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• W2031259080 abstract "Computational lead design procedures require fast and accurate scoring functions to rank millions of generated virtual ligands for protein targets. In this article, we present an improved version of the SMoG scoring function, called SMoG2001. This function is based on a knowledge-based approach-that is, the free energy parameters are derived from the observed frequencies of atom-atom contacts in the database of three-dimensional structures of protein-ligand complexes via a procedure based on statistical mechanics. We obtained the statistics from the set of 725 complexes. SMoG2001 reproduces the experimental binding constants of the majority of 119 complexes of the testing set with good accuracy. On similar testing sets, SMoG2001 performs better than two other widely used scoring functions, PMF and SCORE1(LUDI), and comparably to DrugScore. SMoG2001 poorly predicts the affinities of ligands interacting via quantum mechanical forces with metal ions and ligands that are large and flexible. We attribute significant improvement in accuracy over previous versions of the SMoG scoring function to a better description of the reference state-that is, the state of no interactions." @default.
• W2031259080 created "2016-06-24" @default.
• W2031259080 creator A5020621313 @default.
• W2031259080 creator A5082765817 @default.
• W2031259080 date "2002-05-14" @default.
• W2031259080 modified "2023-10-17" @default.
• W2031259080 title "SMall Molecule Growth 2001 (SMoG2001): An Improved Knowledge-Based Scoring Function for Protein−Ligand Interactions" @default.
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• W2031259080 doi "https://doi.org/10.1021/jm0105833" @default.
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