scholarly journals Molecular mechanisms and design principles for promiscuous inhibitors to avoid drug resistance: Lessons learned from HIV ‐1 protease inhibition

2015 ◽  
Vol 83 (2) ◽  
pp. 351-372 ◽  
Author(s):  
Yang Shen ◽  
Mala L. Radhakrishnan ◽  
Bruce Tidor
Keyword(s):  
Drug Resistance ◽  
Molecular Mechanisms ◽  
Design Principles ◽  
Lessons Learned ◽  
Protease Inhibition ◽  
Hiv 1

Genetic Diversity and Drug Resistance of HIV-1 CRF55_01B in Guangdong, China

2020 ◽  
Vol 18 (3) ◽  
pp. 210-218
Author(s):  
Guolong Yu ◽  
Yan Li ◽  
Xuhe Huang ◽  
Pingping Zhou ◽  
Jin Yan ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Phylogenetic Analyses ◽  
Resistance Mutations ◽  
Protease Inhibition ◽  
Subtype B ◽  
Primary Drug Resistance ◽  
Hiv 1 ◽  
Primary Drug

Background: HIV-1 CRF55_01B was first reported in 2013. At present, no report is available regarding this new clade’s polymorphisms in its functionally critical regions protease and reverse transcriptase. Objective: To identify the diversity difference in protease and reverse transcriptase between CRF55_01B and its parental clades CRF01_AE and subtype B; and to investigate CRF55_01B’s drug resistance mutations associated with the protease inhibition and reverse transcriptase inhibition. Methods: HIV-1 RNA was extracted from plasma derived from a MSM population. The reverse transcription and nested PCR amplification were performed following our in-house PCR procedure. Genotyping and drug resistant-associated mutations and polymorphisms were identified based on polygenetic analyses and the usage of the HIV Drug Resistance Database, respectively. Results: A total of 9.24 % of the identified CRF55_01B sequences bear the primary drug resistance. CRF55_01B contains polymorphisms I13I/V, G16E and E35D that differ from those in CRF01_AE. Among the 11 polymorphisms in the RT region, seven were statistically different from CRF01_AE’s. Another three polymorphisms, R211K (98.3%), F214L (98.3%), and V245A/E (98.3 %.), were identified in the RT region and they all were statistically different with that of the subtype B. The V179E/D mutation, responsible for 100% potential low-level drug resistance, was found in all CRF55_01B sequences. Lastly, the phylogenetic analyses demonstrated 18 distinct clusters that account for 35% of the samples. Conclusions: CRF55_01B’s pol has different genetic diversity comparing to its counterpart in CRF55_01B’s parental clades. CRF55_01B has a high primary drug resistance presence and the V179E/D mutation may confer more vulnerability to drug resistance.

scholarly journals A Rough Set-Based Model of HIV-1 Reverse Transcriptase Resistome

2009 ◽  
Vol 3 ◽  
pp. BBI.S3382 ◽  
Author(s):  
Marcin Kierczak ◽  
Krzysztof Ginalski ◽  
Michał Dramiñski ◽  
Jacek Koronacki ◽  
Witold Rudnicki ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Rough Set ◽  
Molecular Mechanisms ◽  
3D Structure ◽  
Feature Selection Method ◽  
Resistance Mutations ◽  
Monte Carlo Feature Selection ◽  
Rt Inhibitors ◽  
Hiv 1

Reverse transcriptase (RT) is a viral enzyme crucial for HIV-1 replication. Currently, 12 drugs are targeted against the RT. The low fidelity of the RT-mediated transcription leads to the quick accumulation of drug-resistance mutations. The sequence-resistance relationship remains only partially understood. Using publicly available data collected from over 15 years of HIV proteome research, we have created a general and predictive rule-based model of HIV-1 resistance to eight RT inhibitors. Our rough set-based model considers changes in the physicochemical properties of a mutated sequence as compared to the wild-type strain. Thanks to the application of the Monte Carlo feature selection method, the model takes into account only the properties that significantly contribute to the resistance phenomenon. The obtained results show that drug-resistance is determined in more complex way than believed. We confirmed the importance of many resistance-associated sites, found some sites to be less relevant than formerly postulated and—more importantly—identified several previously neglected sites as potentially relevant. By mapping some of the newly discovered sites on the 3D structure of the RT, we were able to suggest possible molecular-mechanisms of drug-resistance. Importantly, our model has the ability to generalize predictions to the previously unseen cases. The study is an example of how computational biology methods can increase our understanding of the HIV-1 resistome.

Probing the Molecular Mechanisms of AZT Drug Resistance Mediated by HIV-1 Reverse Transcriptase Using a Transient Kinetic Analysis†

Biochemistry ◽  
2003 ◽  
Vol 42 (29) ◽  
pp. 8831-8841 ◽  
Author(s):  
Adrian S. Ray ◽  
Eisuke Murakami ◽  
Aravind Basavapathruni ◽  
Joseph A. Vaccaro ◽  
Dagny Ulrich ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Reverse Transcriptase ◽  
Kinetic Analysis ◽  
Molecular Mechanisms ◽  
Hiv 1

Drug resistance among patients with HIV-1

2013 ◽  
Vol 4 (5) ◽  
pp. 317-323
Author(s):  
Miłosz Parczewski
Keyword(s):  
Drug Resistance ◽  
Hiv 1
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