View the peer-reviewed version (peerj.com/articles/476), which is the preferred citable publication unless you specifically need to cite this preprint. Jamal S, Scaria V, Open Source Drug Discovery Consortium. 2014. Datamining of potential antitubercular activities from molecular ingredients of traditional Chinese medicines. PeerJ 2:e476 https://doi.org/10.7717/peerj.476 Data-mining of potential antitubercular activities from molecular ingredients of Traditional Chinese MedicinesBackground Traditional Chinese medicine encompasses a well established alternate system of medicine based on a broad range of herbal formulations and is practiced extensively in the region for the treatment of a wide variety of diseases. In recent years, several reports describe in depth studies of the molecular ingredients of Traditional Chinese Medicines on the biological activities including anti-bacterial activities. The availability of a well-curated dataset of molecular ingredients of Traditional Chinese Medicines and accurate in-silico cheminformatics models for data mining for antitubercular agents and computational filters to prioritize molecules has prompted us to search for potential hits from these datasets. ResultsWe used a consensus approach to predict molecules with potential antitubercular activities from a large dataset of molecular ingredients of Traditional Chinese Medicines available in the public domain. We further prioritized 160 molecules based on five computational filters (SMARTSfilter) so as to avoid potentially undesirable molecules. We further examined the molecules for permeability across Mycobacterial cell wall and for potential activities against non-replicating and drug tolerant Mycobacteria. Additional in-depth literature surveys for the reported antitubercular activities of the molecular ingredients and their sources were considered for drawing support to prioritization. Conclusions Our analysis suggests that datasets of molecular ingredients of TraditionalChinese Medicines offer a new opportunity to mine for potential biological activities. In this report, we suggest a proof-of-concept methodology to prioritize molecules for further experimental assays using a variety of computational tools. We also additionally suggest that a subset of prioritized molecules could be used for evaluation for tuberculosis due to their additional effect against non-replicating tuberculosis as well as the additional hepatoprotection offered by the source of these ingredients. PrePrints Background Traditional Chinese medicine encompasses a well established alternate system of medicine based on a broad range of herbal formulations and is practiced extensively in the region for the treatment of a wide variety of diseases. In recent years, several reports describe in depth studies of the molecular ingredients of Traditional Chinese Medicines on the biological activities including anti-bacterial activities. The availability of a well-curated dataset of molecular ingredients of Traditional Chinese Medicines and accurate in-silico...
We report a case of SARS-CoV-2 Omicron variant co-infection with influenza A H3N2 detected from Kerala, India. The patient, a 10-year-old girl, had symptoms of low-grade fever, cough, and cold. As part of the ongoing surveillance, a throat swab was taken and sent for testing, and the influenza A virus isolated from the patient was identified as subtype H3N2. Whole-genome sequencing and analysis of the viral isolates suggested that the SARS-CoV-2 isolate belonged to BA.4.1 sublineage of Omicron while the influenza A isolate belonged to the 2a.3 clade of H3N2 and clustered with other H3N2 genomes from Maldives, India, Bangladesh, and the United Arab Emirates. The report highlights the importance of genomic surveillance of SARS-CoV-2 co-infections with other respiratory illnesses for understanding the prevalence of co-infections and their rapid detection and prevention.
Genetic variants in human platelet antigens (HPAs) considered allo‐ or auto antigens are associated with various disorders, including neonatal alloimmune thrombocytopenia, platelet transfusion refractoriness and post‐transfusion purpura. Although global differences in genotype frequencies were observed, the distributions of HPA variants in the Indian population are largely unknown. This study aims to explore the landscape of HPA variants in India to provide a basis for risk assessment and management of related complications. Population‐specific frequencies of genetic variants associated with the 35 classes of HPAs (HPA‐1 to HPA‐35) were estimated by systematically analysing genomic variations of 1029 healthy Indian individuals as well as from global population genome datasets. Allele frequencies of the most clinically relevant HPA systems in the Indian population were found as follows, HPA‐1a – 0.884, HPA‐1b – 0.117, HPA‐2a – 0.941, HPA‐2b – 0.059, HPA‐3a – 0.653, HPA‐3b – 0.347, HPA‐4a – 0.999, HPA‐4b – 0.0010, HPA‐5a – 0.923, HPA‐5b – 0.077, HPA‐6a – 0.998, HPA‐6b – 0.002, HPA‐15a – 0.582 and HPA‐15b – 0.418. This study provides the first comprehensive analysis of HPA allele and genotype frequencies using large scale representative whole genome sequencing data of the Indian population.
Human neutrophil antigens possess significant clinical implications especially in the fields of transfusion and transplantation medicine. Efforts to estimate the prevalence of genetic variations underpinning the antigenic expression are emerging. However, there lacks a precise capture of the global frequency profiles. Our article emphasizes the potential utility of maintaining an organized online repository of evidence on neutrophil antigen‐associated genetic variants from published literature and reports. This, in our opinion, is an emerging area and would significantly benefit from the awareness and understanding of population‐level diversities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.