AIMC Topic: HIV-1

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Machine learning approaches identify immunologic signatures of total and intact HIV DNA during long-term antiretroviral therapy.

eLife
Understanding the interplay between the HIV reservoir and the host immune system may yield insights into HIV persistence during antiretroviral therapy (ART) and inform strategies for a cure. Here, we applied machine learning (ML) approaches to cross-...

RAIN: machine learning-based identification for HIV-1 bNAbs.

Nature communications
Broadly neutralizing antibodies (bNAbs) are promising candidates for the treatment and prevention of HIV-1 infections. Despite their critical importance, automatic detection of HIV-1 bNAbs from immune repertoires is still lacking. Here, we develop a ...

A deep learning approach to real-time HIV outbreak detection using genetic data.

PLoS computational biology
Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylo...

Switching to a NRTI-free 2 drug regimen (2DR) -a sub-analysis of the 48 weeks DUALIS study on metabolic and renal changes.

HIV research & clinical practice
Switching from a three-drug regimen (3DR: boosted darunavir [bDRV] and two nucleoside reverse transcriptase inhibitors [NRTIs]) to a two-drug regimen (2DR: bDRV and dolutegravir [DTG]) demonstrated non-inferiority with regard to viral suppression in...

Different features identified by machine learning associated with the HIV compartmentalization in semen.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
Genetic compartmentalization in semen has been observed in previous studies. However, genetic signatures associated with compartmentalization in semen are only beginning to be explored. A total of 2071 partial HIV env sequences for paired blood and s...

Long-term safety and efficacy of rilpivirine in combination with nucleoside/nucleotide reverse transcriptase inhibitors in HIV-1 infected patients: 336-week rollover study of phase 2b and 3 clinical studies.

Antiviral therapy
BACKGROUND: To evaluate the long-term safety and efficacy of rilpivirine (RPV), a non-nucleoside reverse transcriptase inhibitor (NNRTI), in combination with nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) in human immunodeficiency vir...

Rilpivirine plus cobicistat-boosted darunavir as alternative to standard three-drug therapy in HIV-infected, virologically suppressed subjects: Final results of the PROBE 2 trial.

Antiviral therapy
BACKGROUND: Primary analysis at 24 weeks showed that switching to rilpivirine plus darunavir/cobicistat was non-inferior to continuing a standard three-drug antiretroviral regimen in virologically suppressed people with HIV. We present efficacy and s...

Using machine learning and big data to explore the drug resistance landscape in HIV.

PLoS computational biology
Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to reveal new DRMs is to test for significant frequency differences of mutations between treated and naive...

Application of deep learning and molecular modeling to identify small drug-like compounds as potential HIV-1 entry inhibitors.

Journal of biomolecular structure & dynamics
A generative adversarial autoencoder for the rational design of potential HIV-1 entry inhibitors able to block CD4-binding site of the viral envelope protein gp120 was developed. To do this, the following studies were carried out: (i) an autoencoder ...

Classification and Design of HIV-1 Integrase Inhibitors Based on Machine Learning.

Computational and mathematical methods in medicine
A key enzyme in human immunodeficiency virus type 1 (HIV-1) life cycle, integrase (IN) aids the integration of viral DNA into the host DNA, which has become an ideal target for the development of anti-HIV drugs. A total of 1785 potential HIV-1 IN inh...