首页|Recent Findings from University of Brunei Darussalam Has Provided New Informatio n about Machine Learning (Consensus Holistic Virtual Screening for Drug Discover y: a Novel Machine Learning Model Approach)
Recent Findings from University of Brunei Darussalam Has Provided New Informatio n about Machine Learning (Consensus Holistic Virtual Screening for Drug Discover y: a Novel Machine Learning Model Approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting originating in Gadong, Brunei, by NewsRx journalists, research stated, "In drug discovery, virtual screening is cr ucial for identifying potential hit compounds. This study aims to present a nove l pipeline that employs machine learning models that amalgamates various convent ional screening methods." Financial support for this research came from Council for Research and Advanceme nt in Technology and Science (CREATES) MTIC/CREATES under the Ministry of Transp ort and Infocommunications (MTIC). The news reporters obtained a quote from the research from the University of Bru nei Darussalam, "A diverse array of protein targets was selected, and their corr esponding datasets were subjected to active/decoy distribution analysis prior to scoring using four distinct methods: QSAR, Pharmacophore, docking, and 2D shape similarity, which were ultimately integrated into a single consensus score. The fine-tuned machine learning models were ranked using the novel formula 'w_ new', consensus scores were calculated, and an enrichment study was performed fo r each target. Distinctively, consensus scoring outperformed other methods in sp ecific protein targets such as PPARG and DPP4, achieving AUC values of 0.90 and 0.84, respectively. Remarkably, this approach consistently prioritized compounds with higher experimental PIC50 values compared to all other screening methodolo gies. Moreover, the models demonstrated a range of moderate to high performance in terms of R2 values during external validation."
GadongBruneiCyborgsDrugs and Thera piesEmerging TechnologiesMachine LearningUniversity of Brunei Darussalam
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