A benchmarking-informed structure-based virtual screening strategy targeting Lm-PTR1: Leveraging the Northern African natural products database

J Mol Graph Model. 2026 Jul 1;148:109503. doi: 10.1016/j.jmgm.2026.109503. Online ahead of print.

ABSTRACT

Leishmaniasis is a neglected tropical disease (NTD) affecting millions worldwide. Current treatments have limitations, highlighting the need for new strategies for leishmaniasis drug discovery. Herein, we utilized a benchmarking-informed structure-based virtual screening (SBVS) strategy against Leishmania major folate pathway, especially via targeting pteridine reductase 1 (PTR1). Firstly, representative bioactive molecules against Lm-PTR1 were compiled. Secondly, a challenging DEKOIS 2.0 benchmark set was generated to assess the screening performance of three docking tools, FRED, AutoDock Vina, and PLANTS. Interestingly, FRED showed the best screening performance, with pROC-AUC of 0.84 and EF 1% of 12.5. Consequently, as an example, an ensemble VS of NANPDB using FRED against PTR1 was conducted. The results nominated three candidates for further investigations, namely Anastatin A, valoneic acid dilactone, and 1,6-di-O-galloyl glucose. To assess the binding stability of the candidates, four MD simulations for 500 ns including folic acid - PTR1 complex system as a reference were conducted. Consequently, MM-GBSA calculations and MD profiles confirmed the stable binding of valoneic dilactone and 1,6-di-O-galloyl glucose and ranked them superior to the reference folic acid. These results suggest the ability of both candidates to hinder the access of folic acid to the cofactor NADPH and hence modulate the catalytic function of Lm-PTR1. The identified candidates are recommended for subsequent in vitro evaluations in future investigations. Overall, this benchmarking strategy against Lm-PTR1 can be broadly applied to any accessible compound database for SBVS campaigns. The benchmark dataset for Lm-PTR1 will be made publicly accessible on www.dekois.com.

PMID:42398487 | DOI:10.1016/j.jmgm.2026.109503