RL-MSVP: Reinforcement Learning and Multi-scale Validation Pipeline Investigating Azole-Fused Pyrimidines as Potential <i>Pf</i>DHODH Inhibitors.

ABSTRACT: The rising incidence of antimalarial drug resistance necessitates the urgent development of novel therapeutic agents targeting Plasmodium falciparum (Pf). This work presents a thorough computational framework that combines reinforcement learning (RL) driven molecular generation with multiscale validation techniques to find strong inhibitors of Pfdihydroorotate dehydrogenase (PfDHODH), a proven antimalarial target in the pyrimidine biosynthesis pathway. To create new molecular entities featuring DSM cores such as triazolopyrimidine and isoxazolopyrimidine scaffolds, we used REINVENT4.0 and its unique LibINVENT model. The 20,000 initial compounds produced by the RL approach were then further screened using filtering protocols that included drug-likeness parameters

SUBMITTER: Thomas TV 

PROVIDER: S-EPMC12750384 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature