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Molecules 2017, 22(11), 2029;

Dynamic Docking: A Paradigm Shift in Computational Drug Discovery

Department of Pharmacy and Biotechnology, Alma Mater Studiorum—Universita’ di Bologna, via Belmeloro 6, I-40126 Bologna, Italy
Computational Sciences, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genova, Italy
Authors to whom correspondence should be addressed.
Received: 27 October 2017 / Revised: 18 November 2017 / Accepted: 19 November 2017 / Published: 22 November 2017
(This article belongs to the Special Issue Frontiers in Computational Chemistry for Drug Discovery)
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Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD) have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking). Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress. View Full-Text
Keywords: protein-ligand binding; molecular dynamics; enhanced sampling; binding kinetics; drug discovery protein-ligand binding; molecular dynamics; enhanced sampling; binding kinetics; drug discovery

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Gioia, D.; Bertazzo, M.; Recanatini, M.; Masetti, M.; Cavalli, A. Dynamic Docking: A Paradigm Shift in Computational Drug Discovery. Molecules 2017, 22, 2029.

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