Computational mutation scanning and drug resistance mechanisms of HIV-1 protease inhibitors.
The drug resistance of various clinically available HIV-1 protease inhibitors has been studied using a new computational protocol, that is, computational mutation scanning (CMS), leading to valuable insights into the resistance mechanisms and structure-resistance correction of the HIV-1 protease inhibitors associated with a variety of active site and nonactive site mutations. By using the CMS method, the calculated mutation-caused shifts of the binding free energies linearly correlate very well with those derived from the corresponding experimental data, suggesting that the CMS protocol may be used as a generalized approach to predict drug resistance associated with amino acid mutations. Because it is essentially important for understanding the structure-resistance correlation and for structure-based drug design to develop an effective computational protocol for drug resistance prediction, the reasonable and computationally efficient CMS protocol for drug resistance prediction should be valuable for future structure-based design and discovery of antiresistance drugs in various therapeutic areas.
Hao
Ge-Fei
GF
Key Laboratory of Pesticide & Chemical Biology of Ministry of Education, College of Chemistry, Central China Normal University, Wuhan 430079, PR China.
Yang
Guang-Fu
GF
Zhan
Chang-Guo
CG
D019295:Computational Biology; D024882:Drug Resistance, Viral; D016333:HIV Protease / Q000737:chemistry* / Q000378:metabolism; D017320:HIV Protease Inhibitors / Q000737:chemistry*; D015497:HIV-1 / Q000187:drug effects; D006801:Humans; D056004:Molecular Dynamics Simulation; D009154:Mutation; D013816:Thermodynamics
D017320:HIV Protease Inhibitors; D016333:HIV Protease; C514803:p16 protease, Human immunodeficiency virus 1