Browse views: by Year, by Function, by GLF, by Subfunction, by Conference, by Journal

New scoring functions for virtual screening from molecular dynamics simulations with a quantum-refined force-field (QRFF-MD). Application to cyclin-dependent kinase 2.

Ferrara, Philippe, Curioni, A, Vangrevelinghe, Eric, Meyer, Thomas, Mordasini, T, Andreoni, W, Acklin, Pierre and Jacoby, Edgar (2006) New scoring functions for virtual screening from molecular dynamics simulations with a quantum-refined force-field (QRFF-MD). Application to cyclin-dependent kinase 2. Journal of Chemical Information and Modeling, 46 (1). pp. 254-263. ISSN 1549-9596

Abstract

A recently introduced new methodology based on ultrashort (50-100 ps) molecular dynamics simulations with a quantum-refined force-field (QRFF-MD) is here evaluated in its ability both to predict protein-ligand binding affinities and to discriminate active compounds from inactive ones. Physically based scoring functions are derived from this approach, and their performance is compared to that of several standard knowledge-based scoring functions. About 40 inhibitors of cyclin-dependent kinase 2 (CDK2) representing a broad chemical diversity were considered. The QRFF-MD method achieves a correlation coefficient, R(2), of 0.55, which is significantly better than that obtained by a number of traditional approaches in virtual screening but only slightly better than that obtained by consensus scoring (R(2) = 0.50). Compounds from the Available Chemical Directory, along with the known active compounds, were docked into the ATP binding site of CDK2 using the program Glide, and the 650 ligands from the top scored poses were considered for a QRFF-MD analysis. Combined with structural information extracted from the simulations, the QRFF-MD methodology results in similar enrichment of known actives compared to consensus scoring. Moreover, a new scoring function is introduced that combines a QRFF-MD based scoring function with consensus scoring, which results in substantial improvement on the enrichment profile.

Item Type: Article
Related URLs:
Additional Information: archiving not formally supported by this publisher
Related URLs:
Date Deposited: 14 Dec 2009 14:00
Last Modified: 31 Jan 2013 01:17
URI: https://oak.novartis.com/id/eprint/440

Search

Email Alerts

Register with OAK to receive email alerts for saved searches.