Literature DB >> 17004705

PMF scoring revisited.

Ingo Muegge1.   

Abstract

Knowledge-based scoring functions have become accepted choices for fast scoring putative protein-ligand complexes according to their binding affinities. Since their introduction 5 years ago, the knowledge base of protein-ligand complexes has grown to the point were rederiving potentials of mean force becomes meaningful for statistical reasons. Revisiting potential of mean force (PMF) scoring (J. Med. Chem. 1999, 42, 791), we present an updated PMF04 scoring function that is based on 7152 protein-ligand complexes from the PDB. This constitutes an increase of about 10-fold compared to the knowledge base of the original PMF99 score (697 complexes). Because of the increased statistical basis of the PMF04 score, potentials for metal ions have been derived for the first time. In addition, potentials for halogens have reached statistical significance and are included also. Comparison of scoring accuracies between PMF99 and PMF04 shows an increased performance of the new score for many well-established test sets. Extending the testing of PMF scoring to the recently introduced PDBbind database containing the large number of 800 protein-ligand complexes illustrates the current limits of the approach.

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Year:  2006        PMID: 17004705     DOI: 10.1021/jm050038s

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  55 in total

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8.  Inclusion of solvation and entropy in the knowledge-based scoring function for protein-ligand interactions.

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9.  A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction.

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10.  BioDrugScreen: a computational drug design resource for ranking molecules docked to the human proteome.

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