Toward resistance‐compromised DHFR inhibitors part 1: Combined structure/ligand‐based virtual screenings and ADME‐Tox profiling

The front‐line antimalarial drugs, for example, chloroquine, mefloquine, sulfadoxine, pyrimethamine, atovaquone, and artemether, are often failing because of the worldwide spread of drug‐resistant parasites. There has been significant recent interest in virtual screening to drive innovative drug discovery and to combat resistance efforts for a wide range of diseases. In fact, virtual screening has become the “gold standard” for major pharmaceutical industries and some university groups. Therefore, we present herein a structure‐based LibDock/CHARMM modeling and a set of appropriate scoring function evaluation criteria: correlation, consensus score, correlation‐based score, generally applicable replacement for root‐mean‐square deviation using a training set of 38 phenylthiazolyl‐1,3,5‐triazines from our previous reports and followed by a ligand‐based model to identify molecular features like hydrogen‐bond acceptor, hydrogen‐bond donor, hydrophobicity, and ring aromatic (RA) using Catalyst HipHop/HypoGen module. Next, TOPKAT module was applied to predict ADME‐Tox properties. The combined structure/ligand‐based approaches inadvertently arrived at a conserved Arg122 binding site from reliable LigScore1_dreiding top scoring function and are subsequently attributed to reserve important interactions and combat mutational drug resistance. The best pharmacophore model suggested that 1 hydrogen‐bond acceptor, 2 hydrophobicities, and 1 ring aromatic feature with good sensitivity at 0.50, specificity at 0.66, enrichment at 1.60, and accuracy at 0.50. Finally, good pharmacokinetics, metabolic stability, and toxicity endpoints were predicted in the comparison of proguanil and cycloguanil. These druggability insights are useful for researchers to deliver more effective, safer, both wild‐type and resistance‐compromised, and more economical dihydrofolate reductase inhibitors in the near future.     

Binding of α-hydroxy-β-amino acid inhibitors to methionine aminopeptidase. The performance of two types of scoring functions

The binding mode of a recently described set of -hydroxy--amino acid inhibitors of methionine aminopeptidase type 2 is suggested in the present work. The binding mode is supported by analysis of published structures of transition state analogues co-crystallised with E. coli methionine aminopeptidase and by a comparison of molecular interaction fields calculated using GRID for E. coli and human methionine aminopeptidase. Based on the suggested binding mode two types of scoring functions have been evaluated and compared. These are the commercially available consensus score, CScore, and scoring of the ligands employing energies calculated using the Merck Molecular Force Field (MMFF). Enriched subsets of ligands were obtained when using CScore, but these scores could not be used to assess the relative affinities of individual compounds. Although still not sufficiently accurate for reliable predictive purposes, an improved correlation was obtained between structure and affinity using a combined force field energy including contributions from solvation and conformational energy penalty for binding.