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Updated: Feb 6, 2026
10:24
A Fluorescence-based Protocol for Preliminary Screening of Protein Synthesis Inhibitors from Natural Sources
Published on: January 27, 2026
149
Proposing novel TNFα direct inhibitor Scaffolds using fragment-docking based e-pharmacophore modeling and binary
Mehreen Zaka1, Bilal Haider Abbasi2, Serdar Durdagi3
1Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey; Department of Biotechnology, Quaid-i-Azam University, Islamabad, Pakistan.
Journal of Molecular Graphics & Modelling
|August 28, 2018
Summary
This study developed novel computational models to screen for small molecule inhibitors of tumor necrosis factor alpha (TNFα), a key protein in inflammation and autoimmune diseases. Researchers identified potential safe and effective drug candidates, offering alternatives to current biological therapies.
Area of Science:
- Computational chemistry and drug discovery
- Immunology and molecular biology
- Pharmacology and medicinal chemistry
Background:
- Tumor necrosis factor alpha (TNFα) is a critical protein in immune responses and autoimmune diseases like rheumatoid arthritis (RA).
- Current biological treatments for TNFα-related diseases have limitations, including potential side effects.
- Small molecule-based therapies present a promising alternative for treating inflammatory conditions.
Purpose of the Study:
- To develop and apply novel in silico methods for identifying small molecule inhibitors of TNFα.
- To screen large compound libraries for potential drug candidates targeting TNFα.
- To assess the safety and efficacy of identified compounds.
Main Methods:
- Development of energetically optimized, structure-based pharmacophore models using fragment-based docking.
- Screening of diverse compound libraries (Specs-SC, Specs-NP, NCGC pharmaceutical collection) using pharmacophore and quantitative structure-activity relationship (QSAR) models.
- Prediction of pharmacokinetic and toxicity profiles using the MetaCore/MetaDrug platform.
- Molecular docking and molecular dynamics simulations of selected hit molecules against TNFα (homodimer and homotrimer forms).
Main Results:
- Identification of indinavir and medroxalol from the NCGC pharmaceutical collection as potential TNFα inhibitors.
- Discovery of several compounds (e.g., AT-057/43115940, AP-970/42897107) from the Specs-SC database with potential direct TNFα inhibitory activity.
- Selected compounds were predicted to be safe and active direct inhibitors of TNFα.
Conclusions:
- Novel computational approaches enable efficient in silico screening for small molecule TNFα inhibitors.
- The study identified promising drug candidates for TNFα-related inflammatory and autoimmune diseases.
- These findings support the development of small molecule-based therapies as alternatives to current biological treatments.
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