Marilyn B Kroeger Smith, Sandra Ruby, Stanislav Horouzhenko, Bryan Buckingham, Julia Richardson, Ina Puleri, Emily Potts, William L Jorgensen, Edward Arnold, Wanyi Zhang, Stephen H Hughes, Christopher J Michejda, Richard H Smith
{"title":"HIV-1逆转录酶变异体:使用蒙特卡罗模拟结合线性响应方法的非核苷抑制剂对Y181C, V106A, L100I和K103N突变进行分子建模。","authors":"Marilyn B Kroeger Smith, Sandra Ruby, Stanislav Horouzhenko, Bryan Buckingham, Julia Richardson, Ina Puleri, Emily Potts, William L Jorgensen, Edward Arnold, Wanyi Zhang, Stephen H Hughes, Christopher J Michejda, Richard H Smith","doi":"10.3109/10559610390484203","DOIUrl":null,"url":null,"abstract":"<p><p>The energies and physical descriptors for the binding of 21 novel 1-(2,6-difluorobenzyl)-2-(2,6-difluorophenyl)-benzimidazole (BPBI) analogs to HIV-1 reverse transcriptase (RT) variants Y181C, L100I, V106A, and K103N have been determined using Monte Carlo (MC) simulations. The crystallographic structure of the lead compound, 4-methyl BPBI, was used as a starting point to model the inhibitors in both the mutant bound and the unbound states. The energy terms and physical descriptors obtained from the calculations were reasonably correlated with the respective experimental EC50 values for the inhibitors against the various mutant RTs. Using the linear response correlations from the calculations, 2 novel BPBI inhibitors have been designed and simulations have been carried out. The results show the computed deltaG(binding) values match the experimental data for the analogs. Given the ongoing problem with drug resistance, the ability to predict the activity of novel analogs against variants prior to synthesis is highly advantageous.</p>","PeriodicalId":11297,"journal":{"name":"Drug design and discovery","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2003-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/10559610390484203","citationCount":"3","resultStr":"{\"title\":\"HIV-1 reverse transcriptase variants: molecular modeling of Y181C, V106A, L100I, and K103N mutations with nonnucleoside inhibitors using Monte Carlo simulations in combination with a linear response method.\",\"authors\":\"Marilyn B Kroeger Smith, Sandra Ruby, Stanislav Horouzhenko, Bryan Buckingham, Julia Richardson, Ina Puleri, Emily Potts, William L Jorgensen, Edward Arnold, Wanyi Zhang, Stephen H Hughes, Christopher J Michejda, Richard H Smith\",\"doi\":\"10.3109/10559610390484203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The energies and physical descriptors for the binding of 21 novel 1-(2,6-difluorobenzyl)-2-(2,6-difluorophenyl)-benzimidazole (BPBI) analogs to HIV-1 reverse transcriptase (RT) variants Y181C, L100I, V106A, and K103N have been determined using Monte Carlo (MC) simulations. The crystallographic structure of the lead compound, 4-methyl BPBI, was used as a starting point to model the inhibitors in both the mutant bound and the unbound states. The energy terms and physical descriptors obtained from the calculations were reasonably correlated with the respective experimental EC50 values for the inhibitors against the various mutant RTs. Using the linear response correlations from the calculations, 2 novel BPBI inhibitors have been designed and simulations have been carried out. The results show the computed deltaG(binding) values match the experimental data for the analogs. Given the ongoing problem with drug resistance, the ability to predict the activity of novel analogs against variants prior to synthesis is highly advantageous.</p>\",\"PeriodicalId\":11297,\"journal\":{\"name\":\"Drug design and discovery\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.3109/10559610390484203\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Drug design and discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3109/10559610390484203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug design and discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3109/10559610390484203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
HIV-1 reverse transcriptase variants: molecular modeling of Y181C, V106A, L100I, and K103N mutations with nonnucleoside inhibitors using Monte Carlo simulations in combination with a linear response method.
The energies and physical descriptors for the binding of 21 novel 1-(2,6-difluorobenzyl)-2-(2,6-difluorophenyl)-benzimidazole (BPBI) analogs to HIV-1 reverse transcriptase (RT) variants Y181C, L100I, V106A, and K103N have been determined using Monte Carlo (MC) simulations. The crystallographic structure of the lead compound, 4-methyl BPBI, was used as a starting point to model the inhibitors in both the mutant bound and the unbound states. The energy terms and physical descriptors obtained from the calculations were reasonably correlated with the respective experimental EC50 values for the inhibitors against the various mutant RTs. Using the linear response correlations from the calculations, 2 novel BPBI inhibitors have been designed and simulations have been carried out. The results show the computed deltaG(binding) values match the experimental data for the analogs. Given the ongoing problem with drug resistance, the ability to predict the activity of novel analogs against variants prior to synthesis is highly advantageous.