An integrative computational approach for the identification of dual inhibitors of isocitrate dehydrogenase 1 and 2 from phytocompounds of .

Genetic alterations of the genes encoding the isocitrate dehydrogenase (IDH) enzymes have been identified in about 20% of acute myeloid leukemia (AML) cases as well as many other forms of cancers. Notable among these alterations are the neomorphic IDH1_R132H and IDH2_R140Q mutations which lead to the production of an oncometabolite. Hence, their inhibition is widely considered a therapeutic strategy in the treatment of many cancers. While many inhibitors of the mutant enzymes have been developed, an inhibitor that is capable of co-inhibiting both enzymes are currently lacking while drug resistance has also limited the clinical usage of previously identified mono inhibitors. Consequently, this study employed molecular modeling approaches, such as molecular docking, molecular mechanics generalized Born Surface area (MM/GBSA), molecular dynamics (MD) simulation, and density functional theory (DFT) analysis to identify potential dual inhibitors of the previously mentioned mutant IDH1/2 from the phytocompounds of . Of the 31 phytocompounds identified, 20 showed good binding affinities for both IDH1 _R132H and IDH2 _R140Q (ranging from -5.2 Kca/mol to -9.6 Kcal/mol) and had desirable pharmacokinetic properties. However, ellagic acid and pinoresinol possessed better pharmacokinetic properties, rendering suitable hits. Investigation of the behavior of the IDH1_R132H and IDH2_R140Q complexes with ellagic acid and pinoresinol the RMSD, RMSF, and contact map analyses showed that all the complexes-maintained stability throughout the simulation time. Ultimately, ellagic acid and pinoresinol were identified as promising hits for the development of IDH1_R132H and IDH2_R140Q dual inhibitors. However, further experimental studies are needed to confirm their potential as therapies.Communicated by Ramaswamy H. Sarma.