Diabetic wound healing of aloe vera major phytoconstituents through TGF-ß1 suppression via in-silico docking, molecular dynamic simulation and pharmacokinetic studies.

To restore the integrity of the skin and subcutaneous tissue, the wound healing process involves a complex series of well-orchestrated biochemical and cellular events. Due to the existence of various active components, accessibility and few side effects, some plant extracts and their phytoconstituents are recognised as viable options for wound healing agents. To find possible inhibitors of diabetic wound healing, four main constituents of aloe vera were identified from the literature. TGF-ß1 and the compounds were studied using molecular docking to see how they interacted with the active site of target protein (PDB ID: 6B8Y). The pharmacokinetics investigation of the aloe emodin with the highest dock score complied with all the Lipinski's rule of five and pharmacokinetics criteria. Conformational change in the docked complex of Aloe emodin was investigated with the Amber simulation software, via a molecular dynamic (MD) simulation. The MD simulations of aloe emodin bound to TGF-ß1 showed the significant structural rotations and twists occurring from 0 to 200 ns. The estimate of the aloe emodin-TGF-ß1 complex's binding free energy has also been done using MM-PBSA/GBSA techniques. Additionally, aloe emodin has a wide range of enzymatic activities since their probability active (Pa) values is >0.700. 'Aloe emodin', an active extract of aloe vera, has been identified as the key chemical in the current investigation that can inhibit diabetic wound healing. Both in-vitro and in-vivo experiments will be used in a wet lab to confirm the current computational findings.Communicated by Ramaswamy H. Sarma.

Usnic acid as potential inhibitors of BCL2 and P13K protein through network pharmacology-based analysis, molecular docking and molecular dynamic simulation.

Usnic acid (UA) lately piqued the interest of researchers for its extraordinary biological characteristics, including anticancer activity. Here, the mechanism was clarified through network pharmacology,molecular docking and molecular dynamic simulation. Sixteen proteins were selected through network pharmacology study as they are probable to interact with UA. Out of these proteins, 13 were filtered from PPI network analysis based on their significance of interactions (p < 0.05). KEGG pathway analysis has also aided us in determining the three most significant protein targets for UA, which are BCL2, PI3KCA and PI3KCG. Therefore molecular docking and molecular dynamic (MD) simulations throughout 100 ns were performed for usnic acid onto the three proteins mentioned. However, UA's docking score in all proteins is lower than their co-crystalised ligand, especially for BCL2 (-36.5158 kcal/mol) and PI3KCA (-44.5995 kcal/mol) proteins. The only exception is PI3KCG which has comparable results with the co-crystallised ligand with (-41.9351 kcal/mol). Furthermore, MD simulation has also revealed that usnic acid does not stay fit in the protein throughout the simulation trajectory for PI3KCA protein evident from RMSF and RMSD plots. Nevertheless, it still poses good ability in inhibiting BCL2 and PI3KCG protein in MD simulation. In the end, usnic acid has exhibited good potential in the inhibition of PI3KCG proteins, rather than the other proteins mentioned. Thus further study on structural modification of usnic acid could enhance the ability of usnic acid in the inhibition of PI3KCG as anti-colorectal and anti-small cell lung cancer drug candidate.Communicated by Ramaswamy H. Sarma.

COVID-19 outbreak in Malaysia: Decoding D614G mutation of SARS-CoV-2 virus isolated from an asymptomatic case in Pahang.

SARS-CoV-2 is a very transmissible and pathogenic coronavirus which detected in Malaysia in January 2020. Nevertheless, the sample from Malaysia is still under-sequenced. Hence lacking clarity of the circulating strain in Malaysia leads to a deadlock in understanding the virus infectivity. This study aimed to investigate the genome identity of circulating COVID-19 strains in Pahang and understand disease epidemiology during the pandemic. This study leveraged high-throughput sequencing analysis for the whole genome sequencing and implemented bioinformatic technique for the analysis. Here we reported that the virus with D614G mutation in Spike protein circulates in a few Malaysia states before the Sivagangga cluster announced in Kedah in July 2020. This mutated virus includes our virus sample isolated in April 2020 from an asymptomatic patient in Pahang. Based on the phylogenetic analysis, we discovered the origin of our sample Pahang/IIUM91 was not related to Sivagangga cluster. Here, we have generated 3D structure model of Pahang/IIUM91 Spike protein. D614G mutation in Pahang/IIUM91 Spike protein increases viral stability and flexibility, hence render higher infectivity. Collectively, our results suggest for the establishment of a complete SARS-CoV-2 genome database in Malaysia. Hence, more research should be established to learn the behaviour of this virus.

Near-Complete Genome Sequences of Nine SARS-CoV-2 Strains Harboring the D614G Mutation in Malaysia.

Here, we report the nearly complete genome sequences of nine severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with the D614G mutation. These viruses were detected from various infected individuals with different levels of severity from Pahang, Malaysia. In addition, this study described the presence of lineage B.1.351 as a type of variant of concern (VOC) and lineages B.1.466.2 and B.1.524 as local variants.

Type 1 diabetes linked PTPN22 gene polymorphism is associated with the frequency of circulating regulatory T cells.

Dysfunction of FOXP3-positive regulatory T cells (Tregs) likely plays a major role in the pathogenesis of multiple autoimmune diseases including type 1 diabetes (T1D). Whether genetic polymorphisms associated with the risk of autoimmune diseases affect Treg frequency or function is currently unclear. Here, we analysed the effect of T1D-associated major HLA class II haplotypes and seven single nucleotide polymorphisms in six non-HLA genes [INS (rs689), PTPN22 (rs2476601), IL2RA (rs12722495 and rs2104286), PTPN2 (rs45450798), CTLA4 (rs3087243), and ERBB3 (rs2292239)] on peripheral blood Treg frequencies. These were determined by flow cytometry in 65 subjects who had progressed to T1D, 86 islet autoantibody-positive at-risk subjects, and 215 islet autoantibody-negative healthy controls. The PTPN22 rs2476601 risk allele A was associated with an increase in total (p = 6 × 10-6 ) and naïve (p = 4 × 10-5 ) CD4+CD25+CD127lowFOXP3+ Treg frequencies. These findings were validated in a separate cohort comprising ten trios of healthy islet autoantibody-negative children carrying each of the three PTPN22 rs2476601 genotypes AA, AG, and GG (p = 0.005 for total and p = 0.03 for naïve Tregs, respectively). In conclusion, our analysis implicates the autoimmune PTPN22 rs2476601 risk allele A in controlling the frequency of Tregs in human peripheral blood.