Approaches to predict ligands affinity towards translocator protein TSPO 18 kDa in order to create molecules possessing neuropsychotropic activity

Abstract

Predict of anxiolytic activity and affinity for the translocator protein (TSPO), compounds in the 1-arylpyrrolo[1,2-a]pyrazine-3-carboxamide series by QSAR (Quantitative structure-activity relationship) and molecular docking was carried out. 9 Models were created from a combination of three methods of machine learning (ASNN, FSMLR, PLS) with a different set of 2D fragmented descriptors (OEState, ISIDA, GSFrag). For the validation of the model, 5-fold cross-checking was used. For molecular docking, the following programs were used: for building 3D ligand models, Marvin software package from ChemAxon, preparation of protein 2MGY (Protein Data Bank) was performed in AutodockTools, and to establish the affinity of Autodock 4.2. In addition, a study was made of the hydrophobic correspondence in the PLATINUM web service. As a result of these studies, the most promising TSPO ligands were identified. Also, the structure-property relationship was evaluated.

Keywords

• 18 кда транслокаторный белок tspo
• молекулярный докинг
• qsar
• нейропсихотропная активность
• 18 kda translocator protein tspo
• molecular docking
• qsar
• neuropsychotropic activity