1
|
Pantaleão SQ, Philot EA, de Paula H, Inês de Sairre M, Lima AN, Pires LM, Alves Dos Santos R, Scott AL, Honorio KM. Virtual screening and in vitro assays of novel hits as promising DPP-4 inhibitors. Biochimie 2021; 194:43-50. [PMID: 34952193 DOI: 10.1016/j.biochi.2021.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 12/06/2021] [Accepted: 12/16/2021] [Indexed: 11/02/2022]
Abstract
Diabetes is a metabolic disorder that presents hyperglycemia and vascular complications due to the non-production of insulin or its inappropriate use by the body. One of the strategies to treat diabetes is the inhibition of dipeptidyl peptidase-4 (DPP-4) and it is interesting to conduct virtual screening studies to search for new inhibitors of the DPP-4 enzyme. This study involves a virtual screening using the crystallographic structure of DPP-4 and a compound subset from the ZINC database. To filter this compound subset, we used some physicochemical properties, positioning at the three DPP-4 binding sites, molecular interactions, and ADME-Tox properties. The conformations of ligands obtained from AutoDock Vina were analyzed using a consensus with other algorithms (AutoDock and GOLD). The compounds selected from virtual screening were submitted to biological assays using the "DPPIV-Glo™ protease assay". Cytotoxicity tests were also performed. One promising compound (ZINC1572309) established interactions with important residues at the binding site. The results of the ADME-Tox prediction for ZINC1572309 were compared with a reference drug (sitagliptin). The cytotoxicity of sitagliptin and ZINC1572309 were evaluated using the XTT short-term cytotoxic assay, including normal and tumor cell lines to observe the cellular response to inhibitor treatment at different genetic bases. Both compounds (ZINC1572309 and the reference drug - sitagliptin) also inhibited DPP-4 activity, suggesting interesting biological effects of the selected compound at non-cytotoxic concentrations. Therefore, from in silico and in vitro studies, a potential hit as DPP-4 inhibitor was discovered and it can be structurally optimized to achieve suitable activity and pharmacokinetic profiles.
Collapse
Affiliation(s)
- Simone Queiroz Pantaleão
- Center for Sciences Natural and Human, Federal University of ABC, 09210-170, Santo André, SP, Brazil
| | - Eric Allison Philot
- Center for Mathematics, Computing and Cognition, Federal University of ABC, 09210-170, Santo André, SP, Brazil
| | - Heberth de Paula
- Center for Exact, Natural and Health Sciences, Federal University of Espírito Santo, 29075-910, Vitória, ES, Brazil
| | - Mirela Inês de Sairre
- Center for Sciences Natural and Human, Federal University of ABC, 09210-170, Santo André, SP, Brazil
| | - Angelica Nakagawa Lima
- Department of Medical Genetics and Genomic Medicine, Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, SP, Brazil
| | - Loren Monielly Pires
- Laboratory of Genetics and Molecular Biology, University of Franca, 14404-600, Franca, SP, Brazil
| | - Raquel Alves Dos Santos
- Laboratory of Genetics and Molecular Biology, University of Franca, 14404-600, Franca, SP, Brazil
| | - Ana Ligia Scott
- Center for Mathematics, Computing and Cognition, Federal University of ABC, 09210-170, Santo André, SP, Brazil
| | - Kathia Maria Honorio
- Center for Sciences Natural and Human, Federal University of ABC, 09210-170, Santo André, SP, Brazil; School of Arts, Sciences and Humanities, University of São Paulo, 03828-0000, São Paulo, SP, Brazil.
| |
Collapse
|
2
|
Machiraju PK, Yedla P, Gubbala SP, Bohari T, Abdul JK, Xu S, Patel R, Chittireddy VRR, Boppana K, Jagarlapudi SA, Neamati N, Syed R, Amanchy R. Identification, synthesis and evaluation of CSF1R inhibitors using fragment based drug design. Comput Biol Chem 2019; 80:374-383. [DOI: 10.1016/j.compbiolchem.2019.04.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 03/12/2019] [Accepted: 04/28/2019] [Indexed: 02/07/2023]
|
3
|
Varela JN, Lammoglia Cobo MF, Pawar SV, Yadav VG. Cheminformatic Analysis of Antimalarial Chemical Space Illuminates Therapeutic Mechanisms and Offers Strategies for Therapy Development. J Chem Inf Model 2017; 57:2119-2131. [PMID: 28810125 DOI: 10.1021/acs.jcim.7b00072] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The clear and present danger of malaria, which has been amplified in recent years by climate change, and the progressive thinning of our drug arsenal over the past two decades raise uncomfortable questions about the current state and future of antimalarial drug development. Besides suffering from many of the same technical challenges that affect drug development in other disease areas, the quest for new antimalarial therapies is also hindered by the complex, dynamic life cycle of the malaria parasite, P. falciparum, in its mosquito and human hosts, and its role thereof in the elicitation of drug resistance. New strategies are needed in order to ensure economical and expeditious development of new, more efficacious treatments. In the present study, we employ open-source cheminformatics tools to analyze the chemical space traversed by approved antimalarial drugs and promising candidates at various stages of development to uncover insights that could shape future endeavors in the field. Our scaffold-centric analysis reveals that the antimalarial chemical space is disjointed and segregated into a few dominant structural groups. In fact, the structures of antimalarial drugs and drug candidates are distributed according to Pareto's principle. This structural convergence can potentially be exploited for future drug discovery by incorporating it into bioinformatics workflows that are typically employed for solving problems in structural biology. Significantly, we demonstrate how molecular scaffold hunting can be applied to unearth putative mechanisms of action of drugs whose activities remain a mystery, and how scaffold-centric analysis of drug space can also provide a recipe for combination therapies that minimize the likelihood of emergence of drug resistance, as well as identify areas on which to focus efforts. Finally, we also observe that over half of the molecules in the antimalarial space bear no resemblance to other molecules in the collection, which suggests that the pharmacobiology of antimalarial drugs has not been entirely surveyed.
Collapse
Affiliation(s)
- Julia Nogueira Varela
- Department of Chemical & Biological Engineering, The University of British Columbia , Vancouver, BC, Canada , V6T 1Z3
| | - María Fernanda Lammoglia Cobo
- Department of Chemical & Biological Engineering, The University of British Columbia , Vancouver, BC, Canada , V6T 1Z3.,Life Sciences Department, Monterrey Institute of Technology and Higher Education , Mexico City Campus, Mexico City, Mexico , 14380
| | - Sandip V Pawar
- Department of Chemical & Biological Engineering, The University of British Columbia , Vancouver, BC, Canada , V6T 1Z3
| | - Vikramaditya G Yadav
- Department of Chemical & Biological Engineering, The University of British Columbia , Vancouver, BC, Canada , V6T 1Z3.,Neglected Global Diseases Initiative, The University of British Columbia , Vancouver, BC, Canada , V6T 1Z3
| |
Collapse
|
4
|
Nair PC, McKinnon RA, Miners JO. A Fragment-Based Approach for the Computational Prediction of the Nonspecific Binding of Drugs to Hepatic Microsomes. ACTA ACUST UNITED AC 2016; 44:1794-1798. [PMID: 27543205 DOI: 10.1124/dmd.116.071852] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2016] [Accepted: 08/18/2016] [Indexed: 11/22/2022]
Abstract
Correction for the nonspecific binding (NSB) of drugs to liver microsomes is essential for the accurate measurement of the kinetic parameters Km and Ki, and hence in vitro-in vivo extrapolation to predict hepatic clearance and drug-drug interaction potential. Although a number of computational approaches for the estimation of drug microsomal NSB have been published, they generally rely on compound lipophilicity and charge state at the expense of other physicochemical and chemical properties. In this work, we report the development of a fragment-based hologram quantitative structure activity relationship (HQSAR) approach for the prediction of NSB using a database of 132 compounds. The model has excellent predictivity, with a noncross-validated r2 of 0.966 and cross-validated r2 of 0.680, with a predictive r2 of 0.748 for an external test set comprising 34 drugs. The HQSAR method reliably predicted the fraction unbound in incubations of 95% of the training and test set drugs, excluding compounds with a steroid or morphinan 4,5-epoxide nucleus. Using the same data set of compounds, performance of the HQSAR method was superior to a model based on logP/D as the sole descriptor (predictive r2 for the test set compounds, 0.534). Thus, the HQSAR method provides an alternative approach to laboratory-based procedures for the prediction of the NSB of drugs to liver microsomes, irrespective of the drug charge state (acid, base, or neutral).
Collapse
Affiliation(s)
- Pramod C Nair
- Department of Clinical Pharmacology (P.C.N., J.O.M.) and Flinders Centre for Innovation in Cancer (P.C.N., R.A.M., J.O.M.), School of Medicine, Flinders University, Adelaide, Australia
| | - Ross A McKinnon
- Department of Clinical Pharmacology (P.C.N., J.O.M.) and Flinders Centre for Innovation in Cancer (P.C.N., R.A.M., J.O.M.), School of Medicine, Flinders University, Adelaide, Australia
| | - John O Miners
- Department of Clinical Pharmacology (P.C.N., J.O.M.) and Flinders Centre for Innovation in Cancer (P.C.N., R.A.M., J.O.M.), School of Medicine, Flinders University, Adelaide, Australia
| |
Collapse
|
5
|
Wang J, Yang Y, Li Y, Wang Y. Computational Study Exploring the Interaction Mechanism of Benzimidazole Derivatives as Potent Cattle Bovine Viral Diarrhea Virus Inhibitors. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2016; 64:5941-5950. [PMID: 27355875 DOI: 10.1021/acs.jafc.6b01067] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Bovine viral diarrhea virus (BVDV) infections are prevailing in cattle populations on a worldwide scale. The BVDV RNA-dependent RNA polymerase (RdRp), as a promising target for new anti-BVDV drug development, has attracted increasing attention. To explore the interaction mechanism of 65 benzimidazole scaffold-based derivatives as BVDV inhibitors, presently, a computational study was performed based on a combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations. The resultant optimum CoMFA and CoMSIA models present proper reliabilities and strong predictive abilities (with Q(2) = 0. 64, R(2)ncv = 0.93, R(2)pred = 0.80 and Q(2) = 0. 65, R(2)ncv = 0.98, R(2)pred = 0.86, respectively). In addition, there was good concordance between these models, molecular docking, and MD results. Moreover, the MM-PBSA energy analysis reveals that the major driving force for ligand binding is the polar solvation contribution term. Hopefully, these models and the obtained findings could offer better understanding of the interaction mechanism of BVDV inhibitors as well as benefit the new discovery of more potent BVDV inhibitors.
Collapse
Affiliation(s)
- Jinghui Wang
- Key Laboratory of Xinjiang Endemic Phytomedicine Resources, Pharmacy School, Ministry of Education, Shihezi University , Shihezi 832002, China
- Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology , Dalian, Liaoning 116024, P. R. China
| | - Yinfeng Yang
- Key Laboratory of Xinjiang Endemic Phytomedicine Resources, Pharmacy School, Ministry of Education, Shihezi University , Shihezi 832002, China
- Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology , Dalian, Liaoning 116024, P. R. China
| | - Yan Li
- Key Laboratory of Xinjiang Endemic Phytomedicine Resources, Pharmacy School, Ministry of Education, Shihezi University , Shihezi 832002, China
- Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Faculty of Chemical, Environmental and Biological Science and Technology, Dalian University of Technology , Dalian, Liaoning 116024, P. R. China
| | - Yonghua Wang
- Key Laboratory of Xinjiang Endemic Phytomedicine Resources, Pharmacy School, Ministry of Education, Shihezi University , Shihezi 832002, China
| |
Collapse
|
6
|
Kothandan G, Gadhe CG, Cho SJ. Investigation of the Binding Site of CCR2 using 4-Azetidinyl-1-aryl-cyclohexane Derivatives: A Membrane Modeling and Molecular Dynamics Study. B KOREAN CHEM SOC 2013. [DOI: 10.5012/bkcs.2013.34.11.3429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
|
7
|
Horvath D, Marcou G, Varnek A. Do not hesitate to use Tversky-and other hints for successful active analogue searches with feature count descriptors. J Chem Inf Model 2013; 53:1543-62. [PMID: 23731338 DOI: 10.1021/ci400106g] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
This study is an exhaustive analysis of the neighborhood behavior over a large coherent data set (ChEMBL target/ligand pairs of known Ki, for 165 targets with >50 associated ligands each). It focuses on similarity-based virtual screening (SVS) success defined by the ascertained optimality index. This is a weighted compromise between purity and retrieval rate of active hits in the neighborhood of an active query. One key issue addressed here is the impact of Tversky asymmetric weighing of query vs candidate features (represented as integer-value ISIDA colored fragment/pharmacophore triplet count descriptor vectors). The nearly a 3/4 million independent SVS runs showed that Tversky scores with a strong bias in favor of query-specific features are, by far, the most successful and the least failure-prone out of a set of nine other dissimilarity scores. These include classical Tanimoto, which failed to defend its privileged status in practical SVS applications. Tversky performance is not significantly conditioned by tuning of its bias parameter α. Both initial "guesses" of α = 0.9 and 0.7 were more successful than Tanimoto (at its turn, better than Euclid). Tversky was eventually tested in exhaustive similarity searching within the library of 1.6 M commercial + bioactive molecules at http://infochim.u-strasbg.fr/webserv/VSEngine.html , comparing favorably to Tanimoto in terms of "scaffold hopping" propensity. Therefore, it should be used at least as often as, perhaps in parallel to Tanimoto in SVS. Analysis with respect to query subclasses highlighted relationships of query complexity (simply expressed in terms of pharmacophore pattern counts) and/or target nature vs SVS success likelihood. SVS using more complex queries are more robust with respect to the choice of their operational premises (descriptors, metric). Yet, they are best handled by "pro-query" Tversky scores at α > 0.5. Among simpler queries, one may distinguish between "growable" (allowing for active analogs with additional features), and a few "conservative" queries not allowing any growth. These (typically bioactive amine transporter ligands) form the specific application domain of "pro-candidate" biased Tversky scores at α < 0.5.
Collapse
Affiliation(s)
- Dragos Horvath
- Laboratoire d'Infochimie, UMR 7140 CNRS-University Strasbourg, 1 Rue Blaise Pascal, Strasbourg 67000, France.
| | | | | |
Collapse
|
8
|
Singh R, Balupuri A, Sobhia ME. Development of 3D-pharmacophore model followed by successive virtual screening, molecular docking and ADME studies for the design of potent CCR2 antagonists for inflammation-driven diseases. MOLECULAR SIMULATION 2013. [DOI: 10.1080/08927022.2012.701743] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
|
9
|
HOU CUIFEN, SUI ZHIHUA. CCR2 Antagonists for the Treatment of Diseases Associated with Inflammation. ANTI-INFLAMMATORY DRUG DISCOVERY 2012. [DOI: 10.1039/9781849735346-00350] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The CCR2 and MCP-1 pathway has become one of the most-studied chemokine systems for therapeutic use in inflammatory diseases and conditions. It plays a pivotal role in inflammatory diseases, especially those that are characterized by monocyte-rich infiltration. This chapter reviews the biology of CCR2 and MCP-1, and their roles in diseases and conditions related to inflammation such as rheumatoid arthritis, multiple sclerosis, asthma, obesity, type 2 diabetes, atherosclerosis, nephropathy, cancer, pulmonary fibrosis and pain. Intense drug-discovery efforts over the past 15 years have generated a large number of CCR2 antagonists in diverse structural classes. Mutagenesis studies have elucidated important residues on CCR2 that interact with many classes of these CCR2 antagonists. To facilitate understanding of CCR2 antagonist SAR, a simple pharmacophore model is used to summarize the large number of diverse chemical structures. The majority of published compounds are classified based on their central core structures using this model. Key SAR points in the published literature are briefly discussed for most of the series. Lead compounds in each chemical series are highlighted where information is available. The challenges in drug discovery and development of CCR2 antagonists are briefly discussed. Clinical candidates in various diseases in the public domain are summarized with a brief discussion about the clinical challenges.
Collapse
Affiliation(s)
- CUIFEN HOU
- Johnson & Johnson Pharmaceutical Research and Development Welsh and McKean Roads, Spring House, PA 19477 USA
| | - ZHIHUA SUI
- Johnson & Johnson Pharmaceutical Research and Development Welsh and McKean Roads, Spring House, PA 19477 USA
| |
Collapse
|
10
|
Kothandan G, Gadhe CG, Madhavan T, Cho SJ. Binding Site Analysis of CCR2 Through In Silico Methodologies: Docking, CoMFA, and CoMSIA. Chem Biol Drug Des 2011; 78:161-74. [DOI: 10.1111/j.1747-0285.2011.01095.x] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
|
11
|
4-aminoquinolines active against chloroquine-resistant Plasmodium falciparum: basis of antiparasite activity and quantitative structure-activity relationship analyses. Antimicrob Agents Chemother 2011; 55:2233-44. [PMID: 21383099 DOI: 10.1128/aac.00675-10] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Chloroquine (CQ) is a safe and economical 4-aminoquinoline (AQ) antimalarial. However, its value has been severely compromised by the increasing prevalence of CQ resistance. This study examined 108 AQs, including 68 newly synthesized compounds. Of these 108 AQs, 32 (30%) were active only against CQ-susceptible Plasmodium falciparum strains and 59 (55%) were active against both CQ-susceptible and CQ-resistant P. falciparum strains (50% inhibitory concentrations [IC50s], ≤25 nM). All AQs active against both CQ-susceptible and CQ-resistant P. falciparum strains shared four structural features: (i) an AQ ring without alkyl substitution, (ii) a halogen at position 7 (Cl, Br, or I but not F), (iii) a protonatable nitrogen at position 1, and (iv) a second protonatable nitrogen at the end of the side chain distal from the point of attachment to the AQ ring via the nitrogen at position 4. For activity against CQ-resistant parasites, side chain lengths of ≤3 or ≥10 carbons were necessary but not sufficient; they were identified as essential factors by visual comparison of 2-dimensional (2-D) structures in relation to the antiparasite activities of the AQs and were confirmed by computer-based 3-D comparisons and differential contour plots of activity against P. falciparum. The advantage of the method reported here (refinement of quantitative structure-activity relationship [QSAR] descriptors by random assignment of compounds to multiple training and test sets) is that it retains QSAR descriptors according to their abilities to predict the activities of unknown test compounds rather than according to how well they fit the activities of the compounds in the training sets.
Collapse
|
12
|
Abstract
This chapter is a review of the most recent developments in the field of pharmacophore modeling, covering both methodology and application. Pharmacophore-based virtual screening is nowadays a mature technology, very well accepted in the medicinal chemistry laboratory. Nevertheless, like any empirical approach, it has specific limitations and efforts to improve the methodology are still ongoing. Fundamentally, the core idea of "stripping" functional groups of their actual chemical nature in order to classify them into very few pharmacophore types, according to their dominant physico-chemical features, is both the main advantage and the main drawback of pharmacophore modeling. The advantage is the one of simplicity - the complex nature of noncovalent ligand binding interactions is rendered intuitive and comprehensible by the human mind. Although computers are much better suited for comparisons of pharmacophore patterns, a chemist's intuition is primarily scaffold-oriented. Its underlying simplifications render pharmacophore modeling unable to provide perfect predictions of ligand binding propensities - not even if all its subsisting technical problems would be solved. Each step in pharmacophore modeling and exploitation has specific drawbacks: from insufficient or inaccurate conformational sampling to ambiguities in pharmacophore typing (mainly due to uncertainty regarding the tautomeric/protonation status of compounds), to computer time limitations in complex molecular overlay calculations, and to the choice of inappropriate anchoring points in active sites when ligand cocrystals structures are not available. Yet, imperfections notwithstanding, the approach is accurate enough in order to be practically useful and actually is the most used virtual screening technique in medicinal chemistry - notably for "scaffold hopping" approaches, allowing the discovery of new chemical classes carriers of a desired biological activity.
Collapse
Affiliation(s)
- Dragos Horvath
- Laboratoire d'InfoChime, UMR 7177, Université de Strasbourg - CNRSInstitut de Chimie, Strasbourg, France
| |
Collapse
|
13
|
Saghaie L, Shahlaei M, Fassihi A, Madadkar-Sobhani A, Gholivand MB, Pourhossein A. QSAR Analysis for Some Diaryl-substituted Pyrazoles as CCR2 Inhibitors by GA-Stepwise MLR. Chem Biol Drug Des 2010; 77:75-85. [DOI: 10.1111/j.1747-0285.2010.01053.x] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
|
14
|
Lead generation and optimization based on protein-ligand complementarity. Molecules 2010; 15:4382-400. [PMID: 20657448 PMCID: PMC6264460 DOI: 10.3390/molecules15064382] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2010] [Accepted: 06/07/2010] [Indexed: 01/16/2023] Open
Abstract
This work proposes a computational procedure for structure-based lead generation and optimization, which relies on the complementarity of the protein-ligand interactions. This procedure takes as input the known structure of a protein-ligand complex. Retaining the positions of the ligand heavy atoms in the protein binding site it designs structurally similar compounds considering all possible combinations of atomic species (N, C, O, CH3, NH, etc). Compounds are ranked based on a score which incorporates energetic contributions evaluated using molecular mechanics force fields. This procedure was used to design new inhibitor molecules for three serine/threonine protein kinases (p38 MAP kinase, p42 MAP kinase (ERK2), and c-Jun N-terminal kinase 3 (JNK3)). For each enzyme, the calculations produce a set of potential inhibitors whose scores are in agreement with IC50 data and Ki values. Furthermore, the native ligands for each protein target, scored within the five top-ranking compounds predicted by our method, one of the top-ranking compounds predicted to inhibit JNK3 was synthesized and his inhibitory activity confirmed against ATP hydrolysis. Our computational procedure is therefore deemed to be a useful tool for generating chemically diverse molecules active against known target proteins.
Collapse
|
15
|
Sobhia ME, Singh R, Kare P, Chavan S. Rational design of CCR2 antagonists: a survey of computational studies. Expert Opin Drug Discov 2010; 5:543-57. [DOI: 10.1517/17460441.2010.482559] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
|
16
|
Salum LB, Andricopulo AD. Fragment-based QSAR strategies in drug design. Expert Opin Drug Discov 2010; 5:405-12. [DOI: 10.1517/17460441003782277] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
|