Deepak Kumar Behera

Bio: Deepak Kumar Behera is an academic researcher from Siksha O Anusandhan University. The author has contributed to research in topics: Virtual screening & Pharmacophore. The author has an hindex of 4, co-authored 5 publications receiving 23 citations.

Pharmacophore modelling, virtual screening and molecular docking studies on PLD1 inhibitors.

Abstract: Lipid metabolism plays a significant role in influenza virus replication and subsequent infection. The regulatory mechanism governing lipid metabolism and viral replication is not properly understood to date, but both Phospholipase D (PLD1 and PLD2) activities are stimulated in viral infection. In vitro studies indicate that chemical inhibition of PLD1 delays viral entry and reduction of viral loads. The current study reports a three-dimensional pharmacophore model based on 35 known PLD1 inhibitors. A sub-set of 25 compounds was selected as the training set and the remaining 10 compounds were kept in the test set. One hundred and twelve pharmacophore models were generated; a six-featured pharmacophore model (AADDHR.57) with survival score (2.69) produced a statistically significant three-dimensional quantitative structure-activity relationship model with r2 = 0.97 (internal training set), r2 = 0.71 (internal test set) and Q2 = 0.64. The predictive power of the pharmacophore model was validated with an external test set (r2 = 0.73) and a systematic virtual screening work-flow was employed showing an enrichment factor of 23.68 at the top 2% of the dataset (active and decoys). Finally, the model was used for screening of the filtered PubChem database to fetch molecules which can be proposed as potential PLD1 inhibitors for blocking influenza infection.

Molecular modeling and identification of novel glucokinase activators through stepwise virtual screening.

Abstract: The glucose phosphorylating enzyme glucokinase (GK) is a 50 kD monomeric protein having 465 amino acids. It maintains glucose homeostasis inside cells, acts as a glucose sensor in pancreatic β-cells and as a rate controlling enzyme for hepatic glucose clearance and glycogen synthesis. It has two binding sites, one for binding d -glucose and the other for a putative allosteric activator named glucokinase activator (GKA). The GKAs interact with the same region of the GK enzyme that is commonly affected by naturally occurring mutations in humans. However, many GKAs do not bind to GK in the absence of glucose. Recently, it has been reported that GKAs are highly effective in patients with type 2 diabetes mellitus. In this milieu a molecular modeling study has been carried out on three natural variants of GK that lie in the GKA binding site and are known to cause maturity onset diabetes of young (MODY). Additionally, a 10 ns molecular dynamics simulation was done on each of the modeled variant in order to explore the flexibility of this site. Subsequently, a systematic virtual screening study was done to identify compounds which can bind with high affinity at GKA binding site of mutant GK.

In Silico Biology of H1N1: Molecular Modelling of Novel Receptors and Docking Studies of Inhibitors to Reveal New Insight in Flu Treatment

Abstract: Influenza is an infectious disease caused by RNA viruses of the family Orthomyxoviridae The new influenza H1N1 viral stain has emerged by the genetic combination of genes from human, pig, and bird's H1N1 virus The influenza virus is roughly spherical and is enveloped by a lipid membrane There are two glycoproteins in this lipid membrane; namely, hemagglutinin (HA) which helps in attachment of the viral strain on the host cell surface and neuraminidase (NA) that is responsible for initiation of viral infection We have developed homology models of both Hemagglutinin and Neuraminidase receptors from H1N1 strains in eastern India The docking studies of B-Sialic acid and O-Sialic acid in the optimized and energy-minimized homology models show important H-bonding interactions with ALA142, ASP230, GLN231, GLU232, and THR141 This information can be used for structure-based and pharmacophore-based new drug design We have also calculated ADME properties (Human Oral Absorption (HOA) and % HOA) for Oseltamivir which have been subject of debate for long

In silico expressed sequence tag analysis in identification of probable diabetic genes as virtual therapeutic targets.

Abstract: The expressed sequence tags (ESTs) are major entities for gene discovery, molecular transcripts, and single nucleotide polymorphism (SNPs) analysis as well as functional annotation of putative gene products In our quest for identification of novel diabetic genes as virtual targets for type II diabetes, we searched various publicly available databases and found 7 reported genes The in silico EST analysis of these reported genes produced 6 consensus contigs which illustrated some good matches to a number of chromosomes of the human genome Again the conceptual translation of these contigs produced 3 protein sequences The functional and structural annotations of these proteins revealed some important features which may lead to the discovery of novel therapeutic targets for the treatment of diabetes

Development and validation of pharmacophore and QSAR models for influenza PB2 inhibitors

Abstract: The Swine influenza is a highly contagious respiratory disease caused by one of several swine influenza A viruses. The viral replication complex of H1N1, formed by three proteins PA, PB1 and PB2, plays a major role in host adaptation and subsequent infection. The conserved interaction sites of these three proteins have been suggested as potential drug targets and several inhibitors are designed for the purpose. We report a six featured 3D pharmacophore model based on 38 reported inhibitors of PB2. It was used for development of a statistically significant 3D QSAR model with R 2 = 0.70 (internal training set), R 2 = 0.67 (internal test set) and Q 2 (0.64). The predictive power of concerned pharmacophore model was validated with an external test set R 2 (0.54) and used for screening of filtered PubChem database to fetch some important molecules. Both pharmacophore and QSAR models gave detailed structural insights as well as highlighted important features which can help in the design of potential PB2 inhibitors in future.

Proteome scale comparative modeling for conserved drug and vaccine targets identification in Corynebacterium pseudotuberculosis

Abstract: Corynebacterium pseudotuberculosis (Cp) is a pathogenic bacterium that causes caseous lymphadenitis (CLA), ulcerative lymphangitis, mastitis, and edematous to a broad spectrum of hosts, including ruminants, thereby threatening economic and dairy industries worldwide. Currently there is no effective drug or vaccine available against Cp. To identify new targets, we adopted a novel integrative strategy, which began with the prediction of the modelome (tridimensional protein structures for the proteome of an organism, generated through comparative modeling) for 15 previously sequenced C. pseudotuberculosis strains. This pan-modelomics approach identified a set of 331 conserved proteins having 95-100% intra-species sequence similarity. Next, we combined subtractive proteomics and modelomics to reveal a set of 10 Cp proteins, which may be essential for the bacteria. Of these, 4 proteins (tcsR, mtrA, nrdI, and ispH) were essential and non-host homologs (considering man, horse, cow and sheep as hosts) and satisfied all criteria of being putative targets. Additionally, we subjected these 4 proteins to virtual screening of a drug-like compound library. In all cases, molecules predicted to form favorable interactions and which showed high complementarity to the target were found among the top ranking compounds. The remaining 6 essential proteins (adk, gapA, glyA, fumC, gnd, and aspA) have homologs in the host proteomes. Their active site cavities were compared to the respective cavities in host proteins. We propose that some of these proteins can be selectively targeted using structure-based drug design approaches (SBDD). Our results facilitate the selection of C. pseudotuberculosis putative proteins for developing broad-spectrum novel drugs and vaccines. A few of the targets identified here have been validated in other microorganisms, suggesting that our modelome strategy is effective and can also be applicable to other pathogens.

Corona virus SARS-CoV-2 disease COVID-19: Infection, prevention and clinical advances of the prospective chemical drug therapeutics

Abstract: The recent outbreak of Corona virus SARS-CoV-2 disease COVID-19 in the China and subsequent intermittent spread of infection to other countries has alarmed the medical and scientific community mainly because of lethal nature of this infection. Being a new virus in the category, the immediate emergency therapy is not available for the treatment of this disease, leading to widespread fear of infection and has created social issues for infected peoples. Herein, the epidemiology of COVID-19 infection, transmission characteristics of SARS-CoV-2 virus spread, effectiveness of preventive measures, coronavirus family, structural characteristics of virus, current literature advances for the diagnostics development (RT-PCR, CT-Scan, Elisa) and possible drug development based virus life cycle (Entry inhibitors, replication inhibitors, nucleoside, nucleotide, protease inhibitors, heterocyclic drugs, including biological therapeutics (monoclonal antibodies therapy, vaccine development) and herbal formulations have been reviewed. The chemical drug molecules with prospective application in the treatment of COVID-19 have been included in the discussion.

Promising Anti-influenza Properties of Active Constituent of Withania somnifera Ayurvedic Herb in Targeting Neuraminidase of H1N1 Influenza: Computational Study

Abstract: Neuraminidase (NA) is a membrane surface antigen which helps in the release of influenza viruses from the host cells after replication. Anti-influenza drugs such as zanamivir bind with eight highly conserved functional residues (R118, D151, R152, R224, E276, R292, R371, and Y406) in the active site of NA, thus restricting the viral release the from host cells. Binding of the drug in active site inhibits the ability of enzyme to cleave sialic acid residues on the cell membrane. Reports on the emergence of zanamivir-resistant strains of H1N1 Influenza virus necessitated a search for alternative drug candidates, preferably from plant source due to their known benefits such as less or no side effects, availability, and low cost. Withaferin A (WA), an active constituent of Withania somnifera ayurvedic herb, has been shown to have a broad range of medicinal properties including its anti-viral activity. The present study demonstrated that WA has the potential to attenuate the neuraminidase of H1N1 influenza. Our docking and simulation results predicted high binding affinity of the WA toward NA and revealed several interesting molecular interactions with the residues which are catalytically important during molecular dynamic simulations. The results presented in the article could be of high importance for further designing of target-specific anti-influenza drug candidates.

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

Abstract: 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.

Drug repositioning: current approaches and their implications in the precision medicine era

Abstract: Introduction: Drug repositioning implies finding new medical uses for existing drugs. It represents a cost-efficient approach, since the new indications are built on the basis of available informat...