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Modeling and Analysis of HIV-1 Pol Polyprotein as a Case Study for Predicting Large Polyprotein Structures

  1. Author:
    Hao,Ming [ORCID]
    Imamichi,Tomozumi [ORCID]
    Chang,Weizhong [ORCID]
  2. Author Address

    Laboratory of Human Retrovirology and Immunoinformatics, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.,
    1. Year: 2024
    2. Date: Feb 02
    3. Epub Date: 2024 02 02
  1. Journal: International Journal of Molecular Sciences
    1. 25
    2. 3
  2. Type of Article: Article
  3. Article Number: 1809
  1. Abstract:

    Acquired immunodeficiency syndrome (AIDS) is caused by human immunodeficiency virus (HIV). HIV protease, reverse transcriptase, and integrase are targets of current drugs to treat the disease. However, anti-viral drug-resistant strains have emerged quickly due to the high mutation rate of the virus, leading to the demand for the development of new drugs. One attractive target is Gag-Pol polyprotein, which plays a key role in the life cycle of HIV. Recently, we found that a combination of M50I and V151I mutations in HIV-1 integrase can suppress virus release and inhibit the initiation of Gag-Pol autoprocessing and maturation without interfering with the dimerization of Gag-Pol. Additional mutations in integrase or RNase H domain in reverse transcriptase can compensate for the defect. However, the molecular mechanism is unknown. There is no tertiary structure of the full-length HIV-1 Pol protein available for further study. Therefore, we developed a workflow to predict the tertiary structure of HIV-1 NL4.3 Pol polyprotein. The modeled structure has comparable quality compared with the recently published partial HIV-1 Pol structure (PDB ID: 7SJX). Our HIV-1 NL4.3 Pol dimer model is the first full-length Pol tertiary structure. It can provide a structural platform for studying the autoprocessing mechanism of HIV-1 Pol and for developing new potent drugs. Moreover, the workflow can be used to predict other large protein structures that cannot be resolved via conventional experimental methods.

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External Sources

  1. DOI: 10.3390/ijms25031809
  2. PMID: 38339086
  3. PMCID: PMC10855158
  4. PII : ijms25031809

Library Notes

  1. Fiscal Year: FY2023-2024
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