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Background: In recent days, COVID-19 cases are increasing globally at an alarming rate due to the COVID-19 second wave despite the mass vaccination programs. Search for the potential vaccine for SARS-CoV-2 is still under progress. The epitope-based vaccine is effective and is a cornerstone in vaccine development. The quick prediction of epitopes could be a proficient way to monitor vaccine development during a global health crisis. Objective: This study is designed to predict the potential epitopes with computational tools for vaccine development. Methods: NetCTLpan v. 1.1 and NetMHCIIpan v. 3.2 servers were used for T-cell epitope analysis. IEDB servers were employed for HLA and DRB1 peptide calculations. The epitope Immunogenicity, toxicity, physiochemical character, and other features are measured by immunogen evaluation. Furthermore, the top-ranked immunogenic epitopes were computationally validated by molecular docking analysis. The epitopes are docked to Toll-like receptors (TLRs), which is helpful to generate an immune response against SARS-CoV-2. Results: Overall, six HTL and CTL epitopes were predicted (IDGYFKIYSKH, HPLSHFVNLDNL, RIGNNYKLNT, and WTAGAAAYYVG, MACLVGLMWLS, FRLKGGAPIKGVT), which had good immunogenicity scores, and stable interaction with Toll-like receptor (TLR). Therefore, these epitopes can bind with HLA and DRB1 molecules, respectively. Conclusion: The computationally predicted antigenic regions might be considered for epitope-based vaccine against SARS-CoV-2 after in vitro

The novel SARS-CoV-2 uses ACE2 (Angiotensin-Converting Enzyme 2) receptor as an entry point. Insights on S protein receptor-binding domain (RBD) interaction with ACE2 receptor and drug repurposing has accelerated drug discovery for the novel SARS-CoV-2 infection. Finding small molecule binding sites in S protein and ACE2 interface is crucial in search of effective drugs to prevent viral entry. In this study, we employed molecular dynamics simulations in mixed solvents together with virtual screening to identify small molecules that could be potential inhibitors of S protein -ACE2 interaction. Observation of organic probe molecule localization during the simulations revealed multiple sites at the S protein surface related to small molecule, antibody, and ACE2 binding. In addition, a novel conformation of the S protein was discovered that could be stabilized by small molecules to inhibit attachment to ACE2. The most promising binding site on RBD-ACE2 interface was targeted with virtual screening and top-ranked compounds (DB08248, DB02651, DB03714, and DB14826) are suggested for experimental testing. The protocol described here offers an extremely fast method for characterizing key proteins of a novel pathogen and for the identification of compounds that could inhibit or accelerate spreading of the disease.

Key message: Overexpression of OsiSAP8 driven by Port Ubi2.3 from Porteresia coarctata imparts drought and salinity stress tolerance in transgenic rice. Stress associated proteins (SAPs) possess the zinc-finger domains that are wildly evolving functional and conserved regions/factors in plants to combat abiotic stresses. In this study, the promoter region of OsiSAP8, an intron-less, multiple stress inducible gene, was compared in silico with a strong constitutive promoter, Port Ubi2.3. This resulted in developing rice, resistant to drought and salinity expressing OsiSAP8 promoted by Port Ubi2.3. (Porteresia coarctata), through Agrobacterium-mediated transformation in the popular rice varieties, IR36 and IR64. Southern blot hybridization confirmed the integration of OsiSAP8, and the T0 transgenic lines of IR36 and IR64 were evaluated for their drought and salinity tolerance. The IR36-T1 progenies showed an enhanced tolerance to water withhold stress compared to wild type and IR64-T1 progenies. Physiological parameters, such as the panicle weight, number of panicles, leaf wilting, and TBARS assay, showed the transgenic IR36 to be superior. The transgenic lines performed better with higher 80–95% relative leaf water content when subjected to drought for 14 days. Gene expression analysis of OsiSAP8 in IR36 T1 showed a 1.5-fold upregulation under mannitol stress. However, IR64 T1 showed a two-fold upregulation in NaCl stress. An enhanced drought and salinity stress tolerance in the transgenic IR36 cultivar through overexpression of OsiSAP8 was observed as it had a native copy of OsiSAP8. This is perhaps the first study using a novel ubiquitin promoter (Port Ubi2.3) to generate drought and salinity stress-tolerant transgenic rice. Thus, we report the overexpression of a rice gene (OsiSAP8) by a rice promoter (Port Ubi2.3) in rice (IR36) to resist drought and salinity.

Diabetes mellitus has become a troublesome and increasingly widespread condition. Treatment strategies for diabetes prevention in high-risk as well as in affected individuals are largely attributed to improvements in lifestyle and dietary control. Therefore, it is important to understand the nutritional factors to be used in dietary intervention. A decreased risk of diabetes is associated with daily intake of millet-based foods. Pearl millet is a highly nutritious grain, nutritionally comparable and even superior in calories, protein, vitamins, and minerals to other large cereals, although its intake is confined to lower income segments of society. Pearl millet contains phenolic compounds which possess antidiabetic activity. Thus, it can be used to prepare a variety of food products for diabetes mellitus. Moreover, it also has many health benefits, including combating diabetes mellitus, cancer, cardiovascular conditions, decreasing tumour occurrence, lowering blood pressure, heart disease risk, cholesterol, and fat absorption rate. Therefore, the current review addresses the role of pearl millet in managing diabetes.

Background: Syzygium densiflorum Wall. ex Wight & Arn (Myrtaceae) has been traditionally used by the local tribes of the Nilgiris, Tamil Nadu, India, for the treatment of diabetes. Objective: This study aimed to isolate the major phytoconstituents from the S. densiflorum fruits and to perform computational studies for chemical reactivity and biological activity of the isolated compound. Materials and Methods: Two different compounds were isolated from ethanolic extract of S. densiflorum fruits and purified using HPLC. The structures of the compounds were elucidated on the basis of their 1H NMR, 13C NMR, 1H-1H COSY, HMBC, HRESIMS, and FT-IR data. Further, the chemical reactivity of the compounds was analyzed by density functional theory calculations and its therapeutic role in diabetic management was examined by comparing the structure of isolated compounds with previously reported bioactive compounds. Results: Of the two compounds ((6,6 & 1-kestopentaose (1) and 6-(hydroxymethyl)-3-[3,4,5- trihydroxy- 6-[(3,4,5-trihydroxyoxan-2-yl)oxymethyl]oxan-2-yl]oxyoxane-2,4,5-triol)(2)). β-glucosidase, β-galactosidase, α-glucosidase and β-amylase inhibition activity of the compounds were predicted by structure activity relationship. Conclusion: Structure-activity relationship analysis was performed to predict the therapeutic role of isolated compounds. These computational studies may be performed to minimize the efforts to determine the therapeutic role of natural compounds.

The COVID-19 pandemic, caused by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a severe global health crisis now. SARS-CoV-2 utilizes its Spike protein receptor-binding domain (S-protein) to invade human cell through binding to Angiotensin-Converting Enzyme 2 receptor (ACE2). S-protein is the key target for many therapeutics and vaccines. Potential S-protein-ACE2 fusion inhibitor is expected to block the virus entry into the host cell. In many countries, traditional practices, based on natural products (NPs) have been in use to slow down COVID-19 infection. In this study, a protocol was applied that combines mixed solvent molecular dynamics simulations (MixMD) with high-throughput virtual screening (HTVS) to search NPs to block SARS-CoV-2 entry into the human cell. MixMD simulations were employed to discover the most promising stable binding conformations of drug-like probes in the S-protein-ACE2 interface. Detected stable sites were used for HTVs of 612093 NPs to identify molecules that could interfere with the S-protein-ACE2 interaction. In total, 19 NPs were selected with rescoring model. These top-ranked NP-S-protein complexes were subjected to classical MD simulations for 300 ns (3 replicates of 100 ns) to estimate the stability and affinity of binding. Three compounds, ZINC000002128789, ZINC000002159944 and SN00059335, showed better stability in all MD runs, of which ZINC000002128789 was predicted to have the highest binding affinity, suggesting that it could be effective modulator in RBD-ACE2 interface to prevent SARS-CoV-2 infection. Our results support that NPs may provide tools to fight COVID-19.

Recent advancements in genomics and proteomics provide a solid foundation for understanding the pathogenesis of diabetes. Proteomics of diabetes associated pathways help to identify the most potent target for the management of diabetes. The relevant datasets are scattered in various prominent sources which takes much time to select the therapeutic target for the clinical management of diabetes. However, additional information about target proteins is needed for validation. This lacuna may be resolved by linking diabetes associated genes, pathways and proteins and it will provide a strong base for the treatment and planning management strategies of diabetes. Thus, a web source "Diabetes Associated Proteins Database (DAPD)" has been developed to link the diabetes associated genes, pathways and proteins using PHP, MySQL. The current version of DAPD has been built with proteins associated with different types of diabetes. In addition, DAPD has been linked to external sources to gain the access to more participatory proteins and their pathway network. DAPD will reduce the time and it is expected to pave the way for the discovery of novel anti-diabetic leads using computational drug designing for diabetes management. DAPD is open accessed via following url www.mkarthikeyan.bioinfoau.org/dapd.