Bioinformatics Approach that Identifies Therapies for Chronic Inflammatory Diseases

Greek scientists have come up with a new bioinformatics tool that identifies potential therapies for chronic inflammatory diseases. The researchers used this approach to identify and confirm therapeutic potential of two molecules to target a protein known as Tumor Necrosis Factor (TNF) that is active in rheumatoid arthritis, multiple sclerosis and other diseases.

TNF is not only a key protein in almost all inflammatory processes but also have negative effects in chronic inflammatory diseases. For long, drug companies have been trying to develop anti-TNF treatments that target the protein, blocking TNF function. However existing therapies can be lethal and cause negative side effects. In addition, not all patients respond well to approve anti-TNF therapies.

Recently, the scientists developed a bioinformatics approach to virtually screen nearly 15,000 small molecules whose activities are not known. Concentrating on the protein chemical structures and compound, this new method identified all molecules that could interrupt Tumor Necrosis Factor and its receptor interaction.

Since both Tumor Necrosis Factor shares structural characteristics with RANK, another protein that is also involved in inflammatory processes, the researchers identified compounds that target pro-inflammatory proteins using their virtual screen tool. The scientists identified two small molecules (T8 and T23) that could interact with both TNF and RANKL.



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