IScore: A ML-Based Scoring Function for De Novo Drug Discovery.

ABSTRACT: In the quest for accelerating de novo drug discovery, the development of efficient and accurate scoring functions represents a fundamental challenge. This study introduces iScore, a novel machine learning (ML)-based scoring function designed to predict the binding affinity of protein-ligand complexes with remarkable speed and precision. Uniquely, iScore circumvents the conventional reliance on explicit knowledge of protein-ligand interactions and a full picture of atomic contacts, instead leveraging a set of ligand and binding pocket descriptors to directly evaluate binding affinity. This approach enables skipping the inefficient and slow conformational sampling stage, thereby enabling the rapid screening of ultrahuge molecular libraries, a crucial advancement given the practically infinit

SUBMITTER: Mahdizadeh SJ 

PROVIDER: S-EPMC11938276 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature