ABSTRACT
Acute myeloid leukemia (AML) is one of the leading leukemic malignancies in adults. The heterogeneity of the disease makes the diagnosis and treatment extremely difficult. With the advent of next-generation sequencing (NGS) technologies, exploration at the molecular level for the identification of biomarkers and drug targets has been the focus for the researchers to come up with novel therapies for better prognosis and survival outcomes of AML patients. However, the huge amount of data from NGS platforms requires a comprehensive AML platform to streamline literature mining efforts and save time. To facilitate this, we developed AMLdb, an interactive multi-omics platform that allows users to query, visualize, retrieve, and analyse AML related multi-omics data. AMLdb contains 86 datasets for gene expression profiles, 15 datasets for methylation profiles, CRISPR-Cas9 knockout screens of 26 AML cell lines, sensitivity of 26 AML cell lines to 288 drugs, mutations in 41 unique genes in 23 AML cell lines, and information on 41 experimentally validated biomarkers. In this study, we have reported five genes, i.e. CBFB, ENO1, IMPDH2, SEPHS2, and MYH9 identified via our analysis using AMLdb. ENO1 is uniquely identified gene which requires further investigation as a novel potential target while other reported genes have been previously confirmed as targets through experimental studies. Top of form we believe that these findings utilizing AMLdb can make it an invaluable resource to accelerate the development of effective therapies for AML and assisting the research community in advancing their understanding of AML pathogenesis. AMLdb is freely available at https://project.iith.ac.in/cgntlab/amldb.
ABSTRACT
The process of aging is an intrinsic and inevitable aspect of life that impacts every living organism. As biotechnological advancements continue to shape our understanding of medicine, peptide therapeutics have emerged as a promising strategy for anti-aging interventions. This is primarily due to their favorable attributes, such as low immunogenicity and cost-effective production. Peptide-based treatments have garnered widespread acceptance and interest in aging research, particularly in the context of age-related therapies. To effectively develop anti-aging treatments, a comprehensive understanding of the physicochemical characteristics of anti-aging peptides is essential. Factors such as amino acid composition, instability index, hydrophobic areas and other relevant properties significantly determine their efficacy as potential therapeutic agents. Consequently, the creation of 'AagingBase', a comprehensive database for anti-aging peptides, aims to facilitate research on aging by leveraging the potential of peptide therapies. AagingBase houses experimentally validated 282 anti-aging peptides collected from 54 research articles and 236 patents. Employing state-of-the-art computational techniques, the acquired sequences have undergone rigorous physicochemical calculations. Furthermore, AagingBase presents users with various informative analyses highlighting atomic compositions, secondary structure fractions, tertiary structure, amino acid compositions and frequencies. The database also offers advanced search and filtering options and similarity search, thereby aiding researchers in understanding their biological functions. Hence, the database enables efficient identification and prioritization of potential peptide candidates in geriatric medicine and holds immense potential for advancing geriatric medicine research and innovations. AagingBase can be accessed without any restriction. Database URL: https://project.iith.ac.in/cgntlab/aagingbase/.
