Article ; Online: Shedding Light on the Drug–Target Prediction of the Anti-Inflammatory Peptide Tn P with Bioinformatics Tools
Pharmaceuticals, Vol 15, Iss 8, p
2022 Volume 994
Abstract: Peptide–protein interactions are involved in various fundamental cellular functions, and their identification is crucial for designing efficacious peptide therapeutics. Drug–target interactions can be inferred by in silico prediction using bioinformatics ...
| Abstract | Peptide–protein interactions are involved in various fundamental cellular functions, and their identification is crucial for designing efficacious peptide therapeutics. Drug–target interactions can be inferred by in silico prediction using bioinformatics and computational tools. We patented the Tn P family of synthetic cyclic peptides, which is in the preclinical stage of developmental studies for chronic inflammatory diseases such as multiple sclerosis. In an experimental autoimmune enceph-alomyelitis model, we found that Tn P controls neuroinflammation and prevents demyelination due to its capacity to cross the blood–brain barrier and to act in the central nervous system blocking the migration of inflammatory cells responsible for neuronal degeneration. Therefore, the identification of potential targets for Tn P is the objective of this research. In this study, we used bioinformatics and computational approaches, as well as bioactivity databases, to evaluate Tn P–target prediction for proteins that were not experimentally tested, specifically predicting the 3D structure of Tn P and its biochemical characteristics, Tn P–target protein binding and docking properties, and dynamics of Tn P competition for the protein/receptor complex interaction, construction of a network of con-nectivity and interactions between molecules as a result of Tn P blockade, and analysis of similarities with bioactive molecules. Based on our results, integrins were identified as important key proteins and considered responsible to regulate Tn P-governed pharmacological effects. This comprehensive in silico study will help to understand how Tn P induces its anti-inflammatory effects and will also facilitate the identification of possible side effects, as it shows its link with multiple biologically important targets in humans. |
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| Keywords | cyclic peptides ; Tn P ; bioinformatics and computational tools ; drug–target protein interactions ; in silico prediction ; integrin antagonist ; Medicine ; R ; Pharmacy and materia medica ; RS1-441 |
| Subject code | 540 |
| Language | English |
| Publishing date | 2022-08-01T00:00:00Z |
| Publisher | MDPI AG |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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