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.

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.

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.

Human papillomavirus (HPV), a life-threatening infection is the leading cause of cancer mortality among women worldwide and needs for designing anti-cancerous drugs. In the present study, we explored specific novel inhibitors against E6 onco-protein of high risk HPV 16, known to inactivate tumor suppressor p53 protein. A homology model of HPV 16 E6 was built and validated using bioinformatics approach. A total of 5000 drug like compounds were downloaded from ZINC database based on the properties similar to the known inhibitor Jaceosidin (5, 7-Dihydroxy-2-(4-hydroxy-3-methoxyphenyl)-6-methoxy-4H-chromen-4-one). Virtual-ligand-screenings approaches were applied to screen appropriate drug like compounds using molecular docking program Auto Dock Vina in PyRx 0.8 and 5 best novel drug-like compounds were identified as potential competitive inhibitors against HPV 16 E6 compared to Jaceosidin. Two amongst these 5 identified most potential inhibitors, N-[(5-methyl-1Hbenzimidazol-2-yl)methyl]-4-oxo-3, 4-dihydrophthalazine-1-carboxamide and 6-[3-(3-fluoro-4-methyl-phenyl)-1, 2, 4-oxadiazol-5-yl]-1, 4-dihydroquinoxaline-2, 3-dione were found to interact with E6 with binding energy of -7.7 and -7.0 Kcal/mol respectively and form H-bonds with p53 binding site of E6 protein residues 113-122 (CQKPLCPEEK). These two inhibitors may help restoration of p53 functioning. The Bioinformatics approach extends a promising platform for developing anti-cancerous competitive inhibitors targeting high-risk HPV 16.

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.