Computational Identification and Anti-Inflammatory Evaluation of T19093 as a TLR4/MD2 Inhibitor.

ABSTRACT:

Background

The TLR4 (Toll-like receptor 4)/MD2 (Myeloid differentiation protein-2) is a crucial target for developing novel anti-inflammatory drugs. Nevertheless, current inhibitors often have significant adverse effects, necessitating the discovery of safer alternatives.

Objective

The investigation aims to identify novel TLR4/MD2 inhibitors with potential antiinflammatory activity using machine learning and virtual screening technology.

Methods

A machine-learning model was created using the MACCS (Molecular ACCess Systems) key fingerprint. Subsequently, virtual screening and molecular docking were used to evaluate candidate compounds' binding free energy to the TLR4/MD2 complex. Furthermore, ADMET (absorption, distribution, metabolism, excretion, and toxicity) predic

SUBMITTER: Chen K 

PROVIDER: S-EPMC12728533 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature