Targeting key players in Alzheimer's disease: bioactive compounds from Moringa oleifera, Desmodium gangeticum, and Centella asiatica as potential therapeutics.

Alzheimer's Disease (AD) is one of the critical reasons for dementia around the world, with a huge number of cases being reported every year. The breakdown of Amyloid Precursor Protein (APP) plays a crucial role in AD development. The Beta-site APP Cleaving Enzyme 1 (BACE1) is a highly significant proteolytic enzyme found to be critically involved in the APP breakdown process and generates beta-amyloid plaques in the extracellular neuronal membrane. In this study, we have used natural compounds with cognitive and neuroprotective activities from three plants, Centella asiatica, Moringa oleifera, and Desmodium gangeticum to inhibit the activity of BACE1. We have identified nine compounds out of 73 compounds filtered out from the three plants showing high affinity with the catalytic dyad region of BACE1 through molecular docking studies. Interestingly, the 200 ns molecular dynamics simulation study further confirmed the stability of the complexes formed between 9 compounds and the BACE1 protein. Furthermore, the free energy calculations also revealed these complexes possess favorable energies. Astilbin, Delphinidin 3-glucoside, and kaempferol 7-O-glucoside showed good binding affinity and structural stability when compared to other compounds and the control CNP520. Following a preliminary screening, the Astilbin compound was chosen based on the grounds of binding affinity, ADMET Properties, Hbond formation, Molecular Dynamic simulation, and MM-PBSA studies. A subsequent 1microsecond molecular dynamics simulation was conducted for the Astilbin complex. Through microsecond simulation, it was found that Astilbin alters BACE1's behavior and induces conformational rearrangements. Thus, this study opens a gateway to inhibit the activity of BACE1 protein through Astilbin thereby disclosing the possibility of managing Alzheimer's Disease.Communicated by Ramaswamy H. Sarma.

Molecular crosstalk between COVID-19 and Alzheimer's disease using microarray and RNA-seq datasets: A system biology approach.

Objective: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The clinical and epidemiological analysis reported the association between SARS-CoV-2 and neurological diseases. Among neurological diseases, Alzheimer's disease (AD) has developed as a crucial comorbidity of SARS-CoV-2. This study aimed to understand the common transcriptional signatures between SARS-CoV-2 and AD. Materials and methods: System biology approaches were used to compare the datasets of AD and COVID-19 to identify the genetic association. For this, we have integrated three human whole transcriptomic datasets for COVID-19 and five microarray datasets for AD. We have identified differentially expressed genes for all the datasets and constructed a protein-protein interaction (PPI) network. Hub genes were identified from the PPI network, and hub genes-associated regulatory molecules (transcription factors and miRNAs) were identified for further validation. Results: A total of 9,500 differentially expressed genes (DEGs) were identified for AD and 7,000 DEGs for COVID-19. Gene ontology analysis resulted in 37 molecular functions, 79 cellular components, and 129 biological processes were found to be commonly enriched in AD and COVID-19. We identified 26 hub genes which includes AKT1, ALB, BDNF, CD4, CDH1, DLG4, EGF, EGFR, FN1, GAPDH, INS, ITGB1, ACTB, SRC, TP53, CDC42, RUNX2, HSPA8, PSMD2, GFAP, VAMP2, MAPK8, CAV1, GNB1, RBX1, and ITGA2B. Specific miRNA targets associated with Alzheimer's disease and COVID-19 were identified through miRNA target prediction. In addition, we found hub genes-transcription factor and hub genes-drugs interaction. We also performed pathway analysis for the hub genes and found that several cell signaling pathways are enriched, such as PI3K-AKT, Neurotrophin, Rap1, Ras, and JAK-STAT. Conclusion: Our results suggest that the identified hub genes could be diagnostic biomarkers and potential therapeutic drug targets for COVID-19 patients with AD comorbidity.

Cross-regulatory network in Pseudomonas aeruginosa biofilm genes and TiO2 anatase induced molecular perturbations in key proteins unraveled by a systems biology approach.

A systems biology approach was used to study all the biofilm related genes of P. aeruginosa PAO1, and the interaction of titanium dioxide (TiO2) anatase with biofilm related proteins. Among the 71 genes, the interactions of all the nodal pairs were extracted by STRING 10.5 database. The inter-relationship among these genes was predicted by constructing complete PPI network and visualized in Cytoscape v 3.4.0. Total number of nodes of the network was found to be 335 and edges were 795. The network was further investigated for its clusters and the best cluster was further analyzed for the hub proteins which significantly contribute in cross-regulation of the biofilm related process. The hub proteins were identified based on four topological parameters of degree, closeness, betweeness and radiality. Four major hub proteins of P. aeruginosa PAO1 were identified to be algD, gacS, rpoS and rpoN which were common in all the hubs. Further, we have also elucidated the probable mechanism of TiO2 interaction with P. aeruginosa PAO1 at molecular level. Using STITCH server, the major target gene of TiO2 was identified as katA which also appeared commonly in our main dataset and this gene has been focused for the further study because of its unique common appearance in gene-gene network as well as gene-anatase network. The direct interacting partners of katA were found to be dnaK, hfq, rpoS and rpoA. Based on these findings and available gene regulatory information, probable TiO2 interacting cascade has been represented. This in silico study of P. aeruginosa PAO1 biofilm genes and the interaction of protein products with TiO2 might be significant to understand the perspective pathogenic resistance as well as the toxicity research pertaining to nanoparticles.

RAACFDb: Rheumatoid arthritis ayurvedic classical formulations database.

ETHNOPHARMACOLOGICAL RELEVANCE: In the past years, the treatment of rheumatoid arthritis (RA) has undergone remarkable changes in all therapeutic modes. The present newfangled care in clinical research is to determine and to pick a new track for better treatment options for RA. Recent ethnopharmacological investigations revealed that traditional herbal remedies are the most preferred modality of complementary and alternative medicine (CAM). However, several ayurvedic modes of treatments and formulations for RA are not much studied and documented from Indian traditional system of medicine. Therefore, this directed us to develop an integrated database, RAACFDb (acronym: Rheumatoid Arthritis Ayurvedic Classical Formulations Database) by consolidating data from the repository of Vedic Samhita - The Ayurveda to retrieve the available formulations information easily. MATERIALS AND METHODS: Literature data was gathered using several search engines and from ayurvedic practitioners for loading information in the database. In order to represent the collected information about classical ayurvedic formulations, an integrated database is constructed and implemented on a MySQL and PHP back-end. RESULTS: The database is supported by describing all the ayurvedic classical formulations for the treatment rheumatoid arthritis. It includes composition, usage, plant parts used, active ingredients present in the composition and their structures. CONCLUSION: The prime objective is to locate ayurvedic formulations proven to be quite successful and highly effective among the patients with reduced side effects. The database (freely available at www.beta.vit.ac.in/raacfdb/index.html) hopefully enables easy access for clinical researchers and students to discover novel leads with reduced side effects.

Analysis and modeling of heat-labile enterotoxins of Escherichia coli suggests a novel space with insights into receptor preference.

Features of heat-labile enterotoxins of Escherichia coli which make them fit to use as novel receptors for antidiarrheals are not completely explored. Data-set of 14 different serovars of enterotoxigenic Escherichia coli producing heat-labile toxins were taken from NCBI Genbank database and used in the study. Sequence analysis showed mutations in different subunits and also at their interface residues. As these toxins lack crystallography structures, homology modeling using Modeller 9.11 led to the structural approximation for the E. coli producing heat-labile toxins. Interaction of modeled toxin subunits with proanthocyanidin, an antidiarrheal showed several strong hydrogen bonding interactions at the cost of minimized energy. The hits were subsequently characterized by molecular dynamics simulation studies to monitor their binding stabilities. This study looks into novel space where the ligand can choose the receptor preference not as a whole but as an individual subunit. Mutation at interface residues and interaction among subunits along with the binding of ligand to individual subunits would help to design a non-toxic labile toxin and also to improve the therapeutics.