Further development and validation of empirical scoring functions for structure-based binding affinity prediction
dc.contributor.author | Wang, Renxiao | en_US |
dc.contributor.author | Lai, Luhua | en_US |
dc.contributor.author | Wang, Shaomeng | en_US |
dc.date.accessioned | 2006-09-08T20:55:18Z | |
dc.date.available | 2006-09-08T20:55:18Z | |
dc.date.issued | 2002-01 | en_US |
dc.identifier.citation | Wang, Renxiao; Lai, Luhua; Wang, Shaomeng; (2002). "Further development and validation of empirical scoring functions for structure-based binding affinity prediction." Journal of Computer-Aided Molecular Design 16(1): 11-26. <http://hdl.handle.net/2027.42/42967> | en_US |
dc.identifier.issn | 0920-654X | en_US |
dc.identifier.issn | 1573-4951 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/42967 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=12197663&dopt=citation | en_US |
dc.description.abstract | New empirical scoring functions have been developed to estimate the binding affinity of a given protein-ligand complex with known three-dimensional structure. These scoring functions include terms accounting for van der Waals interaction, hydrogen bonding, deformation penalty, and hydrophobic effect. A special feature is that three different algorithms have been implemented to calculate the hydrophobic effect term, which results in three parallel scoring functions. All three scoring functions are calibrated through multivariate regression analysis of a set of 200 protein-ligand complexes and they reproduce the binding free energies of the entire training set with standard deviations of 2.2 kcal/mol, 2.1 kcal/mol, and 2.0 kcal/mol, respectively. These three scoring functions are further combined into a consensus scoring function, X-CSCORE. When tested on an independent set of 30 protein-ligand complexes, X-CSCORE is able to predict their binding free energies with a standard deviation of 2.2 kcal/mol. The potential application of X-CSCORE to molecular docking is also investigated. Our results show that this consensus scoring function improves the docking accuracy considerably when compared to the conventional force field computation used for molecular docking. | en_US |
dc.format.extent | 208795 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Chemistry | en_US |
dc.subject.other | Computer Applications in Chemistry | en_US |
dc.subject.other | Physical Chemistry | en_US |
dc.subject.other | Animal Anatomy / Morphology / Histology | en_US |
dc.subject.other | Binding Affinity Prediction | en_US |
dc.subject.other | Consensus Scoring | en_US |
dc.subject.other | Empirical Scoring Molecular Docking | en_US |
dc.subject.other | Structure-based Drug Design | en_US |
dc.title | Further development and validation of empirical scoring functions for structure-based binding affinity prediction | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Chemistry | en_US |
dc.subject.hlbsecondlevel | Chemical Engineering | en_US |
dc.subject.hlbsecondlevel | Materials Science and Engineering | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Medical Chemistry and Comprehensive Cancer Center, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-0934, U.S.A | en_US |
dc.contributor.affiliationum | Medical Chemistry and Comprehensive Cancer Center, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109-0934, U.S.A; Institute of Physical Chemistry, Peking University, Beijing, 100871, P.R. China | en_US |
dc.contributor.affiliationother | Institute of Physical Chemistry, Peking University, Beijing, 100871, P.R. China | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.identifier.pmid | 12197663 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/42967/1/10822_2004_Article_405419.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1016357811882 | en_US |
dc.identifier.source | Journal of Computer-Aided Molecular Design | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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