Interdisciplinary in silico studies to understand in-depth molecular level mechanism of drug resistance involving NS3-4A protease of HCV

Abstract

Hepatitis C virus (HCV) causes hepatitis, a life-threatening disease responsible for liver cirrhosis. Urgent measures have been taken to develop therapeutics against this deadly pathogen. NS3/4A protease is an extremely important target. A series of inhibitors have been developed against this viral protease including Faldaprevir. Unfortunately, the error-prone viral RNA polymerase causes the emergence of resistance, thereby causing reduced effectiveness of those peptidomimetic inhibitors. Among the drug resistant variants, three single amino acid residues (R155, A156 and D168) are notable for their presence in clinical isolates and also their effectivity against most of the known inhibitors in clinical development. Therefore, it is crucial to understand the mechanistic role of those drug resistant variants while designing potent novel inhibitors. In this communication, we have deeply analyzed through using in silico studies to understand the molecular mechanism of alteration of inhibitor binding between wild type and its R155K, A156V and D168V variants. Principal component analysis was carried to identify the backbone fluctuations of important residues in HCV NS3/4A responsible for the inhibitor binding and maintaining drug resistance. Free energy landscape as a function of the principal components has been used to identify the stability and conformation of the key residues that regulate inhibitor binding and their impact in developing drug resistance. Our findings are consistent with the trend of experimental results. The observations are also true in case of other Faldaprevir-like peptidomimetic inhibitors. Understanding this binding mechanism would be significant for the development of novel inhibitors with less susceptibility towards drug resistance.

Communicated by Ramaswamy H. Sarma

Graphical Abstract

Keywords:

• HCV
• NS3/4A protease
• protease inhibitors
• molecular dynamics simulation
• MM-PBSA
• MM-GBSA
• drug resistance
• substrate envelope
• Residue interaction network (RIN)
• per-residue energy decomposition
• NMA
• molecular surface analysis
• serine protease
• principal component analysis
• free energy landscape

Acknowledgments

The authors are thankful to the Head, Department of Botany and Microbiology, Gurukula Kangri (Deemed to be University) for providing computer facility. We wish to thank to the other institutions for helping for conducting a part of the work, namely ICC (IIT-Roorkee), Bioinformatics Facility, Department of Biosciences and Bioengineering (IIT-Roorkee), and Bioinformatics Resources and Applications Facility (BRAF), C-DAC (Pune) for the provision of computational facilities and support.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

The author(s) reported there is no funding associated with the work featured in this article.