Molecular Docking: A Powerful Approach for Structure-Based Drug Discovery

Meng, Xuan-Yu; Zhang, Hong-Xing; Mezei, Mihaly; Cui, Meng

doi:10.2174/157340911795677602

Cited by 3,771Computational Drug Discovery MethodsProtein Structure and DynamicsProtein Interaction Studies and Fluorescence Analysis

Molecular Docking: A Powerful Approach for Structure-Based Drug Discovery

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Meng, Xuan-Yu, Zhang, Hong-Xing, Mezei, Mihaly, Cui, Meng·2011·Current Computer Aided-Drug Design

DOI 10.2174/157340911795677602PMC PMC3151162

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Abstract

Molecular docking has become an increasingly important tool for drug discovery. In this review, we present a brief introduction of the available molecular docking methods, and their development and applications in drug discovery. The relevant basic theories, including sampling algorithms and scoring functions, are summarized. The differences in and performance of available docking software are also discussed. Flexible receptor molecular docking approaches, especially those including backbone flexibility in receptors, are a challenge for available docking methods. A recently developed Local Move Monte Carlo (LMMC) based approach is introduced as a potential solution to flexible receptor docking problems. Three application examples of molecular docking approaches for drug discovery are provided. Keywords: Conformational sampling, scoring, flexible protein-ligand docking, backbone flexibility, local move Monte Carlo sampling, molecular docking, drug discovery, virtual screening, high throughput screening, QSAR

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There are advances in computationally modeling how small molecules and proteins interact via docking.
“Within the chemoinformatics space, there are advances in computationally modeling how small molecules and proteins interact via docking.157–159”
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[108]Totrov M Abagyan R Raffa RB Protein-ligand docking as an energy optimization problem Drug-receptor thermodynamics: Introduction and experimental applications 2001 603 624 John Wiley & Sons New York

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Authors: Meng, X.-Y., Zhang, H.-X., Mezei, M., & Cui, M.
Affiliations: Jilin University (CN)
Icahn School of Medicine at Mount Sinai (US)
Corresponding author: Meng, Xuan-Yu
Cui, Meng
ORCID: Meng, Xuan-Yu
Zhang, Hong-Xing
Mezei, Mihaly
Cui, Meng
Venue: Current Computer Aided-Drug Design
Publisher: Bentham Science Publishers Ltd.
Published: 2011-06-01
Volume: 7
Issue: 2
Pages: 146-157
ISSN: 1573-4099 (ISSN-L)
DOI: 10.2174/157340911795677602
PMC: PMC3151162
OpenAlex: W2152630148
Cited by: 3,771
References: 134
Citations by year: 2026: 500 · 2025: 522 · 2024: 569 · 2023: 508 · 2022: 489 · 2021: 340 · 2020: 278 · 2019: 178 · 2018: 136 · 2017: 114 · 2016: 71 · 2015: 24 · 2014: 17 · 2013: 20 · 2012: 4
FWCI: 12.69
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Current Computer - Aided Drug Design (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health
National Institute on Deafness and Other Communication Disorders (DC008996, R21DC008996)
National Center for Research Resources (S10RR027411)
Topics: Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
Keywords: molecular docking, structure-based drug design, conformational sampling, scoring functions, backbone flexibility, protein-ligand docking, virtual screening
MeSH terms: Algorithms, Animals, Humans, Models, Molecular, Monte Carlo Method, Protein Binding, Protein Conformation, Proteins, Structure-Activity Relationship, Drug Design

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Molecular Docking: A Powerful Approach for Structure-Based Drug Discovery

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