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GeauxDock: A novel approach for mixed‐resolution ligand docking using a descriptor‐based force field
Author(s) -
Ding Yun,
Fang Ye,
Feinstein Wei P.,
Ramanujam Jagannathan,
Koppelman David M.,
Moreno Juana,
Brylinski Michal,
Jarrell Mark
Publication year - 2015
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.24031
Subject(s) - docking (animal) , dock , protein–ligand docking , benchmarking , force field (fiction) , computer science , monte carlo method , biological system , computational biology , molecular dynamics , computational chemistry , chemistry , artificial intelligence , virtual screening , mathematics , biology , medicine , biochemistry , statistics , nursing , marketing , business
Molecular docking is an important component of computer-aided drug discovery. In this communication, we describe GeauxDock, a new docking approach that builds on the ideas of ligand homology modeling. GeauxDock features a descriptor-based scoring function integrating evolutionary constraints with physics-based energy terms, a mixed-resolution molecular representation of protein-ligand complexes, and an efficient Monte Carlo sampling protocol. To drive docking simulations toward experimental conformations, the scoring function was carefully optimized to produce a correlation between the total pseudoenergy and the native-likeness of binding poses. Indeed, benchmarking calculations demonstrate that GeauxDock has a strong capacity to identify near-native conformations across docking trajectories with the area under receiver operating characteristics of 0.85. By excluding closely related templates, we show that GeauxDock maintains its accuracy at lower levels of homology through the increased contribution from physics-based energy terms compensating for weak evolutionary constraints. GeauxDock is available at http://www.institute.loni.org/lasigma/package/dock/.