首页|Chongqing University Reports Findings in Machine Learning (Exploring novel lead scaffolds for SGLT2 inhibitors: Insights from machine learning and molecular dyn amics simulations)
Chongqing University Reports Findings in Machine Learning (Exploring novel lead scaffolds for SGLT2 inhibitors: Insights from machine learning and molecular dyn amics simulations)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting out of Chongqing, People's Republic of C hina, by NewsRx editors, research stated, "Sodium-glucose cotransporter 2 (SGLT2 ) plays a pivotal role in mediating glucose reabsorption within the renal filtra te, representing a well-known target in type 2 diabetes and heart failure. Recen t emphasis has been directed toward designing SGLT2 inhibitors, with C-glycoside inhibitors emerging as front-runners." Our news journalists obtained a quote from the research from Chongqing Universit y, "The architecture of SGLT2 has been successfully resolved using cryo-electron microscopy. However, comprehension of the pharmacophores within the binding sit e of SGLT2 remains unclear. Here, we use machine learning and molecular dynamics simulations on SGLT2 bound with its inhibitors in preclinical or clinical devel opment to shed light on this issue. Our dataset comprises 1240 SGLT2 inhibitors amalgamated from diverse sources, forming the basis for constructing machine lea rning models. SHapley Additive exPlanation (SHAP) elucidates the crucial fragmen ts that contribute to inhibitor activity, specifically Morgan_3, 16 2, 310, 325, 366, 470, 597, 714, 926, and 975. Furthermore, the computed binding free energies and per- residue contributions for SGLT2-inhibitor complexes unvei l crucial fragments of inhibitors that interact with residues Asn-75, His-80, Va l-95, Phe-98, Val-157, Leu-274, and Phe-453 in the binding site of SGLT2."
ChongqingPeople's Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningMolecular DynamicsPhysi cs
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