Antiretroviral therapy: dolutegravir sets SAIL(ING)

Prevalence of resistance mutations associated with integrase inhibitors in therapy-naive HIV-positive patients in Baoding, Hebei province, China

Antiretroviral therapy (ART) regimens containing integrase strand transfer inhibitors (INSTIs) are the recommended treatment for human immunodeficiency virus type 1 (HIV-1)-infected patients in the most recent guidelines in China. In this study, we investigated INSTI resistance mutations in newly diagnosed therapy-naive HIV-positive patients in Baoding City, Hebei Province (China) to provide guidance for implementing routine INSTI-associated HIV-1 genotypic resistance testing. Plasma samples were collected from HIV-1-infected patients without treatment at Baoding People’s Hospital from January 2020 to December 2021. The part of HIV-1 pol gene encoding integrase was amplified, sequenced, and analyzed for INSTI resistance. Clinical data including demographic data, CD4⁺ T cell counts, HIV-RNA loads, and resistance mutations were collected. Treatment-naïve HIV-1 patients (n = 131) were enrolled. We identified ten genotypes, and the predominant genotype was CRF01_AE in 67 patients (51.15%), CRF07_ BC in 39 patients (29.77%), subtype B in 11 patients (8.40%), and other subtypes (CRF68_01B, 3.82%; CRF55_01B, 1.53%, CRF80_0107, 1.53%; URFs 1.53%; and CRF103_01B, CRF59_01B, and CRF65_cpx, 1.4% each). Four major (E138A, R263k, G140S, and S147G) and three accessory (H51Y, Q146QL, and S153F) INSTI-resistance mutations were observed (genotype CRF01_AE, three patients; genotype B, one patient; and genotype CRF07_BC, one patient), resulting in different degrees of resistance to the following five INSTIs: raltegravir, elvitegravir, dolutegravir, bictegravir, and cabotegravir. The overall resistance rate was 3.82% (5/131). All INSTI-resistant strains were cross-resistant. The primary INSTI drug resistance rate among newly diagnosed HIV-infected patients in Baoding was low, but monitoring and research on HIV INSTI resistance should be strengthened in Baoding because INSTI-based regimen prescriptions are anticipated to increase in the near future.

Prevalence of integrase strand transfer inhibitor (INSTIs) resistance mutations in Henan Province, China (2018-2020)

BACKGROUND

Antiretroviral therapy (ART) regimens containing integrase strand transfer inhibitors (INSTIs) have become the recommended treatment for human immunodeficiency virus type 1 (HIV-1)-infected patients in the updated guidelines in China. In this study, we investigated the prevalence of acquired and transmitted INSTI-associated resistance of HIV-1 strains in the Henan Province (China) to provide guidance on the implementation of routine INSTI-associated HIV-1 genotypic resistance testing.

METHODS

Serum samples from HIV-1-infected patients seeking treatment in our hospital from August 2018 to December 2020 were collected and the HIV-1 integrase gene coding sequence was amplified, sequenced and analyzed for INSTI resistance.

RESULTS

We obtained integrase sequence data from a total of 999 HIV-1-infected patients, including 474 ART-naive patients, 438 ART-treated patients, and 87 patients with unknown treatment history. We detected INSTI resistance in 12 patients (1.2%, 12/999) of the study group, which included 9 ART-treated patients (2.05%, 9/438), with 6 being INSTI-treated (14.63%, 6/41) and 3 INSTI-naive (0.76%, 3/397) and 3 ART-naive (0.63%, 3/474) patients. The most common major resistance mutation was E138AK (0.5%, 5/999), while the most common accessory resistance mutation was E157Q (1.8%, 18/999). Phylogenetic analysis based on the HIV-1 integrase gene indicated that INSTI resistance was primarily detected in patients infected with HIV-1 subtype B.

CONCLUSIONS

In conclusion, our study reveals that INSTI resistance is observed in INSTI-treated patients, as expected, and the prevalence of INSTI resistance in ART-naive patients in Henan Province is low. However, baseline INSTI resistance testing should be considered, as the prescription of INSTI-based regimens is anticipated to increase considerably in the near future.

Development of a receptor model for efficient in silico screening of HIV-1 integrase inhibitors

Integrase (IN) is a key viral enzyme for the replication of the type-1 human immunodeficiency virus (HIV-1), and as such constitutes a relevant therapeutic target for the development of anti-HIV agents. However, the lack of crystallographic data of HIV IN complexed with the corresponding viral DNA has historically hindered the application of modern structure-based drug design techniques to the discovery of new potent IN inhibitors (INIs). Consequently, the development and validation of reliable HIV IN structural models that may be useful for the screening of large databases of chemical compounds is of particular interest. In this study, four HIV-1 IN homology models were evaluated respect to their capability to predict the inhibition potency of a training set comprising 36 previously reported INIs with IC50 values in the low nanomolar to the high micromolar range. Also, 9 inactive structurally related compounds were included in this training set. In addition, a crystallographic structure of the IN-DNA complex corresponding to the prototype foamy virus (PFV) was also evaluated as structural model for the screening of inhibitors. The applicability of high throughput screening techniques, such as blind and ligand-guided exhaustive rigid docking was assessed. The receptor models were also refined by molecular dynamics and clustering techniques to assess protein sidechain flexibility and solvent effect on inhibitor binding. Among the studied models, we conclude that the one derived from the X-ray structure of the PFV integrase exhibited the best performance to rank the potencies of the compounds in the training set, with the predictive power being further improved by explicitly modeling five water molecules within the catalytic side of IN. Also, accounting for protein sidechain flexibility enhanced the prediction of inhibition potencies among the studied compounds. Finally, an interaction fingerprint pattern was established for the fast identification of potent IN inhibitors. In conclusion, we report an exhaustively validated receptor model if IN that is useful for the efficient screening of large chemical compounds databases in the search of potent HIV-1 IN inhibitors.