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Article

A Critical Assessment of the Performance of Protein−Ligand Scoring Functions Based on NMR Chemical Shift Perturbations

Bing Wang,^† Lance M. Westerhoff,^‡ and Kenneth M. Merz Jr.*^†

Department of Chemistry, Quantum Theory Project, University of Florida, P.O. Box 118435 Gainesville, Florida 32611-8435, and QuantumBio Inc. 200 Innovation Boulevard, Suite 261, State College, Pennsylvania 16802

J. Med. Chem., 2007, 50 (21), pp 5128–5134

DOI: 10.1021/jm070484a

Publication Date (Web): September 15, 2007

†

Department of Chemistry, Quantum Theory Project, University of Florida, P.O. Box 118435 Gainesville, FL 32611-8435

‡

QuantumBio Inc. 200 Innovation Blvd, Suite 261, State College, PA, 16902

Author to whom correspondence should be addressed. E-mail: merz@qtp.ufl.edu.

Abstract

We have generated docking poses for the FKBP−GPI complex using eight docking programs, and compared their scoring functions with scoring based on NMR chemical shift perturbations (NMRScore). Because the chemical shift perturbation (CSP) is exquisitely sensitive on the orientation of the ligand inside the binding pocket, NMRScore offers an accurate and straightforward approach to score different poses. All scoring functions were inspected by their abilities to highly rank the native-like structures and separate them from decoy poses generated for a protein−ligand complex. The overall performance of NMRScore is much better than that of energy-based scoring functions associated with docking programs in both aspects. In summary, we find that the combination of docking programs with NMRScore results in an approach that can robustly determine the binding site structure for a protein−ligand complex, thereby providing a new tool facilitating the structure-based drug discovery process.

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PDB: 1F40

History

Published In Issue October 18, 2007
Received April 25, 2007

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Article

A Critical Assessment of the Performance of Protein−Ligand Scoring Functions Based on NMR Chemical Shift Perturbations

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A Critical Assessment of Docking Programs and Scoring Functions

Prediction of Protein−Ligand Interactions. Docking and Scoring: Successes and Gaps

Identification of Ellagic Acid as Potent Inhibitor of Protein Kinase CK2: A Successful Example of a Virtual Screening Application

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