The identification of new ATAD2 bromodomain inhibitors: the application of combined ligand and structure-based virtual screening

Virtual Screening-Based Drug Development for the Treatment of Nervous System Diseases

The incidence rate of nervous system diseases has increased in recent years. Nerve injury or neurodegenerative diseases usually cause neuronal loss and neuronal circuit damage, which seriously affect motor nerve and autonomic nervous function. Therefore, safe and effective treatment is needed. As traditional drug research becomes slower and more expensive, it is vital to enlist the help of cutting- edge technology. Virtual screening (VS) is an attractive option for the identification and development of promising new compounds with high efficiency and low cost. With the assistance of computer- aided drug design (CADD), VS is becoming more and more popular in new drug development and research. In recent years, it has become a reality to transform non-neuronal cells into functional neurons through small molecular compounds, which provides a broader application prospect than transcription factor-mediated neuronal reprogramming. This review mainly summarizes related theory and technology of VS and the drug research and development using VS technology in nervous system diseases in recent years, and focuses more on the potential application of VS technology in neuronal reprogramming, thus facilitating new drug design for both prevention and treatment of nervous system diseases.

Identifying SARS-CoV-2 main protease inhibitors by applying the computer screening of a large database of molecules

The outbreak of coronavirus disease 2019 (COVID-19) at the end of 2019 affected global health. Its infection agent was called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Wearing a mask, maintaining social distance, and vaccination are effective ways to prevent infection of SARS-CoV-2, but none of them help infected people. Targeting the enzymes of SARS-CoV-2 is an effective way to stop the replication of the virus in infected people and treat COVID-19 patients. SARS-CoV-2 main protease is a therapeutic target which the inhibition of its enzymatic activity prevents from the replication of SARS-CoV-2. A large database of molecules has been searched to identify new inhibitors for SARS-CoV-2 main protease enzyme. At the first step, ligand screening based on similarity search was used to select similar compounds to known SARS-CoV-2 main protease inhibitors. Then molecules with better predicted pharmacokinetic properties were selected. Structure-based virtual screening based on the application of molecular docking and molecular dynamics simulation methods was used to select more effective inhibitors among selected molecules in previous step. Finally two compounds were considered as SARS-CoV-2 main protease inhibitors.

Emerging oncogene ATAD2: Signaling cascades and therapeutic initiatives

ATAD2 is a promising oncoprotein with tumor-promoting functions in many cancers. It is a valid cancer drug-target and a potential cancer-biomarker for multiple malignancies. As a cancer/testis antigen (CTA), ATAD2 could also be a probable candidate for immunotherapy. It is a unique CTA that belongs to both AAA+ ATPase and bromodomain family proteins. Since 2007, several research groups have been reported on the pleiotropic oncogenic functions of ATAD2 in diverse signaling pathways, including Rb/E2F-cMyc pathway, steroid hormone signaling pathway, p53 and p38-MAPK-mediated apoptotic pathway, AKT pathway, hedgehog signaling pathway, HIF1α signaling pathway, and Epithelial to Mesenchymal Transition (EMT) pathway in various cancers. In all these pathways, ATAD2 participates in chromatin dynamics, DNA replication, and gene transcription, demonstrating its role as an epigenetic reader and transcription factor or coactivator to promote tumorigenesis. However, despite the progress, an overall mechanism of ATAD2-mediated oncogenesis in diverse origin is elusive. In this review, we summarize the accumulated evidence to envision the overall ATAD2 signaling networks during carcinogenesis and highlight the area where missing links await further research. Besides, the structure-function aspect of ATAD2 is also discussed. Since the efforts have already been initiated to explore targeted drug molecules and RNA-based therapeutic alternatives against ATAD2, their potency and prospects have been elucidated. Together, we believe this is a well-rounded review on ATAD2, facilitating a new drift in ATAD2 research, essential for its clinical implication as a biomarker and/or cancer drug-target.

Development linear and non-linear QSAR models for predicting AXL kinase inhibitory activity of N-[4-(quinolin-4-yloxy)phenyl]benzenesulfonamides

In this research, we used CoMFA, LSSVM and FFANN for creating QSAR models for predicting AXL Kinase inhibitory activity of N-[4-(Quinolin-4-yloxy)phenyl]benzenesulfonamides. A CoMFA model with three components was developed and CoMFA contour maps were interpreted to extract chemical features that influence the inhibitory activity of these molecules. R2 for train and test set of CoMFA model were 0.8900 and 0.8171, respectively. Model created by five Dragon descriptors and LSSVM model showed slightly better predictive power with respect to CoMFA model. R2 for train, test set of created LSSVM model were 0.0.8477 and 0.8218, respectively. Also, a FFANN model, using the same five descriptors, was developed with 2 neurons in its hidden layer and R2 for its train and test sets were 0.8314 and 0.8522, respectively. All created models were validated by calculating several statistical parameters and their applicability domain were investigated by calculating leverage. Furthermore, a homology model was built for Axl structure and molecules with the lowest and the greatest activity were docked to it and their interactions with Axl were investigated.