Chemical-Space-Based de Novo Design Method To Generate Drug-Like Molecules.

PubMed

Takeda, Shunichi; Kaneko, Hiromasa; Funatsu, Kimito

2016-10-24

To discover drug compounds in chemical space containing an enormous number of compounds, a structure generator is required to produce virtual drug-like chemical structures. The de novo design algorithm for exploring chemical space (DAECS) visualizes the activity distribution on a two-dimensional plane corresponding to chemical space and generates structures in a target area on a plane selected by the user. In this study, we modify the DAECS to enable the user to select a target area to consider properties other than activity and improve the diversity of the generated structures by visualizing the drug-likeness distribution and the activity distribution, generating structures by substructure-based structural changes, including addition, deletion, and substitution of substructures, as well as the slight structural changes used in the DAECS. Through case studies using ligand data for the human adrenergic alpha2A receptor and the human histamine H1 receptor, the modified DAECS can generate high diversity drug-like structures, and the usefulness of the modification of the DAECS is verified.

Structure-based drug design: aiming for a perfect fit

PubMed Central

van Montfort, Rob L.M.; Workman, Paul

2017-01-01

Knowledge of the three-dimensional structure of therapeutically relevant targets has informed drug discovery since the first protein structures were determined using X-ray crystallography in the 1950s and 1960s. In this editorial we provide a brief overview of the powerful impact of structure-based drug design (SBDD), which has its roots in computational and structural biology, with major contributions from both academia and industry. We describe advances in the application of SBDD for integral membrane protein targets that have traditionally proved very challenging. We emphasize the major progress made in fragment-based approaches for which success has been exemplified by over 30 clinical drug candidates and importantly three FDA-approved drugs in oncology. We summarize the articles in this issue that provide an excellent snapshot of the current state of the field of SBDD and fragment-based drug design and which offer key insights into exciting new developments, such as the X-ray free-electron laser technology, cryo-electron microscopy, open science approaches and targeted protein degradation. We stress the value of SBDD in the design of high-quality chemical tools that are used to interrogate biology and disease pathology, and to inform target validation. We emphasize the need to maintain the scientific rigour that has been traditionally associated with structural biology and extend this to other methods used in drug discovery. This is particularly important because the quality and robustness of any form of contributory data determines its usefulness in accelerating drug design, and therefore ultimately in providing patient benefit. PMID:29118091

Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key.

PubMed

Haupt, V Joachim; Daminelli, Simone; Schroeder, Michael

2013-01-01

Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) - a drug's ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor influence.

Oral and transdermal drug delivery systems: role of lipid-based lyotropic liquid crystals.

PubMed

Rajabalaya, Rajan; Musa, Muhammad Nuh; Kifli, Nurolaini; David, Sheba R

2017-01-01

Liquid crystal (LC) dosage forms, particularly those using lipid-based lyotropic LCs (LLCs), have generated considerable interest as potential drug delivery systems. LCs have the physical properties of liquids but retain some of the structural characteristics of crystalline solids. They are compatible with hydrophobic and hydrophilic compounds of many different classes and can protect even biologicals and nucleic acids from degradation. This review, focused on research conducted over the past 5 years, discusses the structural evaluation of LCs and their effects in drug formulations. The structural classification of LLCs into lamellar, hexagonal and micellar cubic phases is described. The structures of these phases are influenced by the addition of surfactants, which include a variety of nontoxic, biodegradable lipids; these also enhance drug solubility. LLC structure influences drug localization, particle size and viscosity, which, in turn, determine drug delivery properties. Through several specific examples, we describe the applications of LLCs in oral and topical drug formulations, the latter including transdermal and ocular delivery. In oral LLC formulations, micelle compositions and the resulting LLC structures can determine drug solubilization and stability as well as intestinal transport and absorption. Similarly, in topical LLC formulations, composition can influence whether the drug is retained in the skin or delivered transdermally. Owing to their enhancement of drug stability and promotion of controlled drug delivery, LLCs are becoming increasingly popular in pharmaceutical formulations.

Oral and transdermal drug delivery systems: role of lipid-based lyotropic liquid crystals

PubMed Central

Rajabalaya, Rajan; Musa, Muhammad Nuh; Kifli, Nurolaini; David, Sheba R

2017-01-01

Liquid crystal (LC) dosage forms, particularly those using lipid-based lyotropic LCs (LLCs), have generated considerable interest as potential drug delivery systems. LCs have the physical properties of liquids but retain some of the structural characteristics of crystalline solids. They are compatible with hydrophobic and hydrophilic compounds of many different classes and can protect even biologicals and nucleic acids from degradation. This review, focused on research conducted over the past 5 years, discusses the structural evaluation of LCs and their effects in drug formulations. The structural classification of LLCs into lamellar, hexagonal and micellar cubic phases is described. The structures of these phases are influenced by the addition of surfactants, which include a variety of nontoxic, biodegradable lipids; these also enhance drug solubility. LLC structure influences drug localization, particle size and viscosity, which, in turn, determine drug delivery properties. Through several specific examples, we describe the applications of LLCs in oral and topical drug formulations, the latter including transdermal and ocular delivery. In oral LLC formulations, micelle compositions and the resulting LLC structures can determine drug solubilization and stability as well as intestinal transport and absorption. Similarly, in topical LLC formulations, composition can influence whether the drug is retained in the skin or delivered transdermally. Owing to their enhancement of drug stability and promotion of controlled drug delivery, LLCs are becoming increasingly popular in pharmaceutical formulations. PMID:28243062

Solution NMR Spectroscopy in Target-Based Drug Discovery.

PubMed

Li, Yan; Kang, Congbao

2017-08-23

Solution NMR spectroscopy is a powerful tool to study protein structures and dynamics under physiological conditions. This technique is particularly useful in target-based drug discovery projects as it provides protein-ligand binding information in solution. Accumulated studies have shown that NMR will play more and more important roles in multiple steps of the drug discovery process. In a fragment-based drug discovery process, ligand-observed and protein-observed NMR spectroscopy can be applied to screen fragments with low binding affinities. The screened fragments can be further optimized into drug-like molecules. In combination with other biophysical techniques, NMR will guide structure-based drug discovery. In this review, we describe the possible roles of NMR spectroscopy in drug discovery. We also illustrate the challenges encountered in the drug discovery process. We include several examples demonstrating the roles of NMR in target-based drug discoveries such as hit identification, ranking ligand binding affinities, and mapping the ligand binding site. We also speculate the possible roles of NMR in target engagement based on recent processes in in-cell NMR spectroscopy.

Integrating structure-based and ligand-based approaches for computational drug design.

PubMed

Wilson, Gregory L; Lill, Markus A

2011-04-01

Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.

Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions.

PubMed

Lipinski, Christopher A

2016-06-01

The rule of five (Ro5), based on physicochemical profiles of phase II drugs, is consistent with structural limitations in protein targets and the drug target ligands. Three of four parameters in Ro5 are fundamental to the structure of both target and drug binding sites. The chemical structure of the drug ligand depends on the ligand chemistry and design philosophy. Two extremes of chemical structure and design philosophy exist; ligands constructed in the medicinal chemistry synthesis laboratory without input from natural selection and natural product (NP) metabolites biosynthesized based on evolutionary selection. Exceptions to Ro5 are found mostly among NPs. Chemistry chameleon-like behavior of some NPs due to intra-molecular hydrogen bonding as exemplified by cyclosporine A is a strong contributor to NP Ro5 outliers. The fragment derived, drug Navitoclax is an example of the extensive expertise, resources, time and key decisions required for the rare discovery of a non-NP Ro5 outlier. Copyright © 2016 Elsevier B.V. All rights reserved.

Collaborative Core Research Program for Chemical-Biological Warfare Defense

DTIC Science & Technology

2015-01-04

Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD...Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD) Current pharmaceutical approaches involving drug discovery...structural analysis and docking program generally known as fragment based drug design (FBDD). The main advantage of using these approaches is that

X-ray and cryo-EM structures of inhibitor-bound cytochrome bc 1 complexes for structure-based drug discovery

PubMed Central

Amporndanai, Kangsa; O’Neill, Paul M.

2018-01-01

Cytochrome bc 1, a dimeric multi-subunit electron-transport protein embedded in the inner mitochondrial membrane, is a major drug target for the treatment and prevention of malaria and toxoplasmosis. Structural studies of cytochrome bc 1 from mammalian homologues co-crystallized with lead compounds have underpinned structure-based drug design to develop compounds with higher potency and selectivity. However, owing to the limited amount of cytochrome bc 1 that may be available from parasites, all efforts have been focused on homologous cytochrome bc 1 complexes from mammalian species, which has resulted in the failure of some drug candidates owing to toxicity in the host. Crystallographic studies of the native parasite proteins are not feasible owing to limited availability of the proteins. Here, it is demonstrated that cytochrome bc 1 is highly amenable to single-particle cryo-EM (which uses significantly less protein) by solving the apo and two inhibitor-bound structures to ∼4.1 Å resolution, revealing clear inhibitor density at the binding site. Therefore, cryo-EM is proposed as a viable alternative method for structure-based drug discovery using both host and parasite enzymes. PMID:29765610

Structural systems pharmacology: a new frontier in discovering novel drug targets.

PubMed

Tan, Hepan; Ge, Xiaoxia; Xie, Lei

2013-08-01

The modern target-based drug discovery process, characterized by the one-drug-one-gene paradigm, has been of limited success. In contrast, phenotype-based screening produces thousands of active compounds but gives no hint as to what their molecular targets are or which ones merit further research. This presents a question: What is a suitable target for an efficient and safe drug? In this paper, we argue that target selection should take into account the proteome-wide energetic and kinetic landscape of drug-target interactions, as well as their cellular and organismal consequences. We propose a new paradigm of structural systems pharmacology to deconvolute the molecular targets of successful drugs as well as to identify druggable targets and their drug-like binders. Here we face two major challenges in structural systems pharmacology: How do we characterize and analyze the structural and energetic origins of drug-target interactions on a proteome scale? How do we correlate the dynamic molecular interactions to their in vivo activity? We will review recent advances in developing new computational tools for biophysics, bioinformatics, chemoinformatics, and systems biology related to the identification of genome-wide target profiles. We believe that the integration of these tools will realize structural systems pharmacology, enabling us to both efficiently develop effective therapeutics for complex diseases and combat drug resistance.

Bioinformatics and variability in drug response: a protein structural perspective

PubMed Central

Lahti, Jennifer L.; Tang, Grace W.; Capriotti, Emidio; Liu, Tianyun; Altman, Russ B.

2012-01-01

Marketed drugs frequently perform worse in clinical practice than in the clinical trials on which their approval is based. Many therapeutic compounds are ineffective for a large subpopulation of patients to whom they are prescribed; worse, a significant fraction of patients experience adverse effects more severe than anticipated. The unacceptable risk–benefit profile for many drugs mandates a paradigm shift towards personalized medicine. However, prior to adoption of patient-specific approaches, it is useful to understand the molecular details underlying variable drug response among diverse patient populations. Over the past decade, progress in structural genomics led to an explosion of available three-dimensional structures of drug target proteins while efforts in pharmacogenetics offered insights into polymorphisms correlated with differential therapeutic outcomes. Together these advances provide the opportunity to examine how altered protein structures arising from genetic differences affect protein–drug interactions and, ultimately, drug response. In this review, we first summarize structural characteristics of protein targets and common mechanisms of drug interactions. Next, we describe the impact of coding mutations on protein structures and drug response. Finally, we highlight tools for analysing protein structures and protein–drug interactions and discuss their application for understanding altered drug responses associated with protein structural variants. PMID:22552919

From Protein Structure to Small-Molecules: Recent Advances and Applications to Fragment-Based Drug Discovery.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2017-01-01

Fragment-based drug discovery (FBDD) is a broadly used strategy in structure-guided ligand design, whereby low-molecular weight hits move from lead-like to drug-like compounds. Over the past 15 years, an increasingly important role of the integration of these strategies into industrial and academic research platforms has been successfully established, allowing outstanding contributions to drug discovery. One important factor for the current prominence of FBDD is the better coverage of the chemical space provided by fragment-like libraries. The development of the field relies on two features: (i) the growing number of structurally characterized drug targets and (ii) the enormous chemical diversity available for experimental and virtual screenings. Indeed, fragment-based campaigns have contributed to address major challenges in lead optimization, such as the appropriate physicochemical profile of clinical candidates. This perspective paper outlines the usefulness and applications of FBDD approaches in medicinal chemistry and drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Endoperoxide antimalarials: development, structural diversity and pharmacodynamic aspects with reference to 1,2,4-trioxane-based structural scaffold

PubMed Central

Rudrapal, Mithun; Chetia, Dipak

2016-01-01

Malaria disease continues to be a major health problem worldwide due to the emergence of multidrug-resistant strains of Plasmodium falciparum. In recent days, artemisinin (ART)-based drugs and combination therapies remain the drugs of choice for resistant P. falciparum malaria. However, resistance to ART-based drugs has begun to appear in some parts of the world. Endoperoxide compounds (natural/semisynthetic/synthetic) representing a huge number of antimalarial agents possess a wide structural diversity with a desired antimalarial effectiveness against resistant P. falciparum malaria. The 1,2,4-trioxane ring system lacking the lactone ring that constitutes the most important endoperoxide structural scaffold is believed to be the key pharmacophoric moiety and is primarily responsible for the pharmacodynamic potential of endoperoxide-based antimalarials. Due to this reason, research into endoperoxide, particularly 1,2,4-trioxane-, 1,2,4-trioxolane- and 1,2,4,5-teraoxane-based scaffolds, has gained significant interest in recent years for developing antimalarial drugs against resistant malaria. In this paper, a comprehensive effort has been made to review the development of endoperoxide antimalarials from traditional antimalarial leads (natural/semisynthetic) and structural diversity of endoperoxide molecules derived from 1,2,4-trioxane-, 1,2,4-trioxolane- and 1,2,4,5-teraoxane-based structural scaffolds, including their chimeric (hybrid) molecules, which are newer and potent antimalarial agents. PMID:27843298

Learning the Structure of Biomedical Relationships from Unstructured Text

PubMed Central

Percha, Bethany; Altman, Russ B.

2015-01-01

The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured text of over 23 million articles. The creation of structured resources that catalog the relationships between drugs and genes would accelerate the translation of basic molecular knowledge into discoveries of genomic biomarkers for drug response and prediction of unexpected drug-drug interactions. Extracting these relationships from natural language sentences on such a large scale, however, requires text mining algorithms that can recognize when different-looking statements are expressing similar ideas. Here we describe a novel algorithm, Ensemble Biclustering for Classification (EBC), that learns the structure of biomedical relationships automatically from text, overcoming differences in word choice and sentence structure. We validate EBC's performance against manually-curated sets of (1) pharmacogenomic relationships from PharmGKB and (2) drug-target relationships from DrugBank, and use it to discover new drug-gene relationships for both knowledge bases. We then apply EBC to map the complete universe of drug-gene relationships based on their descriptions in Medline, revealing unexpected structure that challenges current notions about how these relationships are expressed in text. For instance, we learn that newer experimental findings are described in consistently different ways than established knowledge, and that seemingly pure classes of relationships can exhibit interesting chimeric structure. The EBC algorithm is flexible and adaptable to a wide range of problems in biomedical text mining. PMID:26219079

Structure-based drug design of RN486, a potent and selective Bruton's tyrosine kinase (BTK) inhibitor, for the treatment of rheumatoid arthritis.

PubMed

Lou, Yan; Han, Xiaochun; Kuglstatter, Andreas; Kondru, Rama K; Sweeney, Zachary K; Soth, Michael; McIntosh, Joel; Litman, Renee; Suh, Judy; Kocer, Buelent; Davis, Dana; Park, Jaehyeon; Frauchiger, Sandra; Dewdney, Nolan; Zecic, Hasim; Taygerly, Joshua P; Sarma, Keshab; Hong, Junbae; Hill, Ronald J; Gabriel, Tobias; Goldstein, David M; Owens, Timothy D

2015-01-08

Structure-based drug design was used to guide the optimization of a series of selective BTK inhibitors as potential treatments for Rheumatoid arthritis. Highlights include the introduction of a benzyl alcohol group and a fluorine substitution, each of which resulted in over 10-fold increase in activity. Concurrent optimization of drug-like properties led to compound 1 (RN486) ( J. Pharmacol. Exp. Ther. 2012 , 341 , 90 ), which was selected for advanced preclinical characterization based on its favorable properties.

Computer-Aided Drug Design Methods.

PubMed

Yu, Wenbo; MacKerell, Alexander D

2017-01-01

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

Anti-infectious drug repurposing using an integrated chemical genomics and structural systems biology approach.

PubMed

Ng, Clara; Hauptman, Ruth; Zhang, Yinliang; Bourne, Philip E; Xie, Lei

2014-01-01

The emergence of multi-drug and extensive drug resistance of microbes to antibiotics poses a great threat to human health. Although drug repurposing is a promising solution for accelerating the drug development process, its application to anti-infectious drug discovery is limited by the scope of existing phenotype-, ligand-, or target-based methods. In this paper we introduce a new computational strategy to determine the genome-wide molecular targets of bioactive compounds in both human and bacterial genomes. Our method is based on the use of a novel algorithm, ligand Enrichment of Network Topological Similarity (ligENTS), to map the chemical universe to its global pharmacological space. ligENTS outperforms the state-of-the-art algorithms in identifying novel drug-target relationships. Furthermore, we integrate ligENTS with our structural systems biology platform to identify drug repurposing opportunities via target similarity profiling. Using this integrated strategy, we have identified novel P. falciparum targets of drug-like active compounds from the Malaria Box, and suggest that a number of approved drugs may be active against malaria. This study demonstrates the potential of an integrative chemical genomics and structural systems biology approach to drug repurposing.

Crystal structures of ASK1-inhibtor complexes provide a platform for structure-based drug design

PubMed Central

Singh, Onkar; Shillings, Anthony; Craggs, Peter; Wall, Ian; Rowland, Paul; Skarzynski, Tadeusz; Hobbs, Clare I; Hardwick, Phil; Tanner, Rob; Blunt, Michelle; Witty, David R; Smith, Kathrine J

2013-01-01

ASK1, a member of the MAPK Kinase Kinase family of proteins has been shown to play a key role in cancer, neurodegeneration and cardiovascular diseases and is emerging as a possible drug target. Here we describe a ‘replacement-soaking’ method that has enabled the high-throughput X-ray structure determination of ASK1/ligand complexes. Comparison of the X-ray structures of five ASK1/ligand complexes from 3 different chemotypes illustrates that the ASK1 ATP binding site is able to accommodate a range of chemical diversity and different binding modes. The replacement-soaking system is also able to tolerate some protein flexibility. This crystal system provides a robust platform for ASK1/ligand structure determination and future structure based drug design. PMID:23776076

COMPUTER-AIDED DRUG DISCOVERY AND DEVELOPMENT (CADDD): in silico-chemico-biological approach

PubMed Central

Kapetanovic, I.M.

2008-01-01

It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415

Molecular Docking of Enzyme Inhibitors: A Computational Tool for Structure-Based Drug Design

ERIC Educational Resources Information Center

Rudnitskaya, Aleksandra; Torok, Bela; Torok, Marianna

2010-01-01

Molecular docking is a frequently used method in structure-based rational drug design. It is used for evaluating the complex formation of small ligands with large biomolecules, predicting the strength of the bonding forces and finding the best geometrical arrangements. The major goal of this advanced undergraduate biochemistry laboratory exercise…

Using the [beta][subscript 2]-Adrenoceptor for Structure-Based Drug Design

ERIC Educational Resources Information Center

Manallack, David T.; Chalmers, David K.; Yuriev, Elizabeth

2010-01-01

The topics of molecular modeling and drug design are studied in a medicinal chemistry course. The recently reported structures of several G protein-coupled receptors (GPCR) with bound ligands have been used to develop a simple computer-based experiment employing molecular-modeling software. Knowledge of the specific interactions between a ligand…

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus.

PubMed

Ekins, Sean; Freundlich, Joel S; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested. PMID:25653841

Sequence-dependent effects in drug-DNA interaction: the crystal structure of Hoechst 33258 bound to the d(CGCAAATTTGCG)2 duplex.

PubMed Central

Spink, N; Brown, D G; Skelly, J V; Neidle, S

1994-01-01

The bis-benzimidazole drug Hoechst 33258 has been co-crystallized with the dodecanucleotide sequence d(CGCAAATTTGCG)2. The structure has been solved by molecular replacement and refined to an R factor of 18.5% for 2125 reflections collected on a Xentronics area detector. The drug is bound in the minor groove, at the five base-pair site 5'-ATTTG and is in a unique orientation. This is displaced by one base pair in the 5' direction compared to previously-determined structures of this drug with the sequence d(CGCGAATTCGCG)2. Reasons for this difference in behaviour are discussed in terms of several sequence-dependent structural features of the DNA, with particular reference to differences in propeller twist and minor-groove width. Images PMID:7515488

Synthesis and structural characterization of some trisulfide analoges of thiouracil-based antithyroid drugs

NASA Astrophysics Data System (ADS)

Bhabak, Krishna P.; Bhowmick, Debasish

2012-08-01

Thiourea-based antithyroid drugs are effectively used for the treatment of hyperthyroidism. In this paper, we describe the synthesis of new trisulfides (11-12) from the commonly used thiourea-based antithyroid drugs such as 6-n-propyl-2-thiouracil (PTU) and 6-methyl-2-thiouracil (MTU) in the reaction with I2/KI system. Structural analysis by single crystal X-ray diffraction studies revealed the stabilization of trisulfides by a lactam-lactim tautomerism facilitating effective intramolecular as well as intermolecular non-covalent interactions. Although the structures of both trisulfides were found to be quite similar, a notable difference in the intermolecular interactions was observed between compounds 11 and 12 leading to different structural patterns. Structural stabilization of these trisulfides by tautomerism followed by intramolecular as well as intermolecular H-bonds makes these molecules as perfect examples in molecular recognition with self-complementary donor and acceptor units within a single molecule.

Non-amine-based dopamine transporter (reuptake) inhibitors retain properties of amine-based progenitors.

PubMed

Madras, Bertha K; Fahey, Michele A; Miller, Gregory M; De La Garza, Richard; Goulet, Martin; Spealman, Roger D; Meltzer, Peter C; George, Susan R; O'Dowd, Brian F; Bonab, Ali A; Livni, Eli; Fischman, Alan J

2003-10-31

Without exception, therapeutic and addictive drugs that produce their primary effects by blocking monoamine transporters in brain contain an amine nitrogen in their structure. This fundamental canon of drug design was based on a prevailing premise that an amine nitrogen is required to mimic the structures of monoamine neurotransmitters and other natural products. Non-amines, a novel class of compounds that contain no amine nitrogen, block monoamine transporters in the nM range and display markedly high selectivity for monoamine transporters, but not for receptors. Non-amines retain the spectrum of biochemical and pharmacological properties characteristic of amine-bearing counterparts. These novel drugs compel a revision of current concepts of drug-monoamine transporter complex formation and open avenues for discovery of a new generation of therapeutic drugs.

A machine-learned computational functional genomics-based approach to drug classification.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-12-01

The public accessibility of "big data" about the molecular targets of drugs and the biological functions of genes allows novel data science-based approaches to pharmacology that link drugs directly with their effects on pathophysiologic processes. This provides a phenotypic path to drug discovery and repurposing. This paper compares the performance of a functional genomics-based criterion to the traditional drug target-based classification. Knowledge discovery in the DrugBank and Gene Ontology databases allowed the construction of a "drug target versus biological process" matrix as a combination of "drug versus genes" and "genes versus biological processes" matrices. As a canonical example, such matrices were constructed for classical analgesic drugs. These matrices were projected onto a toroid grid of 50 × 82 artificial neurons using a self-organizing map (SOM). The distance, respectively, cluster structure of the high-dimensional feature space of the matrices was visualized on top of this SOM using a U-matrix. The cluster structure emerging on the U-matrix provided a correct classification of the analgesics into two main classes of opioid and non-opioid analgesics. The classification was flawless with both the functional genomics and the traditional target-based criterion. The functional genomics approach inherently included the drugs' modulatory effects on biological processes. The main pharmacological actions known from pharmacological science were captures, e.g., actions on lipid signaling for non-opioid analgesics that comprised many NSAIDs and actions on neuronal signal transmission for opioid analgesics. Using machine-learned techniques for computational drug classification in a comparative assessment, a functional genomics-based criterion was found to be similarly suitable for drug classification as the traditional target-based criterion. This supports a utility of functional genomics-based approaches to computational system pharmacology for drug discovery and repurposing.

Quantitative structure-activity relationship: promising advances in drug discovery platforms.

PubMed

Wang, Tao; Wu, Mian-Bin; Lin, Jian-Ping; Yang, Li-Rong

2015-12-01

Quantitative structure-activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced. In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization. QSAR should intentionally be used as a powerful tool for fragment-based drug design platforms in the field of drug discovery and design. Although there have been an increasing number of experimentally determined protein structures in recent years, a great number of protein structures cannot be easily obtained (i.e., membrane transport proteins and G-protein coupled receptors). Fragment-based drug discovery, such as QSAR, could be applied further and have a significant role in dealing with these problems. Moreover, along with the development of computer software and hardware, it is believed that QSAR will be increasingly important.

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Wei, Yu-Tuo; Pang, Zong-Wen; Du, Li-Qin; Chou, Kuo-Chen

2009-01-30

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. (c) 2008 Wiley Periodicals, Inc.

Controlled and extended drug release behavior of chitosan-based nanoparticle carrier.

PubMed

Yuan, Q; Shah, J; Hein, S; Misra, R D K

2010-03-01

Controlled drug release is presently gaining significant attention. In this regard, we describe here the synthesis (based on the understanding of chemical structure), structural morphology, swelling behavior and drug release response of chitosan intercalated in an expandable layered aluminosilicate. In contrast to pure chitosan, for which there is a continuous increase in drug release with time, the chitosan-aluminosilicate nanocomposite carrier was characterized by controlled and extended release. Drug release from the nanocomposite particle carrier occurred by degradation of the carrier to its individual components or nanostructures with a different composition. In both the layered aluminosilicate-based mineral and chitosan-aluminosilicate nanocomposite carriers the positively charged chemotherapeutic drug strongly bound to the negatively charged aluminosilicate and release of the drug was slow. Furthermore, the pattern of drug release from the chitosan-aluminosilicate nanocomposite carrier was affected by pH and the chitosan/aluminosilicate ratio. The study points to the potential application of this hybrid nanocomposite carrier in biomedical applications, including tissue engineering and controlled drug delivery. Copyright 2009 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Categorizing Drugs and Drug-Taking: A More Meaningful Approach.

ERIC Educational Resources Information Center

Gold, Robert S.; Duncan, David F.

This document reviews various definitions of the nature and classification of drugs. Difficulties with existing categorizations which use such bases as clinical utility, molecular structure, effects on the central nervous system, legality, and hazard potential are disucssed. A more meaningful categorization based on the availability and sources of…

Computational methods in drug discovery

PubMed Central

Leelananda, Sumudu P

2016-01-01

The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed. PMID:28144341

Computational methods in drug discovery.

PubMed

Leelananda, Sumudu P; Lindert, Steffen

2016-01-01

The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein-ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

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.

Structure-based drug design enables conversion of a DFG-in binding CSF-1R kinase inhibitor to a DFG-out binding mode

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

Meyers, Marvin J.; Pelc, Matthew; Kamtekar, Satwik

2010-08-11

The work described herein demonstrates the utility of structure-based drug design (SBDD) in shifting the binding mode of an HTS hit from a DFG-in to a DFG-out binding mode resulting in a class of novel potent CSF-1R kinase inhibitors suitable for lead development.

Application of 3D-QSAR in the rational design of receptor ligands and enzyme inhibitors.

PubMed

Mor, Marco; Rivara, Silvia; Lodola, Alessio; Lorenzi, Simone; Bordi, Fabrizio; Plazzi, Pier Vincenzo; Spadoni, Gilberto; Bedini, Annalida; Duranti, Andrea; Tontini, Andrea; Tarzia, Giorgio

2005-11-01

Quantitative structure-activity relationships (QSARs) are frequently employed in medicinal chemistry projects, both to rationalize structure-activity relationships (SAR) for known series of compounds and to help in the design of innovative structures endowed with desired pharmacological actions. As a difference from the so-called structure-based drug design tools, they do not require the knowledge of the biological target structure, but are based on the comparison of drug structural features, thus being defined ligand-based drug design tools. In the 3D-QSAR approach, structural descriptors are calculated from molecular models of the ligands, as interaction fields within a three-dimensional (3D) lattice of points surrounding the ligand structure. These descriptors are collected in a large X matrix, which is submitted to multivariate analysis to look for correlations with biological activity. Like for other QSARs, the reliability and usefulness of the correlation models depends on the validity of the assumptions and on the quality of the data. A careful selection of compounds and pharmacological data can improve the application of 3D-QSAR analysis in drug design. Some examples of the application of CoMFA and CoMSIA approaches to the SAR study and design of receptor or enzyme ligands is described, pointing the attention to the fields of melatonin receptor ligands and FAAH inhibitors.

A New Era for Cancer Target Therapies: Applying Systems Biology and Computer-Aided Drug Design to Cancer Therapies.

PubMed

Wong, Yung-Hao; Chiu, Chia-Chiun; Lin, Chih-Lung; Chen, Ting-Shou; Jheng, Bo-Ren; Lee, Yu-Ching; Chen, Jeremy; Chen, Bor-Sen

In recent years, many systems biology approaches have been used with various cancers. The materials described here can be used to build bases to discover novel cancer therapy targets in connection with computer-aided drug design (CADD). A deeper understanding of the mechanisms of cancer will provide more choices and correct strategies in the development of multiple target drug therapies, which is quite different from the traditional cancer single target therapy. Targeted therapy is one of the most powerful strategies against cancer and can also be applied to other diseases. Due to the large amount of progress in computer hardware and the theories of computational chemistry and physics, CADD has been the main strategy for developing novel drugs for cancer therapy. In contrast to traditional single target therapies, in this review we will emphasize the future direction of the field, i.e., multiple target therapies. Structure-based and ligand-based drug designs are the two main topics of CADD. The former needs both 3D protein structures and ligand structures, while the latter only needs ligand structures. Ordinarily it is estimated to take more than 14 years and 800 million dollars to develop a new drug. Many new CADD software programs and techniques have been developed in recent decades. We conclude with an example where we combined and applied systems biology and CADD to the core networks of four cancers and successfully developed a novel cocktail for drug therapy that treats multiple targets.

Software and resources for computational medicinal chemistry

PubMed Central

Liao, Chenzhong; Sitzmann, Markus; Pugliese, Angelo; Nicklaus, Marc C

2011-01-01

Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools. PMID:21707404

Structural investigation of chitosan-based microspheres with some anti-inflammatory drugs

NASA Astrophysics Data System (ADS)

Dreve, Simina; Kacso, Iren; Popa, Adriana; Raita, Oana; Dragan, Felicia; Bende, A.; Borodi, Gh.; Bratu, I.

2011-06-01

The use of chitosan as an excipient in oral formulations, as a drug delivery vehicle for ulcerogenic anti-inflammatory drugs and as base in polyelectrolyte complex systems, to prepare solid release systems as sponges was investigated. The preparation by double emulsification of chitosan hydrogels carrying diclofenac, acetyl-salycilic acid and hydrocortisone acetate as anti-inflammatory drugs is reported. The concentration of anti-inflammatory drug in the chitosan hydrogel generating the sponges was 0.08 mmol. Chitosan-drug loaded sponges with anti-inflammatory drugs were prepared by freeze-drying at -60 °C and 0.009 atm. Structural investigations of the solid formulations were done by Fourier-transformed infrared and ultraviolet-visible spectroscopy, spectrofluorimetry, differential scanning calorimetry and X-ray diffractometry. The results indicated that the drug molecules are forming temporary chelates in chitosan hydrogels and sponges. Electron paramagnetic resonance demonstrates the presence of free radicals in a wide range and the antioxidant activity for chitosan-drug supramolecular cross-linked assemblies.

Exploring the Role of Receptor Flexibility in Structure-Based Drug Discovery

PubMed Central

Feixas, Ferran; Lindert, Steffen; Sinko, William; McCammon, J. Andrew

2015-01-01

The proper understanding of biomolecular recognition mechanisms that take place in a drug target is of paramount importance to improve the efficiency of drug discovery and development. The intrinsic dynamic character of proteins has a strong influence on biomolecular recognition mechanisms and models such as conformational selection have been widely used to account for this dynamic association process. However, conformational changes occurring in the receptor prior and upon association with other molecules are diverse and not obvious to predict when only a few structures of the receptor are available. In view of the prominent role of protein flexibility in ligand binding and its implications for drug discovery, it is of great interest to identify receptor conformations that play a major role in biomolecular recognition before starting rational drug design efforts. In this review, we discuss a number of recent advances in computer-aided drug discovery techniques that have been proposed to incorporate receptor flexibility into structure-based drug design. The allowance for receptor flexibility provided by computational techniques such as molecular dynamics simulations or enhanced sampling techniques helps to improve the accuracy of methods used to estimate binding affinities and, thus, such methods can contribute to the discovery of novel drug leads. PMID:24332165

Advantages of Structure-Based Drug Design Approaches in Neurological Disorders

PubMed Central

Aarthy, Murali; Panwar, Umesh; Selvaraj, Chandrabose; Singh, Sanjeev Kumar

2017-01-01

Objective: The purpose of the review is to portray the theoretical concept on neurological disorders from research data. Background: The freak changes in chemical response of nerve impulse causes neurological disorders. The research evidence of the effort done in the older history suggests that the biological drug targets and their effective feature with responsive drugs could be valuable in promoting the future development of health statistics structure for improved treatment for curing the nervous disorders. Methods: In this review, we summarized the most iterative theoretical concept of structure based drug design approaches in various neurological disorders to unfathomable understanding of reported information for future drug design and development. Results: On the premise of reported information we analyzed the model of theoretical drug designing process for understanding the mechanism and pathology of the neurological diseases which covers the development of potentially effective inhibitors against the biological drug targets. Finally, it also suggests the management and implementation of the current treatment in improving the human health system behaviors. Conclusion: With the survey of reported information we concluded the development strategies of diagnosis and treatment against neurological diseases which leads to supportive progress in the drug discovery. PMID:28042767

Social and Structural Challenges to Drug Cessation Among Couples in Northern Mexico: Implications for Drug Treatment in Underserved Communities

PubMed Central

Bazzi, Angela Robertson; Syvertsen, Jennifer L.; Rolón, María Luisa; Martinez, Gustavo; Rangel, Gudelia; Vera, Alicia; Amaro, Hortensia; Ulibarri, Monica D.; Hernandez, Daniel O.; Strathdee, Steffanie A.

2015-01-01

Background Available drug treatment modalities may inadequately address social and structural contexts surrounding recovery efforts. Methods This mixed methods analysis drew on (1) surveys with female sex workers and their intimate male partners and (2) semi-structured interviews with a subsample of 41 couples (n = 82 individuals, 123 total interviews) in Northern Mexico. Descriptive and content analyses examined drug cessation and treatment experiences. Results Perceived need for drug treatment was high, yet only 35% had ever accessed services. Financial and institutional barriers (childcare needs, sex-segregated facilities) prevented partners from enrolling in residential programs together or simultaneously, leading to self-treatment attempts. Outpatient methadone was experienced more positively, yet financial constraints limited access and treatment duration. Relapse was common, particularly when one partner enrolled alone while the other continued using drugs. Conclusions Affordable, accessible, evidence-based drug treatment and recovery services that acknowledge social and structural contexts surrounding recovery are urgently needed for drug-involved couples. PMID:26470596

The future of crystallography in drug discovery

PubMed Central

Zheng, Heping; Hou, Jing; Zimmerman, Matthew D; Wlodawer, Alexander; Minor, Wladek

2014-01-01

Introduction X-ray crystallography plays an important role in structure-based drug design (SBDD), and accurate analysis of crystal structures of target macromolecules and macromolecule–ligand complexes is critical at all stages. However, whereas there has been significant progress in improving methods of structural biology, particularly in X-ray crystallography, corresponding progress in the development of computational methods (such as in silico high-throughput screening) is still on the horizon. Crystal structures can be overinterpreted and thus bias hypotheses and follow-up experiments. As in any experimental science, the models of macromolecular structures derived from X-ray diffraction data have their limitations, which need to be critically evaluated and well understood for structure-based drug discovery. Areas covered This review describes how the validity, accuracy and precision of a protein or nucleic acid structure determined by X-ray crystallography can be evaluated from three different perspectives: i) the nature of the diffraction experiment; ii) the interpretation of an electron density map; and iii) the interpretation of the structural model in terms of function and mechanism. The strategies to optimally exploit a macromolecular structure are also discussed in the context of ‘Big Data’ analysis, biochemical experimental design and structure-based drug discovery. Expert opinion Although X-ray crystallography is one of the most detailed ‘microscopes’ available today for examining macromolecular structures, the authors would like to re-emphasize that such structures are only simplified models of the target macromolecules. The authors also wish to reinforce the idea that a structure should not be thought of as a set of precise coordinates but rather as a framework for generating hypotheses to be explored. Numerous biochemical and biophysical experiments, including new diffraction experiments, can and should be performed to verify or falsify these hypotheses. X-ray crystallography will find its future application in drug discovery by the development of specific tools that would allow realistic interpretation of the outcome coordinates and/or support testing of these hypotheses. PMID:24372145

Structure-based drug design for G protein-coupled receptors.

PubMed

Congreve, Miles; Dias, João M; Marshall, Fiona H

2014-01-01

Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed. © 2014 Elsevier B.V. All rights reserved.

Conformational Transitions upon Ligand Binding: Holo-Structure Prediction from Apo Conformations

PubMed Central

Seeliger, Daniel; de Groot, Bert L.

2010-01-01

Biological function of proteins is frequently associated with the formation of complexes with small-molecule ligands. Experimental structure determination of such complexes at atomic resolution, however, can be time-consuming and costly. Computational methods for structure prediction of protein/ligand complexes, particularly docking, are as yet restricted by their limited consideration of receptor flexibility, rendering them not applicable for predicting protein/ligand complexes if large conformational changes of the receptor upon ligand binding are involved. Accurate receptor models in the ligand-bound state (holo structures), however, are a prerequisite for successful structure-based drug design. Hence, if only an unbound (apo) structure is available distinct from the ligand-bound conformation, structure-based drug design is severely limited. We present a method to predict the structure of protein/ligand complexes based solely on the apo structure, the ligand and the radius of gyration of the holo structure. The method is applied to ten cases in which proteins undergo structural rearrangements of up to 7.1 Å backbone RMSD upon ligand binding. In all cases, receptor models within 1.6 Å backbone RMSD to the target were predicted and close-to-native ligand binding poses were obtained for 8 of 10 cases in the top-ranked complex models. A protocol is presented that is expected to enable structure modeling of protein/ligand complexes and structure-based drug design for cases where crystal structures of ligand-bound conformations are not available. PMID:20066034

Strategies for the Optimization of Natural Leads to Anticancer Drugs or Drug Candidates

PubMed Central

Xiao, Zhiyan; Morris-Natschke, Susan L.; Lee, Kuo-Hsiung

2015-01-01

Natural products have made significant contribution to cancer chemotherapy over the past decades and remain an indispensable source of molecular and mechanistic diversity for anticancer drug discovery. More often than not, natural products may serve as leads for further drug development rather than as effective anticancer drugs by themselves. Generally, optimization of natural leads into anticancer drugs or drug candidates should not only address drug efficacy, but also improve ADMET profiles and chemical accessibility associated with the natural leads. Optimization strategies involve direct chemical manipulation of functional groups, structure-activity relationship-directed optimization and pharmacophore-oriented molecular design based on the natural templates. Both fundamental medicinal chemistry principles (e.g., bio-isosterism) and state-of-the-art computer-aided drug design techniques (e.g., structure-based design) can be applied to facilitate optimization efforts. In this review, the strategies to optimize natural leads to anticancer drugs or drug candidates are illustrated with examples and described according to their purposes. Furthermore, successful case studies on lead optimization of bioactive compounds performed in the Natural Products Research Laboratories at UNC are highlighted. PMID:26359649

Hierarchical virtual screening approaches in small molecule drug discovery.

PubMed

Kumar, Ashutosh; Zhang, Kam Y J

2015-01-01

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

Structural Factors Influencing Patterns of Drug Selling and Use and HIV Risk in the San Salvador Metropolitan Area

PubMed Central

Dickson-Gomez, Julia

2013-01-01

This article explores differences in the social context in which crack sales and use and HIV risk take place in seven low-income communities in San Salvador, and structural factors that may influence these differences. The organization of drug selling varied among the communities on a number of dimensions including: whether drug sales were open or closed systems; the type of drug-selling site; and the participation of drug users in drug-distribution roles. Drug-use sites also varied according to whether crack was used in private, semiprivate, or public spaces, and whether individuals used drugs alone or with other drug users. Three patterns of drug use and selling were identified based on the dimensions outlined above. Structural factors that influenced these patterns included the geographic location of the communities, their physical layout, gang involvement in drug sales, and police surveillance. Implications for HIV risk and prevention are explored for each pattern. PMID:20550091

Bridging quantum mechanics and structure-based drug design.

PubMed

De Vivo, Marco

2011-01-01

The last decade has seen great advances in the use of quantum mechanics (QM) to solve biological problems of pharmaceutical relevance. For instance, enzymatic catalysis is often investigated by means of the so-called QM/MM approach, which uses QM and molecular mechanics (MM) methods to determine the (free) energy landscape of the enzymatic reaction mechanism. Here, I will discuss a few representative examples of QM and QM/MM studies of important metalloenzymes of pharmaceutical interest (i.e. metallophosphatases and metallo-beta-lactamases). This review article aims to show how QM-based methods can be used to elucidate ligand-receptor interactions. The challenge is then to exploit this knowledge for the structure-based design of new and potent inhibitors, such as transition state (TS) analogues that resemble the structure and physicochemical properties of the enzymatic TS. Given the results and potential expressed to date by QM-based methods in studying biological problems, the application of QM in structure-based drug design will likely increase, making of these once-prohibitive computations a routinely used tool for drug design.

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

PubMed

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

A Structural Biology and Protein Engineering Approach to the Development of Antidotes against the Inhibition of Human Acetylcholinesterase by OP-based Nerve Agents

DTIC Science & Technology

2014-03-01

for Biotechnology, Gurgaon, India (Sep, 2013) by Joel L. Sussman, title: “Molecular Basis of How Nerve Agents through anti- Alzheimer Drugs Function...Molecular Basis of How Nerve Agents through anti- Alzheimer Drugs Function: 3D Structure of Acetylcholinesterase • Florida International University...FIU), Miami, FL (Dec 2013) - Invited Lecture by Joel L. Sussman, title: “Molecular Basis of anti- Alzheimer Drugs & Nerve Agents: 3D Structure of

Knowledge-Based Elastic Potentials for Docking Drugs or Proteins with Nucleic Acids

PubMed Central

Ge, Wei; Schneider, Bohdan; Olson, Wilma K.

2005-01-01

Elastic ellipsoidal functions defined by the observed hydration patterns around the DNA bases provide a new basis for measuring the recognition of ligands in the grooves of double-helical structures. Here a set of knowledge-based potentials suitable for quantitative description of such behavior is extracted from the observed positions of water molecules and amino acid atoms that form hydrogen bonds with the nitrogenous bases in high resolution crystal structures. Energies based on the displacement of hydrogen-bonding sites on drugs in DNA-crystal complexes relative to the preferred locations of water binding around the heterocyclic bases are low, pointing to the reliability of the potentials and the apparent displacement of water molecules by drug atoms in these structures. The validity of the energy functions has been further examined in a series of sequence substitution studies based on the structures of DNA bound to polyamides that have been designed to recognize the minor-groove edges of Watson-Crick basepairs. The higher energies of binding to incorrect sequences superimposed (without conformational adjustment or displacement of polyamide ligands) on observed high resolution structures confirm the hypothesis that the drug subunits associate with specific DNA bases. The knowledge-based functions also account satisfactorily for the measured free energies of DNA-polyamide association in solution and the observed sites of polyamide binding on nucleosomal DNA. The computations are generally consistent with mechanisms by which minor-groove binding ligands are thought to recognize DNA basepairs. The calculations suggest that the asymmetric distributions of hydrogen-bond-forming atoms on the minor-groove edge of the basepairs may underlie ligand discrimination of G·C from C·G pairs, in addition to the commonly believed role of steric hindrance. The analysis of polyamide-bound nucleosomal structures reveals other discrepancies in the expected chemical design, including unexpected contacts to DNA and modified basepair targets of some ligands. The ellipsoidal potentials thus appear promising as a mathematical tool for the study of drug- and protein-DNA interactions and for gaining new insights into DNA-binding mechanisms. PMID:15501936

Structured product labeling improves detection of drug-intolerance issues.

PubMed

Schadow, Gunther

2009-01-01

This study sought to assess the value of the Health Level 7/U.S. Food and Drug Administration Structured Product Labeling (SPL) drug knowledge representation standard and its associated terminology sources for drug-intolerance (allergy) decision support in computerized provider order entry (CPOE) systems. The Regenstrief Institute CPOE drug-intolerance issue detection system and its knowledge base was compared with a method based on existing SPL label content enriched with knowledge sources used with SPL (NDF-RT/MeSH). Both methods were applied to a large set of drug-intolerance (allergy) records, drug orders, and medication dispensing records covering >50,000 patients over 30 years. The number of drug-intolerance issues detected by both methods was counted, as well as the number of patients with issues, number of distinct drugs, and number of distinct intolerances. The difference between drug-intolerance issues detected or missed by either method was qualitatively analyzed. Although <70% of terms were mapped to SPL, the new approach detected four times as many drug-intolerance issues on twice as many patients. The SPL-based approach is more sensitive and suggests that mapping local dictionaries to SPL, and enhancing the depth and breadth of coverage of SPL content are worth accelerating. The study also highlights specificity problems known to trouble drug-intolerance decision support and suggests how terminology and methods of recording drug intolerances could be improved.

Structured Product Labeling Improves Detection of Drug-intolerance Issues

PubMed Central

Schadow, Gunther

2009-01-01

Objectives This study sought to assess the value of the Health Level 7/U.S. Food and Drug Administration Structured Product Labeling (SPL) drug knowledge representation standard and its associated terminology sources for drug-intolerance (allergy) decision support in computerized provider order entry (CPOE) systems. Design The Regenstrief Institute CPOE drug-intolerance issue detection system and its knowledge base was compared with a method based on existing SPL label content enriched with knowledge sources used with SPL (NDF-RT/MeSH). Both methods were applied to a large set of drug-intolerance (allergy) records, drug orders, and medication dispensing records covering >50,000 patients over 30 years. Measurements The number of drug-intolerance issues detected by both methods was counted, as well as the number of patients with issues, number of distinct drugs, and number of distinct intolerances. The difference between drug-intolerance issues detected or missed by either method was qualitatively analyzed. Results Although <70% of terms were mapped to SPL, the new approach detected four times as many drug-intolerance issues on twice as many patients. Conclusion The SPL-based approach is more sensitive and suggests that mapping local dictionaries to SPL, and enhancing the depth and breadth of coverage of SPL content are worth accelerating. The study also highlights specificity problems known to trouble drug-intolerance decision support and suggests how terminology and methods of recording drug intolerances could be improved. PMID:18952933

Characterizing protein domain associations by Small-molecule ligand binding

PubMed Central

Li, Qingliang; Cheng, Tiejun; Wang, Yanli; Bryant, Stephen H.

2012-01-01

Background Protein domains are evolutionarily conserved building blocks for protein structure and function, which are conventionally identified based on protein sequence or structure similarity. Small molecule binding domains are of great importance for the recognition of small molecules in biological systems and drug development. Many small molecules, including drugs, have been increasingly identified to bind to multiple targets, leading to promiscuous interactions with protein domains. Thus, a large scale characterization of the protein domains and their associations with respect to small-molecule binding is of particular interest to system biology research, drug target identification, as well as drug repurposing. Methods We compiled a collection of 13,822 physical interactions of small molecules and protein domains derived from the Protein Data Bank (PDB) structures. Based on the chemical similarity of these small molecules, we characterized pairwise associations of the protein domains and further investigated their global associations from a network point of view. Results We found that protein domains, despite lack of similarity in sequence and structure, were comprehensively associated through binding the same or similar small-molecule ligands. Moreover, we identified modules in the domain network that consisted of closely related protein domains by sharing similar biochemical mechanisms, being involved in relevant biological pathways, or being regulated by the same cognate cofactors. Conclusions A novel protein domain relationship was identified in the context of small-molecule binding, which is complementary to those identified by traditional sequence-based or structure-based approaches. The protein domain network constructed in the present study provides a novel perspective for chemogenomic study and network pharmacology, as well as target identification for drug repurposing. PMID:23745168

Creation of a Novel Class of Potent and Selective MutT Homologue 1 (MTH1) Inhibitors Using Fragment-Based Screening and Structure-Based Drug Design.

PubMed

Rahm, Fredrik; Viklund, Jenny; Trésaugues, Lionel; Ellermann, Manuel; Giese, Anja; Ericsson, Ulrika; Forsblom, Rickard; Ginman, Tobias; Günther, Judith; Hallberg, Kenth; Lindström, Johan; Persson, Lars Boukharta; Silvander, Camilla; Talagas, Antoine; Díaz-Sáez, Laura; Fedorov, Oleg; Huber, Kilian V M; Panagakou, Ioanna; Siejka, Paulina; Gorjánácz, Mátyás; Bauser, Marcus; Andersson, Martin

2018-03-22

Recent literature has both suggested and questioned MTH1 as a novel cancer target. BAY-707 was just published as a target validation small molecule probe for assessing the effects of pharmacological inhibition of MTH1 on tumor cell survival, both in vitro and in vivo. (1) In this report, we describe the medicinal chemistry program creating BAY-707, where fragment-based methods were used to develop a series of highly potent and selective MTH1 inhibitors. Using structure-based drug design and rational medicinal chemistry approaches, the potency was increased over 10,000 times from the fragment starting point while maintaining high ligand efficiency and drug-like properties.

INTEGRATING GENETIC AND STRUCTURAL DATA ON HUMAN PROTEIN KINOME IN NETWORK-BASED MODELING OF KINASE SENSITIVITIES AND RESISTANCE TO TARGETED AND PERSONALIZED ANTICANCER DRUGS.

PubMed

Verkhivker, Gennady M

2016-01-01

The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling complex relationships between robustness of targeted kinase genes and binding specificity of targeted kinase drugs. We discuss how these approaches can exploit advances in chemical biology and network science to develop novel strategies for rationally tailored and robust personalized drug therapies.

Calcium silicate-based drug delivery systems.

PubMed

Zhu, Ying-Jie; Guo, Xiao-Xuan; Sham, Tsun-Kong

2017-02-01

Compared with other inorganic materials such as silica, metal oxides, noble metals and carbon, calcium silicate-based materials, especially nanostructured calcium silicate materials, have high biocompatibility, bioactivity and biodegradability, high specific surface area, nanoporous/hollow structure, high drug-loading capacity, pH-responsive drug release behavior and desirable drug release properties, and thus they are promising for the application in drug delivery. Calcium silicate-based drug delivery systems have a long drug-release time, which can significantly prolong the therapeutic effect of drugs. Another advantage of calcium silicate-based drug delivery systems is their pH-responsive drug release property, which can act as an ideal platform for targeted drug delivery. Areas covered: In recent years, studies have been carried out on calcium silicate-based drug delivery systems, and important results and insights have been documented. This article is not intended to offer a comprehensive review on the research on calcium silicate-based drug delivery systems, but presents some examples reported in the literature, and includes new insights obtained by tracking the interactions between drug molecules and calcium silicate carriers on the molecular level using the synchrotron-based X-ray spectroscopy. Expert opinion: Finally, our opinions on calcium silicate-based drug delivery systems are provided, and several research directions for the future studies are proposed.

Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome

PubMed Central

Low, Yen S; Caster, Ola; Bergvall, Tomas; Fourches, Denis; Zang, Xiaoling; Norén, G Niklas; Rusyn, Ivan; Edwards, Ralph

2016-01-01

Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%–81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations. PMID:26499102

Drug Distribution. Part 1. Models to Predict Membrane Partitioning.

PubMed

Nagar, Swati; Korzekwa, Ken

2017-03-01

Tissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution. Two structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs. The resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs). Together these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.

TaxKB: a knowledge base for new taxane-related drug discovery.

PubMed

Murugan, Kasi; Shanmugasamy, Sangeetha; Al-Sohaibani, Saleh; Vignesh, Naga; Palanikannan, Kandavel; Vimala, Antonydhason; Kumar, Gopal Ramesh

2015-01-01

Taxanes are naturally occurring compounds which belong to a powerful group of chemotherapeutic drugs with anticancer properties. Their current use, clinical efficacy, and unique mechanism of action indicate their potentiality for cancer drug discovery and development thereby promising to reduce the high economy associated with cancer worldwide. Extensive research has been carried out on taxanes with the aim to combat issues of drug resistance, side effects, limited natural supply, and also to increase the therapeutic index of these molecules. These efforts have led to the isolation of many naturally occurring compounds belonging to this family (more than 350 different kinds), and the synthesis of semisynthetic analogs of the naturally existing molecules (>500), and has also led to the characterization of many (>1000) of them. A web-based database system on clinically exploitable taxanes, providing a link between the structure and the pharmacological property of these molecules could help to reduce the druggability gap for these molecules. Taxane knowledge base (TaxKB, http://bioinfo.au-kbc.org.in/taxane/Taxkb/), is an online multi-tier relational database that currently holds data on 42 parameters of 250 natural and 503 semisynthetic analogs of taxanes. This database provides researchers with much-needed information necessary for drug development. TaxKB enables the user to search data on the structure, drug-likeness, and physicochemical properties of both natural and synthetic taxanes with a "General Search" option in addition to a "Parameter Specific Search." It displays 2D structure and allows the user to download the 3D structure (a PDB file) of taxanes that can be viewed with any molecular visualization tool. The ultimate aim of TaxKB is to provide information on Absorption, Distribution, Metabolism, and Excretion/Toxicity (ADME/T) as well as data on bioavailability and target interaction properties of candidate anticancer taxanes, ahead of expensive clinical trials. This first web-based single-information portal will play a central role and help researchers to move forward in taxane-based cancer drug research.

Supramolecular Drug Delivery Systems Based on Water-Soluble Pillar[n]arenes.

PubMed

Wu, Xuan; Gao, Lei; Hu, Xiao-Yu; Wang, Leyong

2016-06-01

Supramolecular drug delivery systems (SDDSs), including various kinds of nanostructures that are assembled by reversible noncovalent interactions, have attracted considerable attention as ideal drug carriers owing to their fascinating ability to undergo dynamic switching of structure, morphology, and function in response to various external stimuli, which provides a flexible and robust platform for designing and developing functional and smart supramolecular nano-drug carriers. Pillar[n]arenes represent a new generation of macrocyclic hosts, which have unique structures and excellent properties in host-guest chemistry. This account describes recent progress in our group to develop pillararene-based stimuli-responsive supramolecular nanostructures constructed by reversible host-guest interactions for controllable anticancer drug delivery. The potential applications of these supramolecular drug carriers in cancer treatment and the fundamental questions facing SDDSs are also discussed. © 2016 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative self-assembly prediction yields targeted nanomedicines

NASA Astrophysics Data System (ADS)

Shamay, Yosi; Shah, Janki; Işık, Mehtap; Mizrachi, Aviram; Leibold, Josef; Tschaharganeh, Darjus F.; Roxbury, Daniel; Budhathoki-Uprety, Januka; Nawaly, Karla; Sugarman, James L.; Baut, Emily; Neiman, Michelle R.; Dacek, Megan; Ganesh, Kripa S.; Johnson, Darren C.; Sridharan, Ramya; Chu, Karen L.; Rajasekhar, Vinagolu K.; Lowe, Scott W.; Chodera, John D.; Heller, Daniel A.

2018-02-01

Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

Computer-aided drug design for AMP-activated protein kinase activators.

PubMed

Wang, Zhanli; Huo, Jianxin; Sun, Lidan; Wang, Yongfu; Jin, Hongwei; Yu, Hui; Zhang, Liangren; Zhou, Lishe

2011-09-01

AMP-activated protein kinase (AMPK) is an important therapeutic target for the potential treatment of metabolic disorders, cardiovascular disease and cancer. Recently, various classes of compounds that activate AMPK by direct or indirect interactions have been reported. The importance of computer-aided drug design approaches in the search for potent activators of AMPK is now established, including structure-based design, ligand-based design, fragment-based design, as well as structural analysis. This review article highlights the computer-aided drug design approaches utilized to discover of activators targeting AMPK. The principles, advantages or limitation of the different methods are also being discussed together with examples of applications taken from the literatures.

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery.

PubMed

Heifetz, Alexander; Southey, Michelle; Morao, Inaki; Townsend-Nicholson, Andrea; Bodkin, Mike J

2018-01-01

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

Using in Vitro Evolution and Whole Genome Analysis To Discover Next Generation Targets for Antimalarial Drug Discovery

PubMed Central

2018-01-01

Although many new anti-infectives have been discovered and developed solely using phenotypic cellular screening and assay optimization, most researchers recognize that structure-guided drug design is more practical and less costly. In addition, a greater chemical space can be interrogated with structure-guided drug design. The practicality of structure-guided drug design has launched a search for the targets of compounds discovered in phenotypic screens. One method that has been used extensively in malaria parasites for target discovery and chemical validation is in vitro evolution and whole genome analysis (IVIEWGA). Here, small molecules from phenotypic screens with demonstrated antiparasitic activity are used in genome-based target discovery methods. In this Review, we discuss the newest, most promising druggable targets discovered or further validated by evolution-based methods, as well as some exceptions. PMID:29451780

Structural stigma and sexual orientation disparities in adolescent drug use.

PubMed

Hatzenbuehler, Mark L; Jun, Hee-Jin; Corliss, Heather L; Bryn Austin, S

2015-07-01

Although epidemiologic studies have established the existence of large sexual orientation disparities in illicit drug use among adolescents and young adults, the determinants of these disparities remain understudied. This study sought to determine whether sexual orientation disparities in illicit drug use are potentiated in states that are characterized by high levels of stigma surrounding sexual minorities. State-level structural stigma was coded using a previously established measure based on a 4-item composite index: (1) density of same-sex couples; (2) proportion of Gay-Straight Alliances per public high school; (3) 5 policies related to sexual orientation discrimination (e.g., same-sex marriage, employment non-discrimination); and (4) public opinion toward homosexuality (aggregated responses from 41 national polls). The index was linked to individual-level data from the Growing Up Today Study, a prospective community-based study of adolescents (2001-2010). Sexual minorities report greater illicit drug use than their heterosexual peers. However, for both men and women, there were statistically significant interactions between sexual orientation status and structural stigma, such that sexual orientation disparities in marijuana and illicit drug use were more pronounced in high-structural stigma states than in low-structural stigma states, controlling for individual- and state-level confounders. For instance, among men, the risk ratio indicating the association between sexual orientation and marijuana use was 24% greater in high- versus low-structural stigma states, and for women it was 28% greater in high- versus low-structural stigma states. Stigma in the form of social policies and attitudes may contribute to sexual orientation disparities in illicit drug use. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Significance of G Protein-Coupled Receptor Crystallography for Drug Discovery

PubMed Central

Salon, John A.; Lodowski, David T.

2011-01-01

Crucial as molecular sensors for many vital physiological processes, seven-transmembrane domain G protein-coupled receptors (GPCRs) comprise the largest family of proteins targeted by drug discovery. Together with structures of the prototypical GPCR rhodopsin, solved structures of other liganded GPCRs promise to provide insights into the structural basis of the superfamily's biochemical functions and assist in the development of new therapeutic modalities and drugs. One of the greatest technical and theoretical challenges to elucidating and exploiting structure-function relationships in these systems is the emerging concept of GPCR conformational flexibility and its cause-effect relationship for receptor-receptor and receptor-effector interactions. Such conformational changes can be subtle and triggered by relatively small binding energy effects, leading to full or partial efficacy in the activation or inactivation of the receptor system at large. Pharmacological dogma generally dictates that these changes manifest themselves through kinetic modulation of the receptor's G protein partners. Atomic resolution information derived from increasingly available receptor structures provides an entrée to the understanding of these events and practically applying it to drug design. Supported by structure-activity relationship information arising from empirical screening, a unified structural model of GPCR activation/inactivation promises to both accelerate drug discovery in this field and improve our fundamental understanding of structure-based drug design in general. This review discusses fundamental problems that persist in drug design and GPCR structural determination. PMID:21969326

Fragment-based approaches to anti-HIV drug discovery: state of the art and future opportunities.

PubMed

Huang, Boshi; Kang, Dongwei; Zhan, Peng; Liu, Xinyong

2015-12-01

The search for additional drugs to treat HIV infection is a continuing effort due to the emergence and spread of HIV strains resistant to nearly all current drugs. The recent literature reveals that fragment-based drug design/discovery (FBDD) has become an effective alternative to conventional high-throughput screening strategies for drug discovery. In this critical review, the authors describe the state of the art in FBDD strategies for the discovery of anti-HIV drug-like compounds. The article focuses on fragment screening techniques, direct fragment-based design and early hit-to-lead progress. Rapid progress in biophysical detection and in silico techniques has greatly aided the application of FBDD to discover candidate agents directed at a variety of anti-HIV targets. Growing evidence suggests that structural insights on key proteins in the HIV life cycle can be applied in the early phase of drug discovery campaigns, providing valuable information on the binding modes and efficiently prompting fragment hit-to-lead progression. The combination of structural insights with improved methodologies for FBDD, including the privileged fragment-based reconstruction approach, fragment hybridization based on crystallographic overlays, fragment growth exploiting dynamic combinatorial chemistry, and high-speed fragment assembly via diversity-oriented synthesis followed by in situ screening, offers the possibility of more efficient and rapid discovery of novel drugs for HIV-1 prevention or treatment. Though the use of FBDD in anti-HIV drug discovery is still in its infancy, it is anticipated that anti-HIV agents developed via fragment-based strategies will be introduced into the clinic in the future.

Polymeric hydrogels for novel contact lens-based ophthalmic drug delivery systems: a review.

PubMed

Xinming, Li; Yingde, Cui; Lloyd, Andrew W; Mikhalovsky, Sergey V; Sandeman, Susan R; Howel, Carol A; Liewen, Liao

2008-04-01

Only about 5% of drugs administrated by eye drops are bioavailable, and currently eye drops account for more than 90% of all ophthalmic formulations. The bioavailability of ophthalmic drugs can be improved by a soft contact lens-based ophthalmic drug delivery system. Several polymeric hydrogels have been investigated for soft contact lens-based ophthalmic drug delivery systems: (i) polymeric hydrogels for conventional contact lens to absorb and release ophthalmic drugs; (ii) polymeric hydrogels for piggyback contact lens combining with a drug plate or drug solution; (iii) surface-modified polymeric hydrogels to immobilize drugs on the surface of contact lenses; (iv) polymeric hydrogels for inclusion of drugs in a colloidal structure dispersed in the lens; (v) ion ligand-containing polymeric hydrogels; (vi) molecularly imprinted polymeric hydrogels which provide the contact lens with a high affinity and selectivity for a given drug. Polymeric hydrogels for these contact lens-based ophthalmic drug delivery systems, their advantages and drawbacks are critically analyzed in this review.

Return to drug use and overdose after release from prison: a qualitative study of risk and protective factors.

PubMed

Binswanger, Ingrid A; Nowels, Carolyn; Corsi, Karen F; Glanz, Jason; Long, Jeremy; Booth, Robert E; Steiner, John F

2012-01-01

Former inmates are at high risk for death from drug overdose, especially in the immediate post-release period. The purpose of the study is to understand the drug use experiences, perceptions of overdose risk, and experiences with overdose among former prisoners. This qualitative study included former prison inmates (N=29) who were recruited within two months after their release. Interviewers conducted in-person, semi-structured interviews which explored participants' experiences and perceptions. Transcripts were analyzed utilizing a team-based method of inductive analysis. The following themes emerged: 1) Relapse to drugs and alcohol occurred in a context of poor social support, medical co-morbidity and inadequate economic resources; 2) former inmates experienced ubiquitous exposure to drugs in their living environments; 3) intentional overdose was considered "a way out" given situational stressors, and accidental overdose was perceived as related to decreased tolerance; and 4) protective factors included structured drug treatment programs, spirituality/religion, community-based resources (including self-help groups), and family. Former inmates return to environments that strongly trigger relapse to drug use and put them at risk for overdose. Interventions to prevent overdose after release from prison may benefit from including structured treatment with gradual transition to the community, enhanced protective factors, and reductions of environmental triggers to use drugs.

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

PubMed Central

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

2010-01-01

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

Combining functional and structural genomics to sample the essential Burkholderia structome.

PubMed

Baugh, Loren; Gallagher, Larry A; Patrapuvich, Rapatbhorn; Clifton, Matthew C; Gardberg, Anna S; Edwards, Thomas E; Armour, Brianna; Begley, Darren W; Dieterich, Shellie H; Dranow, David M; Abendroth, Jan; Fairman, James W; Fox, David; Staker, Bart L; Phan, Isabelle; Gillespie, Angela; Choi, Ryan; Nakazawa-Hewitt, Steve; Nguyen, Mary Trang; Napuli, Alberto; Barrett, Lynn; Buchko, Garry W; Stacy, Robin; Myler, Peter J; Stewart, Lance J; Manoil, Colin; Van Voorhis, Wesley C

2013-01-01

The genus Burkholderia includes pathogenic gram-negative bacteria that cause melioidosis, glanders, and pulmonary infections of patients with cancer and cystic fibrosis. Drug resistance has made development of new antimicrobials critical. Many approaches to discovering new antimicrobials, such as structure-based drug design and whole cell phenotypic screens followed by lead refinement, require high-resolution structures of proteins essential to the parasite. We experimentally identified 406 putative essential genes in B. thailandensis, a low-virulence species phylogenetically similar to B. pseudomallei, the causative agent of melioidosis, using saturation-level transposon mutagenesis and next-generation sequencing (Tn-seq). We selected 315 protein products of these genes based on structure-determination criteria, such as excluding very large and/or integral membrane proteins, and entered them into the Seattle Structural Genomics Center for Infection Disease (SSGCID) structure determination pipeline. To maximize structural coverage of these targets, we applied an "ortholog rescue" strategy for those producing insoluble or difficult to crystallize proteins, resulting in the addition of 387 orthologs (or paralogs) from seven other Burkholderia species into the SSGCID pipeline. This structural genomics approach yielded structures from 31 putative essential targets from B. thailandensis, and 25 orthologs from other Burkholderia species, yielding an overall structural coverage for 49 of the 406 essential gene families, with a total of 88 depositions into the Protein Data Bank. Of these, 25 proteins have properties of a potential antimicrobial drug target i.e., no close human homolog, part of an essential metabolic pathway, and a deep binding pocket. We describe the structures of several potential drug targets in detail. This collection of structures, solubility and experimental essentiality data provides a resource for development of drugs against infections and diseases caused by Burkholderia. All expression clones and proteins created in this study are freely available by request.

Protein crystallography and infectious diseases.

PubMed Central

Verlinde, C. L.; Merritt, E. A.; Van den Akker, F.; Kim, H.; Feil, I.; Delboni, L. F.; Mande, S. C.; Sarfaty, S.; Petra, P. H.; Hol, W. G.

1994-01-01

The current rapid growth in the number of known 3-dimensional protein structures is producing a database of structures that is increasingly useful as a starting point for the development of new medically relevant molecules such as drugs, therapeutic proteins, and vaccines. This development is beautifully illustrated in the recent book, Protein structure: New approaches to disease and therapy (Perutz, 1992). There is a great and growing promise for the design of molecules for the treatment or prevention of a wide variety of diseases, an endeavor made possible by the insights derived from the structure and function of crucial proteins from pathogenic organisms and from man. We present here 2 illustrations of structure-based drug design. The first is the prospect of developing antitrypanosomal drugs based on crystallographic, ligand-binding, and molecular modeling studies of glycolytic glycosomal enzymes from Trypanosomatidae. These unicellular organisms are responsible for several tropical diseases, including African and American trypanosomiases, as well as various forms of leishmaniasis. Because the target enzymes are also present in the human host, this project is a pioneering study in selective design. The second illustrative case is the prospect of designing anti-cholera drugs based on detailed analysis of the structure of cholera toxin and the closely related Escherichia coli heat-labile enterotoxin. Such potential drugs can be targeted either at inhibiting the toxin's receptor binding site or at blocking the toxin's intracellular catalytic activity. Study of the Vibrio cholerae and E. coli toxins serves at the same time as an example of a general approach to structure-based vaccine design. These toxins exhibit a remarkable ability to stimulate the mucosal immune system, and early results have suggested that this property can be maintained by engineered fusion proteins based on the native toxin structure. The challenge is thus to incorporate selected epitopes from foreign pathogens into the native framework of the toxin such that crucial features of both the epitope and the toxin are maintained. That is, the modified toxin must continue to evoke a strong mucosal immune response, and this response must be directed against an epitope conformation characteristic of the original pathogen. PMID:7849584

Structure-based discovery of selective serotonin 5-HT(1B) receptor ligands.

PubMed

Rodríguez, David; Brea, José; Loza, María Isabel; Carlsson, Jens

2014-08-05

The development of safe and effective drugs relies on the discovery of selective ligands. Serotonin (5-hydroxytryptamine [5-HT]) G protein-coupled receptors are therapeutic targets for CNS disorders but are also associated with adverse drug effects. The determination of crystal structures for the 5-HT1B and 5-HT2B receptors provided an opportunity to identify subtype selective ligands using structure-based methods. From docking screens of 1.3 million compounds, 22 molecules were predicted to be selective for the 5-HT1B receptor over the 5-HT2B subtype, a requirement for safe serotonergic drugs. Nine compounds were experimentally verified as 5-HT1B-selective ligands, with up to 300-fold higher affinities for this subtype. Three of the ligands were agonists of the G protein pathway. Analysis of state-of-the-art homology models of the two 5-HT receptors revealed that the crystal structures were critical for predicting selective ligands. Our results demonstrate that structure-based screening can guide the discovery of ligands with specific selectivity profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data

PubMed Central

Wang, Yongcui; Chen, Shilong; Deng, Naiyang; Wang, Yong

2013-01-01

Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems. PMID:24244318

Computational predictive models for P-glycoprotein inhibition of in-house chalcone derivatives and drug-bank compounds.

PubMed

Ngo, Trieu-Du; Tran, Thanh-Dao; Le, Minh-Tri; Thai, Khac-Minh

2016-11-01

The human P-glycoprotein (P-gp) efflux pump is of great interest for medicinal chemists because of its important role in multidrug resistance (MDR). Because of the high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of this transmembrane protein, ligand-based, and structure-based approaches which were machine learning, homology modeling, and molecular docking were combined for this study. In ligand-based approach, individual two-dimensional quantitative structure-activity relationship models were developed using different machine learning algorithms and subsequently combined into the Ensemble model which showed good performance on both the diverse training set and the validation sets. The applicability domain and the prediction quality of the developed models were also judged using the state-of-the-art methods and tools. In our structure-based approach, the P-gp structure and its binding region were predicted for a docking study to determine possible interactions between the ligands and the receptor. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening using prediction models and molecular docking in an attempt to restore cancer cell sensitivity to cytotoxic drugs.

Interaction of cardiac troponin with cardiotonic drugs: a structural perspective.

PubMed

Li, Monica X; Robertson, Ian M; Sykes, Brian D

2008-04-25

Over the 40 years since its discovery, many studies have focused on understanding the role of troponin as a myofilament based molecular switch in regulating the Ca(2+)-dependent activation of striated muscle contraction. Recently, studies have explored the role of cardiac troponin as a target for cardiotonic agents. These drugs are clinically useful for treating heart failure, a condition in which the heart is no longer able to pump enough blood to other organs. These agents act via a mechanism that modulates the Ca(2+)-sensitivity of troponin; such a mode of action is therapeutically desirable because intracellular Ca(2+) concentration is not perturbed, preserving the regulation of other Ca(2+)-based signaling pathways. This review describes molecular details of the interaction of cardiac troponin with a variety of cardiotonic drugs. We present recent structural work that has identified the docking sites of several cardiotonic drugs in the troponin C-troponin I interface and discuss their relevance in the design of troponin based drugs for the treatment of heart disease.

Structural Biology and the Design of New Therapeutics: From HIV and Cancer to Mycobacterial Infections: A Paper Dedicated to John Kendrew.

PubMed

Thomas, Sherine E; Mendes, Vitor; Kim, So Yeon; Malhotra, Sony; Ochoa-Montaño, Bernardo; Blaszczyk, Michal; Blundell, Tom L

2017-08-18

Interest in applications of protein crystallography to medicine was evident, as the first high-resolution structures emerged in the 50s and 60s. In Cambridge, Max Perutz and John Kendrew sought to understand mutations in sickle cell and other genetic diseases related to hemoglobin, while in Oxford, the group of Dorothy Hodgkin became interested in long-lasting zinc-insulin crystals for treatment of diabetes and later considered insulin redesign, as synthetic insulins became possible. The use of protein crystallography in structure-guided drug discovery emerged as enzyme structures allowed the identification of potential inhibitor-binding sites and optimization of interactions of hits using the structure of the target protein. Early examples of this approach were the use of the structure of renin to design antihypertensives and the structure of HIV protease in design of AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design and has been used to progress three oncology drugs through clinical trials to FDA approval. We exemplify current developments in structure-guided target identification and fragment-based lead discovery with efforts to develop new antimicrobials for mycobacterial infections. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation

PubMed Central

Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio

2012-01-01

Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurological, psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homology models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with molecular dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in molecular docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calculation. Robust correlation of computed and experimental Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands. PMID:22970199

Advances in Mycobacterium tuberculosis therapeutics discovery utlizing structural biology

PubMed Central

Chim, Nicholas; Owens, Cedric P.; Contreras, Heidi; Goulding, Celia W.

2013-01-01

In 2012, tuberculosis (TB) remains a global health threat and is exacerbated both by the emergence of drug resistant Mycobacterium tuberculosis strains and its synergy with HIV infection. The waning effectiveness of current treatment regimens necessitates the development of new or repurposed anti-TB therapeutics for improved combination therapies against the disease. Exploiting atomic resolution structural information of proteins in complex with their substrates and/or inhibitors can facilitate structure-based rational drug design. Since our last review in 2009, there has been a wealth of new M. tuberculosis protein structural information. Once again, we have compiled the most promising structures with regards to potential anti-TB drug development and present them in this updated review. PMID:23167715

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing

PubMed Central

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A.; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space. PMID:29545755

Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing.

PubMed

de Anda-Jáuregui, Guillermo; Guo, Kai; McGregor, Brett A; Hur, Junguk

2018-01-01

The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space.

Structure and ligand-based design of P-glycoprotein inhibitors: a historical perspective.

PubMed

Palmeira, Andreia; Sousa, Emilia; Vasconcelos, M Helena; Pinto, Madalena; Fernandes, Miguel X

2012-01-01

Computer-assisted drug design (CADD) is a valuable approach for the discovery of new chemical entities in the field of cancer therapy. There is a pressing need to design and develop new, selective, and safe drugs for the treatment of multidrug resistance (MDR) cancer forms, specifically active against P-glycoprotein (P-gp). Recently, a crystallographic structure for mouse P-gp was obtained. However, for decades the design of new P-gp inhibitors employed mainly ligand-based approaches (SAR, QSAR, 3D-QSAR and pharmacophore studies), and structure-based studies used P-gp homology models. However, some of those results are still the pillars used as a starting point for the design of potential P-gp inhibitors. Here, pharmacophore mapping, (Q)SAR, 3D-QSAR and homology modeling, for the discovery of P-gp inhibitors are reviewed. The importance of these methods for understanding mechanisms of drug resistance at a molecular level, and design P-gp inhibitors drug candidates are discussed. The examples mentioned in the review could provide insights into the wide range of possibilities of using CADD methodologies for the discovery of efficient P-gp inhibitors.

Effects of HIV-1 protease on cellular functions and their potential applications in antiretroviral therapy

PubMed Central

2012-01-01

Human Immunodeficiency Virus Type 1 (HIV-1) protease inhibitors (PIs) are the most potent class of drugs in antiretroviral therapies. However, viral drug resistance to PIs could emerge rapidly thus reducing the effectiveness of those drugs. Of note, all current FDA-approved PIs are competitive inhibitors, i.e., inhibitors that compete with substrates for the active enzymatic site. This common inhibitory approach increases the likelihood of developing drug resistant HIV-1 strains that are resistant to many or all current PIs. Hence, new PIs that move away from the current target of the active enzymatic site are needed. Specifically, allosteric inhibitors, inhibitors that prohibit PR enzymatic activities through non-competitive binding to PR, should be sought. Another common feature of current PIs is they were all developed based on the structure-based design. Drugs derived from a structure-based strategy may generate target specific and potent inhibitors. However, this type of drug design can only target one site at a time and drugs discovered by this method are often associated with strong side effects such as cellular toxicity, limiting its number of target choices, efficacy, and applicability. In contrast, a cell-based system may provide a useful alternative strategy that can overcome many of the inherited shortcomings associated with structure-based drug designs. For example, allosteric PIs can be sought using a cell-based system without considering the site or mechanism of inhibition. In addition, a cell-based system can eliminate those PIs that have strong cytotoxic effect. Most importantly, a simple, economical, and easy-to-maintained eukaryotic cellular system such as yeast will allow us to search for potential PIs in a large-scaled high throughput screening (HTS) system, thus increasing the chances of success. Based on our many years of experience in using fission yeast as a model system to study HIV-1 Vpr, we propose the use of fission yeast as a possible surrogate system to study the effects of HIV-1 protease on cellular functions and to explore its utility as a HTS system to search for new PIs to battle HIV-1 resistant strains. PMID:22971934

Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing

PubMed Central

2013-01-01

Background A large-scale, highly accurate, machine-understandable drug-disease treatment relationship knowledge base is important for computational approaches to drug repurposing. The large body of published biomedical research articles and clinical case reports available on MEDLINE is a rich source of FDA-approved drug-disease indication as well as drug-repurposing knowledge that is crucial for applying FDA-approved drugs for new diseases. However, much of this information is buried in free text and not captured in any existing databases. The goal of this study is to extract a large number of accurate drug-disease treatment pairs from published literature. Results In this study, we developed a simple but highly accurate pattern-learning approach to extract treatment-specific drug-disease pairs from 20 million biomedical abstracts available on MEDLINE. We extracted a total of 34,305 unique drug-disease treatment pairs, the majority of which are not included in existing structured databases. Our algorithm achieved a precision of 0.904 and a recall of 0.131 in extracting all pairs, and a precision of 0.904 and a recall of 0.842 in extracting frequent pairs. In addition, we have shown that the extracted pairs strongly correlate with both drug target genes and therapeutic classes, therefore may have high potential in drug discovery. Conclusions We demonstrated that our simple pattern-learning relationship extraction algorithm is able to accurately extract many drug-disease pairs from the free text of biomedical literature that are not captured in structured databases. The large-scale, accurate, machine-understandable drug-disease treatment knowledge base that is resultant of our study, in combination with pairs from structured databases, will have high potential in computational drug repurposing tasks. PMID:23742147

Chemical Proteomics and Structural Biology Define EPHA2 Inhibition by Clinical Kinase Drugs.

PubMed

Heinzlmeir, Stephanie; Kudlinzki, Denis; Sreeramulu, Sridhar; Klaeger, Susan; Gande, Santosh Lakshmi; Linhard, Verena; Wilhelm, Mathias; Qiao, Huichao; Helm, Dominic; Ruprecht, Benjamin; Saxena, Krishna; Médard, Guillaume; Schwalbe, Harald; Kuster, Bernhard

2016-12-16

The receptor tyrosine kinase EPHA2 (Ephrin type-A receptor 2) plays important roles in oncogenesis, metastasis, and treatment resistance, yet therapeutic targeting, drug discovery, or investigation of EPHA2 biology is hampered by the lack of appropriate inhibitors and structural information. Here, we used chemical proteomics to survey 235 clinical kinase inhibitors for their kinase selectivity and identified 24 drugs with submicromolar affinities for EPHA2. NMR-based conformational dynamics together with nine new cocrystal structures delineated drug-EPHA2 interactions in full detail. The combination of selectivity profiling, structure determination, and kinome wide sequence alignment allowed the development of a classification system in which amino acids in the drug binding site of EPHA2 are categorized into key, scaffold, potency, and selectivity residues. This scheme should be generally applicable in kinase drug discovery, and we anticipate that the provided information will greatly facilitate the development of selective EPHA2 inhibitors in particular and the repurposing of clinical kinase inhibitors in general.

Functionalization of protein-based nanocages for drug delivery applications.

PubMed

Schoonen, Lise; van Hest, Jan C M

2014-07-07

Traditional drug delivery strategies involve drugs which are not targeted towards the desired tissue. This can lead to undesired side effects, as normal cells are affected by the drugs as well. Therefore, new systems are now being developed which combine targeting functionalities with encapsulation of drug cargo. Protein nanocages are highly promising drug delivery platforms due to their perfectly defined structures, biocompatibility, biodegradability and low toxicity. A variety of protein nanocages have been modified and functionalized for these types of applications. In this review, we aim to give an overview of different types of modifications of protein-based nanocontainers for drug delivery applications.

Molecular models of NS3 protease variants of the Hepatitis C virus.

PubMed

da Silveira, Nelson J F; Arcuri, Helen A; Bonalumi, Carlos E; de Souza, Fátima P; Mello, Isabel M V G C; Rahal, Paula; Pinho, João R R; de Azevedo, Walter F

2005-01-21

Hepatitis C virus (HCV) currently infects approximately three percent of the world population. In view of the lack of vaccines against HCV, there is an urgent need for an efficient treatment of the disease by an effective antiviral drug. Rational drug design has not been the primary way for discovering major therapeutics. Nevertheless, there are reports of success in the development of inhibitor using a structure-based approach. One of the possible targets for drug development against HCV is the NS3 protease variants. Based on the three-dimensional structure of these variants we expect to identify new NS3 protease inhibitors. In order to speed up the modeling process all NS3 protease variant models were generated in a Beowulf cluster. The potential of the structural bioinformatics for development of new antiviral drugs is discussed. The atomic coordinates of crystallographic structure 1CU1 and 1DY9 were used as starting model for modeling of the NS3 protease variant structures. The NS3 protease variant structures are composed of six subdomains, which occur in sequence along the polypeptide chain. The protease domain exhibits the dual beta-barrel fold that is common among members of the chymotrypsin serine protease family. The helicase domain contains two structurally related beta-alpha-beta subdomains and a third subdomain of seven helices and three short beta strands. The latter domain is usually referred to as the helicase alpha-helical subdomain. The rmsd value of bond lengths and bond angles, the average G-factor and Verify 3D values are presented for NS3 protease variant structures. This project increases the certainty that homology modeling is an useful tool in structural biology and that it can be very valuable in annotating genome sequence information and contributing to structural and functional genomics from virus. The structural models will be used to guide future efforts in the structure-based drug design of a new generation of NS3 protease variants inhibitors. All models in the database are publicly accessible via our interactive website, providing us with large amount of structural models for use in protein-ligand docking analysis.

Beyond 'peer pressure': rethinking drug use and 'youth culture'.

PubMed

Pilkington, Hilary

2007-05-01

The study of drug use by young people in the West has been transformed over the last decade by the development of sociological approaches to drug use which take serious account of the cultural context in which young people encounter drugs. One consequence is that the notion of 'peer pressure', as the primary articulation of the engagement between youth culture and drug use, has been displaced by that of 'normalisation', which envisages 'recreational' drug use as one expression of consumer-based youth cultural lifestyles. In stark contrast, academic discussion of drug use in Russia remains primarily concerned with the prevalence and health consequences of (intravenous) drug use while explanations of rising rates of drug use focus on structural factors related to the expansion of drugs supply and, to a lesser extent, post-Soviet social and economic dislocation. In this article, original empirical research in Russia is used to develop an understanding of young people's drug use that synthesises structural and cultural explanations of it. It does this by situating young people's narratives of their drugs choices in the context of local drugs markets and broader socio-economic processes. However, it attempts to go beyond seeing structural location as simply a 'constraint' on individual choice by adopting an understanding of 'youth culture' as a range of youth cultural practices and formations that simultaneously embody, reproduce and negotiate the structural locations of their subjects.

An emerging integration between ionic liquids and nanotechnology: general uses and future prospects in drug delivery.

PubMed

de Almeida, Tânia Santos; Júlio, Ana; Mota, Joana Portugal; Rijo, Patrícia; Reis, Catarina Pinto

2017-06-01

There is a growing need to develop drug-delivery systems that overcome drawbacks such as poor drug solubility/loading/release, systemic side effects and limited stability. Ionic liquids (ILs) offer many advantages and their tailoring represents a valuable tuning tool. Nano-based systems are also prized materials that prevent drug degradation, enhance their transport/distribution and extend their release. Consequently, structures containing ILs and nanoparticles (NPs) have been developed to attain synergistic effects. This overview on the properties of ILs, NPs and of their combined structures, reveals the recent advances in these areas through a review of pertinent literature. The IL-NP structures present enhanced properties and the subsequent performance upgrade proves to be useful in drug delivery, although much is yet to be done.

Successful generation of structural information for fragment-based drug discovery.

PubMed

Öster, Linda; Tapani, Sofia; Xue, Yafeng; Käck, Helena

2015-09-01

Fragment-based drug discovery relies upon structural information for efficient compound progression, yet it is often challenging to generate structures with bound fragments. A summary of recent literature reveals that a wide repertoire of experimental procedures is employed to generate ligand-bound crystal structures successfully. We share in-house experience from setting up and executing fragment crystallography in a project that resulted in 55 complex structures. The ligands span five orders of magnitude in affinity and the resulting structures are made available to be of use, for example, for development of computational methods. Analysis of the results revealed that ligand properties such as potency, ligand efficiency (LE) and, to some degree, clogP influence the success of complex structure generation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Highly porous drug-eluting structures

PubMed Central

Elsner, Jonathan J.; Kraitzer, Amir; Grinberg, Orly; Zilberman, Meital

2012-01-01

For many biomedical applications, there is need for porous implant materials. The current article focuses on a method for preparation of drug-eluting porous structures for various biomedical applications, based on freeze drying of inverted emulsions. This fabrication process enables the incorporation of any drug, to obtain an “active implant” that releases drugs to the surrounding tissue in a controlled desired manner. Examples for porous implants based on this technique are antibiotic-eluting mesh/matrix structures used for wound healing applications, antiproliferative drug-eluting composite fibers for stent applications and local cancer treatment, and protein-eluting films for tissue regeneration applications. In the current review we focus on these systems. We show that the release profiles of both types of drugs, water-soluble and water-insoluble, are affected by the emulsion's formulation parameters. The former's release profile is affected mainly through the emulsion stability and the resulting porous microstructure, whereas the latter's release mechanism occurs via water uptake and degradation of the host polymer. Hence, appropriate selection of the formulation parameters enables to obtain desired controllable release profile of any bioactive agent, water-soluble or water-insoluble, and also fit its physical properties to the application. PMID:23507890

SM-TF: A structural database of small molecule-transcription factor complexes.

PubMed

Xu, Xianjin; Ma, Zhiwei; Sun, Hongmin; Zou, Xiaoqin

2016-06-30

Transcription factors (TFs) are the proteins involved in the transcription process, ensuring the correct expression of specific genes. Numerous diseases arise from the dysfunction of specific TFs. In fact, over 30 TFs have been identified as therapeutic targets of about 9% of the approved drugs. In this study, we created a structural database of small molecule-transcription factor (SM-TF) complexes, available online at http://zoulab.dalton.missouri.edu/SM-TF. The 3D structures of the co-bound small molecule and the corresponding binding sites on TFs are provided in the database, serving as a valuable resource to assist structure-based drug design related to TFs. Currently, the SM-TF database contains 934 entries covering 176 TFs from a variety of species. The database is further classified into several subsets by species and organisms. The entries in the SM-TF database are linked to the UniProt database and other sequence-based TF databases. Furthermore, the druggable TFs from human and the corresponding approved drugs are linked to the DrugBank. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Beyond small molecule SAR – using the dopamine D3 receptor crystal structure to guide drug design

PubMed Central

Keck, Thomas M.; Burzynski, Caitlin; Shi, Lei; Newman, Amy Hauck

2016-01-01

The dopamine D3 receptor is a target of pharmacotherapeutic interest in a variety of neurological disorders including schizophrenia, restless leg syndrome, and drug addiction. The high protein sequence homology between the D3 and D2 receptors has posed a challenge to developing D3 receptor-selective ligands whose behavioral actions can be attributed to D3 receptor engagement, in vivo. However, through primarily small molecule structure-activity relationship (SAR) studies, a variety of chemical scaffolds have been discovered over the past two decades that have resulted in several D3 receptor-selective ligands with high affinity and in vivo activity. Nevertheless, viable clinical candidates remain limited. The recent determination of the high-resolution crystal structure of the D3 receptor has invigorated structure-based drug design, providing refinements to the molecular dynamic models and testable predictions about receptor-ligand interactions. This review will highlight recent preclinical and clinical studies demonstrating potential utility of D3 receptor-selective ligands in the treatment of addiction. In addition, new structure-based rational drug design strategies for D3 receptor-selective ligands that complement traditional small molecule SAR to improve the selectivity and directed efficacy profiles are examined. PMID:24484980

"Drug" Discovery with the Help of Organic Chemistry.

PubMed

Itoh, Yukihiro; Suzuki, Takayoshi

2017-01-01

The first step in "drug" discovery is to find compounds binding to a potential drug target. In modern medicinal chemistry, the screening of a chemical library, structure-based drug design, and ligand-based drug design, or a combination of these methods, are generally used for identifying the desired compounds. However, they do not necessarily lead to success and there is no infallible method for drug discovery. Therefore, it is important to explore medicinal chemistry based on not only the conventional methods but also new ideas. So far, we have found various compounds as drug candidates. In these studies, some strategies based on organic chemistry have allowed us to find drug candidates, through 1) construction of a focused library using organic reactions and 2) rational design of enzyme inhibitors based on chemical reactions catalyzed by the target enzyme. Medicinal chemistry based on organic chemical reactions could be expected to supplement the conventional methods. In this review, we present drug discovery with the help of organic chemistry showing examples of our explorative studies on histone deacetylase inhibitors and lysine-specific demethylase 1 inhibitors.

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2012-01-01

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

A structure- and chemical genomics-based approach for repositioning of drugs against VCP/p97 ATPase.

PubMed

Segura-Cabrera, Aldo; Tripathi, Reshmi; Zhang, Xiaoyi; Gui, Lin; Chou, Tsui-Fen; Komurov, Kakajan

2017-03-21

Valosin-containing protein (VCP/p97) ATPase (a.k.a. Cdc48) is a key member of the ER-associated protein degradation (ERAD) pathway. ERAD and VCP/p97 have been implicated in a multitude of human diseases, such as neurodegenerative diseases and cancer. Inhibition of VCP/p97 induces proteotoxic ER stress and cell death in cancer cells, making it an attractive target for cancer treatment. However, no drugs exist against this protein in the market. Repositioning of drugs towards new indications is an attractive alternative to the de novo drug development due to the potential for significantly shorter time to clinical translation. Here, we employed an integrative strategy for the repositioning of drugs as novel inhibitors of the VCP/p97 ATPase. We integrated structure-based virtual screening with the chemical genomics analysis of drug molecular signatures, and identified several candidate inhibitors of VCP/p97 ATPase. Importantly, experimental validation with cell-based and in vitro ATPase assays confirmed three (ebastine, astemizole and clotrimazole) out of seven tested candidates (~40% true hit rate) as direct inhibitors of VCP/p97 and ERAD. This study introduces an effective integrative strategy for drug repositioning, and identified new drugs against the VCP/p97/ERAD pathway in human diseases.

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description.

PubMed

Spyrakis, Francesca; Cavasotto, Claudio N

2015-10-01

Structure-based virtual screening is currently an established tool in drug lead discovery projects. Although in the last years the field saw an impressive progress in terms of algorithm development, computational performance, and retrospective and prospective applications in ligand identification, there are still long-standing challenges where further improvement is needed. In this review, we consider the conceptual frame, state-of-the-art and recent developments of three critical "structural" issues in structure-based drug lead discovery: the use of homology modeling to accurately model the binding site when no experimental structures are available, the necessity of accounting for the dynamics of intrinsically flexible systems as proteins, and the importance of considering active site water molecules in lead identification and optimization campaigns. Copyright © 2015 Elsevier Inc. All rights reserved.

In silico work flow for scaffold hopping in Leishmania.

PubMed

Waugh, Barnali; Ghosh, Ambarnil; Bhattacharyya, Dhananjay; Ghoshal, Nanda; Banerjee, Rahul

2014-11-17

Leishmaniasis,a broad spectrum of diseases caused by several sister species of protozoa belonging to family trypanosomatidae and genus leishmania , generally affects poorer sections of the populace in third world countries. With the emergence of strains resistant to traditional therapies and the high cost of second line drugs which generally have severe side effects, it becomes imperative to continue the search for alternative drugs to combat the disease. In this work, the leishmanial genomes and the human genome have been compared to identify proteins unique to the parasite and whose structures (or those of close homologues) are available in the Protein Data Bank. Subsequent to the prioritization of these proteins (based on their essentiality, virulence factor etc.), inhibitors have been identified for a subset of these prospective drug targets by means of an exhaustive literature survey. A set of three dimensional protein-ligand complexes have been assembled from the list of leishmanial drug targets by culling structures from the Protein Data Bank or by means of template based homology modeling followed by ligand docking with the GOLD software. Based on these complexes several structure based pharmacophores have been designed and used to search for alternative inhibitors in the ZINC database. This process led to a list of prospective compounds which could serve as potential antileishmanials. These small molecules were also used to search the Drug Bank to identify prospective lead compounds already in use as approved drugs. Interestingly, paromomycin which is currently being used as an antileishmanial drug spontaneously appeared in the list, probably giving added confidence to the 'scaffold hopping' computational procedures adopted in this work. The report thus provides the basis to experimentally verify several lead compounds for their predicted antileishmanial activity and includes several useful data bases of prospective drug targets in leishmania, their inhibitors and protein--inhibitor three dimensional complexes.

Latest development on RNA-based drugs and vaccines.

PubMed

Lundstrom, Kenneth

2018-06-01

Drugs and vaccines based on mRNA and RNA viruses show great potential and direct translation in the cytoplasm eliminates chromosomal integration. Limitations are associated with delivery and stability issues related to RNA degradation. Clinical trials on RNA-based drugs have been conducted in various disease areas. Likewise, RNA-based vaccines for viral infections and various cancers have been subjected to preclinical and clinical studies. RNA delivery and stability improvements include RNA structure modifications, targeting dendritic cells and employing self-amplifying RNA. Single-stranded RNA viruses possess self-amplifying RNA, which can provide extreme RNA replication in the cytoplasm to support RNA-based drug and vaccine development. Although oligonucleotide-based approaches have demonstrated potential, the focus here is on mRNA- and RNA virus-based methods.

Structure-based discovery and binding site analysis of histamine receptor ligands.

PubMed

Kiss, Róbert; Keserű, György M

2016-12-01

The application of structure-based drug discovery in histamine receptor projects was previously hampered by the lack of experimental structures. The publication of the first X-ray structure of the histamine H1 receptor has been followed by several successful virtual screens and binding site analysis studies of H1-antihistamines. This structure together with several other recently solved aminergic G-protein coupled receptors (GPCRs) enabled the development of more realistic homology models for H2, H3 and H4 receptors. Areas covered: In this paper, the authors review the development of histamine receptor models and their application in drug discovery. Expert opinion: In the authors' opinion, the application of atomistic histamine receptor models has played a significant role in understanding key ligand-receptor interactions as well as in the discovery of novel chemical starting points. The recently solved H1 receptor structure is a major milestone in structure-based drug discovery; however, our analysis also demonstrates that for building H3 and H4 receptor homology models, other GPCRs may be more suitable as templates. For these receptors, the authors envisage that the development of higher quality homology models will significantly contribute to the discovery and optimization of novel H3 and H4 ligands.

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.

Structure-based discovery of clinically approved drugs as Zika virus NS2B-NS3 protease inhibitors that potently inhibit Zika virus infection in vitro and in vivo.

PubMed

Yuan, Shuofeng; Chan, Jasper Fuk-Woo; den-Haan, Helena; Chik, Kenn Ka-Heng; Zhang, Anna Jinxia; Chan, Chris Chung-Sing; Poon, Vincent Kwok-Man; Yip, Cyril Chik-Yan; Mak, Winger Wing-Nga; Zhu, Zheng; Zou, Zijiao; Tee, Kah-Meng; Cai, Jian-Piao; Chan, Kwok-Hung; de la Peña, Jorge; Pérez-Sánchez, Horacio; Cerón-Carrasco, José Pedro; Yuen, Kwok-Yung

2017-09-01

Zika virus (ZIKV) infection may be associated with severe complications in fetuses and adults, but treatment options are limited. We performed an in silico structure-based screening of a large chemical library to identify potential ZIKV NS2B-NS3 protease inhibitors. Clinically approved drugs belonging to different drug classes were selected among the 100 primary hit compounds with the highest predicted binding affinities to ZIKV NS2B-NS3-protease for validation studies. ZIKV NS2B-NS3 protease inhibitory activity was validated in most of the selected drugs and in vitro anti-ZIKV activity was identified in two of them (novobiocin and lopinavir-ritonavir). Molecular docking and molecular dynamics simulations predicted that novobiocin bound to ZIKV NS2B-NS3-protease with high stability. Dexamethasone-immunosuppressed mice with disseminated ZIKV infection and novobiocin treatment had significantly (P < 0.05) higher survival rate (100% vs 0%), lower mean blood and tissue viral loads, and less severe histopathological changes than untreated controls. This structure-based drug discovery platform should facilitate the identification of additional enzyme inhibitors of ZIKV. Copyright © 2017 Elsevier B.V. All rights reserved.

Increasing the structural coverage of tuberculosis drug targets.

PubMed

Baugh, Loren; Phan, Isabelle; Begley, Darren W; Clifton, Matthew C; Armour, Brianna; Dranow, David M; Taylor, Brandy M; Muruthi, Marvin M; Abendroth, Jan; Fairman, James W; Fox, David; Dieterich, Shellie H; Staker, Bart L; Gardberg, Anna S; Choi, Ryan; Hewitt, Stephen N; Napuli, Alberto J; Myers, Janette; Barrett, Lynn K; Zhang, Yang; Ferrell, Micah; Mundt, Elizabeth; Thompkins, Katie; Tran, Ngoc; Lyons-Abbott, Sally; Abramov, Ariel; Sekar, Aarthi; Serbzhinskiy, Dmitri; Lorimer, Don; Buchko, Garry W; Stacy, Robin; Stewart, Lance J; Edwards, Thomas E; Van Voorhis, Wesley C; Myler, Peter J

2015-03-01

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus "homolog-rescue" strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. Of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structures would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD <1 Å, >85% side chain identity, and ≥80% PSAPF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases. Copyright © 2014 Elsevier Ltd. All rights reserved.

Increasing the Structural Coverage of Tuberculosis Drug Targets

PubMed Central

Baugh, Loren; Phan, Isabelle; Begley, Darren W.; Clifton, Matthew C.; Armour, Brianna; Dranow, David M.; Taylor, Brandy M.; Muruthi, Marvin M.; Abendroth, Jan; Fairman, James W.; Fox, David; Dieterich, Shellie H.; Staker, Bart L.; Gardberg, Anna S.; Choi, Ryan; Hewitt, Stephen N.; Napuli, Alberto J.; Myers, Janette; Barrett, Lynn K.; Zhang, Yang; Ferrell, Micah; Mundt, Elizabeth; Thompkins, Katie; Tran, Ngoc; Lyons-Abbott, Sally; Abramov, Ariel; Sekar, Aarthi; Serbzhinskiy, Dmitri; Lorimer, Don; Buchko, Garry W.; Stacy, Robin; Stewart, Lance J.; Edwards, Thomas E.; Van Voorhis, Wesley C.; Myler, Peter J.

2015-01-01

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus “homolog-rescue” strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. Of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structures would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD <1Å, >85% side chain identity, and ≥80% PSAPF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases. PMID:25613812

Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

PubMed

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

Establishing Structure Property Relationship in Drug Partitioning into and Release from Niosomes: Physical Chemistry Insights with Anti-Inflammatory Drugs.

PubMed

Dasgupta, Moumita; Kishore, Nand

2017-09-28

Understanding the physical chemistry underlying interactions of drugs with delivery formulations is extremely important in devising effective drug delivery systems. The partitioning and release kinetics of diclofenac sodium and naproxen from Brij 30 and Triton X-100 niosomal formulations have been addressed based on structural characterization, partitioning energetics, and release kinetics, thus establishing a relationship between structures and observed properties. Both the drugs partition in nonpolar regions of TX-100 niosomes via stacking of aromatic rings. The combined effects of interactions of the drugs with polar head groups and the rigidity of the niosome vesicles determine entry and partitioning of drugs into niosomes. The observed slower rate of release of the drugs from the drug encapsulated niosomes of TX-100 than those of Brij 30, suggest stable complexation of drugs in the nonpolar interior of the former. No release of drugs from the niosomes was observed until 24 h even upon varying pH conditions without SDS. However, SDS in drug loaded niosomes led to release of drugs in as early as 6 h. The sustained pattern of in vitro release kinetics of the drugs thus observed from our niosomal preparations suggest these vesicular systems to be promising for pharamaceutical applications as potential drug delivery vehicles.

Computer-Aided Structure Based Drug Design Approaches for the Discovery of New Anti-CHIKV Agents.

PubMed

Jadav, Surender Singh; Sinha, Barij Nayan; Hilgenfeld, Rolf; Jayaprakash, Venkatesan

2017-11-10

Chikungunya is a viral infection caused by Chikungunya virus (CHIKV), an arbovirus transmitted through mosquito (Aedes aegypti and Aedes albopictus) bite. The virus from sylvatic cycle in Africa mutated to new vector adaptation and became one of the major emerging and re-emerging viral infections in the past decade, affecting more than 40 countries. Efforts are being made by many researches to develop means to prevent and control the infection through vaccines and vector control strategy. On the other hand, search for novel chemotherapeutic agents for the treatment of infected patients is on. Approach of repurposed drug is one way of identifying an existing drug for the treatment of CHIKV infection. Review the history of CHIKV nsp2 protease inhibitors derived through structure-based computer-aided drug design along with phytochemicals identified as anti-CHIKV agents. A survey on CHIKV inhibitors reported till date has been carriedout. The data obtained were organized and discussed under natural substances and synthetic derivatives obtained as result of rational design. The review provides a well organized content in chronological order that has highly significant information for medicinal chemist who wish to explore the area of Anti-CHIKV drug design and development. Natural compounds with different scaffolds provides an opportunity to explore Ligand based drug design (LBDD), while rational drug design approaches provides opportunity to explore the Structure based drug design. From the presented mini-review, readers can understand that this area is less explored and has lots of potential in anti-CHIKVviral drug design & development. of reported literature inferred that, unlike other viral proteases, the nsP2 protease can be targeted for CHIKV viral inhibition. The HTVS process for the identification of anti-CHIK agents provided a few successive validated lead compounds against CHIKV infections. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Microstructural investigation using synchrotron radiation X-ray microtomography reveals taste-masking mechanism of acetaminophen microspheres.

PubMed

Guo, Zhen; Yin, Xianzhen; Liu, Congbiao; Wu, Li; Zhu, Weifeng; Shao, Qun; York, Peter; Patterson, Laurence; Zhang, Jiwen

2016-02-29

The structure of solid drug delivery systems has considerable influence on drug release behaviors from particles and granules and also impacts other properties relevant to release characteristics such as taste. In this study, lipid-based microspheres of acetaminophen were prepared to mask the undesirable taste of drug and therefore to identify the optimal formulation for drug release. Synchrotron radiation X-ray computed microtomography (SR-μCT) was used to investigate the fine structural architectures of microspheres non-destructively at different sampling times during drug release test, which were simultaneously determined to quantitatively correlate the structural data with drug release behaviors. The results demonstrated that the polymeric formulation component, namely, cationic polymethacrylate (Eudragit E100), was the key factor to mask the bitter taste of acetaminophen by inhibiting immediate drug release thereby reducing the interaction intensity of the bitter material with the oral cavity taste buds. The structure and morphology of the microspheres were found to be influenced by the shape and particle size of the drug, which was also an important factor for taste-masking performance. The quantitative analysis generated detailed structural information which was correlated well with drug release behaviors. Thus, SR-μCT has been proved as a powerful tool to investigate the fine microstructure of particles and provides a new approach in the design of particles for taste masking. Copyright © 2015 Elsevier B.V. All rights reserved.

Effect of benzocaine and propranolol on phospholipid-based bilayers.

PubMed

Mangiapia, G; Gvaramia, M; Kuhrts, L; Teixeira, J; Koutsioubas, A; Soltwedel, O; Frielinghaus, H

2017-12-06

Cell membranes play a fundamental role in protecting the cell from its surroundings, in addition to hosting many proteins with fundamental biological tasks. A study of drug/lipid interactions is a necessary and important step in fully clarifying the role and action mechanism of active ingredients, and shedding light on possible complications caused by drug overdosage. In this paper, the influence of benzocaine and propranolol drugs on the structure of l-α-phosphatidylcholine-based membranes has been investigated by means of neutron reflectivity, grazing incidence small angle neutron scattering, and small/ultra-small angle neutron scattering. Investigations allowed discovering a stiffening of the membranes and the formation of stalks, caused by the presence of benzocaine. On the other hand, disordered bilayers (lamellar powders) and highly curved structures were found in the presence of propranolol. The results obtained may be rationalized in terms of the molecular structures of drugs and may serve as a starting point for explaining the toxic behavior in long-term and overdosage scenarios.

Combining NMR and X-ray crystallography in fragment-based drug discovery: discovery of highly potent and selective BACE-1 inhibitors.

PubMed

Wyss, Daniel F; Wang, Yu-Sen; Eaton, Hugh L; Strickland, Corey; Voigt, Johannes H; Zhu, Zhaoning; Stamford, Andrew W

2012-01-01

Fragment-based drug discovery (FBDD) has become increasingly popular over the last decade. We review here how we have used highly structure-driven fragment-based approaches to complement more traditional lead discovery to tackle high priority targets and those struggling for leads. Combining biomolecular nuclear magnetic resonance (NMR), X-ray crystallography, and molecular modeling with structure-assisted chemistry and innovative biology as an integrated approach for FBDD can solve very difficult problems, as illustrated in this chapter. Here, a successful FBDD campaign is described that has allowed the development of a clinical candidate for BACE-1, a challenging CNS drug target. Crucial to this achievement were the initial identification of a ligand-efficient isothiourea fragment through target-based NMR screening and the determination of its X-ray crystal structure in complex with BACE-1, which revealed an extensive H-bond network with the two active site aspartate residues. This detailed 3D structural information then enabled the design and validation of novel, chemically stable and accessible heterocyclic acylguanidines as aspartic acid protease inhibitor cores. Structure-assisted fragment hit-to-lead optimization yielded iminoheterocyclic BACE-1 inhibitors that possess desirable molecular properties as potential therapeutic agents to test the amyloid hypothesis of Alzheimer's disease in a clinical setting.

Lactose-modified DNA tile nanostructures as drug carriers.

PubMed

Akkus Sut, Pinar; Tunc, Cansu Umran; Culha, Mustafa

2016-09-01

DNA hybridization allows the preparation of nanoscale DNA structures with desired shape and size. DNA structures using simple base pairing can be used for the delivery of drug molecules into the cells. Since DNA carries multiple negative charges, their cellular uptake efficiency is low. Thus, the modification of the DNA structures with molecules that may enhance the cellular internalization may be an option. The objective of this study is to construct DNA-based nanocarrier system and to investigate the cellular uptake of DNA tile with/without lactose modification. Doxorubicin was intercalated to DNA tile and cellular uptake of drug-loaded DNA-based carrier with/without lactose modification was investigated in vitro. HeLa, BT-474, and MDA-MB-231 cancer cells were used for cellular uptake studies and cytotoxicity assays. Using fluorescence spectroscopy, flow cytometry, and confocal microscopy, cellular uptake behavior of DNA tile was investigated. The cytotoxicity of DNA tile structures was determined with WST-1 assay. The results show that modification with lactose effectively increases the intracellular uptake of doxorubicin loaded DNA tile structure by cancer cells compared with the unmodified DNA tile. The findings of this study suggest that DNA-based nanostructures modified with carbohydrates can be used as suitable multifunctional nanocarriers with simple chemical modifications.

Increasing the structural coverage of tuberculosis drug targets

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

Baugh, Loren; Phan, Isabelle; Begley, Darren W.

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus “homolog-rescue” strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. We found that of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structuresmore » would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD <1 Å, >85% side chain identity, and ≥80% PS APF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases.« less

Increasing the structural coverage of tuberculosis drug targets

DOE PAGES

Baugh, Loren; Phan, Isabelle; Begley, Darren W.; ...

2014-12-19

High-resolution three-dimensional structures of essential Mycobacterium tuberculosis (Mtb) proteins provide templates for TB drug design, but are available for only a small fraction of the Mtb proteome. Here we evaluate an intra-genus “homolog-rescue” strategy to increase the structural information available for TB drug discovery by using mycobacterial homologs with conserved active sites. We found that of 179 potential TB drug targets selected for x-ray structure determination, only 16 yielded a crystal structure. By adding 1675 homologs from nine other mycobacterial species to the pipeline, structures representing an additional 52 otherwise intractable targets were solved. To determine whether these homolog structuresmore » would be useful surrogates in TB drug design, we compared the active sites of 106 pairs of Mtb and non-TB mycobacterial (NTM) enzyme homologs with experimentally determined structures, using three metrics of active site similarity, including superposition of continuous pharmacophoric property distributions. Pair-wise structural comparisons revealed that 19/22 pairs with >55% overall sequence identity had active site Cα RMSD <1 Å, >85% side chain identity, and ≥80% PS APF (similarity based on pharmacophoric properties) indicating highly conserved active site shape and chemistry. Applying these results to the 52 NTM structures described above, 41 shared >55% sequence identity with the Mtb target, thus increasing the effective structural coverage of the 179 Mtb targets over three-fold (from 9% to 32%). The utility of these structures in TB drug design can be tested by designing inhibitors using the homolog structure and assaying the cognate Mtb enzyme; a promising test case, Mtb cytidylate kinase, is described. The homolog-rescue strategy evaluated here for TB is also generalizable to drug targets for other diseases.« less

Multi-target parallel processing approach for gene-to-structure determination of the influenza polymerase PB2 subunit.

PubMed

Armour, Brianna L; Barnes, Steve R; Moen, Spencer O; Smith, Eric; Raymond, Amy C; Fairman, James W; Stewart, Lance J; Staker, Bart L; Begley, Darren W; Edwards, Thomas E; Lorimer, Donald D

2013-06-28

Pandemic outbreaks of highly virulent influenza strains can cause widespread morbidity and mortality in human populations worldwide. In the United States alone, an average of 41,400 deaths and 1.86 million hospitalizations are caused by influenza virus infection each year (1). Point mutations in the polymerase basic protein 2 subunit (PB2) have been linked to the adaptation of the viral infection in humans (2). Findings from such studies have revealed the biological significance of PB2 as a virulence factor, thus highlighting its potential as an antiviral drug target. The structural genomics program put forth by the National Institute of Allergy and Infectious Disease (NIAID) provides funding to Emerald Bio and three other Pacific Northwest institutions that together make up the Seattle Structural Genomics Center for Infectious Disease (SSGCID). The SSGCID is dedicated to providing the scientific community with three-dimensional protein structures of NIAID category A-C pathogens. Making such structural information available to the scientific community serves to accelerate structure-based drug design. Structure-based drug design plays an important role in drug development. Pursuing multiple targets in parallel greatly increases the chance of success for new lead discovery by targeting a pathway or an entire protein family. Emerald Bio has developed a high-throughput, multi-target parallel processing pipeline (MTPP) for gene-to-structure determination to support the consortium. Here we describe the protocols used to determine the structure of the PB2 subunit from four different influenza A strains.

Computational challenges of structure-based approaches applied to HIV.

PubMed

Forli, Stefano; Olson, Arthur J

2015-01-01

Here, we review some of the opportunities and challenges that we face in computational modeling of HIV therapeutic targets and structural biology, both in terms of methodology development and structure-based drug design (SBDD). Computational methods have provided fundamental support to HIV research since the initial structural studies, helping to unravel details of HIV biology. Computational models have proved to be a powerful tool to analyze and understand the impact of mutations and to overcome their structural and functional influence in drug resistance. With the availability of structural data, in silico experiments have been instrumental in exploiting and improving interactions between drugs and viral targets, such as HIV protease, reverse transcriptase, and integrase. Issues such as viral target dynamics and mutational variability, as well as the role of water and estimates of binding free energy in characterizing ligand interactions, are areas of active computational research. Ever-increasing computational resources and theoretical and algorithmic advances have played a significant role in progress to date, and we envision a continually expanding role for computational methods in our understanding of HIV biology and SBDD in the future.

Marijuana-based drugs: innovative therapeutics or designer drugs of abuse?

PubMed

Seely, Kathryn A; Prather, Paul L; James, Laura P; Moran, Jeffery H

2011-02-01

The principal psychoactive component of marijuana, Δ(9)-tetrahydrocannabinol (THC), activates CB1 cannabinoid receptors (CB1Rs). Unfortunately, pharmacological research into the design of effective THC analogs has been hampered by psychiatric side effects. THC-based drug design of a less academic nature, however, has led to the marketing of "synthetic marijuana," labeled as K2 or "Spice," among other terms, which elicits psychotropic actions via CB1R activation. Because of structural dissimilarity to THC, the active ingredients of K2/Spice preparations are widely unregulated. The K2/Spice "phenomenon" provides a context for considering whether marijuana-based drugs will truly provide innovative therapeutics or merely perpetuate drug abuse.

De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks.

PubMed

Schneider, G; Lee, M L; Stahl, M; Schneider, P

2000-07-01

An evolutionary algorithm was developed for fragment-based de novo design of molecules (TOPAS, TOPology-Assigning System). This stochastic method aims at generating a novel molecular structure mimicking a template structure. A set of approximately 25,000 fragment structures serves as the building block supply, which were obtained by a straightforward fragmentation procedure applied to 36,000 known drugs. Eleven reaction schemes were implemented for both fragmentation and building block assembly. This combination of drug-derived building blocks and a restricted set of reaction schemes proved to be a key for the automatic development of novel, synthetically tractable structures. In a cyclic optimization process, molecular architectures were generated from a parent structure by virtual synthesis, and the best structure of a generation was selected as the parent for the subsequent TOPAS cycle. Similarity measures were used to define 'fitness', based on 2D-structural similarity or topological pharmacophore distance between the template molecule and the variants. The concept of varying library 'diversity' during a design process was consequently implemented by using adaptive variant distributions. The efficiency of the design algorithm was demonstrated for the de novo construction of potential thrombin inhibitors mimicking peptide and non-peptide template structures.

Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship.

PubMed

Huang, Xiao Yan; Shan, Zhi Jie; Zhai, Hong Lin; Li, Li Na; Zhang, Xiao Yun

2011-08-22

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.

Development and application of hybrid structure based method for efficient screening of ligands binding to G-protein coupled receptors

NASA Astrophysics Data System (ADS)

Kortagere, Sandhya; Welsh, William J.

2006-12-01

G-protein coupled receptors (GPCRs) comprise a large superfamily of proteins that are targets for nearly 50% of drugs in clinical use today. In the past, the use of structure-based drug design strategies to develop better drug candidates has been severely hampered due to the absence of the receptor's three-dimensional structure. However, with recent advances in molecular modeling techniques and better computing power, atomic level details of these receptors can be derived from computationally derived molecular models. Using information from these models coupled with experimental evidence, it has become feasible to build receptor pharmacophores. In this study, we demonstrate the use of the Hybrid Structure Based (HSB) method that can be used effectively to screen and identify prospective ligands that bind to GPCRs. Essentially; this multi-step method combines ligand-based methods for building enriched libraries of small molecules and structure-based methods for screening molecules against the GPCR target. The HSB method was validated to identify retinal and its analogues from a random dataset of ˜300,000 molecules. The results from this study showed that the 9 top-ranking molecules are indeed analogues of retinal. The method was also tested to identify analogues of dopamine binding to the dopamine D2 receptor. Six of the ten top-ranking molecules are known analogues of dopamine including a prodrug, while the other thirty-four molecules are currently being tested for their activity against all dopamine receptors. The results from both these test cases have proved that the HSB method provides a realistic solution to bridge the gap between the ever-increasing demand for new drugs to treat psychiatric disorders and the lack of efficient screening methods for GPCRs.

Molecular structure and pronounced conformational flexibility of doxorubicin in free and conjugated state within a drug-peptide compound.

PubMed

Tsoneva, Yana; Jonker, Hendrik R A; Wagner, Manfred; Tadjer, Alia; Lelle, Marco; Peneva, Kalina; Ivanova, Anela

2015-02-19

The search for targeted drug delivery systems requires the design of drug-carrier complexes, which could both reach the malignant cells and preserve the therapeutic substance activity. A promising strategy aimed at enhancing the uptake and reducing the systemic toxicity is to bind covalently the drug to a cell-penetrating peptide. To understand the structure-activity relationship in such preparations, the chemotherapeutic drug doxorubicin was investigated by unrestrained molecular dynamics simulations, supported by NMR, which yielded its molecular geometry in aqueous environment. Furthermore, the structure and dynamics of a conjugate of the drug with a cell-penetrating peptide was obtained from molecular dynamics simulations in aqueous solution. The geometries of the unbound compounds were characterized at different temperatures, as well as the extent to which they change after covalent binding and whether/how they influence each other in the drug-peptide conjugate. The main structural fragments that affect the conformational ensemble of every molecule were found. The results show that the transitions between different substructures of the three compounds require a modest amount of energy. At increased temperature, either more conformations become populated as a result of the thermal fluctuations or the relative shares of the various conformers equalize at the nanosecond scale. These frequent structural interconversions suggest expressed conformational freedom of the molecules. Conjugation into the drug-peptide compound partially immobilizes the molecules of the parent compounds. Nevertheless, flexibility still exists, as well as an effective intra- and intermolecular hydrogen bonding that stabilizes the structures. We observe compact packing of the drug within the peptide that is also based on stacking interactions. All this outlines the drug-peptide conjugate as a prospective building block of a more complex drug-carrier system.

Permeation enhancer strategies in transdermal drug delivery.

PubMed

Marwah, Harneet; Garg, Tarun; Goyal, Amit K; Rath, Goutam

2016-01-01

Today, ∼74% of drugs are taken orally and are not found to be as effective as desired. To improve such characteristics, transdermal drug delivery was brought to existence. This delivery system is capable of transporting the drug or macromolecules painlessly through skin into the blood circulation at fixed rate. Topical administration of therapeutic agents offers many advantages over conventional oral and invasive techniques of drug delivery. Several important advantages of transdermal drug delivery are prevention from hepatic first pass metabolism, enhancement of therapeutic efficiency and maintenance of steady plasma level of the drug. Human skin surface, as a site of drug application for both local and systemic effects, is the most eligible candidate available. New controlled transdermal drug delivery systems (TDDS) technologies (electrically-based, structure-based and velocity-based) have been developed and commercialized for the transdermal delivery of troublesome drugs. This review article covers most of the new active transport technologies involved in enhancing the transdermal permeation via effective drug delivery system.

Structural insights into ligand recognition and selectivity for class A, B, and C GPCRs

PubMed Central

Lee, Sang-Min; Booe, Jason M.; Pioszak, Augen A.

2015-01-01

The G protein-coupled receptor (GPCR) superfamily constitutes the largest collection of cell surface signaling proteins with approximately 800 members in the human genome. GPCRs regulate virtually all aspects of physiology and they are an important class of drug targets with ~30% of drugs on the market targeting a GPCR. Breakthroughs in GPCR structural biology in recent years have significantly expanded our understanding of GPCR structure and function and ushered in a new era of structure-based drug design for GPCRs. Crystal structures for nearly thirty distinct GPCRs are now available including receptors from each of the major classes, A, B, C, and F. These structures provide a foundation for understanding the molecular basis of GPCR pharmacology. Here, we review structural mechanisms of ligand recognition and selectivity of GPCRs with a focus on selected examples from classes A, B, and C, and we highlight major unresolved questions for future structural studies. PMID:25981303

Structural studies of G protein-coupled receptors.

PubMed

Lu, Mengjie; Wu, Beili

2016-11-01

G protein-coupled receptors (GPCRs) comprise the largest membrane protein family. These receptors sense a variety of signaling molecules, activate multiple intracellular signal pathways, and act as the targets of over 40% of marketed drugs. Recent progress on GPCR structural studies provides invaluable insights into the structure-function relationship of the GPCR superfamily, deepening our understanding about the molecular mechanisms of GPCR signal transduction. Here, we review recent breakthroughs on GPCR structure determination and the structural features of GPCRs, and take the structures of chemokine receptor CCR5 and purinergic receptors P2Y 1 R and P2Y 12 R as examples to discuss the importance of GPCR structures on functional studies and drug discovery. In addition, we discuss the prospect of GPCR structure-based drug discovery. © 2016 IUBMB Life, 68(11):894-903, 2016. © 2016 International Union of Biochemistry and Molecular Biology.

Structurally Based Therapeutic Evaluation: A Therapeutic and Practical Approach to Teaching Medicinal Chemistry.

ERIC Educational Resources Information Center

Alsharif, Naser Z.; And Others

1997-01-01

Explains structurally based therapeutic evaluation of drugs, which uses seven therapeutic criteria in translating chemical and structural knowledge into therapeutic decision making in pharmaceutical care. In a Creighton University (Nebraska) medicinal chemistry course, students apply the approach to solve patient-related therapeutic problems in…

In silico modeling to predict drug-induced phospholipidosis

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

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

2013-06-01

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

First-principles modeling of biological systems and structure-based drug-design.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2013-03-01

Molecular modeling techniques play a relevant role in drug design providing detailed information at atomistic level on the structural, dynamical, mechanistic and electronic properties of biological systems involved in diseases' onset, integrating and supporting commonly used experimental approaches. These information are often not accessible to the experimental techniques taken singularly, but are of crucial importance for drug design. Due to the enormous increase of the computer power in the last decades, quantum mechanical (QM) or first-principles-based methods have become often used to address biological issues of pharmaceutical relevance, providing relevant information for drug design. Due to their complexity and their size, biological systems are often investigated by means of a mixed quantum-classical (QM/MM) approach, which treats at an accurate QM level a limited chemically relevant portion of the system and at the molecular mechanics (MM) level the remaining of the biomolecule and its environment. This method provides a good compromise between computational cost and accuracy, allowing to characterize the properties of the biological system and the (free) energy landscape of the process in study with the accuracy of a QM description. In this review, after a brief introduction of QM and QM/MM methods, we will discuss few representative examples, taken from our work, of the application of these methods in the study of metallo-enzymes of pharmaceutical interest, of metal-containing anticancer drugs targeting the DNA as well as of neurodegenerative diseases. The information obtained from these studies may provide the basis for a rationale structure-based drug design of new and more efficient inhibitors or drugs.

Oil and drug control the release rate from lyotropic liquid crystals.

PubMed

Martiel, Isabelle; Baumann, Nicole; Vallooran, Jijo J; Bergfreund, Jotam; Sagalowicz, Laurent; Mezzenga, Raffaele

2015-04-28

The control of the diffusion coefficient by the dimensionality d of the structure appears as a most promising lever to efficiently tune the release rate from lyotropic liquid crystalline (LLC) phases and dispersed particles towards sustained, controlled and targeted release. By using phosphatidylcholine (PC)- and monolinoleine (MLO)-based mesophases with various apolar structural modifiers and water-soluble drugs, we present a comprehensive study of the dimensional structural control of hydrophilic drug release, including 3-d bicontinuous cubic, 2-d lamellar, 1-d hexagonal and 0-d micellar cubic phases in excess water. We investigate how the surfactant, the oil properties and the drug hydrophilicity mitigate or even cancel the effect of structure variation on the drug release rate. Unexpectedly, the observed behavior cannot be fully explained by the thermodynamic partition of the drug into the lipid matrix, which points out to previously overlooked kinetic effects. We therefore interpret our results by discussing the mechanism of structural control of the diffusion rate in terms of drug permeation through the lipid membrane, which includes exchange kinetics. A wide range of implications follow regarding formulation and future developments, both for dispersed LLC delivery systems and topical applications in bulk phase. Copyright © 2015 Elsevier B.V. All rights reserved.

Combining Functional and Structural Genomics to Sample the Essential Burkholderia Structome

PubMed Central

Baugh, Loren; Gallagher, Larry A.; Patrapuvich, Rapatbhorn; Clifton, Matthew C.; Gardberg, Anna S.; Edwards, Thomas E.; Armour, Brianna; Begley, Darren W.; Dieterich, Shellie H.; Dranow, David M.; Abendroth, Jan; Fairman, James W.; Fox, David; Staker, Bart L.; Phan, Isabelle; Gillespie, Angela; Choi, Ryan; Nakazawa-Hewitt, Steve; Nguyen, Mary Trang; Napuli, Alberto; Barrett, Lynn; Buchko, Garry W.; Stacy, Robin; Myler, Peter J.; Stewart, Lance J.; Manoil, Colin; Van Voorhis, Wesley C.

2013-01-01

Background The genus Burkholderia includes pathogenic gram-negative bacteria that cause melioidosis, glanders, and pulmonary infections of patients with cancer and cystic fibrosis. Drug resistance has made development of new antimicrobials critical. Many approaches to discovering new antimicrobials, such as structure-based drug design and whole cell phenotypic screens followed by lead refinement, require high-resolution structures of proteins essential to the parasite. Methodology/Principal Findings We experimentally identified 406 putative essential genes in B. thailandensis, a low-virulence species phylogenetically similar to B. pseudomallei, the causative agent of melioidosis, using saturation-level transposon mutagenesis and next-generation sequencing (Tn-seq). We selected 315 protein products of these genes based on structure-determination criteria, such as excluding very large and/or integral membrane proteins, and entered them into the Seattle Structural Genomics Center for Infection Disease (SSGCID) structure determination pipeline. To maximize structural coverage of these targets, we applied an “ortholog rescue” strategy for those producing insoluble or difficult to crystallize proteins, resulting in the addition of 387 orthologs (or paralogs) from seven other Burkholderia species into the SSGCID pipeline. This structural genomics approach yielded structures from 31 putative essential targets from B. thailandensis, and 25 orthologs from other Burkholderia species, yielding an overall structural coverage for 49 of the 406 essential gene families, with a total of 88 depositions into the Protein Data Bank. Of these, 25 proteins have properties of a potential antimicrobial drug target i.e., no close human homolog, part of an essential metabolic pathway, and a deep binding pocket. We describe the structures of several potential drug targets in detail. Conclusions/Significance This collection of structures, solubility and experimental essentiality data provides a resource for development of drugs against infections and diseases caused by Burkholderia. All expression clones and proteins created in this study are freely available by request. PMID:23382856

Chemical Structural Novelty: On-Targets and Off-Targets

PubMed Central

Yera, Emmanuel R.; Cleves, Ann. E.; Jain, Ajay N.

2011-01-01

Drug structures may be quantitatively compared based on 2D topological structural considerations and based on 3D characteristics directly related to binding. A framework for combining multiple similarity computations is presented along with its systematic application to 358 drugs with overlapping pharmacology. Given a new molecule along with a set of molecules sharing some biological effect, a single score based on comparison to the known set is produced, reflecting either 2D similarity, 3D similarity, or their combination. For prediction of primary targets, the benefit of 3D over 2D was relatively small, but for prediction of off-targets, the added benefit was large. In addition to assessing prediction, the relationship between chemical similarity and pharmacological novelty was studied. Drug pairs that shared high 3D similarity but low 2D similarity (i.e. a novel scaffold) were shown to be much more likely to exhibit pharmacologically relevant differences in terms of specific protein target modulation. PMID:21916467

Modulated evaluation metrics for drug-based ontologies.

PubMed

Amith, Muhammad; Tao, Cui

2017-04-24

Research for ontology evaluation is scarce. If biomedical ontological datasets and knowledgebases are to be widely used, there needs to be quality control and evaluation for the content and structure of the ontology. This paper introduces how to effectively utilize a semiotic-inspired approach to ontology evaluation, specifically towards drug-related ontologies hosted on the National Center for Biomedical Ontology BioPortal. Using the semiotic-based evaluation framework for drug-based ontologies, we adjusted the quality metrics based on the semiotic features of drug ontologies. Then, we compared the quality scores before and after tailoring. The scores revealed a more precise measurement and a closer distribution compared to the before-tailoring. The results of this study reveal that a tailored semiotic evaluation produced a more meaningful and accurate assessment of drug-based ontologies, lending to the possible usefulness of semiotics in ontology evaluation.

Nanoporous anodic titanium dioxide layers as potential drug delivery systems: Drug release kinetics and mechanism.

PubMed

Jarosz, Magdalena; Pawlik, Anna; Szuwarzyński, Michał; Jaskuła, Marian; Sulka, Grzegorz D

2016-07-01

Nanoporous anodic titanium dioxide (ATO) layers on Ti foil were prepared via a three step anodization process in an electrolyte based on an ethylene glycol solution with fluoride ions. Some of the ATO samples were heat-treated in order to achieve two different crystallographic structures - anatase (400°C) and a mixture of anatase and rutile (600°C). The structural and morphological characterizations of ATO layers were performed using a field emission scanning electron microscope (SEM). The hydrophilicity of ATO layers was determined with contact angle measurements using distilled water. Ibuprofen and gentamicin were loaded effectively inside the ATO nanopores. Afterwards, an in vitro drug release was conducted for 24h under a static and dynamic flow conditions in a phosphate buffer solution at 37°C. The drug concentrations were determined using UV-Vis spectrophotometry. The absorbance of ibuprofen was measured directly at 222nm, whether gentamicin was determined as a complex with silver nanoparticles (Ag NPs) at 394nm. Both compounds exhibited long term release profiles, despite the ATO structure. A new release model, based on the desorption of the drug from the ATO top surface followed by the desorption and diffusion of the drug from the nanopores, was derived. The proposed release model was fitted to the experimental drug release profiles, and kinetic parameters were calculated. Copyright © 2016 Elsevier B.V. All rights reserved.

Improving the apo-state detergent stability of NTS1 with CHESS for pharmacological and structural studies.

PubMed

Scott, Daniel J; Kummer, Lutz; Egloff, Pascal; Bathgate, Ross A D; Plückthun, Andreas

2014-11-01

The largest single class of drug targets is the G protein-coupled receptor (GPCR) family. Modern high-throughput methods for drug discovery require working with pure protein, but this has been a challenge for GPCRs, and thus the success of screening campaigns targeting soluble, catalytic protein domains has not yet been realized for GPCRs. Therefore, most GPCR drug screening has been cell-based, whereas the strategy of choice for drug discovery against soluble proteins is HTS using purified proteins coupled to structure-based drug design. While recent developments are increasing the chances of obtaining GPCR crystal structures, the feasibility of screening directly against purified GPCRs in the unbound state (apo-state) remains low. GPCRs exhibit low stability in detergent micelles, especially in the apo-state, over the time periods required for performing large screens. Recent methods for generating detergent-stable GPCRs, however, offer the potential for researchers to manipulate GPCRs almost like soluble enzymes, opening up new avenues for drug discovery. Here we apply cellular high-throughput encapsulation, solubilization and screening (CHESS) to the neurotensin receptor 1 (NTS1) to generate a variant that is stable in the apo-state when solubilized in detergents. This high stability facilitated the crystal structure determination of this receptor and also allowed us to probe the pharmacology of detergent-solubilized, apo-state NTS1 using robotic ligand binding assays. NTS1 is a target for the development of novel antipsychotics, and thus CHESS-stabilized receptors represent exciting tools for drug discovery. Copyright © 2014 Elsevier B.V. All rights reserved.

Silk-Based Biomaterials for Sustained Drug Delivery

PubMed Central

Yucel, Tuna; Lovett, Michael L.; Kaplan, David L.

2014-01-01

Silk presents a rare combination of desirable properties for sustained drug delivery, including aqueous-based purification and processing options without chemical cross-linkers, compatibility with common sterilization methods, controllable and surface-mediated biodegradation into non-inflammatory by-products, biocompatibility, utility in drug stabilization, and robust mechanical properties. A versatile silk-based toolkit is currently available for sustained drug delivery formulations of small molecule through macromolecular drugs, with a promise to mitigate several drawbacks associated with other degradable sustained delivery technologies in the market. Silk-based formulations utilize silk’s well-defined nano- through microscale structural hierarchy, stimuli-responsive self-assembly pathways and crystal polymorphism, as well as sequence and genetic modification options towards targeted pharmaceutical outcomes. Furthermore, by manipulating the interactions between silk and drug molecules, near-zero order sustained release may be achieved through diffusion- and degradation-based release mechanisms. Because of these desirable properties, there has been increasing industrial interest in silk-based drug delivery systems currently at various stages of the developmental pipeline from pre-clinical to FDA-approved products. Here, we discuss the unique aspects of silk technology as a sustained drug delivery platform and highlight the current state of the art in silk-based drug delivery. We also offer a potential early development pathway for silk-based sustained delivery products. PMID:24910193

Crystal structure of Zika virus NS5 RNA-dependent RNA polymerase.

PubMed

Godoy, Andre S; Lima, Gustavo M A; Oliveira, Ketllyn I Z; Torres, Naiara U; Maluf, Fernando V; Guido, Rafael V C; Oliva, Glaucius

2017-03-27

The current Zika virus (ZIKV) outbreak became a global health threat of complex epidemiology and devastating neurological impacts, therefore requiring urgent efforts towards the development of novel efficacious and safe antiviral drugs. Due to its central role in RNA viral replication, the non-structural protein 5 (NS5) RNA-dependent RNA-polymerase (RdRp) is a prime target for drug discovery. Here we describe the crystal structure of the recombinant ZIKV NS5 RdRp domain at 1.9 Å resolution as a platform for structure-based drug design strategy. The overall structure is similar to other flaviviral homologues. However, the priming loop target site, which is suitable for non-nucleoside polymerase inhibitor design, shows significant differences in comparison with the dengue virus structures, including a tighter pocket and a modified local charge distribution.

Emergence of cytotoxic resistance in cancer cell populations: Single-cell mechanisms and population-level consequences

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

Lorenzi, Tommaso; Chisholm, Rebecca H.; Lorz, Alexander

We formulate an individual-based model and a population model of phenotypic evolution, under cytotoxic drugs, in a cancer cell population structured by the expression levels of survival-potential and proliferation-potential. We apply these models to a recently studied experimental system. Our results suggest that mechanisms based on fundamental laws of biology can reversibly push an actively-proliferating, and drug-sensitive, cell population to transition into a weakly-proliferative and drug-tolerant state, which will eventually facilitate the emergence of more potent, proliferating and drug-tolerant cells.

Characterization of Aptamer BC 007 Substance and Product Using Circular Dichroism and Nuclear Magnetic Resonance Spectroscopy.

PubMed

Weisshoff, Hardy; Wenzel, Katrin; Schulze-Rothe, Sarah; Nikolenko, Heike; Davideit, Hanna; Becker, Niels-Peter; Göttel, Peter; Srivatsa, G Susan; Dathe, Margitta; Müller, Johannes; Haberland, Annekathrin

2018-04-18

Possible unwanted folding of biopharmaceuticals during manufacturing and storage has resulted in analysis schemes compared to small molecules that include bioanalytical characterization besides chemical characterization. Whether bioanalytical characterization is required for nucleotide-based drugs, may be decided on a case-by-case basis. Nucleotide-based pharmaceuticals, if chemically synthesized, occupy an intermediate position between small-molecule drugs and biologics. Here, we tested whether a physicochemical characterization of a nucleotide-based drug substance, BC 007, was adequate, using circular dichroism (CD) spectroscopy. Nuclear magnetic resonance confirmed CD data in one experimental setup. BC 007 forms a quadruplex structure under specific external conditions, which was characterized for its stability and structural appearance also after denaturation using CD and nuclear magnetic resonance. The amount of the free energy (ΔG 0 ) involved in quadruplex formation of BC 007 was estimated at +8.7 kJ/mol when dissolved in water and +1.4 kJ/mol in 154 mM NaCl, indicating structural instability under these conditions. However, dissolution of the substance in 5 mM of KCl reduced the ΔG 0 to -5.6 kJ/mol due to the stabilizing effect of cations. These results show that positive ΔG 0 of quadruplex structure formation in water and aqueous NaCl prevents BC 007 from preforming stable 3-dimensional structures, which could potentially affect drug function. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

[Prerequisites for electronic systems evaluating safe and effective drug therapy. A contribution to the Action Plan of the Federal Health Ministry].

PubMed

Aly, A-F; Menges, K; Haas, C H; Zimmermann, L; Kaltschmidt, J; Criegee-Rieck, M

2011-11-01

Evaluation of effective and safe drug therapy assisted by electronic systems is based on certain prerequisites, including structured data of drugs and from patients. These prerequisites were identified in a workshop within the scope of the National Action Plan and have been reported in a 7+1-point plan: medicinal product data must be correct and up-to-date based on the summary of product characteristics approved by the responsible authorities. Product data must be available in an agreed textual structure and must use defined semantic elements within this structure. Identifiers must be allocated to all drugs and substances in order to enable unique identification and exchange across systems. Semantic structures of the product data, on the one hand, and of patient data, on the other, must be defined across system boundaries and for the whole German national health care system, and be available to every stakeholder, up-to-date, and preferably freely accessible. This consensus regarding content and structural conventions is a prerequisite for other scenarios in the health care system, such as transmitting individual case safety reports without system and media discontinuity, and is currently of great importance with respect to the European legislation on pharmacovigilance, which will be implemented nationally.

Role of Components in the Formation of Self-microemulsifying Drug Delivery Systems.

PubMed

Gurram, A K; Deshpande, P B; Kar, S S; Nayak, Usha Y; Udupa, N; Reddy, M S

2015-01-01

Pharmaceutical research is focused in designing novel drug delivery systems to improve the bioavailability of poorly water soluble drugs. Self-microemulsifying drug delivery systems, one among the lipid-based dosage forms were proven to be promising in improving the oral bioavailability of such drugs by enhancing solubility, permeability and avoiding first-pass metabolism via enhanced lymphatic transport. Further, they have been successful in avoiding both inter and intra individual variations as well as the dose disproportionality. Aqueous insoluble drugs, in general, show greater solubility in lipid based excipients, and hence they are formulated as lipid based drug delivery systems. The extent of solubility of a hydrophobic drug in lipid excipients i.e. oil, surfactant and co-surfactant (components of self-microemulsifying drug delivery systems) greatly affects the drug loading and in producing stable self-microemulsifying drug delivery systems. The present review highlighted the influence of physicochemical factors and structural features of the hydrophobic drug on its solubility in lipid excipients and an attempt was made to explore the role of each component of self-microemulsifying drug delivery systems in the formation of stable microemulsion upon dilution.

Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering.

PubMed

Shi, Jian-Yu; Yiu, Siu-Ming; Li, Yiming; Leung, Henry C M; Chin, Francis Y L

2015-07-15

Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there are two shortcomings that have not yet been addressed appropriately. Firstly, most of the methods only use 2D chemical structures and protein sequences to measure the similarity of drugs and targets respectively. However, this information may not fully capture the characteristics determining whether a drug will interact with a target. Secondly, there are very few known interactions, i.e. many interactions are "missing" in the database. Existing approaches are biased towards known interactions and have no good solutions to handle possibly missing interactions which affect the accuracy of the prediction. In this paper, we enhance the similarity measures to include non-structural (and non-sequence-based) information and introduce the concept of a "super-target" to handle the problem of possibly missing interactions. Based on evaluations on real data, we show that our similarity measure is better than the existing measures and our approach is able to achieve higher accuracy than the two best existing algorithms, WNN-GIP and KBMF2K. Our approach is available at http://web.hku.hk/∼liym1018/projects/drug/drug.html or http://www.bmlnwpu.org/us/tools/PredictingDTI_S2/METHODS.html. Copyright © 2015 Elsevier Inc. All rights reserved.

Correlation of HIV protease structure with Indinavir resistance: a data mining and neural networks approach

NASA Astrophysics Data System (ADS)

Draghici, Sorin; Cumberland, Lonnie T., Jr.; Kovari, Ladislau C.

2000-04-01

This paper presents some results of data mining HIV genotypic and structural data. Our aim is to try to relate structural features of HIV enzymes essential to its reproductive abilities to the drug resistance phenomenon. This paper concentrates on the HIV protease enzyme and Indinavir which is one of the FDA approved protease inhibitors. Our starting point was the current list of HIV mutations related to drug resistance. We used the fact that some molecular structures determined through high resolution X-ray crystallography were available for the protease-Indinavir complex. Starting with these structures and the known mutations, we modelled the mutant proteases and studied the pattern of atomic contacts between the protease and the drug. After suitable pre- processing, these patterns have been used as the input of our data mining process. We have used both supervised and unsupervised learning techniques with the aim of understanding the relationship between structural features at a molecular level and resistance to Indinavir. The supervised learning was aimed at predicting IC90 values for arbitrary mutants. The SOFM was aimed at identifying those structural features that are important for drug resistance and discovering a classifier based on such features. We have used validation and cross validation to test the generalization abilities of the learning paradigm we have designed. The straightforward supervised learning was able to learn very successfully but validation results are less than satisfactory. This is due to the insufficient number of patterns in the training set which in turn is due to the scarcity of the available data. The data mining using SOFM was very successful. We have managed to distinguish between resistant and non-resistant mutants using structural features. We have been able to divide all reported HIV mutants into several categories based on their 3- dimensional molecular structures and the pattern of contacts between the mutant protease and Indinavir. Our classifier shows reasonably good prediction performance being able to predict the drug resistance of previously unseen mutants with an accuracy of between 60% and 70%. We believe that this performance can be greatly improved once more data becomes available. The results presented here support the hypothesis that structural features of the molecular structure can be used in antiviral drug treatment selection and drug design.

Knowledge-based fragment binding prediction.

PubMed

Tang, Grace W; Altman, Russ B

2014-04-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening.

Knowledge-based Fragment Binding Prediction

PubMed Central

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

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.

Using the ribosome to synthesize peptidomimetics

PubMed Central

2009-01-01

Peptidomimetic research is an approach to identify peptide-based drugs designed to mimic structural, conformational, and biological properties of peptides while overcoming their limitations, such as protease instability and poor cell penetration. With recent advances in ribosomal synthesis of peptides containing unnatural amino acids, this technology appears suitable for preparing large structurally diverse libraries of peptidomimetics for drug discovery screening. PMID:20948631

Homology modeling and docking analyses of M. leprae Mur ligases reveals the common binding residues for structure based drug designing to eradicate leprosy.

PubMed

Shanmugam, Anusuya; Natarajan, Jeyakumar

2012-06-01

Multi drug resistance capacity for Mycobacterium leprae (MDR-Mle) demands the profound need for developing new anti-leprosy drugs. Since most of the drugs target a single enzyme, mutation in the active site renders the antibiotic ineffective. However, structural and mechanistic information on essential bacterial enzymes in a pathway could lead to the development of antibiotics that targets multiple enzymes. Peptidoglycan is an important component of the cell wall of M. leprae. The biosynthesis of bacterial peptidoglycan represents important targets for the development of new antibacterial drugs. Biosynthesis of peptidoglycan is a multi-step process that involves four key Mur ligase enzymes: MurC (EC:6.3.2.8), MurD (EC:6.3.2.9), MurE (EC:6.3.2.13) and MurF (EC:6.3.2.10). Hence in our work, we modeled the three-dimensional structure of the above Mur ligases using homology modeling method and analyzed its common binding features. The residues playing an important role in the catalytic activity of each of the Mur enzymes were predicted by docking these Mur ligases with their substrates and ATP. The conserved sequence motifs significant for ATP binding were predicted as the probable residues for structure based drug designing. Overall, the study was successful in listing significant and common binding residues of Mur enzymes in peptidoglycan pathway for multi targeted therapy.

A Structural View on Medicinal Chemistry Strategies against Drug Resistance.

PubMed

Agnello, Stefano; Brand, Michael; Chellat, Mathieu F; Gazzola, Silvia; Riedl, Rainer

2018-05-30

The natural phenomenon of drug resistance represents a generic impairment that hampers the benefits of drugs in all major clinical indications. Antibacterials and antifungals are affected as well as compounds for the treatment of cancer, viral infections or parasitic diseases. Despite the very diverse set of biological targets and organisms involved in the development of drug resistance, underlying molecular processes have been identified to understand the emergence of resistance and to overcome this detrimental mechanism. Detailed structural information of the root causes for drug resistance is nowadays frequently available to design next generation drugs anticipated to suffer less from resistance. This knowledge-based approach is a prerequisite in the fight against the inevitable occurrence of drug resistance to secure the achievements of medicinal chemistry in the future. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Social and structural aspects of the overdose risk environment in St. Petersburg, Russia.

PubMed

Green, Traci C; Grau, Lauretta E; Blinnikova, Ksenia N; Torban, Mikhail; Krupitsky, Evgeny; Ilyuk, Ruslan; Kozlov, Andrei; Heimer, Robert

2009-05-01

While overdose is a common cause of mortality among opioid injectors worldwide, little information exists on opioid overdoses or how context may influence overdose risk in Russia. This study sought to uncover social and structural aspects contributing to fatal overdose risk in St. Petersburg and assess prevention intervention feasibility. Twenty-one key informant interviews were conducted with drug users, treatment providers, toxicologists, police, and ambulance staff. Thematic coding of interview content was conducted to elucidate elements of the overdose risk environment. Several factors within St. Petersburg's environment were identified as shaping illicit drug users' risk behaviours and contributing to conditions of suboptimal response to overdose in the community. Most drug users live and experience overdoses at home, where family and home environment may mediate or moderate risk behaviours. The overdose risk environment is also worsened by inefficient emergency response infrastructure, insufficient cardiopulmonary or naloxone training resources, and the preponderance of abstinence-based treatment approaches to the exclusion of other treatment modalities. However, attitudes of drug users and law enforcement officials generally support overdose prevention intervention feasibility. Modifiable aspects of the risk environment suggest community-based and structural interventions, including overdose response training for drug users and professionals that encompasses naloxone distribution to the users and equipping more ambulances with naloxone. Local social and structural elements influence risk environments for overdose. Interventions at the community and structural levels to prevent and respond to opioid overdoses are needed for and integral to reducing overdose mortality in St. Petersburg.

Fragment-Based Drug Discovery Using NMR Spectroscopy

PubMed Central

Harner, Mary J.; Frank, Andreas O.; Fesik, Stephen W.

2013-01-01

Nuclear magnetic resonance (NMR) spectroscopy has evolved into a powerful tool for fragment-based drug discovery over the last two decades. While NMR has been traditionally used to elucidate the three-dimensional structures and dynamics of biomacromolecules and their interactions, it can also be a very valuable tool for the reliable identification of small molecules that bind to proteins and for hit-to-lead optimization. Here, we describe the use of NMR spectroscopy as a method for fragment-based drug discovery and how to most effectively utilize this approach for discovering novel therapeutics based on our experience. PMID:23686385

Structural basis for ligand recognition at the benzodiazepine binding site of GABAA alpha 3 receptor, and pharmacophore-based virtual screening approach.

PubMed

Vijayan, R S K; Ghoshal, Nanda

2008-10-01

Given the heterogeneity of GABA(A) receptor, the pharmacological significance of identifying subtype selective modulators is increasingly being recognized. Thus, drugs selective for GABA(A) alpha(3) receptors are expected to display fewer side effects than the drugs presently in clinical use. Hence we carried out 3D QSAR (three-dimensional quantitative structure-activity relationship) studies on a series of novel GABA(A) alpha(3) subtype selective modulators to gain more insight into subtype affinity. To identify the 3D functional attributes required for subtype selectivity, a chemical feature-based pharmacophore, primarily based on selective ligands representing diverse structural classes was generated. The obtained pseudo receptor model of the benzodiazepine binding site revealed a binding mode akin to "Message-Address" concept. Scaffold hopping was carried out across multi-conformational May Bridge database for the identification of novel chemotypes. Further a focused data reduction approach was employed to choose a subset of enriched compounds based on "Drug likeness" and "Similarity-based" methods. These results taken together could provide impetus for rational design and optimization of more selective and high affinity leads with a potential to have decreased adverse effects.

Structure-Based Virtual Screening for Drug Discovery: Principles, Applications and Recent Advances

PubMed Central

Lionta, Evanthia; Spyrou, George; Vassilatis, Demetrios K.; Cournia, Zoe

2014-01-01

Structure-based drug discovery (SBDD) is becoming an essential tool in assisting fast and cost-efficient lead discovery and optimization. The application of rational, structure-based drug design is proven to be more efficient than the traditional way of drug discovery since it aims to understand the molecular basis of a disease and utilizes the knowledge of the three-dimensional structure of the biological target in the process. In this review, we focus on the principles and applications of Virtual Screening (VS) within the context of SBDD and examine different procedures ranging from the initial stages of the process that include receptor and library pre-processing, to docking, scoring and post-processing of topscoring hits. Recent improvements in structure-based virtual screening (SBVS) efficiency through ensemble docking, induced fit and consensus docking are also discussed. The review highlights advances in the field within the framework of several success studies that have led to nM inhibition directly from VS and provides recent trends in library design as well as discusses limitations of the method. Applications of SBVS in the design of substrates for engineered proteins that enable the discovery of new metabolic and signal transduction pathways and the design of inhibitors of multifunctional proteins are also reviewed. Finally, we contribute two promising VS protocols recently developed by us that aim to increase inhibitor selectivity. In the first protocol, we describe the discovery of micromolar inhibitors through SBVS designed to inhibit the mutant H1047R PI3Kα kinase. Second, we discuss a strategy for the identification of selective binders for the RXRα nuclear receptor. In this protocol, a set of target structures is constructed for ensemble docking based on binding site shape characterization and clustering, aiming to enhance the hit rate of selective inhibitors for the desired protein target through the SBVS process. PMID:25262799

Chemical and protein structural basis for biological crosstalk between PPAR α and COX enzymes

NASA Astrophysics Data System (ADS)

Cleves, Ann E.; Jain, Ajay N.

2015-02-01

We have previously validated a probabilistic framework that combined computational approaches for predicting the biological activities of small molecule drugs. Molecule comparison methods included molecular structural similarity metrics and similarity computed from lexical analysis of text in drug package inserts. Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk. Considering those cases where the predicted target was an enzyme with known 3D structure allowed incorporation of information from molecular docking and protein binding pocket similarity in addition to ligand-based comparisons. Taken together, the combination of orthogonal information sources led to investigation of a surprising predicted relationship between a transcription factor and an enzyme, specifically, PPAR α and the cyclooxygenase enzymes. These predictions were confirmed by direct biochemical experiments which validate the approach and show for the first time that PPAR α agonists are cyclooxygenase inhibitors.

Development of 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, molecular docking, and structure-based pharmacophore approaches

EPA Science Inventory

Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligands bound, structure-based appr...

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.

Triclosan Derivatives: Towards Potent Inhibitors of Drug-Sensitive and Drug-Resistant Mycobacterium tuberculosis

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

Freundlich, Joel S.; Wang, Feng; Vilchèze, Catherine

Isoniazid (INH) is a frontline antitubercular drug that inhibits the enoyl acyl carrier protein reductase InhA. Novel inhibitors of InhA that are not cross-resistant to INH represent a significant goal in antitubercular chemotherapy. The design, synthesis, and biological activity of a series of triclosan-based inhibitors is reported, including their promising efficacy against INH-resistant strains of M. tuberculosis. Triclosan has been previously shown to inhibit InhA, an essential enoyl acyl carrier protein reductase involved in mycolic acid biosynthesis, the inhibition of which leads to the lysis of Mycobacterium tuberculosis. Using a structure-based drug design approach, a series of 5-substituted triclosan derivativesmore » was developed. Two groups of derivatives with alkyl and aryl substituents, respectively, were identified with dramatically enhanced potency against purified InhA. The most efficacious inhibitor displayed an IC{sub 50} value of 21 nM, which was 50-fold more potent than triclosan. X-ray crystal structures of InhA in complex with four triclosan derivatives revealed the structural basis for the inhibitory activity. Six selected triclosan derivatives were tested against isoniazid-sensitive and resistant strains of M. tuberculosis. Among those, the best inhibitor had an MIC value of 4.7 {mu}g mL{sup -1} (13 {mu}M), which represents a tenfold improvement over the bacteriocidal activity of triclosan. A subset of these triclosan analogues was more potent than isoniazid against two isoniazid-resistant M. tuberculosis strains, demonstrating the significant potential for structure-based design in the development of next generation antitubercular drugs.« less

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

PubMed Central

Moen, Spencer O.; Smith, Eric; Raymond, Amy C.; Fairman, James W.; Stewart, Lance J.; Staker, Bart L.; Begley, Darren W.; Edwards, Thomas E.; Lorimer, Donald D.

2013-01-01

Pandemic outbreaks of highly virulent influenza strains can cause widespread morbidity and mortality in human populations worldwide. In the United States alone, an average of 41,400 deaths and 1.86 million hospitalizations are caused by influenza virus infection each year 1. Point mutations in the polymerase basic protein 2 subunit (PB2) have been linked to the adaptation of the viral infection in humans 2. Findings from such studies have revealed the biological significance of PB2 as a virulence factor, thus highlighting its potential as an antiviral drug target. The structural genomics program put forth by the National Institute of Allergy and Infectious Disease (NIAID) provides funding to Emerald Bio and three other Pacific Northwest institutions that together make up the Seattle Structural Genomics Center for Infectious Disease (SSGCID). The SSGCID is dedicated to providing the scientific community with three-dimensional protein structures of NIAID category A-C pathogens. Making such structural information available to the scientific community serves to accelerate structure-based drug design. Structure-based drug design plays an important role in drug development. Pursuing multiple targets in parallel greatly increases the chance of success for new lead discovery by targeting a pathway or an entire protein family. Emerald Bio has developed a high-throughput, multi-target parallel processing pipeline (MTPP) for gene-to-structure determination to support the consortium. Here we describe the protocols used to determine the structure of the PB2 subunit from four different influenza A strains. PMID:23851357

Recent developments with metalloprotease inhibitor class of drug candidates for Botulinum neurotoxins

DOE PAGES

Kumar, Gyanendra; Swaminathan, Subramanyam

2015-03-01

Botulinum Neurotoxins are the most poisonous of all toxins with lethal dose in nanogram quantities. They are also potential biological warfare and bioterrorism agents due to their high toxicity and ease of preparation. On the other hand BoNTs are also being increasingly used for therapeutic and cosmetic purposes, and with that the chances of accidental overdose are increasing. And despite the potential damage they could cause to human health, there are no post-intoxication drugs available so far. But progress is being made in this direction. The crystal structures in native form and bound with substrate peptides have been determined, andmore » these are enabling structure-based drug discovery possible. High throughput assays have also been designed to speed up the screening progress. Substrate-based and small molecule inhibitors have been identified. But turning high affinity inhibitors into clinically viable drug candidates has remained a challenge. We discuss here the latest developments and the future challenges in drug discovery for Botulinum neurotoxins.« less

Recent developments with metalloprotease inhibitor class of drug candidates for botulinum neurotoxins.

PubMed

Kumar, Gyanendra; Swaminathan, Subramanyam

2015-01-01

Botulinum Neurotoxins are the most poisonous of all toxins with lethal dose in nanogram quantities. They are potential biological warfare and bioterrorism agents due to their high toxicity and ease of preparation. On the other hand BoNTs are also being increasingly used for therapeutic and cosmetic purposes, and with that the chances of accidental overdose are increasing. And despite the potential damage they could cause to human health, there are no post-intoxication drugs available so far. But progress is being made in this direction. The crystal structures in native form and bound with substrate peptides have been determined, and these are enabling structure-based drug discovery possible. High throughput assays have also been designed to speed up the screening progress. Substrate-based and small molecule inhibitors have been identified. But turning high affinity inhibitors into clinically viable drug candidates has remained a challenge. We discuss here the latest developments and the future challenges in drug discovery for Botulinum neurotoxins.

Nanofibers based tissue engineering and drug delivery approaches for myocardial regeneration.

PubMed

Joshi, Jyotsna; Kothapalli, Chandrasekhar R

2015-01-01

Human heart has endogenous regenerative capability; however, the intrinsic repair mechanism is not sufficient to overcome the impact placed by adverse pathological conditions, such as myocardial infarction (MI). In such circumstances, the damaged tissue initiates a series of remodeling process which results in the deterioration of structural, functional, and mechanical properties of the myocardium. To address such adverse conditions, clinical approaches ranging from surgical interventions, pharmaceutical drugs, and device implantation are administered which have played significant role in reducing the mortality rate. However, these approaches do not replace the lost cardiomyocytes, or restore the degraded structure-function relationship of the myocardium. In this aspect, cell-based therapy has gained substantial interest as a potential clinical approach for myocardial regeneration; however this method is impeded by lower graft retention and poor cell viability. To overcome these limitations, biomaterials are being developed as "trojan horses", i.e., vehicles for homing and deploying cells, and as matrices for delivering specific biological, mechanical, and chemical cues intended for tissue regeneration. Similarly, several candidate drugs, potent synthetic and biological molecules, and advanced drug delivery systems are being examined to provide exogenous cues in a controlled fashion to the diseased myocardium. In this article, we review biomaterials-based drug delivery systems for myocardial regeneration, specifically on the applications of hydrogels, microgels, nanoparticles, and nanofibers in the field. The prime focus of the article is on nanofibers-based drug delivery systems that is gaining considerable attention as a biomimetic pharmacological approach. We highlight literature on fabrication methods of self-assembling and electrospun nanofibers, drug incorporation methods and release kinetics, and in vitro and in vivo outcomes from nanofiber-based drug delivery systems in cardiac regeneration.

Application of Various Types of Liposomes in Drug Delivery Systems

PubMed Central

Alavi, Mehran; Karimi, Naser; Safaei, Mohsen

2017-01-01

Liposomes, due to their various forms, require further exploration. These structures can deliver both hydrophilic and hydrophobic drugs for cancer, antibacterial, antifungal, immunomodulation, diagnostics, ophtalmica, vaccines, enzymes and genetic elements. Preparation of liposomes results in different properties for these systems. In addition, based on preparation methods, liposomes types can be unilamellar, multilamellar and giant unilamellar; however, there are many factors and difficulties that affect the development of liposome drug delivery structure. In the present review, we discuss some problems that impact drug delivery by liposomes. In addition, we discuss a new generation of liposomes, which is utilized for decreasing the limitation of the conventional liposomes. PMID:28507932

Receptor-based 3D-QSAR in Drug Design: Methods and Applications in Kinase Studies.

PubMed

Fang, Cheng; Xiao, Zhiyan

2016-01-01

Receptor-based 3D-QSAR strategy represents a superior integration of structure-based drug design (SBDD) and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. It combines the accurate prediction of ligand poses by the SBDD approach with the good predictability and interpretability of statistical models derived from the 3D-QSAR approach. Extensive efforts have been devoted to the development of receptor-based 3D-QSAR methods and two alternative approaches have been exploited. One associates with computing the binding interactions between a receptor and a ligand to generate structure-based descriptors for QSAR analyses. The other concerns the application of various docking protocols to generate optimal ligand poses so as to provide reliable molecular alignments for the conventional 3D-QSAR operations. This review highlights new concepts and methodologies recently developed in the field of receptorbased 3D-QSAR, and in particular, covers its application in kinase studies.

Preparation of ionic-crosslinked chitosan-based gel beads and effect of reaction conditions on drug release behaviors.

PubMed

Chen, Shilan; Liu, Mingzhu; Jin, Shuping; Wang, Bin

2008-02-12

Drug-loaded chitosan (CS) beads were prepared under simple and mild condition using trisodium citrate as ionic crosslinker. The beads were further coated with poly(methacrylic acid) (PMAA) by dipping the beads in PMAA aqueous solution. The surface and cross-section morphology of these beads were observed by scanning electron microscopy and the observation showed that the coating beads had core-shell structure. In vitro release of model drug from these beads obtained under different reaction conditions was investigated in buffer medium (pH 1.8). The results showed that the rapid drug release was restrained by PMAA coating and the optimum conditions for preparing CS-based drug-loaded beads were decided through the effect of reaction conditions on the drug release behaviors. In addition, the drug release mechanism of CS-based drug-loaded beads was analyzed by Peppa's potential equation. According to this study, the ionic-crosslinked CS beads coated by PMAA could serve as suitable candidate for drug site-specific carrier in stomach.

Too Good for Drugs[TM]. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2006

2006-01-01

"Too Good for Drugs"[TM] is designed to promote life skills, character values, resistance skills to negative peer influence, and resistance to the use of illegal drugs, alcohol, and tobacco. The program, which targets elementary and middle school students, is based on classroom discussions and structured activities that center on…

Antiviral agents: structural basis of action and rational design.

PubMed

Menéndez-Arias, Luis; Gago, Federico

2013-01-01

During the last 30 years, significant progress has been made in the development of novel antiviral drugs, mainly crystallizing in the establishment of potent antiretroviral therapies and the approval of drugs inhibiting hepatitis C virus replication. Although major targets of antiviral intervention involve intracellular processes required for the synthesis of viral proteins and nucleic acids, a number of inhibitors blocking virus assembly, budding, maturation, entry or uncoating act on virions or viral capsids. In this review, we focus on the drug discovery process while presenting the currently used methodologies to identify novel antiviral drugs by using a computer-based approach. We provide examples illustrating structure-based antiviral drug development, specifically neuraminidase inhibitors against influenza virus (e.g. oseltamivir and zanamivir) and human immunodeficiency virus type 1 protease inhibitors (i.e. the development of darunavir from early peptidomimetic compounds such as saquinavir). A number of drugs in preclinical development acting against picornaviruses, hepatitis B virus and human immunodeficiency virus and their mechanism of action are presented to show how viral capsids can be exploited as targets of antiviral therapy.

Updates on drug-target network; facilitating polypharmacology and data integration by growth of DrugBank database.

PubMed

Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi

2016-11-01

Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Ensemble-based docking: From hit discovery to metabolism and toxicity predictions.

PubMed

Evangelista, Wilfredo; Weir, Rebecca L; Ellingson, Sally R; Harris, Jason B; Kapoor, Karan; Smith, Jeremy C; Baudry, Jerome

2016-10-15

This paper describes and illustrates the use of ensemble-based docking, i.e., using a collection of protein structures in docking calculations for hit discovery, the exploration of biochemical pathways and toxicity prediction of drug candidates. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials. Copyright © 2016 Elsevier Ltd. All rights reserved.

Leveraging structure determination with fragment screening for infectious disease drug targets: MECP synthase from Burkholderia pseudomallei

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

Begley, Darren W.; Hartley, Robert C.; Davies, Douglas R.

As part of the Seattle Structural Genomics Center for Infectious Disease, we seek to enhance structural genomics with ligand-bound structure data which can serve as a blueprint for structure-based drug design. We have adapted fragment-based screening methods to our structural genomics pipeline to generate multiple ligand-bound structures of high priority drug targets from pathogenic organisms. In this study, we report fragment screening methods and structure determination results for 2C-methyl-D-erythritol-2,4-cyclo-diphosphate (MECP) synthase from Burkholderia pseudomallei, the gram-negative bacterium which causes melioidosis. Screening by nuclear magnetic resonance spectroscopy as well as crystal soaking followed by X-ray diffraction led to the identification ofmore » several small molecules which bind this enzyme in a critical metabolic pathway. A series of complex structures obtained with screening hits reveal distinct binding pockets and a range of small molecules which form complexes with the target. Additional soaks with these compounds further demonstrate a subset of fragments to only bind the protein when present in specific combinations. This ensemble of fragment-bound complexes illuminates several characteristics of MECP synthase, including a previously unknown binding surface external to the catalytic active site. These ligand-bound structures now serve to guide medicinal chemists and structural biologists in rational design of novel inhibitors for this enzyme.« less

The right drug, but from whose perspective? A framework for analysing the structure and activities of drug and therapeutics committees.

PubMed

Hoffmann, Mikael

2013-05-01

During the last five decades drug and therapeutics committees (DTCs), have evolved from mainly hospital-based groups of experts in pharmacotherapy and drug logistics into an arena for healthcare professionals employing evidence-based methods of promoting rational drug use. The purpose of this study was to suggest a framework for analysing the structure and activities of DTCs. A literature search was carried out in the Medline, Cinahl and Web of Sciences databases for the period 1993-2012. A total of 207 articles were included. Based on these articles a framework for the analysis of the DTCs based on the role of the DTC, target groups, budget perspective and type of economic decisions could be suggested. In order to respond to future demands the DTCs will have to develop their skill in pharmacoeconomics. Their processes will have to be standardised and made more transparent in order to be better adapted to evidence-based decision-making. They will also have to embrace the possibilities created by electronic health records in both influencing the decisions of physicians, and in improving quality assurance programmes and longitudinal follow-up of drug therapy and outcomes. They will have to find new ways of interacting with the public and policy makers in order to get the resources needed for their work. Finally, they will have to handle the conflict among national, regional and local decision-making processes and the relationship between formularies and therapeutic guidelines.

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

Kumar, Gyanendra; Swaminathan, Subramanyam

Botulinum Neurotoxins are the most poisonous of all toxins with lethal dose in nanogram quantities. They are also potential biological warfare and bioterrorism agents due to their high toxicity and ease of preparation. On the other hand BoNTs are also being increasingly used for therapeutic and cosmetic purposes, and with that the chances of accidental overdose are increasing. And despite the potential damage they could cause to human health, there are no post-intoxication drugs available so far. But progress is being made in this direction. The crystal structures in native form and bound with substrate peptides have been determined, andmore » these are enabling structure-based drug discovery possible. High throughput assays have also been designed to speed up the screening progress. Substrate-based and small molecule inhibitors have been identified. But turning high affinity inhibitors into clinically viable drug candidates has remained a challenge. We discuss here the latest developments and the future challenges in drug discovery for Botulinum neurotoxins.« less

Nucleic acid binding drugs. Part XIII. Molecular motion in a drug-nucleic acid model system: thermal motion analysis of a proflavine-dinucleoside crystal structure.

PubMed Central

Aggarwal, A K; Neidle, S

1985-01-01

The high-resolution crystal structure of the intercalation complex between proflavine and cytidylyl-3',5'-guanosine (CpG) has been studied by thermalmotion analysis. This has provided information on the translational and librational motions of individual groups in the complex. Many of these motions are similar to, though of larger magnitude than in uncomplexed dinucleosides. Pronounced librational effects were observed along the base pairs and in the plane of the drug chromophore. PMID:4034394

Computer aided drug design

NASA Astrophysics Data System (ADS)

Jain, A.

2017-08-01

Computer based method can help in discovery of leads and can potentially eliminate chemical synthesis and screening of many irrelevant compounds, and in this way, it save time as well as cost. Molecular modeling systems are powerful tools for building, visualizing, analyzing and storing models of complex molecular structure that can help to interpretate structure activity relationship. The use of various techniques of molecular mechanics and dynamics and software in Computer aided drug design along with statistics analysis is powerful tool for the medicinal chemistry to synthesis therapeutic and effective drugs with minimum side effect.

Phenylpyrrolidine structural mimics of pirfenidone lacking antifibrotic activity: A new tool for mechanism of action studies.

PubMed

Haak, Andrew J; Girtman, Megan A; Ali, Mohamed F; Carmona, Eva M; Limper, Andrew H; Tschumperlin, Daniel J

2017-09-15

Pirfenidone recently received FDA approval as one of the first two drugs designed to treat idiopathic pulmonary fibrosis. While the clinical data continues to support the efficacy of pirfenidone, the specific molecular mechanism of action of this drug has not been fully defined. From a chemical perspective the comparatively simple and lipophilic structure of pirfenidone combined with its administration at high doses, both experimentally and clinically, complicates some of the basic tenants of drug action and drug design. Our objective here was to identify a commercially available structural mimic of pirfenidone which retains key aspects of its physical chemical properties but does not display any of its antifibrotic effects. We tested these molecules using lung fibroblasts derived from patients with idiopathic pulmonary fibrosis and found phenylpyrrolidine based analogs of pirfenidone that were non-toxic and lacked antifibrotic activity even when applied at millimolar concentrations. Based on our findings, these molecules represent pharmacological tools for future studies delineating pirfenidone's mechanism of action. Copyright © 2017 Elsevier B.V. All rights reserved.

Ligand Binding Site Detection by Local Structure Alignment and Its Performance Complementarity

PubMed Central

Lee, Hui Sun; Im, Wonpil

2013-01-01

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is a room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands’ positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a non-template geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy. The G-LoSA source code is freely available at http://im.bioinformatics.ku.edu/GLoSA. PMID:23957286

Alkaloids and leishmania donovani UDP-galactopyarnose mutase: Anovel approach in drug designing against Visceral leishmaniasis.

PubMed

Srivastava, Ankita; Chandra, Deepak

2017-06-05

The unsatisfactory treatment options for Visceral Leishmaniasis (VL), needs identification of new drug targets. Among natural products, Alkaloids have been proved to be highly effective against number of diseases. In Leishmania UDP-galactopyranose mutase (UGM) is a critical enzyme required for cell wall synthesis and thus a drug target for structure based drug designing against L. donovani. To build the homology model of UDP galactopyranse mutase and investigate the interaction of selected alkaloids with this modeled UDP galactopyranose mutase by molecular docking. Since there is no crystal structure record has been found with this protein, a homology modeling was performed and a three dimensional structure of L. donovani UGM was created using MODELLER v9.9, structure quality was validated using PROCHECK and QMEAN programs which confirms that the structure is reliable. Further Molecular docking was performed with previously reported 15 alkaloids. It was found that Protopine shows a binding energy of -12.39Kcal/mole, binds at Flavin adenine dinucleotide (FAD) biding site. Concluding that Protopine, an alkaloid could interrupt the functional aspect of L. donovani UGM and thus may be useful for drug designing studies. These finding would contribute to the understanding of effect of drug on the parasite. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Structures of Pseudomonas aeruginosa β-ketoacyl-(acyl-carrier-protein) synthase II (FabF) and a C164Q mutant provide templates for antibacterial drug discovery and identify a buried potassium ion and a ligand-binding site that is an artefact of the crystal form

PubMed Central

Baum, Bernhard; Lecker, Laura S. M.; Zoltner, Martin; Jaenicke, Elmar; Schnell, Robert; Hunter, William N.; Brenk, Ruth

2015-01-01

Bacterial infections remain a serious health concern, in particular causing life-threatening infections of hospitalized and immunocompromised patients. The situation is exacerbated by the rise in antibacterial drug resistance, and new treatments are urgently sought. In this endeavour, accurate structures of molecular targets can support early-stage drug discovery. Here, crystal structures, in three distinct forms, of recombinant Pseudomonas aeruginosa β-ketoacyl-(acyl-carrier-protein) synthase II (FabF) are presented. This enzyme, which is involved in fatty-acid biosynthesis, has been validated by genetic and chemical means as an antibiotic target in Gram-positive bacteria and represents a potential target in Gram-negative bacteria. The structures of apo FabF, of a C164Q mutant in which the binding site is altered to resemble the substrate-bound state and of a complex with 3-(benzoylamino)-2-hydroxybenzoic acid are reported. This compound mimics aspects of a known natural product inhibitor, platensimycin, and surprisingly was observed binding outside the active site, interacting with a symmetry-related molecule. An unusual feature is a completely buried potassium-binding site that was identified in all three structures. Comparisons suggest that this may represent a conserved structural feature of FabF relevant to fold stability. The new structures provide templates for structure-based ligand design and, together with the protocols and reagents, may underpin a target-based drug-discovery project for urgently needed antibacterials. PMID:26249693

An integrated structure- and system-based framework to identify new targets of metabolites and known drugs

PubMed Central

Naveed, Hammad; Hameed, Umar S.; Harrus, Deborah; Bourguet, William; Arold, Stefan T.; Gao, Xin

2015-01-01

Motivation: The inherent promiscuity of small molecules towards protein targets impedes our understanding of healthy versus diseased metabolism. This promiscuity also poses a challenge for the pharmaceutical industry as identifying all protein targets is important to assess (side) effects and repositioning opportunities for a drug. Results: Here, we present a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to enable the large-scale discovery of new targets for small molecules, such as pharmaceutical drugs, co-factors and metabolites (collectively called ‘drugs’). For a given drug, our method uses sequence order–independent structure alignment, hierarchical clustering and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets. A drug’s PPE is combined with an approximation of its delivery profile to reduce false positives. In our cross-validation study, we use iDTP to predict the known targets of 11 drugs, with 63% sensitivity and 81% specificity. We then predicted novel targets for these drugs—two that are of high pharmacological interest, the peroxisome proliferator-activated receptor gamma and the oncogene B-cell lymphoma 2, were successfully validated through in vitro binding experiments. Our method is broadly applicable for the prediction of protein-small molecule interactions with several novel applications to biological research and drug development. Availability and implementation: The program, datasets and results are freely available to academic users at http://sfb.kaust.edu.sa/Pages/Software.aspx. Contact: xin.gao@kaust.edu.sa and stefan.arold@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26286808

Structure-based assessment of disease-related mutations in human voltage-gated sodium channels.

PubMed

Huang, Weiyun; Liu, Minhao; Yan, S Frank; Yan, Nieng

2017-06-01

Voltage-gated sodium (Na v ) channels are essential for the rapid upstroke of action potentials and the propagation of electrical signals in nerves and muscles. Defects of Na v channels are associated with a variety of channelopathies. More than 1000 disease-related mutations have been identified in Na v channels, with Na v 1.1 and Na v 1.5 each harboring more than 400 mutations. Na v channels represent major targets for a wide array of neurotoxins and drugs. Atomic structures of Na v channels are required to understand their function and disease mechanisms. The recently determined atomic structure of the rabbit voltage-gated calcium (Ca v ) channel Ca v 1.1 provides a template for homology-based structural modeling of the evolutionarily related Na v channels. In this Resource article, we summarized all the reported disease-related mutations in human Na v channels, generated a homologous model of human Na v 1.7, and structurally mapped disease-associated mutations. Before the determination of structures of human Na v channels, the analysis presented here serves as the base framework for mechanistic investigation of Na v channelopathies and for potential structure-based drug discovery.

Local anesthetic and antiepileptic drug access and binding to a bacterial voltage-gated sodium channel

PubMed Central

Boiteux, Céline; Vorobyov, Igor; French, Robert J.; French, Christopher; Yarov-Yarovoy, Vladimir; Allen, Toby W.

2014-01-01

Voltage-gated sodium (Nav) channels are important targets in the treatment of a range of pathologies. Bacterial channels, for which crystal structures have been solved, exhibit modulation by local anesthetic and anti-epileptic agents, allowing molecular-level investigations into sodium channel-drug interactions. These structures reveal no basis for the “hinged lid”-based fast inactivation, seen in eukaryotic Nav channels. Thus, they enable examination of potential mechanisms of use- or state-dependent drug action based on activation gating, or slower pore-based inactivation processes. Multimicrosecond simulations of NavAb reveal high-affinity binding of benzocaine to F203 that is a surrogate for FS6, conserved in helix S6 of Domain IV of mammalian sodium channels, as well as low-affinity sites suggested to stabilize different states of the channel. Phenytoin exhibits a different binding distribution owing to preferential interactions at the membrane and water–protein interfaces. Two drug-access pathways into the pore are observed: via lateral fenestrations connecting to the membrane lipid phase, as well as via an aqueous pathway through the intracellular activation gate, despite being closed. These observations provide insight into drug modulation that will guide further developments of Nav inhibitors. PMID:25136136

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

PubMed

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

2018-03-13

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

Structures of Pseudomonas aeruginosa β-ketoacyl-(acyl-carrier-protein) synthase II (FabF) and a C164Q mutant provide templates for antibacterial drug discovery and identify a buried potassium ion and a ligand-binding site that is an artefact of the crystal form

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

Baum, Bernhard; Lecker, Laura S. M.; Zoltner, Martin

Three crystal structures of recombinant P. aeruginosa FabF are reported: the apoenzyme, an active-site mutant and a complex with a fragment of a natural product inhibitor. The characterization provides reagents and new information to support antibacterial drug discovery. Bacterial infections remain a serious health concern, in particular causing life-threatening infections of hospitalized and immunocompromised patients. The situation is exacerbated by the rise in antibacterial drug resistance, and new treatments are urgently sought. In this endeavour, accurate structures of molecular targets can support early-stage drug discovery. Here, crystal structures, in three distinct forms, of recombinant Pseudomonas aeruginosa β-ketoacyl-(acyl-carrier-protein) synthase II (FabF)more » are presented. This enzyme, which is involved in fatty-acid biosynthesis, has been validated by genetic and chemical means as an antibiotic target in Gram-positive bacteria and represents a potential target in Gram-negative bacteria. The structures of apo FabF, of a C164Q mutant in which the binding site is altered to resemble the substrate-bound state and of a complex with 3-(benzoylamino)-2-hydroxybenzoic acid are reported. This compound mimics aspects of a known natural product inhibitor, platensimycin, and surprisingly was observed binding outside the active site, interacting with a symmetry-related molecule. An unusual feature is a completely buried potassium-binding site that was identified in all three structures. Comparisons suggest that this may represent a conserved structural feature of FabF relevant to fold stability. The new structures provide templates for structure-based ligand design and, together with the protocols and reagents, may underpin a target-based drug-discovery project for urgently needed antibacterials.« less

Predicting drug side-effect profiles: a chemical fragment-based approach

PubMed Central

2011-01-01

Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169

Development of a 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, docking, and structure-based pharmacophore approaches - Conference Abstract

EPA Science Inventory

Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligands bound, structure-based appr...

Smart drug release systems based on stimuli-responsive polymers.

PubMed

Qing, Guangyan; Li, Minmin; Deng, Lijing; Lv, Ziyu; Ding, Peng; Sun, Taolei

2013-07-01

Stimuli-responsive polymers could respond to external stimuli, such as temperature, pH, photo-irradiation, electric field, biomolecules in solution, etc., which further induce reversible transformations in the structures and conformations of polymers, providing an excellent platform for controllable drug release, while the accuracy of drug delivery could obtain obvious improvement in this system. In this review, recent progresses in the drug release systems based on stimuli-responsive polymers are summarized, in which drugs can be released in an intelligent mode with high accuracy and efficiency, while potential damages to normal cells and tissues can also be effectively prevented owing to the unique characteristics of materials. Moreover, we introduce some smart nanoparticles-polymers conjugates and drug release devices, which are especially suitable for the long-term sustained drug release.

Current progress in Structure-Based Rational Drug Design marks a new mindset in drug discovery

PubMed Central

Lounnas, Valère; Ritschel, Tina; Kelder, Jan; McGuire, Ross; Bywater, Robert P.; Foloppe, Nicolas

2013-01-01

The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented. PMID:24688704

Ozonation of wastewater: removal and transformation products of drugs of abuse.

PubMed

Rodayan, Angela; Segura, Pedro Alejandro; Yargeau, Viviane

2014-07-15

In this study amphetamine, methamphetamine, methylenedioxymethamphetamine (MDMA), cocaine (COC), benzoylecgonine (BE), ketamine (KET) and oxycodone (OXY) in wastewater at concentrations of 100 μgL(-1) were subjected to ozone to determine their removals as a function of ozone dose and to identify significant oxidation transformation products (OTPs) produced as a result of ozonation. A method based on high resolution mass spectrometry and differential analysis was used to facilitate and accelerate the identification and structural elucidation of the transformation products. The drug removal ranged from 3 to 50% depending on the complexity of the matrix and whether a mixture or individual drugs were ozonated. Both transient and persistent oxidation transformation products were identified for MDMA, COC and OXY and their chemical formulae were determined. Three possible structures of the persistent transformation product of MDMA (OTP-213) with chemical formula C10H16O4N, were determined based on MS(n) mass spectra and the most plausible structure (OTP-213a) was determined based on the chemistry of ozone. These results indicate that ozone is capable of removing drugs of abuse from wastewater to varying extents and that persistent transformation products are produced as a result of treatment. Copyright © 2013 Elsevier B.V. All rights reserved.

Structure and Ligand Based Drug Design Strategies in the Development of Novel 5-LOX Inhibitors

PubMed Central

Aparoy, Polamarasetty; Kumar Reddy, Kakularam; Reddanna, Pallu

2012-01-01

Lipoxygenases (LOXs) are non-heme iron containing dioxygenases involved in the oxygenation of polyunsaturated fatty acids (PUFAs) such as arachidonic acid (AA). Depending on the position of insertion of oxygen, LOXs are classified into 5-, 8-, 9-, 12- and 15-LOX. Among these, 5-LOX is the most predominant isoform associated with the formation of 5-hydroperoxyeicosatetraenoic acid (5-HpETE), the precursor of non-peptido (LTB4) and peptido (LTC4, LTD4, and LTE4) leukotrienes. LTs are involved in inflammatory and allergic diseases like asthma, ulcerative colitis, rhinitis and also in cancer. Consequently 5-LOX has become target for the development of therapeutic molecules for treatment of various inflammatory disorders. Zileuton is one such inhibitor of 5-LOX approved for the treatment of asthma. In the recent times, computer aided drug design (CADD) strategies have been applied successfully in drug development processes. A comprehensive review on structure based drug design strategies in the development of novel 5-LOX inhibitors is presented in this article. Since the crystal structure of 5-LOX has been recently solved, efforts to develop 5-LOX inhibitors have mostly relied on ligand based rational approaches. The present review provides a comprehensive survey on these strategies in the development of 5-LOX inhibitors. PMID:22680930

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

Modeling the full length HIV-1 Gag polyprotein reveals the role of its p6 subunit in viral maturation and the effect of non-cleavage site mutations in protease drug resistance.

PubMed

Su, Chinh Tran-To; Kwoh, Chee-Keong; Verma, Chandra Shekhar; Gan, Samuel Ken-En

2017-12-27

HIV polyprotein Gag is increasingly found to contribute to protease inhibitor resistance. Despite its role in viral maturation and in developing drug resistance, there remain gaps in the knowledge of the role of certain Gag subunits (e.g. p6), and that of non-cleavage mutations in drug resistance. As p6 is flexible, it poses a problem for structural experiments, and is hence often omitted in experimental Gag structural studies. Nonetheless, as p6 is an indispensable component for viral assembly and maturation, we have modeled the full length Gag structure based on several experimentally determined constraints and studied its structural dynamics. Our findings suggest that p6 can mechanistically modulate Gag conformations. In addition, the full length Gag model reveals that allosteric communication between the non-cleavage site mutations and the first Gag cleavage site could possibly result in protease drug resistance, particularly in the absence of mutations in Gag cleavage sites. Our study provides a mechanistic understanding to the structural dynamics of HIV-1 Gag, and also proposes p6 as a possible drug target in anti-HIV therapy.

Mass Spectrometry Imaging of Drug Related Crystal-Like Structures in Formalin-Fixed Frozen and Paraffin-Embedded Rabbit Kidney Tissue Sections

NASA Astrophysics Data System (ADS)

Bruinen, Anne L.; van Oevelen, Cateau; Eijkel, Gert B.; Van Heerden, Marjolein; Cuyckens, Filip; Heeren, Ron M. A.

2016-01-01

A multimodal mass spectrometry imaging (MSI) based approach was used to characterize the molecular content of crystal-like structures in a frozen and paraffin embedded piece of a formalin-fixed rabbit kidney. Matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) imaging and desorption electrospray ionization (DESI) mass spectrometry imaging were combined to analyze the frozen and paraffin embedded sample without further preparation steps to remove the paraffin. The investigated rabbit kidney was part of a study on a drug compound in development, in which severe renal toxicity was observed in dosed rabbits. Histological examination of the kidney showed tubular degeneration with precipitation of crystal-like structures in the cortex, which were assumed to cause the renal toxicity. The MS imaging approach was used to find out whether the crystal-like structures were composed of the drug compound, metabolites, or an endogenous compound as a reaction to the drug administration. The generated MALDI-MSI data were analyzed using principal component analysis. In combination with the MS/MS results, this way of data processing demonstrates that the crystal structures were mainly composed of metabolites and relatively little parent drug.

Diffusion-Based Design of Multi-Layered Ophthalmic Lenses for Controlled Drug Release

PubMed Central

Pimenta, Andreia F. R.; Serro, Ana Paula; Paradiso, Patrizia; Saramago, Benilde

2016-01-01

The study of ocular drug delivery systems has been one of the most covered topics in drug delivery research. One potential drug carrier solution is the use of materials that are already commercially available in ophthalmic lenses for the correction of refractive errors. In this study, we present a diffusion-based mathematical model in which the parameters can be adjusted based on experimental results obtained under controlled conditions. The model allows for the design of multi-layered therapeutic ophthalmic lenses for controlled drug delivery. We show that the proper combination of materials with adequate drug diffusion coefficients, thicknesses and interfacial transport characteristics allows for the control of the delivery of drugs from multi-layered ophthalmic lenses, such that drug bursts can be minimized, and the release time can be maximized. As far as we know, this combination of a mathematical modelling approach with experimental validation of non-constant activity source lamellar structures, made of layers of different materials, accounting for the interface resistance to the drug diffusion, is a novel approach to the design of drug loaded multi-layered contact lenses. PMID:27936138

Drug-Drug Multicomponent Solid Forms: Cocrystal, Coamorphous and Eutectic of Three Poorly Soluble Antihypertensive Drugs Using Mechanochemical Approach.

PubMed

Haneef, Jamshed; Chadha, Renu

2017-08-01

The present study deals with the application of mechanochemical approach for the preparation of drug-drug multicomponent solid forms of three poorly soluble antihypertensive drugs (telmisartan, irbesartan and hydrochlorothiazide) using atenolol as a coformer. The resultant solid forms comprise of cocrystal (telmisartan-atenolol), coamorphous (irbesartan-atenolol) and eutectic (hydrochlorothiazide-atenolol). The study emphasizes that solid-state transformation of drug molecules into new forms is a result of the change in structural patterns, diminishing of dimers and creating new facile hydrogen bonding network based on structural resemblance. The propensity for heteromeric or homomeric interaction between two different drugs resulted into diverse solid forms (cocrystal/coamorphous/eutectics) and become one of the interesting aspects of this research work. Evaluation of these solid forms revealed an increase in solubility and dissolution leading to better antihypertensive activity in deoxycorticosterone acetate (DOCA) salt-induced animal model. Thus, development of these drug-drug multicomponent solid forms is a promising and viable approach to addressing the issue of poor solubility and could be of considerable interest in dual drug therapy for the treatment of hypertension.

Social and structural aspects of the overdose risk environment in St. Petersburg, Russia

PubMed Central

Grau, Lauretta E.; Blinnikova, Ksenia N.; Torban, Mikhail; Krupitsky, Evgeny; Ilyuk, Ruslan; Kozlov, Andrei; Heimer, Robert

2009-01-01

Background While overdose is a common cause of mortality among opioid injectors worldwide, little information exists on opioid overdoses or how context may influence overdose risk in Russia. This study sought to uncover social and structural aspects contributing to fatal overdose risk in St. Petersburg and assess prevention intervention feasibility. Methods Twenty-one key informant interviews were conducted with drug users, treatment providers, toxicologists, police, and ambulance staff. Thematic coding of interview content was conducted to elucidate elements of the overdose risk environment. Results Several factors within St. Petersburg’s environment were identified as shaping illicit drug users’ risk behaviors and contributing to conditions of suboptimal response to overdose in the community. Most drug users live and experience overdoses at home, where family and home environment may mediate or moderate risk behaviors. The overdose risk environment is also worsened by inefficient emergency response infrastructure, insufficient cardiopulmonary or naloxone training resources, and the preponderance of abstinence-based treatment approaches to the exclusion of other treatment modalities. However, attitudes of drug users and law enforcement officials generally support overdose prevention intervention feasibility. Modifiable aspects of the risk environment suggest community-based and structural interventions, including overdose response training for drug users and professionals that encompasses naloxone distribution to the users and equipping more ambulances with naloxone. Conclusion Local social and structural elements influence risk environments for overdose. Interventions at the community and structural levels to prevent and respond to opioid overdoses are needed for and integral to reducing overdose mortality in St. Petersburg. PMID:18774283

A New Carbon Nanotube-Based Breast Cancer Drug Delivery System: Preparation and In Vitro Analysis Using Paclitaxel.

PubMed

Shao, Wei; Paul, Arghya; Rodes, Laetitia; Prakash, Satya

2015-04-01

Paclitaxel (PTX) is one of the most important drugs for breast cancer; however, the drug effects are limited by its systematic toxicity and poor water solubility. Nanoparticles have been applied for delivery of cancer drugs to overcome their limitations. Toward this goal, a novel single-walled carbon nanotube (SWNT)-based drug delivery system was developed by conjugation of human serum albumin (HSA) nanoparticles for loading of antitumor agent PTX. The nanosized macromolecular SWNT-drug carrier (SWNT-HSA) was characterized by TEM, UV-Vis-NIR spectrometry, and TGA. The SWNT-based drug carrier displayed high intracellular delivery efficiency (cell uptake rate of 80%) in breast cancer MCF-7 cells, as examined by fluorescence-labeled drug carriers, suggesting the needle-shaped SWNT-HSA drug carrier was able to transport drugs across cell membrane despite its macromolecular structure. The drug loading on SWNT-based drug carrier was through high binding affinity of PTX to HSA proteins. The PTX formulated with SWNT-HSA showed greater growth inhibition activity in MCF-7 breast cancer cells than PTX formulated with HSA nanoparticle only (cell viability of 63 vs 70% in 48 h and 53 vs 62% in 72 h). The increased drug efficacy could be driven by SWNT-mediated cell internalization. These data suggest that the developed SWNT-based antitumor agent is functional and effective. However, more studies for in vivo drug delivery efficacy and other properties are needed before this delivery system can be fully realized.

Chitosan based hydrogels: characteristics and pharmaceutical applications

PubMed Central

Ahmadi, F.; Oveisi, Z.; Samani, S. Mohammadi; Amoozgar, Z.

2015-01-01

Hydrogel scaffolds serve as semi synthetic or synthetic extra cellular matrix to provide an amenable environment for cellular adherence and cellular remodeling in three dimensional structures mimicking that of natural cellular environment. Additionally, hydrogels have the capacity to carry small molecule drugs and/or proteins, growth factors and other necessary components for cell growth and differentiation. In the context of drug delivery, hydrogels can be utilized to localize drugs, increase drugs concentration at the site of action and consequently reduce off-targeted side effects. The current review aims to describe and classify hydrogels and their methods of production. The main highlight is chitosan-based hydrogels as biocompatible and medically relevant hydrogels for drug delivery. PMID:26430453

Calculation of Drug Solubilities by Pharmacy Students.

ERIC Educational Resources Information Center

Cates, Lindley A.

1981-01-01

A method of estimating the solubilities of drugs in water is reported that is based on a principle applied in quantitative structure-activity relationships. This procedure involves correlation of partition coefficient values using the octanol/water system and aqueous solubility. (Author/MLW)

Exploring the associations between drug side-effects and therapeutic indications.

PubMed

Wang, Fei; Zhang, Ping; Cao, Nan; Hu, Jianying; Sorrentino, Robert

2014-10-01

Drug therapeutic indications and side-effects are both measurable patient phenotype changes in response to the treatment. Inferring potential drug therapeutic indications and identifying clinically interesting drug side-effects are both important and challenging tasks. Previous studies have utilized either chemical structures or protein targets to predict indications and side-effects. In this study, we compared drug therapeutic indication prediction using various information including chemical structures, protein targets and side-effects. We also compared drug side-effect prediction with various information sources including chemical structures, protein targets and therapeutic indication. Prediction performance based on 10-fold cross-validation demonstrates that drug side-effects and therapeutic indications are the most predictive information source for each other. In addition, we extracted 6706 statistically significant indication-side-effect associations from all known drug-disease and drug-side-effect relationships. We further developed a novel user interface that allows the user to interactively explore these associations in the form of a dynamic bipartitie graph. Many relationship pairs provide explicit repositioning hypotheses (e.g., drugs causing postural hypotension are potential candidates for hypertension) and clear adverse-reaction watch lists (e.g., drugs for heart failure possibly cause impotence). All data sets and highly correlated disease-side-effect relationships are available at http://astro.temple.edu/∼tua87106/druganalysis.html. Copyright © 2014 Elsevier Inc. All rights reserved.

Innovative polymeric system (IPS) for solvent-free lipophilic drug transdermal delivery via dissolving microneedles.

PubMed

Dangol, Manita; Yang, Huisuk; Li, Cheng Guo; Lahiji, Shayan Fakhraei; Kim, Suyong; Ma, Yonghao; Jung, Hyungil

2016-02-10

Lipophilic drugs are potential drug candidates during drug development. However, due to the need for hazardous organic solvents for their solubilization, these drugs often fail to reach the pharmaceutical market, and in doing so highlight the importance of solvent free systems. Although transdermal drug delivery systems (TDDSs) are considered prospective safe drug delivery routes, a system involving lipophilic drugs in solvent free or powder form has not yet been described. Here, we report, for the first time, a novel approach for the delivery of every kind of lipophilic drug in powder form based on an innovative polymeric system (IPS). The phase transition of powder form of lipophilic drugs due to interior chemical bonds between drugs and biodegradable polymers and formation of nano-sized colloidal structures allowed the fabrication of dissolving microneedles (DMNs) to generate a powerful TDDS. We showed that IPS based DMN with powder capsaicin enhances the therapeutic effect for treatment of the rheumatic arthritis in a DBA/1 mouse model compared to a solvent-based system, indicating the promising potential of this new solvent-free platform for lipophilic drug delivery. Copyright © 2016 Elsevier B.V. All rights reserved.

The Structures of Life

ERIC Educational Resources Information Center

National Institute of General Medical Sciences (NIGMS), 2007

2007-01-01

This booklet reveals how structural biology provides insight into health and disease and is useful in developing new medications. It contains a general introduction to proteins, coverage of the techniques used to determine protein structures, and a chapter on structure-based drug design. The booklet features "Student Snapshots," designed to…

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.

Structure-guided fragment-based in silico drug design of dengue protease inhibitors.

PubMed

Knehans, Tim; Schüller, Andreas; Doan, Danny N; Nacro, Kassoum; Hill, Jeffrey; Güntert, Peter; Madhusudhan, M S; Weil, Tanja; Vasudevan, Subhash G

2011-03-01

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC(50) = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC(50) = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.

Structure-guided fragment-based in silico drug design of dengue protease inhibitors

NASA Astrophysics Data System (ADS)

Knehans, Tim; Schüller, Andreas; Doan, Danny N.; Nacro, Kassoum; Hill, Jeffrey; Güntert, Peter; Madhusudhan, M. S.; Weil, Tanja; Vasudevan, Subhash G.

2011-03-01

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC50 = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC50 = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.

Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

PubMed

Babcock, Joseph J; Du, Fang; Xu, Kaiping; Wheelan, Sarah J; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.

Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors

PubMed Central

Babcock, Joseph J.; Du, Fang; Xu, Kaiping; Wheelan, Sarah J.; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays. PMID:23936032

Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors.

PubMed

Lorz, Alexander; Lorenzi, Tommaso; Clairambault, Jean; Escargueil, Alexandre; Perthame, Benoît

2015-01-01

Histopathological evidence supports the idea that the emergence of phenotypic heterogeneity and resistance to cytotoxic drugs can be considered as a process of selection in tumor cell populations. In this framework, can we explain intra-tumor heterogeneity in terms of selection driven by the local cell environment? Can we overcome the emergence of resistance and favor the eradication of cancer cells by using combination therapies? Bearing these questions in mind, we develop a model describing cell dynamics inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs. Cancer cells are assumed to be structured as a population by two real variables standing for space position and the expression level of a phenotype of resistance to cytotoxic drugs. The model takes explicitly into account the dynamics of resources and anticancer drugs as well as their interactions with the cell population under treatment. We analyze the effects of space structure and combination therapies on phenotypic heterogeneity and chemotherapeutic resistance. Furthermore, we study the efficacy of combined therapy protocols based on constant infusion and bang-bang delivery of cytotoxic and cytostatic drugs.

Structural Mass Spectrometry of Proteins Using Hydroxyl Radical Based Protein Footprinting

PubMed Central

Wang, Liwen; Chance, Mark R.

2011-01-01

Structural MS is a rapidly growing field with many applications in basic research and pharmaceutical drug development. In this feature article the overall technology is described and several examples of how hydroxyl radical based footprinting MS can be used to map interfaces, evaluate protein structure, and identify ligand dependent conformational changes in proteins are described. PMID:21770468

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.

Porous starch-based drug delivery systems processed by a microwave route.

PubMed

Malafaya, P B; Elvira, C; Gallardo, A; San Román, J; Reis, R L

2001-01-01

Abstract-A new simple processing route to produce starch-based porous materials was developed based on a microwave baking methodology. This innovative processing route was used to obtain non-loaded controls and loaded drug delivery carriers, incorporating a non-steroid anti-inflammatory agent. This bioactive agent was selected as model drug with expectations that the developed methodology might be used for other drugs and growth factors. The prepared systems were characterized by 1H and 13C NMR spectroscopy which allow the study of the interactions between the starch-based materials and the processing components, i.e, the blowing agents. The porosity of the prepared materials was estimated by measuring their apparent density and studied by comparing drug-loaded and non-loaded carriers. The behaviour of the porous structures, while immersed in aqueous media, was studied in terms of swelling and degradation, being intimately related to their porosity. Finally, in vitro drug release studies were performed showing a clear burst effect, followed by a slow controlled release of the drug over several days (up to 10 days).

Discovery of novel drugs for promising targets.

PubMed

Martell, Robert E; Brooks, David G; Wang, Yan; Wilcoxen, Keith

2013-09-01

Once a promising drug target is identified, the steps to actually discover and optimize a drug are diverse and challenging. The goal of this study was to provide a road map to navigate drug discovery. Review general steps for drug discovery and provide illustrating references. A number of approaches are available to enhance and accelerate target identification and validation. Consideration of a variety of potential mechanisms of action of potential drugs can guide discovery efforts. The hit to lead stage may involve techniques such as high-throughput screening, fragment-based screening, and structure-based design, with informatics playing an ever-increasing role. Biologically relevant screening models are discussed, including cell lines, 3-dimensional culture, and in vivo screening. The process of enabling human studies for an investigational drug is also discussed. Drug discovery is a complex process that has significantly evolved in recent years. © 2013 Elsevier HS Journals, Inc. All rights reserved.

Surfactant-based drug delivery systems for treating drug-resistant lung cancer.

PubMed

Kaur, Prabhjot; Garg, Tarun; Rath, Goutam; Murthy, R S R; Goyal, Amit K

2016-01-01

Among all cancers, lung cancer is the major cause of deaths. Lung cancer can be categorized into two classes for prognostic and treatment purposes: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Both categories of cancer are resistant to certain drugs. Various mechanisms behind drug resistance are over-expression of superficial membrane proteins [glycoprotein (P-gp)], lung resistance-associated proteins, aberration of the intracellular enzyme system, enhancement of the cell repair system and deregulation of cell apoptosis. Structure-performance relationships and chemical compatibility are consequently major fundamentals in surfactant-based formulations, with the intention that a great deal investigation is committed to this region. With the purpose to understand the potential of P-gp in transportation of anti-tumor drugs to cancer cells with much effectiveness and specificity, several surfactant-based delivery systems have been developed which may include microspheres, nanosized drug carriers (nanoparticles, nanoemulsions, stealth liposomes, nanogels, polymer-drug conjugates), novel powders, hydrogels and mixed micellar systems intended for systemic and/or localized delivery.

Advances in structural design of lipid-based nanoparticle carriers for delivery of macromolecular drugs, phytochemicals and anti-tumor agents.

PubMed

Angelova, Angelina; Garamus, Vasil M; Angelov, Borislav; Tian, Zhenfen; Li, Yawen; Zou, Aihua

2017-11-01

The present work highlights recent achievements in development of nanostructured dispersions and biocolloids for drug delivery applications. We emphasize the key role of biological small-angle X-ray scattering (BioSAXS) investigations for the nanomedicine design. A focus is given on controlled encapsulation of small molecular weight phytochemical drugs in lipid-based nanocarriers as well as on encapsulation of macromolecular siRNA, plasmid DNA, peptide and protein pharmaceuticals in nanostructured nanoparticles that may provide efficient intracellular delivery and triggered drug release. Selected examples of utilisation of the BioSAXS method for characterization of various types of liquid crystalline nanoorganizations (liposome, spongosome, cubosome, hexosome, and nanostructured lipid carriers) are discussed in view of the successful encapsulation and protection of phytochemicals and therapeutic biomolecules in the hydrophobic or the hydrophilic compartments of the nanocarriers. We conclude that the structural design of the nanoparticulate carriers is of crucial importance for the therapeutic outcome and the triggered drug release from biocolloids. Copyright © 2017 Elsevier B.V. All rights reserved.

Insights from investigating the interactions of adamantane-based drugs with the M2 proton channel from the H1N1 swine virus.

PubMed

Wang, Jing-Fang; Wei, Dong-Qing; Chou, Kuo-Chen

2009-10-16

The M2 proton channel is one of indispensable components for the influenza A virus that plays a vital role in its life cycle and hence is an important target for drug design against the virus. In view of this, the three-dimensional structure of the H1N1-M2 channel was developed based on the primary sequence taken from a patient recently infected by the H1N1 (swine flu) virus. With an explicit water-membrane environment, molecular docking studies were performed for amantadine and rimantadine, the two commercial drugs generally used to treat influenza A infection. It was found that their binding affinity to the H1N1-M2 channel is significantly lower than that to the H5N1-M2 channel, fully consistent with the recent report that the H1N1 swine virus was resistant to the two drugs. The findings and the relevant analysis reported here might provide useful structural insights for developing effective drugs against the new swine flu virus.

Description of a drug hierarchy in a concept-based reference terminology.

PubMed Central

Kim, J. M.; Frosdick, P.

2001-01-01

A concept-based reference terminology that covers all aspects of healthcare is essential in developing the Electronic Health Record (EHR). SNOMED Clinical Terms (CT), scheduled for release in December 2001, integrates the relative strengths of SNOMED RT, and the United Kingdom s Clinical Terms Version 3, formerly known as the Read Codes Version 3. It promises to be the most comprehensive terminology available. Since a significant portion of the EHR can be drug-related information, we describe here some of the background information and rationale for the structure and scope of the merged drug hierarchy within SNOMED CT. A controlled drug terminology within a reference terminology has the potential to support a number of functions within healthcare practice. One of the functions proposed is to serve as the bridge between reference terminology and drug knowledge bases. PMID:11825202

Specific Stereoisomeric Conformations Determine the Drug Potency of Cladosporin Scaffold against Malarial Parasite.

PubMed

Das, Pronay; Babbar, Palak; Malhotra, Nipun; Sharma, Manmohan; Jachak, Gorakhnath R; Gonnade, Rajesh G; Shanmugam, Dhanasekaran; Harlos, Karl; Yogavel, Manickam; Sharma, Amit; Reddy, D Srinivasa

2018-05-21

The dependence of drug potency on diastereomeric configurations is a key facet. Using a novel general divergent synthetic route for a three-chiral centre anti-malarial natural product cladosporin, we built its complete library of stereoisomers (cladologs) and assessed their inhibitory potential using parasite-, enzyme- and structure-based assays. We show that potency is manifest via tetrahyropyran ring conformations that are housed in the ribose binding pocket of parasite lysyl tRNA synthetase (KRS). Strikingly, drug potency between top and worst enantiomers varied 500-fold, and structures of KRS-cladolog complexes reveal that alterations at C3 and C10 are detrimental to drug potency where changes at C3 are sensed by rotameric flipping of Glutamate332. Given that scores of anti-malarial and anti-infective drugs contain chiral centers, this work provides a new foundation for focusing on inhibitor stereochemistry as a facet of anti-microbial drug development.

DOTAM derivatives as active cartilage-targeting drug carriers for the treatment of osteoarthritis.

PubMed

Hu, Hai-Yu; Lim, Ngee-Han; Ding-Pfennigdorff, Danping; Saas, Joachim; Wendt, K Ulrich; Ritzeler, Olaf; Nagase, Hideaki; Plettenburg, Oliver; Schultz, Carsten; Nazare, Marc

2015-03-18

Targeted drug-delivery methods are crucial for effective treatment of degenerative joint diseases such as osteoarthritis (OA). Toward this goal, we developed a small multivalent structure as a model drug for the attenuation of cartilage degradation. The DOTAM (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid amide)-based model structure is equipped with the cathepsin D protease inhibitor pepstatin A, a fluorophore, and peptide moieties targeting collagen II. In vivo injection of these soluble probes into the knee joints of mice resulted in 7-day-long local retention, while the drug carrier equipped with a scrambled peptide sequence was washed away within 6-8 h. The model drug conjugate successfully reduced the cathepsin D protease activity as measured by release of GAG peptide. Therefore, these conjugates represent a promising first drug conjugate for the targeted treatment of degenerative joint diseases.

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.

Chemoinformatic Analysis of Combinatorial Libraries, Drugs, Natural Products and Molecular Libraries Small Molecule Repository

PubMed Central

Singh, Narender; Guha, Rajarshi; Giulianotti, Marc; Pinilla, Clemencia; Houghten, Richard; Medina-Franco, Jose L.

2009-01-01

A multiple criteria approach is presented, that is used to perform a comparative analysis of four recently developed combinatorial libraries to drugs, Molecular Libraries Small Molecule Repository (MLSMR) and natural products. The compound databases were assessed in terms of physicochemical properties, scaffolds and fingerprints. The approach enables the analysis of property space coverage, degree of overlap between collections, scaffold and structural diversity and overall structural novelty. The degree of overlap between combinatorial libraries and drugs was assessed using the R-NN curve methodology, which measures the density of chemical space around a query molecule embedded in the chemical space of a target collection. The combinatorial libraries studied in this work exhibit scaffolds that were not observed in the drug, MLSMR and natural products collections. The fingerprint-based comparisons indicate that these combinatorial libraries are structurally different to current drugs. The R-NN curve methodology revealed that a proportion of molecules in the combinatorial libraries are located within the property space of the drugs. However, the R-NN analysis also showed that there are a significant number of molecules in several combinatorial libraries that are located in sparse regions of the drug space. PMID:19301827

Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.

PubMed

Yu, Hui; Mao, Kui-Tao; Shi, Jian-Yu; Huang, Hua; Chen, Zhi; Dong, Kai; Yiu, Siu-Ming

2018-04-11

Drug-drug interactions (DDIs) always cause unexpected and even adverse drug reactions. It is important to identify DDIs before drugs are used in the market. However, preclinical identification of DDIs requires much money and time. Computational approaches have exhibited their abilities to predict potential DDIs on a large scale by utilizing pre-market drug properties (e.g. chemical structure). Nevertheless, none of them can predict two comprehensive types of DDIs, including enhancive and degressive DDIs, which increases and decreases the behaviors of the interacting drugs respectively. There is a lack of systematic analysis on the structural relationship among known DDIs. Revealing such a relationship is very important, because it is able to help understand how DDIs occur. Both the prediction of comprehensive DDIs and the discovery of structural relationship among them play an important guidance when making a co-prescription. In this work, treating a set of comprehensive DDIs as a signed network, we design a novel model (DDINMF) for the prediction of enhancive and degressive DDIs based on semi-nonnegative matrix factorization. Inspiringly, DDINMF achieves the conventional DDI prediction (AUROC = 0.872 and AUPR = 0.605) and the comprehensive DDI prediction (AUROC = 0.796 and AUPR = 0.579). Compared with two state-of-the-art approaches, DDINMF shows it superiority. Finally, representing DDIs as a binary network and a signed network respectively, an analysis based on NMF reveals crucial knowledge hidden among DDIs. Our approach is able to predict not only conventional binary DDIs but also comprehensive DDIs. More importantly, it reveals several key points about the DDI network: (1) both binary and signed networks show fairly clear clusters, in which both drug degree and the difference between positive degree and negative degree show significant distribution; (2) the drugs having large degrees tend to have a larger difference between positive degree and negative degree; (3) though the binary DDI network contains no information about enhancive and degressive DDIs at all, it implies some of their relationship in the comprehensive DDI matrix; (4) the occurrence of signs indicating enhancive and degressive DDIs is not random because the comprehensive DDI network is equipped with a structural balance.

A combination of spin diffusion methods for the determination of protein-ligand complex structural ensembles.

PubMed

Pilger, Jens; Mazur, Adam; Monecke, Peter; Schreuder, Herman; Elshorst, Bettina; Bartoschek, Stefan; Langer, Thomas; Schiffer, Alexander; Krimm, Isabelle; Wegstroth, Melanie; Lee, Donghan; Hessler, Gerhard; Wendt, K-Ulrich; Becker, Stefan; Griesinger, Christian

2015-05-26

Structure-based drug design (SBDD) is a powerful and widely used approach to optimize affinity of drug candidates. With the recently introduced INPHARMA method, the binding mode of small molecules to their protein target can be characterized even if no spectroscopic information about the protein is known. Here, we show that the combination of the spin-diffusion-based NMR methods INPHARMA, trNOE, and STD results in an accurate scoring function for docking modes and therefore determination of protein-ligand complex structures. Applications are shown on the model system protein kinase A and the drug targets glycogen phosphorylase and soluble epoxide hydrolase (sEH). Multiplexing of several ligands improves the reliability of the scoring function further. The new score allows in the case of sEH detecting two binding modes of the ligand in its binding site, which was corroborated by X-ray analysis. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of structure of hyperfine poly(3-hydroxybutyrate) fibers (PHB) for controlled drug delivery

NASA Astrophysics Data System (ADS)

Olkhov, A. A.; Kosenko, R. Yu; Markin, V. S.; Zykova, A. K.; Pantyukhov, P. V.; Karpova, S. G.; Iordanskii, A. L.

2017-12-01

Hyperfine fibers based on biodegradable poly (3-hydroxybutyrate) with encapsulated drug substance (dipyridamol) were obtained by using electrospinning method. Addition of dipyridamol has a significant effect on geometrical shape and structure of microfibers as well as total porosity of fibrous material. Observation of fibers using scanning electron microscopy (SEM) method showed that without or at lower dipyridamol content (<3%) fibers consisted of interleaved ellipsoid and cylindrical fragments. At higher dipyridamol content (3-5%) anomalous ellipsoid structures did not practically form, and fiber’s shape became cylindrical. The totality of morphological and structural characteristics determined the rate of dipyridamol diffusive transports. The simplified model of drug desorption from fibrous matrix was presented. In current work it was showed that the rate-limiting stage of transport was the diffusion of dipyridamol in the bulk of cylindrical fibers.

Structure of the Angiotensin Receptor Revealed by Serial Femtosecond Crystallography

DOE PAGES

Zhang, Haitao; Unal, Hamiyet; Gati, Cornelius; ...

2015-05-07

We report that angiotensin II type 1 receptor (AT 1R) is a G protein-coupled receptor that serves as a primary regulator for blood pressure maintenance. Although several anti-hypertensive drugs have been developed as AT 1R blockers (ARBs), the structural basis for AT 1R ligand-binding and regulation has remained elusive, mostly due to the difficulties of growing high quality crystals for structure determination using synchrotron radiation. By applying the recently developed method of serial femtosecond crystallography at an X-ray free-electron laser, we successfully determined the room-temperature crystal structure of the human AT 1R in complex with its selective antagonist ZD7155 atmore » 2.9 Å resolution. The AT 1R-ZD7155 complex structure revealed key structural features ofAT 1R and critical interactions for ZD7155 binding. Finally, docking simulations of the clinically used ARBs into the AT 1R structure further elucidated both the common and distinct binding modes for these anti-hypertensive drugs. Our results thereby provide fundamental insights into AT 1R structure-function relationship and structure-based drug design.« less

Structure of the Angiotensin Receptor Revealed by Serial Femtosecond Crystallography

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

Zhang, Haitao; Unal, Hamiyet; Gati, Cornelius

We report that angiotensin II type 1 receptor (AT 1R) is a G protein-coupled receptor that serves as a primary regulator for blood pressure maintenance. Although several anti-hypertensive drugs have been developed as AT 1R blockers (ARBs), the structural basis for AT 1R ligand-binding and regulation has remained elusive, mostly due to the difficulties of growing high quality crystals for structure determination using synchrotron radiation. By applying the recently developed method of serial femtosecond crystallography at an X-ray free-electron laser, we successfully determined the room-temperature crystal structure of the human AT 1R in complex with its selective antagonist ZD7155 atmore » 2.9 Å resolution. The AT 1R-ZD7155 complex structure revealed key structural features ofAT 1R and critical interactions for ZD7155 binding. Finally, docking simulations of the clinically used ARBs into the AT 1R structure further elucidated both the common and distinct binding modes for these anti-hypertensive drugs. Our results thereby provide fundamental insights into AT 1R structure-function relationship and structure-based drug design.« less

G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

PubMed

Lee, Hui Sun; Im, Wonpil

2016-04-01

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.

Principles that underpin effective school-based drug education.

PubMed

Midford, Richard; Munro, Geoffrey; McBride, Nyanda; Snow, Pamela; Ladzinski, Ursula

2002-01-01

This study identifies the conceptual underpinnings of effective school-based drug education practice in light of contemporary research evidence and the practical experience of a broad range of drug education stakeholders. The research involved a review of the literature, a national survey of 210 Australian teachers and others involved in drug education, and structured interviews with 22 key Australian drug education policy stakeholders. The findings from this research have been distilled and presented as a list of 16 principles that underpin effective drug education. In broad terms, drug education should be evidence-based, developmentally appropriate, sequential, and contextual. Programs should be initiated before drug use commences. Strategies should be linked to goals and should incorporate harm minimization. Teaching should be interactive and use peer leaders. The role of the classroom teacher is central. Certain program content is important, as is social and resistance skills training. Community values, the social context of use, and the nature of drug harm have to be addressed. Coverage needs to be adequate and supported by follow-up. It is envisaged that these principles will provide all those involved in the drug education field with a set of up-to-date, research-based guidelines against which to reference decisions on program design, selection, implementation, and evaluation.

Novel Non-Peptide Inhibitors against SmCL1 of Schistosoma mansoni: In Silico Elucidation, Implications and Evaluation via Knowledge Based Drug Discovery

PubMed Central

Zafar, Atif; Ahmad, Sabahuddin; Rizvi, Asim; Ahmad, Masood

2015-01-01

Schistosomiasis is a major endemic disease known for excessive mortality and morbidity in developing countries. Because praziquantel is the only drug available for its treatment, the risk of drug resistance emphasizes the need to discover new drugs for this disease. Cathepsin SmCL1 is the critical target for drug design due to its essential role in the digestion of host proteins for growth and development of Schistosoma mansoni. Inhibiting the function of SmCL1 could control the wide spread of infections caused by S. mansoni in humans. With this objective, a homology modeling approach was used to obtain theoretical three-dimensional (3D) structure of SmCL1. In order to find the potential inhibitors of SmCL1, a plethora of in silico techniques were employed to screen non-peptide inhibitors against SmCL1 via structure-based drug discovery protocol. Receiver operating characteristic (ROC) curve analysis and molecular dynamics (MD) simulation were performed on the results of docked protein-ligand complexes to identify top ranking molecules against the modelled 3D structure of SmCL1. MD simulation results suggest the phytochemical Simalikalactone-D as a potential lead against SmCL1, whose pharmacophore model may be useful for future screening of potential drug molecules. To conclude, this is the first report to discuss the virtual screening of non-peptide inhibitors against SmCL1 of S. mansoni, with significant therapeutic potential. Results presented herein provide a valuable contribution to identify the significant leads and further derivatize them to suitable drug candidates for antischistosomal therapy. PMID:25933436

Characterization and Higher-Order Structure Assessment of an Interchain Cysteine-Based ADC: Impact of Drug Loading and Distribution on the Mechanism of Aggregation.

PubMed

Guo, Jianxin; Kumar, Sandeep; Chipley, Mark; Marcq, Olivier; Gupta, Devansh; Jin, Zhaowei; Tomar, Dheeraj S; Swabowski, Cecily; Smith, Jacquelynn; Starkey, Jason A; Singh, Satish K

2016-03-16

The impact of drug loading and distribution on higher order structure and physical stability of an interchain cysteine-based antibody drug conjugate (ADC) has been studied. An IgG1 mAb was conjugated with a cytotoxic auristatin payload following the reduction of interchain disulfides. The 2-D LC-MS analysis shows that there is a preference for certain isomers within the various drug to antibody ratios (DARs). The physical stability of the unconjugated monoclonal antibody, the ADC, and isolated conjugated species with specific DAR, were compared using calorimetric, thermal, chemical denaturation and molecular modeling techniques, as well as techniques to assess hydrophobicity. The DAR was determined to have a significant impact on the biophysical properties and stability of the ADC. The CH2 domain was significantly perturbed in the DAR6 species, which was attributable to quaternary structural changes as assessed by molecular modeling. At accelerated storage temperatures, the DAR6 rapidly forms higher molecular mass species, whereas the DAR2 and the unconjugated mAb were largely stable. Chemical denaturation study indicates that DAR6 may form multimers while DAR2 and DAR4 primarily exist in monomeric forms in solution at ambient conditions. The physical state differences were correlated with a dramatic increase in the hydrophobicity and a reduction in the surface tension of the DAR6 compared to lower DAR species. Molecular modeling of the various DAR species and their conformers demonstrates that the auristatin-based linker payload directly contributes to the hydrophobicity of the ADC molecule. Higher order structural characterization provides insight into the impact of conjugation on the conformational and colloidal factors that determine the physical stability of cysteine-based ADCs, with implications for process and formulation development.

Light-switchable systems for remotely controlled drug delivery.

PubMed

Shim, Gayong; Ko, Seungbeom; Kim, Dongyoon; Le, Quoc-Viet; Park, Gyu Thae; Lee, Jaiwoo; Kwon, Taekhyun; Choi, Han-Gon; Kim, Young Bong; Oh, Yu-Kyoung

2017-12-10

Light-switchable systems have recently received attention as a new mode of remotely controlled drug delivery. In the past, a multitude of nanomedicine studies have sought to enhance the specificity of drug delivery to target sites by focusing on receptors overexpressed on malignant cells or environmental features of diseases sites. Despite these immense efforts, however, there are few clinically available nanomedicines. We need a paradigm shift in drug delivery. One strategy that may overcome the limitations of pathophysiology-based drug delivery is the use of remotely controlled delivery technology. Unlike pathophysiology-based active drug targeting strategies, light-switchable systems are not affected by the heterogeneity of cells, tissue types, and/or microenvironments. Instead, they are triggered by remote light (i.e., near-infrared) stimuli, which are absorbed by photoresponsive molecules or three-dimensional nanostructures. The sequential conversion of light to heat or reactive oxygen species can activate drug release and allow it to be spatio-temporally controlled. Light-switchable systems have been used to activate endosomal drug escape, modulate the release of chemical and biological drugs, and alter nanoparticle structures to control the release rates of drugs. This review will address the limitations of pathophysiology-based drug delivery systems, the current status of light-based remote-switch systems, and future directions in the application of light-switchable systems for remotely controlled drug delivery. Copyright © 2017 Elsevier B.V. All rights reserved.

Prevalence and structural correlates of gender based violence among a prospective cohort of female sex workers

PubMed Central

Kerr, T; Strathdee, S A; Shoveller, J; Montaner, J S; Tyndall, M W

2009-01-01

Objective To examine the prevalence and structural correlates of gender based violence against female sex workers in an environment of criminalised prostitution. Design Prospective observational study. Setting Vancouver, Canada during 2006-8. Participants Female sex workers 14 years of age or older (inclusive of transgender women) who used illicit drugs (excluding marijuana) and engaged in street level sex work. Main outcome measure Self reported gender based violence. Results Of 267 female sex workers invited to participate, 251 women returned to the study office and consented to participate (response rate of 94%). Analyses were based on 237 female sex workers who completed a baseline visit and at least one follow-up visit. Of these 237 female sex workers, 57% experienced gender based violence over an 18 month follow-up period. In multivariate models adjusted for individual and interpersonal risk practices, the following structural factors were independently correlated with violence against female sex workers: homelessness (adjusted odds ratio for physical violence (aORphysicalviolence) 2.14, 95% confidence interval 1.34 to 3.43; adjusted odds ratio for rape (aORrape) 1.73, 1.09 to 3.12); inability to access drug treatment (adjusted odds ratio for client violence (aORclientviolence) 2.13, 1.26 to 3.62; aORphysicalviolence 1.96, 1.03 to 3.43); servicing clients in cars or public spaces (aORclientviolence 1.50, 1.08 to 2.57); prior assault by police (aORclientviolence 3.45, 1.98 to 6.02; aORrape 2.61, 1.32 to 5.16); confiscation of drug use paraphernalia by police without arrest (aORphysicalviolence 1.50, 1.02 to 2.41); and moving working areas away from main streets owing to policing (aORclientviolence 2.13, 1.26 to 3.62). Conclusions Our results demonstrate an alarming prevalence of gender based violence against female sex workers. The structural factors of criminalisation, homelessness, and poor availability of drug treatment independently correlated with gender based violence against street based female sex workers. Socio-legal policy reforms, improved access to housing and drug treatment, and scale up of violence prevention efforts, including police-sex worker partnerships, will be crucial to stemming violence against female sex workers. PMID:19671935

Prevalence and structural correlates of gender based violence among a prospective cohort of female sex workers.

PubMed

Shannon, Kate; Kerr, T; Strathdee, S A; Shoveller, J; Montaner, J S; Tyndall, M W

2009-08-11

To examine the prevalence and structural correlates of gender based violence against female sex workers in an environment of criminalised prostitution. Prospective observational study. Vancouver, Canada during 2006-8. Female sex workers 14 years of age or older (inclusive of transgender women) who used illicit drugs (excluding marijuana) and engaged in street level sex work. Self reported gender based violence. Of 267 female sex workers invited to participate, 251 women returned to the study office and consented to participate (response rate of 94%). Analyses were based on 237 female sex workers who completed a baseline visit and at least one follow-up visit. Of these 237 female sex workers, 57% experienced gender based violence over an 18 month follow-up period. In multivariate models adjusted for individual and interpersonal risk practices, the following structural factors were independently correlated with violence against female sex workers: homelessness (adjusted odds ratio for physical violence (aOR(physicalviolence)) 2.14, 95% confidence interval 1.34 to 3.43; adjusted odds ratio for rape (aOR(rape)) 1.73, 1.09 to 3.12); inability to access drug treatment (adjusted odds ratio for client violence (aOR(clientviolence)) 2.13, 1.26 to 3.62; aOR(physicalviolence) 1.96, 1.03 to 3.43); servicing clients in cars or public spaces (aOR(clientviolence) 1.50, 1.08 to 2.57); prior assault by police (aOR(clientviolence) 3.45, 1.98 to 6.02; aOR(rape) 2.61, 1.32 to 5.16); confiscation of drug use paraphernalia by police without arrest (aOR(physicalviolence) 1.50, 1.02 to 2.41); and moving working areas away from main streets owing to policing (aOR(clientviolence) 2.13, 1.26 to 3.62). Our results demonstrate an alarming prevalence of gender based violence against female sex workers. The structural factors of criminalisation, homelessness, and poor availability of drug treatment independently correlated with gender based violence against street based female sex workers. Socio-legal policy reforms, improved access to housing and drug treatment, and scale up of violence prevention efforts, including police-sex worker partnerships, will be crucial to stemming violence against female sex workers.

Novel microemulsion-based gels for topical delivery of indomethacin: Formulation, physicochemical properties and in vitro drug release studies.

PubMed

Froelich, Anna; Osmałek, Tomasz; Snela, Agnieszka; Kunstman, Paweł; Jadach, Barbara; Olejniczak, Marta; Roszak, Grzegorz; Białas, Wojciech

2017-12-01

Microemulsion-based semisolid systems may be considered as an interesting alternative to the traditional dosage forms applied in topical drug delivery. Mechanical properties of topical products are important both in terms of application and dosage form effectiveness. In this study we designed and evaluated novel microemulsion-based gels with indomethacin and analyzed the factors affecting their mechanical characteristics and drug release. The impact of the microemulsion composition on the extent of isotropic region was investigated with the use of pseudoternary phase diagrams. Selected microemulsions were analyzed in terms of electrical conductivity and surface tension in order to determine the microemulsion type. Microemulsions were transformed into polymer-based gels and subjected to rheological and textural studies. Finally, the indomethacin release from the analyzed gels was studied and compared to commercially available product. The extent of isotropic domain in pseudoternary phase diagrams seems to be dependent on the polarity of the oil phase. The surface tension and conductivity monitored as a function of water content in microemulsion systems revealed possible structural transformations from w/o through bicontinuous systems into o/w. The mechanical properties of semisolid microemulsion-based systems depended on the composition of surface active agents and the drug presence. The drug release profiles observed in the case of the investigated gels differed from those recorded for the commercially available product which was most probably caused by the different structure of both systems. Copyright © 2017 Elsevier Inc. All rights reserved.

Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review

PubMed Central

Csermely, Peter; Korcsmáros, Tamás; Kiss, Huba J.M.; London, Gábor; Nussinov, Ruth

2013-01-01

Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only gives a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The “central hit strategy” selectively targets central node/edges of the flexible networks of infectious agents or cancer cells to kill them. The “network influence strategy” works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach. PMID:23384594

Adamantane in Drug Delivery Systems and Surface Recognition.

PubMed

Štimac, Adela; Šekutor, Marina; Mlinarić-Majerski, Kata; Frkanec, Leo; Frkanec, Ruža

2017-02-16

The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based structures and self-assembled supramolecular systems for basic chemical investigations as well as for biomedical application.

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

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

PubMed

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

2016-07-01

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

Discovery of Novel GPVI Receptor Antagonists by Structure-Based Repurposing

PubMed Central

Taylor, Lewis; Vasudevan, Sridhar R.; Jones, Chris I.; Gibbins, Jonathan M.; Churchill, Grant C.; Campbell, R. Duncan; Coxon, Carmen H.

2014-01-01

Inappropriate platelet aggregation creates a cardiovascular risk that is largely managed with thienopyridines and aspirin. Although effective, these drugs carry risks of increased bleeding and drug ‘resistance’, underpinning a drive for new antiplatelet agents. To discover such drugs, one strategy is to identify a suitable druggable target and then find small molecules that modulate it. A good and unexploited target is the platelet collagen receptor, GPVI, which promotes thrombus formation. To identify inhibitors of GPVI that are safe and bioavailable, we docked a FDA-approved drug library into the GPVI collagen-binding site in silico. We now report that losartan and cinanserin inhibit GPVI-mediated platelet activation in a selective, competitive and dose-dependent manner. This mechanism of action likely underpins the cardioprotective effects of losartan that could not be ascribed to its antihypertensive effects. We have, therefore, identified small molecule inhibitors of GPVI-mediated platelet activation, and also demonstrated the utility of structure-based repurposing. PMID:24971515

New approaches to structure-based discovery of dengue protease inhibitors.

PubMed

Tomlinson, S M; Malmstrom, R D; Watowich, S J

2009-06-01

Dengue virus (DENV), a member of the family Flaviviridae, presents a tremendous threat to global health since an estimated 2.5 billion people worldwide are at risk for epidemic transmission. DENV infections are primarily restricted to sub-tropical and tropical regions; however, there is concern that the virus will spread into new regions including the United States. There are no approved antiviral drugs or vaccines to combat dengue infection, although DENV vaccines have entered Phase 3 clinical trials. Drug discovery and development efforts against DENV and other viral pathogens must overcome specificity, efficacy, safety, and resistance challenges before the shortage of licensed drugs to treat viral infections can be relieved. Current drug discovery methods are largely inefficient and thus relatively ineffective at tackling the growing threat to public health presented by emerging and remerging viral pathogens. This review discusses current and newly implemented structure-based computational efforts to discover antivirals that target the DENV NS3 protease, although it is clear that these computational tools can be applied to most disease targets.

Prediction of drug indications based on chemical interactions and chemical similarities.

PubMed

Huang, Guohua; Lu, Yin; Lu, Changhong; Zheng, Mingyue; Cai, Yu-Dong

2015-01-01

Discovering potential indications of novel or approved drugs is a key step in drug development. Previous computational approaches could be categorized into disease-centric and drug-centric based on the starting point of the issues or small-scaled application and large-scale application according to the diversity of the datasets. Here, a classifier has been constructed to predict the indications of a drug based on the assumption that interactive/associated drugs or drugs with similar structures are more likely to target the same diseases using a large drug indication dataset. To examine the classifier, it was conducted on a dataset with 1,573 drugs retrieved from Comprehensive Medicinal Chemistry database for five times, evaluated by 5-fold cross-validation, yielding five 1st order prediction accuracies that were all approximately 51.48%. Meanwhile, the model yielded an accuracy rate of 50.00% for the 1st order prediction by independent test on a dataset with 32 other drugs in which drug repositioning has been confirmed. Interestingly, some clinically repurposed drug indications that were not included in the datasets are successfully identified by our method. These results suggest that our method may become a useful tool to associate novel molecules with new indications or alternative indications with existing drugs.

Prediction of Drug Indications Based on Chemical Interactions and Chemical Similarities

PubMed Central

Huang, Guohua; Lu, Yin; Lu, Changhong; Cai, Yu-Dong

2015-01-01

Discovering potential indications of novel or approved drugs is a key step in drug development. Previous computational approaches could be categorized into disease-centric and drug-centric based on the starting point of the issues or small-scaled application and large-scale application according to the diversity of the datasets. Here, a classifier has been constructed to predict the indications of a drug based on the assumption that interactive/associated drugs or drugs with similar structures are more likely to target the same diseases using a large drug indication dataset. To examine the classifier, it was conducted on a dataset with 1,573 drugs retrieved from Comprehensive Medicinal Chemistry database for five times, evaluated by 5-fold cross-validation, yielding five 1st order prediction accuracies that were all approximately 51.48%. Meanwhile, the model yielded an accuracy rate of 50.00% for the 1st order prediction by independent test on a dataset with 32 other drugs in which drug repositioning has been confirmed. Interestingly, some clinically repurposed drug indications that were not included in the datasets are successfully identified by our method. These results suggest that our method may become a useful tool to associate novel molecules with new indications or alternative indications with existing drugs. PMID:25821813

iEzy-Drug: A Web Server for Identifying the Interaction between Enzymes and Drugs in Cellular Networking

PubMed Central

Min, Jian-Liang; Chou, Kuo-Chen

2013-01-01

With the features of extremely high selectivity and efficiency in catalyzing almost all the chemical reactions in cells, enzymes play vitally important roles for the life of an organism and hence have become frequent targets for drug design. An essential step in developing drugs by targeting enzymes is to identify drug-enzyme interactions in cells. It is both time-consuming and costly to do this purely by means of experimental techniques alone. Although some computational methods were developed in this regard based on the knowledge of the three-dimensional structure of enzyme, unfortunately their usage is quite limited because three-dimensional structures of many enzymes are still unknown. Here, we reported a sequence-based predictor, called “iEzy-Drug,” in which each drug compound was formulated by a molecular fingerprint with 258 feature components, each enzyme by the Chou's pseudo amino acid composition generated via incorporating sequential evolution information and physicochemical features derived from its sequence, and the prediction engine was operated by the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iEzy-Drug via rigorous cross-validations was about 91%. Moreover, to maximize the convenience for the majority of experimental scientists, a user-friendly web server was established, by which users can easily obtain their desired results. PMID:24371828

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2

NASA Astrophysics Data System (ADS)

Baumgartner, Matthew P.; Evans, David A.

2018-01-01

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ = 0.614), performed slightly better than our ligand-based methods (ρ = 0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.

Drug Target Protein-Protein Interaction Networks: A Systematic Perspective

PubMed Central

2017-01-01

The identification and validation of drug targets are crucial in biomedical research and many studies have been conducted on analyzing drug target features for getting a better understanding on principles of their mechanisms. But most of them are based on either strong biological hypotheses or the chemical and physical properties of those targets separately. In this paper, we investigated three main ways to understand the functional biomolecules based on the topological features of drug targets. There are no significant differences between targets and common proteins in the protein-protein interactions network, indicating the drug targets are neither hub proteins which are dominant nor the bridge proteins. According to some special topological structures of the drug targets, there are significant differences between known targets and other proteins. Furthermore, the drug targets mainly belong to three typical communities based on their modularity. These topological features are helpful to understand how the drug targets work in the PPI network. Particularly, it is an alternative way to predict potential targets or extract nontargets to test a new drug target efficiently and economically. By this way, a drug target's homologue set containing 102 potential target proteins is predicted in the paper. PMID:28691014

Potential of agricultural fungicides for antifungal drug discovery.

PubMed

Jampilek, Josef

2016-01-01

While it is true that only a small fraction of fungal species are responsible for human mycoses, the increasing prevalence of fungal diseases has highlighted an urgent need to develop new antifungal drugs, especially for systemic administration. This contribution focuses on the similarities between agricultural fungicides and drugs. Inorganic, organometallic and organic compounds can be found amongst agricultural fungicides. Furthermore, fungicides are designed and developed in a similar fashion to drugs based on similar rules and guidelines, with fungicides also having to meet similar criteria of lead-likeness and/or drug-likeness. Modern approved specific-target fungicides are well-characterized entities with a proposed structure-activity relationships hypothesis and a defined mode of action. Extensive toxicological evaluation, including mammalian toxicology assays, is performed during the whole discovery and development process. Thus modern agrochemical research (design of modern agrochemicals) comes close to drug design, discovery and development. Therefore, modern specific-target fungicides represent excellent lead-like structures/models for novel drug design and development.

Drug release from nanoparticles embedded in four different nanofibrillar cellulose aerogels.

PubMed

Valo, Hanna; Arola, Suvi; Laaksonen, Päivi; Torkkeli, Mika; Peltonen, Leena; Linder, Markus B; Serimaa, Ritva; Kuga, Shigenori; Hirvonen, Jouni; Laaksonen, Timo

2013-09-27

Highly porous nanocellulose aerogels prepared by freeze-drying from various nanofibrillar cellulose (NFC) hydrogels are introduced as nanoparticle reservoirs for oral drug delivery systems. Here we show that beclomethasone dipropionate (BDP) nanoparticles coated with amphiphilic hydrophobin proteins can be well integrated into the NFC aerogels. NFCs from four different origins are introduced and compared to microcrystalline cellulose (MCC). The nanocellulose aerogel scaffolds made from red pepper (RC) and MCC release the drug immediately, while bacterial cellulose (BC), quince seed (QC) and TEMPO-oxidized birch cellulose-based (TC) aerogels show sustained drug release. Since the release of the drug is controlled by the structure and interactions between the nanoparticles and the cellulose matrix, modulation of the matrix formers enable a control of the drug release rate. These nanocomposite structures can be very useful in many pharmaceutical nanoparticle applications and open up new possibilities as carriers for controlled drug delivery. Copyright © 2013 Elsevier B.V. All rights reserved.

Nanodiamond-Based Composite Structures for Biomedical Imaging and Drug Delivery.

PubMed

Rosenholm, Jessica M; Vlasov, Igor I; Burikov, Sergey A; Dolenko, Tatiana A; Shenderova, Olga A

2015-02-01

Nanodiamond particles are widely recognized candidates for biomedical applications due to their excellent biocompatibility, bright photoluminescence based on color centers and outstanding photostability. Recently, more complex architectures with a nanodiamond core and an external shell or nanostructure which provides synergistic benefits have been developed, and their feasibility for biomedical applications has been demonstrated. This review is aimed at summarizing recent achievements in the fabrication and functional demonstrations of nanodiamond-based composite structures, along with critical considerations that should be taken into account in the design of such structures from a biomedical point of view. A particular focus of the review is core/shell structures of nanodiamond surrounded by porous silica shells, which demonstrate a remarkable increase in drug loading efficiency; as well as nanodiamonds decorated with carbon dots, which have excellent potential as bioimaging probes. Other combinations are also considered, relying on the discussed inherent properties of the inorganic materials being integrated in a way to advance inorganic nanomedicine in the quest for better health-related nanotechnology.

NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning

PubMed Central

Chen, Ming; Wang, Quanxin; Zhang, Lixin; Yan, Guiying

2016-01-01

Fungal infection has become one of the leading causes of hospital-acquired infections with high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases. Synergistic drug combinations could provide an effective strategy to overcome drug resistance. Meanwhile, synergistic drug combinations can increase treatment efficacy and decrease drug dosage to avoid toxicity. Therefore, computational prediction of synergistic drug combinations for fungus-causing diseases becomes attractive. In this study, we proposed similar nature of drug combinations: principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa. Furthermore, we developed a novel algorithm termed Network-based Laplacian regularized Least Square Synergistic drug combination prediction (NLLSS) to predict potential synergistic drug combinations by integrating different kinds of information such as known synergistic drug combinations, drug-target interactions, and drug chemical structures. We applied NLLSS to predict antifungal synergistic drug combinations and showed that it achieved excellent performance both in terms of cross validation and independent prediction. Finally, we performed biological experiments for fungal pathogen Candida albicans to confirm 7 out of 13 predicted antifungal synergistic drug combinations. NLLSS provides an efficient strategy to identify potential synergistic antifungal combinations. PMID:27415801

[A novel dipeptidyl peptidase IV inhibitors developed through scaffold hopping and drug splicing strategy].

PubMed

Wang, Shan-Chun; Zeng, Li-Li; Ding, Yu-Yang; Zeng, Shao-Gao; Song, Hong-Rui; Hu, Wen-Hui; Xie, Hui

2014-01-01

Though all the marketed drugs of dipeptidyl peptidase IV inhibitors are structurally different, their inherent correlation is worthy of further investigation. Herein we rapidly discovered a novel DPP-IV inhibitor 8g (IC50 = 4.9 nmol.L-1) which exhibits as good activity and selectivity as the market drugs through scaffold hopping and drug splicing strategies based on alogliptin and linagliptin. This study demonstrated that the employment of classic medicinal chemistry strategy to the marketed drugs with specific target is an efficient approach to discover novel bioactive molecules.

Structural and Functional Analyses of the Six1 Transcriptional Complex for Anti-Breast Cancer Drug Design

DTIC Science & Technology

2011-04-01

of structurally highly related initial hits. 
 Fig. 8. A malachite green based secondary assay confirmed the top two initial hits do inhibit ED’s...Crystals (left) and diffraction pattern (right) of ED. using a malachite -green based phosphatase assay (Fig. 8). We further demonstrated that these

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.

PubMed

Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

2012-06-01

Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Many studies have utilized either chemical structures or molecular pathways of the drugs to predict ADRs. Here, the authors propose a machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information. A large-scale study was conducted to predict 1385 known ADRs of 832 approved drugs, and five machine-learning algorithms for this task were compared. This evaluation, based on a fivefold cross-validation, showed that the support vector machine algorithm outperformed the others. Of the three types of information, phenotypic data were the most informative for ADR prediction. When biological and phenotypic features were added to the baseline chemical information, the ADR prediction model achieved significant improvements in area under the curve (from 0.9054 to 0.9524), precision (from 43.37% to 66.17%), and recall (from 49.25% to 63.06%). Most importantly, the proposed model successfully predicted the ADRs associated with withdrawal of rofecoxib and cerivastatin. The results suggest that phenotypic information on drugs is valuable for ADR prediction. Moreover, they demonstrate that different models that combine chemical, biological, or phenotypic information can be built from approved drugs, and they have the potential to detect clinically important ADRs in both preclinical and post-marketing phases.

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.

Drug delivery with microsecond laser pulses into gelatin

NASA Astrophysics Data System (ADS)

Shangguan, Hanqun; Casperson, Lee W.; Shearin, Alan; Gregory, Kenton W.; Prahl, Scott A.

1996-07-01

Photoacoustic drug delivery is a technique for localized drug delivery by laser-induced hydrodynamic pressure following cavitation bubble expansion and collapse. Photoacoustic drug delivery was investigated on gelatin-based thrombus models with planar and cylindrical geometries by use of one microsecond laser pulses. Solutions of a hydrophobic dye in mineral oil permitted monitoring of delivered colored oil into clear gelatin-based thrombus models. Cavitation bubble development and photoacoustic drug delivery were visualized with flash photography. This study demonstrated that cavitation is the governing mechanism for photoacoustic drug delivery, and the deepest penetration of colored oil in gels followed the bubble collapse. Spatial distribution measurements revealed that colored oil could be driven a few millimeters into the gels in both axial and radial directions, and the penetration was less than 500 mu m when the gelatin structure was not fractured. localized drug delivery, cavitation bubble, laser thrombolysis.

In silico prediction of cytochrome P450-mediated drug metabolism.

PubMed

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

2011-06-01

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

A Global Comparison of the Human and T. brucei Degradomes Gives Insights about Possible Parasite Drug Targets

PubMed Central

Mashiyama, Susan T.; Koupparis, Kyriacos; Caffrey, Conor R.; McKerrow, James H.; Babbitt, Patricia C.

2012-01-01

We performed a genome-level computational study of sequence and structure similarity, the latter using crystal structures and models, of the proteases of Homo sapiens and the human parasite Trypanosoma brucei. Using sequence and structure similarity networks to summarize the results, we constructed global views that show visually the relative abundance and variety of proteases in the degradome landscapes of these two species, and provide insights into evolutionary relationships between proteases. The results also indicate how broadly these sequence sets are covered by three-dimensional structures. These views facilitate cross-species comparisons and offer clues for drug design from knowledge about the sequences and structures of potential drug targets and their homologs. Two protease groups (“M32” and “C51”) that are very different in sequence from human proteases are examined in structural detail, illustrating the application of this global approach in mining new pathogen genomes for potential drug targets. Based on our analyses, a human ACE2 inhibitor was selected for experimental testing on one of these parasite proteases, TbM32, and was shown to inhibit it. These sequence and structure data, along with interactive versions of the protein similarity networks generated in this study, are available at http://babbittlab.ucsf.edu/resources.html. PMID:23236535

Design, Synthesis, and Characterization of Novel Zwitterionic Lipids for Drug and siRNA Delivery Applications

NASA Astrophysics Data System (ADS)

Walsh, Colin L.

Lipid-based nanoparticles have long been used to deliver biologically active molecules such as drugs, proteins, peptides, DNA, and siRNA in vivo. Liposomes and lipoplexes alter the biodistribution, pharmacokinetics, and cellular uptake of their encapsulated or associated cargo. This can increase drug efficacy while reducing toxicity, resulting in an increased therapeutic index and better clinical outcomes. Unlike small molecule drugs, which passively diffuse through lipid membranes, nucleic acids and proteins require an active, carrier mediated escape mechanism to reach their site of action. As such, the therapeutic application and drug properties dictate the required biophysical characteristics of the lipid nanoparticle. These carrier properties depend on the structure and biophysical characteristics of the lipids and other components used to formulate them. This dissertation presents a series of studies related to the development of novel synthetic lipids for use in drug delivery systems. First, we developed a novel class of zwitterionic lipids with head groups containing a cationic amine and anionic carboxylate and ester-linked oleic acid tails. These lipids exhibit structure-dependent, pH-responsive biophysical properties, and may be useful components for next-generation drug delivery systems. Second, we extended the idea of amine/carboxylate containing zwitterionic head groups and synthesized a series of acetate terminated diacyl lipids containing a quaternary amine. These lipids have an inverted headgroup orientation compared to naturally occurring zwitterionic lipids, and show interesting salt-dependent biophysical properties. Third, we synthesized and characterized a focused library of ionizable lysine-based lipids, which contain a lysine head group linked to a long-chain dialkylamine. A focused library was synthesized to determine the impact of hydrophobic fluidity, lipid net charge, and lipid pKa on the biophysical and siRNA transfection characteristics of these lipids. Our results indicate that structural variations significantly impact the biophysical and transfection behavior of this class of lipids. In summary, we have synthesized several new classes of lipids with biophysical characteristics that may be useful for drug delivery applications. Our results show that slight modifications to lipid structure impacts their biophysical behavior, which in turn dictates their potential utility in drug delivery systems. Further understanding lipid structure-activity relationships will allow for the rational design and engineering of lipids with appropriate properties for specific delivery applications.

Cyclodextrin based nanosponges for pharmaceutical use: a review.

PubMed

Tejashri, Gursalkar; Amrita, Bajaj; Darshana, Jain

2013-09-01

Nanosponges are a novel class of hyper-crosslinked polymer based colloidal structures consisting of solid nanoparticles with colloidal sizes and nanosized cavities. These nano-sized colloidal carriers have been recently developed and proposed for drug delivery, since their use can solubilize poorly water-soluble drugs and provide prolonged release as well as improve a drug's bioavailability by modifying the pharmacokinetic parameters of actives. Development of nanosponges as drug delivery systems, with special reference to cyclodextrin based nanosponges, is presented in this article. In the current review, attempts have been made to illustrate the features of cyclodextrin based nanosponges and their applications in pharmaceutical formulations. Special emphasis has been placed on discussing the methods of preparation, characterization techniques and applications of these novel drug delivery carriers for therapeutic purposes. Nanosponges can be referred to as solid porous particles having a capacity to load drugs and other actives into their nanocavity; they can be formulated as oral, parenteral, topical or inhalation dosage forms. Nanosponges offer high drug loading compared to other nanocarriers and are thus suitable for solving issues related to stability, solubility and delayed release of actives. Controlled release of the loaded actives and solubility enhancement of poorly water-soluble drugs are major advantages of nanosponge drug delivery systems.

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.

Structural Chemistry of Human RNA Methyltransferases.

PubMed

Schapira, Matthieu

2016-03-18

RNA methyltransferases (RNMTs) play important roles in RNA stability, splicing, and epigenetic mechanisms. They constitute a promising target class that is underexplored by the medicinal chemistry community. Information of relevance to drug design can be extracted from the rich structural coverage of human RNMTs. In this work, the structural chemistry of this protein family is analyzed in depth. Unlike most methyltransferases, RNMTs generally feature a substrate-binding site that is largely open on the cofactor-binding pocket, favoring the design of bisubstrate inhibitors. Substrate purine or pyrimidines are often sandwiched between hydrophobic walls that can accommodate planar ring systems. When the substrate base is laying on a shallow surface, a 5' flanking base is sometimes anchored in a druggable cavity. The cofactor-binding site is structurally more diverse than in protein methyltransferases and more druggable in SPOUT than in Rossman-fold enzymes. Finally, conformational plasticity observed both at the substrate and cofactor binding sites may be a challenge for structure-based drug design. The landscape drawn here may inform ongoing efforts toward the discovery of the first human RNMT inhibitors.

Experiences in fragment-based drug discovery.

PubMed

Murray, Christopher W; Verdonk, Marcel L; Rees, David C

2012-05-01

Fragment-based drug discovery (FBDD) has become established in both industry and academia as an alternative approach to high-throughput screening for the generation of chemical leads for drug targets. In FBDD, specialised detection methods are used to identify small chemical compounds (fragments) that bind to the drug target, and structural biology is usually employed to establish their binding mode and to facilitate their optimisation. In this article, we present three recent and successful case histories in FBDD. We then re-examine the key concepts and challenges of FBDD with particular emphasis on recent literature and our own experience from a substantial number of FBDD applications. Our opinion is that careful application of FBDD is living up to its promise of delivering high quality leads with good physical properties and that in future many drug molecules will be derived from fragment-based approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.

Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design-Part 1.

PubMed

Cheruvallath, Zacharia; Tang, Mingnam; McBride, Christopher; Komandla, Mallareddy; Miura, Joanne; Ton-Nu, Thu; Erikson, Phil; Feng, Jun; Farrell, Pamela; Lawson, J David; Vanderpool, Darin; Wu, Yiqin; Dougan, Douglas R; Plonowski, Artur; Holub, Corine; Larson, Chris

2016-06-15

Methionine aminopeptidase 2 (MetAP2) is an enzyme that cleaves an N-terminal methionine residue from a number of newly synthesized proteins. Pre-clinical and clinical studies suggest that MetAP2 inhibitors could be used as a novel treatment for obesity. Herein we describe our use of fragment screening methods and structural biology to quickly identify and elaborate an indazole fragment into a series of reversible MetAP2 inhibitors with <10nM potency, excellent selectivity, and favorable in vitro safety profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

A receptor-grounded approach to teaching nonsteroidal antiinflammatory drug chemistry and structure-activity relationships.

PubMed

Roche, Victoria F

2009-12-17

To describe a receptor-based approach to promote learning about nonsteroidal anti-inflammatory drug (NSAID) chemistry, structure-activity relationships, and therapeutic decision-making. Three lessons on cyclooxygenase (COX) and NSAID chemistry, and NSAID therapeutic utility, were developed using text-based resources and primary medicinal chemistry and pharmacy practice literature. Learning tools were developed to assist students in content mastery. Student learning was evaluated via performance on quizzes and examinations that measured understanding of COX and NSAID chemistry, and the application of that knowledge to therapeutic problem solving. Student performance on NSAID-focused quizzes and examinations documented the success of this approach.

Drug delivery with microsecond laser pulses into gelatin.

PubMed

Shangguan, H; Casperson, L W; Shearin, A; Gregory, K W; Prahl, S A

1996-07-01

Photo acoustic drug delivery is a technique for localized drug delivery by laser-induced hydrodynamic pressure following cavitation bubble expansion and collapse. Photoacoustic drug delivery was investigated on gelatin-based thrombus models with planar and cylindrical geometries by use of one microsecond laser pulses. Solutions of a hydrophobic dye in mineral oil permitted monitoring of delivered colored oil into clear gelatin-based thrombus models. Cavitation bubble development and photoacoustic drug delivery were visualized with flash photography. This study demonstrated that cavitation is the governing mechanism for photoacoustic drug delivery, and the deepest penetration of colored oil in gels followed the bubble collapse. Spatial distribution measurements revealed that colored oil could be driven a few millimeters into the gels in both axial and radial directions, and the penetration was less than 500 µm when the gelatin structure was not fractured.

Implications of protein- and Peptide-based nanoparticles as potential vehicles for anticancer drugs.

PubMed

Elzoghby, Ahmed O; Elgohary, Mayada M; Kamel, Nayra M

2015-01-01

Protein-based nanocarriers have gained considerable attention as colloidal carrier systems for the delivery of anticancer drugs. Protein nanocarriers possess various advantages including their low cytotoxicity, abundant renewable sources, high drug-binding capacity, and significant uptake into the targeted tumor cells. Moreover, the unique protein structure offers the possibility of site-specific drug conjugation and tumor targeting using various ligands modifying the surface of protein nanocarriers. In this chapter, we highlight the most important applications of protein nanoparticles (NPs) for the delivery of anticancer drugs. We examine the various techniques that have been utilized for the preparation of anticancer drug-loaded protein NPs. Finally, the current chapter also reviews the major outcomes of the in vitro and in vivo investigations of surface-modified tumor-targeted protein NPs. © 2015 Elsevier Inc. All rights reserved.

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

PubMed

Uesawa, Yoshihiro

2018-01-01

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

26th National Medicinal Chemistry Symposium--Developments in chemokines, carbohydrates, p53 and drug metabolism. 14-18 June 1998, Richmond, Virginia, USA.

PubMed

Swords, B

1998-08-01

This symposium, organized by the American Chemical Society, is held every two years. This year's meeting, sponsored by the ACS and The Virginia Commonwealth University, was attended by approximately 300 delegates and covered developments in chemokines, carbohydrates, p53, drug metabolism, prodrugs, structure-based design and molecular modeling. At the opening ceremony, John Topliss began by paying tribute to the distinguished medicinal chemistry career of Alfred Burger (University of Virginia, USA). He then reviewed the application of physicochemical principles to drug design, including the development and application of quantitative structure-activity relationship methodology.

LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

PubMed

González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

2012-03-01

Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.

Beyond Membrane Protein Structure: Drug Discovery, Dynamics and Difficulties.

PubMed

Biggin, Philip C; Aldeghi, Matteo; Bodkin, Michael J; Heifetz, Alexander

2016-01-01

Most of the previous content of this book has focused on obtaining the structures of membrane proteins. In this chapter we explore how those structures can be further used in two key ways. The first is their use in structure based drug design (SBDD) and the second is how they can be used to extend our understanding of their functional activity via the use of molecular dynamics. Both aspects now heavily rely on computations. This area is vast, and alas, too large to consider in depth in a single book chapter. Thus where appropriate we have referred the reader to recent reviews for deeper assessment of the field. We discuss progress via the use of examples from two main drug target areas; G-protein coupled receptors (GPCRs) and ion channels. We end with a discussion of some of the main challenges in the area.

Allosteric Tuning of Caspase-7: A Fragment-Based Drug Discovery Approach.

PubMed

Vance, Nicholas R; Gakhar, Lokesh; Spies, M Ashley

2017-11-13

The caspase family of cysteine proteases are highly sought-after drug targets owing to their essential roles in apoptosis, proliferation, and inflammation pathways. High-throughput screening efforts to discover inhibitors have gained little traction. Fragment-based screening has emerged as a powerful approach for the discovery of innovative drug leads. This method has become a central facet of drug discovery campaigns in the pharmaceutical industry and academia. A fragment-based drug discovery campaign against human caspase-7 resulted in the discovery of a novel series of allosteric inhibitors. An X-ray crystal structure of caspase-7 bound to a fragment hit and a thorough kinetic characterization of a zymogenic form of the enzyme were used to investigate the allosteric mechanism of inhibition. This work further advances our understanding of the mechanisms of allosteric control of this class of pharmaceutically relevant enzymes, and provides a new path forward for drug discovery efforts. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds.

PubMed

Baurin, N; Baker, R; Richardson, C; Chen, I; Foloppe, N; Potter, A; Jordan, A; Roughley, S; Parratt, M; Greaney, P; Morley, D; Hubbard, R E

2004-01-01

We have implemented five drug-like filters, based on 1D and 2D molecular descriptors, and applied them to characterize the drug-like properties of commercially available chemical compounds. In addition to previously published filters (Lipinski and Veber), we implemented a filter for medicinal chemistry tractability based on lists of chemical features drawn up by a panel of medicinal chemists. A filter based on the modeling of aqueous solubility (>1 microM) was derived in-house, as well as another based on the modeling of Caco-2 passive membrane permeability (>10 nm/s). A library of 2.7 million compounds was collated from the 23 compound suppliers and analyzed with these filters, highlighting a tendency toward highly lipophilic compounds. The library contains 1.6 M unique structures, of which 37% (607,223) passed all five drug-like filters. None of the 23 suppliers provides all the members of the drug-like subset, emphasizing the benefit of considering compounds from various compound suppliers as a source of diversity for drug discovery.

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.

Structural basis of RND-type multidrug exporters

PubMed Central

Yamaguchi, Akihito; Nakashima, Ryosuke; Sakurai, Keisuke

2015-01-01

Bacterial multidrug exporters are intrinsic membrane transporters that act as cellular self-defense mechanism. The most notable characteristics of multidrug exporters is that they export a wide range of drugs and toxic compounds. The overexpression of these exporters causes multidrug resistance. Multidrug-resistant pathogens have become a serious problem in modern chemotherapy. Over the past decade, investigations into the structure of bacterial multidrug exporters have revealed the multidrug recognition and export mechanisms. In this review, we primarily discuss RND-type multidrug exporters particularly AcrAB-TolC, major drug exporter in Gram-negative bacteria. RND-type drug exporters are tripartite complexes comprising a cell membrane transporter, an outer membrane channel and an adaptor protein. Cell membrane transporters and outer membrane channels are homo-trimers; however, there is no consensus on the number of adaptor proteins in these tripartite complexes. The three monomers of a cell membrane transporter have varying conformations (access, binding, and extrusion) during transport. Drugs are exported following an ordered conformational change in these three monomers, through a functional rotation mechanism coupled with the proton relay cycle in ion pairs, which is driven by proton translocation. Multidrug recognition is based on a multisite drug-binding mechanism, in which two voluminous multidrug-binding pockets in cell membrane exporters recognize a wide range of substrates as a result of permutations at numerous binding sites that are specific for the partial structures of substrate molecules. The voluminous multidrug-binding pocket may have numerous binding sites even for a single substrate, suggesting that substrates may move between binding sites during transport, an idea named as multisite-drug-oscillation hypothesis. This hypothesis is consistent with the apparently broad substrate specificity of cell membrane exporters and their highly efficient ejection of drugs from the cell. Substrates are transported through dual multidrug-binding pockets via the peristaltic motion of the substrate translocation channel. Although there are no clinically available inhibitors of bacterial multidrug exporters, efforts to develop inhibitors based on structural information are underway. PMID:25941524

Structural basis of RND-type multidrug exporters.

PubMed

Yamaguchi, Akihito; Nakashima, Ryosuke; Sakurai, Keisuke

2015-01-01

Bacterial multidrug exporters are intrinsic membrane transporters that act as cellular self-defense mechanism. The most notable characteristics of multidrug exporters is that they export a wide range of drugs and toxic compounds. The overexpression of these exporters causes multidrug resistance. Multidrug-resistant pathogens have become a serious problem in modern chemotherapy. Over the past decade, investigations into the structure of bacterial multidrug exporters have revealed the multidrug recognition and export mechanisms. In this review, we primarily discuss RND-type multidrug exporters particularly AcrAB-TolC, major drug exporter in Gram-negative bacteria. RND-type drug exporters are tripartite complexes comprising a cell membrane transporter, an outer membrane channel and an adaptor protein. Cell membrane transporters and outer membrane channels are homo-trimers; however, there is no consensus on the number of adaptor proteins in these tripartite complexes. The three monomers of a cell membrane transporter have varying conformations (access, binding, and extrusion) during transport. Drugs are exported following an ordered conformational change in these three monomers, through a functional rotation mechanism coupled with the proton relay cycle in ion pairs, which is driven by proton translocation. Multidrug recognition is based on a multisite drug-binding mechanism, in which two voluminous multidrug-binding pockets in cell membrane exporters recognize a wide range of substrates as a result of permutations at numerous binding sites that are specific for the partial structures of substrate molecules. The voluminous multidrug-binding pocket may have numerous binding sites even for a single substrate, suggesting that substrates may move between binding sites during transport, an idea named as multisite-drug-oscillation hypothesis. This hypothesis is consistent with the apparently broad substrate specificity of cell membrane exporters and their highly efficient ejection of drugs from the cell. Substrates are transported through dual multidrug-binding pockets via the peristaltic motion of the substrate translocation channel. Although there are no clinically available inhibitors of bacterial multidrug exporters, efforts to develop inhibitors based on structural information are underway.

The Impact of Engagement in Street-based Income Generation Activities on Stimulant Drug Use Cessation among People who Inject Drugs

PubMed Central

Ti, Lianping; Richardson, Lindsey; DeBeck, Kora; Nguyen, Paul; Montaner, Julio; Wood, Evan; Kerr, Thomas

2014-01-01

Background Despite the growing prevalence of illicit stimulant drug use internationally, and the widespread involvement of people who inject drugs (IDU) within street-based drug markets, little is known about the impact of different types of street-based income generation activities on the cessation of stimulant use among IDU. Methods Data were derived from an open prospective cohort of IDU in Vancouver, Canada. We used Kaplan-Meier methods and Cox proportional hazards regression to examine the effect of different types of street-based income generation activities (e.g., sex work, drug dealing, and scavenging) on time to cessation of stimulant use. Results Between December, 2005 and November, 2012, 887 IDU who use stimulant drugs (cocaine, crack cocaine, or crystal methamphetamine) were prospectively followed-up for a median duration of 47 months. In Kaplan-Meier analyses, compared to those who did not engage in street-based income generation activities, participants who reported sex work, drug dealing, scavenging, or more than one of these activities were significantly less likely to report stimulant drug use cessation (all p<0.001). When considered as time-updated variables and adjusted for potential confounders in a multivariable model, each type of street-based income generation activity remained significantly associated with a slower time to stimulant drug cessation (all p<0.005). Conclusions Our findings highlight the urgent need for strategies to address stimulant dependence, including novel pharmacotherapies. Also important, structural interventions, such as low-threshold employment opportunities, availability of supportive housing, legal reforms regarding drug use, and evidence-based approaches that reduce harm among IDU are urgently required. PMID:24909853

The impact of engagement in street-based income generation activities on stimulant drug use cessation among people who inject drugs.

PubMed

Ti, Lianping; Richardson, Lindsey; DeBeck, Kora; Nguyen, Paul; Montaner, Julio; Wood, Evan; Kerr, Thomas

2014-08-01

Despite the growing prevalence of illicit stimulant drug use internationally, and the widespread involvement of people who inject drugs (IDU) within street-based drug markets, little is known about the impact of different types of street-based income generation activities on the cessation of stimulant use among IDU. Data were derived from an open prospective cohort of IDU in Vancouver, Canada. We used Kaplan-Meier methods and Cox proportional hazards regression to examine the effect of different types of street-based income generation activities (e.g., sex work, drug dealing, and scavenging) on time to cessation of stimulant use. Between December, 2005 and November, 2012, 887 IDU who use stimulant drugs (cocaine, crack cocaine, or crystal methamphetamine) were prospectively followed-up for a median duration of 47 months. In Kaplan-Meier analyses, compared to those who did not engage in street-based income generation activities, participants who reported sex work, drug dealing, scavenging, or more than one of these activities were significantly less likely to report stimulant drug use cessation (all p<0.001). When considered as time-updated variables and adjusted for potential confounders in a multivariable model, each type of street-based income generation activity remained significantly associated with a slower time to stimulant drug cessation (all p<0.005). Our findings highlight the urgent need for strategies to address stimulant dependence, including novel pharmacotherapies. Also important, structural interventions, such as low-threshold employment opportunities, availability of supportive housing, legal reforms regarding drug use, and evidence-based approaches that reduce harm among IDU are urgently required. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Structure-Based Virtual Screening of Protein Tyrosine Phosphatase Inhibitors: Significance, Challenges, and Solutions.

PubMed

Reddy, Rallabandi Harikrishna; Kim, Hackyoung; Cha, Seungbin; Lee, Bongsoo; Kim, Young Jun

2017-05-28

Phosphorylation, a critical mechanism in biological systems, is estimated to be indispensable for about 30% of key biological activities, such as cell cycle progression, migration, and division. It is synergistically balanced by kinases and phosphatases, and any deviation from this balance leads to disease conditions. Pathway or biological activity-based abnormalities in phosphorylation and the type of involved phosphatase influence the outcome, and cause diverse diseases ranging from diabetes, rheumatoid arthritis, and numerous cancers. Protein tyrosine phosphatases (PTPs) are of prime importance in the process of dephosphorylation and catalyze several biological functions. Abnormal PTP activities are reported to result in several human diseases. Consequently, there is an increased demand for potential PTP inhibitory small molecules. Several strategies in structure-based drug designing techniques for potential inhibitory small molecules of PTPs have been explored along with traditional drug designing methods in order to overcome the hurdles in PTP inhibitor discovery. In this review, we discuss druggable PTPs and structure-based virtual screening efforts for successful PTP inhibitor design.

Dynamic functional connectivity using state-based dynamic community structure: method and application to opioid analgesia.

PubMed

Robinson, Lucy F; Atlas, Lauren Y; Wager, Tor D

2015-03-01

We present a new method, State-based Dynamic Community Structure, that detects time-dependent community structure in networks of brain regions. Most analyses of functional connectivity assume that network behavior is static in time, or differs between task conditions with known timing. Our goal is to determine whether brain network topology remains stationary over time, or if changes in network organization occur at unknown time points. Changes in network organization may be related to shifts in neurological state, such as those associated with learning, drug uptake or experimental conditions. Using a hidden Markov stochastic blockmodel, we define a time-dependent community structure. We apply this approach to data from a functional magnetic resonance imaging experiment examining how contextual factors influence drug-induced analgesia. Results reveal that networks involved in pain, working memory, and emotion show distinct profiles of time-varying connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

How relevant are assembled equilibrium samples in understanding structure formation during lipid digestion?

PubMed

Phan, Stephanie; Salentinig, Stefan; Hawley, Adrian; Boyd, Ben J

2015-10-01

Lipid-based formulations are gaining interest for use as drug delivery systems for poorly water-soluble drug compounds. During digestion, the lipolysis products self-assemble with endogenous surfactants in the gastrointestinal tract to form colloidal structures, enabling enhanced drug solubilisation. Although earlier studies in the literature focus on assembled equilibrium systems, little is known about structure formation under dynamic lipolysis conditions. The purpose of this study was to investigate the likely colloidal structure formation in the small intestine after the ingestion of lipids, under equilibrium and dynamic conditions. The structural aspects were studied using small angle X-ray scattering and dynamic light scattering, and were found to depend on lipid composition, lipid chain length, prandial state and emulsification. Incorporation of phospholipids and lipolysis products into bile salt micelles resulted in swelling of the structure. At insufficient bile salt concentrations, a co-existing lamellar phase was observed, due to a reduction in the solubilisation capacity for lipolysis products. Emulsification accelerated the rate of lipolysis and structure formation. Copyright © 2015 Elsevier B.V. All rights reserved.

Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design-Part 2.

PubMed

McBride, Christopher; Cheruvallath, Zacharia; Komandla, Mallareddy; Tang, Mingnam; Farrell, Pamela; Lawson, J David; Vanderpool, Darin; Wu, Yiqin; Dougan, Douglas R; Plonowski, Artur; Holub, Corine; Larson, Chris

2016-06-15

Methionine aminopeptidase-2 (MetAP2) is an enzyme that cleaves an N-terminal methionine residue from a number of newly synthesized proteins. This step is required before they will fold or function correctly. Pre-clinical and clinical studies with a MetAP2 inhibitor suggest that they could be used as a novel treatment for obesity. Herein we describe the discovery of a series of pyrazolo[4,3-b]indoles as reversible MetAP2 inhibitors. A fragment-based drug discovery (FBDD) approach was used, beginning with the screening of fragment libraries to generate hits with high ligand-efficiency (LE). An indazole core was selected for further elaboration, guided by structural information. SAR from the indazole series led to the design of a pyrazolo[4,3-b]indole core and accelerated knowledge-based fragment growth resulted in potent and efficient MetAP2 inhibitors, which have shown robust and sustainable body weight loss in DIO mice when dosed orally. Copyright © 2016 Elsevier Ltd. All rights reserved.

CREDO: a structural interactomics database for drug discovery

PubMed Central

Schreyer, Adrian M.; Blundell, Tom L.

2013-01-01

CREDO is a unique relational database storing all pairwise atomic interactions of inter- as well as intra-molecular contacts between small molecules and macromolecules found in experimentally determined structures from the Protein Data Bank. These interactions are integrated with further chemical and biological data. The database implements useful data structures and algorithms such as cheminformatics routines to create a comprehensive analysis platform for drug discovery. The database can be accessed through a web-based interface, downloads of data sets and web services at http://www-cryst.bioc.cam.ac.uk/credo. Database URL: http://www-cryst.bioc.cam.ac.uk/credo PMID:23868908

Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry

PubMed Central

2017-01-01

The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein–protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called ‘linear model’, where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world. PMID:28875019

Comparative protein modeling of methionine S-adenosyltransferase (MAT) enzyme from Mycobacterium tuberculosis: a potential target for antituberculosis drug discovery.

PubMed

Khedkar, Santosh A; Malde, Alpeshkumar K; Coutinho, Evans C

2005-01-01

Mycobacterium tuberculosis (Mtb) is a successful pathogen that overcomes the numerous challenges presented by the immune system of the host. In the last 40 years few anti-TB drugs have been developed, while the drug-resistance problem is increasing; there is thus a pressing need to develop new anti-TB drugs active against both the acute and chronic growth phases of the mycobacterium. Methionine S-adenosyltransferase (MAT) is an enzyme involved in the synthesis of S-adenosylmethionine (SAM), a methyl donor essential for mycolipid biosynthesis. As an anti-TB drug target, Mtb-MAT has been well validated. A homology model of MAT has been constructed using the X-ray structures of E. coli MAT (PDB code: 1MXA) and rat MAT (PDB code: 1QM4) as templates, by comparative protein modeling principles. The resulting model has the correct stereochemistry as gauged from the Ramachandran plot and good three-dimensional (3D) structure compatibility as assessed by the Profiles-3D score. The structurally and functionally important residues (active site) of Mtb-MAT have been identified using the E. coli and rat MAT crystal structures and the reported point mutation data. The homology model conserves the topological and active site features of the MAT family of proteins. The differences in the molecular electrostatic potentials (MEP) of Mtb and human MAT provide evidences that selective and specific Mtb-MAT inhibitors can be designed using the homology model, by the structure-based drug design approaches.

Shipment of a photodynamic therapy agent into model membrane and its controlled release: A photophysical approach.

PubMed

Karar, Monaj; Paul, Suvendu; Mallick, Arabinda; Majumdar, Tapas

2018-01-01

Harmine, an efficient cancer cell photosensitizer (PS), emits intense violet color when it is incorporated in well established self assembly based drug carrier formed by cationic surfactants of identical positive charge of head group but varying chain length, namely, dodecyltrimethylammonium bromide (DTAB), tetradecyltrimethylammonium bromide (TTAB) and cetyltrimethylammonium bromide (CTAB). Micelle entrapped drug emits in the UV region when it interacts with non-toxic β-cyclodextrin (β-CD). Inspired by these unique fluorescence/structural switching properties of the anticancer drug, in the present work we have monitored the interplay of the drug between micelles and non-toxic β-CDs. We have observed that the model membranes formed by micelles differing in their hydrophobic chain length interact with the drug differently. Variation in the surfactant chain length plays an important role for structural switching i.e. in choosing a particular structural form of the drug that will be finally presented to their targets. The present study shows that in case of necessity, the bound drug molecule can be removed from its binding site in a controlled manner by the use of non-toxic β-CD and it is exploited to serve a significant purpose for the removal of excess/unused adsorbed drugs from the model cell membranes. We believe this kind of β-CD driven translocation of drugs monitored by fluorescence switching may find possible applications in controlled release of the drug inside cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure.

PubMed

Bender, Andreas; Scheiber, Josef; Glick, Meir; Davies, John W; Azzaoui, Kamal; Hamon, Jacques; Urban, Laszlo; Whitebread, Steven; Jenkins, Jeremy L

2007-06-01

Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from findings in clinical trials, animal experiments, and molecular studies going back more than forty years. In this work we explore PSP chemical space and its relevance for the prediction of adverse drug reactions. Firstly, in silico (computational) Bayesian models for 70 PSP-related targets were built, which are able to detect 93% of the ligands binding at IC(50) < or = 10 microM at an overall correct classification rate of about 94%. Secondly, employing the World Drug Index (WDI), a model for adverse drug reactions was built directly based on normalized side-effect annotations in the WDI, which does not require any underlying functional knowledge. This is, to our knowledge, the first attempt to predict adverse drug reactions across hundreds of categories from chemical structure alone. On average 90% of the adverse drug reactions observed with known, clinically used compounds were detected, an overall correct classification rate of 92%. Drugs withdrawn from the market (Rapacuronium, Suprofen) were tested in the model and their predicted ADRs align well with known ADRs. The analysis was repeated for acetylsalicylic acid and Benperidol which are still on the market. Importantly, features of the models are interpretable and back-projectable to chemical structure, raising the possibility of rationally engineering out adverse effects. By combining PSP and ADR models new hypotheses linking targets and adverse effects can be proposed and examples for the opioid mu and the muscarinic M2 receptors, as well as for cyclooxygenase-1 are presented. It is hoped that the generation of predictive models for adverse drug reactions is able to help support early SAR to accelerate drug discovery and decrease late stage attrition in drug discovery projects. In addition, models such as the ones presented here can be used for compound profiling in all development stages.

Structure of the Trypanosoma cruzi protein tyrosine phosphatase TcPTP1, a potential therapeutic target for Chagas' disease

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

Lountos, George T.; Tropea, Joseph E.; Waugh, David S.

2013-06-05

Chagas’ disease, a neglected tropical affliction transmitted by the flagellated protozoan Trypanosoma cruzi, is prevalent in Latin America and affects nearly 18 million people worldwide, yet few approved drugs are available to treat the disease. Moreover, the currently available drugs exhibit severe toxicity or are poorly effective in the chronic phase of the disease. This limitation, along with the large population at risk, underscores the urgent need to discover new molecular targets and novel therapeutic agents. Recently, the T. cruzi protein tyrosine phosphatase TcPTP1 has been implicated in the cellular differentiation and infectivity of the parasite and is therefore amore » promising target for the design of novel anti-parasitic drugs. Here, we report the X-ray crystal structure of TcPTP1 refined to a resolution of 2.18 Å, which provides structural insights into the active site environment that can be used to initiate structure-based drug design efforts to develop specific TcPTP1 inhibitors. Potential strategies to develop such inhibitors are also discussed.« less

Ensemble-based docking: From hit discovery to metabolism and toxicity predictions

DOE PAGES

Evangelista, Wilfredo; Weir, Rebecca; Ellingson, Sally; ...

2016-07-29

The use of ensemble-based docking for the exploration of biochemical pathways and toxicity prediction of drug candidates is described. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.

Crystal structure of an EfPDF complex with Met-Ala-Ser based on crystallographic packing.

PubMed

Nam, Ki Hyun; Kim, Kook-Han; Kim, Eunice Eun Kyeong; Hwang, Kwang Yeon

2009-04-17

PDF (peptide deformylase) plays a critical role in the production of mature proteins by removing the N-formyl polypeptide of nascent proteins in the prokaryote cell system. This protein is essential for bacterial growth, making it an attractive target for the design of new antibiotics. Accordingly, PDF has been evaluated as a drug target; however, architectural mechanism studies of PDF have not yet fully elucidated its molecular function. We recently reported the crystal structure of PDF produced by Enterococcus faecium [K.H. Nam, J.I. Ham, A. Priyadarshi, E.E. Kim, N. Chung, K.Y. Hwang, "Insight into the antibacterial drug design and architectural mechanism of peptide recognition from the E. faecium peptide deformylase structure", Proteins 74 (2009) 261-265]. Here, we present the crystal structure of the EfPDF complex with MAS (Met-Ser-Ala), thereby not only delineating the architectural mechanism for the recognition of mimic-peptides by N-terminal cleaved expression peptide, but also suggesting possible targets for rational design of antibacterial drugs. In addition to their implications for drug design, these structural studies will facilitate elucidation of the architectural mechanism responsible for the peptide recognition of PDF.

Nexus Between Protein–Ligand Affinity Rank-Ordering, Biophysical Approaches, and Drug Discovery

PubMed Central

2013-01-01

The confluence of computational and biophysical methods to accurately rank-order the binding affinities of small molecules and determine structures of macromolecular complexes is a potentially transformative advance in the work flow of drug discovery. This viewpoint explores the impact that advanced computational methods may have on the efficacy of small molecule drug discovery and optimization, particularly with respect to emerging fragment-based methods. PMID:24900579

A Rapid Python-Based Methodology for Target-Focused Combinatorial Library Design.

PubMed

Li, Shiliang; Song, Yuwei; Liu, Xiaofeng; Li, Honglin

2016-01-01

The chemical space is so vast that only a small portion of it has been examined. As a complementary approach to systematically probe the chemical space, virtual combinatorial library design has extended enormous impacts on generating novel and diverse structures for drug discovery. Despite the favorable contributions, high attrition rates in drug development that mainly resulted from lack of efficacy and side effects make it increasingly challenging to discover good chemical starting points. In most cases, focused libraries, which are restricted to particular regions of the chemical space, are deftly exploited to maximize hit rate and improve efficiency at the beginning of the drug discovery and drug development pipeline. This paper presented a valid methodology for fast target-focused combinatorial library design in both reaction-based and production-based ways with the library creating rates of approximately 70,000 molecules per second. Simple, quick and convenient operating procedures are the specific features of the method. SHAFTS, a hybrid 3D similarity calculation software, was embedded to help refine the size of the libraries and improve hit rates. Two target-focused (p38-focused and COX2-focused) libraries were constructed efficiently in this study. This rapid library enumeration method is portable and applicable to any other targets for good chemical starting points identification collaborated with either structure-based or ligand-based virtual screening.

Drug discovery based on genetic and metabolic findings in schizophrenia.

PubMed

Dwyer, Donard S; Weeks, Kathrine; Aamodt, Eric J

2008-11-01

Recent progress in the genetics of schizophrenia provides the rationale for re-evaluating causative factors and therapeutic strategies for this disease. Here, we review the major candidate susceptibility genes and relate the aberrant function of these genes to defective regulation of energy metabolism in the schizophrenic brain. Disturbances in energy metabolism potentially lead to neurodevelopmental deficits, impaired function of the mature nervous system and failure to maintain neurites/dendrites and synaptic connections. Current antipsychotic drugs do not specifically address these underlying deficits; therefore, a new generation of more effective medications is urgently needed. Novel targets for future drug discovery are identified in this review. The coordinated application of structure-based drug design, systems biology and research on model organisms may greatly facilitate the search for next-generation antipsychotic drugs.

Binding thermodynamics discriminates fragments from druglike compounds: a thermodynamic description of fragment-based drug discovery.

PubMed

Williams, Glyn; Ferenczy, György G; Ulander, Johan; Keserű, György M

2017-04-01

Small is beautiful - reducing the size and complexity of chemical starting points for drug design allows better sampling of chemical space, reveals the most energetically important interactions within protein-binding sites and can lead to improvements in the physicochemical properties of the final drug. The impact of fragment-based drug discovery (FBDD) on recent drug discovery projects and our improved knowledge of the structural and thermodynamic details of ligand binding has prompted us to explore the relationships between ligand-binding thermodynamics and FBDD. Information on binding thermodynamics can give insights into the contributions to protein-ligand interactions and could therefore be used to prioritise compounds with a high degree of specificity in forming key interactions. Copyright © 2016 Elsevier Ltd. All rights reserved.

The impact of structural biology in medicine illustrated with four case studies.

PubMed

Hu, Tiancen; Sprague, Elizabeth R; Fodor, Michelle; Stams, Travis; Clark, Kirk L; Cowan-Jacob, Sandra W

2018-01-01

The contributions of structural biology to drug discovery have expanded over the last 20 years from structure-based ligand optimization to a broad range of clinically relevant topics including the understanding of disease, target discovery, screening for new types of ligands, discovery of new modes of action, addressing clinical challenges such as side effects or resistance, and providing data to support drug registration. This expansion of scope is due to breakthroughs in the technology, which allow structural information to be obtained rapidly and for more complex molecular systems, but also due to the combination of different technologies such as X-ray, NMR, and other biophysical methods, which allows one to get a more complete molecular understanding of disease and ways to treat it. In this review, we provide examples of the types of impact molecular structure information can have in the clinic for both low molecular weight and biologic drug discovery and describe several case studies from our own work to illustrate some of these contributions.

DNA Trojan Horses: Self-Assembled Floxuridine-Containing DNA Polyhedra for Cancer Therapy.

PubMed

Mou, Quanbing; Ma, Yuan; Pan, Gaifang; Xue, Bai; Yan, Deyue; Zhang, Chuan; Zhu, Xinyuan

2017-10-02

Based on their structural similarity to natural nucleobases, nucleoside analogue therapeutics were integrated into DNA strands through conventional solid-phase synthesis. By elaborately designing their sequences, floxuridine-integrated DNA strands were synthesized and self-assembled into well-defined DNA polyhedra with definite drug-loading ratios as well as tunable size and morphology. As a novel drug delivery system, these drug-containing DNA polyhedra could ideally mimic the Trojan Horse to deliver chemotherapeutics into tumor cells and fight against cancer. Both in vitro and in vivo results demonstrate that the DNA Trojan horse with buckyball architecture exhibits superior anticancer capability over the free drug and other formulations. With precise control over the drug-loading ratio and structure of the nanocarriers, the DNA Trojan horse may play an important role in anticancer treatment and exhibit great potential in translational nanomedicine. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs

PubMed Central

2016-01-01

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages. PMID:27074285

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.

PubMed

Wagner, Jeffrey R; Lee, Christopher T; Durrant, Jacob D; Malmstrom, Robert D; Feher, Victoria A; Amaro, Rommie E

2016-06-08

Allosteric drug development holds promise for delivering medicines that are more selective and less toxic than those that target orthosteric sites. To date, the discovery of allosteric binding sites and lead compounds has been mostly serendipitous, achieved through high-throughput screening. Over the past decade, structural data has become more readily available for larger protein systems and more membrane protein classes (e.g., GPCRs and ion channels), which are common allosteric drug targets. In parallel, improved simulation methods now provide better atomistic understanding of the protein dynamics and cooperative motions that are critical to allosteric mechanisms. As a result of these advances, the field of predictive allosteric drug development is now on the cusp of a new era of rational structure-based computational methods. Here, we review algorithms that predict allosteric sites based on sequence data and molecular dynamics simulations, describe tools that assess the druggability of these pockets, and discuss how Markov state models and topology analyses provide insight into the relationship between protein dynamics and allosteric drug binding. In each section, we first provide an overview of the various method classes before describing relevant algorithms and software packages.

Insights from investigating the interactions of adamantane-based drugs with the M2 proton channel from the H1N1 swine virus

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

Wang, Jing-Fang; Wei, Dong-Qing, E-mail: dqwei@gordonlifescience.org; Gordon Life Science Institute, 13784 Torrey Del Mar Drive, San Diego, CA 92130

The M2 proton channel is one of indispensable components for the influenza A virus that plays a vital role in its life cycle and hence is an important target for drug design against the virus. In view of this, the three-dimensional structure of the H1N1-M2 channel was developed based on the primary sequence taken from a patient recently infected by the H1N1 (swine flu) virus. With an explicit water-membrane environment, molecular docking studies were performed for amantadine and rimantadine, the two commercial drugs generally used to treat influenza A infection. It was found that their binding affinity to the H1N1-M2more » channel is significantly lower than that to the H5N1-M2 channel, fully consistent with the recent report that the H1N1 swine virus was resistant to the two drugs. The findings and the relevant analysis reported here might provide useful structural insights for developing effective drugs against the new swine flu virus.« less

Droplet-based microfluidic system for multicellular tumor spheroid formation and anticancer drug testing.

PubMed

Yu, Linfen; Chen, Michael C W; Cheung, Karen C

2010-09-21

Creating multicellular tumor spheroids is critical for characterizing anticancer treatments since it may provide a better model than monolayer culture of tumor cells. Moreover, continuous dynamic perfusion allows the establishment of long term cell culture and subsequent multicellular spheroid formation. A droplet-based microfluidic system was used to form alginate beads with entrapped breast tumor cells. After gelation, the alginate beads were trapped in microsieve structures for cell culture in a continuous perfusion system. The alginate environment permitted cell proliferation and the formation of multicellular spheroids was observed. The dose-dependent response of the tumor spheroids to doxorubicin, and anticancer drug, showed multicellular resistance compared to conventional monolayer culture. The microsieve structures maintain constant location of each bead in the same position throughout the device seeding process, cell proliferation and spheroid formation, treatment with drug, and imaging, permitting temporal and spatial tracking.

The Chemical Basis of Pharmacology

PubMed Central

2010-01-01

Molecular biology now dominates pharmacology so thoroughly that it is difficult to recall that only a generation ago the field was very different. To understand drug action today, we characterize the targets through which they act and new drug leads are discovered on the basis of target structure and function. Until the mid-1980s the information often flowed in reverse: investigators began with organic molecules and sought targets, relating receptors not by sequence or structure but by their ligands. Recently, investigators have returned to this chemical view of biology, bringing to it systematic and quantitative methods of relating targets by their ligands. This has allowed the discovery of new targets for established drugs, suggested the bases for their side effects, and predicted the molecular targets underlying phenotypic screens. The bases for these new methods, some of their successes and liabilities, and new opportunities for their use are described. PMID:21058655

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

PubMed Central

Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

2015-01-01

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

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

PubMed

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

2017-09-01

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

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers.

PubMed

Cao, Han; Ng, Marcus C K; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W I

2017-09-01

[Formula: see text]-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM . Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers

NASA Astrophysics Data System (ADS)

Cao, Han; Ng, Marcus C. K.; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W. I.

2017-09-01

α-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM. Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

PubMed Central

2016-01-01

Abstract Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. PMID:26813336

Preparation and investigation of novel gastro-floating tablets with 3D extrusion-based printing.

PubMed

Li, Qijun; Guan, Xiaoying; Cui, Mengsuo; Zhu, Zhihong; Chen, Kai; Wen, Haoyang; Jia, Danyang; Hou, Jian; Xu, Wenting; Yang, Xinggang; Pan, Weisan

2018-01-15

Three dimensional (3D) extrusion-based printing is a paste-based rapid prototyping process, which is capable of building complex 3D structures. The aim of this study was to explore the feasibility of 3D extrusion-based printing as a pharmaceutical manufacture technique for the fabrication of gastro-floating tablets. Novel low-density lattice internal structure gastro-floating tablets of dipyridamole were developed to prolong the gastric residence time in order to improve drug release rate and consequently, improve bioavailability and therapeutic efficacy. Excipients commonly employed in the pharmaceutical study could be efficiently applied in the room temperature 3D extrusion-based printing process. The tablets were designed with three kinds of infill percentage and prepared by hydroxypropyl methylcellulose (HPMC K4M) and hydroxypropyl methylcellulose (HPMC E15) as hydrophilic matrices and microcrystalline cellulose (MCC PH101) as extrusion molding agent. In vitro evaluation of the 3D printed gastro-floating tablets was performed by determining mechanical properties, content uniformity, and weight variation. Furthermore, re-floating ability, floating duration time, and drug release behavior were also evaluated. Dissolution profiles revealed the relationship between infill percentage and drug release behavior. The results of this study revealed the potential of 3D extrusion-based printing to fabricate gastro-floating tablets with more than 8h floating process with traditional pharmaceutical excipients and lattice internal structure design. Copyright © 2017. Published by Elsevier B.V.

A perspective on targeting non-structural proteins to combat neglected tropical diseases: Dengue, West Nile and Chikungunya viruses.

PubMed

Bhakat, Soumendranath; Karubiu, Wilson; Jayaprakash, Venkatesan; Soliman, Mahmoud E S

2014-11-24

Neglected tropical diseases are major causes of fatality in poverty stricken regions across Africa, Asia and some part of America. The combined potential health risk associated with arthropod-borne viruses (arboviruses); Dengue virus (DENV), West Nile Virus (WNV) and Chikungunya Virus (CHIKV) is immense. These arboviruses are either emerging or re-emerging in many regions with recent documented outbreaks in the United States. Despite several recent evidences of emergence, currently there are no approved drugs or vaccines available to counter these diseases. Non-structural proteins encoded by these RNA viruses are essential for their replication and maturation and thus may offer ideal targets for developing antiviral drugs. In recent years, several protease inhibitors have been sourced from plant extract, synthesis, computer aided drug design and high throughput screening as well as through drug reposition based approaches to target the non-structural proteins. The protease inhibitors have shown different levels of inhibition and may thus provide template to develop selective and potent drugs against these devastating arboviruses. This review seeks to shed light on the design and development of antiviral drugs against DENV, WNV and CHIKV to date. To the best of our knowledge, this review provides the first comprehensive update on the development of protease inhibitors targeting non-structural proteins of three most devastating arboviruses, DENV, WNV and CHIKV. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Molecular modeling on streptolysin-O of multidrug resistant Streptococcus pyogenes and computer aided screening and in vitro assay for novel herbal inhibitors.

PubMed

Skariyachan, Sinosh; Narayan, Naik Sowmyalaxmi; Aggimath, Tejaswini S; Nagaraj, Sushmitha; Reddy, Monika S; Narayanappa, Rajeswari

2014-03-01

Streptococcus pyogenes is a notorious pathogenic bacterium which causes various human diseases ranging from localized infections to life threatening invasive diseases. Streptolysin-O (SLO), pore-forming thiol-activated cytolysin, is the major virulent factor for streptococcal infections. Present therapies against streptococcal infections are limited as most of the strains have developed multi-drug resistance to present generation of drugs. Hence, there is a need for alternative therapeutic substances. Structure based virtual screening is a novel platform to select lead molecules with better pharmacokinetic properties. The 3D structure of SLO (not available in native form), essential for such studies, was computationally generated and this homology model was used as probable drug target. Based on literature survey, several phytoligands from 25 medicinal plants were selected. Out of these, leads from 11 plants showed better pharmacokinetic properties. The best lead molecules were screened based on computer aided drug likeness and pharmacokinetic predictions. The inhibitory properties of selected herbal leads against SLO were studied by molecular docking. An in vitro assay was further carried out and variations observed were found to be significant (p<0.05). Antibiotic sensitivity testing was also performed with the clinical strain of Streptococcus pyogenes with conventional drugs. The clinical strain showed multi-drug resistance to conventional drugs. Our study revealed that numerous phytoligands have better inhibitory properties towards the toxin. We noticed that incorporation of selected herbal extracts in blood agar medium showed significant reduction in hemolysis (MIC 300μl/plate), indicating inhibition of SLO. Furthermore, the butanol extracts of selected herbal preparation based on computer aided screening showed significant inhibitory properties at 250 mcg/disc concentration. We also noticed that selected herbal formulations have better antimicrobial properties at MIC range of 300- 400μl. Hence, our study suggests that these herbal extracts have better inhibitory properties against the toxin as well as drug resistant Streptococcus pyogenes.

Hollow superparamagnetic iron oxide nanoshells as a hydrophobic anticancer drug carrier: intracelluar pH-dependent drug release and enhanced cytotoxicity

NASA Astrophysics Data System (ADS)

Zhu, Xiao-Ming; Yuan, Jing; Leung, Ken Cham-Fai; Lee, Siu-Fung; Sham, Kathy W. Y.; Cheng, Christopher H. K.; Au, Doris W. T.; Teng, Gao-Jun; Ahuja, Anil T.; Wang, Yi-Xiang J.

2012-08-01

With curcumin and doxorubicin (DOX) base as model drugs, intracellular delivery of hydrophobic anticancer drugs by hollow structured superparamagnetic iron oxide (SPIO) nanoshells (hydrodynamic diameter: 191.9 +/- 2.6 nm) was studied in glioblastoma U-87 MG cells. SPIO nanoshell-based encapsulation provided a stable aqueous dispersion of the curcumin. After the SPIO nanoshells were internalized by U-87 MG cells, they localized at the acidic compartments of endosomes and lysosomes. In endosome/lysosome-mimicking buffers with a pH of 4.5-5.5, pH-dependent drug release was observed from curcumin or DOX loaded SPIO nanoshells (curcumin/SPIO or DOX/SPIO). Compared with the free drug, the intracellular curcumin content delivered via curcumin/SPIO was 30 fold higher. Increased intracellular drug content for DOX base delivered via DOX/SPIO was also confirmed, along with a fast intracellular DOX release that was attributed to its protonation in the acidic environment. DOX/SPIO enhanced caspase-3 activity by twofold compared with free DOX base. The concentration that induced 50% cytotoxic effect (CC50) was 0.05 +/- 0.03 μg ml-1 for DOX/SPIO, while it was 0.13 +/- 0.02 μg ml-1 for free DOX base. These results suggested SPIO nanoshells might be a promising intracellular carrier for hydrophobic anticancer drugs.

HPMA Copolymer-Drug Conjugates with Controlled Tumor-Specific Drug Release.

PubMed

Chytil, Petr; Koziolová, Eva; Etrych, Tomáš; Ulbrich, Karel

2018-01-01

Over the past few decades, numerous polymer drug carrier systems are designed and synthesized, and their properties are evaluated. Many of these systems are based on water-soluble polymer carriers of low-molecular-weight drugs and compounds, e.g., cytostatic agents, anti-inflammatory drugs, or multidrug resistance inhibitors, all covalently bound to a carrier by a biodegradable spacer that enables controlled release of the active molecule to achieve the desired pharmacological effect. Among others, the synthetic polymer carriers based on N-(2-hydroxypropyl) methacrylamide (HPMA) copolymers are some of the most promising carriers for this purpose. This review focuses on advances in the development of HPMA copolymer carriers and their conjugates with anticancer drugs, with triggered drug activation in tumor tissue and especially in tumor cells. Specifically, this review highlights the improvements in polymer drug carrier design with respect to the structure of a spacer to influence controlled drug release and activation, and its impact on the drug pharmacokinetics, enhanced tumor uptake, cellular trafficking, and in vivo antitumor activity. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2014-09-01

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

Pharmacology Goes Concept-Based: Course Design, Implementation, and Evaluation.

PubMed

Lanz, Amelia; Davis, Rebecca G

Although concept-based curricula are frequently discussed in the nursing education literature, little information exists to guide the development of a concept-based pharmacology course. Traditionally, nursing pharmacology courses are taught with an emphasis on drug class where a prototype drug serves as an exemplar. When transitioning pharmacology to a concept-based course, special considerations are in order. How can educators successfully integrate essential pharmacological content into a curriculum structured around nursing concepts? This article presents one approach to the design and implementation of a concept-based undergraduate pharmacology course. Planning methods, supportive teaching strategies, and course evaluation procedures are discussed.

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

West Nile virus drug discovery.

PubMed

Lim, Siew Pheng; Shi, Pei-Yong

2013-12-03

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.

Structure-Based Design of Novel HIV-1 Protease Inhibitors to Combat Drug Resistance

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

Ghosh,A.; Sridhar, P.; Leshchenko, S.

2006-01-01

Structure-based design and synthesis of novel HIV protease inhibitors are described. The inhibitors are designed specifically to interact with the backbone of HIV protease active site to combat drug resistance. Inhibitor 3 has exhibited exceedingly potent enzyme inhibitory and antiviral potency. Furthermore, this inhibitor maintains impressive potency against a wide spectrum of HIV including a variety of multi-PI-resistant clinical strains. The inhibitors incorporated a stereochemically defined 5-hexahydrocyclopenta[b]furanyl urethane as the P2-ligand into the (R)-(hydroxyethylamino)sulfonamide isostere. Optically active (3aS,5R,6aR)-5-hydroxy-hexahydrocyclopenta[b]furan was prepared by an enzymatic asymmetrization of meso-diacetate with acetyl cholinesterase, radical cyclization, and Lewis acid-catalyzed anomeric reduction as the key steps.more » A protein-ligand X-ray crystal structure of inhibitor 3-bound HIV-1 protease (1.35 Angstroms resolution) revealed extensive interactions in the HIV protease active site including strong hydrogen bonding interactions with the backbone. This design strategy may lead to novel inhibitors that can combat drug resistance.« less

Molecular dynamics studies of a hexameric purine nucleoside phosphorylase.

PubMed

Zanchi, Fernando Berton; Caceres, Rafael Andrade; Stabeli, Rodrigo Guerino; de Azevedo, Walter Filgueira

2010-03-01

Purine nucleoside phosphorylase (PNP) (EC.2.4.2.1) is an enzyme that catalyzes the cleavage of N-ribosidic bonds of the purine ribonucleosides and 2-deoxyribonucleosides in the presence of inorganic orthophosphate as a second substrate. This enzyme is involved in purine-salvage pathway and has been proposed as a promising target for design and development of antimalarial and antibacterial drugs. Recent elucidation of the three-dimensional structure of PNP by X-ray protein crystallography left open the possibility of structure-based virtual screening initiatives in combination with molecular dynamics simulations focused on identification of potential new antimalarial drugs. Most of the previously published molecular dynamics simulations of PNP were carried out on human PNP, a trimeric PNP. The present article describes for the first time molecular dynamics simulations of hexameric PNP from Plasmodium falciparum (PfPNP). Two systems were simulated in the present work, PfPNP in ligand free form, and in complex with immucillin and sulfate. Based on the dynamical behavior of both systems the main results related to structural stability and protein-drug interactions are discussed.

CANDO and the infinite drug discovery frontier

PubMed Central

Minie, Mark; Chopra, Gaurav; Sethi, Geetika; Horst, Jeremy; White, George; Roy, Ambrish; Hatti, Kaushik; Samudrala, Ram

2014-01-01

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound–proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12–25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 ‘high value’ predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering. PMID:24980786

Nanocrystal for ocular drug delivery: hope or hype.

PubMed

Sharma, Om Prakash; Patel, Viral; Mehta, Tejal

2016-08-01

The complexity of the structure and nature of the eye emanates a challenge for drug delivery to formulation scientists. Lower bioavailability concern of conventional ocular formulation provokes the interest of researchers in the development of novel drug delivery system. Nanotechnology-based formulations have been extensively investigated and found propitious in improving bioavailability of drugs by overcoming ocular barriers prevailing in the eye. The advent of nanocrystals helped in combating the problem of poorly soluble drugs specifically for oral and parenteral drug delivery and led to development of various marketed products. Nanocrystal-based formulations explored for ocular drug delivery have been found successful in achieving increase in retention time, bioavailability, and permeability of drugs across the corneal and conjunctival epithelium. In this review, we have highlighted the ocular physiology and barriers in drug delivery. A comparative analysis of various nanotechnology-based ocular formulations is done with their pros and cons. Consideration is also given to various methods of preparation of nanocrystals with their patented technology. This article highlights the success achieved in conquering various challenges of ocular delivery by the use of nanocrystals while emphasizing on its advantages and application for ocular formulation. The perspectives of nanocrystals as an emerging flipside to explore the frontiers of ocular drug delivery are discussed.

Polysaccharides based nanomaterials for targeted anti-cancer drug delivery.

PubMed

Dheer, Divya; Arora, Divya; Jaglan, Sundeep; Rawal, Ravindra K; Shankar, Ravi

2017-01-01

Polysaccharides, an important class of biological polymers, are effectively bioactive, nontoxic, hydrophilic, biodegradable and offer a wide diversity in structure and properties. These can be easily modified chemically and biochemically to enhance the bioadhesion with biological tissues, better stability and can improve bioavailability of drugs. Most of the chemotherapeutic drugs have a narrow therapeutic index, slow drug delivery systems and poor water solubility that usually proves toxic to human bodies. The inherent biocompatibility of these biopolymers have shown enhancement of solubility of some chemotherapeutic drugs which also leads to the preparation of nanomaterials for the delivery of antibiotics, anticancer, proteins, peptides and nucleic acids using several routes of administration. Recently, synthesis and research on polysaccharides based nanomaterials have gained enormous attention as one of the most applicable resources in nanomedicine area. This review article will provide a specific emphasis on polysaccharides as natural biomaterials for targeted anticancer drug delivery system.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Examination of oral absorption and lymphatic transport of halofantrine in a triple-cannulated canine model after administration in self-microemulsifying drug delivery systems (SMEDDS) containing structured triglycerides.

PubMed

Holm, René; Porter, Christopher J H; Edwards, Glenn A; Müllertz, Anette; Kristensen, Henning G; Charman, William N

2003-09-01

The potential for lipidic self-microemulsifying drug delivery systems (SMEDDS) containing triglycerides with a defined structure, where the different fatty acids on the glycerol backbone exhibit different metabolic fate, to improve the lymphatic transport and the portal absorption of a poorly water-soluble drug, halofantrine, were investigated in fasted lymph cannulated canines. Two different structured triglycerides were incorporated into the SMEDDS; 1,3-dioctanoyl-2-linoleyl-sn-glycerol (C8:0-C18:2-C8:0) (MLM) and 1,3-dilinoyl-2-octanoyl-sn-glycerol (C18:2-C8:0-C18:2) (LML). A previously optimised SMEDDS formulation for halofantrine, comprising of triglyceride, Cremophor EL, Maisine 35-1 and ethanol was selected for bioavailability assessment. The extent of lymphatic transport via the thoracic duct was 17.9% of the dose for the animals dosed with the MLM SMEDDS and 27.4% for LML. Also the plasma availability was affected by the triglyceride incorporated into the multi-component delivery system and availabilities of 56.9% (MLM) and 37.2% (LML) were found. These data indicate that the pharmaceutical scientist can use the structure of the lipid to affect the relative contribution of the two absorption pathways. The MLM formulation produced a total bioavailability of 74.9%, which is higher than the total absorption previously observed after post-prandial administration. This could indicate the utility of disperse lipid-base formulations based on structured triglycerides for the oral delivery of halofantrine, and potentially other lipophilic drugs.

Dual responsive aerogel made from thermo/pH sensitive graft copolymer alginate-g-P(NIPAM-co-NHMAM) for drug controlled release.

PubMed

Shao, Lin; Cao, Yang; Li, Zhanying; Hu, Wenbin; Li, Shize; Lu, Lingbin

2018-07-15

Alginate was grafted with NIPAM and NHMAM successfully, and a new responsive copolymer, alginate-g-P(NIPAM-co-NHMAM), was obtained. A novel dual responsive polysaccharide-based aerogel with thermo/pH sensitive properties was designed from the copolymer as drug controlled release system. The chemical structure of the copolymer was characterized by FT-IR and 1 H NMR. Lower critical solution temperature (LCST) of the copolymer covered a wide temperature range from 27.6 °C to 42.2 °C, which could be adjusted with changing the ratio between NIPAM and NHMAM. The dual responsive aerogel had a three-dimensional network structure. As a drug controlled release system, the aerogel was high responsive to both temperature and pH with drug loading efficiency up to 13.24%. Above LCST, the aerogel had a faster drug release, and drug was completely released in neutral environment, while the drug release was obstructed in acid environment. Furthermore, the drug release mechanism of the aerogel was illuminated. These results indicated that the dual responsive aerogel was a promising candidate for drug carriers. Copyright © 2018 Elsevier B.V. All rights reserved.

Advances in visual representation of molecular potentials.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen

2010-06-01

The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.

Reactivity-based drug discovery using vitamin B(6)-derived pharmacophores.

PubMed

Wondrak, Georg T

2008-05-01

Endogenous reactive intermediates including photoexcited states of tissue chromophores, reactive oxygen species (ROS), reactive carbonyl species (RCS), transition metal ions, and Schiff bases have been implicated in the initiation and progression of diverse human pathologies including tumorigenesis, atherosclerosis, diabetes, and neurodegenerative disease. In contrast to structure-based approaches that target macromolecules by selective ligands, reactivity-based drug discovery uses chemical reagents as therapeutics that target reactive chemical species involved in human pathology. Reactivity-based design of prototype agents that effectively antagonize, modulate, and potentially even reverse the chemistry underlying tissue damage from oxidative and carbonyl stress therefore holds great promise in delivering significant therapeutic benefit. Apart from its established role as an essential cofactor for numerous enzymes, a large body of evidence suggests that B(6)-vitamers contain reactive pharmacophores that mediate therapeutically useful non-vitamin drug actions as potent antioxidants, metal chelators, carbonyl scavengers, Schiff base forming agents, and photosensitizers. Based on the fascinating chemical versatility of B(6)-derived pharmacophores, B(6)-vitamers are therefore promising lead compounds for reactivity-based drug design.

The Influence of Solvent on the Structural Properties of trans-(NHC)PtI2Py Complex: A Platinum-Based Anticancer Drug

NASA Astrophysics Data System (ADS)

Sadigh Vishkaee, Teherh; Fazaeli, Reza

2018-06-01

Quantum chemical calculations using MPW1PW91 method were applied to analyze the solvent effect on the structural, spectral, and thermochemical parameters for a platinum-based anticancer drug trans-(NHC)PtI2Py complex. The solvent effects were examined by the self-consistent reaction field theory (SCRF) based on Polarizable Continuum Model (PCM). The linear correlations between the solvation energies, HOMO-LUMO gaps, IR-active stretching vibration of Pt-N bonds and N-H of NHC ligand with dielectric constants of solvents were studied. The wave numbers of these IR-active stretching vibrations in different solvents were correlated with the Kirkwood-Bauer-Magat equation (KBM). The thermodynamic activation parameter such free energy of solvation, enthalpy of solvation were also calculated.

Homology modeling, binding site identification and docking study of human angiotensin II type I (Ang II-AT1) receptor.

PubMed

Vyas, Vivek K; Ghate, Manjunath; Patel, Kinjal; Qureshi, Gulamnizami; Shah, Surmil

2015-08-01

Ang II-AT1 receptors play an important role in mediating virtually all of the physiological actions of Ang II. Several drugs (SARTANs) are available, which can block the AT1 receptor effectively and lower the blood pressure in the patients with hypertension. Currently, there is no experimental Ang II-AT1 structure available; therefore, in this study we modeled Ang II-AT1 receptor structure using homology modeling followed by identification and characterization of binding sites and thereby assessing druggability of the receptor. Homology models were constructed using MODELLER and I-TASSER server, refined and validated using PROCHECK in which 96.9% of 318 residues were present in the favoured regions of the Ramachandran plots. Various Ang II-AT1 receptor antagonist drugs are available in the market as antihypertensive drug, so we have performed docking study with the binding site prediction algorithms to predict different binding pockets on the modeled proteins. The identification of 3D structures and binding sites for various known drugs will guide us for the structure-based drug design of novel compounds as Ang II-AT1 receptor antagonists for the treatment of hypertension. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

"Pruning of biomolecules and natural products (PBNP)": an innovative paradigm in drug discovery.

PubMed

Bathula, Surendar Reddy; Akondi, Srirama Murthy; Mainkar, Prathama S; Chandrasekhar, Srivari

2015-06-21

The source or inspiration of many marketed drugs can be traced back to natural product research. However, the chemical structure of natural products covers a wide spectrum from very simple to complex. With more complex structures it is often desirable to simplify the molecule whilst retaining the desired biological activity. This approach seeks to identify the structural unit or pharmacophore responsible for the desired activity. Such pharmacophores have been the start point for a wide range of lead generation and optimisation programmes using techniques such as Biology Oriented Synthesis, Diversity Oriented Synthesis, Diverted Total Synthesis, and Fragment Based Drug Discovery. This review discusses the literature precedence of simplification strategies in four areas of natural product research: proteins, polysaccharides, nucleic acids, and compounds isolated from natural product extracts, and their impact on identifying therapeutic products.

A Receptor-Grounded Approach to Teaching Nonsteroidal Antiinflammatory Drug Chemistry and Structure-Activity Relationships

PubMed Central

2009-01-01

Objective To describe a receptor-based approach to promote learning about nonsteroidal anti-inflammatory drug (NSAID) chemistry, structure-activity relationships, and therapeutic decision-making. Design Three lessons on cyclooxygenase (COX) and NSAID chemistry, and NSAID therapeutic utility, were developed using text-based resources and primary medicinal chemistry and pharmacy practice literature. Learning tools were developed to assist students in content mastery. Assessment Student learning was evaluated via performance on quizzes and examinations that measured understanding of COX and NSAID chemistry, and the application of that knowledge to therapeutic problem solving. Conclusion Student performance on NSAID-focused quizzes and examinations documented the success of this approach. PMID:20221336

Alkyl polyglucoside vs. ethoxylated surfactant-based microemulsions as vehicles for two poorly water-soluble drugs: physicochemical characterization and in vivo skin performance.

PubMed

Pajić, Nataša Z Bubić; Todosijević, Marija N; Vuleta, Gordana M; Cekić, Nebojša D; Dobričić, Vladimir D; Vučen, Sonja R; Čalija, Bojan R; Lukić, Milica Ž; Ilić, Tanja M; Savić, Snežana D

2017-12-20

Two types of biocompatible surfactants were evaluated for their capability to formulate skin-friendly/non-irritant microemulsions as vehicles for two poorly water-soluble model drugs differing in properties and concentrations: alkyl polyglucosides (decyl glucoside and caprylyl/capryl glucoside) and ethoxylated surfactants (glycereth-7-caprylate/ caprate and polysorbate 80). Phase behavior, structural inversion and microemulsion solubilization potential for sertaconazole nitrate and adapalene were found to be highly dependent on the surfactants structure and HLB value. Performed characterization (polarized light microscopy, pH, electrical conductivity, rheological, FTIR and DSC measurements) indicated a formulation containing glycereth- 7-caprylate/caprate as suitable for incorporation of both drugs, whereas alkyl polyglucoside-based systems did not exhibit satisfying solubilization capacity for sertaconazole nitrate. Further, monitored parameters were strongly affected by sertaconazole nitrate incorporation, while they remained almost unchanged in adapalene-loaded vehicles. In addition, results of the in vivo skin performance study supported acceptable tolerability for all investigated formulations, suggesting selected microemulsions as promising carriers worth exploring further for effective skin delivery of model drugs.

Microfluidics for producing poly (lactic-co-glycolic acid)-based pharmaceutical nanoparticles.

PubMed

Li, Xuanyu; Jiang, Xingyu

2017-12-24

Microfluidic chips allow the rapid production of a library of nanoparticles (NPs) with distinct properties by changing the precursors and the flow rates, significantly decreasing the time for screening optimal formulation as carriers for drug delivery compared to conventional methods. The batch-to-batch reproducibility which is essential for clinical translation is achieved by precisely controlling the precursors and the flow rate, regardless of operators. Poly (lactic-co-glycolic acid) (PLGA) is the most widely used Food and Drug Administration (FDA)-approved biodegradable polymers. Researchers often combine PLGA with lipids or amphiphilic molecules to assemble into a core/shell structure to exploit the potential of PLGA-based NPs as powerful carriers for cancer-related drug delivery. In this review, we discuss the advantages associated with microfluidic chips for producing PLGA-based functional nanocomplexes for drug delivery. These laboratory-based methods can readily scale up to provide sufficient amount of PLGA-based NPs in microfluidic chips for clinical studies and industrial-scale production. Copyright © 2017. Published by Elsevier B.V.

Bioengineered protein-based nanocage for drug delivery.

PubMed

Lee, Eun Jung; Lee, Na Kyeong; Kim, In-San

2016-11-15

Nature, in its wonders, presents and assembles the most intricate and delicate protein structures and this remarkable phenomenon occurs in all kingdom and phyla of life. Of these proteins, cage-like multimeric proteins provide spatial control to biological processes and also compartmentalizes compounds that may be toxic or unstable and avoids their contact with the environment. Protein-based nanocages are of particular interest because of their potential applicability as drug delivery carriers and their perfect and complex symmetry and ideal physical properties, which have stimulated researchers to engineer, modify or mimic these qualities. This article reviews various existing types of protein-based nanocages that are used for therapeutic purposes, and outlines their drug-loading mechanisms and bioengineering strategies via genetic and chemical functionalization. Through a critical evaluation of recent advances in protein nanocage-based drug delivery in vitro and in vivo, an outlook for de novo and in silico nanocage design, and also protein-based nanocage preclinical and future clinical applications will be presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Inhibitor-based validation of a homology model of the active-site of tripeptidyl peptidase II.

PubMed

De Winter, Hans; Breslin, Henry; Miskowski, Tamara; Kavash, Robert; Somers, Marijke

2005-04-01

A homology model of the active site region of tripeptidyl peptidase II (TPP II) was constructed based on the crystal structures of four subtilisin-like templates. The resulting model was subsequently validated by judging expectations of the model versus observed activities for a broad set of prepared TPP II inhibitors. The structure-activity relationships observed for the prepared TPP II inhibitors correlated nicely with the structural details of the TPP II active site model, supporting the validity of this model and its usefulness for structure-based drug design and pharmacophore searching experiments.

Doxorubicin-loaded micelles based on multiarm star-shaped PLGA-PEG block copolymers: influence of arm numbers on drug delivery.

PubMed

Ma, Guilei; Zhang, Chao; Zhang, Linhua; Sun, Hongfan; Song, Cunxian; Wang, Chun; Kong, Deling

2016-01-01

Star-shaped block copolymers based on poly(D,L-lactide-co-glycolide) (PLGA) and poly(ethylene glycol) (PEG) (st-PLGA-PEG) were synthesized with structural variation on arm numbers in order to investigate the relationship between the arm numbers of st-PLGA-PEG copolymers and their micelle properties. st-PLGA-PEG copolymers with arm numbers 3, 4 and 6 were synthesized by using different cores such as trimethylolpropane, pentaerythritol and dipentaerythritol, and were characterized by nuclear magnetic resonance and gel permeation chromatography. The critical micelle concentration decreased with increasing arm numbers in st-PLGA-PEG copolymers. The doxorubicin-loaded st-PLGA-PEG micelles were prepared by a modified nanoprecipitation method. Micellar properties such as particle size, drug loading content and in vitro drug release behavior were investigated as a function of the number of arms and compared with each other. The doxorubicin-loaded 4-arm PLGA-PEG micelles were found to have the highest cellular uptake efficiency and cytotoxicity compared with 3-arm PLGA-PEG micelles and 6-arm PLGA-PEG micelles. The results suggest that structural tailoring of arm numbers from st-PLGA-PEG copolymers could provide a new strategy for designing drug carriers of high efficiency. Structural tailoring of arm numbers from star shaped-PLGA-PEG copolymers (3-arm/4-arm/6-arm-PLGA-PEG) could provide a new strategy for designing drug carriers of high efficiency.

Silk-based delivery systems of bioactive molecules

PubMed Central

Numata, Keiji; Kaplan, David L

2010-01-01

Silks are biodegradable, biocompatible, self-assemblying proteins that can also be tailored via genetic engineering to contain specific chemical features, offering utility for drug and gene delivery. Silkworm silk has been used in biomedical sutures for decades and has recently achieved Food and Drug Administration approval for expanded biomaterials device utility. With the diversity and control of size, structure and chemistry, modified or recombinant silk proteins can be designed and utilized in various biomedical application, such as for the delivery of bioactive molecules. This review focuses on the biosynthesis and applications of silk-based multi-block copolymer systems and related silk protein drug delivery systems. The utility of these systems for the delivery of small molecule drugs, proteins and genes are reviewed. PMID:20298729

Informatic innovations in glycobiology: relevance to drug discovery.

PubMed

Mamitsuka, Hiroshi

2008-02-01

The recent development and applications of tree-based informatics on glycans have accelerated the biological analysis on glycans, particularly from structural viewpoints. We review three major aspects of recent informatics innovations on glycan structures: maturity of well-organized databases on glycan structures linking with other biological information, implementation of glycan structure matching algorithms and extensive development of methods for mining frequent patterns from glycan structures.

Combining Internet monitoring processes, packaging and isotopic analyses to determine the market structure: example of Gamma Butyrolactone.

PubMed

Pazos, Diego; Giannasi, Pauline; Rossy, Quentin; Esseiva, Pierre

2013-07-10

The Internet is becoming more and more popular among drug users. The use of websites and forums to obtain illicit drugs and relevant information about the means of consumption is a growing phenomenon mainly for new synthetic drugs. Gamma Butyrolactone (GBL), a chemical precursor of Gamma Hydroxy Butyric acid (GHB), is used as a "club drug" and also in drug facilitated sexual assaults. Its market takes place mainly on the Internet through online websites but the structure of the market remains unknown. This research aims to combine digital, physical and chemical information to help understand the distribution routes and the structure of the GBL market. Based on an Internet monitoring process, thirty-nine websites selling GBL, mainly in the Netherlands, were detected between January 2010 and December 2011. Seventeen websites were categorized into six groups based on digital traces (e.g. IP addresses and contact information). In parallel, twenty-five bulk GBL specimens were purchased from sixteen websites for packaging comparisons and carbon isotopic measurements. Packaging information showed a high correlation with digital data confirming the links previously established whereas chemical information revealed undetected links and provided complementary information. Indeed, while digital and packaging data give relevant information about the retailers, the supply routes and the distribution close to the consumer, the carbon isotopic data provides upstream information about the production level and in particular the synthesis pathways and the chemical precursors. A three-level structured market has been thereby identified with a production level mainly located in China and in Germany, an online distribution level mainly hosted in the Netherlands and the customers who order on the Internet. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Nanoporous polymeric nanofibers based on selectively etched PS-b-PDMS block copolymers.

PubMed

Demirel, Gokcen B; Buyukserin, Fatih; Morris, Michael A; Demirel, Gokhan

2012-01-01

One-dimensional nanoporous polymeric nanofibers have been fabricated within an anodic aluminum oxide (AAO) membrane by a facile approach based on selective etching of poly(dimethylsiloxane) (PDMS) domains in polystyrene-block-poly(dimethylsiloxane) (PS-b-PDMS) block copolymers that had been formed within the AAO template. It was observed that prior to etching, the well-ordered PS-b-PDMS nanofibers are solid and do not have any porosity. The postetched PS nanofibers, on the other hand, had a highly porous structure having about 20-50 nm pore size. The nanoporous polymeric fibers were also employed as a drug carrier for the native, continuous, and pulsatile drug release using Rhodamine B (RB) as a model drug. These studies showed that enhanced drug release and tunable drug dosage can be achieved by using ultrasound irradiation. © 2011 American Chemical Society

Droplet-born air blowing: novel dissolving microneedle fabrication.

PubMed

Kim, Jung Dong; Kim, Miroo; Yang, Huisuk; Lee, Kwang; Jung, Hyungil

2013-09-28

The microneedle-mediated drug delivery system has been developed to provide painless self-administration of drugs in a patient-friendly manner. Current dissolving microneedle fabrication methods, however, require harsh conditions for biological drugs and also have problems standardizing the drug dose. Here, we suggested the droplet-born air blowing (DAB) method, which provides gentle (4-25 °C) and fast (≤10min) microneedle fabrication conditions without drug loss. The amount of drug in the microneedle can be controlled by the pressure and time of droplet dispenser and the air blowing shapes this droplet to the microneedle, providing a force sufficient to penetrate skin. Also, the introduction of a base structure of two layered DAB-microneedle could provide complete drug delivery without wasting of drug. The DAB-based insulin loaded microneedle shows similar bioavailability (96.6±2.4%) and down regulation of glucose level compared with subcutaneous injection. We anticipate that DAB described herein will be suitable to design dissolving microneedles for use in biological drug delivery to patients. Copyright © 2013 Elsevier B.V. All rights reserved.

Overlap in drug-disease associations between clinical practice guidelines and drug structured product label indications.

PubMed

Leung, Tiffany I; Dumontier, Michel

2016-06-08

Clinical practice guidelines (CPGs) recommend pharmacologic treatments for clinical conditions, and drug structured product labels (SPLs) summarize approved treatment indications. Both resources are intended to promote evidence-based medical practices and guide clinicians' prescribing decisions. However, it is unclear how well CPG recommendations about pharmacologic therapies match SPL indications for recommended drugs. In this study, we perform text mining of CPG summaries to examine drug-disease associations in CPG recommendations and in SPL treatment indications for 15 common chronic conditions. We constructed an initial text corpus of guideline summaries from the National Guideline Clearinghouse (NGC) from a set of manually selected ICD-9 codes for each of the 15 conditions. We obtained 377 relevant guideline summaries and their Major Recommendations section, which excludes guidelines for pediatric patients, pregnant or breastfeeding women, or for medical diagnoses not meeting inclusion criteria. A vocabulary of drug terms was derived from five medical taxonomies. We used named entity recognition, in combination with dictionary-based and ontology-based methods, to identify drug term occurrences in the text corpus and construct drug-disease associations. The ATC (Anatomical Therapeutic Chemical Classification) was utilized to perform drug name and drug class matching to construct the drug-disease associations from CPGs. We then obtained drug-disease associations from SPLs using conditions mentioned in their Indications section in SIDER. The primary outcomes were the frequency of drug-disease associations in CPGs and SPLs, and the frequency of overlap between the two sets of drug-disease associations, with and without using taxonomic information from ATC. Without taxonomic information, we identified 1444 drug-disease associations across CPGs and SPLs for 15 common chronic conditions. Of these, 195 drug-disease associations overlapped between CPGs and SPLs, 917 associations occurred in CPGs only and 332 associations occurred in SPLs only. With taxonomic information, 859 unique drug-disease associations were identified, of which 152 of these drug-disease associations overlapped between CPGs and SPLs, 541 associations occurred in CPGs only, and 166 associations occurred in SPLs only. Our results suggest that CPG-recommended pharmacologic therapies and SPL indications do not overlap frequently when identifying drug-disease associations using named entity recognition, although incorporating taxonomic relationships between drug names and drug classes into the approach improves the overlap. This has important implications in practice because conflicting or inconsistent evidence may complicate clinical decision making and implementation or measurement of best practices.

Structure–activity relationships study of mTOR kinase inhibition using QSAR and structure-based drug design approaches

PubMed Central

Lakhlili, Wiame; Yasri, Abdelaziz; Ibrahimi, Azeddine

2016-01-01

The discovery of clinically relevant inhibitors of mammalian target of rapamycin (mTOR) for anticancer therapy has proved to be a challenging task. The quantitative structure–activity relationship (QSAR) approach is a very useful and widespread technique for ligand-based drug design, which can be used to identify novel and potent mTOR inhibitors. In this study, we performed two-dimensional QSAR tests, and molecular docking validation tests of a series of mTOR ATP-competitive inhibitors to elucidate their structural properties associated with their activity. The QSAR tests were performed using partial least square method with a correlation coefficient of r2=0.799 and a cross-validation of q2=0.714. The chemical library screening was done by associating ligand-based to structure-based approach using the three-dimensional structure of mTOR developed by homology modeling. We were able to select 22 compounds from two databases as inhibitors of the mTOR kinase active site. We believe that the method and applications highlighted in this study will help future efforts toward the design of selective ATP-competitive inhibitors. PMID:27980424

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

PubMed

Moitessier, Nicolas; Pottel, Joshua; Therrien, Eric; Englebienne, Pablo; Liu, Zhaomin; Tomberg, Anna; Corbeil, Christopher R

2016-09-20

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Chemistry and Biology of the Caged Garcinia Xanthones

PubMed Central

Chantarasriwong, Oraphin; Batova, Ayse; Chavasiri, Warinthorn

2011-01-01

Natural products have been a great source of many small molecule drugs for various diseases. In spite of recent advances in biochemical engineering and fermentation technologies that allow us to explore microorganisms and the marine environment as alternative sources of drugs, more than 70% of the current small molecule therapeutics derive their structures from plants used in traditional medicine. Natural-product-based drug discovery relies heavily on advances made in the sciences of biology and chemistry. Whereas biology aims to investigate the mode of action of a natural product, chemistry aims to overcome challenges related to its supply, bioactivity, and target selectivity. This review summarizes the explorations of the caged Garcinia xanthones, a family of plant metabolites that possess a unique chemical structure, potent bioactivities, and a promising pharmacology for drug design and development. PMID:20648491

Arylazolyl(azinyl)thioacetanilides: Part 19: Discovery of Novel Substituted Imidazo[4,5-b]pyridin-2-ylthioacetanilides as Potent HIV NNRTIs Via a Structure-based Bioisosterism Approach.

PubMed

Li, Xiao; Huang, Boshi; Zhou, Zhongxia; Gao, Ping; Pannecouque, Christophe; Daelemans, Dirk; De Clercq, Erik; Zhan, Peng; Liu, Xinyong

2016-08-01

With the continuation of our unremitting efforts toward the discovery of potent HIV-1 NNRTIs, a series of novel imidazo[4,5-b]pyridin-2-ylthioacetanilides were designed, synthesized, and evaluated for their antiviral activities through combining bioisosteric replacement and structure-based drug design. Almost all of the title compounds displayed moderate to good activities against wild-type (wt) HIV-1 strain with EC50 values ranging from 0.059 to 1.41 μm in a cell-based antiviral assay. Thereinto, compounds 12 and 13 were the most active two analogues possessing an EC50 value of 0.059 and 0.073 μm against wt HIV-1, respectively, which was much more effective than the control drug nevirapine (EC50 = 0.26 μm) and comparable to delavirdine (EC50 = 0.038 μm). In addition, one selected compound showed a remarkable reverse transcriptase inhibitory activity compared to nevirapine and etravirine. In the end of this manuscript, preliminary structure-activity relationships (SARs) and molecular modeling studies were detailedly discussed, which may provide valuable insights for further optimization. © 2016 The Authors. Chemical Biology & Drug Design Published by John Wiley & Sons A/S.

Tailoring drug release rates in hydrogel-based therapeutic delivery applications using graphene oxide

PubMed Central

Zhi, Z. L.; Craster, R. V.

2018-01-01

Graphene oxide (GO) is increasingly used for controlling mass diffusion in hydrogel-based drug delivery applications. On the macro-scale, the density of GO in the hydrogel is a critical parameter for modulating drug release. Here, we investigate the diffusion of a peptide drug through a network of GO membranes and GO-embedded hydrogels, modelled as porous matrices resembling both laminated and ‘house of cards’ structures. Our experiments use a therapeutic peptide and show a tunable nonlinear dependence of the peptide concentration upon time. We establish models using numerical simulations with a diffusion equation accounting for the photo-thermal degradation of fluorophores and an effective percolation model to simulate the experimental data. The modelling yields an interpretation of the control of drug diffusion through GO membranes, which is extended to the diffusion of the peptide in GO-embedded agarose hydrogels. Varying the density of micron-sized GO flakes allows for fine control of the drug diffusion. We further show that both GO density and size influence the drug release rate. The ability to tune the density of hydrogel-like GO membranes to control drug release rates has exciting implications to offer guidelines for tailoring drug release rates in hydrogel-based therapeutic delivery applications. PMID:29445040

Geographic approaches to quantifying the risk environment: a focus on syringe exchange program site access and drug-related law enforcement activities

PubMed Central

Cooper, Hannah LF; Bossak, Brian; Tempalski, Barbara; Des Jarlais, Don C.; Friedman, Samuel R.

2009-01-01

The concept of the “risk environment” – defined as the “space … [where] factors exogenous to the individual interact to increase the chances of HIV transmission” – draws together the disciplines of public health and geography. Researchers have increasingly turned to geographic methods to quantify dimensions of the risk environment that are both structural and spatial (e.g., local poverty rates). The scientific power of the intersection between public health and geography, however, has yet to be fully mined. In particular, research on the risk environment has rarely applied geographic methods to create neighbourhood-based measures of syringe exchange programs (SEPs) or of drug-related law enforcement activities, despite the fact that these interventions are widely conceptualized as structural and spatial in nature and are two of the most well-established dimensions of the risk environment. To strengthen research on the risk environment, this paper presents a way of using geographic methods to create neighbourhood-based measures of (1) access to SEP sites and (2) exposure to drug-related arrests, and then applies these methods to one setting (New York City). NYC-based results identified substantial cross-neighbourhood variation in SEP site access and in exposure to drug-related arrest rates (even within the subset of neighbourhoods nominally experiencing the same drug-related police strategy). These geographic measures – grounded as they are in conceptualizations of SEPs and drug-related law enforcement strategies – can help develop new arenas of inquiry regarding the impact of these two dimensions of the risk environment on injectors’ health, including exploring whether and how neighbourhood-level access to SEP sites and exposure to drug-related arrests shape a range of outcomes among local injectors. PMID:18963907

Fragment-Based Drug Discovery in Academia: Experiences From a Tuberculosis Programme

NASA Astrophysics Data System (ADS)

Heikkila, Timo J.; Surade, Sachin; Silvestre, Hernani L.; Dias, Marcio V. B.; Ciulli, Alessio; Bromfield, Karen; Scott, Duncan; Howard, Nigel; Wen, Shijun; Wei, Alvin Hung; Osborne, David; Abell, Chris; Blundell, Tom L.

The problems associated with neglected diseases are often compounded by increasing incidence of antibiotic resistance. Patient negligence and abuse of antibiotics has lead to explosive growth in cases of tuberculosis, with some M. tuberculosis strains becoming virtually untreatable. Structure-based drug development is viewed as cost-effective and time-consuming method for discovery and development of hits to lead compounds. In this review we will discuss the suitability of fragment-based methods for developing new chemotherapeutics against neglected diseases, providing examples from our tuberculosis programme.

Structure-based drug discovery for combating influenza virus by targeting the PA-PB1 interaction.

PubMed

Watanabe, Ken; Ishikawa, Takeshi; Otaki, Hiroki; Mizuta, Satoshi; Hamada, Tsuyoshi; Nakagaki, Takehiro; Ishibashi, Daisuke; Urata, Shuzo; Yasuda, Jiro; Tanaka, Yoshimasa; Nishida, Noriyuki

2017-08-25

Influenza virus infections are serious public health concerns throughout the world. The development of compounds with novel mechanisms of action is urgently required due to the emergence of viruses with resistance to the currently-approved anti-influenza viral drugs. We performed in silico screening using a structure-based drug discovery algorithm called Nagasaki University Docking Engine (NUDE), which is optimised for a GPU-based supercomputer (DEstination for Gpu Intensive MAchine; DEGIMA), by targeting influenza viral PA protein. The compounds selected by NUDE were tested for anti-influenza virus activity using a cell-based assay. The most potent compound, designated as PA-49, is a medium-sized quinolinone derivative bearing a tetrazole moiety, and it inhibited the replication of influenza virus A/WSN/33 at a half maximal inhibitory concentration of 0.47 μM. PA-49 has the ability to bind PA and its anti-influenza activity was promising against various influenza strains, including a clinical isolate of A(H1N1)pdm09 and type B viruses. The docking simulation suggested that PA-49 interrupts the PA-PB1 interface where important amino acids are mostly conserved in the virus strains tested, suggesting the strain independent utility. Because our NUDE/DEGIMA system is rapid and efficient, it may help effective drug discovery against the influenza virus and other emerging viruses.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Chitosan-based nanocarriers for antimalarials

NASA Astrophysics Data System (ADS)

Dreve, Simina; Kacso, Iren; Popa, Adriana; Raita, Oana; Bende, A.; Borodi, Gh.; Bratu, I.

2012-02-01

The objective of this research was to synthesize and characterize chitosan-based liquid and solid materials with unique absorptive and mechanical properties as carriers for quinine - one of the most used antimalarial drug. The use of chitosan (CTS) as base in polyelectrolyte complex systems, to prepare solid release systems as sponges is presented. The preparation by double emulsification of CTS hydrogels carrying quinine as anti-malarial drug is reported. The concentration of quinine in the CTS hydrogel was 0.08 mmol. Chitosan - drug loaded hydrogel was used to generate solid sponges by freeze-drying at -610°C and 0.09 atm. Structural investigations of the solid formulations were done by Fourier-transformed infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-VIS), spectrofluorimetry, differential scanning calorimetry (DSC) and X-ray diffractometry. The results indicated that the drug molecule is forming temporary chelates in CTS hydrogels and sponges. Electron paramagnetic resonance (EPR) demonstrates the presence of free radicals in a wide range and the antioxidant activity for chitosan - drug supramolecular cross-linked assemblies.

Application of ethyl cellulose, microcrystalline cellulose and octadecanol for wax based floating solid dispersion pellets.

PubMed

Yan, Hong-Xiang; Zhang, Shuang-Shuang; He, Jian-Hua; Liu, Jian-Ping

2016-09-05

The present study aimed to develop and optimize the wax based floating sustained-release dispersion pellets for a weakly acidic hydrophilic drug protocatechuic acid to achieve prolonged gastric residence time and improved bioavailability. This low-density drug delivery system consisted of octadecanol/microcrystalline cellulose mixture matrix pellet cores prepared by extrusion-spheronization technique, coated with drug/ethyl cellulose 100cp solid dispersion using single-step fluid-bed coating method. The formulation-optimized pellets could maintain excellent floating state without lag time and sustain the drug release efficiently for 12h based on non-Fickian transport mechanism. Observed by SEM, the optimized pellet was the dispersion-layered spherical structure containing a compact inner core. DSC, XRD and FTIR analysis revealed drug was uniformly dispersed in the amorphous molecule form and had no significant physicochemical interactions with the polymer dispersion carrier. The stability study of the resultant pellets further proved the rationality and integrity of the developed formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Human cytosolic glutathione-S-transferases: quantitative analysis of expression, comparative analysis of structures and inhibition strategies of isozymes involved in drug resistance.

PubMed

Mohana, Krishnamoorthy; Achary, Anant

2017-08-01

Glutathione-S-transferase (GST) inhibition is a strategy to overcome drug resistance. Several isoforms of human GSTs are present and they are expressed in almost all the organs. Specific expression levels of GSTs in various organs are collected from the human transcriptome data and analysis of the organ-specific expression of GST isoforms is carried out. The variations in the level of expressions of GST isoforms are statistically significant. The GST expression differs in diseased conditions as reported by many investigators and some of the isoforms of GSTs are disease markers or drug targets. Structure analysis of various isoforms is carried out and literature mining has been performed to identify the differences in the active sites of the GSTs. The xenobiotic binding H site is classified into H1, H2, and H3 and the differences in the amino acid composition, the hydrophobicity and other structural features of H site of GSTs are discussed. The existing inhibition strategies are compared. The advent of rational drug design, mechanism-based inhibition strategies, availability of high-throughput screening, target specific, and selective inhibition of GST isoforms involved in drug resistance could be achieved for the reversal of drug resistance and aid in the treatment of diseases.

Metabolism of 4-Aminopiperidine Drugs by Cytochrome P450s: Molecular and Quantum Mechanical Insights into Drug Design

PubMed Central

2011-01-01

4-Aminopiperidines are a variety of therapeutic agents that are extensively metabolized by cytochrome P450s with CYP3A4 as a major isoform catalyzing their N-dealkylation reaction. However, its catalytic mechanism has not been fully elucidated in a molecular interaction level. Here, we applied theoretical approaches including the molecular mechanics-based docking to study the binding patterns and quantum mechanics-based reactivity calculations. They were supported by the experimental human liver microsomal clearance and P450 isoform phenotyping data. Our results herein suggested that the molecular interactions between substrates and CYP3A4 active site residues are essential for the N-dealkylation of 4-aminopiperidines. We also found that the serine 119 residue of CYP3A4 may serve as a key hydrogen-bonding partner to interact with the 4-amino groups of the studied drugs. The reactivity of the side chain α-carbon hydrogens drives the direction of catalysis as well. As a result, structure-based drug design approaches look promising to guide drug discovery programs into the optimized drug metabolism space. PMID:21841964

Alignment-independent comparison of binding sites based on DrugScore potential fields encoded by 3D Zernike descriptors.

PubMed

Nisius, Britta; Gohlke, Holger

2012-09-24

Analyzing protein binding sites provides detailed insights into the biological processes proteins are involved in, e.g., into drug-target interactions, and so is of crucial importance in drug discovery. Herein, we present novel alignment-independent binding site descriptors based on DrugScore potential fields. The potential fields are transformed to a set of information-rich descriptors using a series expansion in 3D Zernike polynomials. The resulting Zernike descriptors show a promising performance in detecting similarities among proteins with low pairwise sequence identities that bind identical ligands, as well as within subfamilies of one target class. Furthermore, the Zernike descriptors are robust against structural variations among protein binding sites. Finally, the Zernike descriptors show a high data compression power, and computing similarities between binding sites based on these descriptors is highly efficient. Consequently, the Zernike descriptors are a useful tool for computational binding site analysis, e.g., to predict the function of novel proteins, off-targets for drug candidates, or novel targets for known drugs.

New strategy for protein interactions and application to structure-based drug design

NASA Astrophysics Data System (ADS)

Zou, Xiaoqin

One of the greatest challenges in computational biophysics is to predict interactions between biological molecules, which play critical roles in biological processes and rational design of therapeutic drugs. Biomolecular interactions involve delicate interplay between multiple interactions, including electrostatic interactions, van der Waals interactions, solvent effect, and conformational entropic effect. Accurate determination of these complex and subtle interactions is challenging. Moreover, a biological molecule such as a protein usually consists of thousands of atoms, and thus occupies a huge conformational space. The large degrees of freedom pose further challenges for accurate prediction of biomolecular interactions. Here, I will present our development of physics-based theory and computational modeling on protein interactions with other molecules. The major strategy is to extract microscopic energetics from the information embedded in the experimentally-determined structures of protein complexes. I will also present applications of the methods to structure-based therapeutic design. Supported by NSF CAREER Award DBI-0953839, NIH R01GM109980, and the American Heart Association (Midwest Affiliate) [13GRNT16990076].

Discovery of the Highly Potent PI3K/mTOR Dual Inhibitor PF-04979064 through Structure-Based Drug Design

PubMed Central

2012-01-01

PI3K, AKT, and mTOR are key kinases from PI3K signaling pathway being extensively pursued to treat a variety of cancers in oncology. To search for a structurally differentiated back-up candidate to PF-04691502, which is currently in phase I/II clinical trials for treating solid tumors, a lead optimization effort was carried out with a tricyclic imidazo[1,5]naphthyridine series. Integration of structure-based drug design and physical properties-based optimization yielded a potent and selective PI3K/mTOR dual kinase inhibitor PF-04979064. This manuscript discusses the lead optimization for the tricyclic series, which both improved the in vitro potency and addressed a number of ADMET issues including high metabolic clearance mediated by both P450 and aldehyde oxidase (AO), poor permeability, and poor solubility. An empirical scaling tool was developed to predict human clearance from in vitro human liver S9 assay data for tricyclic derivatives that were AO substrates. PMID:24900568

Structure-based design of pteridine reductase inhibitors targeting African sleeping sickness and the leishmaniases.

PubMed

Tulloch, Lindsay B; Martini, Viviane P; Iulek, Jorge; Huggan, Judith K; Lee, Jeong Hwan; Gibson, Colin L; Smith, Terry K; Suckling, Colin J; Hunter, William N

2010-01-14

Pteridine reductase (PTR1) is a target for drug development against Trypanosoma and Leishmania species, parasites that cause serious tropical diseases and for which therapies are inadequate. We adopted a structure-based approach to the design of novel PTR1 inhibitors based on three molecular scaffolds. A series of compounds, most newly synthesized, were identified as inhibitors with PTR1-species specific properties explained by structural differences between the T. brucei and L. major enzymes. The most potent inhibitors target T. brucei PTR1, and two compounds displayed antiparasite activity against the bloodstream form of the parasite. PTR1 contributes to antifolate drug resistance by providing a molecular bypass of dihydrofolate reductase (DHFR) inhibition. Therefore, combining PTR1 and DHFR inhibitors might improve therapeutic efficacy. We tested two new compounds with known DHFR inhibitors. A synergistic effect was observed for one particular combination highlighting the potential of such an approach for treatment of African sleeping sickness.

In silico fragment-based drug design.

PubMed

Konteatis, Zenon D

2010-11-01

In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates. Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed. The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs. In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein-protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.

An Ensemble Approach for Drug Side Effect Prediction

PubMed Central

Jahid, Md Jamiul; Ruan, Jianhua

2014-01-01

In silico prediction of drug side-effects in early stage of drug development is becoming more popular now days, which not only reduces the time for drug design but also reduces the drug development costs. In this article we propose an ensemble approach to predict drug side-effects of drug molecules based on their chemical structure. Our idea originates from the observation that similar drugs have similar side-effects. Based on this observation we design an ensemble approach that combine the results from different classification models where each model is generated by a different set of similar drugs. We applied our approach to 1385 side-effects in the SIDER database for 888 drugs. Results show that our approach outperformed previously published approaches and standard classifiers. Furthermore, we applied our method to a number of uncharacterized drug molecules in DrugBank database and predict their side-effect profiles for future usage. Results from various sources confirm that our method is able to predict the side-effects for uncharacterized drugs and more importantly able to predict rare side-effects which are often ignored by other approaches. The method described in this article can be useful to predict side-effects in drug design in an early stage to reduce experimental cost and time. PMID:25327524

Price regulation, new entry, and information shock on pharmaceutical market in Taiwan: a nationwide data-based study from 2001 to 2004

PubMed Central

2010-01-01

Background Using non-steroidal anti-inflammatory drugs (NSAIDs) as a case, we used Taiwan's National Health Insurance (NHI) database, to empirically explore the association between policy interventions (price regulation, new drug entry, and an information shock) and drug expenditures, utilization, and market structure between 2001 and 2004. Methods All NSAIDs prescribed in ambulatory visits in the NHI system during our study period were included and aggregated quarterly. Segmented regression analysis for interrupted time series was used to examine the associations between two price regulations, two new drug entries (cyclooxygennase-2 inhibitors) and the rofecoxib safety signal and expenditures and utilization of all NSAIDs. Herfindahl index (HHI) was applied to further examine the association between these interventions and market structure of NSAIDs. Results New entry was the only variable that was significantly correlated with changes of expenditures (positive change, p = 0.02) and market structure of the NSAIDs market in the NHI system. The correlation between price regulation (first price regulation, p = 0.62; second price regulation, p = 0.26) and information shock (p = 0.31) and drug expenditure were not statistically significant. There was no significant change in the prescribing volume of NSAIDs per rheumatoid arthritis (RA) or osteoarthritis (OA) ambulatory visit during the observational period. The market share of NSAIDs had also been largely substituted by these new drugs up to 50%, in a three-year period and resulted in a more concentrated market structure (HHI 0.17). Conclusions Our empirical study found that new drug entry was the main driving force behind escalating drug spending, especially by altering the market share. PMID:20653979

Uridine monophosphate kinase as potential target for tuberculosis: from target to lead identification.

PubMed

Arvind, Akanksha; Jain, Vaibhav; Saravanan, Parameswaran; Mohan, C Gopi

2013-12-01

Mycobacterium tuberculosis (Mtb) is a causative agent of tuberculosis (TB) disease, which has affected approximately 2 billion people worldwide. Due to the emergence of resistance towards the existing drugs, discovery of new anti-TB drugs is an important global healthcare challenge. To address this problem, there is an urgent need to identify new drug targets in Mtb. In the present study, the subtractive genomics approach has been employed for the identification of new drug targets against TB. Screening the Mtb proteome using the Database of Essential Genes (DEG) and human proteome resulted in the identification of 60 key proteins which have no eukaryotic counterparts. Critical analysis of these proteins using Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways database revealed uridine monophosphate kinase (UMPK) enzyme as a potential drug target for developing novel anti-TB drugs. Homology model of Mtb-UMPK was constructed for the first time on the basis of the crystal structure of E. coli-UMPK, in order to understand its structure-function relationships, and which would in turn facilitate to perform structure-based inhibitor design. Furthermore, the structural similarity search was carried out using physiological inhibitor UTP of Mtb-UMPK to virtually screen ZINC database. Retrieved hits were further screened by implementing several filters like ADME and toxicity followed by molecular docking. Finally, on the basis of the Glide docking score and the mode of binding, 6 putative leads were identified as inhibitors of this enzyme which can potentially emerge as future drugs for the treatment of TB.

Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods.

PubMed

Li, Mengshan; Zhang, Huaijing; Chen, Bingsheng; Wu, Yan; Guan, Lixin

2018-03-05

The pKa value of drugs is an important parameter in drug design and pharmacology. In this paper, an improved particle swarm optimization (PSO) algorithm was proposed based on the population entropy diversity. In the improved algorithm, when the population entropy was higher than the set maximum threshold, the convergence strategy was adopted; when the population entropy was lower than the set minimum threshold the divergence strategy was adopted; when the population entropy was between the maximum and minimum threshold, the self-adaptive adjustment strategy was maintained. The improved PSO algorithm was applied in the training of radial basis function artificial neural network (RBF ANN) model and the selection of molecular descriptors. A quantitative structure-activity relationship model based on RBF ANN trained by the improved PSO algorithm was proposed to predict the pKa values of 74 kinds of neutral and basic drugs and then validated by another database containing 20 molecules. The validation results showed that the model had a good prediction performance. The absolute average relative error, root mean square error, and squared correlation coefficient were 0.3105, 0.0411, and 0.9685, respectively. The model can be used as a reference for exploring other quantitative structure-activity relationships.

The Development of a Korean Drug Dosing Database

PubMed Central

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

2011-01-01

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

Liposome-encapsulated vincristine, vinblastine and vinorelbine: a comparative study of drug loading and retention.

PubMed

Zhigaltsev, Igor V; Maurer, Norbert; Akhong, Quet-Fah; Leone, Robert; Leng, Esther; Wang, Jinfang; Semple, Sean C; Cullis, Pieter R

2005-05-05

A comparative study of the loading and retention properties of three structurally very closely related vinca alkaloids (vincristine, vinorelbine and vinblastine) in liposomal formulations has been performed. All three vinca alkaloids showed high levels of encapsulation when accumulated into egg sphingomyelin/cholesterol vesicles in response to a transmembrane pH gradient generated by the use of the ionophore A23187 and encapsulated MgSO4. However, despite the close similarities of their structures the different vinca drugs exhibited very different release behavior, with vinblastine and vinorelbine being released faster than vincristine both in vitro and in vivo. The differences in loading and retention can be related to the lipophilicity of the drugs tested, where the more hydrophobic drugs are released more rapidly. It was also found that increasing the drug-to-lipid ratio significantly enhanced the retention of vinca alkaloids when the ionophore-based method was used for drug loading. In contrast, drug retention was not dependent on the initial drug-to-lipid ratio for vinca drugs loaded into liposomes containing an acidic citrate buffer. The differences in retention can be explained on the basis of differences in the physical state of the drug inside the liposomes. The drug-to-lipid ratio dependence of retention observed for liposomes loaded with the ionophore technique may provide a way to improve the retention characteristics of liposomal formulations of vinca drugs.

Testing an explanatory model of nurses' intention to report adverse drug reactions in hospital settings.

PubMed

Angelis, Alessia De; Pancani, Luca; Steca, Patrizia; Colaceci, Sofia; Giusti, Angela; Tibaldi, Laura; Alvaro, Rosaria; Ausili, Davide; Vellone, Ercole

2017-05-01

To test an explanatory model of nurses' intention to report adverse drug reactions in hospital settings, based on the theory of planned behaviour. Under-reporting of adverse drug reactions is an important problem among nurses. A cross-sectional design was used. Data were collected with the adverse drug reporting nurses' questionnaire. Confirmatory factor analysis was performed to test the factor validity of the adverse drug reporting nurses' questionnaire, and structural equation modelling was used to test the explanatory model. The convenience sample comprised 500 Italian hospital nurses (mean age = 43.52). Confirmatory factor analysis supported the factor validity of the adverse drug reporting nurses' questionnaire. The structural equation modelling showed a good fit with the data. Nurses' intention to report adverse drug reactions was significantly predicted by attitudes, subjective norms and perceived behavioural control (R² = 0.16). The theory of planned behaviour effectively explained the mechanisms behind nurses' intention to report adverse drug reactions, showing how several factors come into play. In a scenario of organisational empowerment towards adverse drug reaction reporting, the major predictors of the intention to report are support for the decision to report adverse drug reactions from other health care practitioners, perceptions about the value of adverse drug reaction reporting and nurses' favourable self-assessment of their adverse drug reaction reporting skills. © 2017 John Wiley & Sons Ltd.

DNA-PKcs, a novel functional target of acriflavine, mediates acriflavine's p53-dependent synergistic anti-tumor efficiency with melphalan.

PubMed

Cao, Ji; Lin, Guanyu; Gong, Yanling; Pan, Peichen; Ma, Yaxi; Huang, Ping; Ying, Meidan; Hou, Tingjun; He, Qiaojun; Yang, Bo

2016-12-01

Acriflavine (ACF), a known antibacterial drug, has recently been recognized as a suitable candidate for cancer chemotherapy. However, the molecular target of ACF is not fully understood, which limits its application in cancer therapy. In this study, we established a structure-specific probe-based pull-down approach to comprehensively profile the potential target of ACF, and we identified DNA dependent protein kinase catalytic subunit (DNA-PKcs) as the direct target of ACF. Since DNA-PKcs facilitates the repair process following DNA double-strand breaks, we further developed a drug combination strategy that combined ACF with the bifunctional alkylating agent melphalan, which exerted a p53-dependent synergistic efficacy against human cancer cells both in vitro and in vivo. With these findings, our study demonstrated that structure-specific probe-based pull-down approaches can be used to identify new functional target of drug, and provided novel opportunities for the development of ACF-based antitumor chemotherapies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Structure-Dependent Electric Release and Enhanced Oxidation of Drug in Graphene Oxide-Based Nanocarrier Loaded with Anticancer Herbal Drug Berberine.

PubMed

Yu, Danni; Ruan, Pan; Meng, Ziyuan; Zhou, Jianping

2015-08-01

The aim of the current investigation is to explore graphene oxide (GO) special electric and electrochemical properties in modulating and tuning drug delivery in tumor special environment of electrophysiology. The electric-sensitive drug release and redox behavior of GO-bearing berberine (Ber) was studied. Drug release in cell potential was applied in a designed electrode system: tumor environment was simulated at pH 6.2 with 0.1 V pulse voltage, whereas the normal was at pH 7.4 with 0.2 V. Quite different from the pH-depended profile, the electricity-triggered behavior indicated a high correlation with the carriers' structure: GO-based nanocomposite showed a burst release on its special "skin effect," whereas the PEGylated ones released slowly owing to the electroviscous effect of polymer. Cyclic voltammetry was used to investigate the redox behaviors of colloid PEGylated GO toward absorbed Ber in pH 5.8 and 7.2 solutions. After drug loading, the oxidation of Ber was enhanced in a neutral environment, whereas the enhancement of PEG-GO was in an acidic one, which means a possible increased susceptibility of their biotransformation in vivo. The studies designed in this work may help to establish a kind of carrier system for the sensitive delivery and metabolic regulation of drugs according to the different electrophysiological environment in tumor therapy. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can freely available at https://github.com/NwpuSY/DT_all.git for academic users. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

PockDrug-Server: a new web server for predicting pocket druggability on holo and apo proteins

PubMed Central

Hussein, Hiba Abi; Borrel, Alexandre; Geneix, Colette; Petitjean, Michel; Regad, Leslie; Camproux, Anne-Claude

2015-01-01

Predicting protein pocket's ability to bind drug-like molecules with high affinity, i.e. druggability, is of major interest in the target identification phase of drug discovery. Therefore, pocket druggability investigations represent a key step of compound clinical progression projects. Currently computational druggability prediction models are attached to one unique pocket estimation method despite pocket estimation uncertainties. In this paper, we propose ‘PockDrug-Server’ to predict pocket druggability, efficient on both (i) estimated pockets guided by the ligand proximity (extracted by proximity to a ligand from a holo protein structure) and (ii) estimated pockets based solely on protein structure information (based on amino atoms that form the surface of potential binding cavities). PockDrug-Server provides consistent druggability results using different pocket estimation methods. It is robust with respect to pocket boundary and estimation uncertainties, thus efficient using apo pockets that are challenging to estimate. It clearly distinguishes druggable from less druggable pockets using different estimation methods and outperformed recent druggability models for apo pockets. It can be carried out from one or a set of apo/holo proteins using different pocket estimation methods proposed by our web server or from any pocket previously estimated by the user. PockDrug-Server is publicly available at: http://pockdrug.rpbs.univ-paris-diderot.fr. PMID:25956651

PockDrug-Server: a new web server for predicting pocket druggability on holo and apo proteins.

PubMed

Hussein, Hiba Abi; Borrel, Alexandre; Geneix, Colette; Petitjean, Michel; Regad, Leslie; Camproux, Anne-Claude

2015-07-01

Predicting protein pocket's ability to bind drug-like molecules with high affinity, i.e. druggability, is of major interest in the target identification phase of drug discovery. Therefore, pocket druggability investigations represent a key step of compound clinical progression projects. Currently computational druggability prediction models are attached to one unique pocket estimation method despite pocket estimation uncertainties. In this paper, we propose 'PockDrug-Server' to predict pocket druggability, efficient on both (i) estimated pockets guided by the ligand proximity (extracted by proximity to a ligand from a holo protein structure) and (ii) estimated pockets based solely on protein structure information (based on amino atoms that form the surface of potential binding cavities). PockDrug-Server provides consistent druggability results using different pocket estimation methods. It is robust with respect to pocket boundary and estimation uncertainties, thus efficient using apo pockets that are challenging to estimate. It clearly distinguishes druggable from less druggable pockets using different estimation methods and outperformed recent druggability models for apo pockets. It can be carried out from one or a set of apo/holo proteins using different pocket estimation methods proposed by our web server or from any pocket previously estimated by the user. PockDrug-Server is publicly available at: http://pockdrug.rpbs.univ-paris-diderot.fr. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Crystal structure of the μ-opioid receptor bound to a morphinan antagonist

PubMed Central

Manglik, Aashish; Kruse, Andrew C.; Kobilka, Tong Sun; Thian, Foon Sun; Mathiesen, Jesper M.; Sunahara, Roger K.; Pardo, Leonardo; Weis, William I.; Kobilka, Brian K.; Granier, Sébastien

2012-01-01

Summary Opium is one of the world’s oldest drugs, and its derivatives morphine and codeine are among the most used clinical drugs to relieve severe pain. These prototypical opioids produce analgesia as well as many of their undesirable side effects (sedation, apnea and dependence) by binding to and activating the G-protein-coupled μ-opioid receptor (μOR) in the central nervous system. Here we describe the 2.8 Å crystal structure of the μOR in complex with an irreversible morphinan antagonist. Compared to the buried binding pocket observed in most GPCRs published to date, the morphinan ligand binds deeply within a large solvent-exposed pocket. Of particular interest, the μOR crystallizes as a two-fold symmetric dimer through a four-helix bundle motif formed by transmembrane segments 5 and 6. These high-resolution insights into opioid receptor structure will enable the application of structure-based approaches to develop better drugs for the management of pain and addiction. PMID:22437502

What Can Crystal Structures of Aminergic Receptors Tell Us about Designing Subtype-Selective Ligands?

PubMed Central

Michino, Mayako; Beuming, Thijs; Donthamsetti, Prashant; Newman, Amy Hauck; Javitch, Jonathan A.

2015-01-01

G protein–coupled receptors (GPCRs) are integral membrane proteins that represent an important class of drug targets. In particular, aminergic GPCRs interact with a significant portion of drugs currently on the market. However, most drugs that target these receptors are associated with undesirable side effects, which are due in part to promiscuous interactions with close homologs of the intended target receptors. Here, based on a systematic analysis of all 37 of the currently available high-resolution crystal structures of aminergic GPCRs, we review structural elements that contribute to and can be exploited for designing subtype-selective compounds. We describe the roles of secondary binding pockets (SBPs), as well as differences in ligand entry pathways to the orthosteric binding site, in determining selectivity. In addition, using the available crystal structures, we have identified conformational changes in the SBPs that are associated with receptor activation and explore the implications of these changes for the rational development of selective ligands with tailored efficacy. PMID:25527701

Uniform Surface Modification of 3D Bioglass®-Based Scaffolds with Mesoporous Silica Particles (MCM-41) for Enhancing Drug Delivery Capability

PubMed Central

Boccardi, Elena; Philippart, Anahí; Juhasz-Bortuzzo, Judith A.; Beltrán, Ana M.; Novajra, Giorgia; Vitale-Brovarone, Chiara; Spiecker, Erdmann; Boccaccini, Aldo R.

2015-01-01

The design and characterization of a new family of multifunctional scaffolds based on bioactive glass (BG) of 45S5 composition for bone tissue engineering and drug delivery applications are presented. These BG-based scaffolds are developed via a replication method of polyurethane packaging foam. In order to increase the therapeutic functionality, the scaffolds were coated with mesoporous silica particles (MCM-41), which act as an in situ drug delivery system. These sub-micron spheres are characterized by large surface area and pore volume with a narrow pore diameter distribution. The solution used for the synthesis of the silica mesoporous particles was designed to obtain a high-ordered mesoporous structure and spherical shape – both are key factors for achieving the desired controlled drug release. The MCM-41 particles were synthesized directly inside the BG-based scaffolds, and the drug-release capability of this combined system was evaluated. Moreover, the effect of MCM-41 particle coating on the bioactivity of the BG-based scaffolds was assessed. The results indicate that it is possible to obtain a multifunctional scaffold system characterized by high and interconnected porosity, high bioactivity, and sustained drug delivery capability. PMID:26594642

A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

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

Bhagavat, Raghu; Kim, Heung -Bok; Kim, Chang -Yub

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived frommore » a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. In conclusion, as the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.« less

Structures of Trypanosome Vacuolar Soluble Pyrophosphatases: Anti-Parasitic Drug Targets

PubMed Central

Yang, Yunyun; Ko, Tzu-Ping; Chen, Chun-Chi; Huang, Guozhong; Zheng, Yingying; Liu, Weidong; Wang, Iren; Ho, Meng-Ru; Danny Hsu, Shang-Te; O’Dowd, Bing; Huff, Hannah C.; Huang, Chun-Hsiang; Docampo, Roberto; Oldfield, Eric; Guo, Rey-Ting

2016-01-01

Trypanosomatid parasites are the causative agents of many neglected tropical diseases including the leishmaniases, Chagas disease, and human African trypanosomiasis. They exploit unusual vacuolar soluble pyrophosphatases (VSPs), absent in humans, for cell growth and virulence and as such, are drug targets. Here, we report the crystal structures of VSP1s from Trypanosoma cruzi and T. brucei, together with that of the T. cruzi protein bound to a bisphosphonate inhibitor. Both VSP1s form a hybrid structure containing an (N-terminal) EF-hand domain fused to a (C-terminal) pyrophosphatase domain. The two domains are connected via an extended loop of about 17 residues. Crystallographic analysis and size exclusion chromatography indicate that the VSP1s form tetramers containing head-to-tail dimers. Phosphate and diphosphate ligands bind in the PPase substrate-binding pocket and interact with several conserved residues, and a bisphosphonate inhibitor (BPH-1260) binds to the same site. Based on Cytoscape and other bioinformatics analyses it is apparent that similar folds will be found in most if not all trypanosomatid VSP1s, including those found in insects (Angomonas deanei, Strigomonas culicis), plant pathogens (Phytomonas spp.) and Leishmania spp. Overall, the results are of general interest since they open the way to structure-based drug design for many of the neglected tropical diseases. PMID:26907161

A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis

DOE PAGES

Bhagavat, Raghu; Kim, Heung -Bok; Kim, Chang -Yub; ...

2017-10-02

Nucleoside tri-phosphates (NTP) form an important class of small molecule ligands that participate in, and are essential to a large number of biological processes. Here, we seek to identify the NTP binding proteome (NTPome) in M. tuberculosis (M.tb), a deadly pathogen. Identifying the NTPome is useful not only for gaining functional insights of the individual proteins but also for identifying useful drug targets. From an earlier study, we had structural models of M.tb at a proteome scale from which a set of 13,858 small molecule binding pockets were identified. We use a set of NTP binding sub-structural motifs derived frommore » a previous study and scan the M.tb pocketome, and find that 1,768 proteins or 43% of the proteome can theoretically bind NTP ligands. Using an experimental proteomics approach involving dye-ligand affinity chromatography, we confirm NTP binding to 47 different proteins, of which 4 are hypothetical proteins. Our analysis also provides the precise list of binding site residues in each case, and the probable ligand binding pose. In conclusion, as the list includes a number of known and potential drug targets, the identification of NTP binding can directly facilitate structure-based drug design of these targets.« less

Dihydrofolate reductase: A potential drug target in trypanosomes and leishmania

NASA Astrophysics Data System (ADS)

Zuccotto, Fabio; Martin, Andrew C. R.; Laskowski, Roman A.; Thornton, Janet M.; Gilbert, Ian H.

1998-05-01

Dihydrofolate reductase has successfully been used as a drug target in the area of anti-cancer, anti-bacterial and anti-malarial chemotherapy. Little has been done to evaluate it as a drug target for treatment of the trypanosomiases and leishmaniasis. A crystal structure of Leishmania major dihydrofolate reductase has been published. In this paper, we describe the modelling of Trypanosoma cruzi and Trypanosoma brucei dihydrofolate reductases based on this crystal structure. These structures and models have been used in the comparison of protozoan, bacterial and human enzymes in order to highlight the different features that can be used in the design of selective anti-protozoan agents. Comparison has been made between residues present in the active site, the accessibility of these residues, charge distribution in the active site, and the shape and size of the active sites. Whilst there is a high degree of similarity between protozoan, human and bacterial dihydrofolate reductase active sites, there are differences that provide potential for selective drug design. In particular, we have identified a set of residues which may be important for selective drug design and identified a larger binding pocket in the protozoan than the human and bacterial enzymes.

Interactions of antiparasitic sterols with sterol 14α-demethylase (CYP51) of human pathogens.

PubMed

Warfield, Jasmine; Setzer, William N; Ogungbe, Ifedayo Victor

2014-01-01

Sterol 14α-demethylase is a validated and an attractive drug target in human protozoan parasites. Pharmacological inactivation of this important enzyme has proven very effective against fungal infections, and it is a target that is being exploited for new antitrypanosomal and antileishmanial chemotherapy. We have used in silico calculations to identify previously reported antiparasitic sterol-like compounds and their structural congeners that have preferential and high docking affinity for CYP51. The sterol 14α-demethylase from Trypanosoma cruzi and Leishmania infantum, in particular, preferentially dock to taraxerol, epi-oleanolic acid, and α/β-amyrim structural scaffolds. These structural information and predicted interactions can be exploited for fragment/structure-based antiprotozoal drug design.

[Design of the novel dipeptide neuropsychotropic drug preparations].

PubMed

Gudasheva, T A; Skoldinov, A P

2003-01-01

The paper considers a new strategy in the field of neuropsychotropic dipeptide drug design, the main points being as follows: (i) determination of the structural elements of dipeptides, such as fragments of amino acid side radicals and peptide bonds, in nonpeptide drugs; (ii) design of peptide analogs topologically close to the drug; (iii) synthesis and activity testing of these analogs; (iv) determination of the corresponding endogenous neuropeptide among the known neuropeptides or identification of the new neuropeptides in the brain of experimental animals. Using this approach, new pyroglutamyl- and prolyl-containing dipeptides were obtained based on the structure of the well-known classical nootropic drug piracetam. The new drugs exhibit nootropic activity in doses 100-10,000 times lower than those of piracetam. The structure of most active pyroglutamyl dipeptide pGlu-Asn-NH2 coincides with that of the N-end fragment of the endogenous memory peptide AVP(4-9). Noopept (N-phenylacetylprolylglycine ethyl ester), patented in Russia and USA as a new nootropic drug, is currently under stage 2 of successful clinical trials. The main metabolite of noopept, cyclo-Pro-Gly, is identical to the endogenous dipeptide designed in this work and is most close analog of piracetam with respect to pharmacological activity. The universal character of the proposed strategy is demonstrated by the design of active dipeptide analogs of an atypical neuroleptic drug sulpiride. As a result, a potential dipeptide neuroleptic dilept was obtained, which has been patented in Russia and now passes broad preclinical trials.

Discovery of novel dengue virus NS5 methyltransferase non-nucleoside inhibitors by fragment-based drug design.

PubMed

Benmansour, Fatiha; Trist, Iuni; Coutard, Bruno; Decroly, Etienne; Querat, Gilles; Brancale, Andrea; Barral, Karine

2017-01-05

With the aim to help drug discovery against dengue virus (DENV), a fragment-based drug design approach was applied to identify ligands targeting a main component of DENV replication complex: the NS5 AdoMet-dependent mRNA methyltransferase (MTase) domain, playing an essential role in the RNA capping process. Herein, we describe the identification of new inhibitors developed using fragment-based, structure-guided linking and optimization techniques. Thermal-shift assay followed by a fragment-based X-ray crystallographic screening lead to the identification of three fragment hits binding DENV MTase. We considered linking two of them, which bind to proximal sites of the AdoMet binding pocket, in order to improve their potency. X-ray crystallographic structures and computational docking were used to guide the fragment linking, ultimately leading to novel series of non-nucleoside inhibitors of flavivirus MTase, respectively N-phenyl-[(phenylcarbamoyl)amino]benzene-1-sulfonamide and phenyl [(phenylcarbamoyl)amino]benzene-1-sulfonate derivatives, that show a 10-100-fold stronger inhibition of 2'-O-MTase activity compared to the initial fragments. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Extreme Entropy-Enthalpy Compensation in a Drug Resistant Variant of HIV-1 Protease

PubMed Central

King, Nancy M.; Prabu-Jeyabalan, Moses; Bandaranayake, Rajintha M.; Nalam, Madhavi N. L.; Nalivaika, Ellen A.; Özen, Ayşegül; Haliloglu, Türkan; Yılmaz, Neşe Kurt; Schiffer, Celia A.

2012-01-01

The development of HIV-1 protease inhibitors has been the historic paradigm of rational structure-based drug design, where structural and thermodynamic analyses have assisted in the discovery of novel inhibitors. While the total enthalpy and entropy change upon binding determine the affinity, often the thermodynamics are considered in terms of inhibitor properties only. In the current study, profound changes are observed in the binding thermodynamics of a drug resistant variant compared to wild-type HIV-1 protease, irrespective of the inhibitor bound. This variant (Flap+) has a combination of flap and active site mutations and exhibits extremely large entropy-enthalpy compensation compared to wild-type protease, 5–15 kcal/mol, while losing only 1–3 kcal/mol in total binding free energy for any of six FDA approved inhibitors. Although entropy-enthalpy compensation has been previously observed for a variety of systems, never have changes of this magnitude been reported. The co-crystal structures of Flap+ protease with four of the inhibitors were determined and compared with complexes of both the wildtype protease and another drug resistant variant that does not exhibit this energetic compensation. Structural changes conserved across the Flap+ complexes, which are more pronounced for the flaps covering the active site, likely contribute to the thermodynamic compensation. The finding that drug resistant mutations can profoundly modulate the relative thermodynamic properties of a therapeutic target independent of the inhibitor presents a new challenge for rational drug design. PMID:22712830

Modeling the drugs' passive transfer in the body based on their chromatographic behavior.

PubMed

Kouskoura, Maria G; Kachrimanis, Kyriakos G; Markopoulou, Catherine K

2014-11-01

One of the most challenging aims in modern analytical chemistry and pharmaceutical analysis is to create models for drugs' behavior based on simulation experiments. Since drugs' effects are closely related to their molecular properties, numerous characteristics of drugs are used in order to acquire a model of passive absorption and transfer in the human body. Importantly, such direction in innovative bioanalytical methodologies is also of stressful need in the area of personalized medicine to implement nanotechnological and genomics advancements. Simulation experiments were carried out by examining and interpreting the chromatographic behavior of 113 analytes/drugs (400 observations) in RP-HPLC. The dataset employed for this purpose included 73 descriptors which are referring to the physicochemical properties of the mobile phase mixture in different proportions, the physicochemical properties of the analytes and the structural characteristics of their molecules. A series of different software packages was used to calculate all the descriptors apart from those referring to the structure of analytes. The correlation of the descriptors with the retention time of the analytes eluted from a C4 column with an aqueous mobile phase was employed as dataset to introduce the behavior models in the human body. Their evaluation with a Partial Least Squares (PLS) software proved that the chromatographic behavior of a drug on a lipophilic stationary and a polar mobile phase is directly related to its drug-ability. At the same time, the behavior of an unknown drug in the human body can be predicted with reliability via the Artificial Neural Networks (ANNs) software. Copyright © 2014 Elsevier B.V. All rights reserved.

The application of a novel high-resolution mass spectrometry-based analytical strategy to rapid metabolite profiling of a dual drug combination in humans.

PubMed

Xing, Jie; Zang, Meitong; Liu, Huixiang

2017-11-15

Metabolite profiling of combination drugs in complex matrix is a big challenge. Development of an effective data mining technique for simultaneously extracting metabolites of one parent drug from both background matrix and combined drug-related signals could be a solution. This study presented a novel high resolution mass spectrometry (HRMS)-based data-mining strategy to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was verapamil-irbesartan (VER-IRB), which is widely used in clinic to treat hypertension. First, mass defect filter (MDF), as a targeted data mining tool, worked effectively except for those metabolites with similar MDF values. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, was able to recover all relevant metabolites of VER-IRB from the full-scan MS dataset except for trace metabolites buried in the background noise and/or combined drug-related signals. Third, the novel ring double bond (RDB; valence values of elements in structure) filter, could show rich structural information in more sensitive full-scan MS chromatograms; however, it had a low capability to remove background noise and was difficult to differentiate the metabolites with RDB coverage. Fourth, an integrated strategy, i.e., untargeted BS followed by RDB, was effective for metabolite identification of VER and IRB, which have different RDB values. Majority of matrix signals were firstly removed using BS. Metabolite ions for each parent drug were then isolated from remaining background matrix and combined drug-related signals by imposing of preset RDB values/ranges around the parent drug and selected core substructures. In parallel, MDF was used to recover potential metabolites with similar RDB. As a result, a total of 74 metabolites were found for VER-IRB in human plasma and urine, among which ten metabolites have not been previously reported in human. The results demonstrated that the combination of accurate mass-based multiple data-mining techniques, i.e., untargeted background subtraction followed by ring double bond filtering in parallel with targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drug. Copyright © 2017 Elsevier B.V. All rights reserved.

Hospitals as a 'risk environment': an ethno-epidemiological study of voluntary and involuntary discharge from hospital against medical advice among people who inject drugs.

PubMed

McNeil, Ryan; Small, Will; Wood, Evan; Kerr, Thomas

2014-03-01

People who inject drugs (PWID) experience high levels of HIV/AIDS and hepatitis C (HCV) infection that, together with injection-related complications such as non-fatal overdose and injection-related infections, lead to frequent hospitalizations. However, injection drug-using populations are among those most likely to be discharged from hospital against medical advice, which significantly increases their likelihood of hospital readmission, longer overall hospital stays, and death. In spite of this, little research has been undertaken examining how social-structural forces operating within hospital settings shape the experiences of PWID in receiving care in hospitals and contribute to discharges against medical advice. This ethno-epidemiological study was undertaken in Vancouver, Canada to explore how the social-structural dynamics within hospitals function to produce discharges against medical advice among PWID. In-depth interviews were conducted with thirty PWID recruited from among participants in ongoing observational cohort studies of people who inject drugs who reported that they had been discharged from hospital against medical advice within the previous two years. Data were analyzed thematically, and by drawing on the 'risk environment' framework and concepts of social violence. Our findings illustrate how intersecting social and structural factors led to inadequate pain and withdrawal management, which led to continued drug use in hospital settings. In turn, diverse forms of social control operating to regulate and prevent drug use in hospital settings amplified drug-related risks and increased the likelihood of discharge against medical advice. Given the significant morbidity and health care costs associated with discharge against medical advice among drug-using populations, there is an urgent need to reshape the social-structural contexts of hospital care for PWID by shifting emphasis toward evidence-based pain and drug treatment augmented by harm reduction supports, including supervised drug consumption services. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hospitals as a `risk environment: An ethno-epidemiological study of voluntary and involuntary discharge from hospital against medical advice among people who inject drugs

PubMed Central

McNeil, Ryan; Small, Will; Wood, Evan; Kerr, Thomas

2014-01-01

People who inject drugs (PWID) experience high levels of HIV/AIDS and hepatitis C (HCV) infection that, together with injection-related complications such as non-fatal overdose and injection-related infections, lead to frequent hospitalizations. However, injection drug-using populations are among those most likely to be discharged from hospital against medical advice, which significantly increases their likelihood of hospital readmission, longer overall hospital stays, and death. In spite of this, little research has been undertaken examining how social-structural forces operating within hospital settings shape the experiences of PWID in receiving care in hospitals and contribute to discharges against medical advice. This ethno-epidemiological study was undertaken in Vancouver, Canada to explore how the social-structural dynamics within hospitals function to produce discharges against medical advice among PWID. In-depth interviews were conducted with thirty PWID recruited from among participants in ongoing observational cohort studies of people who inject drugs who reported that they had been discharged from hospital against medical advice within the previous two years. Data were analyzed thematically, and by drawing on the `Risk Environment' framework and concepts of social violence. Our findings illustrate how intersecting social and structural factors led to inadequate pain and withdrawal management, which led to continued drug use in hospital settings. In turn, diverse forms of social control operating to regulate and prevent drug use in hospital settings amplified drug-related risks and increased the likelihood of discharge against medical advice. Given the significant morbidity and health care costs associated with discharge against medical advice among drug-using populations, there is an urgent need to reshape the social-structural contexts of hospital care for PWID by shifting emphasis toward evidence-based pain and drug treatment augmented by harm reduction supports, including supervised drug consumption services. PMID:24508718

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.

Specialty pharmaceuticals: policy initiatives to improve assessment, pricing, prescription, and use.

PubMed

Robinson, James C; Howell, Scott

2014-10-01

The value of "specialty pharmaceuticals" for cancer and other complex conditions depends not merely on their molecular structures but also on the manner in which the drugs are assessed, insured, priced, prescribed, and used. This article analyzes the five principal stages through which a specialty drug must pass on its journey from the laboratory to the bedside. These include regulatory approval by the Food and Drug Administration for market access, insurance coverage, pricing and payment, physician prescription, and patient engagement. If structured appropriately, each stage improves performance and supports continued research and development. If structured inappropriately, however, each stage adds to administrative burdens, distorts clinical decision making, and weakens incentives for innovation. Cautious optimism is in order, but neither the continued development of breakthrough products nor their use according to evidence-based guidelines can be taken for granted. Project HOPE—The People-to-People Health Foundation, Inc.

The flavivirus capsid protein: Structure, function and perspectives towards drug design.

PubMed

Oliveira, Edson R A; Mohana-Borges, Ronaldo; de Alencastro, Ricardo B; Horta, Bruno A C

2017-01-02

Flaviviruses, such as dengue and zika viruses, are etiologic agents transmitted to humans mainly by arthropods and are of great epidemiological interest. The flavivirus capsid protein is a structural element required for the viral nucleocapsid assembly that presents the classical function of sheltering the viral genome. After decades of research, many reports have shown its different functionalities and influence over cell normal functioning. The subcellular distribution of this protein, which involves accumulation around lipid droplets and nuclear localization, also corroborates with its multi-functional characteristic. As flavivirus diseases are still in need of global control and in view of the possible key functionalities that the capsid protein promotes over flavivirus biology, novel considerations arise towards anti-flavivirus drug research. This review covers the main aspects concerning structural and functional features of the flavivirus C protein, ultimately, highlighting prospects in drug discovery based on this viral target. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Manglik, Aashish; Kruse, Andrew C.; Kobilka, Tong Sun

Opium is one of the world's oldest drugs, and its derivatives morphine and codeine are among the most used clinical drugs to relieve severe pain. These prototypical opioids produce analgesia as well as many undesirable side effects (sedation, apnoea and dependence) by binding to and activating the G-protein-coupled {mu}-opioid receptor ({mu}-OR) in the central nervous system. Here we describe the 2.8 {angstrom} crystal structure of the mouse {mu}-OR in complex with an irreversible morphinan antagonist. Compared to the buried binding pocket observed in most G-protein-coupled receptors published so far, the morphinan ligand binds deeply within a large solvent-exposed pocket. Ofmore » particular interest, the {mu}-OR crystallizes as a two-fold symmetrical dimer through a four-helix bundle motif formed by transmembrane segments 5 and 6. These high-resolution insights into opioid receptor structure will enable the application of structure-based approaches to develop better drugs for the management of pain and addiction.« less

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.

Characteristics of drug demand reduction structures in Britain and Iran

PubMed Central

Narenjiha, Hooman; Noori, Roya; Ghiabi, Maziyar; Khoddami-Vishteh, Hamid-Reza

2016-01-01

Administrative structure of drug demand reduction and the way in which involved organizations interact with each other has been neglected by researchers, policy makers, and administrators at the national level and even in international institutions in this field. Studying such structures in different countries can reveal their attributes and features. In this study, key experts from the addictive behavior department of St George’s University of London and a group of Iranian specialists in the field of drug demand reduction first wrote on a sheet the name of organizations that are in charge of drug demand reduction. Then, via teamwork, they drew the connections between the organizations and compared the two charts to assess the relations between the member organizations. In total, 17 features of efficient structure were obtained as follow: multi-institutional nature, collaborative inter-institutional activities, clear and relevant inter-institutional and intra-institutional job description, the ability to share the experiences, virtual institutions activity, community-based associations activity, mutual relationships, the existence of feedback sys-tems, evaluation, changeability, the ability to collect data rapidly, being rooted in community, flexibility at the local and regional levels, connection with research centers, updated policymaking, empowering the local level, and seeking the maximum benefit and the minimum resources. Recognizing the characteristics of substance related organizations in various countries could help policy makers to improve drug demand reduction structures and to manage the wide-spread use of psychoactive substances more effectively. PMID:27853729

Characteristics of drug demand reduction structures in Britain and Iran.

PubMed

Narenjiha, Hooman; Noori, Roya; Ghiabi, Maziyar; Khoddami-Vishteh, Hamid-Reza

2015-01-01

Administrative structure of drug demand reduction and the way in which involved organizations interact with each other has been neglected by researchers, policy makers, and administrators at the national level and even in international institutions in this field. Studying such structures in different countries can reveal their attributes and features. In this study, key experts from the addictive behavior department of St George's University of London and a group of Iranian specialists in the field of drug demand reduction first wrote on a sheet the name of organizations that are in charge of drug demand reduction. Then, via teamwork, they drew the connections between the organizations and compared the two charts to assess the relations between the member organizations. In total, 17 features of efficient structure were obtained as follow: multi-institutional nature, collaborative inter-institutional activities, clear and relevant inter-institutional and intra-institutional job description, the ability to share the experiences, virtual institutions activity, community-based associations activity, mutual relationships, the existence of feedback sys-tems, evaluation, changeability, the ability to collect data rapidly, being rooted in community, flexibility at the local and regional levels, connection with research centers, updated policymaking, empowering the local level, and seeking the maximum benefit and the minimum resources. Recognizing the characteristics of substance related organizations in various countries could help policy makers to improve drug demand reduction structures and to manage the wide-spread use of psychoactive substances more effectively.

The multiple roles of computational chemistry in fragment-based drug design

NASA Astrophysics Data System (ADS)

Law, Richard; Barker, Oliver; Barker, John J.; Hesterkamp, Thomas; Godemann, Robert; Andersen, Ole; Fryatt, Tara; Courtney, Steve; Hallett, Dave; Whittaker, Mark

2009-08-01

Fragment-based drug discovery (FBDD) represents a change in strategy from the screening of molecules with higher molecular weights and physical properties more akin to fully drug-like compounds, to the screening of smaller, less complex molecules. This is because it has been recognised that fragment hit molecules can be efficiently grown and optimised into leads, particularly after the binding mode to the target protein has been first determined by 3D structural elucidation, e.g. by NMR or X-ray crystallography. Several studies have shown that medicinal chemistry optimisation of an already drug-like hit or lead compound can result in a final compound with too high molecular weight and lipophilicity. The evolution of a lower molecular weight fragment hit therefore represents an attractive alternative approach to optimisation as it allows better control of compound properties. Computational chemistry can play an important role both prior to a fragment screen, in producing a target focussed fragment library, and post-screening in the evolution of a drug-like molecule from a fragment hit, both with and without the available fragment-target co-complex structure. We will review many of the current developments in the area and illustrate with some recent examples from successful FBDD discovery projects that we have conducted.

Ab initio design of drug carriers for zoledronate guest molecule using phosphonated and sulfonated calix[4]arene and calix[4]resorcinarene host molecules

NASA Astrophysics Data System (ADS)

Jang, Yong-Man; Yu, Chol-Jun; Kim, Jin-Song; Kim, Song-Un

2018-04-01

Monomolecular drug carriers based on calix[n]-arenes and -resorcinarenes containing the interior cavity can enhance the affinity and specificity of the osteoporosis inhibitor drug zoledronate (ZOD). In this work we investigate the suitability of nine different calix[4]-arenes and -resorcinarenes based macrocycles as hosts for the ZOD guest molecule by conducting {\\it ab initio} density functional theory calculations for structures and energetics of eighteen different host-guest complexes. For the optimized molecular structures of the free, phosphonated, sulfonated calix[4]-arenes and -resorcinarenes, the geometric sizes of their interior cavities are measured and compared with those of the host-guest complexes in order to check the appropriateness for host-guest complex formation. Our calculations of binding energies indicate that in gaseous states some of the complexes might be unstable but in aqueous states almost all of the complexes can be formed spontaneously. Of the two different docking ways, the insertion of ZOD with the \\ce{P-C-P} branch into the cavity of host is easier than that with the nitrogen containing heterocycle of ZOD. The work will open a way for developing effective drug delivering systems for the ZOD drug and promote experimentalists to synthesize them.

A novel integrated framework and improved methodology of computer-aided drug design.

PubMed

Chen, Calvin Yu-Chian

2013-01-01

Computer-aided drug design (CADD) is a critical initiating step of drug development, but a single model capable of covering all designing aspects remains to be elucidated. Hence, we developed a drug design modeling framework that integrates multiple approaches, including machine learning based quantitative structure-activity relationship (QSAR) analysis, 3D-QSAR, Bayesian network, pharmacophore modeling, and structure-based docking algorithm. Restrictions for each model were defined for improved individual and overall accuracy. An integration method was applied to join the results from each model to minimize bias and errors. In addition, the integrated model adopts both static and dynamic analysis to validate the intermolecular stabilities of the receptor-ligand conformation. The proposed protocol was applied to identifying HER2 inhibitors from traditional Chinese medicine (TCM) as an example for validating our new protocol. Eight potent leads were identified from six TCM sources. A joint validation system comprised of comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular dynamics simulation further characterized the candidates into three potential binding conformations and validated the binding stability of each protein-ligand complex. The ligand pathway was also performed to predict the ligand "in" and "exit" from the binding site. In summary, we propose a novel systematic CADD methodology for the identification, analysis, and characterization of drug-like candidates.

Quercetin-Based Modified Porous Silicon Nanoparticles for Enhanced Inhibition of Doxorubicin-Resistant Cancer Cells.

PubMed

Liu, Zehua; Balasubramanian, Vimalkumar; Bhat, Chinmay; Vahermo, Mikko; Mäkilä, Ermei; Kemell, Marianna; Fontana, Flavia; Janoniene, Agne; Petrikaite, Vilma; Salonen, Jarno; Yli-Kauhaluoma, Jari; Hirvonen, Jouni; Zhang, Hongbo; Santos, Hélder A

2017-02-01

One of the most challenging obstacles in nanoparticle's surface modification is to achieve the concept that one ligand can accomplish multiple purposes. Upon such consideration, 3-aminopropoxy-linked quercetin (AmQu), a derivative of a natural flavonoid inspired by the structure of dopamine, is designed and subsequently used to modify the surface of thermally hydrocarbonized porous silicon (PSi) nanoparticles. This nanosystem inherits several advanced properties in a single carrier, including promoted anticancer efficiency, multiple drug resistance (MDR) reversing, stimuli-responsive drug release, drug release monitoring, and enhanced particle-cell interactions. The anticancer drug doxorubicin (DOX) is efficiently loaded into this nanosystem and released in a pH-dependent manner. AmQu also effectively quenches the fluorescence of the loaded DOX, thereby allowing the use of the nanosystem for monitoring the intracellular drug release. Furthermore, a synergistic effect with the presence of AmQu is observed in both normal MCF-7 and DOX-resistant MCF-7 breast cancer cells. Due to the similar structure as dopamine, AmQu may facilitate both the interaction and internalization of PSi into the cells. Overall, this PSi-based platform exhibits remarkable superiority in both multifunctionality and anticancer efficiency, making this nanovector a promising system for anti-MDR cancer treatment. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase.

PubMed

Shukla, Rohit; Shukla, Harish; Sonkar, Amit; Pandey, Tripti; Tripathi, Timir

2018-06-01

Mycobacterium tuberculosis is the etiological agent of tuberculosis in humans and is responsible for more than two million deaths annually. M. tuberculosis isocitrate lyase (MtbICL) catalyzes the first step in the glyoxylate cycle, plays a pivotal role in the persistence of M. tuberculosis, which acts as a potential target for an anti-tubercular drug. To identify the potential anti-tuberculosis compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,748) against the MtbICL structure. The ligands were docked against MtbICL in three sequential docking modes that resulted in 340 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 27 compounds were found to fit well with re-docking studies. After refinement by molecular docking and drug-likeness analyses, three potential inhibitors (ZINC1306071, ZINC2111081, and ZINC2134917) were identified. These three ligands and the reference compounds were further subjected to molecular dynamics simulation and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the MtbICL and bound complexes. The binding free energy analyses were calculated to validate and capture the intermolecular interactions. The results suggested that the three compounds had a negative binding energy with -96.462, -143.549, and -122.526 kJ mol -1 for compounds with IDs ZINC1306071, ZINC2111081, and ZINC2134917, respectively. These lead compounds displayed substantial pharmacological and structural properties to be drug candidates. We concluded that ZINC2111081 has a great potential to inhibit MtbICL and would add to the drug discovery process against tuberculosis.

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment

PubMed Central

2010-01-01

Background Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. Results We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. Conclusions In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets. PMID:21034488

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment.

PubMed

Capriles, Priscila V S Z; Guimarães, Ana C R; Otto, Thomas D; Miranda, Antonio B; Dardenne, Laurent E; Degrave, Wim M

2010-10-29

Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets.

How to Choose the Suitable Template for Homology Modelling of GPCRs: 5-HT7 Receptor as a Test Case.

PubMed

Shahaf, Nir; Pappalardo, Matteo; Basile, Livia; Guccione, Salvatore; Rayan, Anwar

2016-09-01

G protein-coupled receptors (GPCRs) are a super-family of membrane proteins that attract great pharmaceutical interest due to their involvement in almost every physiological activity, including extracellular stimuli, neurotransmission, and hormone regulation. Currently, structural information on many GPCRs is mainly obtained by the techniques of computer modelling in general and by homology modelling in particular. Based on a quantitative analysis of eighteen antagonist-bound, resolved structures of rhodopsin family "A" receptors - also used as templates to build 153 homology models - it was concluded that a higher sequence identity between two receptors does not guarantee a lower RMSD between their structures, especially when their pair-wise sequence identity (within trans-membrane domain and/or in binding pocket) lies between 25 % and 40 %. This study suggests that we should consider all template receptors having a sequence identity ≤50 % with the query receptor. In fact, most of the GPCRs, compared to the currently available resolved structures of GPCRs, fall within this range and lack a correlation between structure and sequence. When testing suitability for structure-based drug design, it was found that choosing as a template the most similar resolved protein, based on sequence resemblance only, led to unsound results in many cases. Molecular docking analyses were carried out, and enrichment factors as well as attrition rates were utilized as criteria for assessing suitability for structure-based drug design. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Medicinal electronomics bricolage design of hypoxia-targeting antineoplastic drugs and invention of boron tracedrugs as innovative future-architectural drugs.

PubMed

Hori, Hitoshi; Uto, Yoshihiro; Nakata, Eiji

2010-09-01

We describe herein for the first time our medicinal electronomics bricolage design of hypoxia-targeting antineoplastic drugs and boron tracedrugs as newly emerging drug classes. A new area of antineoplastic drugs and treatments has recently focused on neoplastic cells of the tumor environment/microenvironment involving accessory cells. This tumor hypoxic environment is now considered as a major factor that influences not only the response to antineoplastic therapies but also the potential for malignant progression and metastasis. We review our medicinal electronomics bricolage design of hypoxia-targeting drugs, antiangiogenic hypoxic cell radiosensitizers, sugar-hybrid hypoxic cell radiosensitizers, and hypoxia-targeting 10B delivery agents, in which we design drug candidates based on their electronic structures obtained by molecular orbital calculations, not based solely on pharmacophore development. These drugs include an antiangiogenic hypoxic cell radiosensitizer TX-2036, a sugar-hybrid hypoxic cell radiosensitizer TX-2244, new hypoxia-targeting indoleamine 2,3-dioxygenase (IDO) inhibitors, and a hypoxia-targeting BNCT agent, BSH (sodium borocaptate-10B)-hypoxic cytotoxin tirapazamine (TPZ) hybrid drug TX-2100. We then discuss the concept of boron tracedrugs as a new drug class having broad potential in many areas.

Biomimetic Solid Lipid Nanoparticles of Sophorolipids Designed for Antileprosy Drugs.

PubMed

Kanwar, Rohini; Gradzielski, Michael; Mehta, S K

2018-06-22

The objective of the present work was to develop solid lipid nanoparticles (SLNs) as drug-encapsulating structures by the solvent injection method. In this report, for the first time the inherent potential of lactonic sophorolipid (glycolipid) was exploited to formulate SLNs. A range of different Pluronic copolymers were screened by dynamic and static light scattering with the aim of obtaining most stable SLNs. To comprehend the structure of the SLNs, techniques such as transmission electron microscopy, differential scanning calorimetry, Fourier transform infrared spectroscopy, and X-ray diffraction were employed. A clear correlation between the type of Pluronic and size and stability of the SLNs could be drawn. The vector properties of the formed SLNs were assessed for both the encapsulated hydrophobic drugs-rifampicin and dapsone. To elucidate the transport mechanism of drug release, kinetic modeling was carried out on the drug release profiles. The promising results of sophorolipid-based SLNs have actually established a new arena beneath the significantly developed field of SLNs.

Mycotoxins and antifungal drug interactions: implications in the treatment of illnesses due to indoor chronic toxigenic mold exposures.

PubMed

Anyanwu, Ebere C; Campbell, Andrew W; Ehiri, John E

2004-03-12

Chronic exposure to toxigenic molds in water-damaged buildings is an indoor environmental health problem to which escalating health and property insurance costs are raising a statewide concern in recent times. This paper reviews the structural and functional properties of mycotoxins produced by toxigenic molds and their interactive health implications with antifungal drugs. Fundamental bases of pathophysiological, neurodevelopmental, and cellular mechanisms of mycotoxic effects are evaluated. It is most likely that the interactions of mycotoxins with antifungal drugs may, at least in part, contribute to the observable persistent illnesses, antifungal drug resistance, and allergic reactions in patients exposed to chronic toxigenic molds. Safe dose level of mycotoxin in humans is not clear. Hence, the safety regulations in place at the moment remain inconclusive, precautionary, and arbitrary. Since some of the antifungal drugs are derived from molds, and since they have structural and functional groups similar to those of mycotoxins, the knowledge of their interactions are important in enhancing preventive measures.

Ultrafast protein structure-based virtual screening with Panther

NASA Astrophysics Data System (ADS)

Niinivehmas, Sanna P.; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T.

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Ultrafast protein structure-based virtual screening with Panther.

PubMed

Niinivehmas, Sanna P; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Solid state compatibility study and characterization of a novel degradation product of tacrolimus in formulation.

PubMed

Rozman Peterka, Tanja; Grahek, Rok; Hren, Jure; Bastarda, Andrej; Bergles, Jure; Urleb, Uroš

2015-06-10

Tacrolimus is macrolide drug that is widely used as a potent immunosuppressant. In the present work compatibility testing was conducted on physical mixtures of tacrolimus with excipients and on compatibility mixtures prepared by the simulation of manufacturing process used for the final drug product preparation. Increase in one major degradation product was detected in the presence of magnesium stearate based upon UHPLC analysis. The degradation product was isolated by preparative HPLC and its structure was elucidated by NMR and MS studies. Mechanism of the formation of this degradation product is proposed based on complementary degradation studies in a solution and structural elucidation data. The structure was proven to be alpha-hydroxy acid which is formed from the parent tacrolimus molecule through a benzilic acid type rearrangement reaction in the presence of divalent metallic cations. Degradation is facilitated at higher pH values. Copyright © 2015 Elsevier B.V. All rights reserved.

Design of study without drugs--a Surinamese school-based drug-prevention program for adolescents.

PubMed

Ishaak, Fariel; de Vries, Nanne Karel; van der Wolf, Kees

2015-10-12

The aim of this study was to design the content and accompanying materials for a school-based program--Study without Drugs--for adolescents in junior secondary schools in Suriname based on the starting points and tasks of the fourth step of the Intervention Mapping protocol (which consists of six steps). A program based on this protocol should include a combination of theory, empirical evidence, and qualitative and quantitative research. Two surveys were conducted when designing the program. In Survey I, teachers and students were asked to complete a questionnaire to determine which school year they thought would be most appropriate for implementing a drug-prevention program for adolescents (we completed a similar survey as part of previous research). An attempt was made to identify suitable culturally sensitive elements to include in the program. In Survey II, the same teachers were asked to complete a questionnaire to determine the programs' scope, sequence, structure, and topics as well as the general didactic principles to serve as a basis for program design. After outlining the program plan, lessons, and materials, we conducted a formative pretest evaluation among teachers, students, and parents. That evaluation included measures related to the program's attractiveness, comprehensibility, and usefulness. The resulting lessons were presented to the teachers for assessment. The drug-prevention program we developed comprises 10 activities and lasts 2-2.5 months in an actual school setting. The activities take place during Dutch, biology, physical education, art, religion, and social studies lessons. We based the structure of the lessons in the program on McGuire's Persuasion Communication Model, which takes into account important didactic principles. Evaluations of the program materials and lesson plans by students, teachers, and parents were mostly positive. We believe that using the fourth step of the Intervention Mapping protocol to develop a drug-prevention intervention for adolescents has a produced promising, feasible program.

RNA-dependent RNA polymerase: Addressing Zika outbreak by a phylogeny-based drug target study.

PubMed

Stephen, Preyesh; Lin, Sheng-Xiang

2018-01-01

Since the first major outbreak of Zika virus (ZIKV) in 2007, ZIKV is spreading explosively through South and Central America, and recent reports in highly populated developing countries alarm the possibility of a more catastrophic outbreak. ZIKV infection in pregnant women leads to embryonic microcephaly and Guillain-Barré syndrome in adults. At present, there is limited understanding of the infectious mechanism, and no approved therapy has been reported. Despite the withdrawal of public health emergency, the WHO still considers the ZIKV as a highly significant and long-term public health challenge that the situation has to be addressed rapidly. Non-structural protein 5 is essential for capping and replication of viral RNA and comprises a methyltransferase and RNA-dependent RNA polymerase (RdRp) domain. We used molecular modeling to obtain the structure of ZIKV RdRp, and by molecular docking and phylogeny analysis, we here demonstrate the potential sites for drug screening. Two metal binding sites and an NS3-interacting region in ZIKV RdRp are demonstrated as potential drug screening sites. The docked structures reveal a remarkable degree of conservation at the substrate binding site and the potential drug screening sites. A phylogeny-based approach is provided for an emergency preparedness, where similar class of ligands could target phylogenetically related proteins. © 2017 John Wiley & Sons A/S.

Dendrimers in Medicine: Therapeutic Concepts and Pharmaceutical Challenges.

PubMed

Wu, Lin-Ping; Ficker, Mario; Christensen, Jørn B; Trohopoulos, Panagiotis N; Moghimi, Seyed Moein

2015-07-15

Dendrimers are three-dimensional macromolecular structures originating from a central core molecule and surrounded by successive addition of branching layers (generation). These structures exhibit a high degree of molecular uniformity, narrow molecular weight distribution, tunable size and shape characteristics, as well as multivalency. Collectively, these physicochemical characteristics together with advancements in design of biodegradable backbones have conferred many applications to dendrimers in formulation science and nanopharmaceutical developments. These have included the use of dendrimers as pro-drugs and vehicles for solubilization, encapsulation, complexation, delivery, and site-specific targeting of small-molecule drugs, biopharmaceuticals, and contrast agents. We briefly review these advances, paying particular attention to attributes that make dendrimers versatile for drug formulation as well as challenging issues surrounding the future development of dendrimer-based medicines.

Large-scale computational drug repositioning to find treatments for rare diseases.

PubMed

Govindaraj, Rajiv Gandhi; Naderi, Misagh; Singha, Manali; Lemoine, Jeffrey; Brylinski, Michal

2018-01-01

Rare, or orphan, diseases are conditions afflicting a small subset of people in a population. Although these disorders collectively pose significant health care problems, drug companies require government incentives to develop drugs for rare diseases due to extremely limited individual markets. Computer-aided drug repositioning, i.e., finding new indications for existing drugs, is a cheaper and faster alternative to traditional drug discovery offering a promising venue for orphan drug research. Structure-based matching of drug-binding pockets is among the most promising computational techniques to inform drug repositioning. In order to find new targets for known drugs ultimately leading to drug repositioning, we recently developed e MatchSite, a new computer program to compare drug-binding sites. In this study, e MatchSite is combined with virtual screening to systematically explore opportunities to reposition known drugs to proteins associated with rare diseases. The effectiveness of this integrated approach is demonstrated for a kinase inhibitor, which is a confirmed candidate for repositioning to synapsin Ia. The resulting dataset comprises 31,142 putative drug-target complexes linked to 980 orphan diseases. The modeling accuracy is evaluated against the structural data recently released for tyrosine-protein kinase HCK. To illustrate how potential therapeutics for rare diseases can be identified, we discuss a possibility to repurpose a steroidal aromatase inhibitor to treat Niemann-Pick disease type C. Overall, the exhaustive exploration of the drug repositioning space exposes new opportunities to combat orphan diseases with existing drugs. DrugBank/Orphanet repositioning data are freely available to research community at https://osf.io/qdjup/.

Modeled structure of trypanothione reductase of Leishmania infantum.

PubMed

Singh, Bishal K; Sarkar, Nandini; Jagannadham, M V; Dubey, Vikash K

2008-06-30

Trypanothione reductase is an important target enzyme for structure-based drug design against Leishmania. We used homology modeling to construct a three-dimensional structure of the trypanothione reductase (TR) of Leishmania infantum. The structure shows acceptable Ramachandran statistics and a remarkably different active site from glutathione reductase(GR). Thus, a specific inhibitor against TR can be designed without interfering with host (human) GR activity.

ADME-Space: a new tool for medicinal chemists to explore ADME properties.

PubMed

Bocci, Giovanni; Carosati, Emanuele; Vayer, Philippe; Arrault, Alban; Lozano, Sylvain; Cruciani, Gabriele

2017-07-25

We introduce a new chemical space for drugs and drug-like molecules, exclusively based on their in silico ADME behaviour. This ADME-Space is based on self-organizing map (SOM) applied to 26,000 molecules. Twenty accurate QSPR models, describing important ADME properties, were developed and, successively, used as new molecular descriptors not related to molecular structure. Applications include permeability, active transport, metabolism and bioavailability studies, but the method can be even used to discuss drug-drug interactions (DDIs) or it can be extended to additional ADME properties. Thus, the ADME-Space opens a new framework for the multi-parametric data analysis in drug discovery where all ADME behaviours of molecules are condensed in one map: it allows medicinal chemists to simultaneously monitor several ADME properties, to rapidly select optimal ADME profiles, retrieve warning on potential ADME problems and DDIs or select proper in vitro experiments.

Lessons from Hot Spot Analysis for Fragment-Based Drug Discovery.

PubMed

Hall, David R; Kozakov, Dima; Whitty, Adrian; Vajda, Sandor

2015-11-01

Analysis of binding energy hot spots at protein surfaces can provide crucial insights into the prospects for successful application of fragment-based drug discovery (FBDD), and whether a fragment hit can be advanced into a high-affinity, drug-like ligand. The key factor is the strength of the top ranking hot spot, and how well a given fragment complements it. We show that published data are sufficient to provide a sophisticated and quantitative understanding of how hot spots derive from a protein 3D structure, and how their strength, number, and spatial arrangement govern the potential for a surface site to bind to fragment-sized and larger ligands. This improved understanding provides important guidance for the effective application of FBDD in drug discovery. Copyright © 2015 Elsevier Ltd. All rights reserved.

Silk-based delivery systems of bioactive molecules.

PubMed

Numata, Keiji; Kaplan, David L

2010-12-30

Silks are biodegradable, biocompatible, self-assembling proteins that can also be tailored via genetic engineering to contain specific chemical features, offering utility for drug and gene delivery. Silkworm silk has been used in biomedical sutures for decades and has recently achieved Food and Drug Administration approval for expanded biomaterials device utility. With the diversity and control of size, structure and chemistry, modified or recombinant silk proteins can be designed and utilized in various biomedical application, such as for the delivery of bioactive molecules. This review focuses on the biosynthesis and applications of silk-based multi-block copolymer systems and related silk protein drug delivery systems. The utility of these systems for the delivery of small molecule drugs, proteins and genes is reviewed. Copyright © 2010 Elsevier B.V. All rights reserved.

Scaffold architecture and pharmacophoric properties of natural products and trade drugs: application in the design of natural product-based combinatorial libraries.

PubMed

Lee, M L; Schneider, G

2001-01-01

Natural products were analyzed to determine whether they contain appealing novel scaffold architectures for potential use in combinatorial chemistry. Ring systems were extracted and clustered on the basis of structural similarity. Several such potential scaffolds for combinatorial chemistry were identified that are not present in current trade drugs. For one of these scaffolds a virtual combinatorial library was generated. Pharmacophoric properties of natural products, trade drugs, and the virtual combinatorial library were assessed using a self-organizing map. Obviously, current trade drugs and natural products have several topological pharmacophore patterns in common. These features can be systematically explored with selected combinatorial libraries based on a combination of natural product-derived and synthetic molecular building blocks.

iGPCR-Drug: A Web Server for Predicting Interaction between GPCRs and Drugs in Cellular Networking

PubMed Central

Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

2013-01-01

Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called “iGPCR-drug”, was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug – target interaction networks. PMID:24015221

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

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

Wang, Kejian, E-mail: kejian.wang.bio@gmail.com; Weng, Zuquan; Sun, Liya

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. Inmore » the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.« less

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

PubMed

Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

pH-Responsive Mesoporous Silica and Carbon Nanoparticles for Drug Delivery

PubMed Central

Gisbert-Garzarán, Miguel; Manzano, Miguel; Vallet-Regí, María

2017-01-01

The application of nanotechnology to medicine constitutes a major field of research nowadays. In particular, the use of mesoporous silica and carbon nanoparticles has attracted the attention of numerous researchers due to their unique properties, especially when applied to cancer treatment. Many strategies based on stimuli-responsive nanocarriers have been developed to control the drug release and avoid premature release. Here, we focus on the use of the subtle changes of pH between healthy and diseased areas along the body to trigger the release of the cargo. In this review, different approximations of pH-responsive systems are considered: those based on the use of the host-guest interactions between the nanocarriers and the drugs, those based on the hydrolysis of acid-labile bonds and those based on supramolecular structures acting as pore capping agents. PMID:28952481

Diversity-Oriented Synthesis as a Strategy for Fragment Evolution against GSK3β.

PubMed

Wang, Yikai; Wach, Jean-Yves; Sheehan, Patrick; Zhong, Cheng; Zhan, Chenyang; Harris, Richard; Almo, Steven C; Bishop, Joshua; Haggarty, Stephen J; Ramek, Alexander; Berry, Kayla N; O'Herin, Conor; Koehler, Angela N; Hung, Alvin W; Young, Damian W

2016-09-08

Traditional fragment-based drug discovery (FBDD) relies heavily on structural analysis of the hits bound to their targets. Herein, we present a complementary approach based on diversity-oriented synthesis (DOS). A DOS-based fragment collection was able to produce initial hit compounds against the target GSK3β, allow the systematic synthesis of related fragment analogues to explore fragment-level structure-activity relationship, and finally lead to the synthesis of a more potent compound.

Small Scaffolds, Big Potential: Developing Miniature Proteins as Therapeutic Agents.

PubMed

Holub, Justin M

2017-09-01

Preclinical Research Miniature proteins are a class of oligopeptide characterized by their short sequence lengths and ability to adopt well-folded, three-dimensional structures. Because of their biomimetic nature and synthetic tractability, miniature proteins have been used to study a range of biochemical processes including fast protein folding, signal transduction, catalysis and molecular transport. Recently, miniature proteins have been gaining traction as potential therapeutic agents because their small size and ability to fold into defined tertiary structures facilitates their development as protein-based drugs. This research overview discusses emerging developments involving the use of miniature proteins as scaffolds to design novel therapeutics for the treatment and study of human disease. Specifically, this review will explore strategies to: (i) stabilize miniature protein tertiary structure; (ii) optimize biomolecular recognition by grafting functional epitopes onto miniature protein scaffolds; and (iii) enhance cytosolic delivery of miniature proteins through the use of cationic motifs that facilitate endosomal escape. These objectives are discussed not only to address challenges in developing effective miniature protein-based drugs, but also to highlight the tremendous potential miniature proteins hold for combating and understanding human disease. Drug Dev Res 78 : 268-282, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

ForceGen 3D structure and conformer generation: from small lead-like molecules to macrocyclic drugs

NASA Astrophysics Data System (ADS)

Cleves, Ann E.; Jain, Ajay N.

2017-05-01

We introduce the ForceGen method for 3D structure generation and conformer elaboration of drug-like small molecules. ForceGen is novel, avoiding use of distance geometry, molecular templates, or simulation-oriented stochastic sampling. The method is primarily driven by the molecular force field, implemented using an extension of MMFF94s and a partial charge estimator based on electronegativity-equalization. The force field is coupled to algorithms for direct sampling of realistic physical movements made by small molecules. Results are presented on a standard benchmark from the Cambridge Crystallographic Database of 480 drug-like small molecules, including full structure generation from SMILES strings. Reproduction of protein-bound crystallographic ligand poses is demonstrated on four carefully curated data sets: the ConfGen Set (667 ligands), the PINC cross-docking benchmark (1062 ligands), a large set of macrocyclic ligands (182 total with typical ring sizes of 12-23 atoms), and a commonly used benchmark for evaluating macrocycle conformer generation (30 ligands total). Results compare favorably to alternative methods, and performance on macrocyclic compounds approaches that observed on non-macrocycles while yielding a roughly 100-fold speed improvement over alternative MD-based methods with comparable performance.

Bioresponsive Materials for Drug Delivery Based on Carboxymethyl Chitosan/Poly(γ-Glutamic Acid) Composite Microparticles

PubMed Central

Yan, Xiaoting; Tong, Zongrui; Chen, Yu; Mo, Yanghe; Feng, Huaiyu; Li, Peng; Qu, Xiaosai; Jin, Shaohua

2017-01-01

Carboxymethyl chitosan (CMCS) microparticles are a potential candidate for hemostatic wound dressing. However, its low swelling property limits its hemostatic performance. Poly(γ-glutamic acid) (PGA) is a natural polymer with excellent hydrophilicity. In the current study, a novel CMCS/PGA composite microparticles with a dual-network structure was prepared by the emulsification/internal gelation method. The structure and thermal stability of the composite were determined by Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS), and thermogravimetric analysis (TGA). The effects of preparation conditions on the swelling behavior of the composite were investigated. The results indicate that the swelling property of CMCS/PGA composite microparticles is pH sensitive. Levofloxacin (LFX) was immobilized in the composite microparticles as a model drug to evaluate the drug delivery performance of the composite. The release kinetics of LFX from the composite microparticles with different structures was determined. The results suggest that the CMCS/PGA composite microparticles are an excellent candidate carrier for drug delivery. PMID:28452963

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens

PubMed Central

Sosa, Ezequiel J; Burguener, Germán; Lanzarotti, Esteban; Radusky, Leandro; Pardo, Agustín M; Marti, Marcelo

2018-01-01

Abstract Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request. PMID:29106651

A Maltose-Binding Protein Fusion Construct Yields a Robust Crystallography Platform for MCL1

PubMed Central

Clifton, Matthew C.; Dranow, David M.; Leed, Alison; Fulroth, Ben; Fairman, James W.; Abendroth, Jan; Atkins, Kateri A.; Wallace, Ellen; Fan, Dazhong; Xu, Guoping; Ni, Z. J.; Daniels, Doug; Van Drie, John; Wei, Guo; Burgin, Alex B.; Golub, Todd R.; Hubbard, Brian K.; Serrano-Wu, Michael H.

2015-01-01

Crystallization of a maltose-binding protein MCL1 fusion has yielded a robust crystallography platform that generated the first apo MCL1 crystal structure, as well as five ligand-bound structures. The ability to obtain fragment-bound structures advances structure-based drug design efforts that, despite considerable effort, had previously been intractable by crystallography. In the ligand-independent crystal form we identify inhibitor binding modes not observed in earlier crystallographic systems. This MBP-MCL1 construct dramatically improves the structural understanding of well-validated MCL1 ligands, and will likely catalyze the structure-based optimization of high affinity MCL1 inhibitors. PMID:25909780

Computational neuropharmacology: dynamical approaches in drug discovery.

PubMed

Aradi, Ildiko; Erdi, Péter

2006-05-01

Computational approaches that adopt dynamical models are widely accepted in basic and clinical neuroscience research as indispensable tools with which to understand normal and pathological neuronal mechanisms. Although computer-aided techniques have been used in pharmaceutical research (e.g. in structure- and ligand-based drug design), the power of dynamical models has not yet been exploited in drug discovery. We suggest that dynamical system theory and computational neuroscience--integrated with well-established, conventional molecular and electrophysiological methods--offer a broad perspective in drug discovery and in the search for novel targets and strategies for the treatment of neurological and psychiatric diseases.

Distribution of Drug Molecules in Lipid Membranes: Neutron Diffraction and MD Simulations.

NASA Astrophysics Data System (ADS)

Boggara, Mohan; Mihailescu, Ella; Krishnamoorti, Ramanan

2009-03-01

Non-steroidal anti-inflammatory drugs (NSAIDs) e.g. Aspirin and Ibuprofen, with chronic usage cause gastro intestinal (GI) toxicity. It has been shown experimentally that NSAIDs pre-associated with phospholipids reduce the GI toxicity and also increase the therapeutic activity of these drugs compared to the unmodified ones. In this study, using neutron diffraction, the DOPC lipid bilayer structure (with and without drug) as well as the distribution of a model NSAID (Ibuprofen) as a function of its position along the membrane normal was obtained at sub-nanometer resolution. It was found that the bilayer thickness reduces as the drug is added. Further, the results are successfully compared with atomistic Molecular Dynamics simulations. Based on this successful comparison and motivated by atomic details from MD, quasi-molecular modeling of the lipid membrane is being carried out and will be presented. The above study is expected to provide an effective methodology to design drug delivery nanoparticles based on a variety of soft condensed matter such as lipids or polymers.

Nanostructured ultra-thin patches for ultrasound-modulated delivery of anti-restenotic drug

PubMed Central

Vannozzi, Lorenzo; Ricotti, Leonardo; Filippeschi, Carlo; Sartini, Stefania; Coviello, Vito; Piazza, Vincenzo; Pingue, Pasqualantonio; La Motta, Concettina; Dario, Paolo; Menciassi, Arianna

2016-01-01

This work aims to demonstrate the possibility to fabricate ultra-thin polymeric films loaded with an anti-restenotic drug and capable of tunable drug release kinetics for the local treatment of restenosis. Vascular nanopatches are composed of a poly(lactic acid) supporting membrane (thickness: ~250 nm) on which 20 polyelectrolyte bilayers (overall thickness: ~70 nm) are alternatively deposited. The anti-restenotic drug is embedded in the middle of the polyelectrolyte structure, and released by diffusion mechanisms. Nanofilm fabrication procedure and detailed morphological characterization are reported here. Barium titanate nanoparticles (showing piezoelectric properties) are included in the polymeric support and their role is investigated in terms of influence on nanofilm morphology, drug release kinetics, and cell response. Results show an efficient drug release from the polyelectrolyte structure in phosphate-buffered saline, and a clear antiproliferative effect on human smooth muscle cells, which are responsible for restenosis. In addition, preliminary evidences of ultrasound-mediated modulation of drug release kinetics are reported, thus evaluating the influence of barium titanate nanoparticles on the release mechanism. Such data were integrated with quantitative piezoelectric and thermal measurements. These results open new avenues for a fine control of local therapies based on smart responsive materials. PMID:26730191

Organometallic compounds in the discovery of new agents against kinetoplastid-caused diseases.

PubMed

Ravera, Mauro; Moreno-Viguri, Elsa; Paucar, Rocio; Pérez-Silanes, Silvia; Gabano, Elisabetta

2018-06-01

The development of safe and affordable antiparasitic agents effective against neglected tropical diseases is a big challenge of the drug discovery. The drugs currently employed have limitations such as poor efficacy, drug resistance or side effects. Thus, the search for new promising drugs is more and more crucial. Metal complexes and, in particular, organometallic compounds may expand the list of the drug candidates due to the peculiar attributes that the presence of the metal core add to the organic fragment (e.g., redox and structural features, ability to interact with DNA or protein targets, etc.). To date, most organometallic compounds tested as anti-neglected tropical diseases are based on similarities or activity of the organic ligands against other diseases or parasites and/or consist in modification of existing drugs combining the features of the metal moiety and the organic ligands. This review focuses on recent studies (2012-2017) on organometallic compounds in treating kinetoplastid-caused diseases such as Human African trypanosomiasis, Chagas disease and leishmaniasis. This field of research, however, still lacks exhaustive studies to identify of parasitic targets and quantitative structure-activity relationships for a rational drug design. Copyright © 2018. Published by Elsevier Masson SAS.

Structural interaction fingerprints: a new approach to organizing, mining, analyzing, and designing protein-small molecule complexes.

PubMed

Singh, Juswinder; Deng, Zhan; Narale, Gaurav; Chuaqui, Claudio

2006-01-01

The combination of advances in structure-based drug design efforts in the pharmaceutical industry in parallel with structural genomics initiatives in the public domain has led to an explosion in the number of structures of protein-small molecule complexes structures. This information has critical importance to both the understanding of the structural basis for molecular recognition in biological systems and the design of better drugs. A significant challenge exists in managing this vast amount of data and fully leveraging it. Here, we review our work to develop a simple, fast way to store, organize, mine, and analyze large numbers of protein-small molecule complexes. We illustrate the utility of the approach to the management of inhibitor complexes from the protein kinase family. Finally, we describe our recent efforts in applying this method to the design of target-focused chemical libraries.

ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.

PubMed

González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Orbegozo-Medina, Ricardo Alfredo; Pazos, Alejandro

2014-03-24

This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The new model is able to predict complex networks of AIDS prevalence in the US counties, taking into consideration the social determinants and activity/structure of anti-HIV drugs in preclinical assays. We trained different Artificial Neural Networks (ANNs) using as input information indices of social networks and molecular graphs. We used a Shannon information index based on the Gini coefficient to quantify the effect of income inequality in the social network. We obtained the data on AIDS prevalence and the Gini coefficient from the AIDSVu database of Emory University. We also used the Balaban information indices to quantify changes in the chemical structure of anti-HIV drugs. We obtained the data on anti-HIV drug activity and structure (SMILE codes) from the ChEMBL database. Last, we used Box-Jenkins moving average operators to quantify information about the deviations of drugs with respect to data subsets of reference (targets, organisms, experimental parameters, protocols). The best model found was a Linear Neural Network (LNN) with values of Accuracy, Specificity, and Sensitivity above 0.76 and AUROC > 0.80 in training and external validation series. This model generates a complex network of AIDS prevalence in the US at county level with respect to the preclinical activity of anti-HIV drugs in preclinical assays. To train/validate the model and predict the complex network we needed to analyze 43,249 data points including values of AIDS prevalence in 2,310 counties in the US vs ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4,856 protocols, and 10 possible experimental measures.

Novel nanocarriers for topical drug delivery: investigating delivery efficiency and distribution in skin using two-photon microscopy

NASA Astrophysics Data System (ADS)

Kirejev, Vladimir; Guldbrand, Stina; Bauer, Brigitte; Smedh, Maria; Ericson, Marica B.

2011-03-01

The complex structure of skin represents an effective barrier against external environmental factors, as for example, different chemical and biochemical compounds, yeast, bacterial and viral infections. However, this impermeability prevents efficient transdermal drug delivery which limits the number of drugs that are able to penetrate the skin efficiently. Current trends in drug application through skin focus on the design and use of nanocarriers for transport of active compounds. The transport systems applied so far have several drawbacks, as they often have low payload, high toxicity, a limited variability of inclusion molecules, or long degradation times. The aim of these current studies is to investigate novel topical drug delivery systems, e.g. nanocarriers based on cyclic oligosaccharides - cyclodextrins (CD) or iron (III)-based metal-organic frameworks (MOF). Earlier studies on cell cultures imply that these drug nanocarriers show promising characteristics compared to other drug delivery systems. In our studies, we use two-photon microscopy to investigate the ability of the nanocarriers to deliver compounds through ex-vivo skin samples. Using near infrared light for excitation in the so called optical window of skin allows deep-tissue visualization of drug distribution and localization. In addition, it is possible to employ two-photon based fluorescence correlation spectroscopy for quantitative analysis of drug distribution and concentrations in different cell layers.

In Silico Chemogenomics Drug Repositioning Strategies for Neglected Tropical Diseases.

PubMed

Andrade, Carolina Horta; Neves, Bruno Junior; Melo-Filho, Cleber Camilo; Rodrigues, Juliana; Silva, Diego Cabral; Braga, Rodolpho Campos; Cravo, Pedro Vitor Lemos

2018-03-08

Only ~1% of all drug candidates against Neglected Tropical Diseases (NTDs) have reached clinical trials in the last decades, underscoring the need for new, safe and effective treatments. In such context, drug repositioning, which allows finding novel indications for approved drugs whose pharmacokinetic and safety profiles are already known, is emerging as a promising strategy for tackling NTDs. Chemogenomics is a direct descendent of the typical drug discovery process that involves the systematic screening of chemical compounds against drug targets in high-throughput screening (HTS) efforts, for the identification of lead compounds. However, different to the one-drug-one-target paradigm, chemogenomics attempts to identify all potential ligands for all possible targets and diseases. In this review, we summarize current methodological development efforts in drug repositioning that use state-of-the-art computational ligand- and structure-based chemogenomics approaches. Furthermore, we highlighted the recent progress in computational drug repositioning for some NTDs, based on curation and modeling of genomic, biological, and chemical data. Additionally, we also present in-house and other successful examples and suggest possible solutions to existing pitfalls. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Albumin nanostructures as advanced drug delivery systems

PubMed Central

Karimi, Mahdi; Bahrami, Sajad; Ravari, Soodeh Baghaee; Zangabad, Parham Sahandi; Mirshekari, Hamed; Bozorgomid, Mahnaz; Shahreza, Somayeh; Sori, Masume; Hamblin, Michael R.

2016-01-01

Introduction One of the biggest impacts that the nanotechnology has made on medicine and biology, has been in the area of drug delivery systems (DDSs). Many drugs suffer from serious problems concerning insolubility, instability in biological environments, poor uptake into cells and tissues, suboptimal selectivity for targets and unwanted side effects. Nanocarriers can be designed as DDSs to overcome many of these drawbacks. One of the most versatile building blocks to prepare these nanocarriers is the ubiquitous, readily available and inexpensive protein, serum albumin. Areas covered This review covers the use of different types of albumin (human, bovine, rat, and chicken egg) to prepare nanoparticle and microparticle-based structures to bind drugs. Various methods have been used to modify the albumin structure. A range of targeting ligands can be attached to the albumin that can be recognized by specific cell receptors that are expressed on target cells or tissues. Expert opinion The particular advantages of albumin used in DDSs include ready availability, ease of chemical modification, good biocompatibility, and low immunogenicity. The regulatory approvals that have been received for several albumin-based therapeutic agents suggest that this approach will continue to be successfully explored. PMID:27216915

Exosomes as therapeutic drug carriers and delivery vehicles across biological membranes: current perspectives and future challenges.

PubMed

Ha, Dinh; Yang, Ningning; Nadithe, Venkatareddy

2016-07-01

Exosomes are small intracellular membrane-based vesicles with different compositions that are involved in several biological and pathological processes. The exploitation of exosomes as drug delivery vehicles offers important advantages compared to other nanoparticulate drug delivery systems such as liposomes and polymeric nanoparticles; exosomes are non-immunogenic in nature due to similar composition as body׳s own cells. In this article, the origin and structure of exosomes as well as their biological functions are outlined. We will then focus on specific applications of exosomes as drug delivery systems in pharmaceutical drug development. An overview of the advantages and challenges faced when using exosomes as a pharmaceutical drug delivery vehicles will also be discussed.

Fragment-based approaches to TB drugs.

PubMed

Marchetti, Chiara; Chan, Daniel S H; Coyne, Anthony G; Abell, Chris

2018-02-01

Tuberculosis is an infectious disease associated with significant mortality and morbidity worldwide, particularly in developing countries. The rise of antibiotic resistance in Mycobacterium tuberculosis (Mtb) urgently demands the development of new drug leads to tackle resistant strains. Fragment-based methods have recently emerged at the forefront of pharmaceutical development as a means to generate more effective lead structures, via the identification of fragment molecules that form weak but high quality interactions with the target biomolecule and subsequent fragment optimization. This review highlights a number of novel inhibitors of Mtb targets that have been developed through fragment-based approaches in recent years.

Exploring Polypharmacology Using a ROCS-Based Target Fishing Approach

DTIC Science & Technology

2012-01-01

target representatives. Target profiles were then generated for a given query molecule by computing maximal shape/ chemistry overlap between the query...molecule and the drug sets assigned to each protein target. The overlap was computed using the program ROCS (Rapid Overlay of Chemical Structures ). We...approaches in off-target prediction has been reviewed.9,10 Many structure -based target fishing (SBTF) approaches, such as INVDOCK11 and Target Fishing Dock

Impact of Chemical Structure on Conjunctival Drug Permeability: Adopting Porcine Conjunctiva and Cassette Dosing for Construction of In Silico Model.

PubMed

Ramsay, Eva; Ruponen, Marika; Picardat, Théo; Tengvall, Unni; Tuomainen, Marjo; Auriola, Seppo; Toropainen, Elisa; Urtti, Arto; Del Amo, Eva M

2017-09-01

Conjunctiva occupies most of the ocular surface area, and conjunctival permeability affects ocular and systemic drug absorption of topical ocular medications. Therefore, the aim of this study was to obtain a computational in silico model for structure-based prediction of conjunctival drug permeability. This was done by employing cassette dosing and quantitative structure-property relationship (QSPR) approach. Permeability studies were performed ex vivo across fresh porcine conjunctiva and simultaneous dosing of a cassette mixture composed of 32 clinically relevant drug molecules with wide chemical space. The apparent permeability values were obtained using drug concentrations that were quantified with liquid chromatography tandem-mass spectrometry. The experimental data were utilized for building a QSPR model for conjunctival permeability predictions. The conjunctival permeability values presented a 17-fold range (0.63-10.74 × 10 -6 cm/s). The final QSPR had a Q 2 value of 0.62 and predicted the external test set with a mean fold error of 1.34. The polar surface area, hydrogen bond donor, and halogen ratio were the most relevant descriptors for defining conjunctival permeability. This work presents for the first time a predictive QSPR model of conjunctival drug permeability and a comprehensive description on conjunctival isolation from the porcine eye. The model can be used for developing new ocular drugs. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Robust Structure and Reactivity of Aqueous Arsenous Acid-Platinum(II) Anticancer Complexes**

PubMed Central

Miodragović, Ðenana U.; Quentzel, Jeremy A.; Kurutz, Josh W.; Stern, Charlotte L.; Ahn, Richard W.; Kandela, Irawati; Mazar, Andrew; O’Halloran, Thomas V.

2014-01-01

The first molecular adducts of platinum and arsenic based anticancer drugs - arsenoplatins - show unanticipated structure, substitution chemistry, and cellular cytotoxicity. The PtII-AsIII bonds in these complexes are stable in aqueous solution and strongly influence the lability of the trans ligand. PMID:24038962

Metabolic cancer biology: structural-based analysis of cancer as a metabolic disease, new sights and opportunities for disease treatment.

PubMed

Masoudi-Nejad, Ali; Asgari, Yazdan

2015-02-01

The cancer cell metabolism or the Warburg effect discovery goes back to 1924 when, for the first time Otto Warburg observed, in contrast to the normal cells, cancer cells have different metabolism. With the initiation of high throughput technologies and computational systems biology, cancer cell metabolism renaissances and many attempts were performed to revise the Warburg effect. The development of experimental and analytical tools which generate high-throughput biological data including lots of information could lead to application of computational models in biological discovery and clinical medicine especially for cancer. Due to the recent availability of tissue-specific reconstructed models, new opportunities in studying metabolic alteration in various kinds of cancers open up. Structural approaches at genome-scale levels seem to be suitable for developing diagnostic and prognostic molecular signatures, as well as in identifying new drug targets. In this review, we have considered these recent advances in structural-based analysis of cancer as a metabolic disease view. Two different structural approaches have been described here: topological and constraint-based methods. The ultimate goal of this type of systems analysis is not only the discovery of novel drug targets but also the development of new systems-based therapy strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Implementing drug abuse treatment services in criminal justice settings: Introduction to the CJ-DATS study protocol series.

PubMed

Ducharme, Lori J; Chandler, Redonna K; Wiley, Tisha R A

2013-12-01

Despite a growing pipeline of effective clinical treatments, there remains a persistent research-to-practice gap in drug abuse services. Delivery of effective treatment services is especially lacking in the U.S. criminal justice system, where half of all incarcerated persons meet the need for drug abuse or dependence, yet few receive needed care. Structural, financial, philosophical and other barriers slow the pace of adoption of available evidence-based practices. These challenges led to the development of a multi-site cooperative research endeavor known as the Criminal Justice Drug Abuse Treatment Studies (CJ-DATS), funded by the National Institute on Drug Abuse (NIDA). CJ-DATS engages university-based research teams, criminal justice agencies, and community-based treatment providers in implementation research studies to test strategies for enhancing treatment service delivery to offender populations. This Introduction reviews the mission of NIDA, the structure and goals of the CJ-DATS cooperative, and the implementation studies being conducted by the participating organizations. The component Study Protocols in this article collection are then described. CJ-DATS applies implementation science perspectives and methods to address a vexing problem - the need to link offender populations with effective treatment for drug abuse, HIV, and other related conditions for which they are at high risk. Applying these principles to the U.S. criminal justice system is an innovative extension of lessons that have been learned in mainstream healthcare settings. This collection is offered as both an introduction to NIDA's work in this area, as well as a window onto the challenges of conducting health services research in settings in which improving public health is not the organization's core mission.

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

PubMed Central

Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

2016-01-01

A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

PubMed

Randhawa, Vinay; Kumar Singh, Anil; Acharya, Vishal

2015-12-01

Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize the effectiveness of such pipelines, we first analyzed the dysregulated gene pairs between control and tumor samples and then implemented an ensemble-based feature selection approach to prioritize targets in oral squamous cell carcinoma (OSCC) for therapeutic exploration. Based on the structural information of known inhibitors of CXCR4-one of the best targets identified in this study-a feature selection was implemented for the identification of optimal structural features (molecular descriptor) based on which a classification model was generated. Furthermore, the CXCR4-centered descriptor-based classification model was finally utilized to screen a repository of plant derived small-molecules to obtain potential inhibitors. The application of our methodology may assist effective selection of the best targets which may have previously been overlooked, that in turn will lead to the development of new oral cancer medications. The small molecules identified in this study can be ideal candidates for trials as potential novel anti-oral cancer agents. Importantly, distinct steps of this whole study may provide reference for the analysis of other complex human diseases.

MSN anti-cancer nanomedicines: chemotherapy enhancement, overcoming of drug resistance, and metastasis inhibition.

PubMed

He, Qianjun; Shi, Jianlin

2014-01-22

In the anti-cancer war, there are three main obstacles resulting in high mortality and recurrence rate of cancers: the severe toxic side effect of anti-cancer drugs to normal tissues due to the lack of tumor-selectivity, the multi-drug resistance (MDR) to free chemotherapeutic drugs and the deadly metastases of cancer cells. The development of state-of-art nanomedicines based on mesoporous silica nanoparticles (MSNs) is expected to overcome the above three main obstacles. In the view of the fast development of anti-cancer strategy, this review highlights the most recent advances of MSN anti-cancer nanomedicines in enhancing chemotherapeutic efficacy, overcoming the MDR and inhibiting metastasis. Furthermore, we give an outlook of the future development of MSNs-based anti-cancer nanomedicines, and propose several innovative and forward-looking anti-cancer strategies, including tumor tissue-cell-nuclear successionally targeted drug delivery strategy, tumor cell-selective nuclear-targeted drug delivery strategy, multi-targeting and multi-drug strategy, chemo-/radio-/photodynamic-/ultrasound-/thermo-combined multi-modal therapy by virtue of functionalized hollow/rattle-structured MSNs. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Drug delivery with topically applied nanoparticles: science fiction or reality.

PubMed

Lademann, J; Richter, H; Meinke, M C; Lange-Asschenfeldt, B; Antoniou, C; Mak, W C; Renneberg, R; Sterry, W; Patzelt, A

2013-01-01

The efficacy of topically applied drugs is determined by their action mechanism and their potential capacity of passing the skin barrier. Nanoparticles are assumed to be efficient carrier systems for drug delivery through the skin barrier. For flexible nanoparticles like liposomes, this effect has been well demonstrated. The penetration properties of solid nanoparticles are currently under intensive investigation. The crucial advantage of nanoparticles over non-particulate substances is their capability to penetrate deeply into the hair follicles where they can be stored for several days. There is no evidence, yet, that solid particles ≥40 nm are capable of passing through the healthy skin barrier. Therefore and in spite of the long-standing research efforts in this field, commercially available solid nanoparticle-based products for drug delivery through the healthy skin are still missing. Nevertheless, the prospects for the clinical use of nanoparticles in drug delivery are tremendous. They can be designed as transport systems delivering drugs efficiently into the hair follicles in the vicinity of specific target structures. Once deposited at these structures, specific signals might trigger the release of the drugs and exert their effects on the target cells. In this article, examples of such triggered drug release are presented. © 2013 S. Karger AG, Basel.

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

DOE PAGES

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

2017-05-02

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

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

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

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

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

Strategy for Identifying Repurposed Drugs for the Treatment of Cerebral Cavernous Malformation

PubMed Central

Gibson, Christopher C.; Zhu, Weiquan; Davis, Chadwick T.; Bowman-Kirigin, Jay A.; Chan, Aubrey C.; Ling, Jing; Walker, Ashley E.; Goitre, Luca; Monache, Simona Delle; Retta, Saverio Francesco; Shiu, Yan-Ting E.; Grossmann, Allie H.; Thomas, Kirk R.; Donato, Anthony J.; Lesniewski, Lisa A.; Whitehead, Kevin J.; Li, Dean Y.

2014-01-01

Background Cerebral cavernous malformation (CCM) is a hemorrhagic stroke disease affecting up to 0.5% of North Americans with no approved non-surgical treatment. A subset of patients have a hereditary form of the disease due primarily to loss-of-function mutations in KRIT1, CCM2, or PDCD10. We sought to identify known drugs that could be repurposed to treat CCM. Methods and Results We developed an unbiased screening platform based on both cellular and animal models of loss-of-function of CCM2. Our discovery strategy consisted of four steps: an automated immunofluorescence and machine-learning-based primary screen of structural phenotypes in human endothelial cells deficient in CCM2; a secondary screen of functional changes in endothelial stability in these same cells; a rapid in vivo tertiary screen of dermal microvascular leak in mice lacking endothelial Ccm2; and finally a quaternary screen of CCM lesion burden in these same mice. We screened 2,100 known drugs and bioactive compounds, and identified two candidates for further study, cholecalciferol (Vitamin D3) and tempol (a scavenger of superoxide). Each drug decreased lesion burden in a mouse model of CCM vascular disease by approximately 50%. Conclusions By identifying known drugs as potential therapeutics for CCM, we have decreased the time, cost, and risk of bringing treatments to patients. Each drug also prompts additional exploration of biomarkers of CCM disease. We further suggest that the structure-function screening platform presented here may be adapted and scaled to facilitate drug discovery for diverse loss-of-function genetic vascular disease. PMID:25486933

A mRNA-Responsive G-Quadruplex-Based Drug Release System

PubMed Central

Yaku, Hidenobu; Murashima, Takashi; Miyoshi, Daisuke; Sugimoto, Naoki

2015-01-01

G-quadruplex-based drug delivery carriers (GDDCs) were designed to capture and release a telomerase inhibitor in response to a target mRNA. Hybridization between a loop on the GDDC structure and the mRNA should cause the G-quadruplex structure of the GDDC to unfold and release the bound inhibitor, anionic copper(II) phthalocyanine (CuAPC). As a proof of concept, GDDCs were designed with a 10-30-mer loop, which can hybridize with a target sequence in epidermal growth factor receptor (EGFR) mRNA. Structural analysis using circular dichroism (CD) spectroscopy showed that the GDDCs form a (3 + 1) type G-quadruplex structure in 100 mM KCl and 10 mM MgCl2 in the absence of the target RNA. Visible absorbance titration experiments showed that the GDDCs bind to CuAPC with Ka values of 1.5 × 105 to 5.9 × 105 M−1 (Kd values of 6.7 to 1.7 μM) at 25 °C, depending on the loop length. Fluorescence titration further showed that the G-quadruplex structure unfolds upon binding to the target RNA with Ka values above 1.0 × 108 M−1 (Kd values below 0.01 μM) at 25 °C. These results suggest the carrier can sense and bind to the target RNA, which should result in release of the bound drug. Finally, visible absorbance titration experiments demonstrated that the GDDC release CuAPC in response to the target RNA. PMID:25905703

Controlling silk fibroin particle features for drug delivery

PubMed Central

Lammel, Andreas; Hu, Xiao; Park, Sang-Hyug; Kaplan, David L.; Scheibel, Thomas

2010-01-01

Silk proteins are a promising material for drug delivery due to their aqueous processability, biocompatibility, and biodegradability. A simple aqueous preparation method for silk fibroin particles with controllable size, secondary structure and zeta potential is reported. The particles were produced by salting out a silk fibroin solution with potassium phosphate. The effect of ionic strength and pH of potassium phosphate solution on the yield and morphology of the particles was determined. Secondary structure and zeta potential of the silk particles could be controlled by pH. Particles produced by salting out with 1.25 M potassium phosphate pH 6 showed a dominating silk II (crystalline) structure whereas particles produced at pH 9 were mainly composed of silk I (less crystalline). The results show that silk I rich particles possess chemical and physical stability and secondary structure which remained unchanged during post treatments even upon exposure to 100% ethanol or methanol. A model is presented to explain the process of particle formation based on intra- and intermolecular interactions of the silk domains, influenced by pH and kosmotrope salts. The reported silk fibroin particles can be loaded with small molecule model drugs, such as alcian blue, rhodamine B, and crystal violet, by simple absorption based on electrostatic interactions. In vitro release of these compounds from the silk particles depends on charge – charge interactions between the compounds and the silk. With crystal violet we demonstrated that the release kinetics are dependent on the secondary structure of the particles. PMID:20219241

Methamphetamine-induced increases in putamen gray matter associate with inhibitory control.

PubMed

Groman, Stephanie M; Morales, Angelica M; Lee, Buyean; London, Edythe D; Jentsch, James David

2013-10-01

Problematic drug use is associated with difficulty in exerting self-control over behaviors, and this difficulty may be a consequence of atypical morphometric characteristics that are exhibited by drug-experienced individuals. The extent to which these structural abnormalities result from drug use or reflect neurobiological risk factors that predate drug use, however, is unknown. The purpose of this study is to determine how methamphetamine affects corticostriatal structure and how drug-induced changes relate to alterations in inhibitory control. Structural magnetic resonance images and positron emission tomography (PET) scans, assessing dopamine D₂-like receptor and transporter availability, were acquired in monkeys trained to acquire, retain, and reverse three-choice visual discrimination problems before and after exposure to an escalating dose regimen of methamphetamine (or saline, as a control). Voxel-based morphometry was used to compare changes in corticostriatal gray matter between methamphetamine- and saline-exposed monkeys. The change in gray matter before and after the dosing regimen was compared to the change in the behavioral performance and in dopaminergic markers measured with PET. Methamphetamine exposure, compared to saline, increased gray matter within the right putamen. These changes were positively correlated with changes in performance of methamphetamine-exposed monkeys in the reversal phase, and were negatively correlated with alterations in D₂-like receptor and DAT availability. The results provide the first evidence that exposure to a methamphetamine dosing regimen that resembles human use alters the structural integrity of the striatum and that gray-matter abnormalities detected in human methamphetamine users are due, at least in part, to the pharmacological effects of drug experience.

Methamphetamine-induced increases in putamen gray matter associate with inhibitory control

PubMed Central

Groman, Stephanie M.; Morales, Angelica M.; Lee, Buyean; London, Edythe D.; Jentsch, James David

2013-01-01

Rationale Problematic drug use is associated with difficulty in exerting self-control over behaviors, and this difficulty may be a consequence of atypical morphometric characteristics that are exhibited by drug-experienced individuals. The extent to which these structural abnormalities result from drug use or reflect neurobiological-risk factors that predate drug use, however, is unknown. Objectives To determine how methamphetamine affects corticostriatal structure and how drug-induced changes relate to alterations in inhibitory control. Methods Structural magnetic resonance images and positron emission tomography (PET) scans, assessing dopamine D2-like receptor and transporter availability, were acquired in monkeys trained to acquire, retain and reverse three-choice visual discrimination problems before and after exposure to an escalating dose regimen of methamphetamine (or saline, as a control). Voxel-based morphometry was used to compare changes in corticostriatal gray matter between methamphetamine and saline exposed monkeys. The change in gray matter before and after the dosing regimen was compared to the change in the behavioral performance and in dopaminergic markers measured with PET. Results Methamphetamine exposure, compared to saline, increased gray matter within the right putamen. These changes were positively correlated with changes in performance of methamphetamine-exposed monkeys in the reversal phase, and were negatively correlated with alterations in D2-like receptor and DAT availability. Conclusions The results provide the first evidence that exposure to a methamphetamine dosing regimen that resembles human use alters the structural integrity of the striatum and that gray-matter abnormalities detected in human methamphetamine users are due, at least in part, to the pharmacological effects of drug experience. PMID:23748383

Cooperativity effect involving drug-DNA/RNA intermolecular interaction: A B3LYP-D3 and MP2 theoretical investigation on ketoprofen⋯cytosine⋯H2O system.

PubMed

Zhen, Jun-Ping; Wei, Xiao-Chun; Shi, Wen-Jing; Huang, Zhu-Yuan; Jin, Bo; Zhou, Yu-Kun

2017-11-14

In order to examine the origin of the drug action and design new DNA/RNA-targeted drugs, the cooperativity effect involving drug-DNA/RNA intermolecular interaction in ketoprofen⋯cytosine⋯H 2 O ternary system were investigated by the B3LYP, B3LYP-D3, and MP2 methods with the 6-311++G(2d,p) basis set. The thermodynamic cooperativity was also evaluated at 310.15 K. The N-H⋯O, O-H⋯O, O-H⋯N, C-H⋯N, and C-H⋯O H bonds coexist in ternary complexes. The intermolecular interactions obtained by B3LYP-D3 are close to those calculated by MP2. The steric effects and van der Waals interactions have little influence on the cooperativity effects. The anti-cooperativity effect in ket⋯cyt⋯H 2 O is far more notable than the cooperativity effect, and the stability of the cyclic structure with anti-cooperativity effect is higher than that of the linear structure with cooperativity effect, as is confirmed by the AIM (atoms in molecules) and RDG (reduced density gradient) analysis. Thus, it can be inferred that, in the presence of H 2 O, the anti-cooperativity effect plays a dominant role in the drug-DNA/RNA interaction, and the nature of the hydration in the binding of drugs to DNA/RNA bases is the H-bonding anti-cooperativity effect. Furthermore, the drug always links simultaneously with DNA/RNA base and H 2 O, and only in this way can the biological activity of drugs play a role. In most cases, the enthalpy change is the major factor driving the cooperativity, as is different from most of biomacromolecule complexes.

Predicting drug-target interactions by dual-network integrated logistic matrix factorization

NASA Astrophysics Data System (ADS)

Hao, Ming; Bryant, Stephen H.; Wang, Yanli

2017-01-01

In this work, we propose a dual-network integrated logistic matrix factorization (DNILMF) algorithm to predict potential drug-target interactions (DTI). The prediction procedure consists of four steps: (1) inferring new drug/target profiles and constructing profile kernel matrix; (2) diffusing drug profile kernel matrix with drug structure kernel matrix; (3) diffusing target profile kernel matrix with target sequence kernel matrix; and (4) building DNILMF model and smoothing new drug/target predictions based on their neighbors. We compare our algorithm with the state-of-the-art method based on the benchmark dataset. Results indicate that the DNILMF algorithm outperforms the previously reported approaches in terms of AUPR (area under precision-recall curve) and AUC (area under curve of receiver operating characteristic) based on the 5 trials of 10-fold cross-validation. We conclude that the performance improvement depends on not only the proposed objective function, but also the used nonlinear diffusion technique which is important but under studied in the DTI prediction field. In addition, we also compile a new DTI dataset for increasing the diversity of currently available benchmark datasets. The top prediction results for the new dataset are confirmed by experimental studies or supported by other computational research.

A linguistic rule-based approach to extract drug-drug interactions from pharmacological documents.

PubMed

Segura-Bedmar, Isabel; Martínez, Paloma; de Pablo-Sánchez, César

2011-03-29

A drug-drug interaction (DDI) occurs when one drug influences the level or activity of another drug. The increasing volume of the scientific literature overwhelms health care professionals trying to be kept up-to-date with all published studies on DDI. This paper describes a hybrid linguistic approach to DDI extraction that combines shallow parsing and syntactic simplification with pattern matching. Appositions and coordinate structures are interpreted based on shallow syntactic parsing provided by the UMLS MetaMap tool (MMTx). Subsequently, complex and compound sentences are broken down into clauses from which simple sentences are generated by a set of simplification rules. A pharmacist defined a set of domain-specific lexical patterns to capture the most common expressions of DDI in texts. These lexical patterns are matched with the generated sentences in order to extract DDIs. We have performed different experiments to analyze the performance of the different processes. The lexical patterns achieve a reasonable precision (67.30%), but very low recall (14.07%). The inclusion of appositions and coordinate structures helps to improve the recall (25.70%), however, precision is lower (48.69%). The detection of clauses does not improve the performance. Information Extraction (IE) techniques can provide an interesting way of reducing the time spent by health care professionals on reviewing the literature. Nevertheless, no approach has been carried out to extract DDI from texts. To the best of our knowledge, this work proposes the first integral solution for the automatic extraction of DDI from biomedical texts.

Nanobiotechnology-based strategies for crossing the blood-brain barrier.

PubMed

Jain, Kewal K

2012-08-01

The blood-brain barrier (BBB) is meant to protect the brain from noxious agents; however, it also significantly hinders the delivery of therapeutics to the brain. Several strategies have been employed to deliver drugs across this barrier and some of these may do structural damage to the BBB by forcibly opening it to allow the uncontrolled passage of drugs. The ideal method for transporting drugs across the BBB should be controlled and should not damage the barrier. Among the various approaches that are available, nanobiotechnology-based delivery methods provide the best prospects for achieving this ideal. This review describes various nanoparticle (NP)-based methods used for drug delivery to the brain and the known underlying mechanisms. Some strategies require multifunctional NPs combining controlled passage across the BBB with targeted delivery of the therapeutic cargo to the intended site of action in the brain. An important application of nanobiotechnology is to facilitate the delivery of drugs and biological therapeutics for brain tumors across the BBB. Although there are currently some limitations and concerns for the potential neurotoxicity of NPs, the future prospects for NP-based therapeutic delivery to the brain are excellent.

Co-delivery of ibuprofen and gentamicin from nanoporous anodic titanium dioxide layers.

PubMed

Pawlik, Anna; Jarosz, Magdalena; Syrek, Karolina; Sulka, Grzegorz D

2017-04-01

Although single-drug therapy may prove insufficient in treating bacterial infections or inflammation after orthopaedic surgeries, complex therapy (using both an antibiotic and an anti-inflammatory drug) is thought to address the problem. Among drug delivery systems (DDSs) with prolonged drug release profiles, nanoporous anodic titanium dioxide (ATO) layers on Ti foil are very promising. In the discussed research, ATO samples were synthesized via a three-step anodization process in an ethylene glycol-based electrolyte with fluoride ions. The third step lasted 2, 5 and 10min in order to obtain different thicknesses of nanoporous layers. Annealing the as-prepared amorphous layers at the temperature of 400°C led to obtaining the anatase phase. In this study, water-insoluble ibuprofen and water-soluble gentamicin were used as model drugs. Three different drug loading procedures were applied. The desorption-desorption-diffusion (DDD) model of the drug release was fitted to the experimental data. The effects of crystalline structure, depth of TiO 2 nanopores and loading procedure on the drug release profiles were examined. The duration of the drug release process can be easily altered by changing the drug loading sequence. Water-soluble gentamicin is released for a long period of time if gentamicin is loaded in ATO as the first drug. Additionally, deeper nanopores and anatase phase suppress the initial burst release of drugs. These results confirm that factors such as morphological and crystalline structure of ATO layers, and the procedure of drug loading inside nanopores, allow to alter the drug release performance of nanoporous ATO layers. Copyright © 2017 Elsevier B.V. All rights reserved.

Anti-Cancer Drug Delivery Using Carbohydrate-Based Polymers.

PubMed

Ranjbari, Javad; Mokhtarzadeh, Ahad; Alibakhshi, Abbas; Tabarzad, Maryam; Hejazi, Maryam; Ramezani, Mohammad

2018-02-12

Polymeric drug delivery systems in the form of nanocarriers are the most interesting vehicles in anticancer therapy. Among different types of biocompatible polymers, carbohydrate-based polymers or polysaccharides are the most common natural polymers with complex structures consisting of long chains of monosaccharide or disaccharide units bound by glycosidic linkages. Their appealing properties such as availability, biocompatibility, biodegradability, low toxicity, high chemical reactivity, facile chemical modification and low cost led to their extensive applications in biomedical and pharmaceutical fields including development of nano-vehicles for delivery of anti-cancer therapeutic agents. Generally, reducing systemic toxicity, increasing short half-lives and tumor localization of agents are the top priorities for a successful cancer therapy. Polysaccharide-based or - coated nanosystems with respect to their advantageous features as well as accumulation in tumor tissue due to enhanced permeation and retention (EPR) effect can provide promising carrier systems for the delivery of noblest impressive agents. Most challenging factor in cancer therapy was the toxicity of anti-cancer therapeutic agents for normal cells and therefore, targeted delivery of these drugs to the site of action can be considered as an interesting therapeutic strategy. In this regard, several polysaccharides exhibited selective affinity for specific cell types, and so they can act as a targeting agent in drug delivery systems. Accordingly, different aspects of polysaccharide applications in cancer treatment or diagnosis were reviewed in this paper. In this regard, after a brief introduction of polysaccharide structure and its importance, the pharmaceutical usage of carbohydrate-based polymers was considered according to the identity of accompanying active pharmaceutical agents. It was also presented that the carbohydrate based polymers have been extensively considered as promising materials in the design of efficient nanocarriers for anti-cancer biopharmaceuticals including peptide and proteins or nucleic acid-based therapeutics. Then, the importance of various polysaccharide co-polymers in the drug delivery approaches was illustrated. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Preparation and drug release behavior of temperature-responsive mesoporous carbons

NASA Astrophysics Data System (ADS)

Wang, Xiufang; Liu, Ping; Tian, Yong

2011-06-01

A temperature-responsive composite based on poly (N-isopropylacrylamide) (PNIPAAm) and ordered mesoporous carbons (OMCs) has been successfully prepared by a simple wetness impregnation technique. The structures and properties of the composite were characterized by infrared spectroscopy (IR), X-ray diffraction (XRD), transmission electron microscopy (TEM), N 2 sorption, thermogravimetric analysis (TG) and differential scanning calorimetry (DSC). The results showed that the inclusion of PNIPAAm had not greatly changed the basic ordered pore structure of the OMCs. Ibuprofen (IBU) was selected as model drug, and in vitro test of IBU release exhibited a temperature-responsive controlled release delivery.

Structural analyses of Candida albicans sterol 14α-demethylase complexed with azole drugs address the molecular basis of azole-mediated inhibition of fungal sterol biosynthesis

PubMed Central

Hargrove, Tatiana Y.; Friggeri, Laura; Wawrzak, Zdzislaw; Qi, Aidong; Hoekstra, William J.; Schotzinger, Robert J.; York, John D.; Guengerich, F. Peter; Lepesheva, Galina I.

2017-01-01

With some advances in modern medicine (such as cancer chemotherapy, broad exposure to antibiotics, and immunosuppression), the incidence of opportunistic fungal pathogens such as Candida albicans has increased. Cases of drug resistance among these pathogens have become more frequent, requiring the development of new drugs and a better understanding of the targeted enzymes. Sterol 14α-demethylase (CYP51) is a cytochrome P450 enzyme required for biosynthesis of sterols in eukaryotic cells and is the major target of clinical drugs for managing fungal pathogens, but some of the CYP51 key features important for rational drug design have remained obscure. We report the catalytic properties, ligand-binding profiles, and inhibition of enzymatic activity of C. albicans CYP51 by clinical antifungal drugs that are used systemically (fluconazole, voriconazole, ketoconazole, itraconazole, and posaconazole) and topically (miconazole and clotrimazole) and by a tetrazole-based drug candidate, VT-1161 (oteseconazole: (R)-2-(2,4-difluorophenyl)-1,1-difluoro-3-(1H-tetrazol-1-yl)-1-(5-(4-(2,2,2-trifluoroethoxy)phenyl)pyridin-2-yl)propan-2-ol). Among the compounds tested, the first-line drug fluconazole was the weakest inhibitor, whereas posaconazole and VT-1161 were the strongest CYP51 inhibitors. We determined the X-ray structures of C. albicans CYP51 complexes with posaconazole and VT-1161, providing a molecular mechanism for the potencies of these drugs, including the activity of VT-1161 against Candida krusei and Candida glabrata, pathogens that are intrinsically resistant to fluconazole. Our comparative structural analysis outlines phylum-specific CYP51 features that could direct future rational development of more efficient broad-spectrum antifungals. PMID:28258218

Structural analyses of Candida albicans sterol 14α-demethylase complexed with azole drugs address the molecular basis of azole-mediated inhibition of fungal sterol biosynthesis.

PubMed

Hargrove, Tatiana Y; Friggeri, Laura; Wawrzak, Zdzislaw; Qi, Aidong; Hoekstra, William J; Schotzinger, Robert J; York, John D; Guengerich, F Peter; Lepesheva, Galina I

2017-04-21

With some advances in modern medicine (such as cancer chemotherapy, broad exposure to antibiotics, and immunosuppression), the incidence of opportunistic fungal pathogens such as Candida albicans has increased. Cases of drug resistance among these pathogens have become more frequent, requiring the development of new drugs and a better understanding of the targeted enzymes. Sterol 14α-demethylase (CYP51) is a cytochrome P450 enzyme required for biosynthesis of sterols in eukaryotic cells and is the major target of clinical drugs for managing fungal pathogens, but some of the CYP51 key features important for rational drug design have remained obscure. We report the catalytic properties, ligand-binding profiles, and inhibition of enzymatic activity of C. albicans CYP51 by clinical antifungal drugs that are used systemically (fluconazole, voriconazole, ketoconazole, itraconazole, and posaconazole) and topically (miconazole and clotrimazole) and by a tetrazole-based drug candidate, VT-1161 (oteseconazole: ( R )-2-(2,4-difluorophenyl)-1,1-difluoro-3-(1 H -tetrazol-1-yl)-1-(5-(4-(2,2,2-trifluoroethoxy)phenyl)pyridin-2-yl)propan-2-ol). Among the compounds tested, the first-line drug fluconazole was the weakest inhibitor, whereas posaconazole and VT-1161 were the strongest CYP51 inhibitors. We determined the X-ray structures of C. albicans CYP51 complexes with posaconazole and VT-1161, providing a molecular mechanism for the potencies of these drugs, including the activity of VT-1161 against Candida krusei and Candida glabrata , pathogens that are intrinsically resistant to fluconazole. Our comparative structural analysis outlines phylum-specific CYP51 features that could direct future rational development of more efficient broad-spectrum antifungals. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines.

PubMed

Tian, Sheng; Li, Youyong; Wang, Junmei; Xu, Xiaojie; Xu, Lei; Wang, Xiaohong; Chen, Lei; Hou, Tingjun

2013-01-21

In order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared. First, the different scaffolds were extracted from ACD, MDDR and TCMCD by using three scaffold representations, including Murcko frameworks, Scaffold Tree, and ring systems with different complexity and side chains. Then, by examining the accumulative frequency of the scaffolds in each dataset, we observed that the Level 1 scaffolds of the Scaffold Tree offer advantages over the other scaffold architectures to represent the scaffold diversity of the compound libraries. By comparing the similarity of the scaffold architectures presented in MDDR, ACD and TCMCD, structural overlaps were observed not only between MDDR and TCMCD but also between MDDR and ACD. Finally, Tree Maps were used to cluster the Level 1 scaffolds of the Scaffold Tree and visualize the scaffold space of the three datasets. The analysis of the scaffold architectures of MDDR, ACD and TCMCD shows that, on average, drug-like molecules in MDDR have the highest diversity while natural compounds in TCMCD have the highest complexity. According to the Tree Maps, it can be observed that the Level 1 scaffolds present in MDDR have higher diversity than those presented in TCMCD and ACD. However, some representative scaffolds in MDDR with high frequency show structural similarities to those in TCMCD and ACD, suggesting that some scaffolds in TCMCD and ACD may be potentially drug-like fragments for fragment-based and de novo drug design.

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines

PubMed Central

2013-01-01

Background In order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared. Results First, the different scaffolds were extracted from ACD, MDDR and TCMCD by using three scaffold representations, including Murcko frameworks, Scaffold Tree, and ring systems with different complexity and side chains. Then, by examining the accumulative frequency of the scaffolds in each dataset, we observed that the Level 1 scaffolds of the Scaffold Tree offer advantages over the other scaffold architectures to represent the scaffold diversity of the compound libraries. By comparing the similarity of the scaffold architectures presented in MDDR, ACD and TCMCD, structural overlaps were observed not only between MDDR and TCMCD but also between MDDR and ACD. Finally, Tree Maps were used to cluster the Level 1 scaffolds of the Scaffold Tree and visualize the scaffold space of the three datasets. Conclusion The analysis of the scaffold architectures of MDDR, ACD and TCMCD shows that, on average, drug-like molecules in MDDR have the highest diversity while natural compounds in TCMCD have the highest complexity. According to the Tree Maps, it can be observed that the Level 1 scaffolds present in MDDR have higher diversity than those presented in TCMCD and ACD. However, some representative scaffolds in MDDR with high frequency show structural similarities to those in TCMCD and ACD, suggesting that some scaffolds in TCMCD and ACD may be potentially drug-like fragments for fragment-based and de novo drug design. PMID:23336706

Structures of a Na+-coupled, substrate-bound MATE multidrug transporter

PubMed Central

Lu, Min; Symersky, Jindrich; Radchenko, Martha; Koide, Akiko; Guo, Yi; Nie, Rongxin; Koide, Shohei

2013-01-01

Multidrug transporters belonging to the multidrug and toxic compound extrusion (MATE) family expel dissimilar lipophilic and cationic drugs across cell membranes by dissipating a preexisting Na+ or H+ gradient. Despite its clinical relevance, the transport mechanism of MATE proteins remains poorly understood, largely owing to a lack of structural information on the substrate-bound transporter. Here we report crystal structures of a Na+-coupled MATE transporter NorM from Neisseria gonorrheae in complexes with three distinct translocation substrates (ethidium, rhodamine 6G, and tetraphenylphosphonium), as well as Cs+ (a Na+ congener), all captured in extracellular-facing and drug-bound states. The structures revealed a multidrug-binding cavity festooned with four negatively charged amino acids and surprisingly limited hydrophobic moieties, in stark contrast to the general belief that aromatic amino acids play a prominent role in multidrug recognition. Furthermore, we discovered an uncommon cation–π interaction in the Na+-binding site located outside the drug-binding cavity and validated the biological relevance of both the substrate- and cation-binding sites by conducting drug resistance and transport assays. Additionally, we uncovered potential rearrangement of at least two transmembrane helices upon Na+-induced drug export. Based on our structural and functional analyses, we suggest that Na+ triggers multidrug extrusion by inducing protein conformational changes rather than by directly competing for the substrate-binding amino acids. This scenario is distinct from the canonical antiport mechanism, in which both substrate and counterion compete for a shared binding site in the transporter. Collectively, our findings provide an important step toward a detailed and mechanistic understanding of multidrug transport. PMID:23341609

Medicinal chemistry inspired fragment-based drug discovery.

PubMed

Lanter, James; Zhang, Xuqing; Sui, Zhihua

2011-01-01

Lead generation can be a very challenging phase of the drug discovery process. The two principal methods for this stage of research are blind screening and rational design. Among the rational or semirational design approaches, fragment-based drug discovery (FBDD) has emerged as a useful tool for the generation of lead structures. It is particularly powerful as a complement to high-throughput screening approaches when the latter failed to yield viable hits for further development. Engagement of medicinal chemists early in the process can accelerate the progression of FBDD efforts by incorporating drug-friendly properties in the earliest stages of the design process. Medium-chain acyl-CoA synthetase 2b and ketohexokinase are chosen as examples to illustrate the importance of close collaboration of medicinal chemists, crystallography, and modeling. Copyright © 2011 Elsevier Inc. All rights reserved.

[Strategy for the development of dipeptide drugs].

PubMed

Gudasheva, T A

2011-01-01

The author describes an original approach to the development of dipeptide drugs based on the concept of the leading role of the beta-bend in the interaction of biologically active endogenous peptides with their receptors. The approach called "peptide-based drug design" includes both developments from the structure of a known psychotropic agent toward its topological peptide analog and developments from the active dipeptide site of a neuropeptide toward its mimetic. This strategy has been worked out at the V.V. Zakusov Research Institute of Pharmacology for 25 years. Results of investigations that discovered endogenous peptide prototypes of the known non-peptidic drugs (piracetam and sulpiride) are presented. They provided a basis for the creation of highly active non-toxic oral dipeptide preparations, such as nootrop Noopept, potential anti psychotic Dilept, and potential selective anxiolytic GB-115.

Aptamer-Mediated Up-conversion Core/MOF Shell Nanocomposites for Targeted Drug Delivery and Cell Imaging

PubMed Central

Deng, Kerong; Hou, Zhiyao; Li, Xuejiao; Li, Chunxia; Zhang, Yuanxin; Deng, Xiaoran; Cheng, Ziyong; Lin, Jun

2015-01-01

Multifunctional nanocarriers for targeted bioimaging and drug delivery have attracted much attention in early diagnosis and therapy of cancer. In this work, we develop a novel aptamer-guided nanocarrier based on the mesoporous metal-organic framework (MOF) shell and up-conversion luminescent NaYF4:Yb3+/Er3+ nanoparticles (UCNPs) core for the first time to achieve these goals. These UCNPs, chosen as optical labels in biological assays and medical imaging, could emit strong green emission under 980 nm laser. The MOF structure based on iron (III) carboxylate materials [MIL-100 (Fe)] possesses high porosity and non-toxicity, which is of great value as nanocarriers for drug storage/delivery. As a unique nanoplatform, the hybrid inorganic-organic drug delivery vehicles show great promising for simultaneous targeted labeling and therapy of cancer cells. PMID:25597762

Structure based comprehensive modelling, spatial fingerprints mapping and ADME screening of curcumin analogues as novel ALR2 inhibitors

PubMed Central

Verma, Sant Kumar

2017-01-01

Aldose reductase (ALR2) inhibition is the most legitimate approach for the management of diabetic complications. The limited triumph in the drug development against ALR2 is mainly because of its close structural similarity with the other members of aldo-keto reductase (AKR) superfamily viz. ALR1, AKR1B10; and lipophilicity problem i.e. poor diffusion of synthetic aldose reductase inhibitors (ARIs) to target tissues. The literature evidenced that naturally occurring curcumin demonstrates relatively specific and non-competitive inhibition towards human recombinant ALR2 over ALR1 and AKR1B10; however β-diketone moiety of curcumin is a specific substrate for liver AKRs and accountable for it’s rapid in vivo metabolism. In the present study, structure based comprehensive modelling studies were used to map the pharmacophoric features/spatial fingerprints of curcumin analogues responsible for their ALR2 specificity along with potency on a data set of synthetic curcumin analogues and naturally occurring curcuminoids. The data set molecules were also screened for drug-likeness or ADME parameters, and the screening data strongly support that curcumin analogues could be proposed as a good drug candidate for the development of ALR2 inhibitors with improved pharmacokinetic profile compared to curcuminoids due to the absence of β-diketone moiety in their structural framework. PMID:28399135

Using X-Ray Crystallography to Simplify and Accelerate Biologics Drug Development.

PubMed

Brader, Mark L; Baker, Edward N; Dunn, Michael F; Laue, Thomas M; Carpenter, John F

2017-02-01

Every major biopharmaceutical company incorporates a protein crystallography unit that is central to its structure-based drug discovery efforts. Yet these capabilities are rarely leveraged toward the formal higher order structural characterization that is so challenging but integral to large-scale biologics manufacturing. Although the biotech industry laments the shortcomings of its favored biophysical techniques, x-ray crystallography is not even considered for drug development. Why not? We suggest that this is due, at least in part, to outdated thinking (for a recent industry-wide survey, see Gabrielson JP, Weiss IV WF. Technical decision-making with higher order structure data: starting a new dialogue. J Pharm Sci. 2015;104(4):1240-1245). We examine some myths surrounding protein crystallography and highlight the inherent properties of protein crystals (molecular identity, biochemical purity, conformational uniformity, and macromolecular crowding) as having practicable commonalities with today's patient-focused liquid drug products. In the new millennium, protein crystallography has become essentially a routine analytical test. Its application may aid the identification of better candidate molecules that are more amenable to high-concentration processing, formulation, and analysis thereby helping to make biologics drug development quicker, simpler, and cheaper. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Drug treatment or alleviating the negative consequences of imprisonment? A critical view of prison-based drug treatment in Denmark.

PubMed

Kolind, Torsten; Frank, Vibeke Asmussen; Dahl, Helle

2010-01-01

The availability of prison-based drug treatment has increased markedly throughout Europe over the last 15 years in terms of both volume and programme diversity. However, prison drug treatment faces problems and challenges because of the tension between ideologies of rehabilitation and punishment. This article reports on a study of four cannabis treatment programmes and four psychosocial drug treatment programmes in four Danish prisons during 2007. The data include the transcripts of 22 semi-structured qualitative interviews with counsellors and prison employees, prison statistics, and information about Danish laws and regulations. These treatment programmes reflect the 'treatment guarantee' in Danish prisons. However, they are simultaneously embedded in a new policy of zero tolerance and intensified disciplinary sanctions. This ambivalence is reflected in the experiences of treatment counsellors: reluctantly, they feel associated with the prison institution in the eyes of the prisoners; they experience severe opposition from prison officers; and the official goals of the programmes, such as making clients drug free and preparing them for a life without crime, are replaced by more pragmatic aims such as alleviating the pain of imprisonment felt by programme clients. The article concludes that at a time when prison-based drug treatment is growing, it is crucial that we thoroughly research and critically discuss its content and the restrictions facing such treatment programmes. One way of doing this is through research with counsellors involved in delivering drug treatment services. By so doing, the programmes can become more pragmatic and focused, and alternatives to prison-based drug treatment can be seriously considered.

In Silico target fishing: addressing a "Big Data" problem by ligand-based similarity rankings with data fusion.

PubMed

Liu, Xian; Xu, Yuan; Li, Shanshan; Wang, Yulan; Peng, Jianlong; Luo, Cheng; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang

2014-01-01

Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound. We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion. A large library containing 533 drug relevant targets with 179,807 active ligands was compiled, where each target was defined by its ligand set. For a given query molecule, its target profile is generated by similarity searching against the ligand sets assigned to each target, for which individual searches utilizing multiple reference structures are then fused into a single ranking list representing the potential target interaction profile of the query compound. The proposed approach was validated by 10-fold cross validation and two external tests using data from DrugBank and Therapeutic Target Database (TTD). The use of the approach was further demonstrated with some examples concerning the drug repositioning and drug side-effects prediction. The promising results suggest that the proposed method is useful for not only finding promiscuous drugs for their new usages, but also predicting some important toxic liabilities. With the rapid increasing volume and diversity of data concerning drug related targets and their ligands, the simple ligand-based target fishing approach would play an important role in assisting future drug design and discovery.

Grid Based Technologies for in silico Screening and Drug Design.

PubMed

Potemkin, Vladimir; Grishina, Maria

2018-03-08

Various techniques for rational drug design are presented in the paper. The methods are based on a substitution of antipharmacophore atoms of the molecules of training dataset by new atoms and/or group of atoms increasing the atomic bioactivity increments obtained at a SAR study. Furthermore, a design methodology based on the genetic algorithm DesPot for discrete optimization and generation of new drug candidate structures is described. Additionally, wide spectra of SAR approaches (3D/4D QSAR interior and exterior-based methods - BiS, CiS, ConGO, CoMIn, high-quality docking method - ReDock) using MERA force field and/or AlteQ quantum chemical method for correct prognosis of bioactivity and bioactive probability is described. The design methods are implemented now at www.chemosophia.com web-site for online computational services. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

StraPep: a structure database of bioactive peptides

PubMed Central

Wang, Jian; Yin, Tailang; Xiao, Xuwen; He, Dan; Xue, Zhidong; Jiang, Xinnong; Wang, Yan

2018-01-01

Abstract Bioactive peptides, with a variety of biological activities and wide distribution in nature, have attracted great research interest in biological and medical fields, especially in pharmaceutical industry. The structural information of bioactive peptide is important for the development of peptide-based drugs. Many databases have been developed cataloguing bioactive peptides. However, to our knowledge, database dedicated to collect all the bioactive peptides with known structure is not available yet. Thus, we developed StraPep, a structure database of bioactive peptides. StraPep holds 3791 bioactive peptide structures, which belong to 1312 unique bioactive peptide sequences. About 905 out of 1312 (68%) bioactive peptides in StraPep contain disulfide bonds, which is significantly higher than that (21%) of PDB. Interestingly, 150 out of 616 (24%) bioactive peptides with three or more disulfide bonds form a structural motif known as cystine knot, which confers considerable structural stability on proteins and is an attractive scaffold for drug design. Detailed information of each peptide, including the experimental structure, the location of disulfide bonds, secondary structure, classification, post-translational modification and so on, has been provided. A wide range of user-friendly tools, such as browsing, sequence and structure-based searching and so on, has been incorporated into StraPep. We hope that this database will be helpful for the research community. Database URL: http://isyslab.info/StraPep PMID:29688386

Novel approaches to anticonvulsant drug discovery.

PubMed

Miziak, Barbara; Chrościńska-Krawczyk, Magdalena; Błaszczyk, Barbara; Radzik, Iwona; Czuczwar, Stanisław J

2013-11-01

The history of epilepsy dates back to 2000 BC. Yet, it was not until 1912 that the activity of the first antiepileptic, phenobarbital was discovered by accident. After this discovery, the next antiepileptic drugs to be discovered (phenytoin and primidone) were based on the phenobarbital's structure. Then, in 1960, carbamazepine was developed empirically, while in 1962, valproate demonstrated anticonvulsant activity against experimental seizures. The next antiepileptic drugs synthesized were either modifications of the existing drugs (such as oxcarbazepine and pregabalin) or completely novel chemical structures (lacosamide, perampanel and retigabine). The present paper briefly refers to the history of epilepsy and development of antiepileptic drugs. Further, the paper provides a discussion on the antiepileptogenic effects of antiepileptic drugs in terms of the constant percentage of epileptic patients with refractory seizures. The authors also review the likely factors involved in the false refractoriness (such as through the use of caffeine-containing beverages and smoking). Finally, the authors consider future directions in the search of novel antiepileptic drugs. In spite of the considerable number of newer antiepileptic drugs, the number of drug-resistant epileptic patients remains unchanged. This may be rather an indication of the suitability of the currently available discovery procedures for effective antiepileptic drugs in the whole population of epileptic patients. The authors, however, believe that it is likely that models of mimic chronic epilepsy will help bridge the gaps and aid in the discovery of novel antiepileptic drugs - ones that can effectively modify the course of the disease.

Thiopurine Drugs Repositioned as Tyrosinase Inhibitors

PubMed Central

Choi, Joonhyeok; Lee, You-Mie; Jee, Jun-Goo

2017-01-01

Drug repositioning is the application of the existing drugs to new uses and has the potential to reduce the time and cost required for the typical drug discovery process. In this study, we repositioned thiopurine drugs used for the treatment of acute leukaemia as new tyrosinase inhibitors. Tyrosinase catalyses two successive oxidations in melanin biosynthesis: the conversions of tyrosine to dihydroxyphenylalanine (DOPA) and DOPA to dopaquinone. Continuous efforts are underway to discover small molecule inhibitors of tyrosinase for therapeutic and cosmetic purposes. Structure-based virtual screening predicted inhibitor candidates from the US Food and Drug Administration (FDA)-approved drugs. Enzyme assays confirmed the thiopurine leukaemia drug, thioguanine, as a tyrosinase inhibitor with the inhibitory constant of 52 μM. Two other thiopurine drugs, mercaptopurine and azathioprine, were also evaluated for their tyrosinase inhibition; mercaptopurine caused stronger inhibition than thioguanine did, whereas azathioprine was a poor inhibitor. The inhibitory constant of mercaptopurine (16 μM) was comparable to that of the well-known inhibitor kojic acid (13 μM). The cell-based assay using B16F10 melanoma cells confirmed that the compounds inhibit mammalian tyrosinase. Particularly, 50 μM thioguanine reduced the melanin content by 57%, without apparent cytotoxicity. Cheminformatics showed that the thiopurine drugs shared little chemical similarity with the known tyrosinase inhibitors. PMID:29283382

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

PubMed

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

2013-10-28

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

Differential speciation of ferriprotoporphyrin IX in the presence of free base and diprotic 4-aminoquinoline antimalarial drugs

NASA Astrophysics Data System (ADS)

Gildenhuys, Johandie; Müller, Ronel; le Roex, Tanya; de Villiers, Katherine A.

2017-03-01

The crystal structures of the μ-propionato dimer and π-π dimer of ferriprotoporphyrin IX (Fe(III)PPIX) have been determined by single crystal X-ray diffraction (SCD). Both species were obtained in the presence of the synthetic 4-aminoquinoline antimalarial drug, amodiaquine (AQ). The solution that afforded the μ-propionato dimer contained AQ as a free base (i.e. with both quinoline and terminal amine nitrogen atoms neutral). On the other hand, when the diprotic salt of AQ was included in the crystallization medium, the Fe(III)PPIX π-π dimer was obtained. The structure of the μ-propionato dimer, which is the discrete structural unit that constitutes haemozoin (malaria pigment), is identical to that obtained previously in presence of chloroquine free base. We suspect that the drug, via its two available basic sites, facilitates dissociation of one of the two Fe(III)PPIX propionic acid groups to yield a propionate group that is required for reciprocal coordination of the metal centre to form the centrosymmetric dimer. On the other hand, this proton transfer is not possible when the drug is present as a diprotic salt. In this case, the π-π dimer of Fe(III)PPIX is obtained. In the current study, the π-π dimer of haemin (chloro-Fe(III)PPIX) was obtained as a DMF solvate from non-aqueous aprotic solution (dimethyl formamide and chloroform), however the π-π dimer is also known to exist in aqueous solution (as aqua- or hydroxo-Fe(III)PPIX), where it is purportedly involved in the nucleation of haemozoin. We have been able to unambiguously determine the positions of all non-hydrogen atoms, as well as locate or assign all hydrogen atoms in the structure of the π-π dimer, which was not possible in the SCD structure of haemin reported by Koenig in 1965 owing to disorder in the vinyl and methyl substituents. Interestingly, no disorder in the methyl and vinyl groups is observed in the current structure. Both the π-π and μ-propionato dimers of Fe(III)PPIX are important species in the haem detoxification pathway in the malaria parasite and other blood-feeding organisms, and the structural insight gained in this study may assist target-driven design of new chemotherapeutic agents.

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction.

PubMed

Xu, Youjun; Wang, Shiwei; Hu, Qiwan; Gao, Shuaishi; Ma, Xiaomin; Zhang, Weilin; Shen, Yihang; Chen, Fangjin; Lai, Luhua; Pei, Jianfeng

2018-05-10

CavityPlus is a web server that offers protein cavity detection and various functional analyses. Using protein three-dimensional structural information as the input, CavityPlus applies CAVITY to detect potential binding sites on the surface of a given protein structure and rank them based on ligandability and druggability scores. These potential binding sites can be further analysed using three submodules, CavPharmer, CorrSite, and CovCys. CavPharmer uses a receptor-based pharmacophore modelling program, Pocket, to automatically extract pharmacophore features within cavities. CorrSite identifies potential allosteric ligand-binding sites based on motion correlation analyses between cavities. CovCys automatically detects druggable cysteine residues, which is especially useful to identify novel binding sites for designing covalent allosteric ligands. Overall, CavityPlus provides an integrated platform for analysing comprehensive properties of protein binding cavities. Such analyses are useful for many aspects of drug design and discovery, including target selection and identification, virtual screening, de novo drug design, and allosteric and covalent-binding drug design. The CavityPlus web server is freely available at http://repharma.pku.edu.cn/cavityplus or http://www.pkumdl.cn/cavityplus.

Bottom-up preparation and structural study of monodispersed lipid particles with internal structure

NASA Astrophysics Data System (ADS)

Kim, Hojun; Alfeche, Alana; Leal, Cecilia

Lipid based nanoparticles having internal bicontinuous cubic phases, also known as cubosomes, are becoming increasingly interesting drug delivery platforms. Compared to the liposomes, they offer an augmented surface area for drug encapsulation. However, this simple argument is insufficient to explain the cellular delivery performance of cubosomes compared to other lipid-based nanoparticles. One could argue that their topology facilitates membrane fusion and endosomal escape but at the moment the exact mechanism of cubosome cellular internalization and endosomal escape is still unknown. This is partially because the practical use of cubosomes has been limited due to hurdles of uncontrollable size and shape distributions. The conventional top-down preparation methods (sonication/homogenization) yield large and polydisperse particles. In this presentation we introduce a new system based on microfluidic devices to prepare small (200 nm) and monodisperse cubosomes with a quality not possible using conventional methods. With this approach, we successfully prepared spherical and monodisperse cubosomes (PDI: 0.01) with and without drug loading. To characterize the cubosomes and the formation mechanisms, we utilize Small Angle X-ray Scattering (SAXS) and Cryogenic TEM. We acknowledge the funding source as a NIH.

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.

Discovery of 1-(3-aryl-4-chlorophenyl)-3-(p-aryl)urea derivatives against breast cancer by inhibiting PI3K/Akt/mTOR and Hedgehog signalings.

PubMed

Li, Wenlu; Sun, Qinsheng; Song, Lu; Gao, Chunmei; Liu, Feng; Chen, Yuzong; Jiang, Yuyang

2017-12-01

PI3K/Akt/mTOR and hedgehog (Hh) signalings are two important pathways in breast cancer, which are usually connected with the drug resistance and cancer migration. Many studies indicated that PI3K/Akt/mTOR inhibitors and Hh inhibitors displayed synergistic effects, and the combination of the two signaling drugs could delay drug resistance and inhibit cancer migration in breast cancer. Therefore, the development of molecules simultaneously inhibiting these two pathways is urgent needed. Based on the structures of PI3K inhibitor buparlisib and Hh inhibitor vismodegib, a series of hybrid structures were designed and synthesized utilizing rational drug design and computer-based drug design. Several compounds displayed excellent antiproliferative activities against several breast cancer cell lines, including triple-negative breast cancer (TNBC) MDA-MB-231 cell. Further mechanistic studies demonstrated that the representative compound 9i could inhibit both PI3K/Akt/mTOR and hedgehog (Hh) signalings by inhibiting the phosphorylation of S6K and Akt as well as decreasing the SAG elevated expression of Gli1. Compound 9i could also induce apoptosis remarkably in T47D and MDA-MB-231 cells. In the transwell assay, 9i showed significant inhibition on the migration of MDA-MB-231. Copyright © 2017 Elsevier Masson SAS. All rights reserved.