A novel BH3 mimetic Bcl-2 inhibitor promotes autophagic cell death and reduces in vivo Glioblastoma tumor growth.

Anti-apoptotic members of the Bcl-2 family proteins play central roles in the regulation of cell death in glioblastoma (GBM), the most malignant type of brain tumor. Despite the advances in GBM treatment, there is still an urgent need for new therapeutic approaches. Here, we report a novel 4-thiazolidinone derivative BH3 mimetic, BAU-243 that binds to Bcl-2 with a high affinity. BAU-243 effectively reduced overall GBM cell proliferation including a subpopulation of cancer-initiating cells in contrast to the selective Bcl-2 inhibitor ABT-199. While ABT-199 successfully induces apoptosis in high BCL2-expressing neuroblastoma SHSY-5Y cells, BAU-243 triggered autophagic cell death rather than apoptosis in GBM A172 cells, indicated by the upregulation of BECN1, ATG5, and MAP1LC3B expression. Lc3b-II, a potent autophagy marker, was significantly upregulated following BAU-243 treatment. Moreover, BAU-243 significantly reduced tumor growth in vivo in orthotopic brain tumor models when compared to the vehicle group, and ABT-199 treated animals. To elucidate the molecular mechanisms of action of BAU-243, we performed computational modeling simulations that were consistent with in vitro results. Our results indicate that BAU-243 activates autophagic cell death by disrupting the Beclin 1:Bcl-2 complex and may serve as a potential small molecule for treating GBM.

The neutralization effect of montelukast on SARS-CoV-2 is shown by multiscale in silico simulations and combined in vitro studies.

Small molecule inhibitors have previously been investigated in different studies as possible therapeutics in the treatment of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In the current drug repurposing study, we identified the leukotriene (D4) receptor antagonist montelukast as a novel agent that simultaneously targets two important drug targets of SARS-CoV-2. We initially demonstrated the dual inhibition profile of montelukast through multiscale molecular modeling studies. Next, we characterized its effect on both targets by different in vitro experiments including the enzyme (main protease) inhibition-based assay, surface plasmon resonance (SPR) spectroscopy, pseudovirus neutralization on HEK293T/hACE2+TMPRSS2, and virus neutralization assay using xCELLigence MP real-time cell analyzer. Our integrated in silico and in vitro results confirmed the dual potential effect of montelukast both on the main protease enzyme inhibition and virus entry into the host cell (spike/ACE2). The virus neutralization assay results showed that SARS-CoV-2 virus activity was delayed with montelukast for 20 h on the infected cells. The rapid use of new small molecules in the pandemic is very important today. Montelukast, whose pharmacokinetic and pharmacodynamic properties are very well characterized and has been widely used in the treatment of asthma since 1998, should urgently be completed in clinical phase studies and, if its effect is proved in clinical phase studies, it should be used against coronavirus disease 2019 (COVID-19).

Screening of Clinically Approved and Investigation Drugs as Potential Inhibitors of SARS-CoV-2: A Combined in silico and in†vitro Study.

In the current study, we used 7922 FDA approved small molecule drugs as well as compounds in clinical investigation from NIH's NPC database in our drug repurposing study. SARS-CoV-2 main protease as well as Spike protein/ACE2 targets were used in virtual screening and top-100 compounds from each docking simulations were considered initially in short molecular dynamics (MD) simulations and their average binding energies were calculated by MM/GBSA method. Promising hit compounds selected based on average MM/GBSA scores were then used in long MD simulations. Based on these numerical calculations following compounds were found as hit inhibitors for the SARS-CoV-2 main protease: Pinokalant, terlakiren, ritonavir, cefotiam, telinavir, rotigaptide, and cefpiramide. In addition, following 3 compounds were identified as inhibitors for Spike/ACE2: Denopamine, bometolol, and rotigaptide. In order to verify the predictions of in silico analyses, 4 compounds (ritonavir, rotigaptide, cefotiam, and cefpiramide) for the main protease and 2 compounds (rotigaptide and denopamine) for the Spike/ACE2 interactions were tested by in vitro experiments. While the concentration-dependent inhibition of the ritonavir, rotigaptide, and cefotiam was observed for the main protease; denopamine was effective at the inhibition of Spike/ACE2 binding.

Near-physiological-temperature serial crystallography reveals conformations of SARS-CoV-2 main protease active site for improved drug repurposing.

The COVID-19 pandemic has resulted in 198 million reported infections and more than 4 million deaths as of July 2021 (covid19.who.int). Research to identify effective therapies for COVID-19 includes: (1) designing a vaccine as future protection; (2) de novo drug discovery; and (3) identifying existing drugs to repurpose them as effective and immediate treatments. To assist in drug repurposing and design, we determine two apo structures of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease at ambient temperature by serial femtosecond X-ray crystallography. We employ detailed molecular simulations of selected known main protease inhibitors with the structures and compare binding modes and energies. The combined structural and molecular modeling studies not only reveal the dynamics of small molecules targeting the main protease but also provide invaluable opportunities for drug repurposing and structure-based drug design strategies against SARS-CoV-2.

Association of MTHFR, MTRR and RAD54L Gene Variations with Meningioma and Correlation with Tumor's Histopathological Characteristics on Turkish Cohort.

AIM: To elucidate the association of the MTHFR, MTRR, and RAD54L gene variations with meningioma in Turkish cohort. MATERIAL AND METHODS: DNAs were isolated from 87 retrospective meningioma samples. The MTHFR, MTRR, and RAD54L gene hotspot regions were amplified with specific primers via polymerase chain reaction (PCR), and next-generation sequencing (NGS) was performed. All the detected variations and single-nucleotide polymorphisms (SNPs) were listed and compared with healthy control frequencies in different genomic databases. The histopathological characteristics of meningiomas and genomic variations were compared. Pearson?s chi-squared test was used to detect the statistical differences of SNPs, and correlation analysis was conducted. RESULTS: rs1801131, rs1801133, and rs4846051 on MTHFR, rs1801394 on MTRR, and rs1048771 on RAD54L gene frequencies were found to be significantly altered in the overall cohort of 87 patients with meningioma. The frequency of rs18011031 is 0.09 in the meningioma cohort, which is significantly correlated with WHO tumor grades (p = 0.038). The frequency of rs18011033 is 0.29 in the meningioma cohort, which is significantly correlated with WHO tumor grades (p = 0.045). Furthermore, the frequency of rs4846051 is 0.18 in the meningioma cohort, which is significantly correlated with WHO tumor grades (p = 0.023) and also with low Ki67 proliferation index (p = 0.00455). The frequency of rs1801394 is 0.15 and significantly associated with high Ki67 proliferation index in the meningioma cohort (p = 0.0144). The frequency of rs1048771 is 0.09 in the meningioma cohort and is significantly associated with the non-necrotic histopathological form of the tumor (p = 0.05). CONCLUSION: We reported a significant association between the genetic alterations of folate metabolism (MTHFR, MTRR) and DNA repair mechanism (RAD54L) genes with the histopathological characteristics of meningioma. Five significant SNPs on these genes and four significant correlations of SNPs with histopathological characteristics were identified. This is a preliminary promising study conducted to establish the genetic marker analysis for meningioma diagnosis and prognosis for folate metabolism and DNA repair genes in Turkish cohort.

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.

Antiapoptotic members of B-cell leukemia/lymphoma-2 (BCL-2) family proteins are one of the overexpressed proteins in cancer cells that are oncogenic targets. As such, targeting of BCL-2 family proteins raises hopes for new therapeutic discoveries. Thus, we used multistep screening and filtering approaches that combine structure and ligand-based drug design to identify new, effective BCL-2 inhibitors from a small molecule database (Specs SC), which includes more than 210,000 compounds. This database is first filtered based on binary "cancer-QSAR" model constructed with 886 training and 167 test set compounds and common 26 toxicity quantitative structure-activity relationships (QSAR) models. Predicted non-toxic compounds are considered for target-driven studies. Here, we applied two different approaches to filter and select hit compounds for further in vitro biological assays and human cell line experiments. In the first approach, a molecular docking and filtering approach is used to rank compounds based on their docking scores and only a few top-ranked molecules are selected for further long (100-ns) molecular dynamics (MD) simulations and in vitro tests. While docking algorithms are 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 (1 ns) MD simulations and their binding energies are calculated via molecular mechanics generalized Born surface area (MM/GBSA) method. Then, the compounds are ranked based on their average 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" phrase as many of the approved drugs contain indole and indol derivatives. Around 2700 compounds are filtered based on "cancer-QSAR" model and are then docked into BCL-2. Short MD simulations are performed for the top-docking poses for each compound in complex with BCL-2. The complexes are again ranked based on 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 as well as Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) assay. Inhibitory concentrations are evaluated, and biological activities and apoptotic potentials are assessed by cell culture studies. Four molecules are found to be limiting the proliferation capacity of cancer cells while increasing the apoptotic cell fractions.

Genome-wide identification of Chiari malformation type I associated candidate genes and chromosomal variations.

Chiari malformation type I (CMI) is a brain malformation that is characterized by herniation of the cerebellum into the spinal canal. Chiari malformation type I is highly heterogeneous; therefore, an accurate explanation of the pathogenesis of the disease is often not possible. Although some studies showed the role of genetics in CMI, the involvement of genetic variations in CMI pathogenesis has not been thoroughly elucidated. Therefore, in the current study we aim to reveal CMI-associated genomic variations in familial cases.Four CMI patients and 7 unaffected healthy members of two distinct families were analyzed. A microarray analysis of the affected and unaffected individuals from two Turkish families with CMI was conducted. Analyses of single nucleotide variations (SNVs) and copy number variations (CNVs) were performed by calculation of B allele frequency (BAF) and log R ratio (LRR) values from whole genome SNV data. Two missense variations, OLFML2A (rs7874348) and SLC4A9 (rs6860077), and a 5'UTR variation of COL4A1 (rs9521687) were significantly associated with CMI. Moreover, 12 SNVs in the intronic regions of FAM155A, NR3C1, TRPC7, ASTN2, and TRAF1 were determined to be associated with CMI. The CNV analysis showed that the 11p15.4 chromosome region is inherited in one of the families. The use of familial studies to explain the molecular pathogenesis of complex diseases such as CMI is crucial. It has been suggested that variations in OLFML2A, SLC4A9, and COL4A1 play a role in CMI molecular pathogenesis. The CNV analysis of individuals in both families revealed a potential chromosomal region, 11p15.4, and risk regions that are associated with CMI.