1
|
Schwartz R, Zev S, Major DT. Mechanistic docking in terpene synthases using EnzyDock. Methods Enzymol 2024; 699:265-292. [PMID: 38942507 DOI: 10.1016/bs.mie.2024.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
Terpene Synthases (TPS) catalyze the formation of multicyclic, complex terpenes and terpenoids from linear substrates. Molecular docking is an important research tool that can further our understanding of TPS multistep mechanisms and guide enzyme design. Standard docking programs are not well suited to tackle the unique challenges of TPS, like the many chemical steps which form multiple stereo-centers, the weak dispersion interactions between the isoprenoid chain and the hydrophobic region of the active site, description of carbocation intermediates, and finding mechanistically meaningful sets of docked poses. To address these and other unique challenges, we developed the multistate, multiscale docking program EnzyDock and used it to study many TPS and other enzymes. In this review we discuss the unique challenges of TPS, the special features of EnzyDock developed to address these challenges and demonstrate its successful use in ongoing research on the bacterial TPS CotB2.
Collapse
Affiliation(s)
- Renana Schwartz
- Department of Chemistry and Institute for Nanotechnology Advanced Materials, Bar Ilan University, Ramat Gan, Israel
| | - Shani Zev
- Department of Chemistry and Institute for Nanotechnology Advanced Materials, Bar Ilan University, Ramat Gan, Israel
| | - Dan T Major
- Department of Chemistry and Institute for Nanotechnology Advanced Materials, Bar Ilan University, Ramat Gan, Israel.
| |
Collapse
|
2
|
Bieniek MK, Cree B, Pirie R, Horton JT, Tatum NJ, Cole DJ. An open-source molecular builder and free energy preparation workflow. Commun Chem 2022; 5:136. [PMID: 36320862 PMCID: PMC9607723 DOI: 10.1038/s42004-022-00754-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 10/11/2022] [Indexed: 01/27/2023] Open
Abstract
Automated free energy calculations for the prediction of binding free energies of congeneric series of ligands to a protein target are growing in popularity, but building reliable initial binding poses for the ligands is challenging. Here, we introduce the open-source FEgrow workflow for building user-defined congeneric series of ligands in protein binding pockets for input to free energy calculations. For a given ligand core and receptor structure, FEgrow enumerates and optimises the bioactive conformations of the grown functional group(s), making use of hybrid machine learning/molecular mechanics potential energy functions where possible. Low energy structures are optionally scored using the gnina convolutional neural network scoring function, and output for more rigorous protein-ligand binding free energy predictions. We illustrate use of the workflow by building and scoring binding poses for ten congeneric series of ligands bound to targets from a standard, high quality dataset of protein-ligand complexes. Furthermore, we build a set of 13 inhibitors of the SARS-CoV-2 main protease from the literature, and use free energy calculations to retrospectively compute their relative binding free energies. FEgrow is freely available at https://github.com/cole-group/FEgrow, along with a tutorial.
Collapse
Affiliation(s)
- Mateusz K. Bieniek
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU UK
| | - Ben Cree
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU UK
| | - Rachael Pirie
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU UK
| | - Joshua T. Horton
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU UK
| | - Natalie J. Tatum
- Newcastle University Centre for Cancer, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH UK
| | - Daniel J. Cole
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU UK
| |
Collapse
|
3
|
Saikia S, Bordoloi M. Molecular Docking: Challenges, Advances and its Use in Drug Discovery Perspective. Curr Drug Targets 2020; 20:501-521. [PMID: 30360733 DOI: 10.2174/1389450119666181022153016] [Citation(s) in RCA: 203] [Impact Index Per Article: 50.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 06/08/2018] [Accepted: 08/28/2018] [Indexed: 01/21/2023]
Abstract
Molecular docking is a process through which small molecules are docked into the macromolecular structures for scoring its complementary values at the binding sites. It is a vibrant research area with dynamic utility in structure-based drug-designing, lead optimization, biochemical pathway and for drug designing being the most attractive tools. Two pillars for a successful docking experiment are correct pose and affinity prediction. Each program has its own advantages and drawbacks with respect to their docking accuracy, ranking accuracy and time consumption so a general conclusion cannot be drawn. Moreover, users don't always consider sufficient diversity in their test sets which results in certain programs to outperform others. In this review, the prime focus has been laid on the challenges of docking and troubleshooters in existing programs, underlying algorithmic background of docking, preferences regarding the use of docking programs for best results illustrated with examples, comparison of performance for existing tools and algorithms, state of art in docking, recent trends of diseases and current drug industries, evidence from clinical trials and post-marketing surveillance are discussed. These aspects of the molecular drug designing paradigm are quite controversial and challenging and this review would be an asset to the bioinformatics and drug designing communities.
Collapse
Affiliation(s)
- Surovi Saikia
- Natural Products Chemistry Group, CSIR North East Institute of Science & Technology, Jorhat-785006, Assam, India
| | - Manobjyoti Bordoloi
- Natural Products Chemistry Group, CSIR North East Institute of Science & Technology, Jorhat-785006, Assam, India
| |
Collapse
|
4
|
Spiegel JO, Durrant JD. AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization. J Cheminform 2020; 12:25. [PMID: 33431021 PMCID: PMC7165399 DOI: 10.1186/s13321-020-00429-4] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 03/31/2020] [Indexed: 02/06/2023] Open
Abstract
We here present AutoGrow4, an open-source program for semi-automated computer-aided drug discovery. AutoGrow4 uses a genetic algorithm to evolve predicted ligands on demand and so is not limited to a virtual library of pre-enumerated compounds. It is a useful tool for generating entirely novel drug-like molecules and for optimizing preexisting ligands. By leveraging recent computational and cheminformatics advancements, AutoGrow4 is faster, more stable, and more modular than previous versions. It implements new docking-program compatibility, chemical filters, multithreading options, and selection methods to support a wide range of user needs. To illustrate both de novo design and lead optimization, we here apply AutoGrow4 to the catalytic domain of poly(ADP-ribose) polymerase 1 (PARP-1), a well characterized DNA-damage-recognition protein. AutoGrow4 produces drug-like compounds with better predicted binding affinities than FDA-approved PARP-1 inhibitors (positive controls). The predicted binding modes of the AutoGrow4 compounds mimic those of the known inhibitors, even when AutoGrow4 is seeded with random small molecules. AutoGrow4 is available under the terms of the Apache License, Version 2.0. A copy can be downloaded free of charge from http://durrantlab.com/autogrow4.
Collapse
Affiliation(s)
- Jacob O. Spiegel
- Department of Biological Sciences, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA 15260 USA
| | - Jacob D. Durrant
- Department of Biological Sciences, University of Pittsburgh, 4200 Fifth Ave, Pittsburgh, PA 15260 USA
| |
Collapse
|
5
|
Chen X, Liu H, Xie W, Yang Y, Wang Y, Fan Y, Hua Y, Zhu L, Zhao J, Lu T, Chen Y, Zhang Y. Investigation of Crystal Structures in Structure-Based Virtual Screening for Protein Kinase Inhibitors. J Chem Inf Model 2019; 59:5244-5262. [PMID: 31689093 DOI: 10.1021/acs.jcim.9b00684] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Protein kinases are important drug targets in several therapeutic areas ,and structure-based virtual screening (SBVS) is an important strategy in discovering lead compounds for kinase targets. However, there are multiple crystal structures available for each target, and determining which one is the most favorable is a key step in molecular docking for SBVS due to the ligand induce-fit effect. This work aimed to find the most desirable crystal structures for molecular docking by a comprehensive analysis of the protein kinase database which covers 190 different kinases from all eight main kinase families. Through an integrated self-docking and cross-docking evaluation, 86 targets were eventually evaluated on a total of 2608 crystal structures. Results showed that molecular docking has great capability in reproducing conformation of crystallized ligands and for each target, the most favorable crystal structure was selected, and the AGC family outperformed the other family targets based on RMSD comparison. In addition, RMSD values, GlideScore, and corresponding bioactivity data were compared and demonstrated certain relationships. This work provides great convenience for researchers to directly select the optimal crystal structure in SBVS-based kinase drug design and further validates the effectiveness of molecular docking in drug discovery.
Collapse
Affiliation(s)
- Xingye Chen
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Haichun Liu
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Wuchen Xie
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Yan Yang
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Yuchen Wang
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Yuanrong Fan
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Yi Hua
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Lu Zhu
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Junnan Zhao
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Tao Lu
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China.,State Key Laboratory of Natural Medicines , China Pharmaceutical University , 24 Tongjiaxiang , Nanjing 210009 , China
| | - Yadong Chen
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| | - Yanmin Zhang
- Laboratory of Molecular Design and Drug Discovery, School of Science , China Pharmaceutical University , 639 Longmian Avenue , Nanjing 211198 , China
| |
Collapse
|
6
|
Das S, Shimshi M, Raz K, Nitoker Eliaz N, Mhashal AR, Ansbacher T, Major DT. EnzyDock: Protein–Ligand Docking of Multiple Reactive States along a Reaction Coordinate in Enzymes. J Chem Theory Comput 2019; 15:5116-5134. [DOI: 10.1021/acs.jctc.9b00366] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Susanta Das
- Department of Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel
| | - Mor Shimshi
- Department of Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel
| | - Keren Raz
- Department of Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel
| | | | - Anil Ranu Mhashal
- Department of Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel
| | - Tamar Ansbacher
- Department of Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel
- Hadassah Academic College, 7 Hanevi’im Street, Jerusalem 9101001, Israel
| | - Dan T. Major
- Department of Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel
| |
Collapse
|
7
|
Sommer K, Flachsenberg F, Rarey M. NAOMInext – Synthetically feasible fragment growing in a structure-based design context. Eur J Med Chem 2019; 163:747-762. [DOI: 10.1016/j.ejmech.2018.11.075] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Revised: 11/27/2018] [Accepted: 11/30/2018] [Indexed: 12/31/2022]
|
8
|
Duffy F, Maheshwari N, Buchete NV, Shields D. Computational Opportunities and Challenges in Finding Cyclic Peptide Modulators of Protein-Protein Interactions. Methods Mol Biol 2019; 2001:73-95. [PMID: 31134568 DOI: 10.1007/978-1-4939-9504-2_5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Peptide cyclization can improve stability, conformational constraint, and compactness. However, apart from beta-turn structures, which are well incorporated into cyclic peptides (CPs), many primary peptide structures and functions are markedly altered by cyclization. Accordingly, to mimic linear peptide interfaces with cyclic peptides, it can be beneficial to screen combinatorial cyclic peptide libraries. Computational methods have been developed to screen CPs, but face a number of challenges. Here, we review methods to develop in silico computational libraries, and the potential for screening naturally occurring libraries of CPs. The simplest and most rapid computational pharmacophore methods that estimate peptide three-dimensional structures to be screened versus targets are relatively easy to implement, and while the constraint on structure imposed by cyclization makes them more effective than the same approaches with linear peptides, there are a large number of limiting assumptions. In contrast, full molecular dynamics simulations of cyclic peptide structures not only are costly to implement, but also require careful attention to interpretation, so that not only is the computation time rate limiting, but the interpretation time is also rate limiting due to the analysis of the typically complex underlying conformational space of CPs. A challenge for the field of computational cyclic peptide screening is to bridge this gap effectively. Natural compound libraries of short cyclic peptides, and short cyclized regions of proteins, encoded in the genomes of many organisms present a potential treasure trove of novel functionality which may be screened via combined computational and experimental screening approaches.
Collapse
Affiliation(s)
- Fergal Duffy
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland.,UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
| | - Nikunj Maheshwari
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland.,UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
| | | | - Denis Shields
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland. .,UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.
| |
Collapse
|
9
|
Kooistra AJ, Vass M, McGuire R, Leurs R, de Esch IJP, Vriend G, Verhoeven S, de Graaf C. 3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery. ChemMedChem 2018; 13:614-626. [PMID: 29337438 PMCID: PMC5900740 DOI: 10.1002/cmdc.201700754] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 01/11/2018] [Indexed: 01/06/2023]
Abstract
eScience technologies are needed to process the information available in many heterogeneous types of protein-ligand interaction data and to capture these data into models that enable the design of efficacious and safe medicines. Here we present scientific KNIME tools and workflows that enable the integration of chemical, pharmacological, and structural information for: i) structure-based bioactivity data mapping, ii) structure-based identification of scaffold replacement strategies for ligand design, iii) ligand-based target prediction, iv) protein sequence-based binding site identification and ligand repurposing, and v) structure-based pharmacophore comparison for ligand repurposing across protein families. The modular setup of the workflows and the use of well-established standards allows the re-use of these protocols and facilitates the design of customized computer-aided drug discovery workflows.
Collapse
Affiliation(s)
- Albert J. Kooistra
- Centre for Molecular and Biomolecular Informatics (CMBI)Radboud University Medical Center (RadboudUMC)NijmegenThe Netherlands
- Division of Medicinal Chemistry, Faculty of Science, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS)Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Márton Vass
- Division of Medicinal Chemistry, Faculty of Science, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS)Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Ross McGuire
- Centre for Molecular and Biomolecular Informatics (CMBI)Radboud University Medical Center (RadboudUMC)NijmegenThe Netherlands
- BioAxis Research, Pivot ParkOssThe Netherlands
| | - Rob Leurs
- Division of Medicinal Chemistry, Faculty of Science, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS)Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Iwan J. P. de Esch
- Division of Medicinal Chemistry, Faculty of Science, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS)Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Gert Vriend
- Centre for Molecular and Biomolecular Informatics (CMBI)Radboud University Medical Center (RadboudUMC)NijmegenThe Netherlands
| | | | - Chris de Graaf
- Division of Medicinal Chemistry, Faculty of Science, Amsterdam Institute for Molecules, Medicines and Systems (AIMMS)Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| |
Collapse
|
10
|
Liu T, Liu X, Xiong H, Xu C, Yao J, Zhu X, Zhou J, Yao J. Mechanisms of TPGS and its derivatives inhibiting P-glycoprotein efflux pump and application for reversing multidrug resistance in hepatocellular carcinoma. Polym Chem 2018. [DOI: 10.1039/c8py00344k] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We have developed a TPGS–GA conjugate and TPGS–LA conjugate which possess more effective P-gp inhibition compared to TPGS because of the enhancement of hydrophilicity and negative charge.
Collapse
Affiliation(s)
- Tengfei Liu
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Ability of Biopharmaceuticals
- Department of Pharmaceutics
- China Pharmaceutical University
- Nanjing 210009
- PR China
| | - Xiaoyan Liu
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Ability of Biopharmaceuticals
- Department of Pharmaceutics
- China Pharmaceutical University
- Nanjing 210009
- PR China
| | - Hui Xiong
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Ability of Biopharmaceuticals
- Department of Pharmaceutics
- China Pharmaceutical University
- Nanjing 210009
- PR China
| | - Cheng Xu
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Ability of Biopharmaceuticals
- Department of Pharmaceutics
- China Pharmaceutical University
- Nanjing 210009
- PR China
| | - Jianxu Yao
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Ability of Biopharmaceuticals
- Department of Pharmaceutics
- China Pharmaceutical University
- Nanjing 210009
- PR China
| | - Xiumei Zhu
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Ability of Biopharmaceuticals
- Department of Pharmaceutics
- China Pharmaceutical University
- Nanjing 210009
- PR China
| | - Jianping Zhou
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Ability of Biopharmaceuticals
- Department of Pharmaceutics
- China Pharmaceutical University
- Nanjing 210009
- PR China
| | - Jing Yao
- State Key Laboratory of Natural Medicines and Jiangsu Key Laboratory of Drug Ability of Biopharmaceuticals
- Department of Pharmaceutics
- China Pharmaceutical University
- Nanjing 210009
- PR China
| |
Collapse
|
11
|
Li L, Liu J, Nie S, Ding L, Wang L, Liu J, Liu W, Zhang T. Direct inhibition of Keap1–Nrf2 interaction by egg-derived peptides DKK and DDW revealed by molecular docking and fluorescence polarization. RSC Adv 2017. [DOI: 10.1039/c7ra04352j] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
DKK and DDW, egg-derived direct inhibitors of the Keap1–Nrf2 interaction, screening by fluorescence polarization assays and cell experiments.
Collapse
Affiliation(s)
- Liangyu Li
- Jilin Key Laboratory of Nutrition and Functional Food
- Jilin University
- Changchun 130062
- People's Republic of China
| | - Jingbo Liu
- Jilin Key Laboratory of Nutrition and Functional Food
- Jilin University
- Changchun 130062
- People's Republic of China
| | - Shaoping Nie
- State Key Laboratory Food Science & Technology
- Nanchang University
- Nanchang 330047
- People's Republic of China
| | - Long Ding
- Jilin Key Laboratory of Nutrition and Functional Food
- Jilin University
- Changchun 130062
- People's Republic of China
| | - Liying Wang
- Jilin Key Laboratory of Nutrition and Functional Food
- Jilin University
- Changchun 130062
- People's Republic of China
| | - Jiyun Liu
- Jilin Key Laboratory of Nutrition and Functional Food
- Jilin University
- Changchun 130062
- People's Republic of China
| | - Wenchao Liu
- Jilin Key Laboratory of Nutrition and Functional Food
- Jilin University
- Changchun 130062
- People's Republic of China
| | - Ting Zhang
- Jilin Key Laboratory of Nutrition and Functional Food
- Jilin University
- Changchun 130062
- People's Republic of China
| |
Collapse
|
12
|
Han J, Chen Y, Yang C, Liu T, Wang M, Xu H, Zhang L, Zheng C, Song Y, Zhu J. Structure-based optimization leads to the discovery of NSC765844, a highly potent, less toxic and orally efficacious dual PI3K/mTOR inhibitor. Eur J Med Chem 2016; 122:684-701. [DOI: 10.1016/j.ejmech.2016.06.030] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2016] [Revised: 06/16/2016] [Accepted: 06/17/2016] [Indexed: 01/01/2023]
|
13
|
Bazgier V, Berka K, Otyepka M, Banáš P. Exponential repulsion improves structural predictability of molecular docking. J Comput Chem 2016; 37:2485-94. [PMID: 27620738 DOI: 10.1002/jcc.24473] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Revised: 06/21/2016] [Accepted: 07/16/2016] [Indexed: 01/13/2023]
Abstract
Molecular docking is a powerful tool for theoretical prediction of the preferred conformation and orientation of small molecules within protein active sites. The obtained poses can be used for estimation of binding energies, which indicate the inhibition effect of designed inhibitors, and therefore might be used for in silico drug design. However, the evaluation of ligand binding affinity critically depends on successful prediction of the native binding mode. Contemporary docking methods are often based on scoring functions derived from molecular mechanical potentials. In such potentials, nonbonded interactions are typically represented by electrostatic interactions between atom-centered partial charges and standard 6-12 Lennard-Jones potential. Here, we present implementation and testing of a scoring function based on more physically justified exponential repulsion instead of the standard Lennard-Jones potential. We found that this scoring function significantly improved prediction of the native binding modes in proteins bearing narrow active sites such as serine proteases and kinases. © 2016 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Václav Bazgier
- Laboratory of Growth Regulators, Centre of the Region Haná for Biotechnological and Agricultural Research, Institute of Experimental Botany ASCR & Palacky University, Šlechtitelů 11, Olomouc, 783 71, Czech Republic.,Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc, 17. listopadu 12, Olomouc, 77146, Czech Republic
| | - Karel Berka
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc, 17. listopadu 12, Olomouc, 77146, Czech Republic
| | - Michal Otyepka
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc, 17. listopadu 12, Olomouc, 77146, Czech Republic
| | - Pavel Banáš
- Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc, 17. listopadu 12, Olomouc, 77146, Czech Republic.
| |
Collapse
|
14
|
Chen X, Lu Y, Tan G, Cao Z, Liu W, Wang B, Zhang M, Li Z. Functional and binding characterization of a single chain Fv antibody to abscisic acid and conjugated abscisic acid. FOOD AGR IMMUNOL 2016. [DOI: 10.1080/09540105.2016.1148123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Affiliation(s)
- Xiaojiao Chen
- College of Agriculture and Biotechnology, China Agricultural University, Beijing, China
| | - Yao Lu
- Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Guiyu Tan
- College of Agriculture and Biotechnology, China Agricultural University, Beijing, China
| | - Zhen Cao
- Department of Molecular Biosciences and Bioengineering, University of Hawaii, Honolulu, HI, USA
| | - Wei Liu
- College of Agriculture and Biotechnology, China Agricultural University, Beijing, China
| | - Baomin Wang
- College of Agriculture and Biotechnology, China Agricultural University, Beijing, China
| | - Mingcai Zhang
- College of Agriculture and Biotechnology, China Agricultural University, Beijing, China
| | - Zhaohu Li
- College of Agriculture and Biotechnology, China Agricultural University, Beijing, China
| |
Collapse
|
15
|
Chéron N, Jasty N, Shakhnovich EI. OpenGrowth: An Automated and Rational Algorithm for Finding New Protein Ligands. J Med Chem 2015; 59:4171-88. [DOI: 10.1021/acs.jmedchem.5b00886] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Nicolas Chéron
- Department of Chemistry and
Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Naveen Jasty
- Department of Chemistry and
Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Eugene I. Shakhnovich
- Department of Chemistry and
Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, United States
| |
Collapse
|
16
|
Duffy FJ, Devocelle M, Shields DC. Computational approaches to developing short cyclic peptide modulators of protein-protein interactions. Methods Mol Biol 2015; 1268:241-71. [PMID: 25555728 DOI: 10.1007/978-1-4939-2285-7_11] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Cyclic peptides are a promising class of bioactive molecules potentially capable of modulating "difficult" targets, such as protein-protein interactions. Cyclic peptides have long been used as therapeutics derived from natural product derivatives, but remain an underexplored class of compounds from the perspective of rational drug design, possibly due to the known weaknesses of peptide drugs in general. While cyclic peptides are non"druglike" by the accepted empirical rules, their unique structure may lend itself to both membrane permeability and proteolytic resistance-the main barriers to oral delivery. The constrained shape of cyclic peptides also lends itself better to virtual screening approaches, and new tools and successes in this area have been recently noted. An increasing number of strategies are available, both to generate and screen cyclic peptide libraries, and best practises and current successes are described within. This chapter will describe various computational strategies for virtual screening cyclic peptides, along with known implementations and applications. We will explore the generation and screening of diverse combinatorial virtual libraries, incorporating a range of cyclization strategies and structural modifications. More advanced approaches covered include evolutionary algorithms designed to aid in screening large structural libraries, machine learning approaches, and harnessing bioinformatics resources to bias cyclic peptide virtual libraries towards known bioactive structures.
Collapse
Affiliation(s)
- Fergal J Duffy
- School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland
| | | | | |
Collapse
|
17
|
Abstract
Docking methodology aims to predict the experimental binding modes and affinities of small molecules within the binding site of particular receptor targets and is currently used as a standard computational tool in drug design for lead compound optimisation and in virtual screening studies to find novel biologically active molecules. The basic tools of a docking methodology include a search algorithm and an energy scoring function for generating and evaluating ligand poses. In this review, we present the search algorithms and scoring functions most commonly used in current molecular docking methods that focus on protein-ligand applications. We summarise the main topics and recent computational and methodological advances in protein-ligand docking. Protein flexibility, multiple ligand binding modes and the free-energy landscape profile for binding affinity prediction are important and interconnected challenges to be overcome by further methodological developments in the docking field.
Collapse
|
18
|
Boyd SM, Turnbull AP, Walse B. Fragment library design considerations. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2012. [DOI: 10.1002/wcms.1098] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
|
19
|
Mahmoud AH, Mohamed Abouzid KA, El Ella DAERA, Hamid Ismail MA. Optimization of Benzoisothiazole dioxide inhibitory activity of the NS5B polymerase of HCV genotype 4 using ligand-steered homological modeling, reaction-driven scaffold-hopping and Enovo workflow. Bioinformation 2011; 7:328-33. [PMID: 22355232 PMCID: PMC3280486 DOI: 10.6026/97320630007328] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2011] [Accepted: 11/18/2011] [Indexed: 11/27/2022] Open
Abstract
Infection caused by hepatitis C virus (HCV) is a significant world health problem for which novel therapies are in urgent demand. The virus is highly prevalent in the Middle East and Africa particularly Egypt with more than 90% of infections due to genotype 4. Nonstructural (NS5B) viral proteins have emerged as an attractive target for HCV antivirals discovery. A potent class of inhibitors having benzisothiazole dioxide scaffold has been identified on this target, however they were mainly active on genotype 1 while exhibiting much lowered activity on other genotypes due to the high degree of mutation of its binding site. Based on this fact, we employed a novel strategy to optimize this class on genotype 4. This strategy depends on using a refined ligand-steered homological model of this genotype to study the mutation binding energies of the binding site amino acid residues, the essential features for interaction and provide a structure-based pharmacophore model that can aid optimization. This model was applied on a focused library which was generated using a reaction-driven scaffold-hopping strategy. The hits retrieved were subjected to Enovo pipeline pilot optimization workflow that employs R-group enumeration, core-constrained protein docking using modified CDOCKER and finally ranking of poses using an accurate molecular mechanics generalized Born with surface area method.
Collapse
Affiliation(s)
- Amr Hamed Mahmoud
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Ain Shams University, Cairo 11566, Egypt
| | | | | | | |
Collapse
|
20
|
Lippert T, Schulz-Gasch T, Roche O, Guba W, Rarey M. De novo design by pharmacophore-based searches in fragment spaces. J Comput Aided Mol Des 2011; 25:931-45. [DOI: 10.1007/s10822-011-9473-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2011] [Accepted: 09/05/2011] [Indexed: 01/29/2023]
|
21
|
Abreu RMV, Froufe HJC, Daniel POM, Queiroz MJRP, Ferreira ICFR. ChemT, an open-source software for building template-based chemical libraries. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2011; 22:603-610. [PMID: 21846264 DOI: 10.1080/1062936x.2011.604097] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
In computational chemistry, vast quantities of compounds are generated, and there is a need for cheminformatic tools to efficiently build chemical compound libraries. Several software tools for drawing and editing compound structures are available, but they lack options for automatic generation of chemical libraries. We have implemented ChemT, an easy-to-use open-source software tool that automates the process of preparing custom-made template-based chemical libraries. ChemT automatically generates three-dimensional chemical libraries by inputting a chemical template and the functional groups of interest. The graphical user interface of ChemT is self-explanatory, and a complete tutorial is provided. Several file formats are accepted by ChemT, and it is possible to filter the generated compounds according to different physicochemical properties. The compounds can be subject to force field minimization, and the resulting three-dimensional structures recorded on commonly used file formats. ChemT may be a valuable tool for investigators interested in using in silico virtual screening tools, such as quantitative structure-activity relationship modelling or molecular docking, in order to prioritize compounds for further chemical synthesis. To demonstrate the usefulness of ChemT, we describe an example based on a thieno[3,2-b]pyridine template. ChemT is available free of charge from our website at http://www.esa.ipb.pt/~ruiabreu/chemt .
Collapse
Affiliation(s)
- R M V Abreu
- CIMO-ESA, Instituto Politécnico de Bragança, Campus de Sta Apolónia, Apartado 1172, 5301-855 Bragança, Portugal.
| | | | | | | | | |
Collapse
|
22
|
Li Y, Zhao Y, Liu Z, Wang R. Automatic Tailoring and Transplanting: A Practical Method that Makes Virtual Screening More Useful. J Chem Inf Model 2011; 51:1474-91. [DOI: 10.1021/ci200036m] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Yan Li
- State Key Laboratory of Bioorganic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People's Republic of China
| | - Yuan Zhao
- State Key Laboratory of Bioorganic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People's Republic of China
| | - Zhihai Liu
- State Key Laboratory of Bioorganic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People's Republic of China
| | - Renxiao Wang
- State Key Laboratory of Bioorganic Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People's Republic of China
| |
Collapse
|
23
|
Dobeš P, Fanfrlík J, Řezáč J, Otyepka M, Hobza P. Transferable scoring function based on semiempirical quantum mechanical PM6-DH2 method: CDK2 with 15 structurally diverse inhibitors. J Comput Aided Mol Des 2011; 25:223-35. [DOI: 10.1007/s10822-011-9413-5] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2010] [Accepted: 01/18/2011] [Indexed: 11/30/2022]
|
24
|
Stark JL, Powers R. Application of NMR and molecular docking in structure-based drug discovery. Top Curr Chem (Cham) 2011; 326:1-34. [PMID: 21915777 DOI: 10.1007/128_2011_213] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Drug discovery is a complex and costly endeavor, where few drugs that reach the clinical testing phase make it to market. High-throughput screening (HTS) is the primary method used by the pharmaceutical industry to identify initial lead compounds. Unfortunately, HTS has a high failure rate and is not particularly efficient at identifying viable drug leads. These shortcomings have encouraged the development of alternative methods to drive the drug discovery process. Specifically, nuclear magnetic resonance (NMR) spectroscopy and molecular docking are routinely being employed as important components of drug discovery research. Molecular docking provides an extremely rapid way to evaluate likely binders from a large chemical library with minimal cost. NMR ligand-affinity screens can directly detect a protein-ligand interaction, can measure a corresponding dissociation constant, and can reliably identify the ligand binding site and generate a co-structure. Furthermore, NMR ligand affinity screens and molecular docking are perfectly complementary techniques, where the combination of the two has the potential to improve the efficiency and success rate of drug discovery. This review will highlight the use of NMR ligand affinity screens and molecular docking in drug discovery and describe recent examples where the two techniques were combined to identify new and effective therapeutic drugs.
Collapse
Affiliation(s)
- Jaime L Stark
- Department of Chemistry, University of Nebraska, Lincoln, NE 68588-0304, USA
| | | |
Collapse
|
25
|
Yuriev E, Agostino M, Ramsland PA. Challenges and advances in computational docking: 2009 in review. J Mol Recognit 2010; 24:149-64. [DOI: 10.1002/jmr.1077] [Citation(s) in RCA: 223] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2010] [Revised: 07/20/2010] [Accepted: 07/21/2010] [Indexed: 12/12/2022]
|
26
|
Kutchukian PS, Shakhnovich EI. De novo design: balancing novelty and confined chemical space. Expert Opin Drug Discov 2010; 5:789-812. [PMID: 22827800 DOI: 10.1517/17460441.2010.497534] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
IMPORTANCE OF THE FIELD De novo drug design serves as a tool for the discovery of new ligands for macromolecular targets as well as optimization of known ligands. Recently developed tools aim to address the multi-objective nature of drug design in an unprecedented manner. AREAS COVERED IN THIS REVIEW This article discusses recent advances in de novo drug design programs and accessory programs used to evaluate compounds post-generation. WHAT THE READER WILL GAIN The reader is introduced to the challenges inherent in de novo drug design and will become familiar with current trends in de novo design. Furthermore, the reader will be better prepared to assess the value of a tool, and be equipped to design more elegant tools in the future. TAKE HOME MESSAGE De novo drug design can assist in the efficient discovery of new compounds with a high affinity for a given target. The inclusion of existing chemoinformatic methods with current structure-based de novo design tools provides a means of enhancing the therapeutic value of these generated compounds.
Collapse
Affiliation(s)
- Peter S Kutchukian
- Harvard University, Chemistry and Chemical Biology Department, 12 Oxford Street, Cambridge, MA 02138, USA
| | | |
Collapse
|
27
|
Joubert MK, Kinsley N, Capovilla A, Sewell BT, Jaffer MA, Khati M. A Modeled Structure of an Aptamer−gp120 Complex Provides Insight into the Mechanism of HIV-1 Neutralization. Biochemistry 2010; 49:5880-90. [DOI: 10.1021/bi100301k] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Nichole Kinsley
- Elevation Biotech, 8 Blackwood Avenue, Parktown, Johannesburg 2193, South Africa
| | - Alexio Capovilla
- Elevation Biotech, 8 Blackwood Avenue, Parktown, Johannesburg 2193, South Africa
- Department of Molecular Medicine and Haematology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South Africa
| | - B. Trevor Sewell
- Electron Microscope Unit, University of Cape Town, Rondebosch 7701, South Africa
| | - Mohamed A. Jaffer
- Electron Microscope Unit, University of Cape Town, Rondebosch 7701, South Africa
| | - Makobetsa Khati
- CSIR Biosciences, P.O. Box 395, Pretoria 0001, South Africa
- Department of Medicine, Groote Schuur Hospital and University of Cape Town, Cape Town, South Africa
| |
Collapse
|
28
|
Kore AR, Shanmugasundaram M, Charles I, Hoang Q. Synthesis and biological evaluation of modified pentapeptides as potent proteinase K inhibitors. Bioorg Med Chem Lett 2010; 20:2750-4. [PMID: 20378349 DOI: 10.1016/j.bmcl.2010.03.072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2010] [Revised: 03/17/2010] [Accepted: 03/17/2010] [Indexed: 11/19/2022]
Abstract
This communication reports the first demonstration of synthesis and biological validation of modified pentapeptides, such as methoxysuccinyl-Ala-Ala-Ala-Pro-Leu-chloromethyl ketone 6b as a potent proteinase K inhibitor. The efficacy of MeOSuc-AAAPL-CH(2)Cl 6b analog in inhibiting the proteolytic activity of proteinase K was compared with the known MeOSuc-AAPV-CH(2)Cl analog. The examination of inhibitory activity using RT-PCR assay in the presence of proteinase K revealed that the MeOSuc-AAAPL-CH(2)Cl 6b inhibitor at a concentration of 0.05 mM allows a signal to be obtained for an exogenous target ('Xeno RNA') at 30 cycles (i.e., Ct=30), whereas the control MeOSuc-AAPV-CH(2)Cl requires a fivefold higher concentration (0.25 mM) to produce the same Ct. A plausible explanation for the higher efficiency of MeOSuc-AAAPL-CH(2)Cl 6b over control is proposed based on the molecular modeling studies.
Collapse
Affiliation(s)
- Anilkumar R Kore
- Life Technologies Corporation, Bioorganic Chemistry Division, 2130 Woodward Street, Austin, TX 78744-1832, USA.
| | | | | | | |
Collapse
|
29
|
Compound Collection Enhancement and Paradigms for High-Throughput Screening — an Update. ANNUAL REPORTS IN MEDICINAL CHEMISTRY 2010. [DOI: 10.1016/s0065-7743(10)45025-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/05/2023]
|