ИСТИНА

• Охват: Международная
• Даты проведения: 16-20 сентября 2018
• Место проведения: Thessaloniki, Greece
• Число участников: 200
• Число участников из МГУ: 5
• Число докладчиков: 5
• Веб-сайт: http://www.euroqsar2018.org/
• Описание конференции:

  The European Quantitative Structure-Activity Relationships (EuroQSAR) Symposia are major scientific events that have been organized in different cities of Europe since 1973. They have the fascinating scope to promote and disseminate advances in rational approaches in drug design and discovery and ensure a worldwide attendance of prominent scientists from both academia and industry. The 22nd EuroQSAR 2018 symposium, entitled “Translational and Health Informatics: Implications for Drug Discovery”, will take place September 16-20, 2018 in Thessaloniki, Greece. It is a Turkish-Greek co-organization and an EFMC sponsored event. To honor his impact of his contributions in the field of computer-aided drug discovery (CADD) and QSAR, the 22 nd EuroQSAR Symposium is dedicated to the memory of Prof. Toshio Fujita (1929-2017).

• Добавил в систему: Радченко Евгений Валерьевич

Доклады:

• 2018 Endeavor to analyze antiviral activity data: large-scale analysis of virus-related information allows to find new inhibitors of flavivirus and enterovirus reproduction (Стендовый)
• Авторы: Nikitina A., Orlov A., Osolodkin D., Kozlovskaya L., Palyulin V., Khvatov E.

• 2018 Positive and negative AMPA receptor modulators: design of new scaffolds (Стендовый)
• Авторы: Palyulin V.A., Radchenko E.V., Lavrov M.I., Karlov D.S.

• 2018 Prediction of ligand binding by machine learning analysis of molecular dynamics trajectories (Стендовый)
• Авторы: Berishvili V.P., Perkin V.O., Palyulin V.A., Radchenko E.V., Voronkov A.E.

• 2018 Predictive structural maps of blood-brain permeability to guide the design of neuroactive compounds (Стендовый)
• Авторы: Palyulin V.A., Radchenko E.V.

• 2018 Quasi-docking: comparison of different energy functions in docking (Устный)
• Авторы: Sulimov A.V., Sulimov V.B., Kutov D.C.

• 2018 Target-specific docking scoring functions based on machine learning models to improve virtual screening performance (Стендовый)
• Авторы: Voronkov A.E., Palyulin V.A., Radchenko E.V., Berishvili V.P.