Raltegravir-Induced Adaptations of the HIV-1 Integrase: Analysis of Structure, Variability, and Mutation Co-occurrence

Abstract

The human immunodeficiency virus type 1 (HIV-1) has several proteins of therapeutic importance, many of which are currently used as drug targets in antiretroviral therapy. Among these proteins is the integrase, which is responsible for the integration of the viral DNA into the host genome – a crucial step for HIV-1 replication. Given the importance of this protein in the replication process, three integrase inhibitors are currently used as an option for antiretroviral therapy: Raltegravir, Elvitegravir, and Dolutegravir. However, the crescent emergence of mutations that cause resistance to these drugs has become a worldwide health problem. In this study, we compared the variability of each position of the HIV-1 integrase sequence in clinical isolates of Raltegravir-treated and drug-naïve patients by calculating their Shannon entropies. A co-occurrence network was created to explore how mutations co-occur in patients treated with Raltegravir. Then, by building tridimensional models of the HIV-1 integrase intasomes, we investigated the relationship between variability, architecture, and co-occurrence. We observed that positions bearing some of the major resistance pathways are highly conserved among non-treated patients and variable among the treated ones. The residues involved in the three main resistance-related mutations could be identified in the same group when the positions were clustered according to their entropies. Analysis of the integrase architecture showed that the high-entropy residues S119, T124, and T125, are in contact with the host DNA, and their variations may have impacts in the protein-DNA recognition. The co-occurrence network revealed that the major resistance pathways N155H and Q148HR share more mutations with each other than with the Y143R pathway, this observation corroborates the fact that the N155H pathway is most commonly converted into Q148HRK than into Y143RCH pathway in patients’ isolates. The network and the structure analysis also support the hypothesis that the resistance-related E138K mutation may be a mechanism to compensate for mutations in neighbor lysine residues to maintain DNA binding. The present study reveals patterns by which the HIV-1 integrase adapts during Raltegravir therapy. This information can be useful to comprehend the impacts of the drug in the enzyme, as well as help planning new therapeutic approaches.

Baseline integrase drug resistance mutations and conserved regions across HIV-1 clades in Cameroon: implications for transition to dolutegravir in resource-limited settings

“…This expected low level of major INSTI-DRMs is similar to that found worldwide and confirms the limited current exposure to INSTIs and the relevance of exploiting these findings for a rationale including monitoring of emerging INSTI-DRMs over time. 21,26,30,41,[49][50][51][52][53][54][55][56] However, an intriguing finding is the fact that a dolutegravir-resistance signature, through R263K mutation, 3,[24][25][26][27][28][29]33 was found in two patients infected with recombinant viruses (CRF02_AG and URF). This calls for long-term clinical monitoring of patients with such pre-existing DRMs, in order to ascertain the likelihood of failure to dolutegravir-based regimens during routine clinical care.…”

“…3,22,23 Also, R263K (which particularly impairs response to dolutegravir-containing regimens) is known to be preferentially selected amongst subtype B viruses compared with other viral subtypes. 3,[24][25][26][27][28][29] A few studies have attempted similar analysis on subtype C in South Africa, without exploring viral clades circulating in other African countries. 22,[30][31][32] Thus, translating evidence on INSTI-DRMs from settings with B to those with non-B viruses might first require a preliminary assessment of the latter setting for optimal monitoring and shaping of treatment strategies.…”

“…22,[30][31][32] Thus, translating evidence on INSTI-DRMs from settings with B to those with non-B viruses might first require a preliminary assessment of the latter setting for optimal monitoring and shaping of treatment strategies. 3,[24][25][26][27][28][29] An in-depth understanding of INSTI-resistance patterns requires informed data across genotypes from real-world evidence. In light of this, the Stanford HIV algorithm for drug resistance interpretation (Stanford HIVdb) compared the variations observed at key positions associated with major and accessory 34 Furthermore, in this same setting, Cameroon has been described as an epicentre for HIV in Africa, 35 characterized by a very diversified molecular epidemiology.…”

Analysis of temporal changes in HIV-1 CRF01_AE gag genetic variability and CD8 T-cell epitope evolution

“…the probability of acquiring mutations in a genomic sequence, where an increase in entropy values reflects a higher probability for acquiring mutations [ 29 ]. Shannon entropy has been used as a measure of the variability of HIV-1 in previous studies [ 30 ]. A consistent increase in entropy values was seen across year groups.…”

De novo design based identification of potential HIV-1 integrase inhibitors: A pharmacoinformatics study

“…It can also be effective to manage against drug-resistant mutants HIV infections [6,[9][10][11][12][13]. In general, HIV-1 integrase is comprised of three distinct functional domains: the C-terminal domain (CTD), the catalytic core domain (CCD), and the N-terminal domain (NTD) [14,15]. Each domain has distinct characteristics such as NTD region (residues 1-50) contains high conserved His and Cys amino acid residues (or HHCC motif) and known to help in chelation of zinc ion.…”