Exploration of interaction interface of TRKß/BDNF through fingerprint analysis to disinter potential agonists.

Tyrosine Kinase beta (TRKß), is a type I membrane receptor which plays a major role in various signalling pathways. TRKß was found to be upregulated in various cancers and contrastingly downregulated in various neurodegenerative disorders. Hitherto, contemporary drug research is oriented towards discovery of TRKß inhibitors, thus neglecting the development of TRKß agonists. This research is aimed at identifying FDA approved drugs exhibiting repurposable potential as TRKß agonists by mapping them with fingerprints of the BDNF/TRKß interaction interface. Initially, crucial interacting residues were retrieved and a receptor grid was generated around it. TRKß agonists were retrieved from literature search and a drug library was created for each agonist based on its structural and side effect similarities. Subsequently, molecular docking and dynamics were performed for each library to identify the drugs possessing affinity towards the binding pocket of TRKß. The study revealed molecular interactions of Perospirone, Droperidol, Urapidil, and Clobenzorex with the crucial amino acids lining the active binding pocket of TRKß. Subsequent network pharmacological analysis of the above drugs revealed their interactions with key proteins involved in neurotransmitter signalling pathways. Clobenzorex displayed high stability in dynamics simulation and therefore this drug is recommended for further experimental evaluations to attain better mechanistic insights and predict its implications in correcting neuropathological aberrations. This study's focus on the interaction interface between TRKß and BDNF, combined with the utilization of fingerprint analysis for drug repurposing, contributes to our understanding of neurotrophic signalling and holds potential for identifying new therapeutic options for neurological disorders.

Articulating target-mining techniques to disinter Alzheimer's specific targets for drug repurposing.

BACKGROUND AND OBJECTIVES: Alzheimer's Disease (AD), an extremely progressive neurodegenerative disorder is an amalgamation of numerous intricate pathological networks. This century old disease is still an unmet medical condition owing to the modest efficacy of existing therapeutic agents in antagonizing the multi-targeted pathological pathways underlying AD. Given the paucity in AD specific drugs, fabricating comprehensive research strategies to envision disease specific targets to channelize and expedite drug discovery are mandated. However, the dwindling approval rates and stringent regulatory constraints concerning the approval of a new chemical entity is daunting the pharmaceutical industries from effectuating de novo research. To bridge the existing gaps in AD drug research, a promising contemporary way out could be drug repurposing. This drug repurposing investigation is intended to envisage AD specific targets and create drug libraries pertinent to the shortlisted targets via a series of avant-garde bioinformatics and computational strategies. METHODS: Transcriptomic analysis of three AD specific datasets viz., GSE122063, GSE15222 and GSE5281 revealed significant Differentially Expressed Genes (DEGs) and subsequent Protein-Protein Interactions (PPI) network analysis captured crucial AD targets. Later, homology model was constructed through I-TASSER for a shortlisted target protein which lacked X-ray crystallographic structure and the built protein model was validated by molecular dynamic simulations. Further, drug library was created for the shortlisted target based on structural and side effect similarity with respective standard drugs. Finally, molecular docking, binding energy calculations and molecular dynamics studies were carried out to unravel the interactions exhibited by drugs from the created library with amino acids in active binding pocket of RGS4. RESULTS: SST and RGS4 were shortlisted as potentially significant AD specific targets, however, the less explored target RGS4 was considered for further sequential analysis. Homology model constructed for RGS4 displayed best quality when validated through Ramachandran plot and ERRAT plot. Subsequent docking and molecular dynamics studies showcased substantial affinity demonstrated by three drugs viz., Ziprasidone, Melfoquine and Metaxalone from the created drug libraries, towards RGS4. CONCLUSION: This virtual analysis forecasted the repurposable potential of Ziprasidone, Melfoquine and Metaxalone against AD based on their affinity towards RGS4, a key AD-specific target.

Revelation of Pivotal Genes Pertinent to Alzheimer's Pathogenesis: A Methodical Evaluation of 32 GEO Datasets.

Alzheimer's disease (AD), a dreadful neurodegenerative disorder that affects cognitive and behavioral function in geriatric populations, is characterized by the presence of amyloid deposits and neurofibrillary tangles in brain regions. The International D World Alzheimer Report 2018 noted a global prevalence of 50 million AD cases and forecasted a threefold rise to 139 million by 2050. Although there exist numerous genetic association studies pertinent to AD in different ethnicities, critical genetic factors and signaling pathways underlying its pathogenesis remain ambiguous. This study was aimed to analyze the genetic data retrieved from 32 Gene Expression Omnibus datasets belonging to diverse ethnic cohorts in order to identify overlapping differentially expressed genes (DEGs). Stringent selection criteria were framed to shortlist appropriate datasets based on false discovery rate (FDR) p-value and log FC, and relevant details of upregulated and downregulated DEGs were retrieved. Among the 32 datasets, only six satisfied the selection criteria. The GEO2R tool was employed to retrieve significant DEGs. Nine common DEGs, i.e., SLC5A3, BDNF, SST, SERPINA3, RTN3, RGS4, NPTX, ENC1 and CRYM were found in more than 60% of the selected datasets. These DEGs were later subjected to protein-protein interaction analysis with 18 AD-specific literature-derived genes. Among the nine common DEGs, BDNF, SST, SERPINA3, RTN3 and RGS4 exhibited significant interactions with crucial proteins including BACE1, GRIN2B, APP, APOE, COMT, PSEN1, INS, NEP and MAPT. Functional enrichment analysis revealed involvement of these genes in trans-synaptic signaling, chemical transmission, PI3K pathway signaling, receptor-ligand activity and G protein signaling. These processes are interlinked with AD pathways.

Adverse Drug Reaction Monitoring in a Tertiary Care Psychiatry Setting: A Comparative Study between Inpatients and Outpatients.

BACKGROUND: Psychotropic medications are the mainstay of treatment in psychiatric disorders and are associated with ADRs which affect the compliance and treatment course. Previous studies have looked at the frequency, profile of ADRs and their management aspects. However, the systematic comparison between IP and OP was lacking even though there is a prescription pattern difference. Hence this study was aimed to compare the proportion, pattern, severity and resolution of ADRs once detected. METHODS: This is a hospital based, prospective follow up study done in the psychiatry ward and outpatient setting for a period of 6 months. A total of 491 patients (200 IP, 291 OP) who received psychotropics were monitored in the study. UKU side effect rating scale was used to detect ADRs, WHO - UMC scale for causality, Modified Hartwig and Siegel Scale to assess severity of ADR and CDSCO suspected ADR form for reporting it. RESULTS: Out of 491 patients who were recruited for the study, 83 patients developed ADRs (34 IP, 49 OP, P = 0.963). The mean number of ADRs per patient was found to be higher in IP (IP-2.17±1.14, OP-1.65±1.12, P-0.01). Severe ADRs were observed to be higher IP (IP-67.64%, OP-38.7%, P-0.014) which was statistically significant. There is no statistically significant difference in distribution of ADRs across all age groups (P-0.475). CONCLUSION: The study results emphasises the need for active pharmacovigilance so that ADRs are detected and managed at the earliest, hence reducing the morbidity and improving compliance. There is also need for systematic long term, multicentric study to further examine and correlatethe observations of our study.