phkineticaФармакокинетика и ФармакодинамикаPharmacokinetics and Pharmacodynamics2587-78362686-8830ООО «Издательство ОКИ»10.24411/2587-7836-2019-10036phkinetica-83Research ArticleМЕХАНИЗМ ДЕЙСТВИЯMECHANISM OF ACTIONПодходы к прогнозированию аффинности лигандов 18 кДа транслокаторного белка TSPO с целью создания молекул с нейропсихотропной активностью человека (HUVEC)Approaches to predict ligands affinity towards translocator protein TSPO 18 kDa in order to create molecules possessing neuropsychotropic activityБарабошкинН. М.BaraboshkinN. M.noemail@neicon.ruПантилеевА. С.PantileevA. S.and.pantileev@academpharm.ruМокровГ. В.MokrovG. V.noemail@neicon.ruФГБНУ «НИИ фармакологии имени В.В. Закусова»РоссияFSBI «Zakusov Institute of Pharmacology»Russian Federation201906012019012230Copyright © Барабошкин Н.М., Пантилеев А.С., Мокров Г.В., 20192019Барабошкин Н.М., Пантилеев А.С., Мокров Г.В.Baraboshkin N.M., Pantileev A.S., Mokrov G.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.pharmacokinetica.ru/jour/article/view/83

Выполнено прогнозирование аффинности к 18 кДа транслокаторному белку (TSPO) соединений в ряду 1-арилпирроло[1,2-а]пиразин-3-карбоксамидов методами QSAR (Quantitative structure-activity relationship) и молекулярного докинга. Были созданы 9 моделей из комбинации трёх методов машинного обучения (ASNN, FSMLR, PLS) с различным набором 2D фрагментарных дескрипторов (OEState, ISIDA, GSFrag). Для валидации модели использовался 5-кратный перекрёстный контроль. Для молекулярного докинга использовались следующие программы: для построения 3D моделей лигандов программный пакет Marvin от ChemAxon, подготовка белка 2MGY (Protein Data Bank) выполнялась в AutodockTools, а для установления аффинности Autodock 4.2. дополнительно было проведено исследование гидрофобного соответствия в веб-сервисе PLATINUM. В результате данных исследований были выявлены наиболее перспективные лиганды TSPO. Произведён анализ связи структура-аффинность.

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.

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The authors declare that there are no conflicts of interest present.