Development of the knowledge-based and empirical combined scoring algorithm (KECSA) to score protein-ligand interactions.

ABSTRACT: We describe a novel knowledge-based protein-ligand scoring function that employs a new definition for the reference state, allowing us to relate a statistical potential to a Lennard-Jones (LJ) potential. In this way, the LJ potential parameters were generated from protein-ligand complex structural data contained in the Protein Databank (PDB). Forty-nine (49) types of atomic pairwise interactions were derived using this method, which we call the knowledge-based and empirical combined scoring algorithm (KECSA). Two validation benchmarks were introduced to test the performance of KECSA. The first validation benchmark included two test sets that address the training set and enthalpy/entropy of KECSA. The second validation benchmark suite included two large-scale and five small-scale test sets,

SUBMITTER: Zheng Z 

PROVIDER: S-EPMC3686284 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature