Small-molecule target identification is an important and challenging task for chemical biology and drug discovery. Structure-based virtual target identification has been widely used, which infers and prioritizes potential protein targets for the molecule of interest (MOI) principally via a scoring function. However, current "universal" scoring functions may not always accurately identify targets to which the MOI binds from the retrieved target database, in part due to a lack of consideration of the important binding features for an individual target. Here, we present IFPTarget, a customized virtual target identification method, which uses an interaction fingerprinting (IFP) method for target-specific interaction analyses and a comprehensive index (Cvalue) for target ranking. Evaluation results indicate that the IFP method enables substantially improved binding pose prediction, and Cvalue has an excellent performance in target ranking for the test set. When applied to screen against our established target library that contains 11,863 protein structures covering 2842 unique targets, IFPTarget could retrieve known targets within the top-ranked list and identified new potential targets for chemically diverse drugs. IFPTarget prediction led to the identification of the metallo-β-lactamase VIM-2 as a target for quercetin as validated by enzymatic inhibition assays. This study provides a new in silico target identification tool and will aid future efforts to develop new target-customized methods for target identification.
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Biochem Biophys Res Commun
January 2025
Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia. Electronic address:
Objective And Significance: Transforming growth factor-beta (TGF-β) plays a pivotal role in breast development by modulating tissue composition during the developmental phase. The TGFβ type II receptor (TGFβ RII) is implicated in breast cancer and represents a valuable therapeutic target. Due to the off-target side effects of many existing TGFβI/TGFβ RII inhibitors, a more targeted approach to drug discovery is necessary.
View Article and Find Full Text PDFJMIR Pediatr Parent
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School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin 4, Ireland.
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View Article and Find Full Text PDFPLoS Comput Biol
January 2025
School of Biomedical Engineering, Anhui Medical University, Hefei, China.
Synonymous mutations, once considered neutral, are now understood to have significant implications for a variety of diseases, particularly cancer. It is indispensable to identify these driver synonymous mutations in human cancers, yet current methods are constrained by data limitations. In this study, we initially investigate the impact of sequence-based features, including DNA shape, physicochemical properties and one-hot encoding of nucleotides, and deep learning-derived features from pre-trained chemical molecule language models based on BERT.
View Article and Find Full Text PDFCRISPR J
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OceanOmics, The Minderoo Foundation, Perth, Australia.
Characterizing biodiversity using environmental DNA (eDNA) represents a paradigm shift in our capacity for biomonitoring complex environments, both aquatic and terrestrial. However, eDNA biomonitoring is limited by biases toward certain species and the low taxonomic resolution of current metabarcoding approaches. Shotgun metagenomics of eDNA enables the collection of whole ecosystem data by sequencing all molecules present, allowing characterization and identification.
View Article and Find Full Text PDFJ Med Chem
January 2025
Medicinal Chemistry, Research and Early Development, Respiratory & Immunology, BioPharmaceuicals R&D, AstraZeneca Gothenburg, Pepparedsleden, SE-431 83 Mölndal, Sweden.
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