Binding Analysis and Structure-Based Design of Tricyclic Coumarin-Derived MTHFD2 Inhibitors as Anticancer Agents: Insights from Computational Modeling

• Unfolded protein response (UPR)-dependent metabolic reprogramming diverts metabolites from glycolysis to mitochondrial 1C metabolism, highlighting pharmacological resistance to folate drugs and overexpression of certain enzymes. Methylenetetrahydrofolate dehydrogenase (MTHFD2) is a mitochondrial enzyme that plays a key role in 1C metabolism in purine and thymidine synthesis and is exclusively overexpressed in cancer cells but absent in most healthy adult human tissues. To the best of our knowledge, tricyclic coumarin-based compounds (substrate site binders) and xanthine derivatives (allosteric site binders) are the only selective inhibitors of MTHFD2 reported until the present date. The current study aims at the investigation of the available structural data of MTHFD2 in complex with potent and selective inhibitors that occupy the substrate binding site, further providing insights into binding mode, key protein-ligand interactions, and conformational dynamics, that correspond to the experimental binding affinities and biological activities. In addition, we carried out structure-based drug design on the substrate binding site of MTHFD2, by exploiting the cocrystal structure of MTHFD2 with the tricyclic coumarin-based inhibitor. The structure-based drug design campaign involves R-group enumeration, bioisostere replacement, molecular docking, ADME prediction, MM-GBSA binding free energy calculations, and molecular dynamics simulations, that led to a small library of new and potential compounds, capable of selectively inhibiting MTHFD2. The results reported herein are expected to benefit medicinal chemists working on the development of selective MTHFD2 inhibitors for cancer treatment, although experimental validation by biochemical and/or pharmacokinetic assays is required to substantiate the outcomes of the study.

Ämnesord

NATURVETENSKAP  -- Kemi (hsv//swe)

NATURAL SCIENCES  -- Chemical Sciences (hsv//eng)

Nyckelord

potential functions

accurate docking

protein

prediction

glide

generation

target

Chemistry

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