TLR4-Targeting Therapeutics: Structural Basis and Computer-Aided Drug Discovery Approaches

• Published in: Molecules (Basel, Switzerland) Vol. 25; no. 3; p. 627
• Main Authors: Ain, Qurat Ul, Batool, Maria, Choi, Sangdun
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 31-01-2020; MDPI
• Subjects: agonist; Alzheimer's disease; antagonist; Arthritis; Autoimmune diseases; Biological activity; Cancer therapies; Chronic conditions; Clinical trials; Computational neuroscience; computer-aided drug discovery; Cytokines; Drug development; Drug discovery; Drugs; Inflammatory bowel diseases; Inflammatory diseases; Intestine; Kinases; Ligands; Medical treatment; Molecular docking; molecular dynamics; Molecular structure; Multiple sclerosis; Pharmacology; Proteins; Review; Rheumatoid arthritis; Sepsis; Systemic lupus erythematosus; Therapeutic targets; tlr4; TLR4 protein; Toll-like receptors; Tumor necrosis factor-TNF; virtual screening; agonist; virtual screening; computer-aided drug discovery; molecular dynamics; TLR4; antagonist
• ISSN: 1420-3049; 1420-3049
• DOI: 10.3390/molecules25030627

The integration of computational techniques into drug development has led to a substantial increase in the knowledge of structural, chemical, and biological data. These techniques are useful for handling the big data generated by empirical and clinical studies. Over the last few years, computer-aided drug discovery methods such as virtual screening, pharmacophore modeling, quantitative structure-activity relationship analysis, and molecular docking have been employed by pharmaceutical companies and academic researchers for the development of pharmacologically active drugs. Toll-like receptors (TLRs) play a vital role in various inflammatory, autoimmune, and neurodegenerative disorders such as sepsis, rheumatoid arthritis, inflammatory bowel disease, Alzheimer's disease, multiple sclerosis, cancer, and systemic lupus erythematosus. TLRs, particularly TLR4, have been identified as potential drug targets for the treatment of these diseases, and several relevant compounds are under preclinical and clinical evaluation. This review covers the reported computational studies and techniques that have provided insights into TLR4-targeting therapeutics. Furthermore, this article provides an overview of the computational methods that can benefit a broad audience in this field and help with the development of novel drugs for TLR-related disorders.