Pharmacophore mapping approach to find anti-cancer phytochemicals with metformin-like activities against transforming growth factor (TGF)-beta receptor I kinase: An in silico study.

The most frequently prescribed first-line treatment for type II diabetes mellitus is metformin. Recent reports asserted that this diabetes medication can also shield users from cancer. Metformin induces cell cycle arrest in cancer cells. However, the exact mechanism by which this occurs in the cancer system is yet to be elucidated. Here, we investigated the impact of metformin on cell cycle arrest in cancer cells utilizing transforming growth factor (TGF)-beta pathway. TGF-ß pathway has significant effect on cell progression and growth. In order to gain an insight on the underlying molecular mechanism of metformin's effect on TGF beta receptor 1 kinase, molecular docking was performed. Metformin was predicted to interact with transforming growth factor (TGF)-beta receptor I kinase based on molecular docking and molecular dynamics simulations. Furthermore, pharmacophore was generated for metformin-TGF-ßR1 complex to hunt for novel compounds having similar pharmacophore as metformin with enhanced anti-cancer potentials. Virtual screening with 29,000 natural compounds from NPASS database was conducted separately for the generated pharmacophores in Ligandscout® software. Pharmacophore mapping showed 60 lead compounds for metformin-TGF-ßR1 complex. Molecular docking, molecular dynamics simulation for 100 ns and ADMET analysis were performed on these compounds. Compounds with CID 72473, 10316977 and 45140078 showed promising binding affinities and formed stable complexes during dynamics simulation with aforementioned protein and thus have potentiality to be developed into anti-cancer medicaments.

Biological and clinical significance of the glypican-3 gene in human lung adenocarcinoma: An in silico analysis.

Glypican-3 (GPC3), a membrane-bound heparan sulfate proteoglycan, has long been found to be dysregulated in human lung adenocarcinomas (LUADs). Nevertheless, the function, mutational profile, epigenetic regulation, co-expression profile, and clinicopathological significance of the GPC3 gene in LUAD progression are not well understood. In this study, we analyzed cancer microarray datasets from publicly available databases using bioinformatics tools to elucidate the above parameters. We observed significant downregulation of GPC3 in LUAD tissues compared to their normal counterparts, and this downregulation was associated with shorter overall survival (OS) and relapse-free survival (RFS). Nevertheless, no significant differences in the methylation pattern of GPC3 were observed between LUAD and normal tissues, although lower promoter methylation was observed in male patients. GPC3 expression was also found to correlate significantly with infiltration of B cells, CD8+, CD4+, macrophages, neutrophils, and dendritic cells in LUAD. In addition, a total of 11 missense mutations were identified in LUAD patients, and ~1.4% to 2.2% of LUAD patients had copy number amplifications in GPC3. Seventeen genes, mainly involved in dopamine receptor-mediated signaling pathways, were frequently co-expressed with GPC3. We also found 11 TFs and 7 miRNAs interacting with GPC3 and contributing to disease progression. Finally, we identified 3 potential inhibitors of GPC3 in human LUAD, namely heparitin, gemcitabine and arbutin. In conclusion, GPC3 may play an important role in the development of LUAD and could serve as a promising biomarker in LUAD.

Targeting SARS-CoV-2 non-structural protein 13 via helicase-inhibitor-repurposing and non-structural protein 16 through pharmacophore-based screening.

Novel drug compound hunting was carried out for SARS-CoV-2 proteins with low mutation susceptibility. The probability of escape mutation and drug resistance is lower if conserved microbial proteins are targeted by therapeutic drugs. Mutation rate of all SARS-CoV-2 proteins were analyzed via multiple sequence alignment Non-Structural Protein 13 and Non-Structural Protein 16 were selected for the current study due to low mutation rate among viral strains and significant functionality. Cross-species mutation rate analysis for NSP13 and NSP16 showed these are well-conserved proteins among four coronaviral species. Viral helicase inhibitors, identified using literature-mining, were docked against NSP13. Pharmacophore-based screening of 11,375 natural compounds was conducted for NSP16. Stabilities of top compounds inside human body were confirmed via molecular dynamic simulation. ADME properties and LD50 values of the helicase inhibitors and Ambinter natural compounds were analyzed. Compounds against NSP13 showed binding affinities between -10 and -5.9 kcal/mol whereby ivermectin and scutellarein showed highest binding energies of -10 and -9.9 kcal/mol. Docking of 18 hit compounds against NSP16 yielded binding affinities between -8.9 and -4.1 kcal/mol. Hamamelitannin and deacyltunicamycin were the top compounds with binding affinities of -8.9 kcal/mol and -8.4 kcal/mol. The top compounds showed stable ligand-protein interactions in molecular dynamics simulation. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, high binding affinity and molecular interactions. Conversion of these compounds into drugs after in vitro experimentation can become better treatment options to elevate COVID management.

Causality analysis of the determinants of FDI in Bangladesh: fresh evidence from VAR, VECM and Granger causality approach.

We tested the causality between FDI and its determinants in Bangladesh in the presence of structural break harnessing Vector Autoregression (VAR) model and Granger causality test. Regressors such as GDP growth rate, inflation, interest, corporate tax, exchange and wage rate, and trade openness (TO) have been used. VAR model finds that interest, tax, wage, and exchange rate do not affect inward FDI. However, the inflation rate and TO significantly impact the inward FDI in Bangladesh. The Granger causality test reveals a bidirectional causality in the FDI-inflation and FDI-TO nexus, whereas other explanatory variables do not cause the FDI granger. Variance decomposition (VDC) and impulse response function (IRF) assessment approve strong, moderate, and poor or no explanatory power of TO, inflation, and other explanatory variables, respectively. Regarding FDI-inflation bidirectional causality, we observed both natural (inflation truly causes FDI) and fake causality (FDI does not necessarily cause inflation). Therefore, when inflation causes FDI, then Bangladeshi Taka (BDT) becomes strong against USD, which increases import and reduces export (import > export). Due to the negative trade balance, this is true for Bangladesh. However, if FDI causes inflation, it will depreciate BDT; consequently, the export will surpass the total import, which is not the case in Bangladesh. Therefore, inflation causes FDI in Bangladesh, and this punch line ends the ongoing debate in the FDI-inflation-exchange rate nexus in Bangladesh. Finally, we recommend decreasing the lending interest rates to encourage further investment, adopting tax holidays, developing a skilled and semi-skilled workforce to harness the advantage of lower wage rates, and being more open to facilitating FDI-led development. Supplementary Information: The online version contains supplementary material available at 10.1007/s43546-022-00247-w.

Spatial Insights for Understanding Colorectal Cancer Screening in Disproportionately Affected Populations, Central Texas, 2019.

INTRODUCTION: Colorectal cancer (CRC) screening can reduce morbidity and mortality; however, important disparities exist in CRC uptake. Our study examines the associations of distance to care and frequency of using primary care and screening. METHODS: To examine the distribution of screening geographically and according to several demographic features, we used individual patient-level data, dated September 30, 2018, from a large urban safety-net health system in Central Texas. We used spatial cluster analysis and logistic regression adjusted for age, race, sex, socioeconomic status, and health insurance status. RESULTS: We obtained screening status data for 13,079 age-eligible patients from the health system's electronic medical records. Of those eligible, 55.1% were female, and 55.9% identified as Hispanic. Mean age was 58.1 years. Patients residing more than 20 miles from one of the system's primary care clinics was associated with lower screening rates (odds ratio [OR], 0.63; 95% CI, 0.43-0.93). Patients with higher screening rates included those who had a greater number of primary care-related (nonspecialty) visits within 1 year (OR, 6.90; 95% CI, 6.04-7.88) and those who were part of the county-level medical assistance program (OR, 1.61; 95% CI, 1.40-1.84). Spatial analysis identified an area where the level of CRC screening was particularly low. CONCLUSION: Distance to primary care and use of primary care were associated with screening. Priorities in targeted interventions should include identifying and inviting patients with limited care engagements.

Geographic Variations of Racial/Ethnic Disparities in Late-Stage Diagnosis of Childhood Cancer in Texas.

OBJECTIVES: This study aimed to identify small geographic areas where the childhood cancer yearly incidence and late-stage diagnosis rates were disproportionately higher among racial/ethnic minorities (Hispanics and non-Hispanic African Americans) in Texas. METHODS: The study examined childhood cancer disparities in Texas from 2005 to 2014, based on geographic location and race/ethnicity. Relative (risk ratio) and absolute (risk difference) measures were used to investigate racial disparities of childhood cancer late-stage diagnosis in small geographic areas (census tracts). The study investigated childhood cancer yearly incidence- and late-stage diagnosis rates for three racial groups combined. The study also analyzed the temporal change of childhood cancer late-stage diagnosis rates based on the data from census tracts where disparities existed for Hispanics and non-Hispanic African Americans compared with a non-Hispanic white reference group. RESULTS: A total of 54% of the cases in the study cohort were diagnosed in the late stage. Although there were fewer non-Hispanic African Americans cases compared with non-Hispanic white and Hispanic cases, they showed significant geographic variation in racial/ethnic disparities compared with the non-Hispanic white reference group. The study also revealed that 58 census tracts for non-Hispanic African Americans and 47 census tracts for Hispanics (of 5265) had significantly higher late-stage diagnosis rates compared with non-Hispanic whites. The findings also demonstrated consistent increases in incidence and late-stage diagnosis from 2005 to 2014 for all cases combined. CONCLUSIONS: Most of the significant census tracts with a higher late-stage diagnosis rate for Hispanics were located on the outskirts of the Dallas-Fort Worth, Houston, and San Antonio areas. In contrast, geographic disparities of childhood cancer late-stage diagnosis for non-Hispanic African Americans were found inside the large metropolitan areas of Houston and Dallas-Fort Worth. The findings of this study will help prioritize the geographical allocation of resources, which, in turn, will help to facilitate preventive healthcare services and alleviate the disease burden in children.

Mapping Disease Transmission Risk of Nipah Virus in South and Southeast Asia.

Since 1998, Nipah virus (NiV) (genus: Henipavirus; family: Paramyxoviridae), an often-fatal and highly virulent zoonotic pathogen, has caused sporadic outbreak events. Fruit bats from the genus Pteropus are the wildlife reservoirs and have a broad distribution throughout South and Southeast Asia, and East Africa. Understanding the disease biogeography of NiV is critical to comprehending the potential geographic distribution of this dangerous zoonosis. This study implemented the R packages ENMeval and BIOMOD2 as a means of modeling regional disease transmission risk and additionally measured niche similarity between the reservoir Pteropus and the ecological characteristics of outbreak localities with the Schoener's D index and I statistic. Results indicate a relatively high degree of niche overlap between models in geographic and environmental space (D statistic, 0.64; and I statistic, 0.89), and a potential geographic distribution encompassing 19% (2,963,178 km²) of South and Southeast Asia. This study should contribute to current and future efforts to understand the critical ecological contributors and geography of NiV. Furthermore, this study can be used as a geospatial guide to identify areas of high disease transmission risk and to inform national public health surveillance programs.