4.7 Article

Identification of Potential Cytochrome P450 3A5 Inhibitors: An Extensive Virtual Screening through Molecular Docking, Negative Image-Based Screening, Machine Learning and Molecular Dynamics Simulation Studies

Journal

Publisher

MDPI
DOI: 10.3390/ijms23169374

Keywords

cardiovascular diseases; virtual screening; molecular docking; negative image-based screening; machine learning

Funding

  1. Ministry of SMEs and Startups, Korea [S2788640]
  2. Korea Technology & Information Promotion Agency for SMEs (TIPA) [S2788640] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This study screened the PubChem database and used molecular docking and machine learning to identify potential CYP3A5 molecules for therapeutic applications in cardiovascular diseases. In silico pharmacokinetics and toxicity assessments showed that five molecules had acceptable profiles. Molecular dynamics simulations revealed the dynamic behavior of the molecules in CYP3A5 and binding free energy calculations confirmed their high binding affinity. Further in vitro and in vivo validations are needed.
Cytochrome P450 3A5 (CYP3A5) is one of the crucial CYP family members and has already proven to be an important drug target for cardiovascular diseases. In the current study, the PubChem database was screened through molecular docking and high-affinity molecules were adopted for further assessment. A negative image-based (NIB) model was used for a similarity search by considering the complementary shape and electrostatics of the target and small molecules. Further, the molecules were segregated into active and inactive groups through six machine learning (ML) matrices. The active molecules found in each ML model were used for in silico pharmacokinetics and toxicity assessments. A total of five molecules followed the acceptable pharmacokinetics and toxicity profiles. Several potential binding interactions between the proposed molecules and CYP3A5 were observed. The dynamic behavior of the selected molecules in the CYP3A5 was explored through a molecular dynamics (MD) simulation study. Several parameters obtained from the MD simulation trajectory explained the stability of the protein-ligand complexes in dynamic states. The high binding affinity of each molecule was revealed by the binding free energy calculation through the MM-GBSA methods. Therefore, it can be concluded that the proposed molecules might be potential CYP3A5 molecules for therapeutic application in cardiovascular diseases subjected to in vitro/in vivo validations.

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