Muskmelon (Cucumis melo L.) cultivar 'Birdie' , was evaluated for its response to the tumorigenic Agrobacterium tumefaciens and the oncogenic A. rhizogenes strains. Stem and petiole of three week-old in vitro-grown muskmelon plants were inoculated with five strains of A. tumefaciens and A. rhizogenes each and observed phenotypic expressions i.e. induction of crown galls and hairy roots. This phenotypic expression was efficaciously increased when virulence gene activity of different strains of two Agrobacterium species was enhanced. Intensive studies on enhancement of virulence gene activity of Agrobacterium found to be correlated to the appropriate light intensity (39.3 µmol m -2 s -1) with a specific concentration of monocyclic phenolic compound, acetosyringone (20 µM). The gene activity was also influenced by several other physical factors e.g. plant tissue type, Agrobacterium species and their strains, and plant tissue-Agrobacterium interaction. Among the different A. tumefaciens strains, LBA4404 showed the best virulence gene activity in both stem and petiole through the formation of higher rate of crown galls. On the other hand, strain 15834 of A. rhizogenes showed better gene activity in stem and 8196 in petiole through the formation of higher rate of hairy roots as well as higher average number of hairy roots. Among the two different types of explants, petiole was more susceptible to both Agrobacterium species. Thus it was concluded that future muskmelon transformation study can efficiently be carried out with LBA4404, 15834 and 8196 strains using petiole explants by adding 20 µM of acetosyringone in the medium.

Genetic polymorphisms in DNA damage repair and tumor suppressor genes have been associated with increasing the risk of several types of cancer. Analyses of putative functional single nucleotide polymorphisms (SNP) in such genes can greatly improve human health by guiding choice of therapeutics. In this study, we selected nine genes responsible for various cancer types for gene enrichment analysis and found that BRCA1, ATM, and TP53 were more enriched in connectivity. Therefore, we used different computational algorithms to classify the nonsynonymous SNPs which are deleterious to the structure and/or function of these three proteins. Our study demonstrated that V1687G and V1736G variants of BRCA1, I2865T and V2906A variants of ATM, V216G and L194H variants of TP53 are major mutations with pathogenic impact and are likely to have a greater impact on destabilizing the proteins. To stabilize the high-risk SNPs, we performed mutation site-specific molecular docking analysis and validated using molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) studies. Additionally, SNPs of untranslated regions of these genes affecting miRNA binding were characterized. Hence, this study will assist in developing precision medicines for cancer types related to these polymorphisms.

The emerging variants of SARS Coronavirus-2 (SARS-CoV-2) has been continuously spreading all over the world and raised global health concerns. The B.1.1.7 (United Kingdom), P.1 (Brazil), B.1.351 (South Africa) and B.1.617 (India) variants resulted due to multiple mutations in the spike glycoprotein (SGp), are resistant to neutralizing antibodies and enable increased transmission. Hence, new drugs might be of great importance against the novel variants of SARS-CoV-2. The SGp and main protease (Mpro) of SARS-CoV-2 are important targets to design and develop antiviral compounds for new drug discovery. In this study, we selected seventeen phytochemicals and later performed molecular docking to determine the binding interactions of the compounds with the two receptors and calculated several drug likeliness properties for each compound. Luteolin, myricetin and quercetin demonstrated higher affinity for both the proteins and interacted efficiently. To get better compounds, we designed three analogues from these compounds and showed the greater druggable properties than the parent compounds. Furthermore, we found that the analogues bind to the residues of both proteins including the recent novel variants of SARS-CoV-2. The binding study was further verified by molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) approaches by assessing the stability of the complexes. MD simulations revealed that Arg457 of SGp and Met49 of Mpro are the most important residues that interacted with the designed inhibitors. Our analysis may give some breakthroughs to develop new therapeutics to treat the proliferation of SARS-CoV-2 in vitro and in vivo.

Positive strides have been achieved in developing vaccines to combat the coronavirus-2019 infection (COVID-19) pandemic. Still, the outline of variations, particularly the most current delta divergent, has posed significant health encounters for people. Therefore, developing strong treatment strategies, such as an anti-COVID-19 medicine plan, may help deal with the pandemic more effectively. During the COVID-19 pandemic, some drug design techniques were effectively used to develop and substantiate relevant critical medications. Extensive research, both experimental and computational, has been dedicated to comprehending and characterizing the devastating COVID-19 disease. The urgency of the situation has led to the publication of over 130,000 COVID-19-related research papers in peer-reviewed journals and preprint servers. A significant focus of these efforts has been the identification of novel drug candidates and the repurposing of existing drugs to combat the virus. Many projects have utilized computational or computer-aided approaches to facilitate their studies. In this overview, we will explore the key computational methods and their applications in the discovery of small-molecule therapeutics for COVID-19, as reported in the research literature. We believe that the true effectiveness of computational tools lies in their ability to provide actionable and experimentally testable hypotheses, which in turn facilitate the discovery of new drugs and combinations thereof. Additionally, we recognize that open science and the rapid sharing of research findings are vital in expediting the development of much-needed therapeutics for COVID-19.