Proteochemometric modeling of HIV protease susceptibility Export

@article{Lapins2008, abstract = {BACKGROUND:A major obstacle in treatment of HIV is the ability of the virus to mutate rapidly into drug-resistant variants. A method for predicting the susceptibility of mutated HIV strains to antiviral agents would provide substantial clinical benefit as well as facilitate the development of new candidate drugs. Therefore, we used proteochemometrics to model the susceptibility of HIV to protease inhibitors in current use, utilizing descriptions of the physico-chemical properties of mutated HIV proteases and 3D structural property descriptions for the protease inhibitors. The descriptions were correlated to the susceptibility data of 828 unique HIV protease variants for seven protease inhibitors in current use; the data set comprised 4792 protease-inhibitor combinations.RESULTS:The model provided excellent predictability (R2 = 0.92, Q2 = 0.87) and identified general and specific features of drug resistance. The model's predictive ability was verified by external prediction in which the susceptibilities to each one of the seven inhibitors were omitted from the data set, one inhibitor at a time, and the data for the six remaining compounds were used to create new models. This analysis showed that the over all predictive ability for the omitted inhibitors was Q2 inhibitors = 0.72.CONCLUSION:Our results show that a proteochemometric approach can provide generalized susceptibility predictions for new inhibitors. Our proteochemometric model can directly analyze inhibitor-protease interactions and facilitate treatment selection based on viral genotype. The model is available for public use, and is located at HIV Drug Research Centre.}, author = {Lapins, Maris and Eklund, Martin and Spjuth, Ola and Prusis, Peteris and Wikberg, Jarl}, citeulike-article-id = {2652506}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/1471-2105-9-181}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/18402661}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=18402661}, day = {10}, doi = {10.1186/1471-2105-9-181}, issn = {1471-2105}, journal = {BMC Bioinformatics}, keywords = {cheminformatics, chemometrics, hiv, hiv\_protease, proteochemometrics, qsar, virus}, month = {April}, number = {1}, pages = {181+}, posted-at = {2009-10-12 06:08:08}, priority = {2}, title = {Proteochemometric modeling of HIV protease susceptibility}, url = {http://dx.doi.org/10.1186/1471-2105-9-181}, volume = {9}, year = {2008} }

TY - JOUR ID - Lapins2008 L3 - citeulike-article-id:2652506 N2 - BACKGROUND:A major obstacle in treatment of HIV is the ability of the virus to mutate rapidly into drug-resistant variants. A method for predicting the susceptibility of mutated HIV strains to antiviral agents would provide substantial clinical benefit as well as facilitate the development of new candidate drugs. Therefore, we used proteochemometrics to model the susceptibility of HIV to protease inhibitors in current use, utilizing descriptions of the physico-chemical properties of mutated HIV proteases and 3D structural property descriptions for the protease inhibitors. The descriptions were correlated to the susceptibility data of 828 unique HIV protease variants for seven protease inhibitors in current use; the data set comprised 4792 protease-inhibitor combinations.RESULTS:The model provided excellent predictability (R2 = 0.92, Q2 = 0.87) and identified general and specific features of drug resistance. The model's predictive ability was verified by external prediction in which the susceptibilities to each one of the seven inhibitors were omitted from the data set, one inhibitor at a time, and the data for the six remaining compounds were used to create new models. This analysis showed that the over all predictive ability for the omitted inhibitors was Q2 inhibitors = 0.72.CONCLUSION:Our results show that a proteochemometric approach can provide generalized susceptibility predictions for new inhibitors. Our proteochemometric model can directly analyze inhibitor-protease interactions and facilitate treatment selection based on viral genotype. The model is available for public use, and is located at HIV Drug Research Centre. IS - 1 JF - BMC Bioinformatics SN - 1471-2105 TI - Proteochemometric modeling of HIV protease susceptibility VL - 9 SP - 181 KW - cheminformatics KW - chemometrics KW - hiv KW - hiv_protease KW - proteochemometrics KW - qsar KW - virus AU - Lapins, Maris AU - Eklund, Martin AU - Spjuth, Ola AU - Prusis, Peteris AU - Wikberg, Jarl PY - 2008/04/10/ UR - http://dx.doi.org/10.1186/1471-2105-9-181 ER -