Lin_F9: A Linear Empirical Scoring Function for Protein–Ligand Docking

Molecular docking is one of the most
widely used computational
tools in structure-based drug design and is critically dependent on
accuracy and robustness of the scoring function. In this work, we
introduce a new scoring function Lin_F9, which is a linear combination
of nine empirical terms, including a unified metal bond term to specifically
describe metal–ligand interactions. Parameters in Lin_F9 are
obtained with a multistage fitting protocol using explicit water-included
structures. For the CASF-2016 benchmark test set, Lin_F9 achieves
the top scoring power among all 34 classical scoring functions for
both original crystal poses and locally optimized poses with Pearson
correlation coefficients (R) of 0.680 and 0.687,
respectively. Meanwhile, in comparison with Vina, Lin_F9 achieves
consistently better scoring power and ranking power with various types
of protein–ligand complex structures that mimic real docking
applications, including end-to-end flexible docking for the CASF-2016
benchmark test set using a single or an ensemble of protein receptor
structures, as well as for D3R Grand Challenge (GC4) test sets. Lin_F9
has been implemented in a fork of Smina as an optional built-in scoring
function that can be used for docking applications as well as for
further improvement of scoring functions and docking protocols. Lin_F9
is accessible through https://yzhang.hpc.nyu.edu/Lin_F9/.