The recent pandemic associated with SARS-CoV-2, a virus of the Coronaviridae family, has resulted in an unprecedented number of infected people. The highly contagious nature of this virus makes it imperative for us to identify promising inhibitors from pre-existing antiviral drugs. Two druggable targets, namely 3C-like proteinase (3CLpro) and 2'-O-ribose methyltransferase (2'-O-MTase) were selected in this study due to their indispensable nature in the viral life cycle. 3CLpro is a cysteine protease responsible for the proteolysis of replicase polyproteins resulting in the formation of various functional proteins, whereas 2'-O-MTase methylates the ribose 2'-O position of the first and second nucleotide of viral mRNA, which sequesters it from the host immune system. The selected drug target proteins were screened against an in-house library of 123 antiviral drugs. Two promising drug molecules were identified for each protein based on their estimated free energy of binding (ΔG), the orientation of drug molecules in the active site and the interacting residues. The selected protein-drug complexes were then subjected to MD simulation, which consists of various structural parameters to equivalently reflect their physiological state. From the virtual screening results, two drug molecules were selected for each drug target protein [Paritaprevir (ΔG= -9.8 kcal/mol) &Raltegravir (ΔG= -7.8 kcal/mol) for 3CLpro and Dolutegravir (ΔG= -9.4 kcal/mol) and Bictegravir (ΔG= -8.4 kcal/mol) for 2'-OMTase]. After the extensive computational analysis, we proposed that Raltegravir, Paritaprevir, Bictegravir and Dolutegravir are excellent lead candidates for these crucial proteins and they could become potential therapeutic drugs against SARS-CoV-2.

The COVID-19 pandemic caused by SARS-CoV-2 has shown an exponential trend of infected people across the planet. Crediting its virulent nature, it becomes imperative to identify potential therapeutic agents against the deadly virus. The 3-chymotrypsin-like protease (3CLpro) is a cysteine protease which causes the proteolysis of the replicase polyproteins to generate functional proteins, which is a crucial step for viral replication and infection. Computational methods have been applied in recent studies to identify promising inhibitors against 3CLpro to inhibit the viral activity. This review provides an overview of promising drug/lead candidates identified so far against 3CLpro through various in silico approaches such as structure-based virtual screening (SBVS), ligand-based virtual screening (LBVS) and drug-repurposing/drug-reprofiling/drug-retasking. Further, the drugs have been classified according to their chemical structures or biological activity into flavonoids, peptides, terpenes, quinolines, nucleoside and nucleotide analogues, protease inhibitors, phenalene and antibiotic derivatives. These are then individually discussed based on the various structural parameters namely estimated free energy of binding (ΔG), key interacting residues, types of intermolecular interactions and structural stability of 3CLpro-ligand complexes obtained from the results of molecular dynamics (MD) simulations. The review provides comprehensive information of potential inhibitors identified through several computational methods thus far against 3CLpro from SARS-CoV-2 and provides a better understanding of their interaction patterns and dynamic states of free and ligand-bound 3CLpro structures.

Background: Information on the occurrence of zinc finger protein motifs in genomes is crucial to the developing field of molecular genome engineering. The knowledge of their target DNA-binding sequences is vital to develop chimeric proteins for targeted genome engineering and site-specific gene correction. There is a need to develop a computational resource of zinc finger proteins (ZFP) to identify the potential binding sites and its location, which reduce the time ofin vivotask, and overcome the difficulties in selecting the specific type of zinc finger protein and the target site in the DNA sequence.Description: ZifBASE provides an extensive collection of various natural and engineered ZFP. It uses standard names and a genetic and structural classification scheme to present data retrieved from UniProtKB, GenBank, Protein Data Bank, ModBase, Protein Model Portal and the literature. It also incorporates specialized features of ZFP including finger sequences and positions, number of fingers, physiochemical properties, classes, framework, PubMed citations with links to experimental structures (PDB, if available) and modeled structures of natural zinc finger proteins. ZifBASE provides information on zinc finger proteins (both natural and engineered ones), the number of finger units in each of the zinc finger proteins (with multiple fingers), the synergy between the adjacent fingers and their positions. Additionally, it gives the individual finger sequence and their target DNA site to which it binds for better and clear understanding on the interactions of adjacent fingers. The current version of ZifBASE contains 139 entries of which 89 are engineered ZFPs, containing 3-7F totaling to 296 fingers. There are 50 natural zinc finger protein entries ranging from 2-13F, totaling to 307 fingers. It has sequences and structures from literature, Protein Data Bank, ModBase and Protein Model Portal. The interface is cross linked to other public databases like UniprotKB, PDB, ModBase and Protein Model Portal and PubMed for making it more informative.Conclusion: A database is established to maintain the information of the sequence features, including the class, framework, number of fingers, residues, position, recognition site and physio-chemical properties (molecular weight, isoelectric point) of both natural and engineered zinc finger proteins and dissociation constant of few. ZifBASE can provide more effective and efficient way of accessing the zinc finger protein sequences and their target binding sites with the links to their three-dimensional structures. All the data and functions are available at the advanced web-based search interfacehttp://web.iitd.ac.in/~sundar/zifbase.

Gallic acid (PubChem CID: 370) and quercetin (PubChem CID: 5280343) are major phenolic compounds in many mangrove plants that have been related to health cure. In the present study, the active fractions namely gallic acid (1) and quercetin (2) were isolated from the methanolic extract of leaves of Ceriops tagal in a Tropical mangrove ecosystem of Andaman and Nicobar Island (ANI), India. The chemical structures were determined by spectroscopic analysis: Fourier-Transform Infrared spectroscopy (FT-IR), ¹H, ¹³C Nuclear Magnetic Resonance (NMR) spectroscopy, and High-resolution mass spectrometry (HRMS). The anticancer activity of isolated compounds (1) and (2) were evaluated by in vitro assays against two human cancer cell lines namely, HeLa (Cervical) and MDA-MB231 (Breast) cancer cells revealed that IC₅₀ values of gallic acid (HeLa: 4.179197 ± 0.45 µg/ml; MDA-MB231: 80.0427 ± 0.19 µg/ml at 24 h) and quercetin (HeLa: 99.914 ± 0.18 µg/ml; MDA-MB231: 18.288382 ± 0.12 µg/ml at 24 h), respectively. Antioxidant properties of gallic acid (1) and quercetin (2) are found to be IC₅₀ value of 0.77 ± 0.41 µg/ml and 1.897 ± 0.81 µg/ml, respectively. Molecular docking results explained that gallic acid (1) and quercetin (2) showed estimated binding free energy (ΔG) of −5.4 and −6.9 kcal/mol towards drug target Bcl-B protein, respectively. The estimated inhibition constant (Ki) for these two molecules are 110 and 8.75 μM, respectively. The MD simulation additionally supported that quercetin molecule is significantly improved the structural stability of Bcl-B protein. The present study provides key insights about the importance of polyphenols, and thus leads to open the therapeutic route for anti-cancer drug discovery process. Communicated by Ramaswamy H. Sarma