Identification of Suitable Natural Inhibitor against Influenza A (H1N1) Neuraminidase Protein by Molecular Docking

The influenza A (H1N1) virus, also known as swine flu is a leading cause of morbidity and mortality since 2009. There is a need to explore novel anti-viral drugs for overcoming the epidemics. Traditionally, different plant extracts of garlic, ginger, kalmegh, ajwain, green tea, turmeric, menthe, tulsi, etc. have been used as hopeful source of prevention and treatment of human influenza. The H1N1 virus contains an important glycoprotein, known as neuraminidase (NA) that is mainly responsible for initiation of viral infection and is essential for the life cycle of H1N1. It is responsible for sialic acid cleavage from glycans of the infected cell. We employed amino acid sequence of H1N1 NA to predict the tertiary structure using Phyre2 server and validated using ProCheck, ProSA, ProQ, and ERRAT server. Further, the modelled structure was docked with thirteen natural compounds of plant origin using AutoDock4.2. Most of the natural compounds showed effective inhibitory activity against H1N1 NA in binding condition. This study also highlights interaction of these natural inhibitors with amino residues of NA protein. Furthermore, among 13 natural compounds, theaflavin, found in green tea, was observed to inhibit H1N1 NA proteins strongly supported by lowest docking energy. Hence, it may be of interest to consider theaflavin for further in vitro and in vivo evaluation.

Virtual Screening for Potential Inhibitors of NS3 Protein of Zika Virus

Zika virus (ZIKV) is a mosquito borne pathogen, belongs to Flaviviridae family having a positive-sense single-stranded RNA genome, currently known for causing large epidemics in Brazil. Its infection can cause microcephaly, a serious birth defect during pregnancy. The recent outbreak of ZIKV in February 2016 in Brazil realized it as a major health risk, demands an enhanced surveillance and a need to develop novel drugs against ZIKV. Amodiaquine, prochlorperazine, quinacrine, and berberine are few promising drugs approved by Food and Drug Administration against dengue virus which also belong to Flaviviridae family. In this study, we performed molecular docking analysis of these drugs against nonstructural 3 (NS3) protein of ZIKV. The protease activity of NS3 is necessary for viral replication and its prohibition could be considered as a strategy for treatment of ZIKV infection. Amongst these four drugs, berberine has shown highest binding affinity of –5.8 kcal/mol and it is binding around the active site region of the receptor. Based on the properties of berberine, more similar compounds were retrieved from ZINC database and a structure-based virtual screening was carried out by AutoDock Vina in PyRx 0.8. Best 10 novel drug-like compounds were identified and amongst them ZINC53047591 (2-(benzylsulfanyl)-3-cyclohexyl-3H-spiro[benzo[h]quinazoline-5,1'-cyclopentan]-4(6H)-one) was found to interact with NS3 protein with binding energy of –7.1 kcal/mol and formed H-bonds with Ser135 and Asn152 amino acid residues. Observations made in this study may extend an assuring platform for developing anti-viral competitive inhibitors against ZIKV infection.

In Silico Docking to Explicate Interface between Plant-Originated Inhibitors and E6 Oncogenic Protein of Highly Threatening Human Papillomavirus 18

The leading cause of cancer mortality globally amongst the women is due to human papillomavirus (HPV) infection. There is need to explore anti-cancerous drugs against this life-threatening infection. Traditionally, different natural compounds such as withaferin A, artemisinin, ursolic acid, ferulic acid, (-)-epigallocatechin-3-gallate, berberin, resveratrol, jaceosidin, curcumin, gingerol, indol-3-carbinol, and silymarin have been used as hopeful source of cancer treatment. These natural inhibitors have been shown to block HPV infection by different researchers. In the present study, we explored these natural compounds against E6 oncoprotein of high risk HPV18, which is known to inactivate tumor suppressor p53 protein. E6, a high throughput protein model of HPV18, was predicted to anticipate the interaction mechanism of E6 oncoprotein with these natural inhibitors using structure-based drug designing approach. Docking analysis showed the interaction of these natural inhibitors with p53 binding site of E6 protein residues 108-117 (CQKPLNPAEK) and help reinstatement of normal p53 functioning. Further, docking analysis besides helping in silico validations of natural compounds also helped elucidating the molecular mechanism of inhibition of HPV oncoproteins.

Elucidating Molecular Interactions of Natural Inhibitors with HPV-16 E6 Oncoprotein through Docking Analysis

Human papillomavirus (HPV) infection is the leading cause of cancer mortality among women worldwide. The life-threatening infection caused by HPV demands the need for designing anticancerous drugs. In the recent years, different compounds from natural origins, such as carrageenan, curcumin, epigallocatechin gallate, indole-3-carbinol, jaceosidin, and withaferin, have been used as a hopeful source of anticancer therapy. These compounds have been shown to suppress HPV infection by different researchers. In the present study, we explored these natural inhibitors against E6 oncoprotein of high-risk HPV-16, which is known to inactivate the p53 tumor suppressor protein. A robust homology model of HPV-16 E6 was built to anticipate the interaction mechanism of E6 oncoprotein with natural inhibitory molecules using a structure-based drug designing approach. Docking analysis showed the interaction of these natural compounds with the p53-binding site of E6 protein residues 113-122 (CQKPLCPEEK) and helped the restoration of p53 functioning. Docking analysis, besides helping in silico validation of natural compounds, also helps understand molecular mechanisms of protein-ligand interactions.

Understanding Rifampicin Resistance in Tuberculosis through a Computational Approach

The disease tuberculosis, caused by Mycobacterium tuberculosis (MTB), remains a major cause of morbidity and mortality in developing countries. The evolution of drug-resistant tuberculosis causes a foremost threat to global health. Most drug-resistant MTB clinical strains are showing resistance to isoniazid and rifampicin (RIF), the frontline anti-tuberculosis drugs. Mutation in rpoB, the beta subunit of DNA-directed RNA polymerase of MTB, is reported to be a major cause of RIF resistance. Amongst mutations in the well-defined 81-base-pair central region of the rpoB gene, mutation at codon 450 (S450L) and 445 (H445Y) is mainly associated with RIF resistance. In this study, we modeled two resistant mutants of rpoB (S450L and H445Y) using Modeller9v10 and performed a docking analysis with RIF using AutoDock4.2 and compared the docking results of these mutants with the wild-type rpoB. The docking results revealed that RIF more effectively inhibited the wild-type rpoB with low binding energy than rpoB mutants. The rpoB mutants interacted with RIF with positive binding energy, revealing the incapableness of RIF inhibition and thus showing resistance. Subsequently, this was verified by molecular dynamics simulations. This in silico evidence may help us understand RIF resistance in rpoB mutant strains.

hpvPDB: An Online Proteome Reserve for Human Papillomavirus

Human papillomavirus (HPV) infection is the leading cause of cancer mortality among women worldwide. The molecular understanding of HPV proteins has significant connotation for understanding their intrusion in the host and designing novel protein vaccines and anti-viral agents, etc. Genomic, proteomic, structural, and disease-related information on HPV is available on the web; yet, with trivial annotations and more so, it is not well customized for data analysis, host-pathogen interaction, strain-disease association, drug designing, and sequence analysis, etc. We attempted to design an online reserve with comprehensive information on HPV for the end users desiring the same. The Human Papillomavirus Proteome Database (hpvPDB) domiciles proteomic and genomic information on 150 HPV strains sequenced to date. Simultaneous easy expandability and retrieval of the strain-specific data, with a provision for sequence analysis and exploration potential of predicted structures, and easy access for curation and annotation through a range of search options at one platform are a few of its important features. Affluent information in this reserve could be of help for researchers involved in structural virology, cancer research, drug discovery, and vaccine design.