Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening.

摘要: Target structure-based virtual screening, which employs protein-small molecule docking to identify potential ligands, has been widely used in small-molecule drug discovery. In the present study, we a protein-protein program proteins that bind specific target protein. testing phase, an all-to-all run on large dataset was performed. The three-dimensional rigid SDOCK examine all protein pairs dataset. Both binding affinity and features of energy landscape were considered scoring function order distinguish positive from negative pairs. Thus, lowest score, average Z-score, convergency low-score solutions incorporated analysis. hybrid optimized test. method then screen for tumor necrosis factor-α (TNFα), is well-known therapeutic rheumatoid arthritis other autoimmune diseases. A library containing 677 screen. Proteins with scores among top 20% further examined. Sixteen top-ranking 67 selected experimental study. Two these showed significant TNFα vitro results study demonstrate power application discovery novel targets.