Study elastic properties of the leucine and isoleuicine from first principles calculations

I studied the elastic properties of crystalline L- and DL-forms of leucine and isoleucine within the framework of density functional theory with van der Waals interactions. The energy gaps of the considered crystals are 7.48-7.60 eV. Chiral molecules have the same chemical composition. Therefore, the study of crystalline amino acids provides a better understanding of how the structure of molecules affects mechanical properties of molecular crystals. Complete set of elastic constants for L-leucine, L-isoleucine, DL-leucine and DL-isoleucine were calculated. Linear compressibility of crystals has high anisotropy. The crystalline L- and DL-forms of leucine and isoleucine have different mechanical properties. Linear compressibility has a negative value for DL-isoleucine. My calculations predict that L-leucine and L-isoleucine are ductile compounds, while DL-leucine and DL-isoleucine are brittle compounds.

Computational methods directed towards drug repurposing for COVID-19: advantages and limitations

Novel coronavirus disease 2019 (COVID-19) has significantly altered the socio-economic status of countries. Although vaccines are now available against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a causative agent for COVID-19, it continues to transmit and newer variants of concern have been consistently emerging world-wide. Computational strategies involving drug repurposing offer a viable opportunity to choose a medication from a rundown of affirmed drugs against distinct diseases including COVID-19. While pandemics impede the healthcare systems, drug repurposing or repositioning represents a hopeful approach in which existing drugs can be remodeled and employed to treat newer diseases. In this review, we summarize the diverse computational approaches attempted for developing drugs through drug repurposing or repositioning against COVID-19 and discuss their advantages and limitations. To this end, we have outlined studies that utilized computational techniques such as molecular docking, molecular dynamic simulation, disease-disease association, drug-drug interaction, integrated biological network, artificial intelligence, machine learning and network medicine to accelerate creation of smart and safe drugs against COVID-19.

Trends and Applications of Omics Technologies to Functional Characterisation of Enzymes and Protein Metabolites Produced by Fungi

Identifying and adopting industrial applications for proteins and enzymes derived from fungi strains have been at the focal point of several studies in recent times. To facilitate such studies, it is necessary that advancements and innovation in mycological and molecular characterisation are concomitant. This review aims to provide a detailed overview of the necessary steps employed in both qualitative and quantitative research using the omics technologies that are pertinent to fungi characterisation. This stems from the understanding that data provided from the functional characterisation of fungi and their metabolites is important towards the techno-economic feasibility of large-scale production of biological products. The review further describes how the functional gaps left by genomics, internal transcribe spacer (ITS) regions are addressed by transcriptomics and the various techniques and platforms utilised, including quantitive reverse transcription polymerase chain reaction (RT-qPCR), hybridisation techniques, and RNA-seq, and the insights such data provide on the effect of environmental changes on fungal enzyme production from an expressional standpoint. The review also offers information on the many available bioinformatics tools of analysis necessary for the analysis of the overwhelming data synonymous with the omics approach to fungal characterisation.