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Abstract
Structure-based drug discovery has become a promising and efficient approach for
identifying novel and potent drug candidates with less time and cost than conventional drug
discovery approaches. It has been widely used in the pharmaceutical industry since it uses the 3D
structure of biological protein targets and thereby allows us to understand the molecular basis of
diseases. For the virtual identification of drug candidates based on structure, there are a few steps for
protein and compound preparations to obtain accurate results. In this review, the software and webtools
for the preparation and structure-based simulation are introduced. In addition, recent
improvements in structure-based virtual screening, target library designing for virtual screening,
docking, scoring, and post-processing of top hits are also introduced.
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Affiliation(s)
- Bilal Shaker
- School of Integrative Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul, Korea
| | - Kha Mong Tran
- School of Integrative Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul, Korea
| | - Chanjin Jung
- School of Integrative Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul, Korea
| | - Dokyun Na
- School of Integrative Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul, Korea
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2
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Trosset JY, Cavé C. In Silico Target Druggability Assessment: From Structural to Systemic Approaches. Methods Mol Biol 2019; 1953:63-88. [PMID: 30912016 DOI: 10.1007/978-1-4939-9145-7_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: 01/10/2023]
Abstract
This chapter will focus on today's in silico direct and indirect approaches to assess therapeutic target druggability. The direct approach tries to infer from the 3D structure the capacity of the target protein to bind small molecule in order to modulate its biological function. Algorithms to recognize and characterize the quality of the ligand interaction sites whether within buried protein cavities or within large protein-protein interface will be reviewed in the first part of the paper. In the case a ligand-binding site is already identified, indirect aspects of target druggability can be assessed. These indirect approaches focus first on target promiscuity and the potential difficulties in developing specific drugs. It is based on large-scale comparison of protein-binding sites. The second aspect concerns the capacity of the target to induce resistant pathway once it is inhibited or activated by a drug. The emergence of drug-resistant pathways can be assessed through systemic analysis of biological networks implementing metabolism and/or cell regulation signaling.
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Affiliation(s)
| | - Christian Cavé
- BioCIS UFR Pharmacie UMR CNRS 8076, Université Paris Saclay, Orsay, France
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3
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Abstract
Following the elucidation of the human genome, chemogenomics emerged in the beginning of the twenty-first century as an interdisciplinary research field with the aim to accelerate target and drug discovery by making best usage of the genomic data and the data linkable to it. What started as a systematization approach within protein target families now encompasses all types of chemical compounds and gene products. A key objective of chemogenomics is the establishment, extension, analysis, and prediction of a comprehensive SAR matrix which by application will enable further systematization in drug discovery. Herein we outline future perspectives of chemogenomics including the extension to new molecular modalities, or the potential extension beyond the pharma to the agro and nutrition sectors, and the importance for environmental protection. The focus is on computational sciences with potential applications for compound library design, virtual screening, hit assessment, analysis of phenotypic screens, lead finding and optimization, and systems biology-based prediction of toxicology and translational research.
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Affiliation(s)
- Edgar Jacoby
- Janssen Research & Development, Beerse, Belgium.
| | - J B Brown
- Life Science Informatics Research Unit, Laboratory of Molecular Biosciences, Kyoto University Graduate School of Medicine, Kyoto, Japan
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Jacoby E, Wroblowski B, Buyck C, Neefs JM, Meyer C, Cummings MD, van Vlijmen H. Protocols for the Design of Kinase-focused Compound Libraries. Mol Inform 2017; 37:e1700119. [PMID: 29116686 DOI: 10.1002/minf.201700119] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 10/20/2017] [Indexed: 01/12/2023]
Abstract
Protocols for the design of kinase-focused compound libraries are presented. Kinase-focused compound libraries can be differentiated based on the design goal. Depending on whether the library should be a discovery library specific for one particular kinase, a general discovery library for multiple distinct kinase projects, or even phenotypic screening, there exists today a variety of in silico methods to design candidate compound libraries. We address the following scenarios: 1) Datamining of SAR databases and kinase focused vendor catalogues; 2) Predictions and virtual screening; 3) Structure-based design of combinatorial kinase inhibitors; 4) Design of covalent kinase inhibitors; 5) Design of macrocyclic kinase inhibitors; and 6) Design of allosteric kinase inhibitors and activators.
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Affiliation(s)
- Edgar Jacoby
- Janssen Research & Development, Turnhoutseweg 30, 2340, Beerse, Belgium
| | | | - Christophe Buyck
- Janssen Research & Development, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - Jean-Marc Neefs
- Janssen Research & Development, Turnhoutseweg 30, 2340, Beerse, Belgium
| | | | - Maxwell D Cummings
- Janssen Research & Development, 1400 McKean Rd, Spring House, PA 19477, USA
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5
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Abstract
Drug discovery utilizes chemical biology and computational drug design approaches for the efficient identification and optimization of lead compounds. Chemical biology is mostly involved in the elucidation of the biological function of a target and the mechanism of action of a chemical modulator. On the other hand, computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the determination of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are critical for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with experimental routines, has a powerful impact on rational drug design. In this article, we give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.
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Affiliation(s)
- Stephani Joy Y Macalino
- National Leading Research Laboratory of Molecular Modeling and Drug Design, College of Pharmacy and Graduate School of Pharmaceutical Sciences, and Global Top 5 Research Program, Ewha Womans University, Seoul, 120-750, Korea
| | - Vijayakumar Gosu
- National Leading Research Laboratory of Molecular Modeling and Drug Design, College of Pharmacy and Graduate School of Pharmaceutical Sciences, and Global Top 5 Research Program, Ewha Womans University, Seoul, 120-750, Korea
| | - Sunhye Hong
- National Leading Research Laboratory of Molecular Modeling and Drug Design, College of Pharmacy and Graduate School of Pharmaceutical Sciences, and Global Top 5 Research Program, Ewha Womans University, Seoul, 120-750, Korea
| | - Sun Choi
- National Leading Research Laboratory of Molecular Modeling and Drug Design, College of Pharmacy and Graduate School of Pharmaceutical Sciences, and Global Top 5 Research Program, Ewha Womans University, Seoul, 120-750, Korea.
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Lionta E, Spyrou G, Vassilatis DK, Cournia Z. Structure-based virtual screening for drug discovery: principles, applications and recent advances. Curr Top Med Chem 2015; 14:1923-38. [PMID: 25262799 PMCID: PMC4443793 DOI: 10.2174/1568026614666140929124445] [Citation(s) in RCA: 526] [Impact Index Per Article: 58.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2013] [Revised: 01/01/2014] [Accepted: 02/18/2014] [Indexed: 02/06/2023]
Abstract
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.
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Affiliation(s)
| | | | | | - Zoe Cournia
- Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece.
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Brylinski M. eMatchSite: sequence order-independent structure alignments of ligand binding pockets in protein models. PLoS Comput Biol 2014; 10:e1003829. [PMID: 25232727 PMCID: PMC4168975 DOI: 10.1371/journal.pcbi.1003829] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Accepted: 07/24/2014] [Indexed: 01/26/2023] Open
Abstract
Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4–9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.
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Affiliation(s)
- Michal Brylinski
- Department of Biological Sciences, Louisiana State University, Baton Rouge, Louisiana, United States of America
- Center for Computation & Technology, Louisiana State University, Baton Rouge, Louisiana, United States of America
- * E-mail:
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8
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Abstract
The focus of this chapter is on the important concepts behind the in silico techniques that are used today to assess target druggability. The first step of the assessment consists of finding cavity space in the protein using 2D and/or 3D topological concepts. These concepts underlie the geometry and energy-based pocketfinder algorithms. Analysis pursues on the physico-chemical complementarity between the binding site and the drug like molecule. Geometrical and molecular flexibility aspect are also included in this assessment. The presence of hot interaction spots are shown to be particularly important for targeting protein-protein interactions. Finally, binding site promiscuity can be assessed by large scale structural comparison with other targets. Common chemical features amongst protein cavities can predict potential cross-reactivity with unwanted targets.
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Kochańczyk M. Prediction of functionally important residues in globular proteins from unusual central distances of amino acids. BMC STRUCTURAL BIOLOGY 2011; 11:34. [PMID: 21923943 PMCID: PMC3188475 DOI: 10.1186/1472-6807-11-34] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2011] [Accepted: 09/18/2011] [Indexed: 12/12/2022]
Abstract
BACKGROUND Well-performing automated protein function recognition approaches usually comprise several complementary techniques. Beside constructing better consensus, their predictive power can be improved by either adding or refining independent modules that explore orthogonal features of proteins. In this work, we demonstrated how the exploration of global atomic distributions can be used to indicate functionally important residues. RESULTS Using a set of carefully selected globular proteins, we parametrized continuous probability density functions describing preferred central distances of individual protein atoms. Relative preferred burials were estimated using mixture models of radial density functions dependent on the amino acid composition of a protein under consideration. The unexpectedness of extraordinary locations of atoms was evaluated in the information-theoretic manner and used directly for the identification of key amino acids. In the validation study, we tested capabilities of a tool built upon our approach, called SurpResi, by searching for binding sites interacting with ligands. The tool indicated multiple candidate sites achieving success rates comparable to several geometric methods. We also showed that the unexpectedness is a property of regions involved in protein-protein interactions, and thus can be used for the ranking of protein docking predictions. The computational approach implemented in this work is freely available via a Web interface at http://www.bioinformatics.org/surpresi. CONCLUSIONS Probabilistic analysis of atomic central distances in globular proteins is capable of capturing distinct orientational preferences of amino acids as resulting from different sizes, charges and hydrophobic characters of their side chains. When idealized spatial preferences can be inferred from the sole amino acid composition of a protein, residues located in hydrophobically unfavorable environments can be easily detected. Such residues turn out to be often directly involved in binding ligands or interfacing with other proteins.
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Affiliation(s)
- Marek Kochańczyk
- Faculty of Physics, Jagiellonian University, ul, Reymonta 4, 30-059 Krakow, Poland.
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Moriaud F, Adcock SA, Vorotyntsev A, Doppelt-Azeroual O, Richard SB, Delfaud F. A Computational Fragment Approach by Mining the Protein Data Bank: Library Design and Bioisosterism. LIBRARY DESIGN, SEARCH METHODS, AND APPLICATIONS OF FRAGMENT-BASED DRUG DESIGN 2011. [DOI: 10.1021/bk-2011-1076.ch005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- F. Moriaud
- Felix Concordia SARL, 400 av Roumanille Bât. 7, BP 309 06906 Sophia-Antipolis, France
- MEDIT SA, 2 rue du Belvedere, 91120 Palaiseau, France
| | - S. A. Adcock
- Felix Concordia SARL, 400 av Roumanille Bât. 7, BP 309 06906 Sophia-Antipolis, France
- MEDIT SA, 2 rue du Belvedere, 91120 Palaiseau, France
| | - A. Vorotyntsev
- Felix Concordia SARL, 400 av Roumanille Bât. 7, BP 309 06906 Sophia-Antipolis, France
- MEDIT SA, 2 rue du Belvedere, 91120 Palaiseau, France
| | - O. Doppelt-Azeroual
- Felix Concordia SARL, 400 av Roumanille Bât. 7, BP 309 06906 Sophia-Antipolis, France
- MEDIT SA, 2 rue du Belvedere, 91120 Palaiseau, France
| | - S. B. Richard
- Felix Concordia SARL, 400 av Roumanille Bât. 7, BP 309 06906 Sophia-Antipolis, France
- MEDIT SA, 2 rue du Belvedere, 91120 Palaiseau, France
| | - F. Delfaud
- Felix Concordia SARL, 400 av Roumanille Bât. 7, BP 309 06906 Sophia-Antipolis, France
- MEDIT SA, 2 rue du Belvedere, 91120 Palaiseau, France
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