SARS Coronavirus-2 (SARS-CoV-2) pandemic has become a global issue which has raised the concern of scientific community to design and discover a countermeasure against this deadly virus. So far, the pandemic has caused the death of hundreds of thousands of people upon infection and spreading. To date, no effective vaccine is available which can combat the infection caused by this virus. Therefore, this study was conducted to design possible epitope-based subunit vaccines against the SARS-CoV-2 virus using the approaches of reverse vaccinology and immunoinformatics. Upon continual computational experimentation, three possible vaccine constructs were designed and one vaccine construct was selected as the best vaccine based on molecular docking study which is supposed to effectively act against the SARS-CoV-2. Thereafter, the molecular dynamics simulation and in silico codon adaptation experiments were carried out in order to check biological stability and find effective mass production strategy of the selected vaccine. This study should contribute to uphold the present efforts of the researches to secure a definitive preventative measure against this lethal disease.

Wuhan Novel Coronavirus (2019-nCoV) outbreak has become global pandemic which has raised the concern of scientific community to deign and discover a definitive cure against this deadly virus which has caused deaths of numerous infected people upon infection and spreading. To date, there is no antiviral therapy or vaccine is available which can effectively combat the infection caused by this virus. This study was conducted to design possible epitope-based subunit vaccines against the 2019-nCoV using the approaches of reverse vaccinology and immunoinformatics. Upon continual computational experimentation three possible vaccine constructs were designed and one vaccine construct was selected as the best vaccine based on molecular docking study which is supposed to effectively act against the Wuhan Novel Coronavirus. Later, molecular dynamics simulation and in silico codon adaptation experiments were carried out in order to check biological stability and find effective mass production strategy of the selected vaccine. Hopefully, this study will contribute to uphold the present efforts of the researches to secure a definitive treatment against this nasty virus.

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Highlights Insight into the role of surfactin on B. subtilis cell differentiation. Insight into the molecular genetics of surfactin and its production . Graphical presentation of surfactin mediated signaling cascades via quorum sensing .

Cancer comprises a group of diseases which are involved in the aberrant growth of the cells causing disruption of normal body function. Due to the lack of proper sophisticated treatments this nasty disease leads to the death of most of the patients affected with it. Moreover, treatments like chemotherapy involve other post-treatment complications which make them unfavorable for extended use. Medicinal plants possess many phytochemicals of great therapeutic value and many of them are effective in killing cancer cells. These compounds working by variety of mechanisms and in most of the cases exhibit their anticancer potentiality by inhibiting many proteins involved in cell growth and division. Molecular docking is a computational approach which facilitates the finding of the best molecule from a group which may bind with the highest affinity with the intended target by providing a virtual biological system. This process works on the basis of specific algorithm and involves scoring function to rank the molecules that fit with the target. This study has been designed to investigate the potentiality of four phytochemicals from Clitoria ternatea-Kaempferol, Myricetin, P-Hydroxycinnamic acid and Quercetin as inhibitors of two cell cycle checkpoint proteins-Cyclin Dependent Kinase-2 (CDK-2) and Cyclin Dependent Kinase-6 (CDK-6) in Cyclin/CDK pathway. Quercetin and Myricetin docked with higher affinity with CDK-2 and CDK-6 respectively. Drug likeness property analysis and ADME/T test impose computational approach to investigate physicochemical and pharmacological properties of candidate drug molecules.

Ebola virus is a highly pathogenic RNA virus that causes haemorrhagic fever in human. With very high mortality rate, Ebola virus is considered as one of the dangerous viruses in the world. Although, the Ebola outbreaks claimed many lives in the past, no satisfactory treatment or vaccine have been discovered yet to fight against Ebola. For this reason, in this study, various tools of bioinformatics and immunoinformatics were used to design possible vaccines against Zaire Ebola virus strain Mayinga-76. To construct the vaccine, three potential antigenic proteins of the virus, matrix protein VP40, envelope glycoprotein and nucleoprotein were selected against which the vaccines would be designed. The MHC class-I, MHC class-II and B-cell epitopes were determined and after robust analysis through various tools and molecular docking analysis, three vaccine candidates, designated as EV-1, EV-2 and EV-3, were constructed. Since the highly conserved epitopes were used for vaccine construction, these vaccine constructs are also expected to be effective on other strains of Ebola virus like strain Gabon-94 and Kikwit-95. Next, the molecular docking study on these vaccine constructs were analyzed by molecular docking study and EV-1 emerged as the best vaccine construct. Later, molecular dynamics simulation study revealed the good performances as well as good stability of the vaccine protein. Finally, codon adaptation and in silico cloning were conducted to design a possible plasmid (pET-19b plasmid vector was used) for large scale, industrial production of the EV-1 vaccine.

In this study Curcumin and their different analogues have been analyzed as the inhibitors of signaling proteins i.e., Cycloxygenase-2 (COX-2), Inhibitor of Kappaβ Kinase (IKK) and TANK binding kinase-1 (TBK-1) of Toll Like Receptor 4 (TLR4) pathway involved in inflammation using computational tools. Multiple analogues showed better binding affinity than the approved drugs for the respective targets. Upon continuous computational exploration 6-Gingerol, Yakuchinone A and Yakuchinone B were identified as the best inhibitors of COX-2, IKK and TBK-1 respectively. Then their drug like potentialities were analyzed in different experiments where they also performed sound and similar. Hopefully, this study will uphold the efforts of researchers to identify anti-inflammatory drugs from natural sources.

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