Integrated machine learning and structural bioinformatics guided identification of novel molecular scaffolds as renin inhibitors.

Integrating Molecular Design and Machine Learning for Predictive Modeling of Novel DPP-IV Inhibitors in Diabetes Mellitus

The current investigation focuses on the creation of a supervised machine learning model targeting dipeptidyl peptidase-IV(DPP-IV) associated with diabetes mellitus (DM) for expedited drug discovery. A Random Forest regression model was built utilizing molecular fingerprints to anticipate biological activity (pIC₅₀) us...

Dihydropyrimidinones as Potential Direct Renin Inhibitors: In Silico Molecular Docking and Molecular Dynamics Approach

The potential of DHPM derivatives as lead compounds for the development of new renin-targeted antihypertensive therapies is supported by in silico exploring new inhibitors of the renin-angiotensin-aldosterone system (RAAS).

A molecular modeling and machine learning–based approach for the identification of potential human ALOX15 inhibitors

Discovery of PIM-1 kinase inhibitors from marine natural products through machine learning and structure-based screening

These findings identified CMNPD11687 as a promising marine-derived scaffold for PIM-1 inhibition and demonstrated the value of combining ML-driven screening with molecular simulation to accelerate early-stage anticancer drug discovery.

Interpretable Machine Learning for Structure–Activity Relationship Modeling of Cyclooxygenase-1 Inhibitors

An interpretable computational framework is developed for modeling COX-1 inhibitor activity and characterizing prioritized compounds at the molecular level by integrating QSAR modeling, explainable artificial intelligence, molecular docking, molecular dynamics, and MM/GBSA calculations to investigate COX-1 inhibitors.

Editorial overview: Artificial intelligence (AI) methodology in structural biology.

Renal secretion plays an important role in drug excretion from the kidney. Two major transporters known to be highly involved in renal secretion are MATE1/2-K and OCT2, the former of which is highly related to drug-drug interactions. Among published in silico models for MATE inhibitors, a previous model obtained a ROC-...