Evolving Mutational Buildup in HIV‑1 Protease Shifts Conformational Dynamics to Gain Drug Resistance
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https://figshare.com/articles/dataset/Evolving_Mutational_Buildup_in_HIV_1_Protease_Shifts_Conformational_Dynamics_to_Gain_Drug_Resistance/23316101
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资源简介:
Drug resistance in
antiviral treatments is a serious public health
problem. Viral proteins mutate very fast, giving them a way to escape
drugs by lowering drug binding affinity but with compromised function.
Human immunodeficiency virus type I (HIV-1) protease, a critical antiretroviral
therapeutic target, represents a model for such viral regulation under
inhibition. Drug inhibitors of HIV-1 protease lose effectiveness as
the protein evolves through several variants to become more resistant.
However, the detailed mechanism of drug resistance in HIV-1 protease
is still unclear. Here, we test the hypothesis that mutations throughout
the protease alter the protein conformational ensemble to weaken protein–inhibitor
binding, resulting in an inefficient protease but still viable virus.
Comparing conformational ensembles between variants and the wild type
helps detect these function-related dynamical changes. All analyses
of over 30 μs simulations converge to the conclusion that conformational
dynamics of more drug-resistant variants are more different from that
of the wild type. Distinct roles of mutations during viral evolution
are discussed, including a mutation predominantly contributing to
the increase of drug resistance and a mutation that is responsible
(synergistically) for restoring catalytic efficiency. Drug resistance
is mainly due to altered flap dynamics that hinder the access to the
active site. The mutant variant showing the highest drug resistance
has the most ″collapsed″ active-site pocket and hence
the largest magnitude of hindrance of drug binding. An enhanced difference
contact network community analysis is applied to understand allosteric
communications. The method summarizes multiple conformational ensembles
in one community network and can be used in future studies to detect
function-related dynamics in proteins.
创建时间:
2023-06-07



