AUTHOR=Tutumlu Gurbet , Dogan Berna , Avsar Timucin , Orhan Muge Didem , Calis Seyma , Durdagi Serdar 

TITLE=Integrating Ligand and Target-Driven Based Virtual Screening Approaches With in vitro Human Cell Line Models and Time-Resolved Fluorescence Resonance Energy Transfer Assay to Identify Novel Hit Compounds Against BCL-2

JOURNAL=Frontiers in Chemistry

VOLUME=Volume 8 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2020.00167

DOI=10.3389/fchem.2020.00167

ISSN=2296-2646

ABSTRACT=Antiapoptotic members of  BCL-2 family proteins are one of the overexpressed proteins in cancer cells that are oncogenic targets that raise hopes for new therapeutic discoveries. Here, we have used multi-step screening and filtering approaches that combine structure and ligand-based drug design to identify new, effective BCL-2 inhibitors from small molecules database Specs SC. Compounds are first filtered based on binary “cancer-QSAR” model and common 26 toxicity QSAR models. Non-toxic compounds are considered for target-driven studies and here we have applied two different approaches to select hit compounds for further in vitro human cell line studies. In the first approach, a forward molecular docking and filtering approach is used to rank compounds based on their docking scores and only top-ranked a few molecules are selected for further long (100-ns) molecular simulations (MD) and in vitro tests. Docking algorithms though can be promising in predicting binding poses, they can be less prone to precisely predict ranking of compounds leading to decrease in the success rate of in silico studies. Hence, in the second approach, top-docking poses of each compound filtered through QSAR studies are subjected to initially short (1ns) MD simulations and their binding energies are calculated via MM/GBSA method. Then, the compounds are ranked based on their MM/GBSA energy values to select hit molecules for further long MD simulations and in vitro studies. Additionally, we have applied text-mining approaches to identify molecules that contain indol phased as many of the approved drugs contain indol derivatives. Around 2700 compounds are filtered based on “cancer-QSAR” model and are then docked into BCL-2 protein. Short MD simulations are performed for the top-docking poses for each compound in complex with BCL-2. The complexes are again ranked based their MM/GBSA values to select hit molecules for further long MD simulations and in vitro studies. In total, seven molecules are subjected to biological activity tests in various human cancer cell lines. Inhibitory concentrations are evaluated, and biological activities and apoptotic potentials were assessed by cell culture studies. Four molecules are found to be limiting the proliferation capacity of cancer cells while increasing the apoptotic cell fractions.