Drug Re-positioning Studies for Novel HIV-1 Inhibitors Using Binary QSAR Models and Multi-target-driven In Silico Studies

Berna Dogan*, Serdar Durdagi*

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

8 Atıf (Scopus)

Özet

Current antiretroviral therapies against HIV involve the usage of at least two drugs that target different stages of HIV life cycle. However, potential drug interactions and side effects pose a problem. A promising concept for complex disease treatment is ‘one molecule-multiple target’ approach to overcome undesired effects of multiple drugs. Additionally, it is beneficial to consider drug re-purposing due to the cost of taking a drug into the market. Taking these into account, here potential anti-HIV compounds are suggested by virtually screening small approved drug molecules and clinical candidates. Initially, binary QSAR models are used to predict the therapeutic activity of around 7900 compounds against HIV and to predict the toxicity of molecules with high therapeutic activities. Selected compounds are considered for molecular docking studies against two targets, HIV-1 protease enzyme, and chemokine co-receptor CCR5. The top docking poses for all 549 molecules are then subjected to short (1 ns) individual molecular dynamics (MD) simulations and they are ranked based on their calculated relative binding free energies. Finally, 25 molecules are selected for long (200 ns) MD simulations, and 5 molecules are suggested as promising multi-target HIV agents. The results of this study may open new avenues for the designing of new dual HIV-1 inhibitor scaffolds.

Orijinal dilİngilizce
Makale numarası2000012
DergiMolecular Informatics
Hacim40
Basın numarası2
DOI'lar
Yayın durumuYayınlandı - Şub 2021
Harici olarak yayınlandıEvet

Bibliyografik not

Publisher Copyright:
© 2020 Wiley-VCH GmbH

Finansman

This study has been financially funded by Scientific and Technological Research Council of Turkey (TUBITAK) under the program of TUBITAK‐2218.

FinansörlerFinansör numarası
Türkiye Bilimsel ve Teknolojik Araştırma KurumuTUBITAK‐2218

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