What does this research mean for the field?

Computational modeling identifies five novel indole-glyoxamide derivatives that demonstrate strong predicted HIV-1 inhibitory action, stable receptor binding, and favorable, non-toxic pharmacokinetic profiles. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This study aims to analyze the inhibitory effects of indole-glyoxamide derivatives against HIV-1 using computational methods.

June 3, 2026Open Access

Computational Modeling Analysis and Retrosynthesis of Indole-Glyoxamide Derivatives as Potential HIV-1 Binding Inhibitors.

Key Points

This study aims to analyze the inhibitory effects of indole-glyoxamide derivatives against HIV-1 using computational methods.
Utilized 3D-QSAR models with CoMFA and CoMSIA to predict efficacy, achieving Q2=0.689 and R2=0.933.
Conducted molecular docking and molecular dynamics simulations to assess binding mechanisms and inhibitor stability.
Proposed five new compounds with enhanced inhibitory activity based on 3D-QSAR and docking data.
The CoMSIA model had a significant coefficient of determination R2test=0.932, indicating strong predictive capability.
Molecular docking revealed the binding stability of proposed compounds in the receptor (PDB code: 1SJ0).
All proposed compounds demonstrated favorable pharmacokinetic properties and non-toxicity.

Abstract

The current study uses computational 3D-QSAR, molecular docking, and molecular dynamics (MD) simulation approaches to examine the inhibitory effect of indole-glyoxamide-based drugs against HIV. The 3D-QSAR models were created using CoMFA and CoMSIA approaches, resulting in Q2=0.689, R2=0.933, and SEE=0.508. The CoMSIA model demonstrated strong molecule prediction, with a significant coefficient of determination R2test=0.932. The molecular docking and molecular dynamics simulations identified the binding mechanism and stability of the inhibitors under research. Additionally, we proposed five additional compounds (T2-T6) with much better inhibitory action based on the data retained by the CoMSIA contour maps. Additionally, the 3D-QSAR results were supported by molecular docking and MD simulation analyses, which supported the proposed compounds' stability in the receptor (PDB code: 1SJ0). The chosen compounds also exhibited acceptable pharmacokinetic characteristics and were non-toxic.

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