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◆ ACS medicinal chemistry letters2026-09-10

A‑iMPO: A Design-Time Prediction Toolbox for Blood Brain Barrier Permeation Using an Integrated and Interpretable Multiparameter Optimization Framework.

Samiron Phukan, Ashis Nandy, Manjunath Ramarao

原始摘要(英文原文)· Original abstract
Design time prioritization of central nervous system (CNS) drug candidates remains a challenge due to the restrictive nature of the blood-brain barrier (BBB) governing brain exposure. Although various multiparameter optimization (MPO) strategies have guided CNS medicinal chemistry for over a decade, existing frameworks rely heavily on heuristic cutoffs and offer limited interpretability across chemically diverse scaffolds. Here, we introduce a next generation CNS-MPO frameworkAragen-iMPO, (A-iMPO)which was developed using 5,129 curated compounds through an integrated workflow combining explainable machine learning, rigorous descriptor selection, and low-dimensional discriminant mapping. This yielded six chemically intuitive features capturing polarity, ionization, size, rigidity, and electronic distribution. The resulting score provides a transparent discriminant function enabling direct compound prioritization through a simple threshold rule. Across internal and external validation sets, A-iMPO outperformed established CNS-focused scoring methods while maintaining mechanistic interpretability, providing a practical and design ready tool for CNS drug discovery.
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A‑iMPO: A Design-Time Prediction Toolbox for Blood Brain Barrier Permeation Using an Integrated and Interpretable Multiparameter Optimization Framework. — 科研速览 Science Skim