MedusaScore: an accurate force field-based scoring function for virtual drug screening.
Virtual screening is becoming an important tool for drug discovery. However, the application of virtual screening has been limited by the lack of accurate scoring functions. Here, we present a novel scoring function, MedusaScore, for evaluating protein-ligand binding. MedusaScore is based on models of physical interactions that include van der Waals, solvation, and hydrogen bonding energies. To ensure the best transferability of the scoring function, we do not use any protein-ligand experimental data for parameter training. We then test the MedusaScore for docking decoy recognition and binding affinity prediction and find superior performance compared to other widely used scoring functions. Statistical analysis indicates that one source of inaccuracy of MedusaScore may arise from the unaccounted entropic loss upon ligand binding, which suggests avenues of approach for further MedusaScore improvement.
Yin
Shuangye
S
Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Biedermannova
Lada
L
Vondrasek
Jiri
J
Dokholyan
Nikolay V
NV
D004353:Drug Evaluation, Preclinical; D008024:Ligands; D008958:Models, Molecular; D017434:Protein Structure, Tertiary; D012985:Software Design; D013820:Thermolysin / Q000737:chemistry / Q000378:metabolism
D008024:Ligands; D013820:Thermolysin