Probing the origin of dihydrofolate reductase inhibition via proteochemometric modeling

Abstract

AbstractDihydrofolate reductase (DHFR) is an essential enzyme in the folate metabolism pathway and an important target of antineoplastic, antimicrobial, antiprotozoal, and antiinflammatory drugs. Despite the clinical effectiveness of current antifolate treatments, new drugs are needed to be designed due to developing resistance of this enzyme through multiple‐site mutagenesis. Understanding the factors affecting the ligand binding selectivity profiles among DHFR families is critical for the design of novel potent and selective inhibitors, with the least side effects, against DHFR of pathogens. Hybrid scaffolds containing pyrimidine ring are effective in DHFR inhibition. In this study, using proteochemometric (PCM) modeling, we designed and evaluated new potent pyrimidine scaffold‐based inhibitors via 3‐dimensional alignment‐free GRid‐INdependent Descriptors (GRIND), VolSurf molecular, and sequence‐based (z‐scale) descriptors to provide ligand and receptor descriptors, respectively. Validation and robustness of the model were confirmed by venetian blinds cross‐validation and Y‐scrambling approaches, respectively. Applicability domain (AD) analysis was performed to estimate the likelihood of reliable prediction for compounds. To show the applicability of the PCM model, new ligands were designed using structural data retrieved from this model. Inhibitory activities of the designs were then predicted, and selectivity ratio profiles were investigated. Finally, potent and highly selective inhibitors were identified regarding the protozoan parasite Toxoplasma gondii, followed by evaluating the ADMET parameters of the ligands.