is through experience the student learns the best methods to work successfully and efficiently. These virtual landscapes are not replacements for geological fieldwork rather virtual spaces between classroom and field in which to train and reinforcement essential skills. Importantly, these virtual landscapes offer accessible parallel provision for students unable to visit, or fully partake in visiting, the field. The project has received positive feedback from both staff and students. Results show students find it easier to focus on learning these basic field skills in a classroom, rather than field setting, and make the same mistakes as when learning in the field, validating the realistic nature of the virtual experience and providing opportunity to learn from these mistakes. The approach also saves time, and therefore resources, in the field as basic skills are already embedded. 70% of students report increased confidence with how to map boundaries and 80% have found the virtual training a useful experience. We are also developing landscapes based on real places with 3D photogrammetric outcrops, and a virtual urban landscape in which Engineering Geology students can conduct a site investigation. This project is a collaboration between the University of Leeds and Leeds College of Art, UK, and all our virtual landscapes are freely available online at www.see.leeds.ac.uk/virtual-landscapes/.

Bias to experience approaching motion in a three-dimensional virtual environment.

PubMed

Lewis, Clifford F; McBeath, Michael K

2004-01-01

We used two-frame apparent motion in a three-dimensional virtual environment to test whether observers had biases to experience approaching or receding motion in depth. Observers viewed a tunnel of tiles receding in depth, that moved ambiguously either toward or away from them. We found that observers exhibited biases to experience approaching motion. The strengths of the biases were decreased when stimuli pointed away, but size of the display screen had no effect. Tests with diamond-shaped tiles that varied in the degree of pointing asymmetry resulted in a linear trend in which the bias was strongest for stimuli pointing toward the viewer, and weakest for stimuli pointing away. We show that the overall bias to experience approaching motion is consistent with a computational strategy of matching corresponding features between adjacent foreshortened stimuli in consecutive visual frames. We conclude that there are both adaptational and geometric reasons to favor the experience of approaching motion.

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

PubMed

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

Structure Based Library Design (SBLD) for new 1,4-dihydropyrimidine scaffold as simultaneous COX-1/COX-2 and 5-LOX inhibitors.

PubMed

Lokwani, Deepak; Azad, Rajaram; Sarkate, Aniket; Reddanna, Pallu; Shinde, Devanand

2015-08-01

The various scaffolds containing 1,4-dihydropyrimidine ring were designed by considering the environment of the active site of COX-1/COX-2 and 5-LOX enzymes. The structure-based library design approach, including the focused library design (Virtual Combinatorial Library Design) and virtual screening was used to select the 1,4-dihydropyrimidine scaffold for simultaneous inhibition of both enzyme pathways (COX-1/COX-2 and 5-LOX). The virtual library on each 1,4-dihydropyrimidine scaffold was enumerated in two alternative ways. In first way, the chemical reagents at R groups were filtered by docking of scaffold with single position substitution, that is, only at R1, or R2, or R3, … Rn on COX-2 enzyme using Glide XP docking mode. The structures that do not dock well were removed and the library was enumerated with filtered chemical reagents. In second alternative way, the single position docking stage was bypassed, and the entire library was enumerated using all chemical reagents by docking on the COX-2 enzyme. The entire library of approximately 15,629 compounds obtained from both ways after screening for drug like properties, were further screened for their binding affinity against COX-1 and 5-LOX enzymes using Virtual Screening Workflow. Finally, 142 hits were obtained and divided into two groups based on their binding affinity for COX-1/COX-2 and for both enzyme pathways (COX-1/COX-2 and 5-LOX). The ten molecules were selected, synthesized and evaluated for their COX-1, COX-2 and 5-LOX inhibiting activity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pharmacophore based approach to design inhibitors in crustaceans: an insight into the molt inhibition response to the receptor guanylyl cyclase.

PubMed

Shrivastava, Sajal; Princy, S Adline

2014-04-01

The first set of competitive inhibitors of molt inhibiting hormone (MIH) has been developed using the effective approaches such as Hip-Hop, virtual screening and manual alterations. Moreover, the conserved residues at 71 and 72 positions in the molt inhibiting hormone is known to be significant for selective inhibition of ecdysteroidogenesis; thus, the information from mutation and solution structure were used to generate common pharmacophore features. The geometry of the final six-feature pharmacophore was also found to be consistent with the homology-modeled MIH structures from various other decapod crustaceans. The Hypo-1, comprising six features hypothesis was carefully selected as a best pharmacophore model for virtual screening created on the basis of rank score and cluster processes. The hypothesis was validated and the database was virtually screened using this 3D query and the compounds were then manually altered to enhance the fit value. The hits obtained were further filtered for drug-likeness, which is expressed as physicochemical properties that contribute to favorable ADME/Tox profiles to eliminate the molecules exhibit toxicity and poor pharmacokinetics. In conclusion, the higher fit values of CI-1 (4.6), CI-4 (4.9) and CI-7 (4.2) in conjunction with better pharmacokinetic profile made these molecules practically helpful tool to increase production by accelerating molt in crustaceans. The use of feeding sub-therapeutic dosages of these growth enhancers can be very effectively implemented and certainly turn out to be a vital part of emerging nutritional strategies for economically important crustacean livestock.

An Integrated In Silico Method to Discover Novel Rock1 Inhibitors: Multi- Complex-Based Pharmacophore, Molecular Dynamics Simulation and Hybrid Protocol Virtual Screening.

PubMed

Chen, Haining; Li, Sijia; Hu, Yajiao; Chen, Guo; Jiang, Qinglin; Tong, Rongsheng; Zang, Zhihe; Cai, Lulu

2016-01-01

Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) is an important regulator of focal adhesion, actomyosin contraction and cell motility. In this manuscript, a combination of the multi-complex-based pharmacophore (MCBP), molecular dynamics simulation and a hybrid protocol of a virtual screening method, comprised of multipharmacophore- based virtual screening (PBVS) and ensemble docking-based virtual screening (DBVS) methods were used for retrieving novel ROCK1 inhibitors from the natural products database embedded in the ZINC database. Ten hit compounds were selected from the hit compounds, and five compounds were tested experimentally. Thus, these results may provide valuable information for further discovery of more novel ROCK1 inhibitors.

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach

PubMed Central

Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets–Maximum Unbiased Validation Dataset–which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6. PMID:29652912

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

Markidis, S.; Rizwan, U.

The use of virtual nuclear control room can be an effective and powerful tool for training personnel working in the nuclear power plants. Operators could experience and simulate the functioning of the plant, even in critical situations, without being in a real power plant or running any risk. 3D models can be exported to Virtual Reality formats and then displayed in the Virtual Reality environment providing an immersive 3D experience. However, two major limitations of this approach are that 3D models exhibit static textures, and they are not fully interactive and therefore cannot be used effectively in training personnel. Inmore » this paper we first describe a possible solution for embedding the output of a computer application in a 3D virtual scene, coupling real-world applications and VR systems. The VR system reported here grabs the output of an application running on an X server; creates a texture with the output and then displays it on a screen or a wall in the virtual reality environment. We then propose a simple model for providing interaction between the user in the VR system and the running simulator. This approach is based on the use of internet-based application that can be commanded by a laptop or tablet-pc added to the virtual environment. (authors)« less

Integration of Lead Discovery Tactics and the Evolution of the Lead Discovery Toolbox.

PubMed

Leveridge, Melanie; Chung, Chun-Wa; Gross, Jeffrey W; Phelps, Christopher B; Green, Darren

2018-06-01

There has been much debate around the success rates of various screening strategies to identify starting points for drug discovery. Although high-throughput target-based and phenotypic screening has been the focus of this debate, techniques such as fragment screening, virtual screening, and DNA-encoded library screening are also increasingly reported as a source of new chemical equity. Here, we provide examples in which integration of more than one screening approach has improved the campaign outcome and discuss how strengths and weaknesses of various methods can be used to build a complementary toolbox of approaches, giving researchers the greatest probability of successfully identifying leads. Among others, we highlight case studies for receptor-interacting serine/threonine-protein kinase 1 and the bromo- and extra-terminal domain family of bromodomains. In each example, the unique insight or chemistries individual approaches provided are described, emphasizing the synergy of information obtained from the various tactics employed and the particular question each tactic was employed to answer. We conclude with a short prospective discussing how screening strategies are evolving, what this screening toolbox might look like in the future, how to maximize success through integration of multiple tactics, and scenarios that drive selection of one combination of tactics over another.

Inhibitors of Helicobacter pylori Protease HtrA Found by ‘Virtual Ligand’ Screening Combat Bacterial Invasion of Epithelia

PubMed Central

Schneider, Petra; Hoy, Benjamin; Wessler, Silja; Schneider, Gisbert

2011-01-01

Background The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention. Methodology/Principal Findings We present a method for structure-based virtual screening that is based on the comprehensive prediction of ligand binding sites on a protein model and automated construction of a ligand-receptor interaction map. Pharmacophoric features of the map are clustered and transformed in a correlation vector (‘virtual ligand’) for rapid virtual screening of compound databases. This computer-based technique was validated for 18 different targets of pharmaceutical interest in a retrospective screening experiment. Prospective screening for inhibitory agents was performed for the protease HtrA from the human pathogen H. pylori using a homology model of the target protein. Among 22 tested compounds six block E-cadherin cleavage by HtrA in vitro and result in reduced scattering and wound healing of gastric epithelial cells, thereby preventing bacterial infiltration of the epithelium. Conclusions/Significance This study demonstrates that receptor-based virtual screening with a permissive (‘fuzzy’) pharmacophore model can help identify small bioactive agents for combating bacterial infection. PMID:21483848

Scaffold-Focused Virtual Screening: Prospective Application to the Discovery of TTK Inhibitors

PubMed Central

2013-01-01

We describe and apply a scaffold-focused virtual screen based upon scaffold trees to the mitotic kinase TTK (MPS1). Using level 1 of the scaffold tree, we perform both 2D and 3D similarity searches between a query scaffold and a level 1 scaffold library derived from a 2 million compound library; 98 compounds from 27 unique top-ranked level 1 scaffolds are selected for biochemical screening. We show that this scaffold-focused virtual screen prospectively identifies eight confirmed active compounds that are structurally differentiated from the query compound. In comparison, 100 compounds were selected for biochemical screening using a virtual screen based upon whole molecule similarity resulting in 12 confirmed active compounds that are structurally similar to the query compound. We elucidated the binding mode for four of the eight confirmed scaffold hops to TTK by determining their protein–ligand crystal structures; each represents a ligand-efficient scaffold for inhibitor design. PMID:23672464

Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets.

PubMed

Feinstein, Wei P; Brylinski, Michal

2015-01-01

Computational approaches have emerged as an instrumental methodology in modern research. For example, virtual screening by molecular docking is routinely used in computer-aided drug discovery. One of the critical parameters for ligand docking is the size of a search space used to identify low-energy binding poses of drug candidates. Currently available docking packages often come with a default protocol for calculating the box size, however, many of these procedures have not been systematically evaluated. In this study, we investigate how the docking accuracy of AutoDock Vina is affected by the selection of a search space. We propose a new procedure for calculating the optimal docking box size that maximizes the accuracy of binding pose prediction against a non-redundant and representative dataset of 3,659 protein-ligand complexes selected from the Protein Data Bank. Subsequently, we use the Directory of Useful Decoys, Enhanced to demonstrate that the optimized docking box size also yields an improved ranking in virtual screening. Binding pockets in both datasets are derived from the experimental complex structures and, additionally, predicted by eFindSite. A systematic analysis of ligand binding poses generated by AutoDock Vina shows that the highest accuracy is achieved when the dimensions of the search space are 2.9 times larger than the radius of gyration of a docking compound. Subsequent virtual screening benchmarks demonstrate that this optimized docking box size also improves compound ranking. For instance, using predicted ligand binding sites, the average enrichment factor calculated for the top 1 % (10 %) of the screening library is 8.20 (3.28) for the optimized protocol, compared to 7.67 (3.19) for the default procedure. Depending on the evaluation metric, the optimal docking box size gives better ranking in virtual screening for about two-thirds of target proteins. This fully automated procedure can be used to optimize docking protocols in order to improve the ranking accuracy in production virtual screening simulations. Importantly, the optimized search space systematically yields better results than the default method not only for experimental pockets, but also for those predicted from protein structures. A script for calculating the optimal docking box size is freely available at www.brylinski.org/content/docking-box-size. Graphical AbstractWe developed a procedure to optimize the box size in molecular docking calculations. Left panel shows the predicted binding pose of NADP (green sticks) compared to the experimental complex structure of human aldose reductase (blue sticks) using a default protocol. Right panel shows the docking accuracy using an optimized box size.

Scoring ligand similarity in structure-based virtual screening.

PubMed

Zavodszky, Maria I; Rohatgi, Anjali; Van Voorst, Jeffrey R; Yan, Honggao; Kuhn, Leslie A

2009-01-01

Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds. (c) 2009 John Wiley & Sons, Ltd.

How to Achieve Better Results Using Pass-Based Virtual Screening: Case Study for Kinase Inhibitors

NASA Astrophysics Data System (ADS)

Pogodin, Pavel V.; Lagunin, Alexey A.; Rudik, Anastasia V.; Filimonov, Dmitry A.; Druzhilovskiy, Dmitry S.; Nicklaus, Mark C.; Poroikov, Vladimir V.

2018-04-01

Discovery of new pharmaceutical substances is currently boosted by the possibility of utilization of the Synthetically Accessible Virtual Inventory (SAVI) library, which includes about 283 million molecules, each annotated with a proposed synthetic one-step route from commercially available starting materials. The SAVI database is well-suited for ligand-based methods of virtual screening to select molecules for experimental testing. In this study, we compare the performance of three approaches for the analysis of structure-activity relationships that differ in their criteria for selecting of “active” and “inactive” compounds included in the training sets. PASS (Prediction of Activity Spectra for Substances), which is based on a modified Naïve Bayes algorithm, was applied since it had been shown to be robust and to provide good predictions of many biological activities based on just the structural formula of a compound even if the information in the training set is incomplete. We used different subsets of kinase inhibitors for this case study because many data are currently available on this important class of drug-like molecules. Based on the subsets of kinase inhibitors extracted from the ChEMBL 20 database we performed the PASS training, and then applied the model to ChEMBL 23 compounds not yet present in ChEMBL 20 to identify novel kinase inhibitors. As one may expect, the best prediction accuracy was obtained if only the experimentally confirmed active and inactive compounds for distinct kinases in the training procedure were used. However, for some kinases, reasonable results were obtained even if we used merged training sets, in which we designated as inactives the compounds not tested against the particular kinase. Thus, depending on the availability of data for a particular biological activity, one may choose the first or the second approach for creating ligand-based computational tools to achieve the best possible results in virtual screening.

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.

Position specific interaction dependent scoring technique for virtual screening based on weighted protein--ligand interaction fingerprint profiles.

PubMed

Nandigam, Ravi K; Kim, Sangtae; Singh, Juswinder; Chuaqui, Claudio

2009-05-01

The desire to exploit structural information to aid structure based design and virtual screening led to the development of the interaction fingerprint for analyzing, mining, and filtering the binding patterns underlying the complex 3D data. In this paper we introduce a new approach, weighted SIFt (or w-SIFt), extending the concept of SIFt to capture the relative importance of different binding interactions. The methodology presented here for determining the weights in w-SIFt involves utilizing a dimensionality reduction technique for eliminating linear redundancies in the data followed by a stochastic optimization. We find that the relative weights of the fingerprint bits provide insight into what interactions are critical in determining inhibitor potency. Moreover, the weighted interaction fingerprint can serve as an interpretable position dependent scoring function for ligand protein interactions.

Novel colchicine-site binders with a cyclohexanedione scaffold identified through a ligand-based virtual screening approach.

PubMed

Canela, María-Dolores; Pérez-Pérez, María-Jesús; Noppen, Sam; Sáez-Calvo, Gonzalo; Díaz, J Fernando; Camarasa, María-José; Liekens, Sandra; Priego, Eva-María

2014-05-22

Vascular disrupting agents (VDAs) constitute an innovative anticancer therapy that targets the tumor endothelium, leading to tumor necrosis. Our approach for the identification of new VDAs has relied on a ligand 3-D shape similarity virtual screening (VS) approach using the ROCS program as the VS tool and as query colchicine and TN-16, which both bind the α,β-tubulin dimer. One of the hits identified, using TN-16 as query, has been explored by the synthesis of its structural analogues, leading to 2-(1-((2-methoxyphenyl)amino)ethylidene)-5-phenylcyclohexane-1,3-dione (compound 16c) with an IC50 = 0.09 ± 0.01 μM in HMEC-1 and BAEC, being 100-fold more potent than the initial hit. Compound 16c caused cell cycle arrest in the G2/M phase and interacted with the colchicine-binding site in tubulin, as confirmed by a competition assay with N,N'-ethylenebis(iodoacetamide) and by fluorescence spectroscopy. Moreover, 16c destroyed an established endothelial tubular network at 1 μM and inhibited the migration and invasion of human breast carcinoma cells at 0.4 μM. In conclusion, our approach has led to a new chemotype of promising antiproliferative compounds with antimitotic and potential VDA properties.

Customizing G Protein-coupled receptor models for structure-based virtual screening.

PubMed

de Graaf, Chris; Rognan, Didier

2009-01-01

This review will focus on the construction, refinement, and validation of G Protein-coupled receptor models for the purpose of structure-based virtual screening. Practical tips and tricks derived from concrete modeling and virtual screening exercises to overcome the problems and pitfalls associated with the different steps of the receptor modeling workflow will be presented. These examples will not only include rhodopsin-like (class A), but also secretine-like (class B), and glutamate-like (class C) receptors. In addition, the review will present a careful comparative analysis of current crystal structures and their implication on homology modeling. The following themes will be discussed: i) the use of experimental anchors in guiding the modeling procedure; ii) amino acid sequence alignments; iii) ligand binding mode accommodation and binding cavity expansion; iv) proline-induced kinks in transmembrane helices; v) binding mode prediction and virtual screening by receptor-ligand interaction fingerprint scoring; vi) extracellular loop modeling; vii) virtual filtering schemes. Finally, an overview of several successful structure-based screening shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands.

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment.

PubMed

Minovski, Nikola; Perdih, Andrej; Solmajer, Tom

2012-05-01

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.

Stereo 3D vision adapter using commercial DIY goods

NASA Astrophysics Data System (ADS)

Sakamoto, Kunio; Ohara, Takashi

2009-10-01

The conventional display can show only one screen, but it is impossible to enlarge the size of a screen, for example twice. Meanwhile the mirror supplies us with the same image but this mirror image is usually upside down. Assume that the images on an original screen and a virtual screen in the mirror are completely different and both images can be displayed independently. It would be possible to enlarge a screen area twice. This extension method enables the observers to show the virtual image plane and to enlarge a screen area twice. Although the displaying region is doubled, this virtual display could not produce 3D images. In this paper, we present an extension method using a unidirectional diffusing image screen and an improvement for displaying a 3D image using orthogonal polarized image projection.

From genome to drug lead: identification of a small-molecule inhibitor of the SARS virus.

PubMed

Dooley, Andrea J; Shindo, Nice; Taggart, Barbara; Park, Jewn-Giew; Pang, Yuan-Ping

2006-02-15

Virtual screening, a fast, computational approach to identify drug leads [Perola, E.; Xu, K.; Kollmeyer, T. M.; Kaufmann, S. H.; Prendergast, F. G. J. Med. Chem.2000, 43, 401; Miller, M. A. Nat. Rev. Drug Disc.2002, 1 220], is limited by a known challenge in crystallographically determining flexible regions of proteins. This approach has not been able to identify active inhibitors of the severe acute respiratory syndrome-associated coronavirus (SARS-CoV) using solely the crystal structures of a SARS-CoV cysteine proteinase with a flexible loop in the active site [Yang, H. T.; Yang, M. J.; Ding, Y.; Liu, Y. W.; Lou, Z. Y. Proc. Natl. Acad. Sci. U.S.A.2003, 100, 13190; Jenwitheesuk, E.; Samudrala, R. Bioorg. Med. Chem. Lett.2003, 13, 3989; Rajnarayanan, R. V.; Dakshanamurthy, S.; Pattabiraman, N. Biochem. Biophys. Res. Commun.2004, 321, 370; Du, Q.; Wang, S.; Wei, D.; Sirois, S.; Chou, K. Anal. Biochem.2005, 337, 262; Du, Q.; Wang, S.; Zhu, Y.; Wei, D.; Guo, H. Peptides2004, 25, 1857; Lee, V.; Wittayanarakul, K.; Remsungenen, T.; Parasuk, V.; Sompornpisut, P. Science (Asia)2003, 29, 181; Toney, J.; Navas-Martin, S.; Weiss, S.; Koeller, A. J. Med. Chem.2004, 47, 1079; Zhang, X. W.; Yap, Y. L. Bioorg. Med. Chem.2004, 12, 2517]. This article demonstrates a genome-to-drug-lead approach that uses terascale computing to model flexible regions of proteins, thus permitting the utilization of genetic information to identify drug leads expeditiously. A small-molecule inhibitor of SARS-CoV, exhibiting an effective concentration (EC50) of 23 microM in cell-based assays, was identified through virtual screening against a computer-predicted model of the cysteine proteinase. Screening against two crystal structures of the same proteinase failed to identify the 23-microM inhibitor. This study suggests that terascale computing can complement crystallography, broaden the scope of virtual screening, and accelerate the development of therapeutics to treat emerging infectious diseases such as SARS and Bird Flu.

Virtual screening of inorganic materials synthesis parameters with deep learning

NASA Astrophysics Data System (ADS)

Kim, Edward; Huang, Kevin; Jegelka, Stefanie; Olivetti, Elsa

2017-12-01

Virtual materials screening approaches have proliferated in the past decade, driven by rapid advances in first-principles computational techniques, and machine-learning algorithms. By comparison, computationally driven materials synthesis screening is still in its infancy, and is mired by the challenges of data sparsity and data scarcity: Synthesis routes exist in a sparse, high-dimensional parameter space that is difficult to optimize over directly, and, for some materials of interest, only scarce volumes of literature-reported syntheses are available. In this article, we present a framework for suggesting quantitative synthesis parameters and potential driving factors for synthesis outcomes. We use a variational autoencoder to compress sparse synthesis representations into a lower dimensional space, which is found to improve the performance of machine-learning tasks. To realize this screening framework even in cases where there are few literature data, we devise a novel data augmentation methodology that incorporates literature synthesis data from related materials systems. We apply this variational autoencoder framework to generate potential SrTiO3 synthesis parameter sets, propose driving factors for brookite TiO2 formation, and identify correlations between alkali-ion intercalation and MnO2 polymorph selection.

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.

Effective virtual screening protocol for CYP2C9 ligands using a screening site constructed from flurbiprofen and S-warfarin pockets

NASA Astrophysics Data System (ADS)

Polgár, Tímea; Menyhárd, Dóra K.; Keserű, György M.

2007-09-01

An effective virtual screening protocol was developed against an extended active site of CYP2C9, which was derived from X-ray structures complexed with flubiprofen and S-warfarin. Virtual screening has been effectively supported by our structure-based pharmacophore model. Importance of hot residues identified by mutation data and structural analysis was first estimated in an enrichment study. Key role of Arg108 and Phe114 in ligand binding was also underlined. Our screening protocol successfully identified 76% of known CYP2C9 ligands in the top 1% of the ranked database resulting 76-fold enrichment relative to random situation. Relevance of the protocol was further confirmed in selectivity studies, when 89% of CYP2C9 ligands were retrieved from a mixture of CYP2C9 and CYP2C8 ligands, while only 22% of CYP2C8 ligands were found applying the structure-based pharmacophore constraints. Moderate discrimination of CYP2C9 ligands from CYP2C18 and CYP2C19 ligands could also be achieved extending the application domain of our virtual screening protocol for the entire CYP2C family. Our findings further demonstrate the existence of an active site comprising of at least two binding pockets and strengthens the need of involvement of protein flexibility in virtual screening.

Sense of presence and anxiety during virtual social interactions between a human and virtual humans.

PubMed

Morina, Nexhmedin; Brinkman, Willem-Paul; Hartanto, Dwi; Emmelkamp, Paul M G

2014-01-01

Virtual reality exposure therapy (VRET) has been shown to be effective in treatment of anxiety disorders. Yet, there is lack of research on the extent to which interaction between the individual and virtual humans can be successfully implanted to increase levels of anxiety for therapeutic purposes. This proof-of-concept pilot study aimed at examining levels of the sense of presence and anxiety during exposure to virtual environments involving social interaction with virtual humans and using different virtual reality displays. A non-clinical sample of 38 participants was randomly assigned to either a head-mounted display (HMD) with motion tracker and sterescopic view condition or a one-screen projection-based virtual reality display condition. Participants in both conditions engaged in free speech dialogues with virtual humans controlled by research assistants. It was hypothesized that exposure to virtual social interactions will elicit moderate levels of sense of presence and anxiety in both groups. Further it was expected that participants in the HMD condition will report higher scores of sense of presence and anxiety than participants in the one-screen projection-based display condition. Results revealed that in both conditions virtual social interactions were associated with moderate levels of sense of presence and anxiety. Additionally, participants in the HMD condition reported significantly higher levels of presence than those in the one-screen projection-based display condition (p = .001). However, contrary to the expectations neither the average level of anxiety nor the highest level of anxiety during exposure to social virtual environments differed between the groups (p = .97 and p = .75, respectively). The findings suggest that virtual social interactions can be successfully applied in VRET to enhance sense of presence and anxiety. Furthermore, our results indicate that one-screen projection-based displays can successfully activate levels of anxiety in social virtual environments. The outcome can prove helpful in using low-cost projection-based virtual reality environments for treating individuals with social phobia.

1001 Ways to run AutoDock Vina for virtual screening

NASA Astrophysics Data System (ADS)

Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D.

2016-03-01

Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

1001 Ways to run AutoDock Vina for virtual screening.

PubMed

Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D

2016-03-01

Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

Colon cancer screening

MedlinePlus

Screening for colon cancer; Colonoscopy - screening; Sigmoidoscopy - screening; Virtual colonoscopy - screening; Fecal immunochemical test; Stool DNA test; sDNA test; Colorectal cancer - screening; Rectal ...

Graph wavelet alignment kernels for drug virtual screening.

PubMed

Smalter, Aaron; Huan, Jun; Lushington, Gerald

2009-06-01

In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art chemical classification approaches. In addition, our results also show that the use of wavelet functions significantly decreases the computational costs for graph kernel computation with more than ten fold speedup.

Accessible high-throughput virtual screening molecular docking software for students and educators.

PubMed

Jacob, Reed B; Andersen, Tim; McDougal, Owen M

2012-05-01

We survey low cost high-throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms.

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.

What do we know and when do we know it?

NASA Astrophysics Data System (ADS)

Nicholls, Anthony

2008-03-01

Two essential aspects of virtual screening are considered: experimental design and performance metrics. In the design of any retrospective virtual screen, choices have to be made as to the purpose of the exercise. Is the goal to compare methods? Is the interest in a particular type of target or all targets? Are we simulating a `real-world' setting, or teasing out distinguishing features of a method? What are the confidence limits for the results? What should be reported in a publication? In particular, what criteria should be used to decide between different performance metrics? Comparing the field of molecular modeling to other endeavors, such as medical statistics, criminology, or computer hardware evaluation indicates some clear directions. Taken together these suggest the modeling field has a long way to go to provide effective assessment of its approaches, either to itself or to a broader audience, but that there are no technical reasons why progress cannot be made.

Application of virtual screening and molecular dynamics for the analysis of selectivity of inhibitors of HU proteins targeted to the DNA-recognition site

NASA Astrophysics Data System (ADS)

Talyzina, A. A.; Agapova, Yu. K.; Podshivalov, D. D.; Timofeev, V. I.; Sidorov-Biryukov, D. D.; Rakitina, T. V.

2017-11-01

DNA-Binding HU proteins are essential for the maintenance of genomic DNA supercoiling and compaction in prokaryotic cells and are promising pharmacological targets for the design of new antibacterial agents. The virtual screening for low-molecular-weight compounds capable of specifically interacting with the DNA-recognition loop of the HU protein from the mycoplasma Spiroplasma melliferum was performed. The ability of the initially selected ligands to form stable complexes with the protein target was assessed by molecular dynamics simulation. One compound, which forms an unstable complex, was eliminated by means of a combination of computational methods, resulting in a decrease in the number of compounds that will pass to the experimental test phase. This approach can be used to solve a wide range of problems related to the search for and validation of low-molecular-weight inhibitors specific for a particular protein target.

Target specific proteochemometric model development for BACE1 - protein flexibility and structural water are critical in virtual screening.

PubMed

Manoharan, Prabu; Chennoju, Kiranmai; Ghoshal, Nanda

2015-07-01

BACE1 is an attractive target in Alzheimer's disease (AD) treatment. A rational drug design effort for the inhibition of BACE1 is actively pursued by researchers in both academic and pharmaceutical industries. This continued effort led to the steady accumulation of BACE1 crystal structures, co-complexed with different classes of inhibitors. This wealth of information is used in this study to develop target specific proteochemometric models and these models are exploited for predicting the prospective BACE1 inhibitors. The models developed in this study have performed excellently in predicting the computationally generated poses, separately obtained from single and ensemble docking approaches. The simple protein-ligand contact (SPLC) model outperforms other sophisticated high end models, in virtual screening performance, developed during this study. In an attempt to account for BACE1 protein active site flexibility information in predictive models, we included the change in the area of solvent accessible surface and the change in the volume of solvent accessible surface in our models. The ensemble and single receptor docking results obtained from this study indicate that the structural water mediated interactions improve the virtual screening results. Also, these waters are essential for recapitulating bioactive conformation during docking study. The proteochemometric models developed in this study can be used for the prediction of BACE1 inhibitors, during the early stage of AD drug discovery.

Rational approach to identify newer caspase-1 inhibitors using pharmacophore based virtual screening, docking and molecular dynamic simulation studies.

PubMed

Patel, Shivani; Modi, Palmi; Chhabria, Mahesh

2018-05-01

Caspase-1 is a key endoprotease responsible for the post-translational processing of pro-inflammatory cytokines IL-1β, 18 & 33. Excessive secretion of IL-1β leads to numerous inflammatory and autoimmune diseases. Thus caspase-1 inhibition would be considered as an important therapeutic strategy for development of newer anti-inflammatory agents. Here we have employed an integrated virtual screening by combining pharmacophore mapping and docking to identify small molecules as caspase-1 inhibitors. The ligand based 3D pharmacophore model was generated having the essential structural features of (HBA, HY & RA) using a data set of 27 compounds. A validated pharmacophore hypothesis (Hypo 1) was used to screen ZINC and Minimaybridge chemical databases. The retrieved virtual hits were filtered by ADMET properties and molecular docking analysis. Subsequently, the cross-docking study was also carried out using crystal structure of caspase-1, 3, 7 and 8 to identify the key residual interaction for specific caspase-1 inhibition. Finally, the best mapped and top scored (ZINC00885612, ZINC72003647, BTB04175 and BTB04410) molecules were subjected to molecular dynamics simulation for accessing the dynamic structure of protein after ligand binding. This study identifies the most promising hits, which can be leads for the development of novel caspase-1 inhibitors as anti-inflammatory agents. Copyright © 2018 Elsevier Inc. All rights reserved.

Virtual screening on an α-helix to β-strand switchable region of the FGFR2 extracellular domain revealed positive and negative modulators.

PubMed

Diaz, Constantino; Corentin, Herbert; Thierry, Vermat; Chantal, Alcouffe; Tanguy, Bozec; David, Sibrac; Jean-Marc, Herbert; Pascual, Ferrara; Françoise, Bono; Edgardo, Ferran

2014-11-01

The secondary structure of some protein segments may vary between α-helix and β-strand. To predict these switchable segments, we have developed an algorithm, Switch-P, based solely on the protein sequence. This algorithm was used on the extracellular parts of FGF receptors. For FGFR2, it predicted that β4 and β5 strands of the third Ig-like domain were highly switchable. These two strands possess a high number of somatic mutations associated with cancer. Analysis of PDB structures of FGF receptors confirmed the switchability prediction for β5. We thus evaluated if compound-driven α-helix/β-strand switching of β5 could modulate FGFR2 signaling. We performed the virtual screening of a library containing 1.4 million of chemical compounds with two models of the third Ig-like domain of FGFR2 showing different secondary structures for β5, and we selected 32 compounds. Experimental testing using proliferation assays with FGF7-stimulated SNU-16 cells and a FGFR2-dependent Erk1/2 phosphorylation assay with FGFR2-transfected L6 cells, revealed activators and inhibitors of FGFR2. Our method for the identification of switchable proteinic regions, associated with our virtual screening approach, provides an opportunity to discover new generation of drugs with under-explored mechanism of action. © 2014 Wiley Periodicals, Inc.

Structure-Based Virtual Screening and Biochemical Evaluation for the Identification of Novel Trypanosoma Brucei Aldolase Inhibitors.

PubMed

Ferreira, Leonardo L G; Ferreira, Rafaela S; Palomino, David L; Andricopulo, Adriano D

2018-04-27

The glycolytic enzyme fructose-1,6-bisphosphate aldolase is a validated molecular target in human African trypanosomiasis (HAT) drug discovery, a neglected tropical disease (NTD) caused by the protozoan Trypanosoma brucei. Herein, a structure-based virtual screening (SBVS) approach to the identification of novel T. brucei aldolase inhibitors is described. Distinct molecular docking algorithms were used to screen more than 500,000 compounds against the X-ray structure of the enzyme. This SBVS strategy led to the selection of a series of molecules which were evaluated for their activity on recombinant T. brucei aldolase. The effort led to the discovery of structurally new ligands able to inhibit the catalytic activity the enzyme. The predicted binding conformations were additionally investigated in molecular dynamics simulations, which provided useful insights into the enzyme-inhibitor intermolecular interactions. The molecular modeling results along with the enzyme inhibition data generated practical knowledge to be explored in further structure-based drug design efforts in HAT drug discovery. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The Texas-Indiana Virtual STAR Center: Zebrafish Models for Developmental Toxicity Screening

EPA Pesticide Factsheets

The Texas-Indiana Virtual STAR Center: Zebrafish Models for Developmental Toxicity Screening (Presented by Maria Bondesson Bolin, Ph.D, University of Houston, Center for Nuclear Receptors and Cell Signaling) (3/22/2012)

Virtual screening of B-Raf kinase inhibitors: A combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy calculation studies.

PubMed

Zhang, Wen; Qiu, Kai-Xiong; Yu, Fang; Xie, Xiao-Guang; Zhang, Shu-Qun; Chen, Ya-Juan; Xie, Hui-Ding

2017-10-01

B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG bind ) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines. In the result, five hit compounds show good biological activities (IC 50 <50μM). The present method of virtual screening can be applied to find structurally diverse inhibitors, and the obtained five structurally diverse compounds are expected to develop novel BRIs. Copyright © 2017. Published by Elsevier Ltd.

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.

Automated Inference of Chemical Discriminants of Biological Activity.

PubMed

Raschka, Sebastian; Scott, Anne M; Huertas, Mar; Li, Weiming; Kuhn, Leslie A

2018-01-01

Ligand-based virtual screening has become a standard technique for the efficient discovery of bioactive small molecules. Following assays to determine the activity of compounds selected by virtual screening, or other approaches in which dozens to thousands of molecules have been tested, machine learning techniques make it straightforward to discover the patterns of chemical groups that correlate with the desired biological activity. Defining the chemical features that generate activity can be used to guide the selection of molecules for subsequent rounds of screening and assaying, as well as help design new, more active molecules for organic synthesis.The quantitative structure-activity relationship machine learning protocols we describe here, using decision trees, random forests, and sequential feature selection, take as input the chemical structure of a single, known active small molecule (e.g., an inhibitor, agonist, or substrate) for comparison with the structure of each tested molecule. Knowledge of the atomic structure of the protein target and its interactions with the active compound are not required. These protocols can be modified and applied to any data set that consists of a series of measured structural, chemical, or other features for each tested molecule, along with the experimentally measured value of the response variable you would like to predict or optimize for your project, for instance, inhibitory activity in a biological assay or ΔG binding . To illustrate the use of different machine learning algorithms, we step through the analysis of a dataset of inhibitor candidates from virtual screening that were tested recently for their ability to inhibit GPCR-mediated signaling in a vertebrate.

Physics-based scoring of protein-ligand interactions: explicit polarizability, quantum mechanics and free energies.

PubMed

Bryce, Richard A

2011-04-01

The ability to accurately predict the interaction of a ligand with its receptor is a key limitation in computer-aided drug design approaches such as virtual screening and de novo design. In this article, we examine current strategies for a physics-based approach to scoring of protein-ligand affinity, as well as outlining recent developments in force fields and quantum chemical techniques. We also consider advances in the development and application of simulation-based free energy methods to study protein-ligand interactions. Fuelled by recent advances in computational algorithms and hardware, there is the opportunity for increased integration of physics-based scoring approaches at earlier stages in computationally guided drug discovery. Specifically, we envisage increased use of implicit solvent models and simulation-based scoring methods as tools for computing the affinities of large virtual ligand libraries. Approaches based on end point simulations and reference potentials allow the application of more advanced potential energy functions to prediction of protein-ligand binding affinities. Comprehensive evaluation of polarizable force fields and quantum mechanical (QM)/molecular mechanical and QM methods in scoring of protein-ligand interactions is required, particularly in their ability to address challenging targets such as metalloproteins and other proteins that make highly polar interactions. Finally, we anticipate increasingly quantitative free energy perturbation and thermodynamic integration methods that are practical for optimization of hits obtained from screened ligand libraries.

Working memory in wayfinding-a dual task experiment in a virtual city.

PubMed

Meilinger, Tobias; Knauff, Markus; Bülthoff, Heinrich H

2008-06-01

This study examines the working memory systems involved in human wayfinding. In the learning phase, 24 participants learned two routes in a novel photorealistic virtual environment displayed on a 220° screen while they were disrupted by a visual, a spatial, a verbal, or-in a control group-no secondary task. In the following wayfinding phase, the participants had to find and to "virtually walk" the two routes again. During this wayfinding phase, a number of dependent measures were recorded. This research shows that encoding wayfinding knowledge interfered with the verbal and with the spatial secondary task. These interferences were even stronger than the interference of wayfinding knowledge with the visual secondary task. These findings are consistent with a dual-coding approach of wayfinding knowledge. 2008 Cognitive Science Society, Inc.

Pharmacophore Based Virtual Screening Approach to Identify Selective PDE4B Inhibitors

PubMed Central

Gaurav, Anand; Gautam, Vertika

2017-01-01

Phosphodiesterase 4 (PDE4) has been established as a promising target in asthma and chronic obstructive pulmonary disease. PDE4B subtype selective inhibitors are known to reduce the dose limiting adverse effect associated with non-selective PDE4B inhibitors. This makes the development of PDE4B subtype selective inhibitors a desirable research goal. To achieve this goal, ligand based pharmacophore modeling approach is employed. Separate pharmacophore hypotheses for PDE4B and PDE4D inhibitors were generated using HypoGen algorithm and 106 PDE4 inhibitors from literature having thiopyrano [3,2-d] Pyrimidines, 2-arylpyrimidines, and triazines skeleton. Suitable training and test sets were created using the molecules as per the guidelines available for HypoGen program. Training set was used for hypothesis development while test set was used for validation purpose. Fisher validation was also used to test the significance of the developed hypothesis. The validated pharmacophore hypotheses for PDE4B and PDE4D inhibitors were used in sequential virtual screening of zinc database of drug like molecules to identify selective PDE4B inhibitors. The hits were screened for their estimated activity and fit value. The top hit was subjected to docking into the active sites of PDE4B and PDE4D to confirm its selectivity for PDE4B. The hits are proposed to be evaluated further using in-vitro assays. PMID:29201082

Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery

PubMed Central

Sun, Huiyong; Pan, Peichen; Tian, Sheng; Xu, Lei; Kong, Xiaotian; Li, Youyong; Dan Li; Hou, Tingjun

2016-01-01

The MIEC-SVM approach, which combines molecular interaction energy components (MIEC) derived from free energy decomposition and support vector machine (SVM), has been found effective in capturing the energetic patterns of protein-peptide recognition. However, the performance of this approach in identifying small molecule inhibitors of drug targets has not been well assessed and validated by experiments. Thereafter, by combining different model construction protocols, the issues related to developing best MIEC-SVM models were firstly discussed upon three kinase targets (ABL, ALK, and BRAF). As for the investigated targets, the optimized MIEC-SVM models performed much better than the models based on the default SVM parameters and Autodock for the tested datasets. Then, the proposed strategy was utilized to screen the Specs database for discovering potential inhibitors of the ALK kinase. The experimental results showed that the optimized MIEC-SVM model, which identified 7 actives with IC50 < 10 μM from 50 purchased compounds (namely hit rate of 14%, and 4 in nM level) and performed much better than Autodock (3 actives with IC50 < 10 μM from 50 purchased compounds, namely hit rate of 6%, and 2 in nM level), suggesting that the proposed strategy is a powerful tool in structure-based virtual screening. PMID:27102549

Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery.

PubMed

Sun, Huiyong; Pan, Peichen; Tian, Sheng; Xu, Lei; Kong, Xiaotian; Li, Youyong; Dan Li; Hou, Tingjun

2016-04-22

The MIEC-SVM approach, which combines molecular interaction energy components (MIEC) derived from free energy decomposition and support vector machine (SVM), has been found effective in capturing the energetic patterns of protein-peptide recognition. However, the performance of this approach in identifying small molecule inhibitors of drug targets has not been well assessed and validated by experiments. Thereafter, by combining different model construction protocols, the issues related to developing best MIEC-SVM models were firstly discussed upon three kinase targets (ABL, ALK, and BRAF). As for the investigated targets, the optimized MIEC-SVM models performed much better than the models based on the default SVM parameters and Autodock for the tested datasets. Then, the proposed strategy was utilized to screen the Specs database for discovering potential inhibitors of the ALK kinase. The experimental results showed that the optimized MIEC-SVM model, which identified 7 actives with IC50 < 10 μM from 50 purchased compounds (namely hit rate of 14%, and 4 in nM level) and performed much better than Autodock (3 actives with IC50 < 10 μM from 50 purchased compounds, namely hit rate of 6%, and 2 in nM level), suggesting that the proposed strategy is a powerful tool in structure-based virtual screening.

Stepping into the virtual unknown: feasibility study of a virtual reality-based test of ocular misalignment.

PubMed

Nesaratnam, N; Thomas, P; Vivian, A

2017-10-01

IntroductionDissociated tests of strabismus provide valuable information for diagnosis and monitoring of ocular misalignment in patients with normal retinal correspondence. However, they are vulnerable to operator error and rely on a fixed head position. Virtual reality headsets obviate the need for head fixation, while providing other clear theoretical advantages, including complete control over the illumination and targets presented for the patient's interaction.PurposeWe compared the performance of a virtual reality-based test of ocular misalignment to that of the traditional Lees screen, to establish the feasibility of using virtual reality technology in ophthalmic settings in the future.MethodsThree patients underwent a traditional Lees screen test, and a virtual reality headset-based test of ocular motility. The virtual reality headset-based programme consisted of an initial test to measure horizontal and vertical deviation, followed by a test for torsion.ResultsThe pattern of deviation obtained using the virtual reality-based test showed agreement with that obtained from the Lees screen for patients with a fourth nerve palsy, comitant esotropia, and restrictive thyroid eye disease.ConclusionsThis study reports the first use of a virtual reality headset in assessing ocular misalignment, and demonstrates that it is a feasible dissociative test of strabismus.

Novel approaches for targeting the adenosine A2A receptor.

PubMed

Yuan, Gengyang; Gedeon, Nicholas G; Jankins, Tanner C; Jones, Graham B

2015-01-01

The adenosine A2A receptor (A2AR) represents a drug target for a wide spectrum of diseases. Approaches for targeting this membrane-bound protein have been greatly advanced by new stabilization techniques. The resulting X-ray crystal structures and subsequent analyses provide deep insight to the A2AR from both static and dynamic perspectives. Application of this, along with other biophysical methods combined with fragment-based drug design (FBDD), has become a standard approach in targeting A2AR. Complementarities of in silico screening based- and biophysical screening assisted- FBDD are likely to feature in future approaches in identifying novel ligands against this key receptor. This review describes evolution of the above approaches for targeting A2AR and highlights key modulators identified. It includes a review of: adenosine receptor structures, homology modeling, X-ray structural analysis, rational drug design, biophysical methods, FBDD and in silico screening. As a drug target, the A2AR is attractive as its function plays a role in a wide spectrum of diseases including oncologic, inflammatory, Parkinson's and cardiovascular diseases. Although traditional approaches such as high-throughput screening and homology model-based virtual screening (VS) have played a role in targeting A2AR, numerous shortcomings have generally restricted their applications to specific ligand families. Using stabilization methods for crystallization, X-ray structures of A2AR have greatly accelerated drug discovery and influenced development of biophysical-in silico hybrid screening methods. Application of these new methods to other ARs and G-protein-coupled receptors is anticipated in the future.

Manually locating physical and virtual reality objects.

PubMed

Chen, Karen B; Kimmel, Ryan A; Bartholomew, Aaron; Ponto, Kevin; Gleicher, Michael L; Radwin, Robert G

2014-09-01

In this study, we compared how users locate physical and equivalent three-dimensional images of virtual objects in a cave automatic virtual environment (CAVE) using the hand to examine how human performance (accuracy, time, and approach) is affected by object size, location, and distance. Virtual reality (VR) offers the promise to flexibly simulate arbitrary environments for studying human performance. Previously, VR researchers primarily considered differences between virtual and physical distance estimation rather than reaching for close-up objects. Fourteen participants completed manual targeting tasks that involved reaching for corners on equivalent physical and virtual boxes of three different sizes. Predicted errors were calculated from a geometric model based on user interpupillary distance, eye location, distance from the eyes to the projector screen, and object. Users were 1.64 times less accurate (p < .001) and spent 1.49 times more time (p = .01) targeting virtual versus physical box corners using the hands. Predicted virtual targeting errors were on average 1.53 times (p < .05) greater than the observed errors for farther virtual targets but not significantly different for close-up virtual targets. Target size, location, and distance, in addition to binocular disparity, affected virtual object targeting inaccuracy. Observed virtual box inaccuracy was less than predicted for farther locations, suggesting possible influence of cues other than binocular vision. Human physical interaction with objects in VR for simulation, training, and prototyping involving reaching and manually handling virtual objects in a CAVE are more accurate than predicted when locating farther objects.

Human Papillomavirus Testing in the Prevention of Cervical Cancer

PubMed Central

Wentzensen, Nicolas; Wacholder, Sholom; Kinney, Walter; Gage, Julia C.; Castle, Philip E.

2011-01-01

Strong evidence now supports the adoption of cervical cancer prevention strategies that explicitly focus on persistent infection with the causal agent, human papillomavirus (HPV). To inform an evidence-based transition to a new public health approach for cervical cancer screening, we summarize the natural history and cervical carcinogenicity of HPV and discuss the promise and uncertainties of currently available screening methods. New HPV infections acquired at any age are virtually always benign, but persistent infections with one of approximately 12 carcinogenic HPV types explain virtually all cases of cervical cancer. In the absence of an overtly persistent HPV infection, the risk of cervical cancer is extremely low. Thus, HPV test results predict the risk of cervical cancer and its precursors (cervical intraepithelial neoplasia grade 3) better and longer than cytological or colposcopic abnormalities, which are signs of HPV infection. The logical and inevitable move to HPV-based cervical cancer prevention strategies will require longer screening intervals that will disrupt current gynecologic and cytology laboratory practices built on frequent screening. A major challenge will be implementing programs that do not overtreat HPV-positive women who do not have obvious long-term persistence of HPV or treatable lesions at the time of initial evaluation. The greatest potential for reduction in cervical cancer rates from HPV screening is in low-resource regions that can implement infrequent rounds of low-cost HPV testing and treatment. PMID:21282563

Novel Computational Approaches to Drug Discovery

NASA Astrophysics Data System (ADS)

Skolnick, Jeffrey; Brylinski, Michal

2010-01-01

New approaches to protein functional inference based on protein structure and evolution are described. First, FINDSITE, a threading based approach to protein function prediction, is summarized. Then, the results of large scale benchmarking of ligand binding site prediction, ligand screening, including applications to HIV protease, and GO molecular functional inference are presented. A key advantage of FINDSITE is its ability to use low resolution, predicted structures as well as high resolution experimental structures. Then, an extension of FINDSITE to ligand screening in GPCRs using predicted GPCR structures, FINDSITE/QDOCKX, is presented. This is a particularly difficult case as there are few experimentally solved GPCR structures. Thus, we first train on a subset of known binding ligands for a set of GPCRs; this is then followed by benchmarking against a large ligand library. For the virtual ligand screening of a number of Dopamine receptors, encouraging results are seen, with significant enrichment in identified ligands over those found in the training set. Thus, FINDSITE and its extensions represent a powerful approach to the successful prediction of a variety of molecular functions.

Enrichment assessment of multiple virtual screening strategies for Toll-like receptor 8 agonists based on a maximal unbiased benchmarking data set.

PubMed

Pei, Fen; Jin, Hongwei; Zhou, Xin; Xia, Jie; Sun, Lidan; Liu, Zhenming; Zhang, Liangren

2015-11-01

Toll-like receptor 8 agonists, which activate adaptive immune responses by inducing robust production of T-helper 1-polarizing cytokines, are promising candidates for vaccine adjuvants. As the binding site of toll-like receptor 8 is large and highly flexible, virtual screening by individual method has inevitable limitations; thus, a comprehensive comparison of different methods may provide insights into seeking effective strategy for the discovery of novel toll-like receptor 8 agonists. In this study, the performance of knowledge-based pharmacophore, shape-based 3D screening, and combined strategies was assessed against a maximum unbiased benchmarking data set containing 13 actives and 1302 decoys specialized for toll-like receptor 8 agonists. Prior structure-activity relationship knowledge was involved in knowledge-based pharmacophore generation, and a set of antagonists was innovatively used to verify the selectivity of the selected knowledge-based pharmacophore. The benchmarking data set was generated from our recently developed 'mubd-decoymaker' protocol. The enrichment assessment demonstrated a considerable performance through our selected three-layer virtual screening strategy: knowledge-based pharmacophore (Phar1) screening, shape-based 3D similarity search (Q4_combo), and then a Gold docking screening. This virtual screening strategy could be further employed to perform large-scale database screening and to discover novel toll-like receptor 8 agonists. © 2015 John Wiley & Sons A/S.

Data Resources for the Computer-Guided Discovery of Bioactive Natural Products.

PubMed

Chen, Ya; de Bruyn Kops, Christina; Kirchmair, Johannes

2017-09-25

Natural products from plants, animals, marine life, fungi, bacteria, and other organisms are an important resource for modern drug discovery. Their biological relevance and structural diversity make natural products good starting points for drug design. Natural product-based drug discovery can benefit greatly from computational approaches, which are a valuable precursor or supplementary method to in vitro testing. We present an overview of 25 virtual and 31 physical natural product libraries that are useful for applications in cheminformatics, in particular virtual screening. The overview includes detailed information about each library, the extent of its structural information, and the overlap between different sources of natural products. In terms of chemical structures, there is a large overlap between freely available and commercial virtual natural product libraries. Of particular interest for drug discovery is that at least ten percent of known natural products are readily purchasable and many more natural products and derivatives are available through on-demand sourcing, extraction and synthesis services. Many of the readily purchasable natural products are of small size and hence of relevance to fragment-based drug discovery. There are also an increasing number of macrocyclic natural products and derivatives becoming available for screening.

Identifying Novel Type ZBGs and Nonhydroxamate HDAC Inhibitors Through a SVM Based Virtual Screening Approach.

PubMed

Liu, X H; Song, H Y; Zhang, J X; Han, B C; Wei, X N; Ma, X H; Cui, W K; Chen, Y Z

2010-05-17

Histone deacetylase inhibitors (HDACi) have been successfully used for the treatment of cancers and other diseases. Search for novel type ZBGs and development of non-hydroxamate HDACi has become a focus in current research. To complement this, it is desirable to explore a virtual screening (VS) tool capable of identifying different types of potential inhibitors from large compound libraries with high yields and low false-hit rates similar to HTS. This work explored the use of support vector machines (SVM) combined with our newly developed putative non-inhibitor generation method as such a tool. SVM trained by 702 pre-2008 hydroxamate HDACi and 64334 putative non-HDACi showed good yields and low false-hit rates in cross-validation test and independent test using 220 diverse types of HDACi reported since 2008. The SVM hit rates in scanning 13.56 M PubChem and 168K MDDR compounds are comparable to HTS rates. Further structural analysis of SVM virtual hits suggests its potential for identification of non-hydroxamate HDACi. From this analysis, a series of novel ZBG and cap groups were proposed for HDACi design. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Virtual reality 3D headset based on DMD light modulators

NASA Astrophysics Data System (ADS)

Bernacki, Bruce E.; Evans, Allan; Tang, Edward

2014-06-01

We present the design of an immersion-type 3D headset suitable for virtual reality applications based upon digital micromirror devices (DMD). Current methods for presenting information for virtual reality are focused on either polarizationbased modulators such as liquid crystal on silicon (LCoS) devices, or miniature LCD or LED displays often using lenses to place the image at infinity. LCoS modulators are an area of active research and development, and reduce the amount of viewing light by 50% due to the use of polarization. Viewable LCD or LED screens may suffer low resolution, cause eye fatigue, and exhibit a "screen door" or pixelation effect due to the low pixel fill factor. Our approach leverages a mature technology based on silicon micro mirrors delivering 720p resolution displays in a small form-factor with high fill factor. Supporting chip sets allow rapid integration of these devices into wearable displays with high-definition resolution and low power consumption, and many of the design methods developed for DMD projector applications can be adapted to display use. Potential applications include night driving with natural depth perception, piloting of UAVs, fusion of multiple sensors for pilots, training, vision diagnostics and consumer gaming. Our design concept is described in which light from the DMD is imaged to infinity and the user's own eye lens forms a real image on the user's retina resulting in a virtual retinal display.

Missing depth cues in virtual reality limit performance and quality of three dimensional reaching movements

PubMed Central

Mayo, Johnathan; Baur, Kilian; Wittmann, Frieder; Riener, Robert; Wolf, Peter

2018-01-01

Background Goal-directed reaching for real-world objects by humans is enabled through visual depth cues. In virtual environments, the number and quality of available visual depth cues is limited, which may affect reaching performance and quality of reaching movements. Methods We assessed three-dimensional reaching movements in five experimental groups each with ten healthy volunteers. Three groups used a two-dimensional computer screen and two groups used a head-mounted display. The first screen group received the typically recreated visual depth cues, such as aerial and linear perspective, occlusion, shadows, and texture gradients. The second screen group received an abstract minimal rendering lacking those. The third screen group received the cues of the first screen group and absolute depth cues enabled by retinal image size of a known object, which realized with visual renderings of the handheld device and a ghost handheld at the target location. The two head-mounted display groups received the same virtually recreated visual depth cues as the second or the third screen group respectively. Additionally, they could rely on stereopsis and motion parallax due to head-movements. Results and conclusion All groups using the screen performed significantly worse than both groups using the head-mounted display in terms of completion time normalized by the straight-line distance to the target. Both groups using the head-mounted display achieved the optimal minimum in number of speed peaks and in hand path ratio, indicating that our subjects performed natural movements when using a head-mounted display. Virtually recreated visual depth cues had a minor impact on reaching performance. Only the screen group with rendered handhelds could outperform the other screen groups. Thus, if reaching performance in virtual environments is in the main scope of a study, we suggest applying a head-mounted display. Otherwise, when two-dimensional screens are used, achievable performance is likely limited by the reduced depth perception and not just by subjects’ motor skills. PMID:29293512

Synergism of virtual screening and medicinal chemistry: identification and optimization of allosteric antagonists of metabotropic glutamate receptor 1.

PubMed

Noeske, Tobias; Trifanova, Dina; Kauss, Valerjans; Renner, Steffen; Parsons, Christopher G; Schneider, Gisbert; Weil, Tanja

2009-08-01

We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by virtual screening and subsequent hit optimization. For ligand-based virtual screening, molecules were represented by a topological pharmacophore descriptor (CATS-2D) and clustered by a self-organizing map (SOM). The most promising compounds were tested in mGluR1 functional and binding assays. We identified a potent chemotype exhibiting selective antagonistic activity at mGluR1 (functional IC(50)=0.74+/-0.29 microM). Hit optimization yielded lead structure 16 with an affinity of K(i)=0.024+/-0.001 microM and greater than 1000-fold selectivity for mGluR1 versus mGluR5. Homology-based receptor modelling suggests a binding site compatible with previously reported mutation studies. Our study demonstrates the usefulness of ligand-based virtual screening for scaffold-hopping and rapid lead structure identification in early drug discovery projects.

Ligand and structure based virtual screening strategies for hit-finding and optimization of hepatitis C virus (HCV) inhibitors.

PubMed

Melagraki, G; Afantitis, A

2011-01-01

Virtual Screening (VS) has experienced increased attention into the recent years due to the large datasets made available, the development of advanced VS techniques and the encouraging fact that VS has contributed to the discovery of several compounds that have either reached the market or entered clinical trials. Hepatitis C Virus (HCV) nonstructural protein 5B (NS5B) has become an attractive target for the development of antiviral drugs and many small molecules have been explored as possible HCV NS5B inhibitors. In parallel with experimental practices, VS can serve as a valuable tool in the identification of novel effective inhibitors. Different techniques and workflows have been reported in literature with the goal to prioritize possible potent hits. In this context, different virtual screening strategies have been deployed for the identification of novel Hepatitis C Virus (HCV) inhibitors. This work reviews recent applications of virtual screening in an effort to identify novel potent HCV inhibitors.

Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.

PubMed

Rohrer, Sebastian G; Baumann, Knut

2009-02-01

Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.

Selection, application, and validation of a set of molecular descriptors for nuclear receptor ligands.

PubMed

Stewart, Eugene L; Brown, Peter J; Bentley, James A; Willson, Timothy M

2004-08-01

A methodology for the selection and validation of nuclear receptor ligand chemical descriptors is described. After descriptors for a targeted chemical space were selected, a virtual screening methodology utilizing this space was formulated for the identification of potential NR ligands from our corporate collection. Using simple descriptors and our virtual screening method, we are able to quickly identify potential NR ligands from a large collection of compounds. As validation of the virtual screening procedure, an 8, 000-membered NR targeted set and a 24, 000-membered diverse control set of compounds were selected from our in-house general screening collection and screened in parallel across a number of orphan NR FRET assays. For the two assays that provided at least one hit per set by the established minimum pEC(50) for activity, the results showed a 2-fold increase in the hit-rate of the targeted compound set over the diverse set.

A large scale virtual screen of DprE1.

PubMed

Wilsey, Claire; Gurka, Jessica; Toth, David; Franco, Jimmy

2013-12-01

Tuberculosis continues to plague the world with the World Health Organization estimating that about one third of the world's population is infected. Due to the emergence of MDR and XDR strains of TB, the need for novel therapeutics has become increasing urgent. Herein we report the results of a virtual screen of 4.1 million compounds against a promising drug target, DrpE1. The virtual compounds were obtained from the Zinc docking site and screened using the molecular docking program, AutoDock Vina. The computational hits have led to the identification of several promising lead compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

DARC: Mapping Surface Topography by Ray-Casting for Effective Virtual Screening at Protein Interaction Sites.

PubMed

Gowthaman, Ragul; Miller, Sven A; Rogers, Steven; Khowsathit, Jittasak; Lan, Lan; Bai, Nan; Johnson, David K; Liu, Chunjing; Xu, Liang; Anbanandam, Asokan; Aubé, Jeffrey; Roy, Anuradha; Karanicolas, John

2016-05-12

Protein-protein interactions represent an exciting and challenging target class for therapeutic intervention using small molecules. Protein interaction sites are often devoid of the deep surface pockets presented by "traditional" drug targets, and crystal structures reveal that inhibitors typically engage these sites using very shallow binding modes. As a consequence, modern virtual screening tools developed to identify inhibitors of traditional drug targets do not perform as well when they are instead deployed at protein interaction sites. To address the need for novel inhibitors of important protein interactions, here we introduce an alternate docking strategy specifically designed for this regime. Our method, termed DARC (Docking Approach using Ray-Casting), matches the topography of a surface pocket "observed" from within the protein to the topography "observed" when viewing a potential ligand from the same vantage point. We applied DARC to carry out a virtual screen against the protein interaction site of human antiapoptotic protein Mcl-1 and found that four of the top-scoring 21 compounds showed clear inhibition in a biochemical assay. The Ki values for these compounds ranged from 1.2 to 21 μM, and each had ligand efficiency comparable to promising small-molecule inhibitors of other protein-protein interactions. These hit compounds do not resemble the natural (protein) binding partner of Mcl-1, nor do they resemble any known inhibitors of Mcl-1. Our results thus demonstrate the utility of DARC for identifying novel inhibitors of protein-protein interactions.

NMR-Fragment Based Virtual Screening: A Brief Overview.

PubMed

Singh, Meenakshi; Tam, Benjamin; Akabayov, Barak

2018-01-25

Fragment-based drug discovery (FBDD) using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the competence of NMR in fragment based drug discovery are discussed, as well as later steps that involve optimization of hits obtained by NMR-FBDD.

Combinatorial support vector machines approach for virtual screening of selective multi-target serotonin reuptake inhibitors from large compound libraries.

PubMed

Shi, Z; Ma, X H; Qin, C; Jia, J; Jiang, Y Y; Tan, C Y; Chen, Y Z

2012-02-01

Selective multi-target serotonin reuptake inhibitors enhance antidepressant efficacy. Their discovery can be facilitated by multiple methods, including in silico ones. In this study, we developed and tested an in silico method, combinatorial support vector machines (COMBI-SVMs), for virtual screening (VS) multi-target serotonin reuptake inhibitors of seven target pairs (serotonin transporter paired with noradrenaline transporter, H(3) receptor, 5-HT(1A) receptor, 5-HT(1B) receptor, 5-HT(2C) receptor, melanocortin 4 receptor and neurokinin 1 receptor respectively) from large compound libraries. COMBI-SVMs trained with 917-1951 individual target inhibitors correctly identified 22-83.3% (majority >31.1%) of the 6-216 dual inhibitors collected from literature as independent testing sets. COMBI-SVMs showed moderate to good target selectivity in misclassifying as dual inhibitors 2.2-29.8% (majority <15.4%) of the individual target inhibitors of the same target pair and 0.58-7.1% of the other 6 targets outside the target pair. COMBI-SVMs showed low dual inhibitor false hit rates (0.006-0.056%, 0.042-0.21%, 0.2-4%) in screening 17 million PubChem compounds, 168,000 MDDR compounds, and 7-8181 MDDR compounds similar to the dual inhibitors. Compared with similarity searching, k-NN and PNN methods, COMBI-SVM produced comparable dual inhibitor yields, similar target selectivity, and lower false hit rate in screening 168,000 MDDR compounds. The annotated classes of many COMBI-SVMs identified MDDR virtual hits correlate with the reported effects of their predicted targets. COMBI-SVM is potentially useful for searching selective multi-target agents without explicit knowledge of these agents. Copyright © 2011 Elsevier Inc. All rights reserved.

Cognitive evaluation for the diagnosis of Alzheimer's disease based on Turing Test and Virtual Environments.

PubMed

Fernandez Montenegro, Juan Manuel; Argyriou, Vasileios

2017-05-01

Alzheimer's screening tests are commonly used by doctors to diagnose the patient's condition and stage as early as possible. Most of these tests are based on pen-paper interaction and do not embrace the advantages provided by new technologies. This paper proposes novel Alzheimer's screening tests based on virtual environments and game principles using new immersive technologies combined with advanced Human Computer Interaction (HCI) systems. These new tests are focused on the immersion of the patient in a virtual room, in order to mislead and deceive the patient's mind. In addition, we propose two novel variations of Turing Test proposed by Alan Turing as a method to detect dementia. As a result, four tests are introduced demonstrating the wide range of screening mechanisms that could be designed using virtual environments and game concepts. The proposed tests are focused on the evaluation of memory loss related to common objects, recent conversations and events; the diagnosis of problems in expressing and understanding language; the ability to recognize abnormalities; and to differentiate between virtual worlds and reality, or humans and machines. The proposed screening tests were evaluated and tested using both patients and healthy adults in a comparative study with state-of-the-art Alzheimer's screening tests. The results show the capacity of the new tests to distinguish healthy people from Alzheimer's patients. Copyright © 2017. Published by Elsevier Inc.

Discovery of small molecules binding to the normal conformation of prion by combining virtual screening and multiple biological activity evaluation methods

NASA Astrophysics Data System (ADS)

Li, Lanlan; Wei, Wei; Jia, Wen-Juan; Zhu, Yongchang; Zhang, Yan; Chen, Jiang-Huai; Tian, Jiaqi; Liu, Huanxiang; He, Yong-Xing; Yao, Xiaojun

2017-12-01

Conformational conversion of the normal cellular prion protein, PrPC, into the misfolded isoform, PrPSc, is considered to be a central event in the development of fatal neurodegenerative diseases. Stabilization of prion protein at the normal cellular form (PrPC) with small molecules is a rational and efficient strategy for treatment of prion related diseases. However, few compounds have been identified as potent prion inhibitors by binding to the normal conformation of prion. In this work, to rational screening of inhibitors capable of stabilizing cellular form of prion protein, multiple approaches combining docking-based virtual screening, steady-state fluorescence quenching, surface plasmon resonance and thioflavin T fluorescence assay were used to discover new compounds interrupting PrPC to PrPSc conversion. Compound 3253-0207 that can bind to PrPC with micromolar affinity and inhibit prion fibrillation was identified from small molecule databases. Molecular dynamics simulation indicated that compound 3253-0207 can bind to the hotspot residues in the binding pocket composed by β1, β2 and α2, which are significant structure moieties in conversion from PrPC to PrPSc.

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

CycloPs: generating virtual libraries of cyclized and constrained peptides including nonnatural amino acids.

PubMed

Duffy, Fergal J; Verniere, Mélanie; Devocelle, Marc; Bernard, Elise; Shields, Denis C; Chubb, Anthony J

2011-04-25

We introduce CycloPs, software for the generation of virtual libraries of constrained peptides including natural and nonnatural commercially available amino acids. The software is written in the cross-platform Python programming language, and features include generating virtual libraries in one-dimensional SMILES and three-dimensional SDF formats, suitable for virtual screening. The stand-alone software is capable of filtering the virtual libraries using empirical measurements, including peptide synthesizability by standard peptide synthesis techniques, stability, and the druglike properties of the peptide. The software and accompanying Web interface is designed to enable the rapid generation of large, structurally diverse, synthesizable virtual libraries of constrained peptides quickly and conveniently, for use in virtual screening experiments. The stand-alone software, and the Web interface for evaluating these empirical properties of a single peptide, are available at http://bioware.ucd.ie .

Identification of Direct Activator of Adenosine Monophosphate-Activated Protein Kinase (AMPK) by Structure-Based Virtual Screening and Molecular Docking Approach.

PubMed

Huang, Tonghui; Sun, Jie; Zhou, Shanshan; Gao, Jian; Liu, Yi

2017-06-30

Adenosine monophosphate-activated protein kinase (AMPK) plays a critical role in the regulation of energy metabolism and has been targeted for drug development of therapeutic intervention in Type II diabetes and related diseases. Recently, there has been renewed interest in the development of direct β1-selective AMPK activators to treat patients with diabetic nephropathy. To investigate the details of AMPK domain structure, sequence alignment and structural comparison were used to identify the key amino acids involved in the interaction with activators and the structure difference between β1 and β2 subunits. Additionally, a series of potential β1-selective AMPK activators were identified by virtual screening using molecular docking. The retrieved hits were filtered on the basis of Lipinski's rule of five and drug-likeness. Finally, 12 novel compounds with diverse scaffolds were obtained as potential starting points for the design of direct β1-selective AMPK activators.

What do we know and when do we know it?

PubMed Central

2008-01-01

Two essential aspects of virtual screening are considered: experimental design and performance metrics. In the design of any retrospective virtual screen, choices have to be made as to the purpose of the exercise. Is the goal to compare methods? Is the interest in a particular type of target or all targets? Are we simulating a ‘real-world’ setting, or teasing out distinguishing features of a method? What are the confidence limits for the results? What should be reported in a publication? In particular, what criteria should be used to decide between different performance metrics? Comparing the field of molecular modeling to other endeavors, such as medical statistics, criminology, or computer hardware evaluation indicates some clear directions. Taken together these suggest the modeling field has a long way to go to provide effective assessment of its approaches, either to itself or to a broader audience, but that there are no technical reasons why progress cannot be made. PMID:18253702

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

Comparative Analysis of Virtual Screening Approaches in the Search for Novel EphA2 Receptor Antagonists.

PubMed

Callegari, Donatella; Pala, Daniele; Scalvini, Laura; Tognolini, Massimiliano; Incerti, Matteo; Rivara, Silvia; Mor, Marco; Lodola, Alessio

2015-09-17

The EphA2 receptor and its ephrin-A1 ligand form a key cell communication system, which has been found overexpressed in many cancer types and involved in tumor growth. Recent medicinal chemistry efforts have identified bile acid derivatives as low micromolar binders of the EphA2 receptor. However, these compounds suffer from poor physicochemical properties, hampering their use in vivo. The identification of compounds able to disrupt the EphA2-ephrin-A1 complex lacking the bile acid scaffold may lead to new pharmacological tools suitable for in vivo studies. To identify the most promising virtual screening (VS) protocol aimed at finding novel EphA2 antagonists, we investigated the ability of both ligand-based and structure-based approaches to retrieve known EphA2 antagonists from libraries of decoys with similar molecular properties. While ligand-based VSs were conducted using UniPR129 and ephrin-A1 ligand as reference structures, structure-based VSs were performed with Glide, using the X-ray structure of the EphA2 receptor/ephrin-A1 complex. A comparison of enrichment factors showed that ligand-based approaches outperformed the structure-based ones, suggesting ligand-based methods using the G-H loop of ephrin-A1 ligand as template as the most promising protocols to search for novel EphA2 antagonists.

Discovery of Novel Hepatitis C Virus NS5B Polymerase Inhibitors by Combining Random Forest, Multiple e-Pharmacophore Modeling and Docking

PubMed Central

Wei, Yu; Li, Jinlong; Qing, Jie; Huang, Mingjie; Wu, Ming; Gao, Fenghua; Li, Dongmei; Hong, Zhangyong; Kong, Lingbao; Huang, Weiqiang; Lin, Jianping

2016-01-01

The NS5B polymerase is one of the most attractive targets for developing new drugs to block Hepatitis C virus (HCV) infection. We describe the discovery of novel potent HCV NS5B polymerase inhibitors by employing a virtual screening (VS) approach, which is based on random forest (RB-VS), e-pharmacophore (PB-VS), and docking (DB-VS) methods. In the RB-VS stage, after feature selection, a model with 16 descriptors was used. In the PB-VS stage, six energy-based pharmacophore (e-pharmacophore) models from different crystal structures of the NS5B polymerase with ligands binding at the palm I, thumb I and thumb II regions were used. In the DB-VS stage, the Glide SP and XP docking protocols with default parameters were employed. In the virtual screening approach, the RB-VS, PB-VS and DB-VS methods were applied in increasing order of complexity to screen the InterBioScreen database. From the final hits, we selected 5 compounds for further anti-HCV activity and cellular cytotoxicity assay. All 5 compounds were found to inhibit NS5B polymerase with IC50 values of 2.01–23.84 μM and displayed anti-HCV activities with EC50 values ranging from 1.61 to 21.88 μM, and all compounds displayed no cellular cytotoxicity (CC50 > 100 μM) except compound N2, which displayed weak cytotoxicity with a CC50 value of 51.3 μM. The hit compound N2 had the best antiviral activity against HCV, with a selective index of 32.1. The 5 hit compounds with new scaffolds could potentially serve as NS5B polymerase inhibitors through further optimization and development. PMID:26845440

Virtual screening of cocrystal formers for CL-20

NASA Astrophysics Data System (ADS)

Zhou, Jun-Hong; Chen, Min-Bo; Chen, Wei-Ming; Shi, Liang-Wei; Zhang, Chao-Yang; Li, Hong-Zhen

2014-08-01

According to the structure characteristics of 2,4,6,8,10,12-hexanitrohexaazaisowurtzitane (CL-20) and the kinetic mechanism of the cocrystal formation, the method of virtual screening CL-20 cocrystal formers by the criterion of the strongest intermolecular site pairing energy (ISPE) was proposed. In this method the strongest ISPE was thought to determine the first step of the cocrystal formation. The prediction results for four sets of common drug molecule cocrystals by this method were compared with those by the total ISPE method from the reference (Musumeci et al., 2011), and the experimental results. This method was then applied to virtually screen the CL-20 cocrystal formers, and the prediction results were compared with the experimental results.

Virtual Screening of Receptor Sites for Molecularly Imprinted Polymers.

PubMed

Bates, Ferdia; Cela-Pérez, María Concepción; Karim, Kal; Piletsky, Sergey; López-Vilariño, José Manuel

2016-08-01

Molecularly Imprinted Polymers (MIPs) are highly advantageous in the field of analytical chemistry. However, interference from secondary molecules can also impede capture of a target by a MIP receptor. This greatly complicates the design process and often requires extensive laboratory screening which is time consuming, costly, and creates substantial waste products. Herein, is presented a new technique for screening of "virtually imprinted receptors" for rebinding of the molecular template as well as secondary structures, correlating the virtual predictions with experimentally acquired data in three case studies. This novel technique is particularly applicable to the evaluation and prediction of MIP receptor specificity and efficiency in complex aqueous systems. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Classification and virtual screening of androgen receptor antagonists.

PubMed

Li, Jiazhong; Gramatica, Paola

2010-05-24

Computational tools, such as quantitative structure-activity relationship (QSAR), are highly useful as screening support for prioritization of substances of very high concern (SVHC). From the practical point of view, QSAR models should be effective to pick out more active rather than inactive compounds, expressed as sensitivity in classification works. This research investigates the classification of a big data set of endocrine-disrupting chemicals (EDCs)-androgen receptor (AR) antagonists, mainly aiming to improve the external sensitivity and to screen for potential AR binders. The kNN, lazy IB1, and ADTree methods and the consensus approach were used to build different models, which improve the sensitivity on external chemicals from 57.1% (literature) to 76.4%. Additionally, the models' predictive abilities were further validated on a blind collected data set (sensitivity: 85.7%). Then the proposed classifiers were used: (i) to distinguish a set of AR binders into antagonists and agonists; (ii) to screen a combined estrogen receptor binder database to find out possible chemicals that can bind to both AR and ER; and (iii) to virtually screen our in-house environmental chemical database. The in silico screening results suggest: (i) that some compounds can affect the normal endocrine system through a complex mechanism binding both to ER and AR; (ii) new EDCs, which are nonER binders, but can in silico bind to AR, are recognized; and (iii) about 20% of compounds in a big data set of environmental chemicals are predicted as new AR antagonists. The priority should be given to them to experimentally test the binding activities with AR.

Lead identification for the K-Ras protein: virtual screening and combinatorial fragment-based approaches

PubMed Central

Pathan, Akbar Ali Khan; Panthi, Bhavana; Khan, Zahid; Koppula, Purushotham Reddy; Alanazi, Mohammed Saud; Sachchidanand; Parine, Narasimha Reddy; Chourasia, Mukesh

2016-01-01

Objective Kirsten rat sarcoma (K-Ras) protein is a member of Ras family belonging to the small guanosine triphosphatases superfamily. The members of this family share a conserved structure and biochemical properties, acting as binary molecular switches. The guanosine triphosphate-bound active K-Ras interacts with a range of effectors, resulting in the stimulation of downstream signaling pathways regulating cell proliferation, differentiation, and apoptosis. Efforts to target K-Ras have been unsuccessful until now, placing it among high-value molecules against which developing a therapy would have an enormous impact. K-Ras transduces signals when it binds to guanosine triphosphate by directly binding to downstream effector proteins, but in case of guanosine diphosphate-bound conformation, these interactions get disrupted. Methods In the present study, we targeted the nucleotide-binding site in the “on” and “off” state conformations of the K-Ras protein to find out suitable lead compounds. A structure-based virtual screening approach has been used to screen compounds from different databases, followed by a combinatorial fragment-based approach to design the apposite lead for the K-Ras protein. Results Interestingly, the designed compounds exhibit a binding preference for the “off” state over “on” state conformation of K-Ras protein. Moreover, the designed compounds’ interactions are similar to guanosine diphosphate and, thus, could presumably act as a potential lead for K-Ras. The predicted drug-likeness properties of these compounds suggest that these compounds follow the Lipinski’s rule of five and have tolerable absorption, distribution, metabolism, excretion and toxicity values. Conclusion Thus, through the current study, we propose targeting only “off” state conformations as a promising strategy for the design of reversible inhibitors to pharmacologically inhibit distinct conformations of K-Ras protein. PMID:27217775

Virtual High-Throughput Screening To Identify Novel Activin Antagonists

PubMed Central

Zhu, Jie; Mishra, Rama K.; Schiltz, Gary E.; Makanji, Yogeshwar; Scheidt, Karl A.; Mazar, Andrew P.; Woodruff, Teresa K.

2015-01-01

Activin belongs to the TGFβ superfamily, which is associated with several disease conditions, including cancer-related cachexia, preterm labor with delivery, and osteoporosis. Targeting activin and its related signaling pathways holds promise as a therapeutic approach to these diseases. A small-molecule ligand-binding groove was identified in the interface between the two activin βA subunits and was used for a virtual high-throughput in silico screening of the ZINC database to identify hits. Thirty-nine compounds without significant toxicity were tested in two well-established activin assays: FSHβ transcription and HepG2 cell apoptosis. This screening workflow resulted in two lead compounds: NUCC-474 and NUCC-555. These potential activin antagonists were then shown to inhibit activin A-mediated cell proliferation in ex vivo ovary cultures. In vivo testing showed that our most potent compound (NUCC-555) caused a dose-dependent decrease in FSH levels in ovariectomized mice. The Blitz competition binding assay confirmed target binding of NUCC-555 to the activin A:ActRII that disrupts the activin A:ActRII complex’s binding with ALK4-ECD-Fc in a dose-dependent manner. The NUCC-555 also specifically binds to activin A compared with other TGFβ superfamily member myostatin (GDF8). These data demonstrate a new in silico-based strategy for identifying small-molecule activin antagonists. Our approach is the first to identify a first-in-class small-molecule antagonist of activin binding to ALK4, which opens a completely new approach to inhibiting the activity of TGFβ receptor superfamily members. in addition, the lead compound can serve as a starting point for lead optimization toward the goal of a compound that may be effective in activin-mediated diseases. PMID:26098096

Rational Drug Discovery of HCV Helicase Inhibitor: Improved Docking Accuracy with Multiple Seeding in AutoDock Vina and In Situ Minimization.

PubMed

Lim, See K; Othman, Rozana; Yusof, Rohana; Heh, Choon H

2017-01-01

Hepatitis C is a significant cause for end-stage liver diseases and liver transplantation which affects approximately 3% of the global populations. Despite the current several direct antiviral agents in the treatment of Hepatitis C, the standard treatment for HCV infection is accompanied by several drawbacks, such as adverse side effects, high pricing of medications and the rapid emerging rate of resistant HCV variants. To discover potential inhibitors for HCV helicase through an optimized in silico approach. In this study, a homology model (HCV Genotype 3 helicase) was used as the target and screened through a benzopyran-based virtual library. Multiple-seedings of AutoDock Vina and in situ minimization were to account for the non-deterministic nature of AutoDock Vina search algorithm and binding site flexibility, respectively. ADME/T and interaction analyses were also done on the top hits via FAFDRUG3 web server and Discovery Studio 4.5. This study involved the development of an improved flow for virtual screening via implemention of multiple-seeding screening approach and in situ minimization. With the new docking protocol, the redocked standards have shown better RMSD value in reference to their native conformations. Ten benzopyran-like compounds with satisfactory physicochemical properties were discovered to be potential inhibitors of HCV helicase. ZINC38649350 was identified as the most potential inhibitor. Ten potential HCV helicase inhibitors were discovered via a new docking optimization protocol with better docking accuracy. These findings could contribute to the discovery of novel HCV antivirals and serve as an alternative approach of in silico rational drug discovery. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Hit identification and optimization in virtual screening: practical recommendations based on a critical literature analysis.

PubMed

Zhu, Tian; Cao, Shuyi; Su, Pin-Chih; Patel, Ram; Shah, Darshan; Chokshi, Heta B; Szukala, Richard; Johnson, Michael E; Hevener, Kirk E

2013-09-12

A critical analysis of virtual screening results published between 2007 and 2011 was performed. The activity of reported hit compounds from over 400 studies was compared to their hit identification criteria. Hit rates and ligand efficiencies were calculated to assist in these analyses, and the results were compared with factors such as the size of the virtual library and the number of compounds tested. A series of promiscuity, druglike, and ADMET filters were applied to the reported hits to assess the quality of compounds reported, and a careful analysis of a subset of the studies that presented hit optimization was performed. These data allowed us to make several practical recommendations with respect to selection of compounds for experimental testing, definition of hit identification criteria, and general virtual screening hit criteria to allow for realistic hit optimization. A key recommendation is the use of size-targeted ligand efficiency values as hit identification criteria.

Design and Development of ChemInfoCloud: An Integrated Cloud Enabled Platform for Virtual Screening.

PubMed

Karthikeyan, Muthukumarasamy; Pandit, Deepak; Bhavasar, Arvind; Vyas, Renu

2015-01-01

The power of cloud computing and distributed computing has been harnessed to handle vast and heterogeneous data required to be processed in any virtual screening protocol. A cloud computing platorm ChemInfoCloud was built and integrated with several chemoinformatics and bioinformatics tools. The robust engine performs the core chemoinformatics tasks of lead generation, lead optimisation and property prediction in a fast and efficient manner. It has also been provided with some of the bioinformatics functionalities including sequence alignment, active site pose prediction and protein ligand docking. Text mining, NMR chemical shift (1H, 13C) prediction and reaction fingerprint generation modules for efficient lead discovery are also implemented in this platform. We have developed an integrated problem solving cloud environment for virtual screening studies that also provides workflow management, better usability and interaction with end users using container based virtualization, OpenVz.

Binding-Site Assessment by Virtual Fragment Screening

PubMed Central

Huang, Niu; Jacobson, Matthew P.

2010-01-01

The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules) would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock ∼11000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates measured experimentally in a previously published NMR-based screening method. Secondly, we show that the in silico fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors. PMID:20404926

Discovery of covalent inhibitors for MIF tautomerase via cocrystal structures with phantom hits from virtual screening

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

McLean, Larry R.; Zhang, Ying; Li, Hua

Biochemical and X-ray crystallographic studies confirmed that hydroxyquinoline derivatives identified by virtual screening were actually covalent inhibitors of the MIF tautomerase. Adducts were formed by N-alkylation of the Pro-1 at the catalytic site with a loss of an amino group of the inhibitor.

Virtual screening and pharmacophore design for a novel theoretical inhibitor of macrophage stimulating factor as a metastatic agent.

PubMed

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies.

Virtual Ligand Screening Using PL-PatchSurfer2, a Molecular Surface-Based Protein-Ligand Docking Method.

PubMed

Shin, Woong-Hee; Kihara, Daisuke

2018-01-01

Virtual screening is a computational technique for predicting a potent binding compound for a receptor protein from a ligand library. It has been a widely used in the drug discovery field to reduce the efforts of medicinal chemists to find hit compounds by experiments.Here, we introduce our novel structure-based virtual screening program, PL-PatchSurfer, which uses molecular surface representation with the three-dimensional Zernike descriptors, which is an effective mathematical representation for identifying physicochemical complementarities between local surfaces of a target protein and a ligand. The advantage of the surface-patch description is its tolerance on a receptor and compound structure variation. PL-PatchSurfer2 achieves higher accuracy on apo form and computationally modeled receptor structures than conventional structure-based virtual screening programs. Thus, PL-PatchSurfer2 opens up an opportunity for targets that do not have their crystal structures. The program is provided as a stand-alone program at http://kiharalab.org/plps2 . We also provide files for two ligand libraries, ChEMBL and ZINC Drug-like.

ChemHTPS - A virtual high-throughput screening program suite for the chemical and materials sciences

NASA Astrophysics Data System (ADS)

Afzal, Mohammad Atif Faiz; Evangelista, William; Hachmann, Johannes

The discovery of new compounds, materials, and chemical reactions with exceptional properties is the key for the grand challenges in innovation, energy and sustainability. This process can be dramatically accelerated by means of the virtual high-throughput screening (HTPS) of large-scale candidate libraries. The resulting data can further be used to study the underlying structure-property relationships and thus facilitate rational design capability. This approach has been extensively used for many years in the drug discovery community. However, the lack of openly available virtual HTPS tools is limiting the use of these techniques in various other applications such as photovoltaics, optoelectronics, and catalysis. Thus, we developed ChemHTPS, a general-purpose, comprehensive and user-friendly suite, that will allow users to efficiently perform large in silico modeling studies and high-throughput analyses in these applications. ChemHTPS also includes a massively parallel molecular library generator which offers a multitude of options to customize and restrict the scope of the enumerated chemical space and thus tailor it for the demands of specific applications. To streamline the non-combinatorial exploration of chemical space, we incorporate genetic algorithms into the framework. In addition to implementing smarter algorithms, we also focus on the ease of use, workflow, and code integration to make this technology more accessible to the community.

Screening and Spectral Summing of LANL Empty Waste Drums - 13226

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

Gruetzmacher, Kathleen M.; Bustos, Roland M.; Ferran, Scott G.

2013-07-01

Empty 55-gallon drums that formerly held transuranic (TRU) waste (often over-packed in 85- gallon drums) are generated at LANL and require radiological characterization for disposition. These drums are typically measured and analyzed individually using high purity germanium (HPGe) gamma detectors. This approach can be resource and time intensive. For a project requiring several hundred drums to be characterized in a short time frame, an alternative approach was developed. The approach utilizes a combination of field screening and spectral summing that was required to be technically defensible and meet the Nevada Nuclear Security Site (NNSS) Waste Acceptance Criteria (WAC). In themore » screening phase of the operation, the drums were counted for 300 seconds (compared to 600 seconds for the typical approach) and checked against Low Level (LL)/TRU thresholds established for each drum configuration and detector. Multiple TRU nuclides and multiple gamma rays for each nuclide were evaluated using an automated spreadsheet utility that can process data from up to 42 drums at a time. Screening results were reviewed by an expert analyst to confirm the field LL/TRU determination. The spectral summing analysis technique combines spectral data (channel-by-channel) associated with a group of individual waste containers producing a composite spectrum. The grouped drums must meet specific similarity criteria. Another automated spreadsheet utility was used to spectral sum data from an unlimited number of similar drums grouped together. The composite spectrum represents a virtual combined drum for the group of drums and was analyzed using the SNAP{sup TM}/Radioassay Data Sheet (RDS)/Batch Data Report (BDR) method. The activity results for a composite virtual drum were divided equally amongst the individual drums to generate characterization results for each individual drum in the group. An initial batch of approximately 500 drums were measured and analyzed in less than 2 months in 2011. A second batch of approximately 500 more drums were measured and analyzed during the following 2 1/2 months. Four different HPGe detectors were employed for the operation. The screening and spectral summing approach can reduce the overall measurement and analysis time required. However, developing the technical details and automation spreadsheets requires a significant amount of expert time prior to beginning field operations and must be considered in the overall project schedule. This approach has continued to be used for characterizing several hundred more empty drums in 2012 and is planned to continue in 2013. (authors)« less

Structure-based drug design: docking and scoring.

PubMed

Kroemer, Romano T

2007-08-01

This review gives an introduction into ligand - receptor docking and illustrates the basic underlying concepts. An overview of different approaches and algorithms is provided. Although the application of docking and scoring has led to some remarkable successes, there are still some major challenges ahead, which are outlined here as well. Approaches to address some of these challenges and the latest developments in the area are presented. Some aspects of the assessment of docking program performance are discussed. A number of successful applications of structure-based virtual screening are described.

mRAISE: an alternative algorithmic approach to ligand-based virtual screening

NASA Astrophysics Data System (ADS)

von Behren, Mathias M.; Bietz, Stefan; Nittinger, Eva; Rarey, Matthias

2016-08-01

Ligand-based virtual screening is a well established method to find new lead molecules in todays drug discovery process. In order to be applicable in day to day practice, such methods have to face multiple challenges. The most important part is the reliability of the results, which can be shown and compared in retrospective studies. Furthermore, in the case of 3D methods, they need to provide biologically relevant molecular alignments of the ligands, that can be further investigated by a medicinal chemist. Last but not least, they have to be able to screen large databases in reasonable time. Many algorithms for ligand-based virtual screening have been proposed in the past, most of them based on pairwise comparisons. Here, a new method is introduced called mRAISE. Based on structural alignments, it uses a descriptor-based bitmap search engine (RAISE) to achieve efficiency. Alignments created on the fly by the search engine get evaluated with an independent shape-based scoring function also used for ranking of compounds. The correct ranking as well as the alignment quality of the method are evaluated and compared to other state of the art methods. On the commonly used Directory of Useful Decoys dataset mRAISE achieves an average area under the ROC curve of 0.76, an average enrichment factor at 1 % of 20.2 and an average hit rate at 1 % of 55.5. With these results, mRAISE is always among the top performing methods with available data for comparison. To access the quality of the alignments calculated by ligand-based virtual screening methods, we introduce a new dataset containing 180 prealigned ligands for 11 diverse targets. Within the top ten ranked conformations, the alignment closest to X-ray structure calculated with mRAISE has a root-mean-square deviation of less than 2.0 Å for 80.8 % of alignment pairs and achieves a median of less than 2.0 Å for eight of the 11 cases. The dataset used to rate the quality of the calculated alignments is freely available at http://www.zbh.uni-hamburg.de/mraise-dataset.html. The table of all PDB codes contained in the ensembles can be found in the supplementary material. The software tool mRAISE is freely available for evaluation purposes and academic use (see http://www.zbh.uni-hamburg.de/raise).

Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking.

PubMed

Chen, H F; Dong, X C; Zen, B S; Gao, K; Yuan, S G; Panaye, A; Doucet, J P; Fan, B T

2003-08-01

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.

Impact of a Virtual Clinic in a Paediatric Cardiology Network on Northeast Brazil.

PubMed

de Araújo, Juliana Sousa Soares; Dias Filho, Adalberto Vieira; Silva Gomes, Renata Grigório; Regis, Cláudio Teixeira; Rodrigues, Klecida Nunes; Siqueira, Nicoly Negreiros; Albuquerque, Fernanda Cruz de Lira; Mourato, Felipe Alves; Mattos, Sandra da Silva

2015-01-01

Introduction. Congenital heart diseases (CHD) affect approximately 1% of live births and is an important cause of neonatal morbidity and mortality. Despite that, there is a shortage of paediatric cardiologists in Brazil, mainly in the northern and northeastern regions. In this context, the implementation of virtual outpatient clinics with the aid of different telemedicine resources may help in the care of children with heart defects. Methods. Patients under 18 years of age treated in virtual outpatient clinics between January 2013 and May 2014 were selected. They were divided into 2 groups: those who had and those who had not undergone a screening process for CHD in the neonatal period. Clinical and demographic characteristics were collected for further statistical analysis. Results. A total of 653 children and teenagers were treated in the virtual outpatient clinics. From these, 229 had undergone a neonatal screening process. Fewer abnormalities were observed on the physical examination of the screened patients. Conclusion. The implementation of pediatric cardiology virtual outpatient clinics can have a positive impact in the care provided to people in areas with lack of skilled professionals.

A Thoroughly Validated Virtual Screening Strategy for Discovery of Novel HDAC3 Inhibitors.

PubMed

Hu, Huabin; Xia, Jie; Wang, Dongmei; Wang, Xiang Simon; Wu, Song

2017-01-18

Histone deacetylase 3 (HDAC3) has been recently identified as a potential target for the treatment of cancer and other diseases, such as chronic inflammation, neurodegenerative diseases, and diabetes. Virtual screening (VS) is currently a routine technique for hit identification, but its success depends on rational development of VS strategies. To facilitate this process, we applied our previously released benchmarking dataset, i.e., MUBD-HDAC3 to the evaluation of structure-based VS (SBVS) and ligand-based VS (LBVS) combinatorial approaches. We have identified FRED (Chemgauss4) docking against a structural model of HDAC3, i.e., SAHA-3 generated by a computationally inexpensive "flexible docking", as the best SBVS approach and a common feature pharmacophore model, i.e., Hypo1 generated by Catalyst/HipHop as the optimal model for LBVS. We then developed a pipeline that was composed of Hypo1, FRED (Chemgauss4), and SAHA-3 sequentially, and demonstrated that it was superior to other combinations in terms of ligand enrichment. In summary, we present the first highly-validated, rationally-designed VS strategy specific to HDAC3 inhibitor discovery. The constructed pipeline is publicly accessible for the scientific community to identify novel HDAC3 inhibitors in a time-efficient and cost-effective way.

A Thoroughly Validated Virtual Screening Strategy for Discovery of Novel HDAC3 Inhibitors

PubMed Central

Hu, Huabin; Xia, Jie; Wang, Dongmei; Wang, Xiang Simon; Wu, Song

2017-01-01

Histone deacetylase 3 (HDAC3) has been recently identified as a potential target for the treatment of cancer and other diseases, such as chronic inflammation, neurodegenerative diseases, and diabetes. Virtual screening (VS) is currently a routine technique for hit identification, but its success depends on rational development of VS strategies. To facilitate this process, we applied our previously released benchmarking dataset, i.e., MUBD-HDAC3 to the evaluation of structure-based VS (SBVS) and ligand-based VS (LBVS) combinatorial approaches. We have identified FRED (Chemgauss4) docking against a structural model of HDAC3, i.e., SAHA-3 generated by a computationally inexpensive “flexible docking”, as the best SBVS approach and a common feature pharmacophore model, i.e., Hypo1 generated by Catalyst/HipHop as the optimal model for LBVS. We then developed a pipeline that was composed of Hypo1, FRED (Chemgauss4), and SAHA-3 sequentially, and demonstrated that it was superior to other combinations in terms of ligand enrichment. In summary, we present the first highly-validated, rationally-designed VS strategy specific to HDAC3 inhibitor discovery. The constructed pipeline is publicly accessible for the scientific community to identify novel HDAC3 inhibitors in a time-efficient and cost-effective way. PMID:28106794

Discovery of Novel MDR-Mycobacterium tuberculosis Inhibitor by New FRIGATE Computational Screen

PubMed Central

Vértessy, Beáta; Pütter, Vera; Grolmusz, Vince; Schade, Markus

2011-01-01

With 1.6 million casualties annually and 2 billion people being infected, tuberculosis is still one of the most pressing healthcare challenges. Here we report on the new computational docking algorithm FRIGATE which unites continuous local optimization techniques (conjugate gradient method) with an inherently discrete computational approach in forcefield computation, resulting in equal or better scoring accuracies than several benchmark docking programs. By utilizing FRIGATE for a virtual screen of the ZINC library against the Mycobacterium tuberculosis (Mtb) enzyme antigen 85C, we identified novel small molecule inhibitors of multiple drug-resistant Mtb, which bind in vitro to the catalytic site of antigen 85C. PMID:22164290

Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios.

PubMed

Hristozov, Dimitar P; Oprea, Tudor I; Gasteiger, Johann

2007-01-01

Four different ligand-based virtual screening scenarios are studied: (1) prioritizing compounds for subsequent high-throughput screening (HTS); (2) selecting a predefined (small) number of potentially active compounds from a large chemical database; (3) assessing the probability that a given structure will exhibit a given activity; (4) selecting the most active structure(s) for a biological assay. Each of the four scenarios is exemplified by performing retrospective ligand-based virtual screening for eight different biological targets using two large databases--MDDR and WOMBAT. A comparison between the chemical spaces covered by these two databases is presented. The performance of two techniques for ligand--based virtual screening--similarity search with subsequent data fusion (SSDF) and novelty detection with Self-Organizing Maps (ndSOM) is investigated. Three different structure representations--2,048-dimensional Daylight fingerprints, topological autocorrelation weighted by atomic physicochemical properties (sigma electronegativity, polarizability, partial charge, and identity) and radial distribution functions weighted by the same atomic physicochemical properties--are compared. Both methods were found applicable in scenario one. The similarity search was found to perform slightly better in scenario two while the SOM novelty detection is preferred in scenario three. No method/descriptor combination achieved significant success in scenario four.

Identification of a New Isoindole-2-yl Scaffold as a Qo and Qi Dual Inhibitor of Cytochrome bc 1 Complex: Virtual Screening, Synthesis, and Biochemical Assay.

PubMed

Azizian, Homa; Bagherzadeh, Kowsar; Shahbazi, Sophia; Sharifi, Niusha; Amanlou, Massoud

2017-09-18

Respiratory chain ubiquinol-cytochrome (cyt) c oxidoreductase (cyt bc 1 or complex III) has been demonstrated as a promising target for numerous antibiotics and fungicide applications. In this study, a virtual screening of NCI diversity database was carried out in order to find novel Qo/Qi cyt bc 1 complex inhibitors. Structure-based virtual screening and molecular docking methodology were employed to further screen compounds with inhibition activity against cyt bc 1 complex after extensive reliability validation protocol with cross-docking method and identification of the best score functions. Subsequently, the application of rational filtering procedure over the target database resulted in the elucidation of a novel class of cyt bc 1 complex potent inhibitors with comparable binding energies and biological activities to those of the standard inhibitor, antimycin.

The influence of negative training set size on machine learning-based virtual screening.

PubMed

Kurczab, Rafał; Smusz, Sabina; Bojarski, Andrzej J

2014-01-01

The paper presents a thorough analysis of the influence of the number of negative training examples on the performance of machine learning methods. The impact of this rather neglected aspect of machine learning methods application was examined for sets containing a fixed number of positive and a varying number of negative examples randomly selected from the ZINC database. An increase in the ratio of positive to negative training instances was found to greatly influence most of the investigated evaluating parameters of ML methods in simulated virtual screening experiments. In a majority of cases, substantial increases in precision and MCC were observed in conjunction with some decreases in hit recall. The analysis of dynamics of those variations let us recommend an optimal composition of training data. The study was performed on several protein targets, 5 machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest) and 2 types of molecular fingerprints (MACCS and CDK FP). The most effective classification was provided by the combination of CDK FP with SMO or Random Forest algorithms. The Naïve Bayes models appeared to be hardly sensitive to changes in the number of negative instances in the training set. In conclusion, the ratio of positive to negative training instances should be taken into account during the preparation of machine learning experiments, as it might significantly influence the performance of particular classifier. What is more, the optimization of negative training set size can be applied as a boosting-like approach in machine learning-based virtual screening.

The influence of negative training set size on machine learning-based virtual screening

PubMed Central

2014-01-01

Background The paper presents a thorough analysis of the influence of the number of negative training examples on the performance of machine learning methods. Results The impact of this rather neglected aspect of machine learning methods application was examined for sets containing a fixed number of positive and a varying number of negative examples randomly selected from the ZINC database. An increase in the ratio of positive to negative training instances was found to greatly influence most of the investigated evaluating parameters of ML methods in simulated virtual screening experiments. In a majority of cases, substantial increases in precision and MCC were observed in conjunction with some decreases in hit recall. The analysis of dynamics of those variations let us recommend an optimal composition of training data. The study was performed on several protein targets, 5 machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest) and 2 types of molecular fingerprints (MACCS and CDK FP). The most effective classification was provided by the combination of CDK FP with SMO or Random Forest algorithms. The Naïve Bayes models appeared to be hardly sensitive to changes in the number of negative instances in the training set. Conclusions In conclusion, the ratio of positive to negative training instances should be taken into account during the preparation of machine learning experiments, as it might significantly influence the performance of particular classifier. What is more, the optimization of negative training set size can be applied as a boosting-like approach in machine learning-based virtual screening. PMID:24976867

Thoracic, Lumbar, and Sacral Pedicle Screw Placement Using Stryker-Ziehm Virtual Screw Technology and Navigated Stryker Cordless Driver 3: Technical Note.

PubMed

Satarasinghe, Praveen; Hamilton, Kojo D; Tarver, Michael J; Buchanan, Robert J; Koltz, Michael T

2018-04-17

Utilization of pedicle screws (PS) for spine stabilization is common in spinal surgery. With reliance on visual inspection of anatomical landmarks prior to screw placement, the free-hand technique requires a high level of surgeon skill and precision. Three-dimensional (3D), computer-assisted virtual neuronavigation improves the precision of PS placement and minimization steps. Twenty-three patients with degenerative, traumatic, or neoplastic pathologies received treatment via a novel three-step PS technique that utilizes a navigated power driver in combination with virtual screw technology. (1) Following visualization of neuroanatomy using intraoperative CT, a navigated 3-mm match stick drill bit was inserted at an anatomical entry point with a screen projection showing a virtual screw. (2) A Navigated Stryker Cordless Driver with an appropriate tap was used to access the vertebral body through a pedicle with a screen projection again showing a virtual screw. (3) A Navigated Stryker Cordless Driver with an actual screw was used with a screen projection showing the same virtual screw. One hundred and forty-four consecutive screws were inserted using this three-step, navigated driver, virtual screw technique. Only 1 screw needed intraoperative revision after insertion using the three-step, navigated driver, virtual PS technique. This amounts to a 0.69% revision rate. One hundred percent of patients had intraoperative CT reconstructed images taken to confirm hardware placement. Pedicle screw placement utilizing the Stryker-Ziehm neuronavigation virtual screw technology with a three step, navigated power drill technique is safe and effective.

Chemogenomics profiling of drug targets of peptidoglycan biosynthesis pathway in Leptospira interrogans by virtual screening approaches.

PubMed

Bhattacharjee, Biplab; Simon, Rose Mary; Gangadharaiah, Chaithra; Karunakar, Prashantha

2013-06-28

Leptospirosis is a worldwide zoonosis of global concern caused by Leptospira interrogans. The availability of ligand libraries has facilitated the search for novel drug targets using chemogenomics approaches, compared with the traditional method of drug discovery, which is time consuming and yields few leads with little intracellular information for guiding target selection. Recent subtractive genomics studies have revealed the putative drug targets in peptidoglycan biosynthesis pathways in Leptospira interrogans. Aligand library for the murD ligase enzyme in the peptidoglycan pathway has also been identified. Our approach in this research involves screening of the pre-existing ligand library of murD with related protein family members in the putative drug target assembly in the peptidoglycan biosynthesis pathway. A chemogenomics approach has been implemented here, which involves screening of known ligands of a protein family having analogous domain architecture for identification of leads for existing druggable protein family members. By means of this approach, one murC and one murF inhibitor were identified, providing a platform for developing an antileptospirosis drug targeting the peptidoglycan biosynthesis pathway. Given that the peptidoglycan biosynthesis pathway is exclusive to bacteria, the in silico identified mur ligase inhibitors are expected to be broad-spectrum Gram-negative inhibitors if synthesized and tested in in vitro and in vivo assays.

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models.

PubMed

Boppana, Kiran; Dubey, P K; Jagarlapudi, Sarma A R P; Vadivelan, S; Rambabu, G

2009-09-01

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

Composing compound libraries for hit discovery--rationality-driven preselection or random choice by structural diversity?

PubMed

Weidel, Elisabeth; Negri, Matthias; Empting, Martin; Hinsberger, Stefan; Hartmann, Rolf W

2014-01-01

In order to identify new scaffolds for drug discovery, surface plasmon resonance is frequently used to screen structurally diverse libraries. Usually, hit rates are low and identification processes are time consuming. Hence, approaches which improve hit rates and, thus, reduce the library size are required. In this work, we studied three often used strategies for their applicability to identify inhibitors of PqsD. In two of them, target-specific aspects like inhibition of a homologous protein or predicted binding determined by virtual screening were used for compound preselection. Finally, a fragment library, covering a large chemical space, was screened and served as comparison. Indeed, higher hit rates were observed for methods employing preselected libraries indicating that target-oriented compound selection provides a time-effective alternative.

Assessment of wheelchair driving performance in a virtual reality-based simulator

PubMed Central

Mahajan, Harshal P.; Dicianno, Brad E.; Cooper, Rory A.; Ding, Dan

2013-01-01

Objective To develop a virtual reality (VR)-based simulator that can assist clinicians in performing standardized wheelchair driving assessments. Design A completely within-subjects repeated measures design. Methods Participants drove their wheelchairs along a virtual driving circuit modeled after the Power Mobility Road Test (PMRT) and in a hallway with decreasing width. The virtual simulator was displayed on computer screen and VR screens and participants interacted with it using a set of instrumented rollers and a wheelchair joystick. Driving performances of participants were estimated and compared using quantitative metrics from the simulator. Qualitative ratings from two experienced clinicians were used to estimate intra- and inter-rater reliability. Results Ten regular wheelchair users (seven men, three women; mean age ± SD, 39.5 ± 15.39 years) participated. The virtual PMRT scores from the two clinicians show high inter-rater reliability (78–90%) and high intra-rater reliability (71–90%) for all test conditions. More research is required to explore user preferences and effectiveness of the two control methods (rollers and mathematical model) and the display screens. Conclusions The virtual driving simulator seems to be a promising tool for wheelchair driving assessment that clinicians can use to supplement their real-world evaluations. PMID:23820148

Virtual screening using molecular simulations.

PubMed

Yang, Tianyi; Wu, Johnny C; Yan, Chunli; Wang, Yuanfeng; Luo, Ray; Gonzales, Michael B; Dalby, Kevin N; Ren, Pengyu

2011-06-01

Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery. Copyright © 2011 Wiley-Liss, Inc.

Investigation of MM-PBSA rescoring of docking poses.

PubMed

Thompson, David C; Humblet, Christine; Joseph-McCarthy, Diane

2008-05-01

Target-based virtual screening is increasingly used to generate leads for targets for which high quality three-dimensional (3D) structures are available. To allow large molecular databases to be screened rapidly, a tiered scoring scheme is often employed whereby a simple scoring function is used as a fast filter of the entire database and a more rigorous and time-consuming scoring function is used to rescore the top hits to produce the final list of ranked compounds. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approaches are currently thought to be quite effective at incorporating implicit solvation into the estimation of ligand binding free energies. In this paper, the ability of a high-throughput MM-PBSA rescoring function to discriminate between correct and incorrect docking poses is investigated in detail. Various initial scoring functions are used to generate docked poses for a subset of the CCDC/Astex test set and to dock one set of actives/inactives from the DUD data set. The effectiveness of each of these initial scoring functions is discussed. Overall, the ability of the MM-PBSA rescoring function to (i) regenerate the set of X-ray complexes when docking the bound conformation of the ligand, (ii) regenerate the X-ray complexes when docking conformationally expanded databases for each ligand which include "conformation decoys" of the ligand, and (iii) enrich known actives in a virtual screen for the mineralocorticoid receptor in the presence of "ligand decoys" is assessed. While a pharmacophore-based molecular docking approach, PhDock, is used to carry out the docking, the results are expected to be general to use with any docking method.

The Role of Affordances in Children's Learning Performance and Efficiency When Using Virtual Manipulative Mathematics Touch-Screen Apps

ERIC Educational Resources Information Center

Moyer-Packenham, Patricia S.; Bullock, Emma K.; Shumway, Jessica F.; Tucker, Stephen I.; Watts, Christina M.; Westenskow, Arla; Anderson-Pence, Katie L.; Maahs-Fladung, Cathy; Boyer-Thurgood, Jennifer; Gulkilik, Hilal; Jordan, Kerry

2016-01-01

This paper focuses on understanding the role that affordances played in children's learning performance and efficiency during clinical interviews of their interactions with mathematics apps on touch-screen devices. One hundred children, ages 3 to 8, each used six different virtual manipulative mathematics apps during 30-40-min interviews. The…

Virtual Screening and Pharmacophore Design for a Novel Theoretical Inhibitor of Macrophage Stimulating Factor as a Metastatic Agent

PubMed Central

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Introduction: Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Methods: Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. Results: The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Conclusion: Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies. PMID:24163807

Hit Identification and Optimization in Virtual Screening: Practical Recommendations Based Upon a Critical Literature Analysis

PubMed Central

Zhu, Tian; Cao, Shuyi; Su, Pin-Chih; Patel, Ram; Shah, Darshan; Chokshi, Heta B.; Szukala, Richard; Johnson, Michael E.; Hevener, Kirk E.

2013-01-01

A critical analysis of virtual screening results published between 2007 and 2011 was performed. The activity of reported hit compounds from over 400 studies was compared to their hit identification criteria. Hit rates and ligand efficiencies were calculated to assist in these analyses and the results were compared with factors such as the size of the virtual library and the number of compounds tested. A series of promiscuity, drug-like, and ADMET filters were applied to the reported hits to assess the quality of compounds reported and a careful analysis of a subset of the studies which presented hit optimization was performed. This data allowed us to make several practical recommendations with respect to selection of compounds for experimental testing, defining hit identification criteria, and general virtual screening hit criteria to allow for realistic hit optimization. A key recommendation is the use of size-targeted ligand efficiency values as hit identification criteria. PMID:23688234

A Fragment-Based Ligand Screen Against Part of a Large Protein Machine: The ND1 Domains of the AAA+ ATPase p97/VCP.

PubMed

Chimenti, Michael S; Bulfer, Stacie L; Neitz, R Jeffrey; Renslo, Adam R; Jacobson, Matthew P; James, Thomas L; Arkin, Michelle R; Kelly, Mark J S

2015-07-01

The ubiquitous AAA+ ATPase p97 functions as a dynamic molecular machine driving several cellular processes. It is essential in regulating protein homeostasis, and it represents a potential drug target for cancer, particularly when there is a greater reliance on the endoplasmic reticulum-associated protein degradation pathway and ubiquitin-proteasome pathway to degrade an overabundance of secreted proteins. Here, we report a case study for using fragment-based ligand design approaches against this large and dynamic hexamer, which has multiple potential binding sites for small molecules. A screen of a fragment library was conducted by surface plasmon resonance (SPR) and followed up by nuclear magnetic resonance (NMR), two complementary biophysical techniques. Virtual screening was also carried out to examine possible binding sites for the experimental hits and evaluate the potential utility of fragment docking for this target. Out of this effort, 13 fragments were discovered that showed reversible binding with affinities between 140 µM and 1 mM, binding stoichiometries of 1:1 or 2:1, and good ligand efficiencies. Structural data for fragment-protein interactions were obtained with residue-specific [U-(2)H] (13)CH3-methyl-labeling NMR strategies, and these data were compared to poses from docking. The combination of virtual screening, SPR, and NMR enabled us to find and validate a number of interesting fragment hits and allowed us to gain an understanding of the structural nature of fragment binding. © 2015 Society for Laboratory Automation and Screening.

Discovery of new GSK-3β inhibitors through structure-based virtual screening.

PubMed

Dou, Xiaodong; Jiang, Lan; Wang, Yanxing; Jin, Hongwei; Liu, Zhenming; Zhang, Liangren

2018-01-15

Glycogen synthase kinase-3β (GSK-3β) is an attractive therapeutic target for human diseases, such as diabetes, cancer, neurodegenerative diseases, and inflammation. Thus, structure-based virtual screening was performed to identify novel scaffolds of GSK-3β inhibitors, and we observed that conserved water molecules of GSK-3β were suitable for virtual screening. We found 14 hits and D1 (IC 50 of 0.71 μM) were identified. Furthermore, the neuroprotection activity of D1-D3 was validated on a cellular level. 2D similarity searches were used to find derivatives of high inhibitory compounds and an enriched structure-activity relationship suggested that these skeletons were worthy of study as potent GSK-3β inhibitors. Copyright © 2017. Published by Elsevier Ltd.

A collaborative virtual reality environment for neurosurgical planning and training.

PubMed

Kockro, Ralf A; Stadie, Axel; Schwandt, Eike; Reisch, Robert; Charalampaki, Cleopatra; Ng, Ivan; Yeo, Tseng Tsai; Hwang, Peter; Serra, Luis; Perneczky, Axel

2007-11-01

We have developed a highly interactive virtual environment that enables collaborative examination of stereoscopic three-dimensional (3-D) medical imaging data for planning, discussing, or teaching neurosurgical approaches and strategies. The system consists of an interactive console with which the user manipulates 3-D data using hand-held and tracked devices within a 3-D virtual workspace and a stereoscopic projection system. The projection system displays the 3-D data on a large screen while the user is working with it. This setup allows users to interact intuitively with complex 3-D data while sharing this information with a larger audience. We have been using this system on a routine clinical basis and during neurosurgical training courses to collaboratively plan and discuss neurosurgical procedures with 3-D reconstructions of patient-specific magnetic resonance and computed tomographic imaging data or with a virtual model of the temporal bone. Working collaboratively with the 3-D information of a large, interactive, stereoscopic projection provides an unambiguous way to analyze and understand the anatomic spatial relationships of different surgical corridors. In our experience, the system creates a unique forum for open and precise discussion of neurosurgical approaches. We believe the system provides a highly effective way to work with 3-D data in a group, and it significantly enhances teaching of neurosurgical anatomy and operative strategies.

QSAR-Driven Design and Discovery of Novel Compounds With Antiplasmodial and Transmission Blocking Activities.

PubMed

Lima, Marilia N N; Melo-Filho, Cleber C; Cassiano, Gustavo C; Neves, Bruno J; Alves, Vinicius M; Braga, Rodolpho C; Cravo, Pedro V L; Muratov, Eugene N; Calit, Juliana; Bargieri, Daniel Y; Costa, Fabio T M; Andrade, Carolina H

2018-01-01

Malaria is a life-threatening infectious disease caused by parasites of the genus Plasmodium , affecting more than 200 million people worldwide every year and leading to about a half million deaths. Malaria parasites of humans have evolved resistance to all current antimalarial drugs, urging for the discovery of new effective compounds. Given that the inhibition of deoxyuridine triphosphatase of Plasmodium falciparum ( Pf dUTPase) induces wrong insertions in plasmodial DNA and consequently leading the parasite to death, this enzyme is considered an attractive antimalarial drug target. Using a combi-QSAR (quantitative structure-activity relationship) approach followed by virtual screening and in vitro experimental evaluation, we report herein the discovery of novel chemical scaffolds with in vitro potency against asexual blood stages of both P. falciparum multidrug-resistant and sensitive strains and against sporogonic development of P. berghei . We developed 2D- and 3D-QSAR models using a series of nucleosides reported in the literature as Pf dUTPase inhibitors. The best models were combined in a consensus approach and used for virtual screening of the ChemBridge database, leading to the identification of five new virtual Pf dUTPase inhibitors. Further in vitro testing on P. falciparum multidrug-resistant (W2) and sensitive (3D7) parasites showed that compounds LabMol-144 and LabMol-146 demonstrated fair activity against both strains and presented good selectivity versus mammalian cells. In addition, LabMol-144 showed good in vitro inhibition of P. berghei ookinete formation, demonstrating that hit-to-lead optimization based on this compound may also lead to new antimalarials with transmission blocking activity.

A method for evaluating the performance of computer-aided detection of pulmonary nodules in lung cancer CT screening: detection limit for nodule size and density

PubMed Central

Kobayashi, Hajime; Ohkubo, Masaki; Narita, Akihiro; Marasinghe, Janaka C; Murao, Kohei; Matsumoto, Toru; Sone, Shusuke

2017-01-01

Objective: We propose the application of virtual nodules to evaluate the performance of computer-aided detection (CAD) of lung nodules in cancer screening using low-dose CT. Methods: The virtual nodules were generated based on the spatial resolution measured for a CT system used in an institution providing cancer screening and were fused into clinical lung images obtained at that institution, allowing site specificity. First, we validated virtual nodules as an alternative to artificial nodules inserted into a phantom. In addition, we compared the results of CAD analysis between the real nodules (n = 6) and the corresponding virtual nodules. Subsequently, virtual nodules of various sizes and contrasts between nodule density and background density (ΔCT) were inserted into clinical images (n = 10) and submitted for CAD analysis. Results: In the validation study, 46 of 48 virtual nodules had the same CAD results as artificial nodules (kappa coefficient = 0.913). Real nodules and the corresponding virtual nodules showed the same CAD results. The detection limits of the tested CAD system were determined in terms of size and density of peripheral lung nodules; we demonstrated that a nodule with a 5-mm diameter was detected when the nodule had a ΔCT > 220 HU. Conclusion: Virtual nodules are effective in evaluating CAD performance using site-specific scan/reconstruction conditions. Advances in knowledge: Virtual nodules can be an effective means of evaluating site-specific CAD performance. The methodology for guiding the detection limit for nodule size/density might be a useful evaluation strategy. PMID:27897029

A structure-based virtual screening approach toward the discovery of histone deacetylase inhibitors: identification of promising zinc-chelating groups.

PubMed

Park, Hwangseo; Kim, Sukyoung; Kim, Yong Eun; Lim, Soo-Jeong

2010-04-06

The inhibitors of histone deacetylases (HDACs) have drawn a great deal of attention due to their promising potential as small-molecule therapeutics for the treatment of cancer. By means of virtual screening with docking simulations under consideration of the effects of ligand solvation, we were able to identify six novel HDAC inhibitors with IC(50) values ranging from 1 to 100 muM. These newly identified inhibitors are structurally diverse and have various chelating groups for the active site zinc ion, including N-[1,3,4]thiadiazol-2-yl sulfonamide, N-thiazol-2-yl sulfonamide, and hydroxamic acid moieties. The former two groups are included in many drugs in current clinical use and have not yet been reported as HDAC inhibitors. Therefore, they can be considered as new inhibitor scaffolds for the development of anticancer drugs by structure-activity relationship studies to improve the inhibitory activities against HDACs. Interactions with the HDAC1 active site residues responsible for stabilizing these new inhibitors are addressed in detail.

Evaluation and optimization of virtual screening workflows with DEKOIS 2.0--a public library of challenging docking benchmark sets.

PubMed

Bauer, Matthias R; Ibrahim, Tamer M; Vogel, Simon M; Boeckler, Frank M

2013-06-24

The application of molecular benchmarking sets helps to assess the actual performance of virtual screening (VS) workflows. To improve the efficiency of structure-based VS approaches, the selection and optimization of various parameters can be guided by benchmarking. With the DEKOIS 2.0 library, we aim to further extend and complement the collection of publicly available decoy sets. Based on BindingDB bioactivity data, we provide 81 new and structurally diverse benchmark sets for a wide variety of different target classes. To ensure a meaningful selection of ligands, we address several issues that can be found in bioactivity data. We have improved our previously introduced DEKOIS methodology with enhanced physicochemical matching, now including the consideration of molecular charges, as well as a more sophisticated elimination of latent actives in the decoy set (LADS). We evaluate the docking performance of Glide, GOLD, and AutoDock Vina with our data sets and highlight existing challenges for VS tools. All DEKOIS 2.0 benchmark sets will be made accessible at http://www.dekois.com.

Grid heterogeneity in in-silico experiments: an exploration of drug screening using DOCK on cloud environments.

PubMed

Yim, Wen-Wai; Chien, Shu; Kusumoto, Yasuyuki; Date, Susumu; Haga, Jason

2010-01-01

Large-scale in-silico screening is a necessary part of drug discovery and Grid computing is one answer to this demand. A disadvantage of using Grid computing is the heterogeneous computational environments characteristic of a Grid. In our study, we have found that for the molecular docking simulation program DOCK, different clusters within a Grid organization can yield inconsistent results. Because DOCK in-silico virtual screening (VS) is currently used to help select chemical compounds to test with in-vitro experiments, such differences have little effect on the validity of using virtual screening before subsequent steps in the drug discovery process. However, it is difficult to predict whether the accumulation of these discrepancies over sequentially repeated VS experiments will significantly alter the results if VS is used as the primary means for identifying potential drugs. Moreover, such discrepancies may be unacceptable for other applications requiring more stringent thresholds. This highlights the need for establishing a more complete solution to provide the best scientific accuracy when executing an application across Grids. One possible solution to platform heterogeneity in DOCK performance explored in our study involved the use of virtual machines as a layer of abstraction. This study investigated the feasibility and practicality of using virtual machine and recent cloud computing technologies in a biological research application. We examined the differences and variations of DOCK VS variables, across a Grid environment composed of different clusters, with and without virtualization. The uniform computer environment provided by virtual machines eliminated inconsistent DOCK VS results caused by heterogeneous clusters, however, the execution time for the DOCK VS increased. In our particular experiments, overhead costs were found to be an average of 41% and 2% in execution time for two different clusters, while the actual magnitudes of the execution time costs were minimal. Despite the increase in overhead, virtual clusters are an ideal solution for Grid heterogeneity. With greater development of virtual cluster technology in Grid environments, the problem of platform heterogeneity may be eliminated through virtualization, allowing greater usage of VS, and will benefit all Grid applications in general.

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.

Combination of Pharmacophore Matching, 2D Similarity Search, and In Vitro Biological Assays in the Selection of Potential 5-HT6 Antagonists from Large Commercial Repositories.

PubMed

Dobi, Krisztina; Flachner, Beáta; Pukáncsik, Mária; Máthé, Enikő; Bognár, Melinda; Szaszkó, Mária; Magyar, Csaba; Hajdú, István; Lőrincz, Zsolt; Simon, István; Fülöp, Ferenc; Cseh, Sándor; Dormán, György

2015-10-01

Rapid in silico selection of target-focused libraries from commercial repositories is an attractive and cost-effective approach. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compound databases, but the generated library requires further focusing. We report here a combination of the 2D approach with pharmacophore matching which was used for selecting 5-HT6 antagonists. In the first screening round, 12 compounds showed >85% antagonist efficacy of the 91 screened. For the second-round (hit validation) screening phase, pharmacophore models were built, applied, and compared with the routine 2D similarity search. Three pharmacophore models were created based on the structure of the reference compounds and the first-round hit compounds. The pharmacophore search resulted in a high hit rate (40%) and led to novel chemotypes, while 2D similarity search had slightly better hit rate (51%), but lacking the novelty. To demonstrate the power of the virtual screening cascade, ligand efficiency indices were also calculated and their steady improvement was confirmed. © 2015 John Wiley & Sons A/S.

Virtual screening and optimization of Type II inhibitors of JAK2 from a natural product library.

PubMed

Ma, Dik-Lung; Chan, Daniel Shiu-Hin; Wei, Guo; Zhong, Hai-Jing; Yang, Hui; Leung, Lai To; Gullen, Elizabeth A; Chiu, Pauline; Cheng, Yung-Chi; Leung, Chung-Hang

2014-11-21

Amentoflavone has been identified as a JAK2 inhibitor by structure-based virtual screening of a natural product library. In silico optimization using the DOLPHIN model yielded analogues with enhanced potency against JAK2 activity and HCV activity in cellulo. Molecular modeling and kinetic experiments suggested that the analogues may function as Type II inhibitors of JAK2.

MegaMiner: A Tool for Lead Identification Through Text Mining Using Chemoinformatics Tools and Cloud Computing Environment.

PubMed

Karthikeyan, Muthukumarasamy; Pandit, Yogesh; Pandit, Deepak; Vyas, Renu

2015-01-01

Virtual screening is an indispensable tool to cope with the massive amount of data being tossed by the high throughput omics technologies. With the objective of enhancing the automation capability of virtual screening process a robust portal termed MegaMiner has been built using the cloud computing platform wherein the user submits a text query and directly accesses the proposed lead molecules along with their drug-like, lead-like and docking scores. Textual chemical structural data representation is fraught with ambiguity in the absence of a global identifier. We have used a combination of statistical models, chemical dictionary and regular expression for building a disease specific dictionary. To demonstrate the effectiveness of this approach, a case study on malaria has been carried out in the present work. MegaMiner offered superior results compared to other text mining search engines, as established by F score analysis. A single query term 'malaria' in the portlet led to retrieval of related PubMed records, protein classes, drug classes and 8000 scaffolds which were internally processed and filtered to suggest new molecules as potential anti-malarials. The results obtained were validated by docking the virtual molecules into relevant protein targets. It is hoped that MegaMiner will serve as an indispensable tool for not only identifying hidden relationships between various biological and chemical entities but also for building better corpus and ontologies.

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

Evaluation of a novel virtual screening strategy using receptor decoy binding sites.

PubMed

Patel, Hershna; Kukol, Andreas

2016-08-23

Virtual screening is used in biomedical research to predict the binding affinity of a large set of small organic molecules to protein receptor targets. This report shows the development and evaluation of a novel yet straightforward attempt to improve this ranking in receptor-based molecular docking using a receptor-decoy strategy. This strategy includes defining a decoy binding site on the receptor and adjusting the ranking of the true binding-site virtual screen based on the decoy-site screen. The results show that by docking against a receptor-decoy site with Autodock Vina, improved Receiver Operator Characteristic Enrichment (ROCE) was achieved for 5 out of fifteen receptor targets investigated, when up to 15 % of a decoy site rank list was considered. No improved enrichment was seen for 7 targets, while for 3 targets the ROCE was reduced. The extent to which this strategy can effectively improve ligand prediction is dependent on the target receptor investigated.

Novel Inhibitors of Mycobacterium tuberculosis dTDP-6-deoxy-L-lyxo-4-hexulose Reductase (RmlD) Identified by Virtual Screening

PubMed Central

Wang, Yi; Hess, Tamara Noelle; Jones, Victoria; Zhou, Joe Zhongxiang; McNeil, Michael R.; McCammon, J. Andrew

2011-01-01

The complex and highly impermeable cell wall of Mycobacterium tuberculosis (Mtb) is largely responsible for the ability of the mycobacterium to resist the action of chemical therapeutics. An L-rhamnosyl residue, which occupies an important anchoring position in the Mtb cell wall, is an attractive target for novel anti-tuberculosis drugs. In this work, we report a virtual screening (VS) study targeting Mtb dTDP-deoxy-L-lyxo-4-hexulose reductase (RmlD), the last enzyme in the L-rhamnosyl synthesis pathway. Through two rounds of VS, we have identified four RmlD inhibitors with half inhibitory concentrations of 0.9-25 μM, and whole-cell minimum inhibitory concentrations of 20-200 μg/ml. Compared with our previous high throughput screening targeting another enzyme involved in L-rhamnosyl synthesis, virtual screening produced higher hit rates, supporting the use of computational methods in future anti-tuberculosis drug discovery efforts. PMID:22014548

A cross docking pipeline for improving pose prediction and virtual screening performance

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2018-01-01

Pose prediction and virtual screening performance of a molecular docking method depend on the choice of protein structures used for docking. Multiple structures for a target protein are often used to take into account the receptor flexibility and problems associated with a single receptor structure. However, the use of multiple receptor structures is computationally expensive when docking a large library of small molecules. Here, we propose a new cross-docking pipeline suitable to dock a large library of molecules while taking advantage of multiple target protein structures. Our method involves the selection of a suitable receptor for each ligand in a screening library utilizing ligand 3D shape similarity with crystallographic ligands. We have prospectively evaluated our method in D3R Grand Challenge 2 and demonstrated that our cross-docking pipeline can achieve similar or better performance than using either single or multiple-receptor structures. Moreover, our method displayed not only decent pose prediction performance but also better virtual screening performance over several other methods.

Search for β2 Adrenergic Receptor Ligands by Virtual Screening via Grid Computing and Investigation of Binding Modes by Docking and Molecular Dynamics Simulations

PubMed Central

Bai, Qifeng; Shao, Yonghua; Pan, Dabo; Zhang, Yang; Liu, Huanxiang; Yao, Xiaojun

2014-01-01

We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD) simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR) from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551). The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com. PMID:25229694

Pharmacophore modeling, docking, and principal component analysis based clustering: combined computer-assisted approaches to identify new inhibitors of the human rhinovirus coat protein.

PubMed

Steindl, Theodora M; Crump, Carolyn E; Hayden, Frederick G; Langer, Thierry

2005-10-06

The development and application of a sophisticated virtual screening and selection protocol to identify potential, novel inhibitors of the human rhinovirus coat protein employing various computer-assisted strategies are described. A large commercially available database of compounds was screened using a highly selective, structure-based pharmacophore model generated with the program Catalyst. A docking study and a principal component analysis were carried out within the software package Cerius and served to validate and further refine the obtained results. These combined efforts led to the selection of six candidate structures, for which in vitro anti-rhinoviral activity could be shown in a biological assay.

IspE Inhibitors Identified by a Combination of In Silico and In Vitro High-Throughput Screening

PubMed Central

Tidten-Luksch, Naomi; Grimaldi, Raffaella; Torrie, Leah S.; Frearson, Julie A.; Hunter, William N.; Brenk, Ruth

2012-01-01

CDP-ME kinase (IspE) contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP) pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens. PMID:22563402

Virtual screening with AutoDock Vina and the common pharmacophore engine of a low diversity library of fragments and hits against the three allosteric sites of HIV integrase: participation in the SAMPL4 protein-ligand binding challenge

NASA Astrophysics Data System (ADS)

Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Santos-Martins, Diogo; Olson, Arthur J.

2014-04-01

To rigorously assess the tools and protocols that can be used to understand and predict macromolecular recognition, and to gain more structural insight into three newly discovered allosteric binding sites on a critical drug target involved in the treatment of HIV infections, the Olson and Levy labs collaborated on the SAMPL4 challenge. This computational blind challenge involved predicting protein-ligand binding against the three allosteric sites of HIV integrase (IN), a viral enzyme for which two drugs (that target the active site) have been approved by the FDA. Positive control cross-docking experiments were utilized to select 13 receptor models out of an initial ensemble of 41 different crystal structures of HIV IN. These 13 models of the targets were selected using our new "Rank Difference Ratio" metric. The first stage of SAMPL4 involved using virtual screens to identify 62 active, allosteric IN inhibitors out of a set of 321 compounds. The second stage involved predicting the binding site(s) and crystallographic binding mode(s) for 57 of these inhibitors. Our team submitted four entries for the first stage that utilized: (1) AutoDock Vina (AD Vina) plus visual inspection; (2) a new common pharmacophore engine; (3) BEDAM replica exchange free energy simulations, and a Consensus approach that combined the predictions of all three strategies. Even with the SAMPL4's very challenging compound library that displayed a significantly lower amount of structural diversity than most libraries that are conventionally employed in prospective virtual screens, these approaches produced hit rates of 24, 25, 34, and 27 %, respectively, on a set with 19 % declared binders. Our only entry for the second stage challenge was based on the results of AD Vina plus visual inspection, and it ranked third place overall according to several different metrics provided by the SAMPL4 organizers. The successful results displayed by these approaches highlight the utility of the computational structure-based drug discovery tools and strategies that are being developed to advance the goals of the newly created, multi-institution, NIH-funded center called the "HIV Interaction and Viral Evolution Center".

Virtual screening with AutoDock Vina and the common pharmacophore engine of a low diversity library of fragments and hits against the three allosteric sites of HIV integrase: participation in the SAMPL4 protein-ligand binding challenge.

PubMed

Perryman, Alexander L; Santiago, Daniel N; Forli, Stefano; Martins, Diogo Santos; Olson, Arthur J

2014-04-01

To rigorously assess the tools and protocols that can be used to understand and predict macromolecular recognition, and to gain more structural insight into three newly discovered allosteric binding sites on a critical drug target involved in the treatment of HIV infections, the Olson and Levy labs collaborated on the SAMPL4 challenge. This computational blind challenge involved predicting protein-ligand binding against the three allosteric sites of HIV integrase (IN), a viral enzyme for which two drugs (that target the active site) have been approved by the FDA. Positive control cross-docking experiments were utilized to select 13 receptor models out of an initial ensemble of 41 different crystal structures of HIV IN. These 13 models of the targets were selected using our new "Rank Difference Ratio" metric. The first stage of SAMPL4 involved using virtual screens to identify 62 active, allosteric IN inhibitors out of a set of 321 compounds. The second stage involved predicting the binding site(s) and crystallographic binding mode(s) for 57 of these inhibitors. Our team submitted four entries for the first stage that utilized: (1) AutoDock Vina (AD Vina) plus visual inspection; (2) a new common pharmacophore engine; (3) BEDAM replica exchange free energy simulations, and a Consensus approach that combined the predictions of all three strategies. Even with the SAMPL4's very challenging compound library that displayed a significantly lower amount of structural diversity than most libraries that are conventionally employed in prospective virtual screens, these approaches produced hit rates of 24, 25, 34, and 27 %, respectively, on a set with 19 % declared binders. Our only entry for the second stage challenge was based on the results of AD Vina plus visual inspection, and it ranked third place overall according to several different metrics provided by the SAMPL4 organizers. The successful results displayed by these approaches highlight the utility of the computational structure-based drug discovery tools and strategies that are being developed to advance the goals of the newly created, multi-institution, NIH-funded center called the "HIV Interaction and Viral Evolution Center".

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

PubMed Central

Fang, Ye; Ding, Yun; Feinstein, Wei P.; Koppelman, David M.; Moreno, Juana; Jarrell, Mark; Ramanujam, J.; Brylinski, Michal

2016-01-01

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249. PMID:27420300

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

PubMed

Fang, Ye; Ding, Yun; Feinstein, Wei P; Koppelman, David M; Moreno, Juana; Jarrell, Mark; Ramanujam, J; Brylinski, Michal

2016-01-01

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.

Chemical correction of pre-mRNA splicing defects associated with sequestration of muscleblind-like 1 protein by expanded r(CAG)-containing transcripts.

PubMed

Kumar, Amit; Parkesh, Raman; Sznajder, Lukasz J; Childs-Disney, Jessica L; Sobczak, Krzysztof; Disney, Matthew D

2012-03-16

Recently, it was reported that expanded r(CAG) triplet repeats (r(CAG)(exp)) associated with untreatable neurological diseases cause pre-mRNA mis-splicing likely due to sequestration of muscleblind-like 1 (MBNL1) splicing factor. Bioactive small molecules that bind the 5'CAG/3'GAC motif found in r(CAG)(exp) hairpin structure were identified by using RNA binding studies and virtual screening/chemical similarity searching. Specifically, a benzylguanidine-containing small molecule was found to improve pre-mRNA alternative splicing of MBNL1-sensitive exons in cells expressing the toxic r(CAG)(exp). The compound was identified by first studying the binding of RNA 1 × 1 nucleotide internal loops to small molecules known to have affinity for nucleic acids. Those studies identified 4',6-diamidino-2-phenylindole (DAPI) as a specific binder to RNAs with the 5'CAG/3'GAC motif. DAPI was then used as a query molecule in a shape- and chemistry alignment-based virtual screen to identify compounds with improved properties, which identified 4-guanidinophenyl 4-guanidinobenzoate, a small molecule that improves pre-mRNA splicing defects associated with the r(CAG)(exp)-MBNL1 complex. This compound may facilitate the development of therapeutics to treat diseases caused by r(CAG)(exp) and could serve as a useful chemical tool to dissect the mechanisms of r(CAG)(exp) toxicity. The approach used in these studies, defining the small RNA motifs that bind small molecules with known affinity for nucleic acids and then using virtual screening to optimize them for bioactivity, may be generally applicable for designing small molecules that target other RNAs in the human genomic sequence.

Chemical correction of pre-mRNA splicing defects associated with sequestration of muscleblind-like 1 protein by expanded r(CAG) transcripts

PubMed Central

Kumar, Amit; Parkesh, Raman; Sznajder, Lukasz J.; Childs-Disney, Jessica; Sobczak, Krzysztof; Disney, Matthew D.

2012-01-01

Recently, it was reported that expanded r(CAG) triplet repeats (r(CAG)exp) associated with untreatable neurological diseases cause pre-mRNA mis-splicing likely due to sequestration of muscleblind-like 1 (MBNL1) splicing factor. Bioactive small molecules that bind the 5’CAG/3’GAC motif found in r(CAG)exp hairpin structure were identified by using RNA binding studies and virtual screening/chemical similarity searching. Specifically, a benzylguanidine-containing small molecule was found to improve pre-mRNA alternative splicing of MBNL1-sensitive exons in cells expressing the toxic r(CAG)exp. The compound was identified by first studying the binding of RNA 1×1 nucleotide internal loops to small molecules known to have affinity for nucleic acids. Those studies identified 4',6-diamidino-2-phenylindole (DAPI) as a specific binder to RNAs with the 5’CAG/3’GAC motif. DAPI was then used as a query molecule in a shape- and chemistry alignment-based virtual screen to identify compounds with improved properties, which identified 4-guanidinophenyl 4-guanidinobenzoate as small molecule capable of improving pre-mRNA splicing defects associated with the r(CAG)exp-MBNL1 complex. This compound may facilitate the development of therapeutics to treat diseases caused by r(CAG)exp and could serve as a useful chemical tool to dissect the mechanisms of r(CAG)exp toxicity. The approach used in these studies, defining the small RNA motifs that bind known nucleic acid binders and then using virtual screening to optimize them for bioactivity, may be generally applicable for designing small molecules that target other RNAs in human genomic sequence. PMID:22252896

Colorectal Cancer Screening

MedlinePlus

... blood test Sigmoidoscopy Colonoscopy Virtual colonoscopy DNA stool test Studies have shown that screening for colorectal cancer using ... decrease the risk of dying from cancer. Scientists study screening tests to find those with the fewest risks and ...

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

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

Zhang, Liying; Sedykh, Alexander; Tripathi, Ashutosh

2013-10-01

Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα bindingmore » affinity (MTL R{sup 2} = 0.71, STL R{sup 2} = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R{sup 2} = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. - Highlights: • This is the largest curated dataset inclusive of ERα and β (the latter is unique). • New methodology that for the first time affords acceptable ERβ models. • A combination of QSAR and docking enables prediction of affinity and function. • The results have potential applications to green chemistry. • Models are publicly available for virtual screening via a web portal.« less

Virtual High-Throughput Screening for Matrix Metalloproteinase Inhibitors.

PubMed

Choi, Jun Yong; Fuerst, Rita

2017-01-01

Structure-based virtual screening (SBVS) is a common method for the fast identification of hit structures at the beginning of a medicinal chemistry program in drug discovery. The SBVS, described in this manuscript, is focused on finding small molecule hits that can be further utilized as a starting point for the development of inhibitors of matrix metalloproteinase 13 (MMP-13) via structure-based molecular design. We intended to identify a set of structurally diverse hits, which occupy all subsites (S1'-S3', S2, and S3) centering the zinc containing binding site of MMP-13, by the virtual screening of a chemical library comprising more than ten million commercially available compounds. In total, 23 compounds were found as potential MMP-13 inhibitors using Glide docking followed by the analysis of the structural interaction fingerprints (SIFt) of the docked structures.

Novel Virtual Screening Approach for the Discovery of Human Tyrosinase Inhibitors

PubMed Central

Ai, Ni; Welsh, William J.; Santhanam, Uma; Hu, Hong; Lyga, John

2014-01-01

Tyrosinase is the key enzyme involved in the human pigmentation process, as well as the undesired browning of fruits and vegetables. Compounds inhibiting tyrosinase catalytic activity are an important class of cosmetic and dermatological agents which show high potential as depigmentation agents used for skin lightening. The multi-step protocol employed for the identification of novel tyrosinase inhibitors incorporated the Shape Signatures computational algorithm for rapid screening of chemical libraries. This algorithm converts the size and shape of a molecule, as well its surface charge distribution and other bio-relevant properties, into compact histograms (signatures) that lend themselves to rapid comparison between molecules. Shape Signatures excels at scaffold hopping across different chemical families, which enables identification of new actives whose molecular structure is distinct from other known actives. Using this approach, we identified a novel class of depigmentation agents that demonstrated promise for skin lightening product development. PMID:25426625

Novel virtual screening approach for the discovery of human tyrosinase inhibitors.

PubMed

Ai, Ni; Welsh, William J; Santhanam, Uma; Hu, Hong; Lyga, John

2014-01-01

Tyrosinase is the key enzyme involved in the human pigmentation process, as well as the undesired browning of fruits and vegetables. Compounds inhibiting tyrosinase catalytic activity are an important class of cosmetic and dermatological agents which show high potential as depigmentation agents used for skin lightening. The multi-step protocol employed for the identification of novel tyrosinase inhibitors incorporated the Shape Signatures computational algorithm for rapid screening of chemical libraries. This algorithm converts the size and shape of a molecule, as well its surface charge distribution and other bio-relevant properties, into compact histograms (signatures) that lend themselves to rapid comparison between molecules. Shape Signatures excels at scaffold hopping across different chemical families, which enables identification of new actives whose molecular structure is distinct from other known actives. Using this approach, we identified a novel class of depigmentation agents that demonstrated promise for skin lightening product development.

Discovery of N-[4-(1H-Pyrazolo[3,4-b]pyrazin-6-yl)-phenyl]-sulfonamides as Highly Active and Selective SGK1 Inhibitors

PubMed Central

2014-01-01

From a virtual screening starting point, inhibitors of the serum and glucocorticoid regulated kinase 1 were developed through a combination of classical medicinal chemistry and library approaches. This resulted in highly active small molecules with nanomolar activity and a good overall in vitro and ADME profile. Furthermore, the compounds exhibited unusually high kinase and off-target selectivity due to their rigid structure. PMID:25589934

Discovery of N-[4-(1H-Pyrazolo[3,4-b]pyrazin-6-yl)-phenyl]-sulfonamides as Highly Active and Selective SGK1 Inhibitors.

PubMed

Halland, Nis; Schmidt, Friedemann; Weiss, Tilo; Saas, Joachim; Li, Ziyu; Czech, Jörg; Dreyer, Matthias; Hofmeister, Armin; Mertsch, Katharina; Dietz, Uwe; Strübing, Carsten; Nazare, Marc

2015-01-08

From a virtual screening starting point, inhibitors of the serum and glucocorticoid regulated kinase 1 were developed through a combination of classical medicinal chemistry and library approaches. This resulted in highly active small molecules with nanomolar activity and a good overall in vitro and ADME profile. Furthermore, the compounds exhibited unusually high kinase and off-target selectivity due to their rigid structure.

Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.

PubMed

Xia, Jie; Tilahun, Ermias Lemma; Kebede, Eyob Hailu; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon

2015-02-23

Histone deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases, and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective histone deacetylase inhibitors (HDACIs). To facilitate the process, we constructed maximal unbiased benchmarking data sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs cover all four classes including Class III (Sirtuins family) and 14 HDAC isoforms, composed of 631 inhibitors and 24609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of "artificial enrichment" and "analogue bias". We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets and demonstrate that our MUBD-HDACs are unique in that they can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the "2D bias" and "LBVS favorable" effect within the benchmarking sets. In summary, MUBD-HDACs are the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that are available so far. MUBD-HDACs are freely available at http://www.xswlab.org/ .

Differentiation of AmpC beta-lactamase binders vs. decoys using classification kNN QSAR modeling and application of the QSAR classifier to virtual screening

NASA Astrophysics Data System (ADS)

Hsieh, Jui-Hua; Wang, Xiang S.; Teotico, Denise; Golbraikh, Alexander; Tropsha, Alexander

2008-09-01

The use of inaccurate scoring functions in docking algorithms may result in the selection of compounds with high predicted binding affinity that nevertheless are known experimentally not to bind to the target receptor. Such falsely predicted binders have been termed `binding decoys'. We posed a question as to whether true binders and decoys could be distinguished based only on their structural chemical descriptors using approaches commonly used in ligand based drug design. We have applied the k-Nearest Neighbor ( kNN) classification QSAR approach to a dataset of compounds characterized as binders or binding decoys of AmpC beta-lactamase. Models were subjected to rigorous internal and external validation as part of our standard workflow and a special QSAR modeling scheme was employed that took into account the imbalanced ratio of inhibitors to non-binders (1:4) in this dataset. 342 predictive models were obtained with correct classification rate (CCR) for both training and test sets as high as 0.90 or higher. The prediction accuracy was as high as 100% (CCR = 1.00) for the external validation set composed of 10 compounds (5 true binders and 5 decoys) selected randomly from the original dataset. For an additional external set of 50 known non-binders, we have achieved the CCR of 0.87 using very conservative model applicability domain threshold. The validated binary kNN QSAR models were further employed for mining the NCGC AmpC screening dataset (69653 compounds). The consensus prediction of 64 compounds identified as screening hits in the AmpC PubChem assay disagreed with their annotation in PubChem but was in agreement with the results of secondary assays. At the same time, 15 compounds were identified as potential binders contrary to their annotation in PubChem. Five of them were tested experimentally and showed inhibitory activities in millimolar range with the highest binding constant Ki of 135 μM. Our studies suggest that validated QSAR models could complement structure based docking and scoring approaches in identifying promising hits by virtual screening of molecular libraries.

Role of Chemical Reactivity and Transition State Modeling for Virtual Screening.

PubMed

Karthikeyan, Muthukumarasamy; Vyas, Renu; Tambe, Sanjeev S; Radhamohan, Deepthi; Kulkarni, Bhaskar D

2015-01-01

Every drug discovery research program involves synthesis of a novel and potential drug molecule utilizing atom efficient, economical and environment friendly synthetic strategies. The current work focuses on the role of the reactivity based fingerprints of compounds as filters for virtual screening using a tool ChemScore. A reactant-like (RLS) and a product- like (PLS) score can be predicted for a given compound using the binary fingerprints derived from the numerous known organic reactions which capture the molecule-molecule interactions in the form of addition, substitution, rearrangement, elimination and isomerization reactions. The reaction fingerprints were applied to large databases in biology and chemistry, namely ChEMBL, KEGG, HMDB, DSSTox, and the Drug Bank database. A large network of 1113 synthetic reactions was constructed to visualize and ascertain the reactant product mappings in the chemical reaction space. The cumulative reaction fingerprints were computed for 4000 molecules belonging to 29 therapeutic classes of compounds, and these were found capable of discriminating between the cognition disorder related and anti-allergy compounds with reasonable accuracy of 75% and AUC 0.8. In this study, the transition state based fingerprints were also developed and used effectively for virtual screening in drug related databases. The methodology presented here provides an efficient handle for the rapid scoring of molecular libraries for virtual screening.

Risks of Colorectal Cancer Screening

MedlinePlus

... blood test Sigmoidoscopy Colonoscopy Virtual colonoscopy DNA stool test Studies have shown that screening for colorectal cancer using ... decrease the risk of dying from cancer. Scientists study screening tests to find those with the fewest risks and ...

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.

Bayesian screening for active compounds in high-dimensional chemical spaces combining property descriptors and molecular fingerprints.

PubMed

Vogt, Martin; Bajorath, Jürgen

2008-01-01

Bayesian classifiers are increasingly being used to distinguish active from inactive compounds and search large databases for novel active molecules. We introduce an approach to directly combine the contributions of property descriptors and molecular fingerprints in the search for active compounds that is based on a Bayesian framework. Conventionally, property descriptors and fingerprints are used as alternative features for virtual screening methods. Following the approach introduced here, probability distributions of descriptor values and fingerprint bit settings are calculated for active and database molecules and the divergence between the resulting combined distributions is determined as a measure of biological activity. In test calculations on a large number of compound activity classes, this methodology was found to consistently perform better than similarity searching using fingerprints and multiple reference compounds or Bayesian screening calculations using probability distributions calculated only from property descriptors. These findings demonstrate that there is considerable synergy between different types of property descriptors and fingerprints in recognizing diverse structure-activity relationships, at least in the context of Bayesian modeling.

Discovery of novel Trypanosoma brucei phosphodiesterase B1 inhibitors by virtual screening against the unliganded TbrPDEB1 crystal structure

PubMed Central

Jansen, Chimed; Wang, Huanchen; Kooistra, Albert J.; de Graaf, Chris; Orrling, Kristina; Tenor, Hermann; Seebeck, Thomas; Bailey, David; de Esch, Iwan J.P.; Ke, Hengming; Leurs, Rob

2013-01-01

Trypanosoma brucei cyclic nucleotide phosphodiesterase B1 (TbrPDEB1) and TbrPDEB2 have recently been validated as new therapeutic targets for human African Trypanosomiasis by both genetic and pharmacological means. In this study we report the crystal structure of the catalytic domain of the unliganded TbrPDEB1 and its use for the in silico screening for new TbrPDEB1 inhibitors with novel scaffolds. The TbrPDEB1 crystal structure shows the characteristic folds of human PDE enzymes, but also contains the parasite-specific P-pocket found in the structures of Leishmania major PDEB1 and Trypanosoma cruzi PDEC. The unliganded TbrPDEB1 X-ray structure was subjected to a structure-based in silico screening approach that combines molecular docking simulations with a protein-ligand interaction fingerprint (IFP) scoring method. This approach identified, six novel TbrPDEB1 inhibitors with IC50 values of 10–80 μM, which may be further optimized as potential selective TbrPDEB inhibitors. PMID:23409953

Colonoscopy procedure simulation: virtual reality training based on a real time computational approach.

PubMed

Wen, Tingxi; Medveczky, David; Wu, Jackie; Wu, Jianhuang

2018-01-25

Colonoscopy plays an important role in the clinical screening and management of colorectal cancer. The traditional 'see one, do one, teach one' training style for such invasive procedure is resource intensive and ineffective. Given that colonoscopy is difficult, and time-consuming to master, the use of virtual reality simulators to train gastroenterologists in colonoscopy operations offers a promising alternative. In this paper, a realistic and real-time interactive simulator for training colonoscopy procedure is presented, which can even include polypectomy simulation. Our approach models the colonoscopy as thick flexible elastic rods with different resolutions which are dynamically adaptive to the curvature of the colon. More material characteristics of this deformable material are integrated into our discrete model to realistically simulate the behavior of the colonoscope. We present a simulator for training colonoscopy procedure. In addition, we propose a set of key aspects of our simulator that give fast, high fidelity feedback to trainees. We also conducted an initial validation of this colonoscopic simulator to determine its clinical utility and efficacy.

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.

Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.

PubMed

Pérez, Germán M; Salomón, Luis A; Montero-Cabrera, Luis A; de la Vega, José M García; Mascini, Marcello

2016-05-01

A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.

Accelerating Virtual High-Throughput Ligand Docking: current technology and case study on a petascale supercomputer.

PubMed

Ellingson, Sally R; Dakshanamurthy, Sivanesan; Brown, Milton; Smith, Jeremy C; Baudry, Jerome

2014-04-25

In this paper we give the current state of high-throughput virtual screening. We describe a case study of using a task-parallel MPI (Message Passing Interface) version of Autodock4 [1], [2] to run a virtual high-throughput screen of one-million compounds on the Jaguar Cray XK6 Supercomputer at Oak Ridge National Laboratory. We include a description of scripts developed to increase the efficiency of the predocking file preparation and postdocking analysis. A detailed tutorial, scripts, and source code for this MPI version of Autodock4 are available online at http://www.bio.utk.edu/baudrylab/autodockmpi.htm.

Surflex-Dock: Docking benchmarks and real-world application

NASA Astrophysics Data System (ADS)

Spitzer, Russell; Jain, Ajay N.

2012-06-01

Benchmarks for molecular docking have historically focused on re-docking the cognate ligand of a well-determined protein-ligand complex to measure geometric pose prediction accuracy, and measurement of virtual screening performance has been focused on increasingly large and diverse sets of target protein structures, cognate ligands, and various types of decoy sets. Here, pose prediction is reported on the Astex Diverse set of 85 protein ligand complexes, and virtual screening performance is reported on the DUD set of 40 protein targets. In both cases, prepared structures of targets and ligands were provided by symposium organizers. The re-prepared data sets yielded results not significantly different than previous reports of Surflex-Dock on the two benchmarks. Minor changes to protein coordinates resulting from complex pre-optimization had large effects on observed performance, highlighting the limitations of cognate ligand re-docking for pose prediction assessment. Docking protocols developed for cross-docking, which address protein flexibility and produce discrete families of predicted poses, produced substantially better performance for pose prediction. Performance on virtual screening performance was shown to benefit by employing and combining multiple screening methods: docking, 2D molecular similarity, and 3D molecular similarity. In addition, use of multiple protein conformations significantly improved screening enrichment.

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

Identification of potential isoform-selective histone deacetylase inhibitors for cancer therapy: a combined approach of structure-based virtual screening, ADMET prediction and molecular dynamics simulation assay.

PubMed

Uba, Abdullahi Ibrahim; Yelekçi, Kemal

2017-10-23

Histone deacetylases (HDACs) have gained increased attention as targets for anticancer drug design and development. HDAC inhibitors have proven to be effective for reversing the malignant phenotype in HDAC-dependent cancer cases. However, lack of selectivity of the many HDAC inhibitors in clinical use and trials contributes to toxicities to healthy cells. It is believed that, the continued identification of isoform-selective inhibitors will eliminate these undesirable adverse effects - a task that remains a major challenge to HDAC inhibitor designs. Here, in an attempt to identify isoform-selective inhibitors, a large compound library containing 2,703,000 compounds retrieved from Otava database was screened against class I HDACs by exhaustive approach of structure-based virtual screening using rDOCK and Autodock Vina. A total of 41 compounds were found to show high-isoform selectivity and were further redocked into their respective targets using Autodock4. Thirty-six compounds showed remarkable isoform selectivity and passed drug-likeness and absorption, distribution, metabolism, elimination and toxicity prediction tests using ADMET Predictor™ and admetSAR. Furthermore, to study the stability of ligand binding modes, 10 ns-molecular dynamics (MD) simulations of the free HDAC isoforms and their complexes with respective best-ranked ligands were performed using nanoscale MD software. The inhibitors remained bound to their respective targets over time of the simulation and the overall potential energy, root-mean-square deviation, root-mean-square fluctuation profiles suggested that the detected compounds may be potential isoform-selective HDAC inhibitors or serve as promising scaffolds for further optimization towards the design of selective inhibitors for cancer therapy.

Integrating virtual screening and biochemical experimental approach to identify potential anti-cancer agents from drug databank.

PubMed

Deka, Suman Jyoti; Roy, Ashalata; Manna, Debasis; Trivedi, Vishal

2018-06-01

Chemical libraries constitute a reservoir of pharmacophoric molecules to identify potent anti-cancer agents. Virtual screening of heterocyclic compound library in conjugation with the agonist-competition assay, toxicity-carcinogenicity analysis, and string-based structural searches enabled us to identify several drugs as potential anti-cancer agents targeting protein kinase C (PKC) as a target. Molecular modeling study indicates that Cinnarizine fits well within the PKC C2 domain and exhibits extensive interaction with the protein residues. Molecular dynamics simulation of PKC-Cinnarizine complex at different temperatures (300, 325, 350, 375, and 400[Formula: see text]K) confirms that Cinnarizine fits nicely into the C2 domain and forms a stable complex. The drug Cinnarizine was found to bind PKC with a dissociation constant Kd of [Formula: see text]M. The breast cancer cells stimulated with Cinnarizine causes translocation of PKC-[Formula: see text] to the plasma membrane as revealed by immunoblotting and immunofluorescence studies. Cinnarizine also dose dependently reduced the viability of MDAMB-231 and MCF-7 breast cancer cells with an IC[Formula: see text] of [Formula: see text] and [Formula: see text]g/mL, respectively. It is due to the disturbance of cell cycle of breast cancer cells with reduction of S-phase and accumulation of cells in G1-phase. It disturbs mitochondrial membrane potentials to release cytochrome C into the cytosol and activates caspase-3 to induce apoptosis in cancer cells. The cell death was due to induction of apoptosis involving mitochondrial pathway. Hence, the current study has assigned an additional role to Cinnarizine as an activator of PKC and potentials of the approach to identify new molecules for anti-cancer therapy. Thus, in silico screening along with biochemical experimentation is a robust approach to assign additional roles to the drugs present in the databank for anti-cancer therapy.

How can machine-learning methods assist in virtual screening for hyperuricemia? A healthcare machine-learning approach.

PubMed

Ichikawa, Daisuke; Saito, Toki; Ujita, Waka; Oyama, Hiroshi

2016-12-01

Our purpose was to develop a new machine-learning approach (a virtual health check-up) toward identification of those at high risk of hyperuricemia. Applying the system to general health check-ups is expected to reduce medical costs compared with administering an additional test. Data were collected during annual health check-ups performed in Japan between 2011 and 2013 (inclusive). We prepared training and test datasets from the health check-up data to build prediction models; these were composed of 43,524 and 17,789 persons, respectively. Gradient-boosting decision tree (GBDT), random forest (RF), and logistic regression (LR) approaches were trained using the training dataset and were then used to predict hyperuricemia in the test dataset. Undersampling was applied to build the prediction models to deal with the imbalanced class dataset. The results showed that the RF and GBDT approaches afforded the best performances in terms of sensitivity and specificity, respectively. The area under the curve (AUC) values of the models, which reflected the total discriminative ability of the classification, were 0.796 [95% confidence interval (CI): 0.766-0.825] for the GBDT, 0.784 [95% CI: 0.752-0.815] for the RF, and 0.785 [95% CI: 0.752-0.819] for the LR approaches. No significant differences were observed between pairs of each approach. Small changes occurred in the AUCs after applying undersampling to build the models. We developed a virtual health check-up that predicted the development of hyperuricemia using machine-learning methods. The GBDT, RF, and LR methods had similar predictive capability. Undersampling did not remarkably improve predictive power. Copyright © 2016 Elsevier Inc. All rights reserved.

Engaging adolescents in a computer-based weight management program: avatars and virtual coaches could help.

PubMed

LeRouge, Cynthia; Dickhut, Kathryn; Lisetti, Christine; Sangameswaran, Savitha; Malasanos, Toree

2016-01-01

This research focuses on the potential ability of animated avatars (a digital representation of the user) and virtual agents (a digital representation of a coach, buddy, or teacher) to deliver computer-based interventions for adolescents' chronic weight management. An exploration of the acceptance and desire of teens to interact with avatars and virtual agents for self-management and behavioral modification was undertaken. The utilized approach was inspired by community-based participatory research. Data was collected from 2 phases: Phase 1) focus groups with teens, provider interviews, parent interviews; and Phase 2) mid-range prototype assessment by teens and providers. Data from all stakeholder groups expressed great interest in avatars and virtual agents assisting self-management efforts. Adolescents felt the avatars and virtual agents could: 1) reinforce guidance and support, 2) fit within their lifestyle, and 3) help set future goals, particularly after witnessing the effect of their current behavior(s) on the projected physical appearance (external and internal organs) of avatars. Teens wanted 2 virtual characters: a virtual agent to act as a coach or teacher and an avatar (extension of themselves) to serve as a "buddy" for empathic support and guidance and as a surrogate for rewards. Preferred modalities for use include both mobile devices to accommodate access and desktop to accommodate preferences for maximum screen real estate to support virtualization of functions that are more contemplative and complex (e.g., goal setting). Adolescents expressed a desire for limited co-user access, which they could regulate. Data revealed certain barriers and facilitators that could affect adoption and use. The current study extends the support of teens, parents, and providers for adding avatars or virtual agents to traditional computer-based interactions. Data supports the desire for a personal relationship with a virtual character in support of previous studies. The study provides a foundation for further work in the area of avatar-driven motivational interviewing. This study provides evidence supporting the use of avatars and virtual agents, designed using participatory approaches, to be included in the continuum of care. Increased probability of engagement and long-term retention of overweight, obese adolescent users and suggests expanding current chronic care models toward more comprehensive, socio-technical representations. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Discovery of a fluorene class of compounds as inhibitors of botulinum neurotoxin serotype E by virtual screening.

PubMed

Kumar, Gyanendra; Agarwal, Rakhi; Swaminathan, Subramanyam

2012-02-28

Botulinum neurotoxins are one of the most poisonous biological substances known to humans and present a potential bioterrorism threat. There are no therapeutic interventions developed so far. Here, we report the first small molecule non-peptide inhibitor for botulinum neurotoxin serotype E discovered by structure-based virtual screening and propose a mechanism for its inhibitory activity. This journal is © The Royal Society of Chemistry 2012

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products.

PubMed

Sun, Yunan; Zhou, Hui; Zhu, Hongmei; Leung, Siu-wai

2016-01-25

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by In Silico Modeling and Virtual Screening Strategies to Combat Early Blight

NASA Astrophysics Data System (ADS)

Iftikhar, Sehrish; Shahid, Ahmad A.; Halim, Sobia A.; Wolters, Pieter J.; Vleeshouwers, Vivianne G. A. A.; Khan, Ajmal; Al-Harrasi, Ahmed; Ahmad, Shahbaz

2017-11-01

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening protocol. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify new and novel fungicides.

Discovering Novel Alternaria solani Succinate Dehydrogenase Inhibitors by in Silico Modeling and Virtual Screening Strategies to Combat Early Blight

PubMed Central

Iftikhar, Sehrish; Shahid, Ahmad A.; Halim, Sobia A.; Wolters, Pieter J.; Vleeshouwers, Vivianne G. A. A.; Khan, Ajmal; Al-Harrasi, Ahmed; Ahmad, Shahbaz

2017-01-01

Alternaria blight is an important foliage disease caused by Alternaria solani. The enzyme Succinate dehydrogenase (SDH) is a potential drug target because of its role in tricarboxylic acid cycle. Hence targeting Alternaria solani SDH enzyme could be efficient tool to design novel fungicides against A. solani. We employed computational methodologies to design new SDH inhibitors using homology modeling; pharmacophore modeling and structure based virtual screening. The three dimensional SDH model showed good stereo-chemical and structural properties. Based on virtual screening results twelve commercially available compounds were purchased and tested in vitro and in vivo. The compounds were found to inhibit mycelial growth of A. solani. Moreover in vitro trials showed that inhibitory effects were enhanced with increase in concentrations. Similarly increased disease control was observed in pre-treated potato tubers. Hence the applied in silico strategy led us to identify novel fungicides. PMID:29204422

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products

NASA Astrophysics Data System (ADS)

Sun, Yunan; Zhou, Hui; Zhu, Hongmei; Leung, Siu-Wai

2016-01-01

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

Discovery of potent inhibitors of soluble epoxide hydrolase by combinatorial library design and structure-based virtual screening.

PubMed

Xing, Li; McDonald, Joseph J; Kolodziej, Steve A; Kurumbail, Ravi G; Williams, Jennifer M; Warren, Chad J; O'Neal, Janet M; Skepner, Jill E; Roberds, Steven L

2011-03-10

Structure-based virtual screening was applied to design combinatorial libraries to discover novel and potent soluble epoxide hydrolase (sEH) inhibitors. X-ray crystal structures revealed unique interactions for a benzoxazole template in addition to the conserved hydrogen bonds with the catalytic machinery of sEH. By exploitation of the favorable binding elements, two iterations of library design based on amide coupling were employed, guided principally by the docking results of the enumerated virtual products. Biological screening of the libraries demonstrated as high as 90% hit rate, of which over two dozen compounds were single digit nanomolar sEH inhibitors by IC(50) determination. In total the library design and synthesis produced more than 300 submicromolar sEH inhibitors. In cellular systems consistent activities were demonstrated with biochemical measurements. The SAR understanding of the benzoxazole template provides valuable insights into discovery of novel sEH inhibitors as therapeutic agents.

Three-dimensional compound comparison methods and their application in drug discovery.

PubMed

Shin, Woong-Hee; Zhu, Xiaolei; Bures, Mark Gregory; Kihara, Daisuke

2015-07-16

Virtual screening has been widely used in the drug discovery process. Ligand-based virtual screening (LBVS) methods compare a library of compounds with a known active ligand. Two notable advantages of LBVS methods are that they do not require structural information of a target receptor and that they are faster than structure-based methods. LBVS methods can be classified based on the complexity of ligand structure information utilized: one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D). Unlike 1D and 2D methods, 3D methods can have enhanced performance since they treat the conformational flexibility of compounds. In this paper, a number of 3D methods will be reviewed. In addition, four representative 3D methods were benchmarked to understand their performance in virtual screening. Specifically, we tested overall performance in key aspects including the ability to find dissimilar active compounds, and computational speed.

Assessing subacute mild traumatic brain injury with a portable virtual reality balance device.

PubMed

Wright, W Geoffrey; McDevitt, Jane; Tierney, Ryan; Haran, F Jay; Appiah-Kubi, Kwadwo Osei; Dumont, Alex

2017-07-01

Balance impairment is a common sensorimotor symptom in mild traumatic brain injury (mTBI). We designed an affordable, portable virtual reality (VR)-based balance screening device (Virtual Environment TBI Screen [VETS]), which will be validated relative to the Neurocom Sensory Organization Test (SOT) to determine if it can replace commonly used postural assessments. This preliminary study examines healthy adults (n = 56) and adults with mTBI (n = 11). Participants performed six upright postural tasks on the VETS and the SOT. Analysis of variance was used to determine between-group differences. Pearson's correlations were used to establish construct validity. Known-groups approach was used to establish classification accuracy. The mTBI cohort performed significantly worse than the healthy cohort on the new device (p = 0.001). The new device has 91.0% accuracy and an ROC curve with a significant area-under-the-curve (AUC = 0.865, p < 0.001). Conditions with dynamic visual stimulation were the most sensitive to health status. The SOT had an 84.8% accuracy and AUC =0.703 (p = 0.034). The new VR-based device is a valid measure for detecting balance impairment following mTBI and can potentially replace more expensive and cumbersome equipment. Assessments that test visual-vestibular processing, such as VETS, increase sensitivity to mTBI-related balance deficits, which can be used to guide rehabilitation. Implications for rehabilitation Emerging technology using virtual reality can be economically integrated into the clinical setting for easy testing of postural control in neurologically impaired populations. Tailoring postural assessments to include tasks that rely on visual and vestibular integration will increase the accuracy of detecting balance impairment following mild traumatic brain injury.

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

LIGSIFT: an open-source tool for ligand structural alignment and virtual screening.

PubMed

Roy, Ambrish; Skolnick, Jeffrey

2015-02-15

Shape-based alignment of small molecules is a widely used approach in computer-aided drug discovery. Most shape-based ligand structure alignment applications, both commercial and freely available ones, use the Tanimoto coefficient or similar functions for evaluating molecular similarity. Major drawbacks of using such functions are the size dependence of the score and the fact that the statistical significance of the molecular match using such metrics is not reported. We describe a new open-source ligand structure alignment and virtual screening (VS) algorithm, LIGSIFT, that uses Gaussian molecular shape overlay for fast small molecule alignment and a size-independent scoring function for efficient VS based on the statistical significance of the score. LIGSIFT was tested against the compounds for 40 protein targets available in the Directory of Useful Decoys and the performance was evaluated using the area under the ROC curve (AUC), the Enrichment Factor (EF) and Hit Rate (HR). LIGSIFT-based VS shows an average AUC of 0.79, average EF values of 20.8 and a HR of 59% in the top 1% of the screened library. LIGSIFT software, including the source code, is freely available to academic users at http://cssb.biology.gatech.edu/LIGSIFT. Supplementary data are available at Bioinformatics online. skolnick@gatech.edu. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors.

PubMed

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W; Schuster, Daniela

2017-01-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing's syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8 - 10 ), one selective CYP11B1 inhibitor (Compound 11 , IC 50 = 2.5 μM), and one selective CYP11B2 inhibitor (compound 12 , IC 50 = 1.1 μM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models.

Virtual screening studies of Chinese medicine Coptidis Rhizoma as alpha7 nicotinic acetylcholine receptor agonists for treatment of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Xiang, Li; Xu, Youdong; Zhang, Yan; Meng, Xianli; Wang, Ping

2015-04-01

Alzheimer's disease (AD) is an age-related neurodegenerative disease. Extensive in vitro and in vivo experiments have proved that the decreased activity of the cholinergic neuron is responsible for the memory and cognition deterioration. The alpha7 nicotinic acetylcholine receptor (α7-nAChR) is proposed to a drug target of AD, and compounds which acting as α7-nAChR agonists are considered as candidates in AD treatment. Chinese medicine CoptidisRhizoma and its compounds are reported in various anti-AD effects. In this study, virtual screening, docking approaches and hydrogen bond analyses were applied to screen potential α7-nAChR agonists from CoptidisRhizome. The 3D structure of the protein was obtained from PDB database. 87 reported compounds were included in this research and their structures were accessed by NCBI Pubchem. Docking analysis of the compounds was performed using AutoDock 4.2 and AutoDock Vina. The images of the binding modes hydrogen bonds and the hydrophobic interaction were rendered with PyMOL1.5.0.4. and LigPlot+ respectively. Finally, N-tran-feruloyltyramine, isolariciresinol, flavanone, secoisolariciresinol, (+)-lariciresinol and dihydrochalcone, exhibited the lowest docking energy of protein-ligand complex. The results indicate these 6 compounds are potential α7 nAChR agonists, and expected to be effective in AD treatment.

Pharmacophore modeling and in silico / in vitro screening for human cytochrome P450 11B1 & cytochrome P450 11B2 inhibitors

NASA Astrophysics Data System (ADS)

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W.; Schuster, Daniela

2017-12-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing’s syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8-10), one selective CYP11B1 inhibitor (Compound 11, IC50 = 2.5 µM), and one selective CYP11B2 inhibitor (compound 12, IC50 = 1.1 µM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models.

High throughput virtual screening and in silico ADMET analysis for rapid and efficient identification of potential PAP248-286 aggregation inhibitors as anti-HIV agents

NASA Astrophysics Data System (ADS)

Malik, Ruchi; Bunkar, Devendra; Choudhary, Bhanwar Singh; Srivastava, Shubham; Mehta, Pakhuri; Sharma, Manish

2016-10-01

Human semen is principal vehicle for transmission of HIV-1 and other enveloped viruses. Several endogenous peptides present in semen, including a 39-amino acid fragments of prostatic acid phosphatase (PAP248-286) assemble into amyloid fibrils named as semen-derived enhancer of viral infection (SEVI) that promote virion attachment to target cells which dramatically enhance HIV virus infection by up to 105-fold. Epigallocatechin-3-gallate (EGCG), a polyphenolic compound, is the major catechin found in green tea which disaggregates existing SEVI fibers, and inhibits the formation of SEVI fibers. The aim of this study was to screen a number of relevant polyphenols to develop a rational approach for designing PAP248-286 aggregation inhibitors as potential anti-HIV agents. The molecular docking based virtual screening results showed that polyphenolic compounds 2-6 possessed good docking score and interacted well with the active site residues of PAP248-286. Amino acid residues of binding site namely; Lys255, Ser256, Leu258 and Asn265 are involved in binding of these compounds. In silico ADMET prediction studies on these hits were also found to be promising. Polyphenolic compounds 2-6 identified as hits may act as novel leads for inhibiting aggregation of PAP248-286 into SEVI.

Monocular display unit for 3D display with correct depth perception

NASA Astrophysics Data System (ADS)

Sakamoto, Kunio; Hosomi, Takashi

2009-11-01

A study of virtual-reality system has been popular and its technology has been applied to medical engineering, educational engineering, a CAD/CAM system and so on. The 3D imaging display system has two types in the presentation method; one is a 3-D display system using a special glasses and the other is the monitor system requiring no special glasses. A liquid crystal display (LCD) recently comes into common use. It is possible for this display unit to provide the same size of displaying area as the image screen on the panel. A display system requiring no special glasses is useful for a 3D TV monitor, but this system has demerit such that the size of a monitor restricts the visual field for displaying images. Thus the conventional display can show only one screen, but it is impossible to enlarge the size of a screen, for example twice. To enlarge the display area, the authors have developed an enlarging method of display area using a mirror. Our extension method enables the observers to show the virtual image plane and to enlarge a screen area twice. In the developed display unit, we made use of an image separating technique using polarized glasses, a parallax barrier or a lenticular lens screen for 3D imaging. The mirror can generate the virtual image plane and it enlarges a screen area twice. Meanwhile the 3D display system using special glasses can also display virtual images over a wide area. In this paper, we present a monocular 3D vision system with accommodation mechanism, which is useful function for perceiving depth.

Virtual screening of mandelate racemase mutants with enhanced activity based on binding energy in the transition state.

PubMed

Gu, Jiali; Liu, Min; Guo, Fei; Xie, Wenping; Lu, Wenqiang; Ye, Lidan; Chen, Zhirong; Yuan, Shenfeng; Yu, Hongwei

2014-02-05

Mandelate racemase (MR) is a promising candidate for the dynamic kinetic resolution of racemates. However, the poor activity of MR towards most of its non-natural substrates limits its widespread application. In this work, a virtual screening method based on the binding energy in the transition state was established to assist in the screening of MR mutants with enhanced catalytic efficiency. Using R-3-chloromandelic acid as a model substrate, a total of 53 mutants were constructed based on rational design in the two rounds of screening. The number of mutants for experimental validation was brought down to 17 by the virtual screening method, among which 14 variants turned out to possess improved catalytic efficiency. The variant V26I/Y54V showed 5.2-fold higher catalytic efficiency (k(cat)/K(m)) towards R-3-chloromandelic acid than that observed for the wild-type enzyme. Using this strategy, mutants were successfully obtained for two other substrates, R-mandelamide and R-2-naphthylglycolate (V26I and V29L, respectively), both with a 2-fold improvement in catalytic efficiency. These results demonstrated that this method could effectively predict the trend of mutational effects on catalysis. Analysis from the energetic and structural assays indicated that the enhanced interactions between the active sites and the substrate in the transition state led to improved catalytic efficiency. It was concluded that this virtual screening method based on the binding energy in the transition state was beneficial in enzyme rational redesign and helped to better understand the catalytic properties of the enzyme. Copyright © 2013 Elsevier Inc. All rights reserved.

Structure-Based Virtual Screening of Commercially Available Compound Libraries.

PubMed

Kireev, Dmitri

2016-01-01

Virtual screening (VS) is an efficient hit-finding tool. Its distinctive strength is that it allows one to screen compound libraries that are not available in the lab. Moreover, structure-based (SB) VS also enables an understanding of how the hit compounds bind the protein target, thus laying ground work for the rational hit-to-lead progression. SBVS requires a very limited experimental effort and is particularly well suited for academic labs and small biotech companies that, unlike pharmaceutical companies, do not have physical access to quality small-molecule libraries. Here, we describe SBVS of commercial compound libraries for Mer kinase inhibitors. The screening protocol relies on the docking algorithm Glide complemented by a post-docking filter based on structural protein-ligand interaction fingerprints (SPLIF).

Screening of Potential Inhibitor against Coat Protein of Apple Chlorotic Leaf Spot Virus.

PubMed

Purohit, Rituraj; Kumar, Sachin; Hallan, Vipin

2018-06-01

In this study, we analyzed Coat protein (CP) of Apple chlorotic leaf spot virus (ACLSV), an important latent virus on Apple. Incidence of the virus is upto 60% in various apple cultivars, affecting yield losses of the order of 10-40% (depending upon the cultivar). CP plays an important role as the sole building block of the viral capsid. Homology approach was used to model 193 amino acid sequence of the coat protein. We used various servers such as ConSurf, TargetS, OSML, COACH, COFACTOR for the prediction of active site residues in coat protein. Virtual screening strategy was employed to search potential inhibitors for CP. Top twenty screened molecules considered for drugability, and toxicity analysis and one potential molecule was further analyzed by docking analysis. Here, we reported a potent molecule which could inhibit the formation of viron assembly by targeting the CP protein of virus.

Cyber risk and privacy liability: a click in the right direction?

PubMed

McDonough, William J

2007-01-01

Cyber risk and privacy exposure exert an impact upon virtually every aspect of a healthcare organization (HCO)--assets, clinical operations, finances and reputation. Exposure is enterprise-wide and includes risk to both physical and non-physical assets in increasing degrees. The consequences of a cyber attack or privacy breach could be operationally and financially catastrophic, so an HCO's move toward an enterprise-wide approach at identifying and minimizing risk, cyber and privacy liability should be on the radar screen for risk managers and leadership.

Optimization of rhodanine scaffold for the development of protein-protein interaction inhibitors.

PubMed

Ferro, Stefania; De Luca, Laura; Agharbaoui, Fatima Ezzahra; Christ, Frauke; Debyser, Zeger; Gitto, Rosaria

2015-07-01

Searching for novel protein-protein interactions inhibitors (PPIs) herein we describe the identification of a new series of rhodanine derivatives. The selection was performed by means virtual-screening, docking studies, Molecular Dynamic (MD) simulations and synthetic approaches. All the new obtained compounds were tested in order to evaluate their ability to inhibit the interaction between the HIV-1 integrase (IN) enzyme and the nuclear protein lens epithelium growth factor LEDGF/p75. Copyright © 2015 Elsevier Ltd. All rights reserved.

Discovering new PI3Kα inhibitors with a strategy of combining ligand-based and structure-based virtual screening

NASA Astrophysics Data System (ADS)

Yu, Miao; Gu, Qiong; Xu, Jun

2018-02-01

PI3Kα is a promising drug target for cancer chemotherapy. In this paper, we report a strategy of combing ligand-based and structure-based virtual screening to identify new PI3Kα inhibitors. First, naïve Bayesian (NB) learning models and a 3D-QSAR pharmacophore model were built based upon known PI3Kα inhibitors. Then, the SPECS library was screened by the best NB model. This resulted in virtual hits, which were validated by matching the structures against the pharmacophore models. The pharmacophore matched hits were then docked into PI3Kα crystal structures to form ligand-receptor complexes, which are further validated by the Glide-XP program to result in structural validated hits. The structural validated hits were examined by PI3Kα inhibitory assay. With this screening protocol, ten PI3Kα inhibitors with new scaffolds were discovered with IC50 values ranging 0.44-31.25 μM. The binding affinities for the most active compounds 33 and 74 were estimated through molecular dynamics simulations and MM-PBSA analyses.

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.

Identification of PPARgamma Partial Agonists of Natural Origin (I): Development of a Virtual Screening Procedure and In Vitro Validation

PubMed Central

Guasch, Laura; Sala, Esther; Castell-Auví, Anna; Cedó, Lidia; Liedl, Klaus R.; Wolber, Gerhard; Muehlbacher, Markus; Mulero, Miquel; Pinent, Montserrat; Ardévol, Anna; Valls, Cristina; Pujadas, Gerard; Garcia-Vallvé, Santiago

2012-01-01

Background Although there are successful examples of the discovery of new PPARγ agonists, it has recently been of great interest to identify new PPARγ partial agonists that do not present the adverse side effects caused by PPARγ full agonists. Consequently, the goal of this work was to design, apply and validate a virtual screening workflow to identify novel PPARγ partial agonists among natural products. Methodology/Principal Findings We have developed a virtual screening procedure based on structure-based pharmacophore construction, protein-ligand docking and electrostatic/shape similarity to discover novel scaffolds of PPARγ partial agonists. From an initial set of 89,165 natural products and natural product derivatives, 135 compounds were identified as potential PPARγ partial agonists with good ADME properties. Ten compounds that represent ten new chemical scaffolds for PPARγ partial agonists were selected for in vitro biological testing, but two of them were not assayed due to solubility problems. Five out of the remaining eight compounds were confirmed as PPARγ partial agonists: they bind to PPARγ, do not or only moderately stimulate the transactivation activity of PPARγ, do not induce adipogenesis of preadipocyte cells and stimulate the insulin-induced glucose uptake of adipocytes. Conclusions/Significance We have demonstrated that our virtual screening protocol was successful in identifying novel scaffolds for PPARγ partial agonists. PMID:23226391

Docking based virtual screening and molecular dynamics study to identify potential monoacylglycerol lipase inhibitors.

PubMed

Afzal, Obaid; Kumar, Suresh; Kumar, Rajiv; Firoz, Ahmad; Jaggi, Manu; Bawa, Sandhya

2014-08-15

Monoacylglycerol lipase (MAGL) is one of the key enzymes of the endocannabinoid system (ECS). It hydrolyzes one of the major endocannabinoid, 2-arachidonoylglycerol (2-AG), an endogenous full agonist at G protein coupled cannabinoid receptors CB1 and CB2. Numerous studies showed that MGL inhibitors are potentially useful for the treatment of pain, inflammation, cancer and CNS disorders. These provocative findings suggested that pharmacological inhibition of MAGL function may confer significant therapeutic benefits. In this study, we presented hybrid ligand and structure-based approaches to obtain a novel set of virtual leads as MAGL inhibitors. The constraints used in this study, were Glide score, binding free energy estimates and ADME properties to screen the ZINC database, containing approximately 21 million compounds. A total of seven virtual hits were obtained, which showed significant binding affinity towards MAGL protein. Ligand, ZINC24092691 was employed in complex form with the protein MAGL, for molecular dynamics simulation study, because of its excellent glide score, binding free energy and ADME properties. The RMSD of ZINC24092691 was observed to stay at 0.1 nm (1 Å) in most of the trajectories, which further confirmed its ability to inhibit the protein MAGL. The hits were then evaluated for their ability to inhibit human MAGL. The compound ZINC24092691 displayed the noteworthy inhibitory activity reducing MAGL activity to 21.15% at 100 nM concentration, with an IC50 value of 10 nM. Copyright © 2014 Elsevier Ltd. All rights reserved.

Virtual reality skills training for health care professionals in alcohol screening and brief intervention.

PubMed

Fleming, Michael; Olsen, Dale; Stathes, Hilary; Boteler, Laura; Grossberg, Paul; Pfeifer, Judie; Schiro, Stephanie; Banning, Jane; Skochelak, Susan

2009-01-01

Educating physicians and other health care professionals about the identification and treatment of patients who drink more than recommended limits is an ongoing challenge. An educational randomized controlled trial was conducted to test the ability of a stand-alone training simulation to improve the clinical skills of health care professionals in alcohol screening and intervention. The "virtual reality simulation" combined video, voice recognition, and nonbranching logic to create an interactive environment that allowed trainees to encounter complex social cues and realistic interpersonal exchanges. The simulation included 707 questions and statements and 1207 simulated patient responses. A sample of 102 health care professionals (10 physicians; 30 physician assistants or nurse practitioners; 36 medical students; 26 pharmacy, physican assistant, or nurse practitioner students) were randomly assigned to a no training group (n = 51) or a computer-based virtual reality intervention (n = 51). Professionals in both groups had similar pretest standardized patient alcohol screening skill scores: 53.2 (experimental) vs 54.4 (controls), 52.2 vs 53.7 alcohol brief intervention skills, and 42.9 vs 43.5 alcohol referral skills. After repeated practice with the simulation there were significant increases in the scores of the experimental group at 6 months after randomization compared with the control group for the screening (67.7 vs 58.1; P < .001) and brief intervention (58.3 vs 51.6; P < .04) scenarios. The technology tested in this trial is the first virtual reality simulation to demonstrate an increase in the alcohol screening and brief intervention skills of health care professionals.

Virtual Reality Skills Training for Health Care Professionals in Alcohol Screening and Brief Intervention

PubMed Central

Fleming, Michael; Olsen, Dale; Stathes, Hilary; Boteler, Laura; Grossberg, Paul; Pfeifer, Judie; Schiro, Stephanie; Banning, Jane; Skochelak, Susan

2009-01-01

Background Educating physicians and other health care professionals to identify and treat patients who drink above recommended limits is an ongoing challenge. Methods An educational Randomized Control Trial (RCT) was conducted to test the ability of a stand alone training simulation to improve the clinical skills of health care professionals in alcohol screening and intervention. The “virtual reality simulation” combines video, voice recognition and non branching logic to create an interactive environment that allows trainees to encounter complex social cues and realistic interpersonal exchanges. The simulation includes 707 questions and statements and 1207 simulated patient responses. Results A sample of 102 health care professionals (10 physicians; 30 physician assistants [PAs] or nurse practitioners [NPs]; 36 medical students; 26 pharmacy, PA or NP students) were randomly assigned to no training (n=51) or a computer based virtual reality intervention (n=51). Subjects in both groups had similar pre-test standardized patient alcohol screening skill scores – 53.2 (experimental) vs. 54.4 (controls), 52.2 vs. 53.7 alcohol brief intervention skills, and 42.9 vs. 43.5 alcohol referral skills. Following repeated practice with the simulation there were significant increases in the scores of the experimental group at 6 months post-randomization compared to the control group for the screening (67.7 vs. 58.1, p<.001) and brief intervention (58.3 vs. 51.6, p<.04) scenarios. Conclusions The technology tested in this trial is the first virtual reality simulation to demonstrate an increase in the alcohol screening and brief intervention skills of health care professionals. PMID:19587253

Can a virtual reality cognitive training application fulfill a dual role? Using the virtual supermarket cognitive training application as a screening tool for mild cognitive impairment.

PubMed

Zygouris, Stelios; Giakoumis, Dimitrios; Votis, Konstantinos; Doumpoulakis, Stefanos; Ntovas, Konstantinos; Segkouli, Sofia; Karagiannidis, Charalampos; Tzovaras, Dimitrios; Tsolaki, Magda

2015-01-01

Recent research advocates the potential of virtual reality (VR) applications in assessing cognitive functions highlighting the possibility of using a VR application for mild cognitive impairment (MCI) screening. The aim of this study is to investigate whether a VR cognitive training application, the virtual supermarket (VSM), can be used as a screening tool for MCI. Two groups, one of healthy older adults (n = 21) and one of MCI patients (n = 34), were recruited from day centers for cognitive disorders and administered the VSM and a neuropsychological test battery. The performance of the two groups in the VSM was compared and correlated with performance in established neuropsychological tests. At the same time, the effectiveness of a combination of traditional neuropsychological tests and the VSM was examined. VSM displayed a correct classification rate (CCR) of 87.30% when differentiating between MCI patients and healthy older adults, while it was unable to differentiate between MCI subtypes. At the same time, the VSM correlates with various established neuropsychological tests. A limited number of tests were able to improve the CCR of the VSM when combined with the VSM for screening purposes. VSM appears to be a valid method of screening for MCI in an older adult population though it cannot be used for MCI subtype assessment. VSM's concurrent validity is supported by the large number of correlations between the VSM and established tests. It is considered a robust test on its own as the inclusion of other tests failed to improve its CCR significantly.

Two-track virtual screening approach to identify both competitive and allosteric inhibitors of human small C-terminal domain phosphatase 1

NASA Astrophysics Data System (ADS)

Park, Hwangseo; Lee, Hye Seon; Ku, Bonsu; Lee, Sang-Rae; Kim, Seung Jun

2017-08-01

Despite a wealth of persuasive evidence for the involvement of human small C-terminal domain phosphatase 1 (Scp1) in the impairment of neuronal differentiation and in Huntington's disease, small-molecule inhibitors of Scp1 have been rarely reported so far. This study aims to the discovery of both competitive and allosteric Scp1 inhibitors through the two-track virtual screening procedure. By virtue of the improvement of the scoring function by implementing a new molecular solvation energy term and by reoptimizing the atomic charges for the active-site Mg2+ ion cluster, we have been able to identify three allosteric and five competitive Scp1 inhibitors with low-micromolar inhibitory activity. Consistent with the results of kinetic studies on the inhibitory mechanisms, the allosteric inhibitors appear to be accommodated in the peripheral binding pocket through the hydrophobic interactions with the nonpolar residues whereas the competitive ones bind tightly in the active site with a direct coordination to the central Mg2+ ion. Some structural modifications to improve the biochemical potency of the newly identified inhibitors are proposed based on the binding modes estimated with docking simulations.

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.

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors

PubMed Central

Xie, Huiding; Chen, Lijun; Zhang, Jianqiang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun

2015-01-01

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q2 = 0.621, r2pred = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained. PMID:26035757

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors.

PubMed

Xie, Huiding; Chen, Lijun; Zhang, Jianqiang; Xie, Xiaoguang; Qiu, Kaixiong; Fu, Jijun

2015-05-29

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q(2) = 0.621, r(2)(pred) = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.

Virtual Screening for the Development of Dual-Inhibitors Targeting Topoisomerase IB and Tyrosyl-DNA Phosphodiesterase 1.

PubMed

Cardamone, Francesca; Pizzi, Simone; Iacovelli, Federico; Falconi, Mattia; Desideri, Alessandro

2017-01-01

Human topoisomerase IB is an important target in cancer therapy and drugs selectively stabilizing the topoisomerase IB-DNA covalent complex are in clinical use for several cancer types. Tyrosyl- DNA phosphodiesterase 1 is involved in the DNA repair resolving the topoisomerase IB-DNA covalent complex that is extremely dangerous for the survival of the cells since it produces an irreversible DNA damage. Given the close biological relationship between these two enzymes, the development of synergistic inhibitors, called dual-inhibitors, is an important challenge in cancer therapy and computer-aided drug design may help in the identification of the best compounds. In this review, an overview of the compounds inhibiting one of the two enzymes or acting as dual inhibitors is provided. Moreover, the general procedures of the virtual screening approach, providing a description of two widely used opensource programs, namely AutoDock4 and AutoDock Vina, are described. Finally, an application of the two programs on a selected number of dual inhibitors for tyrosyl-DNA phosphodiesterase 1 and topoisomerase IB and their performance is briefly discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Uniqueness of Experience and Virtual Playworlds: Playing Is Not Just for Fun

ERIC Educational Resources Information Center

Talamo, Alessandra; Pozzi, Simone; Mellini, Barbara

2010-01-01

Social interactions within virtual communities are often described solely as being online experiences. Such descriptions are limited, for they fail to reference life external to the screen. The terms "virtual" and "real" have a negative connotation for many people and can even be interpreted to mean that something is "false" or "inauthentic."…

Optimal affinity ranking for automated virtual screening validated in prospective D3R grand challenges

NASA Astrophysics Data System (ADS)

Wingert, Bentley M.; Oerlemans, Rick; Camacho, Carlos J.

2018-01-01

The goal of virtual screening is to generate a substantially reduced and enriched subset of compounds from a large virtual chemistry space. Critical in these efforts are methods to properly rank the binding affinity of compounds. Prospective evaluations of ranking strategies in the D3R grand challenges show that for targets with deep pockets the best correlations (Spearman ρ 0.5) were obtained by our submissions that docked compounds to the holo-receptors with the most chemically similar ligand. On the other hand, for targets with open pockets using multiple receptor structures is not a good strategy. Instead, docking to a single optimal receptor led to the best correlations (Spearman ρ 0.5), and overall performs better than any other method. Yet, choosing a suboptimal receptor for crossdocking can significantly undermine the affinity rankings. Our submissions that evaluated the free energy of congeneric compounds were also among the best in the community experiment. Error bars of around 1 kcal/mol are still too large to significantly improve the overall rankings. Collectively, our top of the line predictions show that automated virtual screening with rigid receptors perform better than flexible docking and other more complex methods.

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

From flamingo dance to (desirable) drug discovery: a nature-inspired approach.

PubMed

Sánchez-Rodríguez, Aminael; Pérez-Castillo, Yunierkis; Schürer, Stephan C; Nicolotti, Orazio; Mangiatordi, Giuseppe Felice; Borges, Fernanda; Cordeiro, M Natalia D S; Tejera, Eduardo; Medina-Franco, José L; Cruz-Monteagudo, Maykel

2017-10-01

The therapeutic effects of drugs are well known to result from their interaction with multiple intracellular targets. Accordingly, the pharma industry is currently moving from a reductionist approach based on a 'one-target fixation' to a holistic multitarget approach. However, many drug discovery practices are still procedural abstractions resulting from the attempt to understand and address the action of biologically active compounds while preventing adverse effects. Here, we discuss how drug discovery can benefit from the principles of evolutionary biology and report two real-life case studies. We do so by focusing on the desirability principle, and its many features and applications, such as machine learning-based multicriteria virtual screening. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ligand efficiency based approach for efficient virtual screening of compound libraries.

PubMed

Ke, Yi-Yu; Coumar, Mohane Selvaraj; Shiao, Hui-Yi; Wang, Wen-Chieh; Chen, Chieh-Wen; Song, Jen-Shin; Chen, Chun-Hwa; Lin, Wen-Hsing; Wu, Szu-Huei; Hsu, John T A; Chang, Chung-Ming; Hsieh, Hsing-Pang

2014-08-18

Here we report for the first time the use of fit quality (FQ), a ligand efficiency (LE) based measure for virtual screening (VS) of compound libraries. The LE based VS protocol was used to screen an in-house database of 125,000 compounds to identify aurora kinase A inhibitors. First, 20 known aurora kinase inhibitors were docked to aurora kinase A crystal structure (PDB ID: 2W1C); and the conformations of docked ligand were used to create a pharmacophore (PH) model. The PH model was used to screen the database compounds, and rank (PH rank) them based on the predicted IC50 values. Next, LE_Scale, a weight-dependant LE function, was derived from 294 known aurora kinase inhibitors. Using the fit quality (FQ = LE/LE_Scale) score derived from the LE_Scale function, the database compounds were reranked (PH_FQ rank) and the top 151 (0.12% of database) compounds were assessed for aurora kinase A inhibition biochemically. This VS protocol led to the identification of 7 novel hits, with compound 5 showing aurora kinase A IC50 = 1.29 μM. Furthermore, testing of 5 against a panel of 31 kinase reveals that it is selective toward aurora kinase A & B, with <50% inhibition for other kinases at 10 μM concentrations and is a suitable candidate for further development. Incorporation of FQ score in the VS protocol not only helped identify a novel aurora kinase inhibitor, 5, but also increased the hit rate of the VS protocol by improving the enrichment factor (EF) for FQ based screening (EF = 828), compared to PH based screening (EF = 237) alone. The LE based VS protocol disclosed here could be applied to other targets for hit identification in an efficient manner. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

DOVIS: an implementation for high-throughput virtual screening using AutoDock.

PubMed

Zhang, Shuxing; Kumar, Kamal; Jiang, Xiaohui; Wallqvist, Anders; Reifman, Jaques

2008-02-27

Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. In addition to the selection of a sound docking strategy with appropriate scoring functions, another technical challenge is to in silico screen millions of compounds in a reasonable time. To meet this challenge, it is necessary to use high performance computing (HPC) platforms and techniques. However, the development of an integrated HPC system that makes efficient use of its elements is not trivial. We have developed an application termed DOVIS that uses AutoDock (version 3) as the docking engine and runs in parallel on a Linux cluster. DOVIS can efficiently dock large numbers (millions) of small molecules (ligands) to a receptor, screening 500 to 1,000 compounds per processor per day. Furthermore, in DOVIS, the docking session is fully integrated and automated in that the inputs are specified via a graphical user interface, the calculations are fully integrated with a Linux cluster queuing system for parallel processing, and the results can be visualized and queried. DOVIS removes most of the complexities and organizational problems associated with large-scale high-throughput virtual screening, and provides a convenient and efficient solution for AutoDock users to use this software in a Linux cluster platform.

Serious games for screening pre-dementia conditions: from virtuality to reality? A pilot project.

PubMed

Zucchella, Chiara; Sinforiani, Elena; Tassorelli, Cristina; Cavallini, Elena; Tost-Pardell, Daniela; Grau, Sergi; Pazzi, Stefania; Puricelli, Stefano; Bernini, Sara; Bottiroli, Sara; Vecchi, Tomaso; Sandrini, Giorgio; Nappi, Giuseppe

2014-01-01

Conventional cognitive assessment is based on a pencil-and-paper neuropsychological evaluation, which is time consuming, expensive and requires the involvement of several professionals. Information and communication technology could be exploited to allow the development of tools that are easy to use, reduce the amount of data processing, and provide controllable test conditions. Serious games (SGs) have the potential to be new and effective tools in the management and treatment of cognitive impairments Serious games for screening pre-dementia conditions: from virtuality to reality? A pilot project in the elderly. Moreover, by adopting SGs in 3D virtual reality settings, cognitive functions might be evaluated using tasks that simulate daily activities, increasing the "ecological validity" of the assessment. In this commentary we report our experience in the creation of the Smart Aging platform, a 3D SGand virtual environment-based platform for the early identification and characterization of mild cognitive impairment.

Comparative Modeling and Benchmarking Data Sets for Human Histone Deacetylases and Sirtuin Families

PubMed Central

Xia, Jie; Tilahun, Ermias Lemma; Kebede, Eyob Hailu; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon

2015-01-01

Histone Deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective Histone Deacetylases Inhibitors (HDACIs). To facilitate the process, we constructed the Maximal Unbiased Benchmarking Data Sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs covers all 4 Classes including Class III (Sirtuins family) and 14 HDACs isoforms, composed of 631 inhibitors and 24,609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of “artificial enrichment” and “analogue bias”. We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets, and demonstrate that our MUBD-HDACs is unique in that it can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the “2D bias” and “LBVS favorable” effect within the benchmarking sets. In summary, MUBD-HDACs is the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that is available so far. MUBD-HDACs is freely available at http://www.xswlab.org/. PMID:25633490

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.

Discovery of d-amino acid oxidase inhibitors based on virtual screening against the lid-open enzyme conformation.

PubMed

Szilágyi, Bence; Skok, Žiga; Rácz, Anita; Frlan, Rok; Ferenczy, György G; Ilaš, Janez; Keserű, György M

2018-06-01

d-Amino acid oxidase (DAAO) inhibitors are typically small polar compounds with often suboptimal pharmacokinetic properties. Features of the native binding site limit the operational freedom of further medicinal chemistry efforts. We therefore initiated a structure based virtual screening campaign based on the X-ray structures of DAAO complexes where larger ligands shifted the loop (lid opening) covering the native binding site. The virtual screening of our in-house collection followed by the in vitro test of the best ranked compounds led to the identification of a new scaffold with micromolar IC 50 . Subsequent SAR explorations enabled us to identify submicromolar inhibitors. Docking studies supported by in vitro activity measurements suggest that compounds bind to the active site with a salt-bridge characteristic to DAAO inhibitor binding. In addition, displacement of and interaction with the loop covering the active site contributes significantly to the activity of the most potent compounds. Copyright © 2018 Elsevier Ltd. All rights reserved.

The power metric: a new statistically robust enrichment-type metric for virtual screening applications with early recovery capability.

PubMed

Lopes, Julio Cesar Dias; Dos Santos, Fábio Mendes; Martins-José, Andrelly; Augustyns, Koen; De Winter, Hans

2017-01-01

A new metric for the evaluation of model performance in the field of virtual screening and quantitative structure-activity relationship applications is described. This metric has been termed the power metric and is defined as the fraction of the true positive rate divided by the sum of the true positive and false positive rates, for a given cutoff threshold. The performance of this metric is compared with alternative metrics such as the enrichment factor, the relative enrichment factor, the receiver operating curve enrichment factor, the correct classification rate, Matthews correlation coefficient and Cohen's kappa coefficient. The performance of this new metric is found to be quite robust with respect to variations in the applied cutoff threshold and ratio of the number of active compounds to the total number of compounds, and at the same time being sensitive to variations in model quality. It possesses the correct characteristics for its application in early-recognition virtual screening problems.

Combination of virtual screening protocol by in silico towards the discovery of novel 4-hydroxyphenylpyruvate dioxygenase inhibitors

NASA Astrophysics Data System (ADS)

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2018-02-01

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) is a potent new bleaching herbicide target. Therefore, in silico structure-based virtual screening was performed in order to speed up the identification of promising HPPD inhibitors. In this study, an integrated virtual screening protocol by combining 3D-pharmacophore model, molecular docking and molecular dynamics (MD) simulation was established to find novel HPPD inhibitors from four commercial databases. 3D-pharmacophore Hypo1 model was applied to efficiently narrow potential hits. The hit compounds were subsequently submitted to molecular docking studies, showing four compounds as potent inhibitor with the mechanism of the Fe(II) coordination and interaction with Phe360, Phe403 and Phe398. MD result demonstrated that nonpolar term of compound 3881 made great contributions to binding affinities. It showed an IC50 being 2.49 µM against AtHPPD in vitro. The results provided useful information for developing novel HPPD inhibitors, leading to further understanding of the interaction mechanism of HPPD inhibitors.

Docking and scoring with ICM: the benchmarking results and strategies for improvement

PubMed Central

Neves, Marco A. C.; Totrov, Maxim; Abagyan, Ruben

2012-01-01

Flexible docking and scoring using the Internal Coordinate Mechanics software (ICM) was benchmarked for ligand binding mode prediction against the 85 co-crystal structures in the modified Astex data set. The ICM virtual ligand screening was tested against the 40 DUD target benchmarks and 11-target WOMBAT sets. The self-docking accuracy was evaluated for the top 1 and top 3 scoring poses at each ligand binding site with near native conformations below 2 Å RMSD found in 91% and 95% of the predictions, respectively. The virtual ligand screening using single rigid pocket conformations provided the median area under the ROC curves equal to 69.4 with 22.0% true positives recovered at 2% false positive rate. Significant improvements up to ROC AUC= 82.2 and ROC(2%)= 45.2 were achieved following our best practices for flexible pocket refinement and out-of-pocket binding rescore. The virtual screening can be further improved by considering multiple conformations of the target. PMID:22569591

Enhancing the Sensitivity of Pharmacophore-Based Virtual Screening by Incorporating Customized ZBG Features: A Case Study Using Histone Deacetylase 8.

PubMed

Hou, Xuben; Du, Jintong; Liu, Renshuai; Zhou, Yi; Li, Minyong; Xu, Wenfang; Fang, Hao

2015-04-27

As key regulators of epigenetic regulation, human histone deacetylases (HDACs) have been identified as drug targets for the treatment of several cancers. The proper recognition of zinc-binding groups (ZBGs) will help improve the accuracy of virtual screening for novel HDAC inhibitors. Here, we developed a high-specificity ZBG-based pharmacophore model for HDAC8 inhibitors by incorporating customized ZBG features. Subsequently, pharmacophore-based virtual screening led to the discovery of three novel HDAC8 inhibitors with low micromole IC50 values (1.8-1.9 μM). Further studies demonstrated that compound H8-A5 was selective for HDAC8 over HDAC 1/4 and showed antiproliferation activity in MDA-MB-231 cancer cells. Molecular docking and molecular dynamic studies suggested a possible binding mode for H8-A5, which provides a good starting point for the development of HDAC8 inhibitors in cancer treatment.

Statistical analysis of EGFR structures' performance in virtual screening

NASA Astrophysics Data System (ADS)

Li, Yan; Li, Xiang; Dong, Zigang

2015-11-01

In this work the ability of EGFR structures to distinguish true inhibitors from decoys in docking and MM-PBSA is assessed by statistical procedures. The docking performance depends critically on the receptor conformation and bound state. The enrichment of known inhibitors is well correlated with the difference between EGFR structures rather than the bound-ligand property. The optimal structures for virtual screening can be selected based purely on the complex information. And the mixed combination of distinct EGFR conformations is recommended for ensemble docking. In MM-PBSA, a variety of EGFR structures have identically good performance in the scoring and ranking of known inhibitors, indicating that the choice of the receptor structure has little effect on the screening.

Dynamic undocking and the quasi-bound state as tools for drug discovery

NASA Astrophysics Data System (ADS)

Ruiz-Carmona, Sergio; Schmidtke, Peter; Luque, F. Javier; Baker, Lisa; Matassova, Natalia; Davis, Ben; Roughley, Stephen; Murray, James; Hubbard, Rod; Barril, Xavier

2017-03-01

There is a pressing need for new technologies that improve the efficacy and efficiency of drug discovery. Structure-based methods have contributed towards this goal but they focus on predicting the binding affinity of protein-ligand complexes, which is notoriously difficult. We adopt an alternative approach that evaluates structural, rather than thermodynamic, stability. As bioactive molecules present a static binding mode, we devised dynamic undocking (DUck), a fast computational method to calculate the work necessary to reach a quasi-bound state at which the ligand has just broken the most important native contact with the receptor. This non-equilibrium property is surprisingly effective in virtual screening because true ligands form more-resilient interactions than decoys. Notably, DUck is orthogonal to docking and other 'thermodynamic' methods. We demonstrate the potential of the docking-undocking combination in a fragment screening against the molecular chaperone and oncology target Hsp90, for which we obtain novel chemotypes and a hit rate that approaches 40%.

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.

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.

Systematic Exploitation of Multiple Receptor Conformations for Virtual Ligand Screening

PubMed Central

Bottegoni, Giovanni; Rocchia, Walter; Rueda, Manuel; Abagyan, Ruben; Cavalli, Andrea

2011-01-01

The role of virtual ligand screening in modern drug discovery is to mine large chemical collections and to prioritize for experimental testing a comparatively small and diverse set of compounds with expected activity against a target. Several studies have pointed out that the performance of virtual ligand screening can be improved by taking into account receptor flexibility. Here, we systematically assess how multiple crystallographic receptor conformations, a powerful way of discretely representing protein plasticity, can be exploited in screening protocols to separate binders from non-binders. Our analyses encompass 36 targets of pharmaceutical relevance and are based on actual molecules with reported activity against those targets. The results suggest that an ensemble receptor-based protocol displays a stronger discriminating power between active and inactive molecules as compared to its standard single rigid receptor counterpart. Moreover, such a protocol can be engineered not only to enrich a higher number of active compounds, but also to enhance their chemical diversity. Finally, some clear indications can be gathered on how to select a subset of receptor conformations that is most likely to provide the best performance in a real life scenario. PMID:21625529

On various metrics used for validation of predictive QSAR models with applications in virtual screening and focused library design.

PubMed

Roy, Kunal; Mitra, Indrani

2011-07-01

Quantitative structure-activity relationships (QSARs) have important applications in drug discovery research, environmental fate modeling, property prediction, etc. Validation has been recognized as a very important step for QSAR model development. As one of the important objectives of QSAR modeling is to predict activity/property/toxicity of new chemicals falling within the domain of applicability of the developed models and QSARs are being used for regulatory decisions, checking reliability of the models and confidence of their predictions is a very important aspect, which can be judged during the validation process. One prime application of a statistically significant QSAR model is virtual screening for molecules with improved potency based on the pharmacophoric features and the descriptors appearing in the QSAR model. Validated QSAR models may also be utilized for design of focused libraries which may be subsequently screened for the selection of hits. The present review focuses on various metrics used for validation of predictive QSAR models together with an overview of the application of QSAR models in the fields of virtual screening and focused library design for diverse series of compounds with citation of some recent examples.

Large-scale systematic analysis of 2D fingerprint methods and parameters to improve virtual screening enrichments.

PubMed

Sastry, Madhavi; Lowrie, Jeffrey F; Dixon, Steven L; Sherman, Woody

2010-05-24

A systematic virtual screening study on 11 pharmaceutically relevant targets has been conducted to investigate the interrelation between 8 two-dimensional (2D) fingerprinting methods, 13 atom-typing schemes, 13 bit scaling rules, and 12 similarity metrics using the new cheminformatics package Canvas. In total, 157 872 virtual screens were performed to assess the ability of each combination of parameters to identify actives in a database screen. In general, fingerprint methods, such as MOLPRINT2D, Radial, and Dendritic that encode information about local environment beyond simple linear paths outperformed other fingerprint methods. Atom-typing schemes with more specific information, such as Daylight, Mol2, and Carhart were generally superior to more generic atom-typing schemes. Enrichment factors across all targets were improved considerably with the best settings, although no single set of parameters performed optimally on all targets. The size of the addressable bit space for the fingerprints was also explored, and it was found to have a substantial impact on enrichments. Small bit spaces, such as 1024, resulted in many collisions and in a significant degradation in enrichments compared to larger bit spaces that avoid collisions.

Computational discovery of putative quorum sensing inhibitors against LasR and RhlR receptor proteins of Pseudomonas aeruginosa

NASA Astrophysics Data System (ADS)

Annapoorani, Angusamy; Umamageswaran, Venugopal; Parameswari, Radhakrishnan; Pandian, Shunmugiah Karutha; Ravi, Arumugam Veera

2012-09-01

Drugs have been discovered in the past mainly either by identification of active components from traditional remedies or by unpredicted discovery. A key motivation for the study of structure based virtual screening is the exploitation of such information to design targeted drugs. In this study, structure based virtual screening was used in search for putative quorum sensing inhibitors (QSI) of Pseudomonas aeruginosa. The virtual screening programme Glide version 5.5 was applied to screen 1,920 natural compounds/drugs against LasR and RhlR receptor proteins of P. aeruginosa. Based on the results of in silico docking analysis, five top ranking compounds namely rosmarinic acid, naringin, chlorogenic acid, morin and mangiferin were subjected to in vitro bioassays against laboratory strain PAO1 and two more antibiotic resistant clinical isolates, P. aeruginosa AS1 (GU447237) and P. aeruginosa AS2 (GU447238). Among the five compounds studied, except mangiferin other four compounds showed significant inhibition in the production of protease, elastase and hemolysin. Further, all the five compounds potentially inhibited the biofilm related behaviours. This interaction study provided promising ligands to inhibit the quorum sensing (QS) mediated virulence factors production in P. aeruginosa.

Vitual screening and binding mode elucidation of curcumin analogues on Cyclooxygenase-2 using AYO_COX2_V1.1 protocol

NASA Astrophysics Data System (ADS)

Mulatsari, E.; Mumpuni, E.; Herfian, A.

2017-05-01

Curcumin is yellow colored phenolic compounds contained in Curcuma longa. Curcumin is known to have biological activities as anti-inflammatory, antiviral, antioxidant, and anti-infective agent [1]. Synthesis of curcumin analogue compounds has been done and some of them had biological activity like curcumin. In this research, the virtual screening of curcumin analogue compounds has been conducted. The purpose of this research was to determine the activity of these compounds as selective Cyclooxygenase-2inhibitors in in-silico. Binding mode elucidation was made by active and inactive representative compounds to see the interaction of the amino acids in the binding site of the compounds. This research used AYO_COX2_V.1.1, a structure-based virtual screening protocol (SBVS) that has been validated by Mumpuni E et al, 2014 [2]. AYO_COX2_V.1.1 protocol using a variety of integrated applications such as SPORES, PLANTS, BKchem, OpenBabel and PyMOL. The results of virtual screening conducted on 49 curcumin analogue compounds obtained 8 compounds with 4 active amino acid residues (GLY340, ILE503, PHE343, and PHE367) that were considered active as COX-2 inhibitor.

iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian

2011-06-01

The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.

iScreen: world's first cloud-computing web server for virtual screening and de novo drug design based on TCM database@Taiwan.

PubMed

Tsai, Tsung-Ying; Chang, Kai-Wei; Chen, Calvin Yu-Chian

2011-06-01

The rapidly advancing researches on traditional Chinese medicine (TCM) have greatly intrigued pharmaceutical industries worldwide. To take initiative in the next generation of drug development, we constructed a cloud-computing system for TCM intelligent screening system (iScreen) based on TCM Database@Taiwan. iScreen is compacted web server for TCM docking and followed by customized de novo drug design. We further implemented a protein preparation tool that both extract protein of interest from a raw input file and estimate the size of ligand bind site. In addition, iScreen is designed in user-friendly graphic interface for users who have less experience with the command line systems. For customized docking, multiple docking services, including standard, in-water, pH environment, and flexible docking modes are implemented. Users can download first 200 TCM compounds of best docking results. For TCM de novo drug design, iScreen provides multiple molecular descriptors for a user's interest. iScreen is the world's first web server that employs world's largest TCM database for virtual screening and de novo drug design. We believe our web server can lead TCM research to a new era of drug development. The TCM docking and screening server is available at http://iScreen.cmu.edu.tw/.

Using Hierarchical Virtual Screening To Combat Drug Resistance of the HIV-1 Protease.

PubMed

Li, Nan; Ainsworth, Richard I; Ding, Bo; Hou, Tingjun; Wang, Wei

2015-07-27

Human immunodeficiency virus (HIV) protease inhibitors (PIs) are important components of highly active anti-retroviral therapy (HAART) that block the catalytic site of HIV protease, thus preventing maturation of the HIV virion. However, with two decades of PI prescriptions in clinical practice, drug-resistant HIV mutants have now been found for all of the PI drugs. Therefore, the continuous development of new PI drugs is crucial both to combat the existing drug-resistant HIV strains and to provide treatments for future patients. Here we purpose an HIV PI drug design strategy to select candidate PIs with binding energy distributions dominated by interactions with conserved protease residues in both wild-type and various drug-resistant mutants. On the basis of this strategy, we have constructed a virtual screening pipeline including combinatorial library construction, combinatorial docking, MM/GBSA-based rescoring, and reranking on the basis of the binding energy distribution. We have tested our strategy on lopinavir by modifying its two functional groups. From an initial 751 689 candidate molecules, 18 candidate inhibitors were selected using the pipeline for experimental validation. IC50 measurements and drug resistance predictions successfully identified two ligands with both HIV protease inhibitor activity and an improved drug resistance profile on 2382 HIV mutants. This study provides a proof of concept for the integration of MM/GBSA energy analysis and drug resistance information at the stage of virtual screening and sheds light on future HIV drug design and the use of virtual screening to combat drug resistance.

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge

PubMed Central

Gallicchio, Emilio; Deng, Nanjie; He, Peng; Wickstrom, Lauren; Perryman, Alexander L.; Santiago, Daniel N.; Forli, Stefano; Olson, Arthur J.; Levy, Ronald M.

2014-01-01

As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization. PMID:24504704

Prospective performance evaluation of selected common virtual screening tools. Case study: Cyclooxygenase (COX) 1 and 2.

PubMed

Kaserer, Teresa; Temml, Veronika; Kutil, Zsofia; Vanek, Tomas; Landa, Premysl; Schuster, Daniela

2015-01-01

Computational methods can be applied in drug development for the identification of novel lead candidates, but also for the prediction of pharmacokinetic properties and potential adverse effects, thereby aiding to prioritize and identify the most promising compounds. In principle, several techniques are available for this purpose, however, which one is the most suitable for a specific research objective still requires further investigation. Within this study, the performance of several programs, representing common virtual screening methods, was compared in a prospective manner. First, we selected top-ranked virtual screening hits from the three methods pharmacophore modeling, shape-based modeling, and docking. For comparison, these hits were then additionally predicted by external pharmacophore- and 2D similarity-based bioactivity profiling tools. Subsequently, the biological activities of the selected hits were assessed in vitro, which allowed for evaluating and comparing the prospective performance of the applied tools. Although all methods performed well, considerable differences were observed concerning hit rates, true positive and true negative hits, and hitlist composition. Our results suggest that a rational selection of the applied method represents a powerful strategy to maximize the success of a research project, tightly linked to its aims. We employed cyclooxygenase as application example, however, the focus of this study lied on highlighting the differences in the virtual screening tool performances and not in the identification of novel COX-inhibitors. Copyright © 2015 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Electrophysiological characterization of 14-benzoyltalatisamine, a selective blocker of the delayed rectifier K+ channel found in virtual screening.

PubMed

Song, Ming-Ke; Liu, Hong; Jiang, Hua-Liang; Yue, Jian-Min; Hu, Guo-Yuan

2006-02-15

14-Benzoyltalatisamine is a potent and selective blocker of the delayed rectifier K+ channel found in a computational virtual screening study. The compound was found to block the K+ channel from the extracellular side. However, it is unclear whether 14-benzoyltalatisamine shares the same block mechanism with tetraethylammonium (TEA). In order to elucidate how the hit compound found by the virtual screening interacts with the outer vestibule of the K+ channel, the effects of 14-benzoyltalatisamine and TEA on the delayed rectifier K+ current of rat dissociated hippocampal neurons were compared using whole-cell voltage-clamp recording. External application of 14-benzoyltalatisamine and TEA reversibly inhibited the current with IC50 values of 10.1+/-2.2 microM and 1.05+/-0.21 mM, respectively. 14-Benzoyltalatisamine exerted voltage-dependent inhibition, markedly accelerated the decay of the current, and caused a significant hyperpolarizing shift of the steady-state activation curve, whereas TEA caused voltage-independent inhibition, without affecting the kinetic parameters of the current. The blockade by 14-benzoyltalatisamine, but not by TEA, was significantly diminished in a high K+ (60 mM) external solution. The potency of 14-benzoyltalatisamine was markedly reduced in the presence of 15 mM TEA. The results suggest that 14-benzoyltalatisamine bind to the external pore entry of the delayed rectifier K+ channel with partial insertion into the selectivity filter, which is in conformity with that predicted by the molecular docking model in the virtual screening.

Investigation of tracking systems properties in CAVE-type virtual reality systems

NASA Astrophysics Data System (ADS)

Szymaniak, Magda; Mazikowski, Adam; Meironke, Michał

2017-08-01

In recent years, many scientific and industrial centers in the world developed a virtual reality systems or laboratories. One of the most advanced solutions are Immersive 3D Visualization Lab (I3DVL), a CAVE-type (Cave Automatic Virtual Environment) laboratory. It contains two CAVE-type installations: six-screen installation arranged in a form of a cube, and four-screen installation, a simplified version of the previous one. The user feeling of "immersion" and interaction with virtual world depend on many factors, in particular on the accuracy of the tracking system of the user. In this paper properties of the tracking systems applied in I3DVL was investigated. For analysis two parameters were selected: the accuracy of the tracking system and the range of detection of markers by the tracking system in space of the CAVE. Measurements of system accuracy were performed for six-screen installation, equipped with four tracking cameras for three axes: X, Y, Z. Rotation around the Y axis was also analyzed. Measured tracking system shows good linear and rotating accuracy. The biggest issue was the range of the monitoring of markers inside the CAVE. It turned out, that the tracking system lose sight of the markers in the corners of the installation. For comparison, for a simplified version of CAVE (four-screen installation), equipped with eight tracking cameras, this problem was not occur. Obtained results will allow for improvement of cave quality.

3D-QSAR and virtual screening studies of thiazolidine-2,4-dione analogs: Validation of experimental inhibitory potencies towards PIM-1 kinase

NASA Astrophysics Data System (ADS)

Asati, Vivek; Bharti, Sanjay Kumar; Budhwani, Ashok Kumar

2017-04-01

The proviral insertion site in moloney murine leukemia virus (PIM) is a family of serine/threonine kinase of Ca2+-calmodulin-dependent protein kinase (CAMK) group which is responsible for the activation and regulation of cellular transcription and translation. The three isoforms of PIM kinase (PIM-1, PIM-2 and PIM-3) share high homology and functional idleness are widely expressed and involved in a variety of biological processes including cell survival, proliferation, differentiation and apoptosis. Altered expression of PIM-1 kinase correlated with hematologic malignancies and solid tumors. In the present study, atom-based 3D-QSAR, docking and virtual screening studies have been performed on a series of thiazolidine-2,4-dione derivatives as PIM-1 kinase inhibitors. 3D-QSAR and docking approach has shortlisted the most active thiazolidine-2,4-dione derivatives such as 28, 31, 33 and 35 with the incorporation of more than one structural feature in a single molecule. External validations by various parameters and molecular docking studies at the active site of PIM-1 kinase have proved the reliability of the developed 3D-QSAR model. The generated pharmacophore (AADHR.33) from 3D-QSAR study was used for screening of drug like compounds from ZINC database, where ZINC15056464 and ZINC83292944 showed potential binding affinities at the active site amino acid residues (LYS67, GLU171, ASP128 and ASP186) of PIM-1 kinase.

Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors

PubMed Central

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W.; Schuster, Daniela

2017-01-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing's syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8–10), one selective CYP11B1 inhibitor (Compound 11, IC50 = 2.5 μM), and one selective CYP11B2 inhibitor (compound 12, IC50 = 1.1 μM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models. PMID:29312923

Virtual environment architecture for rapid application development

NASA Technical Reports Server (NTRS)

Grinstein, Georges G.; Southard, David A.; Lee, J. P.

1993-01-01

We describe the MITRE Virtual Environment Architecture (VEA), a product of nearly two years of investigations and prototypes of virtual environment technology. This paper discusses the requirements for rapid prototyping, and an architecture we are developing to support virtual environment construction. VEA supports rapid application development by providing a variety of pre-built modules that can be reconfigured for each application session. The modules supply interfaces for several types of interactive I/O devices, in addition to large-screen or head-mounted displays.

Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance.

PubMed

Chaput, Ludovic; Martinez-Sanz, Juan; Saettel, Nicolas; Mouawad, Liliane

2016-01-01

In a structure-based virtual screening, the choice of the docking program is essential for the success of a hit identification. Benchmarks are meant to help in guiding this choice, especially when undertaken on a large variety of protein targets. Here, the performance of four popular virtual screening programs, Gold, Glide, Surflex and FlexX, is compared using the Directory of Useful Decoys-Enhanced database (DUD-E), which includes 102 targets with an average of 224 ligands per target and 50 decoys per ligand, generated to avoid biases in the benchmarking. Then, a relationship between these program performances and the properties of the targets or the small molecules was investigated. The comparison was based on two metrics, with three different parameters each. The BEDROC scores with α = 80.5, indicated that, on the overall database, Glide succeeded (score > 0.5) for 30 targets, Gold for 27, FlexX for 14 and Surflex for 11. The performance did not depend on the hydrophobicity nor the openness of the protein cavities, neither on the families to which the proteins belong. However, despite the care in the construction of the DUD-E database, the small differences that remain between the actives and the decoys likely explain the successes of Gold, Surflex and FlexX. Moreover, the similarity between the actives of a target and its crystal structure ligand seems to be at the basis of the good performance of Glide. When all targets with significant biases are removed from the benchmarking, a subset of 47 targets remains, for which Glide succeeded for only 5 targets, Gold for 4 and FlexX and Surflex for 2. The performance dramatic drop of all four programs when the biases are removed shows that we should beware of virtual screening benchmarks, because good performances may be due to wrong reasons. Therefore, benchmarking would hardly provide guidelines for virtual screening experiments, despite the tendency that is maintained, i.e., Glide and Gold display better performance than FlexX and Surflex. We recommend to always use several programs and combine their results. Graphical AbstractSummary of the results obtained by virtual screening with the four programs, Glide, Gold, Surflex and FlexX, on the 102 targets of the DUD-E database. The percentage of targets with successful results, i.e., with BDEROC(α = 80.5) > 0.5, when the entire database is considered are in Blue, and when targets with biased chemical libraries are removed are in Red.

Virtual Screening Techniques to Probe the Antimalarial Activity of some Traditionally Used Phytochemicals.

PubMed

Shibi, Indira G; Aswathy, Lilly; Jisha, Radhakrishnan S; Masand, Vijay H; Gajbhiye, Jayant M

2016-01-01

Malaria parasites show resistance to most of the antimalarial drugs and hence developing antimalarials which can act on multitargets rather than a single target will be a promising strategy of drug design. Here we report a new approach by which virtual screening of 292 unique phytochemicals present in 72 traditionally important herbs is used for finding out inhibitors of plasmepsin-2 and falcipain-2 for antimalarial activity against P. falciparum. Initial screenings of the selected molecules by Random Forest algorithm model of Weka using the bioassay datasets AID 504850 and AID 2302 screened 120 out of the total 292 phytochemicals to be active against the targets. Toxtree scan cautioned 21 compounds to be either carcinogenic or mutagenic and were thus removed for further analysis. Out of the remaining 99 compounds, only 46 compounds offered drug-likeness as per the 'rule of five' criteria. Out of ten antimalarial drug targets, only two target proteins such as 3BPF and 3PNR of falcipain-2 and 1PFZ and 2BJU of plasmepsin-2 are selected as targets. The potential binding of the selected 46 compounds to the active sites of these four targets was analyzed using MOE software. The docked conformations and the interactions with the binding pocket residues of the target proteins were understood by 'Ligplot' analysis. It has been found that 8 compounds are dual inhibitors of falcipain-2 and plasmepsin-2, with the best binding energies. Compound 117 (6aR, 12aS)-12a-Hydroxy-9-methoxy-2,3-dimethylenedioxy-8-prenylrotenone (Usaratenoid C) present in the plant Millettia usaramensis showed maximum molecular docking score.

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

SYNOPSIS: The question of how tissues and organs are shaped during development is crucial for understanding human birth defects. Data from high-throughput screening assays on human stem cells may be utilized predict developmental toxicity with reasonable accuracy. Other types of models are necessary, however, for mechanism-specific analysis because embryogenesis requires precise timing and control. Agent-based modeling and simulation (ABMS) is an approach to virtually reconstruct these dynamics, cell-by-cell and interaction-by-interaction. Using ABMS, HTS lesions from ToxCast can be integrated with patterning systems heuristically to propagate key events This presentation to FDA-CFSAN will update progress on the applications of in silico modeling tools and approaches for assessing developmental toxicity.

Identification by Virtual Screening and In Vitro Testing of Human DOPA Decarboxylase Inhibitors

PubMed Central

Cellini, Barbara; Macchiarulo, Antonio; Giardina, Giorgio; Bossa, Francesco; Borri Voltattorni, Carla

2012-01-01

Dopa decarboxylase (DDC), a pyridoxal 5′-phosphate (PLP) enzyme responsible for the biosynthesis of dopamine and serotonin, is involved in Parkinson's disease (PD). PD is a neurodegenerative disease mainly due to a progressive loss of dopamine-producing cells in the midbrain. Co-administration of L-Dopa with peripheral DDC inhibitors (carbidopa or benserazide) is the most effective symptomatic treatment for PD. Although carbidopa and trihydroxybenzylhydrazine (the in vivo hydrolysis product of benserazide) are both powerful irreversible DDC inhibitors, they are not selective because they irreversibly bind to free PLP and PLP-enzymes, thus inducing diverse side effects. Therefore, the main goals of this study were (a) to use virtual screening to identify potential human DDC inhibitors and (b) to evaluate the reliability of our virtual-screening (VS) protocol by experimentally testing the “in vitro” activity of selected molecules. Starting from the crystal structure of the DDC-carbidopa complex, a new VS protocol, integrating pharmacophore searches and molecular docking, was developed. Analysis of 15 selected compounds, obtained by filtering the public ZINC database, yielded two molecules that bind to the active site of human DDC and behave as competitive inhibitors with Ki values ≥10 µM. By performing in silico similarity search on the latter compounds followed by a substructure search using the core of the most active compound we identified several competitive inhibitors of human DDC with Ki values in the low micromolar range, unable to bind free PLP, and predicted to not cross the blood-brain barrier. The most potent inhibitor with a Ki value of 500 nM represents a new lead compound, targeting human DDC, that may be the basis for lead optimization in the development of new DDC inhibitors. To our knowledge, a similar approach has not been reported yet in the field of DDC inhibitors discovery. PMID:22384042

Identification by virtual screening and in vitro testing of human DOPA decarboxylase inhibitors.

PubMed

Daidone, Frederick; Montioli, Riccardo; Paiardini, Alessandro; Cellini, Barbara; Macchiarulo, Antonio; Giardina, Giorgio; Bossa, Francesco; Borri Voltattorni, Carla

2012-01-01

Dopa decarboxylase (DDC), a pyridoxal 5'-phosphate (PLP) enzyme responsible for the biosynthesis of dopamine and serotonin, is involved in Parkinson's disease (PD). PD is a neurodegenerative disease mainly due to a progressive loss of dopamine-producing cells in the midbrain. Co-administration of L-Dopa with peripheral DDC inhibitors (carbidopa or benserazide) is the most effective symptomatic treatment for PD. Although carbidopa and trihydroxybenzylhydrazine (the in vivo hydrolysis product of benserazide) are both powerful irreversible DDC inhibitors, they are not selective because they irreversibly bind to free PLP and PLP-enzymes, thus inducing diverse side effects. Therefore, the main goals of this study were (a) to use virtual screening to identify potential human DDC inhibitors and (b) to evaluate the reliability of our virtual-screening (VS) protocol by experimentally testing the "in vitro" activity of selected molecules. Starting from the crystal structure of the DDC-carbidopa complex, a new VS protocol, integrating pharmacophore searches and molecular docking, was developed. Analysis of 15 selected compounds, obtained by filtering the public ZINC database, yielded two molecules that bind to the active site of human DDC and behave as competitive inhibitors with K(i) values ≥10 µM. By performing in silico similarity search on the latter compounds followed by a substructure search using the core of the most active compound we identified several competitive inhibitors of human DDC with K(i) values in the low micromolar range, unable to bind free PLP, and predicted to not cross the blood-brain barrier. The most potent inhibitor with a K(i) value of 500 nM represents a new lead compound, targeting human DDC, that may be the basis for lead optimization in the development of new DDC inhibitors. To our knowledge, a similar approach has not been reported yet in the field of DDC inhibitors discovery.

Modeling of luminance distribution in CAVE-type virtual reality systems

NASA Astrophysics Data System (ADS)

Meironke, Michał; Mazikowski, Adam

2017-08-01

At present, one of the most advanced virtual reality systems are CAVE-type (Cave Automatic Virtual Environment) installations. Such systems are usually consisted of four, five or six projection screens and in case of six screens arranged in form of a cube. Providing the user with a high level of immersion feeling in such systems is largely dependent of optical properties of the system. The modeling of physical phenomena plays nowadays a huge role in the most fields of science and technology. It allows to simulate work of device without a need to make any changes in the physical constructions. In this paper distribution of luminance in CAVE-type virtual reality systems were modelled. Calculations were performed for the model of 6-walled CAVE-type installation, based on Immersive 3D Visualization Laboratory, situated at the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk University of Technology. Tests have been carried out for two different scattering distribution of the screen material in order to check how these characteristicinfluence on the luminance distribution of the whole CAVE. The basis assumption and simplification of modeled CAVE-type installation and results were presented. The brief discussion about the results and usefulness of developed model were also carried out.

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.

Virtual screening for potential inhibitors of bacterial MurC and MurD ligases.

PubMed

Tomašić, Tihomir; Kovač, Andreja; Klebe, Gerhard; Blanot, Didier; Gobec, Stanislav; Kikelj, Danijel; Mašič, Lucija Peterlin

2012-03-01

Mur ligases are bacterial enzymes involved in the cytoplasmic steps of peptidoglycan biosynthesis and are viable targets for antibacterial drug discovery. We have performed virtual screening for potential ATP-competitive inhibitors targeting MurC and MurD ligases, using a protocol of consecutive hierarchical filters. Selected compounds were evaluated for inhibition of MurC and MurD ligases, and weak inhibitors possessing dual inhibitory activity have been identified. These compounds represent new scaffolds for further optimisation towards multiple Mur ligase inhibitors with improved inhibitory potency.

Rapid identification of Keap1-Nrf2 small-molecule inhibitors through structure-based virtual screening and hit-based substructure search.

PubMed

Zhuang, Chunlin; Narayanapillai, Sreekanth; Zhang, Wannian; Sham, Yuk Yin; Xing, Chengguo

2014-02-13

In this study, rapid structure-based virtual screening and hit-based substructure search were utilized to identify small molecules that disrupt the interaction of Keap1-Nrf2. Special emphasis was placed toward maximizing the exploration of chemical diversity of the initial hits while economically establishing informative structure-activity relationship (SAR) of novel scaffolds. Our most potent noncovalent inhibitor exhibits three times improved cellular activation in Nrf2 activation than the most active noncovalent Keap1 inhibitor known to date.

Evaluating visual discomfort in stereoscopic projection-based CAVE system with a close viewing distance

NASA Astrophysics Data System (ADS)

Song, Weitao; Weng, Dongdong; Feng, Dan; Li, Yuqian; Liu, Yue; Wang, Yongtian

2015-05-01

As one of popular immersive Virtual Reality (VR) systems, stereoscopic cave automatic virtual environment (CAVE) system is typically consisted of 4 to 6 3m-by-3m sides of a room made of rear-projected screens. While many endeavors have been made to reduce the size of the projection-based CAVE system, the issue of asthenopia caused by lengthy exposure to stereoscopic images in such CAVE with a close viewing distance was seldom tangled. In this paper, we propose a light-weighted approach which utilizes a convex eyepiece to reduce visual discomfort induced by stereoscopic vision. An empirical experiment was conducted to examine the feasibility of convex eyepiece in a large depth of field (DOF) at close viewing distance both objectively and subjectively. The result shows the positive effects of convex eyepiece on the relief of eyestrain.

Cheminformatics meets molecular mechanics: a combined application of knowledge-based pose scoring and physical force field-based hit scoring functions improves the accuracy of structure-based virtual screening.

PubMed

Hsieh, Jui-Hua; Yin, Shuangye; Wang, Xiang S; Liu, Shubin; Dokholyan, Nikolay V; Tropsha, Alexander

2012-01-23

Poor performance of scoring functions is a well-known bottleneck in structure-based virtual screening (VS), which is most frequently manifested in the scoring functions' inability to discriminate between true ligands vs known nonbinders (therefore designated as binding decoys). This deficiency leads to a large number of false positive hits resulting from VS. We have hypothesized that filtering out or penalizing docking poses recognized as non-native (i.e., pose decoys) should improve the performance of VS in terms of improved identification of true binders. Using several concepts from the field of cheminformatics, we have developed a novel approach to identifying pose decoys from an ensemble of poses generated by computational docking procedures. We demonstrate that the use of target-specific pose (scoring) filter in combination with a physical force field-based scoring function (MedusaScore) leads to significant improvement of hit rates in VS studies for 12 of the 13 benchmark sets from the clustered version of the Database of Useful Decoys (DUD). This new hybrid scoring function outperforms several conventional structure-based scoring functions, including XSCORE::HMSCORE, ChemScore, PLP, and Chemgauss3, in 6 out of 13 data sets at early stage of VS (up 1% decoys of the screening database). We compare our hybrid method with several novel VS methods that were recently reported to have good performances on the same DUD data sets. We find that the retrieved ligands using our method are chemically more diverse in comparison with two ligand-based methods (FieldScreen and FLAP::LBX). We also compare our method with FLAP::RBLB, a high-performance VS method that also utilizes both the receptor and the cognate ligand structures. Interestingly, we find that the top ligands retrieved using our method are highly complementary to those retrieved using FLAP::RBLB, hinting effective directions for best VS applications. We suggest that this integrative VS approach combining cheminformatics and molecular mechanics methodologies may be applied to a broad variety of protein targets to improve the outcome of structure-based drug discovery studies.

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.

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.

Virtual screening of Indonesian flavonoid as neuraminidase inhibitor of influenza a subtype H5N1

NASA Astrophysics Data System (ADS)

Parikesit, A. A.; Ardiansah, B.; Handayani, D. M.; Tambunan, U. S. F.; Kerami, D.

2016-02-01

Highly Pathogenic Avian Influenza (HPAI) H5N1 poses a significant threat to animal and human health worldwide. The number of H5N1 infection in Indonesia is the highest during 2005-2013, with a mortality rate up to 83%. A mutation that occurred in H5N1 strain made it resistant to commercial antiviral agents such as oseltamivir and zanamivir, so the more potent antiviral agent is needed. In this study, virtual screening of Indonesian flavonoid as neuraminidase inhibitor of H5N1 was conducted. Total 491 flavonoid compound obtained from HerbalDB were screened. Molecular docking was performed using MOE 2008.10. This research resulted in Guajavin B as the best ligand.

Modelling, simulation and verification of the screening process of a swing-bar sieve based on the DEM

NASA Astrophysics Data System (ADS)

Wang, Yang; Yu, Jianqun; Yu, Yajun

2018-05-01

To solve the problems in the DEM simulations of the screening process of a swing-bar sieve, in this paper we propose the real-virtual boundary method to build the geometrical model of the screen deck on a swing-bar sieve. The motion of the swing-bar sieve is modelled by the planer multi-body kinematics. A coupled model of the discrete element method (DEM) with multi-body kinematics (MBK) is presented to simulate the flowing and passing processes of soybean particles on the screen deck. By the comparison of the simulated results with the experimental results of the screening process of the LA-LK laboratory scale swing-bar sieve, the feasibility and validity of the real-virtual boundary method and the coupled DEM-MBK model we proposed in this paper can be verified. This work provides the basis for the optimization design of the swing-bar sieve with circular apertures and complex motion.

Using Virtual Patient Simulations to Prepare Primary Health Care Professionals to Conduct Substance Use and Mental Health Screening and Brief Intervention.

PubMed

Albright, Glenn; Bryan, Craig; Adam, Cyrille; McMillan, Jeremiah; Shockley, Kristen

Primary health care professionals are in an excellent position to identify, screen, and conduct brief interventions for patients with mental health and substance use disorders. However, discomfort in initiating conversations about behavioral health, time concerns, lack of knowledge about screening tools, and treatment resources are barriers. This study examines the impact of an online simulation where users practice role-playing with emotionally responsive virtual patients to learn motivational interviewing strategies to better manage screening, brief interventions, and referral conversations. Baseline data were collected from 227 participants who were then randomly assigned into the treatment or wait-list control groups. Treatment group participants then completed the simulation, postsimulation survey, and 3-month follow-up survey. Results showed significant increases in knowledge/skill to identify and engage in collaborative decision making with patients. Results strongly suggest that role-play simulation experiences can be an effective means of teaching screening and brief intervention.

Three-dimensional virtual planning in orthognathic surgery enhances the accuracy of soft tissue prediction.

PubMed

Van Hemelen, Geert; Van Genechten, Maarten; Renier, Lieven; Desmedt, Maria; Verbruggen, Elric; Nadjmi, Nasser

2015-07-01

Throughout the history of computing, shortening the gap between the physical and digital world behind the screen has always been strived for. Recent advances in three-dimensional (3D) virtual surgery programs have reduced this gap significantly. Although 3D assisted surgery is now widely available for orthognathic surgery, one might still argue whether a 3D virtual planning approach is a better alternative to a conventional two-dimensional (2D) planning technique. The purpose of this study was to compare the accuracy of a traditional 2D technique and a 3D computer-aided prediction method. A double blind randomised prospective study was performed to compare the prediction accuracy of a traditional 2D planning technique versus a 3D computer-aided planning approach. The accuracy of the hard and soft tissue profile predictions using both planning methods was investigated. There was a statistically significant difference between 2D and 3D soft tissue planning (p < 0.05). The statistically significant difference found between 2D and 3D planning and the actual soft tissue outcome was not confirmed by a statistically significant difference between methods. The 3D planning approach provides more accurate soft tissue planning. However, the 2D orthognathic planning is comparable to 3D planning when it comes to hard tissue planning. This study provides relevant results for choosing between 3D and 2D planning in clinical practice. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

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.

Colorectal Cancer Screening (PDQ®)—Patient Version

Cancer.gov

There are five types of tests that are used to screen for colorectal cancer: fecal occult blood test, sigmoidoscopy, colonoscopy, virtual colonoscopy, and DNA stool test. Learn more about these and other tests in this expert-reviewed summary.

Chemoinformatics Profiling of the Chromone Nucleus as a MAO-B/A2AAR Dual Binding Scaffold

PubMed Central

Cruz-Monteagudo, Maykel; Borges, Fernanda; Cordeiro, M. Natália D. S.; Helguera, Aliuska Morales; Tejera, Eduardo; Paz-y-Miño, Cesar; Sánchez-Rodríguez, Aminael; Perera-Sardiña, Yunier; Perez-Castillo, Yunierkis

2017-01-01

Background: In the context of the current drug discovery efforts to find disease modifying therapies for Parkinson´s disease (PD) the current single target strategy has proved inefficient. Consequently, the search for multi-potent agents is attracting more and more attention due to the multiple pathogenetic factors implicated in PD. Multiple evidences points to the dual inhibition of the monoamine oxidase B (MAO-B), as well as adenosine A2A receptor (A2AAR) blockade, as a promising approach to prevent the neurodegeneration involved in PD. Currently, only two chemical scaffolds has been proposed as potential dual MAO-B inhibitors/A2AAR antagonists (caffeine derivatives and benzothiazinones). Methods: In this study, we conduct a series of chemoinformatics analysis in order to evaluate and advance the potential of the chromone nucleus as a MAO-B/A2AAR dual binding scaffold. Results: The information provided by SAR data mining analysis based on network similarity graphs and molecular docking studies support the suitability of the chromone nucleus as a potential MAO-B/A2AAR dual binding scaffold. Additionally, a virtual screening tool based on a group fusion similarity search approach was developed for the prioritization of potential MAO-B/A2AAR dual binder candidates. Among several data fusion schemes evaluated, the MEAN-SIM and MIN-RANK GFSS approaches demonstrated to be efficient virtual screening tools. Then, a combinatorial library potentially enriched with MAO-B/A2AAR dual binding chromone derivatives was assembled and sorted by using the MIN-RANK and then the MEAN-SIM GFSS VS approaches. Conclusion: The information and tools provided in this work represent valuable decision making elements in the search of novel chromone derivatives with a favorable dual binding profile as MAO-B inhibitors and A2AAR antagonists with the potential to act as a disease-modifying therapeutic for Parkinson´s disease. PMID:28093976

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets.

PubMed

Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

PubMed Central

Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817

Probing the structure of Leishmania major DHFR TS and structure based virtual screening of peptide library for the identification of anti-leishmanial leads.

PubMed

Rajasekaran, Rajalakshmi; Chen, Yi-Ping Phoebe

2012-09-01

Leishmaniasis, a multi-faceted ethereal disease is considered to be one of the World's major communicable diseases that demands exhaustive research and control measures. The substantial data on these protozoan parasites has not been utilized completely to develop potential therapeutic strategies against Leishmaniasis. Dihydrofolate reductase thymidylate synthase (DHFR-TS) plays a major role in the infective state of the parasite and hence the DHFR-TS based drugs remains of much interest to researchers working on Leishmaniasis. Although, crystal structures of DHFR-TS from different species including Plasmodium falciparum and Trypanosoma cruzi are available, the experimentally determined structure of the Leishmania major DHFR-TS has not yet been reported in the Protein Data Bank. A high quality three dimensional structure of L.major DHFR-TS has been modeled through the homology modeling approach. Carefully refined and the energy minimized structure of the modeled protein was validated using a number of structure validation programs to confirm its structure quality. The modeled protein structure was used in the process of structure based virtual screening to figure out a potential lead structure against DHFR TS. The lead molecule identified has a binding affinity of 0.51 nM and clearly follows drug like properties.

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.

Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

PubMed Central

Mu, Lin

2018-01-01

This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination. PMID:29309403

Pharmacophore Based 3D-QSAR, Virtual Screening and Docking Studies on Novel Series of HDAC Inhibitors with Thiophen Linker as Anticancer Agents.

PubMed

Patel, Preeti; Singh, Avineesh; Patel, Vijay K; Jain, Deepak K; Veerasamy, Ravichandran; Rajak, Harish

2016-01-01

Histone deacetylase (HDAC) inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. To identify the important pharmacophoric features and correlate 3Dchemical structure with biological activity using 3D-QSAR and Pharmacophore modeling studies. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with wellassigned HDAC inhibitory activity were used for 3D-QSAR model development. Best 3D-QSAR model, which is a five partial least square (PLS) factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811), cross-validated coefficient rcv 2=0.9807 and R2 pred=0.7147 with low standard deviation (0.0952). Additionally, the selected pharmacophore model DDRRR.419 was used as a 3D query for virtual screening against the ZINC database. In the virtual screening workflow, docking studies (HTVS, SP and XP) were carried out by selecting multiple receptors (PDB ID: 1T69, 1T64, 4LXZ, 4LY1, 3MAX, 2VQQ, 3C10, 1W22). Finally, six compounds were obtained based on high scoring function (dock score -11.2278-10.2222 kcal/mol) and diverse structures. The structure activity correlation was established using virtual screening, docking, energetic based pharmacophore modelling, pharmacophore, atom based 3D QSAR models and their validation. The outcomes of these studies could be further employed for the design of novel HDAC inhibitors for anticancer activity.

Identification of Phytochemicals Targeting c-Met Kinase Domain using Consensus Docking and Molecular Dynamics Simulation Studies.

PubMed

Aliebrahimi, Shima; Montasser Kouhsari, Shideh; Ostad, Seyed Nasser; Arab, Seyed Shahriar; Karami, Leila

2018-06-01

c-Met receptor tyrosine kinase is a proto-oncogene whose aberrant activation is attributed to a lower rate of survival in most cancers. Natural product-derived inhibitors known as "fourth generation inhibitors" constitute more than 60% of anticancer drugs. Furthermore, consensus docking approach has recently been introduced to augment docking accuracy and reduce false positives during a virtual screening. In order to obtain novel small-molecule Met inhibitors, consensus docking approach was performed using Autodock Vina and Autodock 4.2 to virtual screen Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target database against active and inactive conformation of c-Met kinase domain structure. Two hit molecules that were in line with drug-likeness criteria, desired docking score, and binding pose were subjected to molecular dynamics simulations to elucidate intermolecular contacts in protein-ligand complexes. Analysis of molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area studies showed that ZINC08234189 is a plausible inhibitor for the active state of c-Met, whereas ZINC03871891 may be more effective toward active c-Met kinase domain compared to the inactive form due to higher binding energy. Our analysis showed that both the hit molecules formed hydrogen bonds with key residues of the hinge region (P1158, M1160) in the active form, which is a hallmark of kinase domain inhibitors. Considering the pivotal role of HGF/c-Met signaling in carcinogenesis, our results propose ZINC08234189 and ZINC03871891 as the therapeutic options to surmount Met-dependent cancers.

Discovery of a small-molecule inhibitor of Dvl-CXXC5 interaction by computational approaches

NASA Astrophysics Data System (ADS)

Ma, Songling; Choi, Jiwon; Jin, Xuemei; Kim, Hyun-Yi; Yun, Ji-Hye; Lee, Weontae; Choi, Kang-Yell; No, Kyoung Tai

2018-05-01

The Wnt/β-catenin signaling pathway plays a significant role in the control of osteoblastogenesis and bone formation. CXXC finger protein 5 (CXXC5) has been recently identified as a negative feedback regulator of osteoblast differentiation through a specific interaction with Dishevelled (Dvl) protein. It was reported that targeting the Dvl-CXXC5 interaction could be a novel anabolic therapeutic target for osteoporosis. In this study, complex structure of Dvl PDZ domain and CXXC5 peptide was simulated with molecular dynamics (MD). Based on the structural analysis of binding modes of MD-simulated Dvl PDZ domain with CXXC5 peptide and crystal Dvl PDZ domain with synthetic peptide-ligands, we generated two different pharmacophore models and applied pharmacophore-based virtual screening to discover potent inhibitors of the Dvl-CXXC5 interaction for the anabolic therapy of osteoporosis. Analysis of 16 compounds selected by means of a virtual screening protocol yielded four compounds that effectively disrupted the Dvl-CXXC5 interaction in the fluorescence polarization assay. Potential compounds were validated by fluorescence spectroscopy and nuclear magnetic resonance. We successfully identified a highly potent inhibitor, BMD4722, which directly binds to the Dvl PDZ domain and disrupts the Dvl-CXXC5 interaction. Overall, CXXC5-Dvl PDZ domain complex based pharmacophore combined with various traditional and simple computational methods is a promising approach for the development of modulators targeting the Dvl-CXXC5 interaction, and the potent inhibitor BMD4722 could serve as a starting point to discover or design more potent and specific the Dvl-CXXC5 interaction disruptors.

Heterogeneous classifier fusion for ligand-based virtual screening: or, how decision making by committee can be a good thing.

PubMed

Riniker, Sereina; Fechner, Nikolas; Landrum, Gregory A

2013-11-25

The concept of data fusion - the combination of information from different sources describing the same object with the expectation to generate a more accurate representation - has found application in a very broad range of disciplines. In the context of ligand-based virtual screening (VS), data fusion has been applied to combine knowledge from either different active molecules or different fingerprints to improve similarity search performance. Machine-learning (ML) methods based on fusion of multiple homogeneous classifiers, in particular random forests, have also been widely applied in the ML literature. The heterogeneous version of classifier fusion - fusing the predictions from different model types - has been less explored. Here, we investigate heterogeneous classifier fusion for ligand-based VS using three different ML methods, RF, naïve Bayes (NB), and logistic regression (LR), with four 2D fingerprints, atom pairs, topological torsions, RDKit fingerprint, and circular fingerprint. The methods are compared using a previously developed benchmarking platform for 2D fingerprints which is extended to ML methods in this article. The original data sets are filtered for difficulty, and a new set of challenging data sets from ChEMBL is added. Data sets were also generated for a second use case: starting from a small set of related actives instead of diverse actives. The final fused model consistently outperforms the other approaches across the broad variety of targets studied, indicating that heterogeneous classifier fusion is a very promising approach for ligand-based VS. The new data sets together with the adapted source code for ML methods are provided in the Supporting Information .

Discovery of a small-molecule inhibitor of Dvl-CXXC5 interaction by computational approaches.

PubMed

Ma, Songling; Choi, Jiwon; Jin, Xuemei; Kim, Hyun-Yi; Yun, Ji-Hye; Lee, Weontae; Choi, Kang-Yell; No, Kyoung Tai

2018-05-01

The Wnt/β-catenin signaling pathway plays a significant role in the control of osteoblastogenesis and bone formation. CXXC finger protein 5 (CXXC5) has been recently identified as a negative feedback regulator of osteoblast differentiation through a specific interaction with Dishevelled (Dvl) protein. It was reported that targeting the Dvl-CXXC5 interaction could be a novel anabolic therapeutic target for osteoporosis. In this study, complex structure of Dvl PDZ domain and CXXC5 peptide was simulated with molecular dynamics (MD). Based on the structural analysis of binding modes of MD-simulated Dvl PDZ domain with CXXC5 peptide and crystal Dvl PDZ domain with synthetic peptide-ligands, we generated two different pharmacophore models and applied pharmacophore-based virtual screening to discover potent inhibitors of the Dvl-CXXC5 interaction for the anabolic therapy of osteoporosis. Analysis of 16 compounds selected by means of a virtual screening protocol yielded four compounds that effectively disrupted the Dvl-CXXC5 interaction in the fluorescence polarization assay. Potential compounds were validated by fluorescence spectroscopy and nuclear magnetic resonance. We successfully identified a highly potent inhibitor, BMD4722, which directly binds to the Dvl PDZ domain and disrupts the Dvl-CXXC5 interaction. Overall, CXXC5-Dvl PDZ domain complex based pharmacophore combined with various traditional and simple computational methods is a promising approach for the development of modulators targeting the Dvl-CXXC5 interaction, and the potent inhibitor BMD4722 could serve as a starting point to discover or design more potent and specific the Dvl-CXXC5 interaction disruptors.

Discovery of a small-molecule inhibitor of Dvl-CXXC5 interaction by computational approaches

NASA Astrophysics Data System (ADS)

Ma, Songling; Choi, Jiwon; Jin, Xuemei; Kim, Hyun-Yi; Yun, Ji-Hye; Lee, Weontae; Choi, Kang-Yell; No, Kyoung Tai

2018-04-01

The Wnt/β-catenin signaling pathway plays a significant role in the control of osteoblastogenesis and bone formation. CXXC finger protein 5 (CXXC5) has been recently identified as a negative feedback regulator of osteoblast differentiation through a specific interaction with Dishevelled (Dvl) protein. It was reported that targeting the Dvl-CXXC5 interaction could be a novel anabolic therapeutic target for osteoporosis. In this study, complex structure of Dvl PDZ domain and CXXC5 peptide was simulated with molecular dynamics (MD). Based on the structural analysis of binding modes of MD-simulated Dvl PDZ domain with CXXC5 peptide and crystal Dvl PDZ domain with synthetic peptide-ligands, we generated two different pharmacophore models and applied pharmacophore-based virtual screening to discover potent inhibitors of the Dvl-CXXC5 interaction for the anabolic therapy of osteoporosis. Analysis of 16 compounds selected by means of a virtual screening protocol yielded four compounds that effectively disrupted the Dvl-CXXC5 interaction in the fluorescence polarization assay. Potential compounds were validated by fluorescence spectroscopy and nuclear magnetic resonance. We successfully identified a highly potent inhibitor, BMD4722, which directly binds to the Dvl PDZ domain and disrupts the Dvl-CXXC5 interaction. Overall, CXXC5-Dvl PDZ domain complex based pharmacophore combined with various traditional and simple computational methods is a promising approach for the development of modulators targeting the Dvl-CXXC5 interaction, and the potent inhibitor BMD4722 could serve as a starting point to discover or design more potent and specific the Dvl-CXXC5 interaction disruptors.

Virtual Environment Training: Auxiliary Machinery Room (AMR) Watchstation Trainer.

ERIC Educational Resources Information Center

Hriber, Dennis C.; And Others

1993-01-01

Describes a project implemented at Newport News Shipbuilding that used Virtual Environment Training to improve the performance of submarine crewmen. Highlights include development of the Auxiliary Machine Room (AMR) Watchstation Trainer; Digital Video Interactive (DVI); screen layout; test design and evaluation; user reactions; authoring language;…

Virtual reality interventions for rehabilitation: considerations for developing protocols.

PubMed

Boechler, Patricia; Krol, Andrea; Raso, Jim; Blois, Terry

2009-01-01

This paper is a preliminary report on a work in progress that explores the existence of practice effects in early use of virtual reality environments for rehabilitation purposes and the effects of increases in level of difficulty as defined by rate of on-screen objects.

November 6, 2017, Virtual Meeting on the Charge Questions for the Federal Insecticide, Fungicide, and Rodenticide Act Scientific Advisory Panel (FIFRA SAP) Meeting on Endocrine Disruption

EPA Pesticide Factsheets

This virtual FIFRA SAP meeting will be discus questions on Continuing Development of Alternative High-Throughput Screens to Determine Endocrine Disruption, focusing on Androgen Receptor, Steroidogenesis, and Thyroid Pathways

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.

Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases.

PubMed

Kaserer, Teresa; Beck, Katharina R; Akram, Muhammad; Odermatt, Alex; Schuster, Daniela

2015-12-19

Computational methods are well-established tools in the drug discovery process and can be employed for a variety of tasks. Common applications include lead identification and scaffold hopping, as well as lead optimization by structure-activity relationship analysis and selectivity profiling. In addition, compound-target interactions associated with potentially harmful effects can be identified and investigated. This review focuses on pharmacophore-based virtual screening campaigns specifically addressing the target class of hydroxysteroid dehydrogenases. Many members of this enzyme family are associated with specific pathological conditions, and pharmacological modulation of their activity may represent promising therapeutic strategies. On the other hand, unintended interference with their biological functions, e.g., upon inhibition by xenobiotics, can disrupt steroid hormone-mediated effects, thereby contributing to the development and progression of major diseases. Besides a general introduction to pharmacophore modeling and pharmacophore-based virtual screening, exemplary case studies from the field of short-chain dehydrogenase/reductase (SDR) research are presented. These success stories highlight the suitability of pharmacophore modeling for the various application fields and suggest its application also in futures studies.

Discovery of thienoquinolone derivatives as selective and ATP non-competitive CDK5/p25 inhibitors by structure-based virtual screening

PubMed Central

Chatterjee, Arindam; Doerksen, Robert J.; Khan, Ikhlas A.

2014-01-01

Calpain mediated cleavage of CDK5 natural precursor p35 causes a stable complex formation of CDK5/p25, which leads to hyperphosphorylation of tau. Thus inhibition of this complex is a viable target for numerous acute and chronic neurodegenerative diseases involving tau protein, including Alzheimer’s disease. Since CDK5 has the highest sequence homology with its mitotic counterpart CDK2, our primary goal was to design selective CDK5/p25 inhibitors targeting neurodegeneration. A novel structure-based virtual screening protocol comprised of e-pharmacophore models and virtual screening work-flow was used to identify nine compounds from a commercial database containing 2.84 million compounds. An ATP non-competitive and selective thieno[3,2-c]quinolin-4(5H)-one inhibitor (10) with ligand efficiency (LE) of 0.3 was identified as the lead molecule. Further SAR optimization led to the discovery of several low micromolar inhibitors with good selectivity. The research represents a new class of potent ATP non-competitive CDK5/p25 inhibitors with good CDK2/E selectivity. PMID:25438765

Multiple search methods for similarity-based virtual screening: analysis of search overlap and precision

PubMed Central

2011-01-01

Background Data fusion methods are widely used in virtual screening, and make the implicit assumption that the more often a molecule is retrieved in multiple similarity searches, the more likely it is to be active. This paper tests the correctness of this assumption. Results Sets of 25 searches using either the same reference structure and 25 different similarity measures (similarity fusion) or 25 different reference structures and the same similarity measure (group fusion) show that large numbers of unique molecules are retrieved by just a single search, but that the numbers of unique molecules decrease very rapidly as more searches are considered. This rapid decrease is accompanied by a rapid increase in the fraction of those retrieved molecules that are active. There is an approximately log-log relationship between the numbers of different molecules retrieved and the number of searches carried out, and a rationale for this power-law behaviour is provided. Conclusions Using multiple searches provides a simple way of increasing the precision of a similarity search, and thus provides a justification for the use of data fusion methods in virtual screening. PMID:21824430

Development of a novel class of B-RafV600E-selective inhibitors through virtual screening and hierarchical hit optimization

PubMed Central

Kong, Xiangqian; Qin, Jie; Li, Zeng; Vultur, Adina; Tong, Linjiang; Feng, Enguang; Rajan, Geena; Liu, Shien; Lu, Junyan; Liang, Zhongjie; Zheng, Mingyue; Zhu, Weiliang; Jiang, Hualiang; Herlyn, Meenhard; Liu, Hong; Marmorstein, Ronen; Luo, Cheng

2012-01-01

Oncogenic mutations in critical nodes of cellular signaling pathways have been associated with tumorigenesis and progression. The B-Raf protein kinase, a key hub in the canonical MAPK signaling cascade, is mutated in a broad range of human cancers and especially in malignant melanoma. The most prevalent B-RafV600E mutant exhibits elevated kinase activity and results in constitutive activation of the MAPK pathway, thus making it a promising drug target for cancer therapy. Herein, we described the development of novel B-RafV600E selective inhibitors via multi-step virtual screening and hierarchical hit optimization. Nine hit compounds with low micromolar IC50 values were identified as B-RafV600E inhibitors through virtual screening. Subsequent scaffold-based analogue searching and medicinal chemistry efforts significantly improved both the inhibitor potency and oncogene selectivity. In particular, compounds 22f and 22q possess nanomolar IC50 values with selectivity for B-RafV600E in vitro and exclusive cytotoxicity against B-RafV600E harboring cancer cells. PMID:22875039

Development of a novel class of B-Raf(V600E)-selective inhibitors through virtual screening and hierarchical hit optimization.

PubMed

Kong, Xiangqian; Qin, Jie; Li, Zeng; Vultur, Adina; Tong, Linjiang; Feng, Enguang; Rajan, Geena; Liu, Shien; Lu, Junyan; Liang, Zhongjie; Zheng, Mingyue; Zhu, Weiliang; Jiang, Hualiang; Herlyn, Meenhard; Liu, Hong; Marmorstein, Ronen; Luo, Cheng

2012-09-28

Oncogenic mutations in critical nodes of cellular signaling pathways have been associated with tumorigenesis and progression. The B-Raf protein kinase, a key hub in the canonical MAPK signaling cascade, is mutated in a broad range of human cancers and especially in malignant melanoma. The most prevalent B-Raf(V600E) mutant exhibits elevated kinase activity and results in constitutive activation of the MAPK pathway, thus making it a promising drug target for cancer therapy. Herein, we describe the development of novel B-Raf(V600E) selective inhibitors via multi-step virtual screening and hierarchical hit optimization. Nine hit compounds with low micromolar IC(50) values were identified as B-Raf(V600E) inhibitors through virtual screening. Subsequent scaffold-based analogue searching and medicinal chemistry efforts significantly improved both the inhibitor potency and oncogene selectivity. In particular, compounds 22f and 22q possess nanomolar IC(50) values with selectivity for B-Raf(V600E)in vitro and exclusive cytotoxicity against B-Raf(V600E) harboring cancer cells.

Discovery of nonsteroidal 17beta-hydroxysteroid dehydrogenase 1 inhibitors by pharmacophore-based screening of virtual compound libraries.

PubMed

Schuster, Daniela; Nashev, Lyubomir G; Kirchmair, Johannes; Laggner, Christian; Wolber, Gerhard; Langer, Thierry; Odermatt, Alex

2008-07-24

17Beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) plays a pivotal role in the local synthesis of the most potent estrogen estradiol. Its expression is a prognostic marker for the outcome of patients with breast cancer and inhibition of 17beta-HSD1 is currently under consideration for breast cancer prevention and treatment. We aimed to identify nonsteroidal 17beta-HSD1 inhibitor scaffolds by virtual screening with pharmacophore models built from crystal structures containing steroidal compounds. The most promising model was validated by comparing predicted and experimentally determined inhibitory activities of several flavonoids. Subsequently, a virtual library of nonsteroidal compounds was screened against the 3D pharmacophore. Analysis of 14 selected compounds yielded four that inhibited the activity of human 17beta-HSD1 (IC 50 below 50 microM). Specificity assessment of identified 17beta-HSD1 inhibitors emphasized the importance of including related short-chain dehydrogenase/reductase (SDR) members to analyze off-target effects. Compound 29 displayed at least 10-fold selectivity over the related SDR enzymes tested.

Tools for building a comprehensive modeling system for virtual screening under real biological conditions: The Computational Titration algorithm.

PubMed

Kellogg, Glen E; Fornabaio, Micaela; Chen, Deliang L; Abraham, Donald J; Spyrakis, Francesca; Cozzini, Pietro; Mozzarelli, Andrea

2006-05-01

Computational tools utilizing a unique empirical modeling system based on the hydrophobic effect and the measurement of logP(o/w) (the partition coefficient for solvent transfer between 1-octanol and water) are described. The associated force field, Hydropathic INTeractions (HINT), contains much rich information about non-covalent interactions in the biological environment because of its basis in an experiment that measures interactions in solution. HINT is shown to be the core of an evolving virtual screening system that is capable of taking into account a number of factors often ignored such as entropy, effects of solvent molecules at the active site, and the ionization states of acidic and basic residues and ligand functional groups. The outline of a comprehensive modeling system for virtual screening that incorporates these features is described. In addition, a detailed description of the Computational Titration algorithm is provided. As an example, three complexes of dihydrofolate reductase (DHFR) are analyzed with our system and these results are compared with the experimental free energies of binding.

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.

Searching Fragment Spaces with feature trees.

PubMed

Lessel, Uta; Wellenzohn, Bernd; Lilienthal, Markus; Claussen, Holger

2009-02-01

Virtual combinatorial chemistry easily produces billions of compounds, for which conventional virtual screening cannot be performed even with the fastest methods available. An efficient solution for such a scenario is the generation of Fragment Spaces, which encode huge numbers of virtual compounds by their fragments/reagents and rules of how to combine them. Similarity-based searches can be performed in such spaces without ever fully enumerating all virtual products. Here we describe the generation of a huge Fragment Space encoding about 5 * 10(11) compounds based on established in-house synthesis protocols for combinatorial libraries, i.e., we encode practically evaluated combinatorial chemistry protocols in a machine readable form, rendering them accessible to in silico search methods. We show how such searches in this Fragment Space can be integrated as a first step in an overall workflow. It reduces the extremely huge number of virtual products by several orders of magnitude so that the resulting list of molecules becomes more manageable for further more elaborated and time-consuming analysis steps. Results of a case study are presented and discussed, which lead to some general conclusions for an efficient expansion of the chemical space to be screened in pharmaceutical companies.

Deep ensemble learning of virtual endoluminal views for polyp detection in CT colonography

NASA Astrophysics Data System (ADS)

Umehara, Kensuke; Näppi, Janne J.; Hironaka, Toru; Regge, Daniele; Ishida, Takayuki; Yoshida, Hiroyuki

2017-03-01

Robust training of a deep convolutional neural network (DCNN) requires a very large number of annotated datasets that are currently not available in CT colonography (CTC). We previously demonstrated that deep transfer learning provides an effective approach for robust application of a DCNN in CTC. However, at high detection accuracy, the differentiation of small polyps from non-polyps was still challenging. In this study, we developed and evaluated a deep ensemble learning (DEL) scheme for reviewing of virtual endoluminal images to improve the performance of computer-aided detection (CADe) of polyps in CTC. Nine different types of image renderings were generated from virtual endoluminal images of polyp candidates detected by a conventional CADe system. Eleven DCNNs that represented three types of publically available pre-trained DCNN models were re-trained by transfer learning to identify polyps from the virtual endoluminal images. A DEL scheme that determines the final detected polyps by a review of the nine types of VE images was developed by combining the DCNNs using a random forest classifier as a meta-classifier. For evaluation, we sampled 154 CTC cases from a large CTC screening trial and divided the cases randomly into a training dataset and a test dataset. At 3.9 falsepositive (FP) detections per patient on average, the detection sensitivities of the conventional CADe system, the highestperforming single DCNN, and the DEL scheme were 81.3%, 90.7%, and 93.5%, respectively, for polyps ≥6 mm in size. For small polyps, the DEL scheme reduced the number of false positives by up to 83% over that of using a single DCNN alone. These preliminary results indicate that the DEL scheme provides an effective approach for improving the polyp detection performance of CADe in CTC, especially for small polyps.

Special Section: New Ways to Detect Colon Cancer 3-D virtual screening now being used

MedlinePlus

... two together," recalls Arie Kaufman, chairman of the computer science department at New York's Stony Brook University. Dr. Kaufman is one of the world's leading researchers in the high-tech medical fields of biomedical visualization, computer graphics, virtual reality, and multimedia. The year was ...

Promising Aedes aegypti repellent chemotypes identified through integrated QSAE, virtual screening, synthesis, and bioassay

USDA-ARS?s Scientific Manuscript database

Molecular field topology analysis, scaffold hopping, and molecular docking were used as complementary computational tools for the design of repellents for Aedes aegypti, the insect vector for yellow fever, West Nile fever, and dengue fever. A large number of analogues were evaluated by virtual scree...

Benchmarking Data Sets for the Evaluation of Virtual Ligand Screening Methods: Review and Perspectives.

PubMed

Lagarde, Nathalie; Zagury, Jean-François; Montes, Matthieu

2015-07-27

Virtual screening methods are commonly used nowadays in drug discovery processes. However, to ensure their reliability, they have to be carefully evaluated. The evaluation of these methods is often realized in a retrospective way, notably by studying the enrichment of benchmarking data sets. To this purpose, numerous benchmarking data sets were developed over the years, and the resulting improvements led to the availability of high quality benchmarking data sets. However, some points still have to be considered in the selection of the active compounds, decoys, and protein structures to obtain optimal benchmarking data sets.

Low-cost, smartphone based frequency doubling technology visual field testing using virtual reality (Conference Presentation)

NASA Astrophysics Data System (ADS)

Alawa, Karam A.; Sayed, Mohamed; Arboleda, Alejandro; Durkee, Heather A.; Aguilar, Mariela C.; Lee, Richard K.

2017-02-01

Glaucoma is the leading cause of irreversible blindness worldwide. Due to its wide prevalence, effective screening tools are necessary. The purpose of this project is to design and evaluate a system that enables portable, cost effective, smartphone based visual field screening based on frequency doubling technology. The system is comprised of an Android smartphone to display frequency doubling stimuli and handle processing, a Bluetooth remote for user input, and a virtual reality headset to simulate the exam. The LG Nexus 5 smartphone and BoboVR Z3 virtual reality headset were used for their screen size and lens configuration, respectively. The system is capable of running the C-20, N-30, 24-2, and 30-2 testing patterns. Unlike the existing system, the smartphone FDT tests both eyes concurrently by showing the same background to both eyes but only displaying the stimulus to one eye at a time. Both the Humphrey Zeiss FDT and the smartphone FDT were tested on five subjects without a history of ocular disease with the C-20 testing pattern. The smartphone FDT successfully produced frequency doubling stimuli at the correct spatial and temporal frequency. Subjects could not tell which eye was being tested. All five subjects preferred the smartphone FDT to the Humphrey Zeiss FDT due to comfort and ease of use. The smartphone FDT is a low-cost, portable visual field screening device that can be used as a screening tool for glaucoma.

Detection of flat colorectal polyps at screening CT colonography in comparison with conventional polypoid lesions.

PubMed

Sakamoto, Takashi; Mitsuzaki, Katsuhiko; Utsunomiya, Daisuke; Matsuda, Katsuhiko; Yamamura, Sadahiro; Urata, Joji; Kawakami, Megumi; Yamashita, Yasuyuki

2012-09-01

Although the screening of small, flat polyps is clinically important, the role of CT colonography (CTC) screening in their detection has not been thoroughly investigated. To evaluate the detection capability and usefulness of CTC in the screening of flat and polypoid lesions by comparing CTC with optic colonoscopy findings as the gold standard. We evaluated the CTC detection capability for flat colorectal polyps with a flat surface and a height not exceeding 3 mm (n = 42) by comparing to conventional polypoid lesions (n = 418) according to the polyp diameter. Four types of reconstruction images including multiplanar reconstruction, volume rendering, virtual gross pathology, and virtual endoscopic images were used for visual analysis. We compared the abilities of the four reconstructions for polyp visualization. Detection sensitivity for flat polyps was 31.3%, 44.4%, and 87.5% for lesions measuring 2-3 mm, 4-5 mm, and ≥6 mm, respectively; the corresponding sensitivity for polypoid lesions was 47.6%, 79.0%, and 91.7%. The overall sensitivity for flat lesions (47.6%) was significantly lower than polypoid lesions (64.1%). Virtual endoscopic imaging showed best visualization among the four reconstructions. Colon cancers were detected in eight patients by optic colonoscopy, and CTC detected colon cancers in all eight patients. CTC using 64-row multidetector CT is useful for colon cancer screening to detect colorectal polyps while the detection of small, flat lesions is still challenging.

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.

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.

Small-Molecule Inhibitor Leads of Ribosome-Inactivating Proteins Developed Using the Doorstop Approach

DTIC Science & Technology

2011-03-01

stereochemistry of R22 used in our virtual screen. R20 or R20b was prepared by coupling 4-formylbenzoic acid with a substituted pyrrole in the keto form for R20 or...a mixture of keto and enol forms for R20b according to a reported process [42] (Figure 4). The substituted pyrrole was obtained via cyclization of 2...1H- pyrrole -3-carboxylate—a close ana- log of R20b—has been reported to have the Z stereochemistry [45]. Therefore, identification of R20 as an active

Virtual Laboratories and Virtual Worlds

NASA Astrophysics Data System (ADS)

Hut, Piet

2008-05-01

Since we cannot put stars in a laboratory, astrophysicists had to wait till the invention of computers before becoming laboratory scientists. For half a century now, we have been conducting experiments in our virtual laboratories. However, we ourselves have remained behind the keyboard, with the screen of the monitor separating us from the world we are simulating. Recently, 3D on-line technology, developed first for games but now deployed in virtual worlds like Second Life, is beginning to make it possible for astrophysicists to enter their virtual labs themselves, in virtual form as avatars. This has several advantages, from new possibilities to explore the results of the simulations to a shared presence in a virtual lab with remote collaborators on different continents. I will report my experiences with the use of Qwaq Forums, a virtual world developed by a new company (see http://www.qwaq.com).

[Virtual microscopy in pathology teaching and postgraduate training (continuing education)].

PubMed

Sinn, H P; Andrulis, M; Mogler, C; Schirmacher, P

2008-11-01

As with conventional microscopy, virtual microscopy permits histological tissue sections to be viewed on a computer screen with a free choice of viewing areas and a wide range of magnifications. This, combined with the possibility of linking virtual microscopy to E-Learning courses, make virtual microscopy an ideal tool for teaching and postgraduate training in pathology. Uses of virtual microscopy in pathology teaching include blended learning with the presentation of digital teaching slides in the internet parallel to presentation in the histology lab, extending student access to histology slides beyond the lab. Other uses are student self-learning in the Internet, as well as the presentation of virtual slides in the classroom with or without replacing real microscopes. Successful integration of virtual microscopy depends on its embedding in the virtual classroom and the creation of interactive E-learning content. Applications derived from this include the use of virtual microscopy in video clips, podcasts, SCORM modules and the presentation of virtual microscopy using interactive whiteboards in the classroom.

Virtual fragment preparation for computational fragment-based drug design.

PubMed

Ludington, Jennifer L

2015-01-01

Fragment-based drug design (FBDD) has become an important component of the drug discovery process. The use of fragments can accelerate both the search for a hit molecule and the development of that hit into a lead molecule for clinical testing. In addition to experimental methodologies for FBDD such as NMR and X-ray Crystallography screens, computational techniques are playing an increasingly important role. The success of the computational simulations is due in large part to how the database of virtual fragments is prepared. In order to prepare the fragments appropriately it is necessary to understand how FBDD differs from other approaches and the issues inherent in building up molecules from smaller fragment pieces. The ultimate goal of these calculations is to link two or more simulated fragments into a molecule that has an experimental binding affinity consistent with the additive predicted binding affinities of the virtual fragments. Computationally predicting binding affinities is a complex process, with many opportunities for introducing error. Therefore, care should be taken with the fragment preparation procedure to avoid introducing additional inaccuracies.This chapter is focused on the preparation process used to create a virtual fragment database. Several key issues of fragment preparation which affect the accuracy of binding affinity predictions are discussed. The first issue is the selection of the two-dimensional atomic structure of the virtual fragment. Although the particular usage of the fragment can affect this choice (i.e., whether the fragment will be used for calibration, binding site characterization, hit identification, or lead optimization), general factors such as synthetic accessibility, size, and flexibility are major considerations in selecting the 2D structure. Other aspects of preparing the virtual fragments for simulation are the generation of three-dimensional conformations and the assignment of the associated atomic point charges.

How should a virtual agent present psychoeducation? Influence of verbal and textual presentation on adherence

PubMed Central

Tielman, Myrthe L.; Neerincx, Mark A.; van Meggelen, Marieke; Franken, Ingmar; Brinkman, Willem-Paul

2017-01-01

BACKGROUND AND OBJECTIVE: With the rise of autonomous e-mental health applications, virtual agents can play a major role in improving trustworthiness, therapy outcome and adherence. In these applications, it is important that patients adhere in the sense that they perform the tasks, but also that they adhere to the specific recommendations on how to do them well. One important construct in improving adherence is psychoeducation, information on the why and how of therapeutic interventions. In an e-mental health context, this can be delivered in two different ways: verbally by a (virtual) embodied conversational agent or just via text on the screen. The aim of this research is to study which presentation mode is preferable for improving adherence. METHODS : This study takes the approach of evaluating a specific part of a therapy, namely psychoeducation. This was done in a non-clinical sample, to first test the general constructs of the human-computer interaction. We performed an experimental study on the effect of presentation mode of psychoeducation on adherence. In this study, we took into account the moderating effects of attitude towards the virtual agent and recollection of the information. Within the paradigm of expressive writing, we asked participants (n= 46) to pick one of their worst memories to describe in a digital diary after receiving verbal or textual psychoeducation. RESULTS AND CONCLUSION: We found that both the attitude towards the virtual agent and how well the psychoeducation was recollected were positively related to adherence in the form of task execution. Moreover, after controlling for the attitude to the agent and recollection, presentation of psychoeducation via text resulted in higher adherence than verbal presentation by the virtual agent did. PMID:28800346

Virtual Conversation Partner for Adults with Autism

PubMed Central

Trepagnier, Cheryl Y.; Olsen, Dale E.; Bell, Corinne A.

2011-01-01

Abstract Autistic Spectrum Disorder (ASD) is notable for severely impaired reciprocal social interaction skills relative to language and intellectual abilities, presenting a major barrier to social integration and vocational success. Evidence-based interventions to address these needs are lacking. We report on the development of a small, prototype conversation simulation to teach conversational skills to adolescents and adults with ASD and average to superior intellectual abilities. We also report on a test of the feasibility and acceptability of the simulation approach with a sample of the target population. The simulation engages the user in a virtual conversation with an on-screen partner whose reactions provide naturalistic feedback geared to the appropriateness of the learner's response choices. The prototype simulation, which provides for up to 12 potentially unique multi-turn conversations, was used over a period of 2 weeks by 16 adolescents and adults who then rated statements about the system on a linear scale of 1 (disagreement) to 5 (high agreement). The participants highly endorsed the majority of positive statements about the quality and credibility of the interaction and the virtual conversation partner. In contrast, agreement with positive statements about instructional features external to the conversation was moderate. Unexpectedly, most participants strongly agreed that using the simulation had been helpful to them. Further development and testing in the context of a controlled study with randomized assignment to control and experimental groups are needed to determine whether this approach is effective in improving real-world pragmatic language behavior of high-functioning adults with ASD. PMID:21329439

Biofragments: An Approach towards Predicting Protein Function Using Biologically Related Fragments and its Application to Mycobacterium tuberculosis CYP126

PubMed Central

Hudson, Sean A; Mashalidis, Ellene H; Bender, Andreas; McLean, Kirsty J; Munro, Andrew W; Abell, Chris

2014-01-01

We present a novel fragment-based approach that tackles some of the challenges for chemical biology of predicting protein function. The general approach, which we have termed biofragments, comprises two key stages. First, a biologically relevant fragment library (biofragment library) can be designed and constructed from known sets of substrate-like ligands for a protein class of interest. Second, the library can be screened for binding to a novel putative ligand-binding protein from the same or similar class, and the characterization of hits provides insight into the basis of ligand recognition, selectivity, and function at the substrate level. As a proof-of-concept, we applied the biofragments approach to the functionally uncharacterized Mycobacterium tuberculosis (Mtb) cytochrome P450 isoform, CYP126. This led to the development of a tailored CYP biofragment library with notable 3D characteristics and a significantly higher screening hit rate (14 %) than standard drug-like fragment libraries screened previously against Mtb CYP121 and 125 (4 % and 1 %, respectively). Biofragment hits were identified that make both substrate-like type-I and inhibitor-like type-II interactions with CYP126. A chemical-fingerprint-based substrate model was built from the hits and used to search a virtual TB metabolome, which led to the discovery that CYP126 has a strong preference for the recognition of aromatics and substrate-like type-I binding of chlorophenol moieties within the active site near the heme. Future catalytic analyses will be focused on assessing CYP126 for potential substrate oxidative dehalogenation. PMID:24677424

Outcomes of Screening Mammography in Elderly Women

DTIC Science & Technology

2004-10-01

program run by the National Health Service (NHS) provides virtually all mammographic screening for women aged 50 or older . 2,3 There are differences also...government-funded National Health Service Breast Screening Program provides free breast cancer screening in the U.K. for women 50 or older . 3, 10 Women aged ...for Public Release; Distribution Unlimited 13. ABSTRACT (Maximum 200 Words) There is uncertainty about whether women older than age 65 should undergo

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.

Third-Graders Learn about Fractions Using Virtual Manipulatives: A Classroom Study

ERIC Educational Resources Information Center

Reimer, Kelly; Moyer, Patricia S.

2005-01-01

With recent advances in computer technology, it is no surprise that the manipulation of objects in mathematics classrooms now includes the manipulation of objects on the computer screen. These objects, referred to as "virtual manipulatives," are essentially replicas of physical manipulatives placed on the World Wide Web in the form of computer…

Active Learning Environments with Robotic Tangibles: Children's Physical and Virtual Spatial Programming Experiences

ERIC Educational Resources Information Center

Burleson, Winslow S.; Harlow, Danielle B.; Nilsen, Katherine J.; Perlin, Ken; Freed, Natalie; Jensen, Camilla Nørgaard; Lahey, Byron; Lu, Patrick; Muldner, Kasia

2018-01-01

As computational thinking becomes increasingly important for children to learn, we must develop interfaces that leverage the ways that young children learn to provide opportunities for them to develop these skills. Active Learning Environments with Robotic Tangibles (ALERT) and Robopad, an analogous on-screen virtual spatial programming…

Selected approaches for rational drug design and high throughput screening to identify anti-cancer molecules.

PubMed

Hedvat, Michael; Emdad, Luni; Das, Swadesh K; Kim, Keetae; Dasgupta, Santanu; Thomas, Shibu; Hu, Bin; Zhu, Shan; Dash, Rupesh; Quinn, Bridget A; Oyesanya, Regina A; Kegelman, Timothy P; Sokhi, Upneet K; Sarkar, Siddik; Erdogan, Eda; Menezes, Mitchell E; Bhoopathi, Praveen; Wang, Xiang-Yang; Pomper, Martin G; Wei, Jun; Wu, Bainan; Stebbins, John L; Diaz, Paul W; Reed, John C; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B

2012-11-01

Structure-based modeling combined with rational drug design, and high throughput screening approaches offer significant potential for identifying and developing lead compounds with therapeutic potential. The present review focuses on these two approaches using explicit examples based on specific derivatives of Gossypol generated through rational design and applications of a cancer-specificpromoter derived from Progression Elevated Gene-3. The Gossypol derivative Sabutoclax (BI-97C1) displays potent anti-tumor activity against a diverse spectrum of human tumors. The model of the docked structure of Gossypol bound to Bcl-XL provided a virtual structure-activity-relationship where appropriate modifications were predicted on a rational basis. These structure-based studies led to the isolation of Sabutoclax, an optically pure isomer of Apogossypol displaying superior efficacy and reduced toxicity. These studies illustrate the power of combining structure-based modeling with rational design to predict appropriate derivatives of lead compounds to be empirically tested and evaluated for bioactivity. Another approach to cancer drug discovery utilizes a cancer-specific promoter as readouts of the transformed state. The promoter region of Progression Elevated Gene-3 is such a promoter with cancer-specific activity. The specificity of this promoter has been exploited as a means of constructing cancer terminator viruses that selectively kill cancer cells and as a systemic imaging modality that specifically visualizes in vivo cancer growth with no background from normal tissues. Screening of small molecule inhibitors that suppress the Progression Elevated Gene-3-promoter may provide relevant lead compounds for cancer therapy that can be combined with further structure-based approaches leading to the development of novel compounds for cancer therapy.

Distance underestimation in virtual space is sensitive to gender but not activity-passivity or mode of interaction.

PubMed

Foreman, Nigel; Sandamas, George; Newson, David

2004-08-01

Four groups of undergraduates (half of each gender) experienced a movement along a corridor containing three distinctive objects, in a virtual environment (VE) with wide-screen projection. One group simulated walking along the virtual corridor using a proprietary step-exercise device. A second group moved along the corridor in conventional flying mode, depressing a keyboard key to initiate continuous forward motion. Two further groups observed the walking and flying participants, by viewing their progress on the screen. Participants then had to walk along a real equivalent but empty corridor, and indicate the positions of the three objects. All groups underestimated distances in the real corridor, the greatest underestimates occurring for the middle distance object. Males' underestimations were significantly lower than females' at all distances. However, there was no difference between the active participants and passive observers, nor between walking and flying conditions.

Experimental validation of FINDSITEcomb virtual ligand screening results for eight proteins yields novel nanomolar and micromolar binders

PubMed Central

2014-01-01

Background Identification of ligand-protein binding interactions is a critical step in drug discovery. Experimental screening of large chemical libraries, in spite of their specific role and importance in drug discovery, suffer from the disadvantages of being random, time-consuming and expensive. To accelerate the process, traditional structure- or ligand-based VLS approaches are combined with experimental high-throughput screening, HTS. Often a single protein or, at most, a protein family is considered. Large scale VLS benchmarking across diverse protein families is rarely done, and the reported success rate is very low. Here, we demonstrate the experimental HTS validation of a novel VLS approach, FINDSITEcomb, across a diverse set of medically-relevant proteins. Results For eight different proteins belonging to different fold-classes and from diverse organisms, the top 1% of FINDSITEcomb’s VLS predictions were tested, and depending on the protein target, 4%-47% of the predicted ligands were shown to bind with μM or better affinities. In total, 47 small molecule binders were identified. Low nanomolar (nM) binders for dihydrofolate reductase and protein tyrosine phosphatases (PTPs) and micromolar binders for the other proteins were identified. Six novel molecules had cytotoxic activity (<10 μg/ml) against the HCT-116 colon carcinoma cell line and one novel molecule had potent antibacterial activity. Conclusions We show that FINDSITEcomb is a promising new VLS approach that can assist drug discovery. PMID:24936211

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.

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.

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.

A review on PARP1 inhibitors: Pharmacophore modeling, virtual and biological screening studies to identify novel PARP1 inhibitors.

PubMed

Singh, Sardar Shamshair; Sarma, Jagarlapudi A R P; Narasu, Lakshmi; Dayam, Raveendra; Xu, Shili; Neamati, Nouri

2014-01-01

A tremendous research on Poly (ADP-ribose) polymerase (PARP) pertaining to cancer and ischemia is in very rapid progress. PARP's are a specific class of enzymes that repairs the damaged DNA. Recent findings suggest also that PARP-1 is the most abundantly expressed nuclear enzyme which involves in various therapeutic areas like inflammation, stroke, cardiac ischemia, cancer and diabetes. The current review describes the overview on clinical candidates of PARP1 and its current status in clinical trials. This paper also covers identification of potent PARP1 inhibitors using structure and ligand based pharmacophore models. Finally 36 potential hits were identified from the virtual screening of pharmacophore models and screened for PARP1 activity. 15 actives were identified as potent PARP1 inhibitors and further optimization of these analogues are in progress.

Immersive Virtual Moon Scene System Based on Panoramic Camera Data of Chang'E-3

NASA Astrophysics Data System (ADS)

Gao, X.; Liu, J.; Mu, L.; Yan, W.; Zeng, X.; Zhang, X.; Li, C.

2014-12-01

The system "Immersive Virtual Moon Scene" is used to show the virtual environment of Moon surface in immersive environment. Utilizing stereo 360-degree imagery from panoramic camera of Yutu rover, the system enables the operator to visualize the terrain and the celestial background from the rover's point of view in 3D. To avoid image distortion, stereo 360-degree panorama stitched by 112 images is projected onto inside surface of sphere according to panorama orientation coordinates and camera parameters to build the virtual scene. Stars can be seen from the Moon at any time. So we render the sun, planets and stars according to time and rover's location based on Hipparcos catalogue as the background on the sphere. Immersing in the stereo virtual environment created by this imaged-based rendering technique, the operator can zoom, pan to interact with the virtual Moon scene and mark interesting objects. Hardware of the immersive virtual Moon system is made up of four high lumen projectors and a huge curve screen which is 31 meters long and 5.5 meters high. This system which take all panoramic camera data available and use it to create an immersive environment, enable operator to interact with the environment and mark interesting objects contributed heavily to establishment of science mission goals in Chang'E-3 mission. After Chang'E-3 mission, the lab with this system will be open to public. Besides this application, Moon terrain stereo animations based on Chang'E-1 and Chang'E-2 data will be showed to public on the huge screen in the lab. Based on the data of lunar exploration，we will made more immersive virtual moon scenes and animations to help the public understand more about the Moon in the future.

TS-Chemscore, a Target-Specific Scoring Function, Significantly Improves the Performance of Scoring in Virtual Screening.

PubMed

Wang, Wen-Jing; Huang, Qi; Zou, Jun; Li, Lin-Li; Yang, Sheng-Yong

2015-07-01

Most of the scoring functions currently used in structure-based drug design belong to 'universal' scoring functions, which often give a poor correlation between the calculated scores and experimental binding affinities. In this investigation, we proposed a simple strategy to construct target-specific scoring functions based on known 'universal' scoring functions. This strategy was applied to Chemscore, a widely used empirical scoring function, which led to a new scoring function, termed TS-Chemscore. TS-Chemscore was validated on 14 protein targets, which cover a wide range of biological target categories. The results showed that TS-Chemscore significantly improved the correlation between the calculated scores and experimental binding affinities compared with the original Chemscore. TS-Chemscore was then applied in virtual screening to retrieve novel JAK3 and YopH inhibitors. Top 30 compounds for each target were selected for experimental validation. Six active compounds for JAK3 and four for YopH were obtained. These compounds were out of the lists of top 30 compounds sorted by Chemscore. Collectively, TS-Chemscore established in this study showed a better performance in virtual screening than its counterpart Chemscore. © 2014 John Wiley & Sons A/S.

Ligand-Based Pharmacophore Modeling and Virtual Screening for the Discovery of Novel 17β-Hydroxysteroid Dehydrogenase 2 Inhibitors

PubMed Central

2014-01-01

17β-Hydroxysteroid dehydrogenase 2 (17β-HSD2) catalyzes the inactivation of estradiol into estrone. This enzyme is expressed only in a few tissues, and therefore its inhibition is considered as a treatment option for osteoporosis to ameliorate estrogen deficiency. In this study, ligand-based pharmacophore models for 17β-HSD2 inhibitors were constructed and employed for virtual screening. From the virtual screening hits, 29 substances were evaluated in vitro for 17β-HSD2 inhibition. Seven compounds inhibited 17β-HSD2 with low micromolar IC50 values. To investigate structure–activity relationships (SAR), 30 more derivatives of the original hits were tested. The three most potent hits, 12, 22, and 15, had IC50 values of 240 nM, 1 μM, and 1.5 μM, respectively. All but 1 of the 13 identified inhibitors were selective over 17β-HSD1, the enzyme catalyzing conversion of estrone into estradiol. Three of the new, small, synthetic 17β-HSD2 inhibitors showed acceptable selectivity over other related HSDs, and six of them did not affect other HSDs. PMID:24960438

New leads for selective GSK-3 inhibition: pharmacophore mapping and virtual screening studies.

PubMed

Patel, Dhilon S; Bharatam, Prasad V

2006-01-01

Glycogen Synthase Kinase-3 is a regulatory serine/threonine kinase, which is being targeted for the treatment of a number of human diseases including type-2 diabetes mellitus, neurodegenerative diseases, cancer and chronic inflammation. Selective GSK-3 inhibition is an important requirement owing to the possibility of side effects arising from other kinases. A pharmacophore mapping strategy is employed in this work to identify new leads for selective GSK-3 inhibition. Ligands known to show selective GSK-3 inhibition were employed in generating a pharmacophore map using distance comparison method (DISCO). The derived pharmacophore map was validated using (i) important interactions involved in selective GSK-3 inhibitions, and (ii) an in-house database containing different classes of GSK-3 selective, non-selective and inactive molecules. New Lead identification was carried out by performing virtual screening using validated pharmacophoric query and three chemical databases namely NCI, Maybridge and Leadquest. Further data reduction was carried out by employing virtual filters based on (i) Lipinski's rule of 5 (ii) van der Waals bumps and (iii) restricting the number of rotatable bonds to seven. Final screening was carried out using FlexX based molecular docking study.

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

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.

New leads for selective GSK-3 inhibition: pharmacophore mapping and virtual screening studies

NASA Astrophysics Data System (ADS)

Patel, Dhilon S.; Bharatam, Prasad V.

2006-01-01

Glycogen Synthase Kinase-3 is a regulatory serine/threonine kinase, which is being targeted for the treatment of a number of human diseases including type-2 diabetes mellitus, neurodegenerative diseases, cancer and chronic inflammation. Selective GSK-3 inhibition is an important requirement owing to the possibility of side effects arising from other kinases. A pharmacophore mapping strategy is employed in this work to identify new leads for selective GSK-3 inhibition. Ligands known to show selective GSK-3 inhibition were employed in generating a pharmacophore map using distance comparison method (DISCO). The derived pharmacophore map was validated using (i) important interactions involved in selective GSK-3 inhibitions, and (ii) an in-house database containing different classes of GSK-3 selective, non-selective and inactive molecules. New Lead identification was carried out by performing virtual screening using validated pharmacophoric query and three chemical databases namely NCI, Maybridge and Leadquest. Further data reduction was carried out by employing virtual filters based on (i) Lipinski's rule of 5 (ii) van der Waals bumps and (iii) restricting the number of rotatable bonds to seven. Final screening was carried out using FlexX based molecular docking study.

Rational design of small-molecule stabilizers of spermine synthase dimer by virtual screening and free energy-based approach.

PubMed

Zhang, Zhe; Martiny, Virginie; Lagorce, David; Ikeguchi, Yoshihiko; Alexov, Emil; Miteva, Maria A

2014-01-01

Snyder-Robinson Syndrome (SRS) is a rare mental retardation disorder which is caused by the malfunctioning of an enzyme, the spermine synthase (SMS), which functions as a homo-dimer. The malfunctioning of SMS in SRS patients is associated with several identified missense mutations that occur away from the active site. This investigation deals with a particular SRS-causing mutation, the G56S mutation, which was shown computationally and experimentally to destabilize the SMS homo-dimer and thus to abolish SMS enzymatic activity. As a proof-of-concept, we explore the possibility to restore the enzymatic activity of the malfunctioning SMS mutant G56S by stabilizing the dimer through small molecule binding at the mutant homo-dimer interface. For this purpose, we designed an in silico protocol that couples virtual screening and a free binding energy-based approach to identify potential small-molecule binders on the destabilized G56S dimer, with the goal to stabilize it and thus to increase SMS G56S mutant activity. The protocol resulted in extensive list of plausible stabilizers, among which we selected and tested 51 compounds experimentally for their capability to increase SMS G56S mutant enzymatic activity. In silico analysis of the experimentally identified stabilizers suggested five distinctive chemical scaffolds. This investigation suggests that druggable pockets exist in the vicinity of the mutation sites at protein-protein interfaces which can be used to alter the disease-causing effects by small molecule binding. The identified chemical scaffolds are drug-like and can serve as original starting points for development of lead molecules to further rescue the disease-causing effects of the Snyder-Robinson syndrome for which no efficient treatment exists up to now.

A Virtual Screening Approach for the Identification of High Affinity Small Molecules Targeting BCR-ABL1 Inhibitors for the Treatment of Chronic Myeloid Leukemia.

PubMed

Sharda, Saphy; Sarmandal, Palash; Cherukommu, Shirisha; Dindhoria, Kiran; Yadav, Manisha; Bandaru, Srinivas; Sharma, Anudeep; Sakhi, Aditi; Vyas, Tanmay; Hussain, Tajamul; Nayarisseri, Anuraj; Singh, Sanjeev Kumar

2017-01-01

CML originates due to reciprocal translocation in Philadelphia chromosome leading to the formation of fusion product BCR-ABL which constitutively activates tyrosine kinase signaling pathways eventually leading to abnormal proliferation of granulocytic cells. As a therapeutic strategy, BCR-ABL inhibitors have been clinically approved which terminates its phosphorylation activity and retards cancer progression. However, a number of patients develop resistance to inhibitors which demand for the discovery of new inhibitors. Given the drawbacks of present inhibitors, by high throughput virtual screening approaches, present study pursues to identify high affinity compounds targeting BCR-ABL1 anticipated to have safer pharmacological profiles. Five established BCR-ABL inhibitors formed the query compounds for identification of structurally similar compounds by Tanimoto coefficient based linear fingerprint search with a threshold of 95% against PubChemdatabase. Assisted by MolDock algorithm all compounds were docked against BCR-ABL protein in order to retrieve high affinity compounds. The parents and similars were further tested for their ADMET propertiesand bioactivity. Rebastinib formed higher affinity inhibitor than rest of the four established compound investigated in the study. Interestingly, Rebastinib similar compound with Pubchem ID: 67254402 was also shown to have highest affinity than other similars including the similars of respective five parents. In terms of ADMET properties Pubchem ID: 67254402 had appreciable ADMET profile and bioactivity. However, Rebastinib still stood as the best inhibitor in terms of binding affinity and ADMET properties than Pubchem ID: 67254402. Nevertheless, owing to the similar pharmacological properties with Rebastinib, Pubchem ID: 67254402 can be expected to form potential BCR-ABL inhibitor. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

[Virtual reality in neurosurgery].

PubMed

Tronnier, V M; Staubert, A; Bonsanto, M M; Wirtz, C R; Kunze, S

2000-03-01

Virtual reality enables users to immerse themselves in a virtual three-dimensional world and to interact in this world. The simulation is different from the kind in computer games, in which the viewer is active but acts in a nonrealistic world, or on the TV screen, where we are passively driven in an active world. In virtual reality elements look realistic, they change their characteristics and have almost real-world unpredictability. Virtual reality is not only implemented in gambling dens and the entertainment industry but also in manufacturing processes (cars, furniture etc.), military applications and medicine. Especially the last two areas are strongly correlated, because telemedicine or telesurgery was originated for military reasons to operate on war victims from a secure distance or to perform surgery on astronauts in an orbiting space station. In medicine and especially neurosurgery virtual-reality methods are used for education, surgical planning and simulation on a virtual patient.

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations.

PubMed

Saxena, Shalini; Abdullah, Maaged; Sriram, Dharmarajan; Guruprasad, Lalitha

2017-10-17

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.

Structure-based virtual screening of hypothetical inhibitors of the enzyme longiborneol synthase-a potential target to reduce Fusarium head blight disease.

PubMed

Bresso, E; Leroux, V; Urban, M; Hammond-Kosack, K E; Maigret, B; Martins, N F

2016-07-01

Fusarium head blight (FHB) is one of the most destructive diseases of wheat and other cereals worldwide. During infection, the Fusarium fungi produce mycotoxins that represent a high risk to human and animal health. Developing small-molecule inhibitors to specifically reduce mycotoxin levels would be highly beneficial since current treatments unspecifically target the Fusarium pathogen. Culmorin possesses a well-known important synergistically virulence role among mycotoxins, and longiborneol synthase appears to be a key enzyme for its synthesis, thus making longiborneol synthase a particularly interesting target. This study aims to discover potent and less toxic agrochemicals against FHB. These compounds would hamper culmorin synthesis by inhibiting longiborneol synthase. In order to select starting molecules for further investigation, we have conducted a structure-based virtual screening investigation. A longiborneol synthase structural model is first built using homology modeling, followed by molecular dynamics simulations that provided the required input for a protein-ligand ensemble docking procedure. From this strategy, the three most interesting compounds (hits) were selected among the 25 top-ranked docked compounds from a library of 15,000 drug-like compounds. These putative inhibitors of longiborneol synthase provide a sound starting point for further studies involving molecular modeling coupled to biochemical experiments. This process could eventually lead to the development of novel approaches to reduce mycotoxin contamination in harvested grain.

Exploring virtual worlds with head-mounted displays

NASA Astrophysics Data System (ADS)

Chung, James C.; Harris, Mark R.; Brooks, F. P.; Fuchs, Henry; Kelley, Michael T.

1989-02-01

Research has been conducted in the use of simple head mounted displays in real world applications. Such units provide the user with non-holographic true 3-D information, since the kinetic depth effect, stereoscopy, and other visual cues combine to immerse the user in a virtual world which behaves like the real world in some respects. UNC's head mounted display was built inexpensively from commercially available off-the-shelf components. Tracking of the user's head position and orientation is performed by a Polhemus Navigation Sciences' 3SPACE tracker. The host computer uses the tracking information to generate updated images corresponding to the user's new left eye and right eye views. The images are broadcast to two liquid crystal television screens (220x320 pixels) mounted on a horizontal shelf at the user's forehead. The user views these color screens through half-silvered mirrors, enabling the computer generated image to be superimposed upon the user's real physical environment. The head mounted display was incorporated into existing molecular and architectural applications being developed at UNC. In molecular structure studies, chemists are presented with a room sized molecule with which they can interact in a manner more intuitive than that provided by conventional 2-D displays and dial boxes. Walking around and through the large molecule may provide quicker understanding of its structure, and such problems as drug enzyme docking may be approached with greater insight.

VSDMIP 1.5: an automated structure- and ligand-based virtual screening platform with a PyMOL graphical user interface.

PubMed

Cabrera, Álvaro Cortés; Gil-Redondo, Rubén; Perona, Almudena; Gago, Federico; Morreale, Antonio

2011-09-01

A graphical user interface (GUI) for our previously published virtual screening (VS) and data management platform VSDMIP (Gil-Redondo et al. J Comput Aided Mol Design, 23:171-184, 2009) that has been developed as a plugin for the popular molecular visualization program PyMOL is presented. In addition, a ligand-based VS module (LBVS) has been implemented that complements the already existing structure-based VS (SBVS) module and can be used in those cases where the receptor's 3D structure is not known or for pre-filtering purposes. This updated version of VSDMIP is placed in the context of similar available software and its LBVS and SBVS capabilities are tested here on a reduced set of the Directory of Useful Decoys database. Comparison of results from both approaches confirms the trend found in previous studies that LBVS outperforms SBVS. We also show that by combining LBVS and SBVS, and using a cluster of ~100 modern processors, it is possible to perform complete VS studies of several million molecules in less than a month. As the main processes in VSDMIP are 100% scalable, more powerful processors and larger clusters would notably decrease this time span. The plugin is distributed under an academic license upon request from the authors. © Springer Science+Business Media B.V. 2011

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

Exhaustive search and solvated interaction energy (SIE) for virtual screening and affinity prediction

NASA Astrophysics Data System (ADS)

Sulea, Traian; Hogues, Hervé; Purisima, Enrico O.

2012-05-01

We carried out a prospective evaluation of the utility of the SIE (solvation interaction energy) scoring function for virtual screening and binding affinity prediction. Since experimental structures of the complexes were not provided, this was an exercise in virtual docking as well. We used our exhaustive docking program, Wilma, to provide high-quality poses that were rescored using SIE to provide binding affinity predictions. We also tested the combination of SIE with our latest solvation model, first shell of hydration (FiSH), which captures some of the discrete properties of water within a continuum model. We achieved good enrichment in virtual screening of fragments against trypsin, with an area under the curve of about 0.7 for the receiver operating characteristic curve. Moreover, the early enrichment performance was quite good with 50% of true actives recovered with a 15% false positive rate in a prospective calculation and with a 3% false positive rate in a retrospective application of SIE with FiSH. Binding affinity predictions for both trypsin and host-guest complexes were generally within 2 kcal/mol of the experimental values. However, the rank ordering of affinities differing by 2 kcal/mol or less was not well predicted. On the other hand, it was encouraging that the incorporation of a more sophisticated solvation model into SIE resulted in better discrimination of true binders from binders. This suggests that the inclusion of proper Physics in our models is a fruitful strategy for improving the reliability of our binding affinity predictions.

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.

Identification of New Human Malaria Parasite Plasmodium Falciparum Dihydroorotate Dehydrogenase Inhibitors by Pharmacophore and Structure-Based Virtual Screening

PubMed Central

Pavadai, Elumalai; El Mazouni, Farah; Wittlin, Sergio; de Kock, Carmen; Phillips, Margaret A.; Chibale, Kelly

2016-01-01

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH), a key enzyme in the de novo pyrimidine biosynthesis pathway, which the Plasmodium falciparum relies on exclusively for survival, has emerged as a promising target for antimalarial drugs. In an effort to discover new and potent PfDHODH inhibitors, 3D-QSAR pharmacophore models were developed based on the structures of known PfDHODH inhibitors and the validated Hypo1 model was used as a 3D search query for virtual screening of the National Cancer Institute database. The virtual hit compounds were further filtered based on molecular docking and Molecular Mechanics/Generalized Born Surface Area binding energy calculations. The combination of the pharmacophore and structure-based virtual screening resulted in the identification of nine new compounds that showed >25% inhibition of PfDHODH at a concentration of 10 μM, three of which exhibited IC50 values in the range of 0.38–20 μM. The most active compound, NSC336047, displayed species-selectivity for PfDHODH over human DHODH and inhibited parasite growth with an IC50 of 26 μM. In addition to this, thirteen compounds inhibited parasite growth with IC50 values of ≤ 50 μM, four of which showed IC50 values in the range of 5–12 μM. These compounds could be further explored in the identification and development of more potent PfDHODH and parasite growth inhibitors. PMID:26915022

Financing state newborn screening programs: sources and uses of funds.

PubMed

Johnson, Kay; Lloyd-Puryear, Michele A; Mann, Marie Y; Ramos, Lauren Raskin; Therrell, Bradford L

2006-05-01

Financing for newborn screening is different from virtually all other public health programs. All except 5 screening programs collect fees as the primary source of program funding. A fee-based approach to financing newborn screening has been adopted by most states, to ensure consistent funding for this critical public health activity. Two types of data are reported here, ie, primary data from a survey of 37 state public health agencies and findings from exploratory case studies from 7 states. Most of the programs that participated in this survey (73%) reported that their newborn screening funding increased between 2002 and 2005, typically through increased fees and to a lesser extent through Medicaid, Title V Maternal and Child Health Services Block Grant, and state general revenue funding. All of the responding states that collect fees (n = 31) use such funds to support laboratory expenses, and most (70%) finance short-term follow-up services and program management. Nearly one half (47%) finance longer-term follow-up services, case management, or family support beyond diagnosis. Other states (43%) finance genetic or nutritional counseling and formula foods or treatment. Regardless of the source of funds, the available evidence indicates that states are committed to maintaining their programs and securing the necessary financing for the initial screening through diagnosis. Use of federal funding is currently limited; however, pressure to provide dedicated federal funding would likely increase if national recommendations for a uniform newborn screening panel were issued.

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.

How Do Students Learn to See Concepts in Visualizations? Social Learning Mechanisms with Physical and Virtual Representations

ERIC Educational Resources Information Center

Rau, Martina A.

2017-01-01

STEM instruction often uses visual representations. To benefit from these, students need to understand how representations show domain-relevant concepts. Yet, this is difficult for students. Prior research shows that physical representations (objects that students manipulate by hand) and virtual representations (objects on a computer screen that…

A Simple Double-Source Model for Interference of Capillaries

ERIC Educational Resources Information Center

Hou, Zhibo; Zhao, Xiaohong; Xiao, Jinghua

2012-01-01

A simple but physically intuitive double-source model is proposed to explain the interferogram of a laser-capillary system, where two effective virtual sources are used to describe the rays reflected by and transmitted through the capillary. The locations of the two virtual sources are functions of the observing positions on the target screen. An…

Working Memory in Wayfinding--A Dual Task Experiment in a Virtual City

ERIC Educational Resources Information Center

Meilinger, Tobias; Knauff, Markus; Bulthoff, Heinrich H.

2008-01-01

This study examines the working memory systems involved in human wayfinding. In the learning phase, 24 participants learned two routes in a novel photorealistic virtual environment displayed on a 220 degrees screen while they were disrupted by a visual, a spatial, a verbal, or--in a control group--no secondary task. In the following wayfinding…

Screening of a virtual mirror-image library of natural products.

PubMed

Noguchi, Taro; Oishi, Shinya; Honda, Kaori; Kondoh, Yasumitsu; Saito, Tamio; Ohno, Hiroaki; Osada, Hiroyuki; Fujii, Nobutaka

2016-06-08

We established a facile access to an unexplored mirror-image library of chiral natural product derivatives using d-protein technology. In this process, two chemical syntheses of mirror-image substances including a target protein and hit compound(s) allow the lead discovery from a virtual mirror-image library without the synthesis of numerous mirror-image compounds.

3D-Lab: a collaborative web-based platform for molecular modeling.

PubMed

Grebner, Christoph; Norrby, Magnus; Enström, Jonatan; Nilsson, Ingemar; Hogner, Anders; Henriksson, Jonas; Westin, Johan; Faramarzi, Farzad; Werner, Philip; Boström, Jonas

2016-09-01

The use of 3D information has shown impact in numerous applications in drug design. However, it is often under-utilized and traditionally limited to specialists. We want to change that, and present an approach making 3D information and molecular modeling accessible and easy-to-use 'for the people'. A user-friendly and collaborative web-based platform (3D-Lab) for 3D modeling, including a blazingly fast virtual screening capability, was developed. 3D-Lab provides an interface to automatic molecular modeling, like conformer generation, ligand alignments, molecular dockings and simple quantum chemistry protocols. 3D-Lab is designed to be modular, and to facilitate sharing of 3D-information to promote interactions between drug designers. Recent enhancements to our open-source virtual reality tool Molecular Rift are described. The integrated drug-design platform allows drug designers to instantaneously access 3D information and readily apply advanced and automated 3D molecular modeling tasks, with the aim to improve decision-making in drug design projects.

Integrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis

PubMed Central

Vizeacoumar, Franco J.; van Dyk, Nydia; S.Vizeacoumar, Frederick; Cheung, Vincent; Li, Jingjing; Sydorskyy, Yaroslav; Case, Nicolle; Li, Zhijian; Datti, Alessandro; Nislow, Corey; Raught, Brian; Zhang, Zhaolei; Frey, Brendan; Bloom, Kerry

2010-01-01

We describe the application of a novel screening approach that combines automated yeast genetics, synthetic genetic array (SGA) analysis, and a high-content screening (HCS) system to examine mitotic spindle morphogenesis. We measured numerous spindle and cellular morphological parameters in thousands of single mutants and corresponding sensitized double mutants lacking genes known to be involved in spindle function. We focused on a subset of genes that appear to define a highly conserved mitotic spindle disassembly pathway, which is known to involve Ipl1p, the yeast aurora B kinase, as well as the cell cycle regulatory networks mitotic exit network (MEN) and fourteen early anaphase release (FEAR). We also dissected the function of the kinetochore protein Mcm21p, showing that sumoylation of Mcm21p regulates the enrichment of Ipl1p and other chromosomal passenger proteins to the spindle midzone to mediate spindle disassembly. Although we focused on spindle disassembly in a proof-of-principle study, our integrated HCS-SGA method can be applied to virtually any pathway, making it a powerful means for identifying specific cellular functions. PMID:20065090

Energy-efficient virtual optical network mapping approaches over converged flexible bandwidth optical networks and data centers.

PubMed

Chen, Bowen; Zhao, Yongli; Zhang, Jie

2015-09-21

In this paper, we develop a virtual link priority mapping (LPM) approach and a virtual node priority mapping (NPM) approach to improve the energy efficiency and to reduce the spectrum usage over the converged flexible bandwidth optical networks and data centers. For comparison, the lower bound of the virtual optical network mapping is used for the benchmark solutions. Simulation results show that the LPM approach achieves the better performance in terms of power consumption, energy efficiency, spectrum usage, and the number of regenerators compared to the NPM approach.

A Systematic Framework of Virtual Laboratories Using Mobile Agent and Design Pattern Technologies

ERIC Educational Resources Information Center

Li, Yi-Hsung; Dow, Chyi-Ren; Lin, Cheng-Min; Chen, Sheng-Chang; Hsu, Fu-Wei

2009-01-01

Innovations in network and information technology have transformed traditional classroom lectures into new approaches that have given universities the opportunity to create a virtual laboratory. However, there is no systematic framework in existing approaches for the development of virtual laboratories. Further, developing a virtual laboratory…

The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.

PubMed

Xia, Jie; Hsieh, Jui-Hua; Hu, Huabin; Wu, Song; Wang, Xiang Simon

2017-06-26

Structure-based virtual screening (SBVS) has become an indispensable technique for hit identification at the early stage of drug discovery. However, the accuracy of current scoring functions is not high enough to confer success to every target and thus remains to be improved. Previously, we had developed binary pose filters (PFs) using knowledge derived from the protein-ligand interface of a single X-ray structure of a specific target. This novel approach had been validated as an effective way to improve ligand enrichment. Continuing from it, in the present work we attempted to incorporate knowledge collected from diverse protein-ligand interfaces of multiple crystal structures of the same target to build PF ensembles (PFEs). Toward this end, we first constructed a comprehensive data set to meet the requirements of ensemble modeling and validation. This set contains 10 diverse targets, 118 well-prepared X-ray structures of protein-ligand complexes, and large benchmarking actives/decoys sets. Notably, we designed a unique workflow of two-layer classifiers based on the concept of ensemble learning and applied it to the construction of PFEs for all of the targets. Through extensive benchmarking studies, we demonstrated that (1) coupling PFE with Chemgauss4 significantly improves the early enrichment of Chemgauss4 itself and (2) PFEs show greater consistency in boosting early enrichment and larger overall enrichment than our prior PFs. In addition, we analyzed the pairwise topological similarities among cognate ligands used to construct PFEs and found that it is the higher chemical diversity of the cognate ligands that leads to the improved performance of PFEs. Taken together, the results so far prove that the incorporation of knowledge from diverse protein-ligand interfaces by ensemble modeling is able to enhance the screening competence of SBVS scoring functions.

(Z)-2-(3-Chlorobenzylidene)-3,4-dihydro-N-(2-methoxyethyl)-3-oxo-2H-benzo[b][1,4]oxazine-6-carboxamide as GSK-3β inhibitor: Identification by virtual screening and its validation in enzyme- and cell-based assay.

PubMed

Joshi, Prashant; Gupta, Mehak; Vishwakarma, Ram A; Kumar, Ajay; Bharate, Sandip B

2017-06-01

Glycogen synthase kinase 3β (GSK-3β) is a widely investigated molecular target for numerous diseases including Alzheimer's disease, cancer, and diabetes mellitus. The present study was aimed to discover new scaffolds for GSK-3β inhibition, through protein structure-guided virtual screening approach. With the availability of large number of GSK-3β crystal structures with varying degree of RMSD in protein backbone and RMSF in side chain geometry, herein appropriate crystal structures were selected based on the characteristic ROC curve and percentage enrichment of actives. The validated docking protocol was employed to screen a library of 50,000 small molecules using molecular docking and binding affinity calculations. Based on the GLIDE docking score, Prime MMGB/SA binding affinity, and interaction pattern analysis, the top 50 ligands were selected for GSK-3β inhibition. (Z)-2-(3-chlorobenzylidene)-3,4-dihydro-N-(2-methoxyethyl)-3-oxo-2H-benzo[b][1,4]oxazine-6-carboxamide (F389-0663, 7) was identified as a potent inhibitor of GSK-3β with an IC 50 value of 1.6 μm. Further, GSK-3β inhibition activity was then investigated in cell-based assay. The treatment of neuroblastoma N2a cells with 12.5 μm of F389-0663 resulted in the significant increase in GSK-3β Ser9 levels, which is indicative of the GSK-3β inhibitory activity of a compound. The molecular dynamic simulations were carried out to understand the interactions of F389-0663 with GSK-3β protein. © 2016 John Wiley & Sons A/S.

Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening

NASA Astrophysics Data System (ADS)

Zavodszky, Maria I.; Sanschagrin, Paul C.; Kuhn, Leslie A.; Korde, Rajesh S.

2002-12-01

For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand candidate, it is important to place these points where the best interactions can be made between the protein and the ligand. This definition of favorable points of interaction can also guide protein structure-based ligand design, which typically focuses on which chemical groups provide the most energetically favorable contacts. In this paper, we present an alternative method of protein template and ligand interaction point design that identifies the most favorable points for making hydrophobic and hydrogen-bond interactions by using a knowledge base. The knowledge-based protein and ligand representations have been incorporated in version 2.0 of SLIDE and resulted in dockings closer to the crystal structure orientations when screening a set of 57 known thrombin and glutathione S-transferase (GST) ligands against the apo structures of these proteins. There was also improved scoring enrichment of the dockings, meaning better differentiation between the chemically diverse known ligands and a ˜15,000-molecule dataset of randomly-chosen small organic molecules. This approach for identifying the most important points of interaction between proteins and their ligands can equally well be used in other docking and design techniques. While much recent effort has focused on improving scoring functions for protein-ligand docking, our results indicate that improving the representation of the chemistry of proteins and their ligands is another avenue that can lead to significant improvements in the identification, docking, and scoring of ligands.

In silico identification of novel ligands for G-quadruplex in the c- MYC promoter

NASA Astrophysics Data System (ADS)

Kang, Hyun-Jin; Park, Hyun-Ju

2015-04-01

G-quadruplex DNA formed in NHEIII1 region of oncogene promoter inhibits transcription of the genes. In this study, virtual screening combining pharmacophore-based search and structure-based docking screening was conducted to discover ligands binding to G-quadruplex in promoter region of c- MYC. Several hit ligands showed the selective PCR-arresting effects for oligonucleotide containing c- MYC G-quadruplex forming sequence. Among them, three hits selectively inhibited cell proliferation and decreased c- MYC mRNA level in Ramos cells, where NHEIII1 is included in translocated c- MYC gene for overexpression. Promoter assay using two kinds of constructs with wild-type and mutant sequences showed that interaction of these ligands with the G-quadruplex resulted in turning-off of the reporter gene. In conclusion, combined virtual screening methods were successfully used for discovery of selective c- MYC promoter G-quadruplex binders with anticancer activity.

Conformation guides molecular efficacy in docking screens of activated β-2 adrenergic G protein coupled receptor.

PubMed

Weiss, Dahlia R; Ahn, SeungKirl; Sassano, Maria F; Kleist, Andrew; Zhu, Xiao; Strachan, Ryan; Roth, Bryan L; Lefkowitz, Robert J; Shoichet, Brian K

2013-05-17

A prospective, large library virtual screen against an activated β2-adrenergic receptor (β2AR) structure returned potent agonists to the exclusion of inverse-agonists, providing the first complement to the previous virtual screening campaigns against inverse-agonist-bound G protein coupled receptor (GPCR) structures, which predicted only inverse-agonists. In addition, two hits recapitulated the signaling profile of the co-crystal ligand with respect to the G protein and arrestin mediated signaling. This functional fidelity has important implications in drug design, as the ability to predict ligands with predefined signaling properties is highly desirable. However, the agonist-bound state provides an uncertain template for modeling the activated conformation of other GPCRs, as a dopamine D2 receptor (DRD2) activated model templated on the activated β2AR structure returned few hits of only marginal potency.

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.

Discovery of novel SERCA inhibitors by virtual screening of a large compound library.

PubMed

Elam, Christopher; Lape, Michael; Deye, Joel; Zultowsky, Jodie; Stanton, David T; Paula, Stefan

2011-05-01

Two screening protocols based on recursive partitioning and computational ligand docking methodologies, respectively, were employed for virtual screens of a compound library with 345,000 entries for novel inhibitors of the enzyme sarco/endoplasmic reticulum calcium ATPase (SERCA), a potential target for cancer chemotherapy. A total of 72 compounds that were predicted to be potential inhibitors of SERCA were tested in bioassays and 17 displayed inhibitory potencies at concentrations below 100 μM. The majority of these inhibitors were composed of two phenyl rings tethered to each other by a short link of one to three atoms. Putative interactions between SERCA and the inhibitors were identified by inspection of docking-predicted poses and some of the structural features required for effective SERCA inhibition were determined by analysis of the classification pattern employed by the recursive partitioning models. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Real-time interactive virtual tour on the World Wide Web (WWW)

NASA Astrophysics Data System (ADS)

Yoon, Sanghyuk; Chen, Hai-jung; Hsu, Tom; Yoon, Ilmi

2003-12-01

Web-based Virtual Tour has become a desirable and demanded application, yet challenging due to the nature of web application's running environment such as limited bandwidth and no guarantee of high computation power on the client side. Image-based rendering approach has attractive advantages over traditional 3D rendering approach in such Web Applications. Traditional approach, such as VRML, requires labor-intensive 3D modeling process, high bandwidth and computation power especially for photo-realistic virtual scenes. QuickTime VR and IPIX as examples of image-based approach, use panoramic photos and the virtual scenes that can be generated from photos directly skipping the modeling process. But, these image-based approaches may require special cameras or effort to take panoramic views and provide only one fixed-point look-around and zooming in-out rather than 'walk around', that is a very important feature to provide immersive experience to virtual tourists. The Web-based Virtual Tour using Tour into the Picture employs pseudo 3D geometry with image-based rendering approach to provide viewers with immersive experience of walking around the virtual space with several snap shots of conventional photos.

Global vision of druggability issues: applications and perspectives.

PubMed

Abi Hussein, Hiba; Geneix, Colette; Petitjean, Michel; Borrel, Alexandre; Flatters, Delphine; Camproux, Anne-Claude

2017-02-01

During the preliminary stage of a drug discovery project, the lack of druggability information and poor target selection are the main causes of frequent failures. Elaborating on accurate computational druggability prediction methods is a requirement for prioritizing target selection, designing new drugs and avoiding side effects. In this review, we describe a survey of recently reported druggability prediction methods mainly based on networks, statistical pocket druggability predictions and virtual screening. An application for a frequent mutation of p53 tumor suppressor is presented, illustrating the complementarity of druggability prediction approaches, the remaining challenges and potential new drug development perspectives. Copyright © 2016 Elsevier Ltd. All rights reserved.

Virtual Reality as Innovative Approach to the Interior Designing

NASA Astrophysics Data System (ADS)

Kaleja, Pavol; Kozlovská, Mária

2017-06-01

We can observe significant potential of information and communication technologies (ICT) in interior designing field, by development of software and hardware virtual reality tools. Using ICT tools offer realistic perception of proposal in its initial idea (the study). A group of real-time visualization, supported by hardware tools like Oculus Rift HTC Vive, provides free walkthrough and movement in virtual interior with the possibility of virtual designing. By improving of ICT software tools for designing in virtual reality we can achieve still more realistic virtual environment. The contribution presented proposal of an innovative approach of interior designing in virtual reality, using the latest software and hardware ICT virtual reality technologies

Design of a Generic Questionnaire for Reflective Evaluation of a Virtual Reality-Based Intervention Using Virtual Dolphins for Children with Autism

ERIC Educational Resources Information Center

Chia, Noel Kok Hwee; Li, Jenyi

2012-01-01

There is an alarming increase in more Singaporean children diagnosed with special needs and it could be attributed to higher awareness and better screening procedure. However, research and development on various intervention strategies for children with special needs is still very lacking. With the introduction of information and communication…

Virtual Liver: Estimating Proliferation and Apoptosis of Hepatocytes Exposed to Environmental Chemicals Using ToxCastTM Data

EPA Science Inventory

The U.S. EPA’s ToxCastTM program has screened over a thousand chemicals for potential toxicity using hundreds of high-throughput, in vitro assays. The U.S. EPA’s Virtual Liver (v-Liver™) is a cellular systems model of hepatic tissues that enables the estimation of in vivo effects...

2D and 3D Traveling Salesman Problem

ERIC Educational Resources Information Center

Haxhimusa, Yll; Carpenter, Edward; Catrambone, Joseph; Foldes, David; Stefanov, Emil; Arns, Laura; Pizlo, Zygmunt

2011-01-01

When a two-dimensional (2D) traveling salesman problem (TSP) is presented on a computer screen, human subjects can produce near-optimal tours in linear time. In this study we tested human performance on a real and virtual floor, as well as in a three-dimensional (3D) virtual space. Human performance on the real floor is as good as that on a…

Discovery of novel EGFR tyrosine kinase inhibitors by structure-based virtual screening.

PubMed

Li, Siyuan; Sun, Xianqiang; Zhao, Hongli; Tang, Yun; Lan, Minbo

2012-06-15

By using of structure-based virtual screening, 13 novel epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors were discovered from 197,116 compounds in the SPECS database here. Among them, 8 compounds significantly inhibited EGFR kinase activity with IC(50) values lower than 10 μM. 3-{[1-(3-Chloro-4-fluorophenyl)-3,5-dioxo-4-pyrazolidinylidene]methyl}phenyl 2-thiophenecarboxylate (13), particularly, was the most potent inhibitor possessing the IC(50) value of 3.5 μM. The docking studies also provide some useful information that the docking models of the 13 compounds are beneficial to find a new path for designing novel EGFR inhibitors. Copyright © 2012 Elsevier Ltd. 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.

Virtual Screening and X-ray Crystallography for Human Kallikrein 6 Inhibitors with an Amidinothiophene P1 Group.

PubMed

Liang, Guyan; Chen, Xin; Aldous, Suzanne; Pu, Su-Fen; Mehdi, Shujaath; Powers, Elaine; Giovanni, Andrew; Kongsamut, Sathapana; Xia, Tianhui; Zhang, Ying; Wang, Rachel; Gao, Zhongli; Merriman, Gregory; McLean, Larry R; Morize, Isabelle

2012-02-09

A series of compounds with an amidinothiophene P1 group and a pyrrolidinone-sulphonamide scaffold linker was identified as potent inhibitors of human kallikrein 6 by structure-based virtual screening based on the union accessible binding space of serine proteases. As the first series of potent nonmechanism-based hK6 inhibitors, they may be used as tool compounds for target validation. An X-ray structure of a representative compound complexed with hK6, resolved at a resolution of 1.88 Å, revealed that the amidinothiophene moiety bound in the S1 pocket and the pyrrolidinone-sulphonamide linker projected the aromatic tail into the S' pocket.

Development and Application of a Virtual Screening Protocol for the Identification of Multitarget Fragments.

PubMed

Bottegoni, Giovanni; Veronesi, Marina; Bisignano, Paola; Kacker, Puneet; Favia, Angelo D; Cavalli, Andrea

2016-06-20

In this study, we report on a virtual ligand screening protocol optimized to identify fragments endowed with activity at multiple targets. Thanks to this protocol, we were able to identify a fragment that displays activity in the low-micromolar range at both β-secretase 1 (BACE-1) and glycogen synthase kinase 3β (GSK-3β). These two structurally and physiologically unrelated enzymes likely contribute, through different pathways, to the onset of Alzheimer's disease (AD). Therefore, their simultaneous inhibition holds great potential in exerting a profound effect on AD. In perspective, the strategy outlined herein can be adapted to other target combinations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Stereoscopic vascular models of the head and neck: A computed tomography angiography visualization.

PubMed

Cui, Dongmei; Lynch, James C; Smith, Andrew D; Wilson, Timothy D; Lehman, Michael N

2016-01-01

Computer-assisted 3D models are used in some medical and allied health science schools; however, they are often limited to online use and 2D flat screen-based imaging. Few schools take advantage of 3D stereoscopic learning tools in anatomy education and clinically relevant anatomical variations when teaching anatomy. A new approach to teaching anatomy includes use of computed tomography angiography (CTA) images of the head and neck to create clinically relevant 3D stereoscopic virtual models. These high resolution images of the arteries can be used in unique and innovative ways to create 3D virtual models of the vasculature as a tool for teaching anatomy. Blood vessel 3D models are presented stereoscopically in a virtual reality environment, can be rotated 360° in all axes, and magnified according to need. In addition, flexible views of internal structures are possible. Images are displayed in a stereoscopic mode, and students view images in a small theater-like classroom while wearing polarized 3D glasses. Reconstructed 3D models enable students to visualize vascular structures with clinically relevant anatomical variations in the head and neck and appreciate spatial relationships among the blood vessels, the skull and the skin. © 2015 American Association of Anatomists.

Tailoring gas sensor arrays via the design of short peptides sequences as binding elements.

PubMed

Mascini, Marcello; Pizzoni, Daniel; Perez, German; Chiarappa, Emilio; Di Natale, Corrado; Pittia, Paola; Compagnone, Dario

2017-07-15

A semi-combinatorial virtual approach was used to prepare peptide-based gas sensors with binding properties towards five different chemical classes (alcohols, aldehydes, esters, hydrocarbons and ketones). Molecular docking simulations were conducted for a complete tripeptide library (8000 elements) versus 58 volatile compounds belonging to those five chemical classes. By maximizing the differences between chemical classes, a subset of 120 tripeptides was extracted and used as scaffolds for generating a combinatorial library of 7912 tetrapeptides. This library was processed in an analogous way to the former. Five tetrapeptides (IHRI, KSDS, LGFD, TGKF and WHVS) were chosen depending on their virtual affinity and cross-reactivity for the experimental step. The five peptides were covalently bound to gold nanoparticles by adding a terminal cysteine to each tetrapeptide and deposited onto 20MHz quartz crystal microbalances to construct the gas sensors. The behavior of peptides after this chemical modification was simulated at the pH range used in the immobilization step. ΔF signals analyzed by principal component analysis matched the virtually screened data. The array was able to clearly discriminate the 13 volatile compounds tested based on their hydrophobicity and hydrophilicity molecules as well as the molecular weight. Copyright © 2016 Elsevier B.V. All rights reserved.

Hierarchical virtual screening of the dual MMP-2/HDAC-6 inhibitors from natural products based on pharmacophore models and molecular docking.

PubMed

Wang, Yijun; Yang, Limei; Hou, Jiaying; Zou, Qing; Gao, Qi; Yao, Wenhui; Yao, Qizheng; Zhang, Ji

2018-02-12

The dual-target inhibitors tend to improve the response rate in treating tumors, comparing with the single-target inhibitors. Matrix metalloproteinase-2 (MMP-2) and histone deacetylase-6 (HDAC-6) are attractive targets for cancer therapy. In this study, the hierarchical virtual screening of dual MMP-2/HDAC-6 inhibitors from natural products is investigated. The pharmacophore model of MMP-2 inhibitors is built based on ligands, but the pharmacophore model of HDAC-6 inhibitors is built based on the experimental crystal structures of multiple receptor-ligand complexes. The reliability of these two pharmacophore models is validated subsequently. The hierarchical virtual screening, combining these two different pharmacophore models of MMP-2 and HDAC-6 inhibitors with molecular docking, is carried out to identify the dual MMP-2/HDAC-6 inhibitors from a database of natural products. The four potential dual MMP-2/HDAC-6 inhibitors of natural products, STOCK1 N-46177, STOCK1 N-52245, STOCK1 N-55477, and STOCK1 N-69706, are found. The studies of binding modes show that the screened four natural products can simultaneously well bind with the MMP-2 and HDAC-6 active sites by different kinds of interactions, to inhibit the MMP-2 and HDAC-6 activities. In addition, the ADMET properties of screened four natural products are assessed. These found dual MMP-2/HDAC-6 inhibitors of natural products could serve as the lead compounds for designing the new dual MMP-2/HDAC-6 inhibitors having higher biological activities by carrying out structural modifications and optimizations in the future studies.

DOVIS 2.0: an efficient and easy to use parallel virtual screening tool based on AutoDock 4.0.

PubMed

Jiang, Xiaohui; Kumar, Kamal; Hu, Xin; Wallqvist, Anders; Reifman, Jaques

2008-09-08

Small-molecule docking is an important tool in studying receptor-ligand interactions and in identifying potential drug candidates. Previously, we developed a software tool (DOVIS) to perform large-scale virtual screening of small molecules in parallel on Linux clusters, using AutoDock 3.05 as the docking engine. DOVIS enables the seamless screening of millions of compounds on high-performance computing platforms. In this paper, we report significant advances in the software implementation of DOVIS 2.0, including enhanced screening capability, improved file system efficiency, and extended usability. To keep DOVIS up-to-date, we upgraded the software's docking engine to the more accurate AutoDock 4.0 code. We developed a new parallelization scheme to improve runtime efficiency and modified the AutoDock code to reduce excessive file operations during large-scale virtual screening jobs. We also implemented an algorithm to output docked ligands in an industry standard format, sd-file format, which can be easily interfaced with other modeling programs. Finally, we constructed a wrapper-script interface to enable automatic rescoring of docked ligands by arbitrarily selected third-party scoring programs. The significance of the new DOVIS 2.0 software compared with the previous version lies in its improved performance and usability. The new version makes the computation highly efficient by automating load balancing, significantly reducing excessive file operations by more than 95%, providing outputs that conform to industry standard sd-file format, and providing a general wrapper-script interface for rescoring of docked ligands. The new DOVIS 2.0 package is freely available to the public under the GNU General Public License.

Combining bioinformatics, chemoinformatics and experimental approaches to design chemical probes: Applications in the field of blood coagulation.

PubMed

Villoutreix, B O

2016-07-01

Bioinformatics and chemoinformatics approaches contribute to the discovery of novel targets, chemical probes, hits, leads and medicinal drugs. A vast repertoire of computational methods has indeed been reported over the years and in this review, I will briefly introduce some concepts and approaches, namely the analysis of potential therapeutic target binding pockets, the preparation of compound collections and virtual screening. An example of application is provided for two proteins acting in the blood coagulation system. Overall, in silico methods have been shown to improve R and D productivity in both, academic settings and in the private sector, if they are integrated in a rational manner with experimental approaches. However, integration of tools and pluridisciplinarity are seldom achieved. Efforts should be done in this direction as pluridisciplinarity and a true acknowledgment of all the contributing actors along the value chain could enhance innovation and reduce skyrocketing costs. Copyright © 2016 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Developing and validating predictive decision tree models from mining chemical structural fingerprints and high-throughput screening data in PubChem.

PubMed

Han, Lianyi; Wang, Yanli; Bryant, Stephen H

2008-09-25

Recent advances in high-throughput screening (HTS) techniques and readily available compound libraries generated using combinatorial chemistry or derived from natural products enable the testing of millions of compounds in a matter of days. Due to the amount of information produced by HTS assays, it is a very challenging task to mine the HTS data for potential interest in drug development research. Computational approaches for the analysis of HTS results face great challenges due to the large quantity of information and significant amounts of erroneous data produced. In this study, Decision Trees (DT) based models were developed to discriminate compound bioactivities by using their chemical structure fingerprints provided in the PubChem system http://pubchem.ncbi.nlm.nih.gov. The DT models were examined for filtering biological activity data contained in four assays deposited in the PubChem Bioassay Database including assays tested for 5HT1a agonists, antagonists, and HIV-1 RT-RNase H inhibitors. The 10-fold Cross Validation (CV) sensitivity, specificity and Matthews Correlation Coefficient (MCC) for the models are 57.2 approximately 80.5%, 97.3 approximately 99.0%, 0.4 approximately 0.5 respectively. A further evaluation was also performed for DT models built for two independent bioassays, where inhibitors for the same HIV RNase target were screened using different compound libraries, this experiment yields enrichment factor of 4.4 and 9.7. Our results suggest that the designed DT models can be used as a virtual screening technique as well as a complement to traditional approaches for hits selection.

Height effects in real and virtual environments.

PubMed

Simeonov, Peter I; Hsiao, Hongwei; Dotson, Brian W; Ammons, Douglas E

2005-01-01

The study compared human perceptions of height, danger, and anxiety, as well as skin conductance and heart rate responses and postural instability effects, in real and virtual height environments. The 24 participants (12 men, 12 women), whose average age was 23.6 years, performed "lean-over-the-railing" and standing tasks on real and comparable virtual balconies, using a surround-screen virtual reality (SSVR) system. The results indicate that the virtual display of elevation provided realistic perceptual experience and induced some physiological responses and postural instability effects comparable to those found in a real environment. It appears that a simulation of elevated work environment in a SSVR system, although with reduced visual fidelity, is a valid tool for safety research. Potential applications of this study include the design of virtual environments that will help in safe evaluation of human performance at elevation, identification of risk factors leading to fall incidents, and assessment of new fall prevention strategies.

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.

WarpEngine, a Flexible Platform for Distributed Computing Implemented in the VEGA Program and Specially Targeted for Virtual Screening Studies.

PubMed

Pedretti, Alessandro; Mazzolari, Angelica; Vistoli, Giulio

2018-05-21

The manuscript describes WarpEngine, a novel platform implemented within the VEGA ZZ suite of software for performing distributed simulations both in local and wide area networks. Despite being tailored for structure-based virtual screening campaigns, WarpEngine possesses the required flexibility to carry out distributed calculations utilizing various pieces of software, which can be easily encapsulated within this platform without changing their source codes. WarpEngine takes advantages of all cheminformatics features implemented in the VEGA ZZ program as well as of its largely customizable scripting architecture thus allowing an efficient distribution of various time-demanding simulations. To offer an example of the WarpEngine potentials, the manuscript includes a set of virtual screening campaigns based on the ACE data set of the DUD-E collections using PLANTS as the docking application. Benchmarking analyses revealed a satisfactory linearity of the WarpEngine performances, the speed-up values being roughly equal to the number of utilized cores. Again, the computed scalability values emphasized that a vast majority (i.e., >90%) of the performed simulations benefit from the distributed platform presented here. WarpEngine can be freely downloaded along with the VEGA ZZ program at www.vegazz.net .

Exploration of multiple Sortase A protein conformations in virtual screening

NASA Astrophysics Data System (ADS)

Gao, Chunxia; Uzelac, Ivana; Gottfries, Johan; Eriksson, Leif A.

2016-02-01

Methicillin resistant Staphylococcus aureus (MRSA) has become a major health concern which has brought about an urgent need for new therapeutic agents. As the S. aureus Sortase A (SrtA) enzyme contributes to the adherence of the bacteria to the host cells, inhibition thereof by small molecules could be employed as potential antivirulence agents, also towards resistant strains. Albeit several virtual docking SrtA campaigns have been reported, no strongly inhibitatory non-covalent binders have as yet emerged therefrom. In order to better understand the binding modes of small molecules, and the effect of different receptor structures employed in the screening, we herein report on an exploratory study employing 10 known binders and 500 decoys on 100 SrtA structures generated from regular or steered molecular dynamics simulations on four different SrtA crystal/NMR structures. The results suggest a correlation between the protein structural flexibility and the virtual screening performance, and confirm the noted immobilization of the β6/β7 loop upon substrate binding. The NMR structures reported appear to perform slightly better than the Xray-crystal structures, but the binding modes fluctuate tremendously, and it might be suspected that the catalytic site is not necessarily the preferred site of binding for some of the reported active compounds.

Exploration of multiple Sortase A protein conformations in virtual screening

PubMed Central

Gao, Chunxia; Uzelac, Ivana; Gottfries, Johan; Eriksson, Leif A.

2016-01-01

Methicillin resistant Staphylococcus aureus (MRSA) has become a major health concern which has brought about an urgent need for new therapeutic agents. As the S. aureus Sortase A (SrtA) enzyme contributes to the adherence of the bacteria to the host cells, inhibition thereof by small molecules could be employed as potential antivirulence agents, also towards resistant strains. Albeit several virtual docking SrtA campaigns have been reported, no strongly inhibitatory non-covalent binders have as yet emerged therefrom. In order to better understand the binding modes of small molecules, and the effect of different receptor structures employed in the screening, we herein report on an exploratory study employing 10 known binders and 500 decoys on 100 SrtA structures generated from regular or steered molecular dynamics simulations on four different SrtA crystal/NMR structures. The results suggest a correlation between the protein structural flexibility and the virtual screening performance, and confirm the noted immobilization of the β6/β7 loop upon substrate binding. The NMR structures reported appear to perform slightly better than the Xray-crystal structures, but the binding modes fluctuate tremendously, and it might be suspected that the catalytic site is not necessarily the preferred site of binding for some of the reported active compounds. PMID:26846342

μ Opioid receptor: novel antagonists and structural modeling

NASA Astrophysics Data System (ADS)

Kaserer, Teresa; Lantero, Aquilino; Schmidhammer, Helmut; Spetea, Mariana; Schuster, Daniela

2016-02-01

The μ opioid receptor (MOR) is a prominent member of the G protein-coupled receptor family and the molecular target of morphine and other opioid drugs. Despite the long tradition of MOR-targeting drugs, still little is known about the ligand-receptor interactions and structure-function relationships underlying the distinct biological effects upon receptor activation or inhibition. With the resolved crystal structure of the β-funaltrexamine-MOR complex, we aimed at the discovery of novel agonists and antagonists using virtual screening tools, i.e. docking, pharmacophore- and shape-based modeling. We suggest important molecular interactions, which active molecules share and distinguish agonists and antagonists. These results allowed for the generation of theoretically validated in silico workflows that were employed for prospective virtual screening. Out of 18 virtual hits evaluated in in vitro pharmacological assays, three displayed antagonist activity and the most active compound significantly inhibited morphine-induced antinociception. The new identified chemotypes hold promise for further development into neurochemical tools for studying the MOR or as potential therapeutic lead candidates.

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

Magnifying Smartphone Screen Using Google Glass for Low-Vision Users.

PubMed

Pundlik, Shrinivas; HuaQi Yi; Rui Liu; Peli, Eli; Gang Luo

2017-01-01

Magnification is a key accessibility feature used by low-vision smartphone users. However, small screen size can lead to loss of context and make interaction with magnified displays challenging. We hypothesize that controlling the viewport with head motion can be natural and help in gaining access to magnified displays. We implement this idea using a Google Glass that displays the magnified smartphone screenshots received in real time via Bluetooth. Instead of navigating with touch gestures on the magnified smartphone display, the users can view different screen locations by rotating their head, and remotely interacting with the smartphone. It is equivalent to looking at a large virtual image through a head contingent viewing port, in this case, the Glass display with ~ 15 ° field of view. The system can transfer seven screenshots per second at 8 × magnification, sufficient for tasks where the display content does not change rapidly. A pilot evaluation of this approach was conducted with eight normally sighted and four visually impaired subjects performing assigned tasks using calculator and music player apps. Results showed that performance in the calculation task was faster with the Glass than with the phone's built-in screen zoom. We conclude that head contingent scanning control can be beneficial in navigating magnified small smartphone displays, at least for tasks involving familiar content layout.

Open Innovation Drug Discovery (OIDD): a potential path to novel therapeutic chemical space.

PubMed

Alvim-Gaston, Maria; Grese, Timothy; Mahoui, Abdelaziz; Palkowitz, Alan D; Pineiro-Nunez, Marta; Watson, Ian

2014-01-01

The continued development of computational and synthetic methods has enabled the enumeration or preparation of a nearly endless universe of chemical structures. Nevertheless, the ability of this chemical universe to deliver small molecules that can both modulate biological targets and have drug-like physicochemical properties continues to be a topic of interest to the pharmaceutical industry and academic researchers alike. The chemical space described by public, commercial, in-house and virtual compound collections has been interrogated by multiple approaches including biochemical, cellular and virtual screening, diversity analysis, and in-silico profiling. However, current drugs and known chemical probes derived from these efforts are contained within a remarkably small volume of the predicted chemical space. Access to more diverse classes of chemical scaffolds that maintain the properties relevant for drug discovery is certainly needed to meet the increasing demands for pharmaceutical innovation. The Lilly Open Innovation Drug Discovery platform (OIDD) was designed to tackle barriers to innovation through the identification of novel molecules active in relevant disease biology models. In this article we will discuss several computational approaches towards describing novel, biologically active, drug-like chemical space and illustrate how the OIDD program may facilitate access to previously untapped molecules that may aid in the search for innovative pharmaceuticals.

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.

Benefits, harms, and costs for breast cancer screening after US implementation of digital mammography.

PubMed

Stout, Natasha K; Lee, Sandra J; Schechter, Clyde B; Kerlikowske, Karla; Alagoz, Oguzhan; Berry, Donald; Buist, Diana S M; Cevik, Mucahit; Chisholm, Gary; de Koning, Harry J; Huang, Hui; Hubbard, Rebecca A; Miglioretti, Diana L; Munsell, Mark F; Trentham-Dietz, Amy; van Ravesteyn, Nicolien T; Tosteson, Anna N A; Mandelblatt, Jeanne S

2014-06-01

Compared with film, digital mammography has superior sensitivity but lower specificity for women aged 40 to 49 years and women with dense breasts. Digital has replaced film in virtually all US facilities, but overall population health and cost from use of this technology are unclear. Using five independent models, we compared digital screening strategies starting at age 40 or 50 years applied annually, biennially, or based on density with biennial film screening from ages 50 to 74 years and with no screening. Common data elements included cancer incidence and test performance, both modified by breast density. Lifetime outcomes included mortality, quality-adjusted life-years, and screening and treatment costs. For every 1000 women screened biennially from age 50 to 74 years, switching to digital from film yielded a median within-model improvement of 2 life-years, 0.27 additional deaths averted, 220 additional false-positive results, and $0.35 million more in costs. For an individual woman, this translates to a health gain of 0.73 days. Extending biennial digital screening to women ages 40 to 49 years was cost-effective, although results were sensitive to quality-of-life decrements related to screening and false positives. Targeting annual screening by density yielded similar outcomes to targeting by age. Annual screening approaches could increase costs to $5.26 million per 1000 women, in part because of higher numbers of screens and false positives, and were not efficient or cost-effective. The transition to digital breast cancer screening in the United States increased total costs for small added health benefits. The value of digital mammography screening among women aged 40 to 49 years depends on women's preferences regarding false positives. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pistacia lentiscus Oleoresin: Virtual Screening and Identification of Masticadienonic and Isomasticadienonic Acids as Inhibitors of 11β-Hydroxysteroid Dehydrogenase 1.

PubMed

Vuorinen, Anna; Seibert, Julia; Papageorgiou, Vassilios P; Rollinger, Judith M; Odermatt, Alex; Schuster, Daniela; Assimopoulou, Andreana N

2015-04-01

In traditional medicine, the oleoresinous gum of Pistacia lentiscus var. chia, so-called mastic gum, has been used to treat multiple conditions such as coughs, sore throats, eczema, dyslipidemia, and diabetes. Mastic gum is rich in triterpenes, which have been postulated to exert antidiabetic effects and improve lipid metabolism. In fact, there is evidence of oleanonic acid, a constituent of mastic gum, acting as a peroxisome proliferator-activated receptor γ agonist, and mastic gum being antidiabetic in mice in vivo. Despite these findings, the exact antidiabetic mechanism of mastic gum remains unknown. Glucocorticoids play a key role in regulating glucose and fatty acid metabolism, and inhibition of 11β-hydroxysteroid dehydrogenase 1 that converts inactive cortisone to active cortisol has been proposed as a promising approach to combat metabolic disturbances including diabetes. In this study, a pharmacophore-based virtual screening was applied to filter a natural product database for possible 11β-hydroxysteroid dehydrogenase 1 inhibitors. The hit list analysis was especially focused on the triterpenoids present in Pistacia species. Multiple triterpenoids, such as masticadienonic acid and isomasticadienonic acid, main constituents of mastic gum, were identified. Indeed, masticadienonic acid and isomasticadienonic acid selectively inhibited 11β-hydroxysteroid dehydrogenase 1 over 11β-hydroxysteroid dehydrogenase 2 at low micromolar concentrations. These findings suggest that inhibition of 11β-hydroxysteroid dehydrogenase 1 contributes to the antidiabetic activity of mastic gum. Georg Thieme Verlag KG Stuttgart · New York.

Computer-Guided Approach to Access the Anti-influenza Activity of Licorice Constituents

PubMed Central

2013-01-01

Neuraminidase (NA), a key enzyme in viral replication, is the first-line drug target to combat influenza. On the basis of a shape-focused virtual screening, the roots of Glycyrrhiza glabra (licorice) were identified as plant species with an accumulation of constituents that show 3D similarities to known influenza NA inhibitors (NAIs). Phytochemical investigation revealed 12 constituents identified as (E)-1-[2,4-dihydroxy-3-(3-methyl-2-butenyl)phenyl]-3-(8-hydroxy-2,2-dimethyl-2H-1-benzopyran-6-yl)-2-propen-1-one (1), 3,4-dihydro-8,8-dimethyl-2H,8H-benzo[1,2-b:3,4-b′]dipyran-3-ol (2), biochanin B (3), glabrol (4), glabrone (5), hispaglabridin B (6), licoflavone B (7), licorice glycoside B (8), licorice glycoside E (9), liquiritigenin (10), liquiritin (11), and prunin (12). Eleven of these constituents showed significant influenza virus NA inhibition in a chemiluminescence (CL)-based assay. Additional tests, including (i) a cell-based cytopathic effect inhibition assay (general antiviral activity), (ii) the evaluation of cytotoxicity, (iii) the inhibition of the NA of Clostridium perfringens (CL- and fluorescence (FL)-based assay), and (iv) the determination of self-fluorescence and quenching, provided further perspective on their anti-influenza virus potential, revealing possible assay interference problems and false-positive results. Compounds 1, 3, 5, and 6 showed antiviral activity, most likely caused by the inhibition of NA. Of these, compounds 1, 3, and 6 were highly ranked in shape-focused virtual screening. PMID:24313801

Macromolecular Modelling and Docking Simulations for the Discovery of Selective GPER Ligands.

PubMed

Rosano, Camillo; Ponassi, Marco; Santolla, Maria Francesca; Pisano, Assunta; Felli, Lamberto; Vivacqua, Adele; Maggiolini, Marcello; Lappano, Rosamaria

2016-01-01

Estrogens influence multiple physiological processes and are implicated in many diseases as well. Cellular responses to estrogens are mainly mediated by the estrogen receptors (ER)α and ERβ, which act as ligand-activated transcription factors. Recently, a member of the G protein-coupled receptor (GPCR) superfamily, namely GPER/GPR30, has been identified as a further mediator of estrogen signalling in different pathophysiological conditions, including cancer. Today, computational methods are commonly used in all areas of health science research. Among these methods, virtual ligand screening has become an established technique for hit discovery and optimization. The absence of an established three-dimensional structure of GPER promoted studies of structure-based drug design in order to build reliable molecular models of this receptor. Here, we discuss the results obtained through the structure-based virtual ligand screening for GPER, which allowed the identification and synthesis of different selective agonist and antagonist moieties. These compounds led significant advances in our understanding of the GPER function at the cellular, tissue, and organismal levels. In particular, selective GPER ligands were critical toward the evaluation of the role elicited by this receptor in several pathophysiological conditions, including cancer. Considering that structure-based approaches are fundamental in drug discovery, future research breakthroughs with the aid of computer-aided molecular design and chemo-bioinformatics could generate a new class of drugs that, acting through GPER, would be useful in a variety of diseases as well as in innovative anticancer strategies.

Selecting an optimal number of binding site waters to improve virtual screening enrichments against the adenosine A2A receptor.

PubMed

Lenselink, Eelke B; Beuming, Thijs; Sherman, Woody; van Vlijmen, Herman W T; IJzerman, Adriaan P

2014-06-23

A major challenge in structure-based virtual screening (VS) involves the treatment of explicit water molecules during docking in order to improve the enrichment of active compounds over decoys. Here we have investigated this in the context of the adenosine A2A receptor, where water molecules have previously been shown to be important for achieving high enrichment rates with docking, and where the positions of some binding site waters are known from a high-resolution crystal structure. The effect of these waters (both their presence and orientations) on VS enrichment was assessed using a carefully curated set of 299 high affinity A2A antagonists and 17,337 decoys. We show that including certain crystal waters greatly improves VS enrichment and that optimization of water hydrogen positions is needed in order to achieve the best results. We also show that waters derived from a molecular dynamics simulation - without any knowledge of crystallographic waters - can improve enrichments to a similar degree as the crystallographic waters, which makes this strategy applicable to structures without experimental knowledge of water positions. Finally, we used decision trees to select an ensemble of structures with different water molecule positions and orientations that outperforms any single structure with water molecules. The approach presented here is validated against independent test sets of A2A receptor antagonists and decoys from the literature. In general, this water optimization strategy could be applied to any target with waters-mediated protein-ligand interactions.

Discovery of Selective Inhibitors of Imidazoleglycerol-Phosphate Dehydratase from Mycobacterium tuberculosis by Virtual Screening

NASA Astrophysics Data System (ADS)

Podshivalov, D.; Mandzhieva, Yu. B.; Sidorov-Biryukov, D. D.; Timofeev, V. I.; Kuranova, I. P.

2018-01-01

Bacterial imidazoleglycerol-phosphate dehydratase from Mycobacterium tuberculosis (HisB- Mt) is a convenient target for the discovery of selective inhibitors as potential antituberculosis drugs. The virtual screening was performed to find compounds suitable for the design of selective inhibitors of HisB- Mt. The positions of four ligands, which were selected based on the docking scoring function and docked to the activesite region of the enzyme, were refined by molecular dynamics simulation. The nearest environment of the ligands was determined. These compounds selectively bind to functionally essential active-site residues, thus blocking access of substrates to the active site of the enzyme, and can be used as lead compounds for the design of selective inhibitors of HisB- M.

Discovery of novel inhibitors of the NorA multidrug transporter of Staphylococcus aureus.

PubMed

Brincat, Jean Pierre; Carosati, Emanuele; Sabatini, Stefano; Manfroni, Giuseppe; Fravolini, Arnaldo; Raygada, Jose L; Patel, Diixa; Kaatz, Glenn W; Cruciani, Gabriele

2011-01-13

Four novel inhibitors of the NorA efflux pump of Staphylococcus aureus, discovered through a virtual screening process, are reported. The four compounds belong to different chemical classes and were tested for their in vitro ability to block the efflux of a well-known NorA substrate, as well as for their ability to potentiate the effect of ciprofloxacin (CPX) on several strains of S. aureus, including a NorA overexpressing strain. Additionally, the MIC values of each of the compounds individually are reported. A structure-activity relationship study was also performed on these novel chemotypes, revealing three new compounds that are also potent NorA inhibitors. The virtual screening procedure employed FLAP, a new methodology based on GRID force field descriptors.

Discovery of novel bacterial RNA polymerase inhibitors: pharmacophore-based virtual screening and hit optimization.

PubMed

Hinsberger, Stefan; Hüsecken, Kristina; Groh, Matthias; Negri, Matthias; Haupenthal, Jörg; Hartmann, Rolf W

2013-11-14

The bacterial RNA polymerase (RNAP) is a validated target for broad spectrum antibiotics. However, the efficiency of drugs is reduced by resistance. To discover novel RNAP inhibitors, a pharmacophore based on the alignment of described inhibitors was used for virtual screening. In an optimization process of hit compounds, novel derivatives with improved in vitro potency were discovered. Investigations concerning the molecular mechanism of RNAP inhibition reveal that they prevent the protein-protein interaction (PPI) between σ(70) and the RNAP core enzyme. Besides of reducing RNA formation, the inhibitors were shown to interfere with bacterial lipid biosynthesis. The compounds were active against Gram-positive pathogens and revealed significantly lower resistance frequencies compared to clinically used rifampicin.

Performance of a docking/molecular dynamics protocol for virtual screening of nutlin-class inhibitors of Mdmx.

PubMed

Bharatham, Nagakumar; Finch, Kristin E; Min, Jaeki; Mayasundari, Anand; Dyer, Michael A; Guy, R Kiplin; Bashford, Donald

2017-06-01

A virtual screening protocol involving docking and molecular dynamics has been tested against the results of fluorescence polarization assays testing the potency of a series of compounds of the nutlin class for inhibition of the interaction between p53 and Mdmx, an interaction identified as a driver of certain cancers. The protocol uses a standard docking method (AutoDock) with a cutoff based on the AutoDock score (ADscore), followed by molecular dynamics simulation with a cutoff based on root-mean-square-deviation (RMSD) from the docked pose. An analysis of the experimental and computational results shows modest performance of ADscore alone, but dramatically improved performance when RMSD is also used. Published by Elsevier Inc.

Engagement with Electronic Screen Media among Students with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Mineo, Beth A.; Ziegler, William; Gill, Susan; Salkin, Donna

2009-01-01

This study investigated the relative engagement potential of four types of electronic screen media (ESM): animated video, video of self, video of a familiar person engaged with an immersive virtual reality (VR) game, and immersion of self in the VR game. Forty-two students with autism, varying in age and expressive communication ability, were…

Towards a Methodology for Managing Competencies in Virtual Teams - A Systemic Approach

NASA Astrophysics Data System (ADS)

Schumacher, Marinita; Stal-Le Cardinal, Julie; Bocquet, Jean-Claude

Virtual instruments and tools are future trends in Engineering which are a response to the growing complexity of engineering tasks, the facility of communication and strong collaborations on the international market. Outsourcing, off-shoring, and the globalization of organisations’ activities have resulted in the formation of virtual product development teams. Individuals who are working in virtual teams must be equipped with diversified competencies that provide a basis for virtual team building. Thanks to the systemic approach of the functional analysis our paper responds to the need of a methodology of competence management to build virtual teams that are active in virtual design projects in the area of New Product Development (NPD).

CSBB-ConeExclusion, adapting structure based solution virtual screening to libraries on solid support.

PubMed

Shave, Steven; Auer, Manfred

2013-12-23

Combinatorial chemical libraries produced on solid support offer fast and cost-effective access to a large number of unique compounds. If such libraries are screened directly on-bead, the speed at which chemical space can be explored by chemists is much greater than that addressable using solution based synthesis and screening methods. Solution based screening has a large supporting body of software such as structure-based virtual screening tools which enable the prediction of protein-ligand complexes. Use of these techniques to predict the protein bound complexes of compounds synthesized on solid support neglects to take into account the conjugation site on the small molecule ligand. This may invalidate predicted binding modes, the linker may be clashing with protein atoms. We present CSBB-ConeExclusion, a methodology and computer program which provides a measure of the applicability of solution dockings to solid support. Output is given in the form of statistics for each docking pose, a unique 2D visualization method which can be used to determine applicability at a glance, and automatically generated PyMol scripts allowing visualization of protein atom incursion into a defined exclusion volume. CSBB-ConeExclusion is then exemplarically used to determine the optimum attachment point for a purine library targeting cyclin-dependent kinase 2 CDK2.

Multiaccommodative stimuli in VR systems: problems & solutions.

PubMed

Marran, L; Schor, C

1997-09-01

Virtual reality environments can introduce multiple and sometimes conflicting accommodative stimuli. For instance, with the high-powered lenses commonly used in head-mounted displays, small discrepancies in screen lens placement, caused by manufacturer error or user adjustment focus error, can change the focal depths of the image by a couple of diopters. This can introduce a binocular accommodative stimulus or, if the displacement between the two screens is unequal, an unequal (anisometropic) accommodative stimulus for the two eyes. Systems that allow simultaneous viewing of virtual and real images can also introduce a conflict in accommodative stimuli: When real and virtual images are at different focal planes, both cannot be in focus at the same time, though they may appear to be in similar locations in space. In this paper four unique designs are described that minimize the range of accommodative stimuli and maximize the visual system's ability to cope efficiently with the focus conflicts that remain: pinhole optics, monocular lens addition combined with aniso-accommodation, chromatic bifocal, and bifocal lens system. The advantages and disadvantages of each design are described and recommendation for design choice is given after consideration of the end use of the virtual reality system (e.g., low or high end, entertainment, technical, or medical use). The appropriate design modifications should allow greater user comfort and better performance.

Possible applications of the LEAP motion controller for more interactive simulated experiments in augmented or virtual reality

NASA Astrophysics Data System (ADS)

Wozniak, Peter; Vauderwange, Oliver; Mandal, Avikarsha; Javahiraly, Nicolas; Curticapean, Dan

2016-09-01

Practical exercises are a crucial part of many curricula. Even simple exercises can improve the understanding of the underlying subject. Most experimental setups require special hardware. To carry out e. g. a lens experiments the students need access to an optical bench, various lenses, light sources, apertures and a screen. In our previous publication we demonstrated the use of augmented reality visualization techniques in order to let the students prepare with a simulated experimental setup. Within the context of our intended blended learning concept we want to utilize augmented or virtual reality techniques for stationary laboratory exercises. Unlike applications running on mobile devices, stationary setups can be extended more easily with additional interfaces and thus allow for more complex interactions and simulations in virtual reality (VR) and augmented reality (AR). The most significant difference is the possibility to allow interactions beyond touching a screen. The LEAP Motion controller is a small inexpensive device that allows for the tracking of the user's hands and fingers in three dimensions. It is conceivable to allow the user to interact with the simulation's virtual elements by the user's very hand position, movement and gesture. In this paper we evaluate possible applications of the LEAP Motion controller for simulated experiments in augmented and virtual reality. We pay particular attention to the devices strengths and weaknesses and want to point out useful and less useful application scenarios.

West Nile Virus Drug Discovery

PubMed Central

Lim, Siew Pheng; Shi, Pei-Yong

2013-01-01

The outbreak of West Nile virus (WNV) in 1999 in the USA, and its continued spread throughout the Americas, parts of Europe, the Middle East and Africa, underscored the need for WNV antiviral development. Here, we review the current status of WNV drug discovery. A number of approaches have been used to search for inhibitors of WNV, including viral infection-based screening, enzyme-based screening, structure-based virtual screening, structure-based rationale design, and antibody-based therapy. These efforts have yielded inhibitors of viral or cellular factors that are critical for viral replication. For small molecule inhibitors, no promising preclinical candidate has been developed; most of the inhibitors could not even be advanced to the stage of hit-to-lead optimization due to their poor drug-like properties. However, several inhibitors developed for related members of the family Flaviviridae, such as dengue virus and hepatitis C virus, exhibited cross-inhibition of WNV, suggesting the possibility to re-purpose these antivirals for WNV treatment. Most promisingly, therapeutic antibodies have shown excellent efficacy in mouse model; one of such antibodies has been advanced into clinical trial. The knowledge accumulated during the past fifteen years has provided better rationale for the ongoing WNV and other flavivirus antiviral development. PMID:24300672