Design and Computational Evaluation of Isatin Derivatives as Dual MAO-A/IDO1 Inhibitors: Molecular Docking and...

Monoamine oxidase-A (MAO-A) and indoleamine 2,3- dioxygenase-1 (IDO1) contribute to major depressive disorder via monoamine depletion and activation of the kynurenine pathway. Dual inhibition of these enzymes represents a rational multitarget therapeutic strategy.

To identify potent dual MAO-A/IDO1 inhibitors from a focused library of isatin derivatives using an integrated computational approach.

A total of 140 isatin derivatives were screened against MAO-A (PDB ID: 2BXR) and IDO1 (PDB ID: 6E35) using AutoDock 4.2. Top-ranked candidates were subjected to 100 ns molecular dynamics simulations using the Desmond module. Complex stability was evaluated through root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (rGyr), and solvent-accessible surface area (SASA) analyses to assess the structural stability and dynamic behavior of the protein- ligand complexes throughout the 100 ns molecular dynamics simulations. Moclobemide was used as the reference inhibitor.

Several derivatives demonstrated improved docking scores and favorable interactions within the catalytic pockets of both targets. SDI-107 and SDI-113 maintained stable binding conformations during 100 ns simulations, with protein backbone deviations within 2.0 to 2.5 Å, limited active-site residue fluctuations, sustained hydrogen bonding, and favorable binding free energy profiles compared with moclobemide.

The combined docking and molecular dynamics analyses indicate that structural stability and persistent intermolecular interactions underpin the dual inhibitory potential of SDI-107 and SDI-113. The isatin scaffold appears well suited for simultaneous engagement of the catalytic environments of MAO-A and IDO1, supporting its potential as a multitarget pharmacophore for antidepressant drug discovery.

SDI-107 and SDI-113 emerged as promising dual MAO-A/IDO1 inhibitors, demonstrating favorable binding affinity, stable protein-ligand interactions, and encouraging binding free energy profiles. These findings support further experimental validation and structural optimization toward the development of multitarget-directed antidepressant agents.