Advances and Challenges in Protein-Ligand Docking

By Shengyou Huang, Xiaoqin Zou. 2010

560 citations recorded by the source corpus.

Molecular docking is a widely-used computational tool for the study of molecular recognition, which aims to predict the binding mode and binding affinity of a complex formed by two or more constituent molecules with known structures. An important type of molecular docking is protein-ligand docking because of its therapeutic applications in modern structure-based drug design. Here, we review the recent advances of protein flexibility, ligand sampling, and scoring functions—the three important aspects in protein-ligand docking. Challenges and possible future directions are discussed in the Conclusion.

Subfields: Computational Theory and Mathematics, Molecular Biology, Organic Chemistry, Representation & Self-Supervised Learning, Computational Chemistry & Drug Discovery

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Citations in the corpus

Molecular Docking and Structure-Based Drug Design Strategies (2015, background): “This process is carried out recursively until converging to a solution of minimum energy [23–25].”
Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods (2016, background): “Protein–ligand docking, which is a branch of the molecular docking field, represents a particularly important methodology due to its importance in the current drug discovery process [14,150,151], i.”
Protein-Protein and Protein-Ligand Docking (2013, methodology): “They were described by Huang et al [1].”
A Structure-Based Drug Discovery Paradigm (2019, methodology): “by means of various scoring functions [49,50].”
Protein-ligand docking in the new millennium--a retrospective of 10 years in the field. (2013, background): “As such they have become an integral part of many scoring functions used in protein-ligand docking [2, 3].”
AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility (2015, background): “Modeling the receptor as fully flexible during the docking calculation is too expensive computationally because of the large number of degrees of freedom to explore during the search [10].”
Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview (2018, methodology): “These functions are the sum of various empirical energy terms such as van der Waals, electrostatic, hydrogen bond, desolvation, entropy, hydrophobicity, etc., which are weighted by coeﬃcients optimized to reproduce binding aﬃnity data of a training set by least squares ﬁtting (Huang and Zou, 2010).”