A Novel Approach to Develop New and Potent Inhibitors for the Simultaneous Inhibition of Protease and Helicase Activities of HCV NS3/4A Protease: A Computational Approach.
Muhammad RiazAshfaq Ur RehmanMuhammad WaqasAsaad KhalidAshraf N AbdallaArif MahmoodJunjian HuAbdul WadoodPublished in: Molecules (Basel, Switzerland) (2023)
Infection of hepatitis C (HCV) is a major threat to human health throughout the world. The current therapy program suffers from restricted efficiency and low tolerance, and there is serious demand frr novel medication. NS3/4A protease is observed to be very effective target for the treatment of HCV. A data set of the already reported HCV NS3/4A protease inhibitors was first docked into the NS3/4A protease (PDB ID: 4A92A) active sites of both protease and helicase sites for calculating the docking score, binding affinity, binding mode, and solvation energy. Then the data set of these reported inhibitors was used in a computer-based program "RECAP Analyses" implemented in MOE to fragment every molecule in the subset according to simple retrosynthetic analysis rules. The RECAP analysis fragments were then used in another computer-based program "RECAP Synthesis" to randomly recombine and generate synthetically reasonable novel chemical structures. The novel chemical structures thus produced were then docked against HCV NS3/4A. After a thorough validation of all undertaken steps, based on Lipinski's rule of five, docking score, binding affinity, solvation energy, and Van der Waal's interactions with HCV NS3/4A, 12 novel chemical structures were identified as inhibitors of HCV NS3/4A. The novel structures thus designed are hoped to play a key role in the development of new effective inhibitors of HCV.
Keyphrases
- hepatitis c virus
- dengue virus
- human immunodeficiency virus
- molecular dynamics
- molecular dynamics simulations
- human health
- high resolution
- quality improvement
- risk assessment
- healthcare
- zika virus
- electronic health record
- stem cells
- machine learning
- emergency department
- climate change
- dna binding
- hiv infected
- artificial intelligence
- protein protein
- clinical evaluation