Literature DB >> 24760437

Anti-HIV drug development through computational methods.

Wan-Gang Gu1, Xuan Zhang, Jun-Fa Yuan.   

Abstract

Although highly active antiretroviral therapy (HAART) is effective in controlling the progression of AIDS, the emergence of drug-resistant strains increases the difficulty of successful treatment of patients with HIV infection. Increasing numbers of patients are facing the dilemma that comes with the running out of drug combinations for HAART. Computational methods play a key role in anti-HIV drug development. A substantial number of studies have been performed in anti-HIV drug development using various computational methods, such as virtual screening, QSAR, molecular docking, and homology modeling, etc. In this review, we summarize recent advances in the application of computational methods to anti-HIV drug development for five key targets as follows: reverse transcriptase, protease, integrase, CCR5, and CXCR4. We hope that this review will stimulate researchers from multiple disciplines to consider computational methods in the anti-HIV drug development process.

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Year:  2014        PMID: 24760437      PMCID: PMC4070255          DOI: 10.1208/s12248-014-9604-9

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  77 in total

1.  Comparison of ligand-based and receptor-based virtual screening of HIV entry inhibitors for the CXCR4 and CCR5 receptors using 3D ligand shape matching and ligand-receptor docking.

Authors:  Violeta I Pérez-Nueno; David W Ritchie; Obdulia Rabal; Rosalia Pascual; Jose I Borrell; Jordi Teixidó
Journal:  J Chem Inf Model       Date:  2008-02-26       Impact factor: 4.956

2.  Impact of the CXCR4 structure on docking-based virtual screening of HIV entry inhibitors.

Authors:  Jesús M Planesas; Violeta I Pérez-Nueno; José I Borrell; Jordi Teixidó
Journal:  J Mol Graph Model       Date:  2012-07-03       Impact factor: 2.518

3.  Highly specific and sensitive pharmacophore model for identifying CXCR4 antagonists. Comparison with docking and shape-matching virtual screening performance.

Authors:  Arnaud S Karaboga; Jesús M Planesas; Florent Petronin; Jordi Teixidó; Michel Souchet; Violeta I Pérez-Nueno
Journal:  J Chem Inf Model       Date:  2013-04-25       Impact factor: 4.956

4.  Bicyclams, a class of potent anti-HIV agents, are targeted at the HIV coreceptor fusin/CXCR-4.

Authors:  D Schols; J A Esté; G Henson; E De Clercq
Journal:  Antiviral Res       Date:  1997-08       Impact factor: 5.970

5.  A novel peptide antagonist of CXCR4 derived from the N-terminus of viral chemokine vMIP-II.

Authors:  N Zhou; Z Luo; J Luo; J W Hall; Z Huang
Journal:  Biochemistry       Date:  2000-04-04       Impact factor: 3.162

6.  Pharmacophore identification of a chemokine receptor (CXCR4) antagonist, T22 ([Tyr(5,12),Lys7]-polyphemusin II), which specifically blocks T cell-line-tropic HIV-1 infection.

Authors:  H Tamamura; M Imai; T Ishihara; M Masuda; H Funakoshi; H Oyake; T Murakami; R Arakaki; H Nakashima; A Otaka; T Ibuka; M Waki; A Matsumoto; N Yamamoto; N Fujii
Journal:  Bioorg Med Chem       Date:  1998-07       Impact factor: 3.641

7.  [A study of anti-HIV compounds which interfere the virus entry via coreceptor CXCR4].

Authors:  K Kanbara; N Fujii; H Nakashima
Journal:  Kansenshogaku Zasshi       Date:  2000-03

8.  Computational modeling of human coreceptor CCR5 antagonist as a HIV-1 entry inhibitor: using an integrated homology modeling, docking, and membrane molecular dynamics simulation analysis approach.

Authors:  Changdev G Gadhe; Gugan Kothandan; Seung Joo Cho
Journal:  J Biomol Struct Dyn       Date:  2012-11-16

9.  In-Silico docking of HIV-1 integrase inhibitors reveals a novel drug type acting on an enzyme/DNA reaction intermediate.

Authors:  Andrea Savarino
Journal:  Retrovirology       Date:  2007-03-20       Impact factor: 4.602

10.  Molecular docking studies of marine diterpenes as inhibitors of wild-type and mutants HIV-1 reverse transcriptase.

Authors:  Leonardo A Miceli; Valéria L Teixeira; Helena C Castro; Carlos R Rodrigues; Juliana F R Mello; Magaly G Albuquerque; Lucio M Cabral; Monique A de Brito; Alessandra M T de Souza
Journal:  Mar Drugs       Date:  2013-10-29       Impact factor: 5.118

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  4 in total

1.  Benchmarking the Performance of Irregular Computations in AutoDock-GPU Molecular Docking.

Authors:  Leonardo Solis-Vasquez; Andreas F Tillack; Diogo Santos-Martins; Andreas Koch; Scott LeGrand; Stefano Forli
Journal:  Parallel Comput       Date:  2021-11-11       Impact factor: 0.986

2.  HIVprotI: an integrated web based platform for prediction and design of HIV proteins inhibitors.

Authors:  Abid Qureshi; Akanksha Rajput; Gazaldeep Kaur; Manoj Kumar
Journal:  J Cheminform       Date:  2018-03-09       Impact factor: 5.514

Review 3.  Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases.

Authors:  David A Winkler
Journal:  Front Chem       Date:  2021-03-15       Impact factor: 5.221

4.  Can plant-derived anti-HIV compounds be used in COVID-19 cases?

Authors:  Diptimayee Das; Atala Bihari Jena; Antara Banerjee; Arun Kumar Radhakrishnan; Asim K Duttaroy; Surajit Pathak
Journal:  Med Hypotheses       Date:  2022-08-03       Impact factor: 4.411

  4 in total

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