Cargando…

Characterizing early drug resistance-related events using geometric ensembles from HIV protease dynamics

The use of antiretrovirals (ARVs) has drastically improved the life quality and expectancy of HIV patients since their introduction in health care. Several millions are still afflicted worldwide by HIV and ARV resistance is a constant concern for both healthcare practitioners and patients, as while...

Descripción completa

Detalles Bibliográficos
Autores principales: Sheik Amamuddy, Olivier, Bishop, Nigel T., Tastan Bishop, Özlem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298995/
https://www.ncbi.nlm.nih.gov/pubmed/30560871
http://dx.doi.org/10.1038/s41598-018-36041-8
Descripción
Sumario:The use of antiretrovirals (ARVs) has drastically improved the life quality and expectancy of HIV patients since their introduction in health care. Several millions are still afflicted worldwide by HIV and ARV resistance is a constant concern for both healthcare practitioners and patients, as while treatment options are finite, the virus constantly adapts via complex mutation patterns to select for resistant strains under the pressure of drug treatment. The HIV protease is a crucial enzyme for viral maturation and has been a game changing drug target since the first application. Due to similarities in protease inhibitor designs, drug cross-resistance is not uncommon across ARVs of the same class. It is known that resistance against protease inhibitors is associated with a wider active site, but results from our large scale molecular dynamics simulations combined with statistical tests and network analysis further show, for the first time, that there are regions of local expansions and compactions associated with high levels of resistance conserved across eight different protease inhibitors visible in their complexed form within closed receptor conformations. The observed conserved expansion sites may provide an alternative drug-targeting site. Further, the method developed here is novel, supplementary to methods of variation analysis at sequence level, and should be applicable in analysing the structural consequences of mutations in other contexts using molecular ensembles.