QSAR and molecular docking studies on designing potent inhibitors of SARS-CoVs main protease.

Background: Severe acute respiratory syndrome coronavirus (SARS-CoVs) have emerged as a global health threat, which had caused a high rate of mortality. There is an urgent need to find effective drugs against these viruses. Objective: This study aims to predict the activity of unsymmetrical aromatic disulfides by constructing a QSAR model, and to design new compounds according to the structural and physicochemical attributes responsible for higher activity towards SARS-CoVs main protease. Methods: All molecules were constructed in ChemOffice software and molecular descriptors were calculated by CODESSA software. A regression-based linear heuristic method was established by changing descriptors datasets and calculating predicted IC50 values of compounds. Then, some new compounds were designed according to molecular descriptors from the heuristic method model. The compounds with predicted values smaller than a set point were constantly screened out. Finally, the properties analysis and molecular docking were conducted to further understand the structure-activity relationships of these finalized compounds. Results: The heuristic method explored the various descriptors responsible for bioactivity and gained the best linear model with R2 0.87. The success of the model fully passed the testing set validation, proving that the model has both high statistical significance and excellent predictive ability. A total of 5 compounds with ideal predicted IC50 were found from the 96 newly designed derivatives and their properties analyze was carried out. Molecular docking experiments were conducted for the optimal compound 31a, which has the best compound activity with good target protein binding capability. Conclusion: The heuristic method was quite reliable for predicting IC50 values of unsymmetrical aromatic disulfides. The present research provides meaningful guidance for further exploration of the highly active inhibitors for SARS-CoVs.

Role of 5-methylcytosine in determining the prognosis, tumor microenvironment, and applicability of precision medicine in patients with hepatocellular carcinoma.

Background: 5-methylcytosine has a profound impact on the development and progression of hepatocellular carcinoma. The aim of this study was to investigate the usefulness of 5-methylcytosine in determining the prognosis, tumor microenvironment, and applicability of precision medicine in hepatocellular carcinoma. Methods: We collected data of seven hepatocellular carcinoma cohorts (The Cancer Genome Atlas, International Cancer Genome Consortium, GSE14520, GSE6764, GSE9843, GSE63898, GSE76427). An unsupervised clustering method was used to identify novel subtypes of hepatocellular carcinoma based on the expression 5-methylcytosine gene signatures. The 5-methylcytosine score was determined using the least absolute shrinkage and selection operator method based on the differential expression of genes in the identified subtypes. Subsequently, we investigated the association between 5-methylcytosine-based clusters (according to the 5-methylcytosine score) and clinical outcomes, immunophenotypes, classical molecular subtypes, and therapeutic opportunities in hepatocellular carcinoma. Finally, we examined the sensitivity of patients with high 5-methylcytosine score to drugs. Results: We identified two hepatocellular carcinoma-specific, 5-methylcytosine-based subtypes (clusters 1 and 2). Cluster 1 exhibited significantly higher 5-methylcytosine scores versus cluster 2. The 5-methylcytosine-based subtypes accurately predicted classical molecular subtypes, immunophenotypes, prognosis, and therapeutic opportunities for patients with hepatocellular carcinoma. Cluster 1 (high 5-methylcytosine score) was characterized by lower anticancer immunity and worse prognosis versus cluster 2 (low 5-methylcytosine score). Moreover, cluster 1 (high 5-methylcytosine score) exhibited low sensitivity to cancer immunotherapy, but high sensitivity to radiotherapy and targeted therapy with lenvatinib. Conclusion: The novel 5-methylcytosine-based subtypes (according to the 5-methylcytosine score) may reflect the prognosis, tumor microenvironment, and applicability of precision medicine in patients with hepatocellular carcinoma.

Novel hypoxia features with appealing implications in discriminating the prognosis, immune escape and drug responses of 947 hepatocellular carcinoma patients.

Background: Hypoxia has a profound impact on the development and progression of hepatocellular carcinoma (HCC). This study aimed to explore and elucidate how hypoxia affect prognosis, immune escape and drug responses in HCC. Methods: HCC-specific hypoxia signatures were identified based on the intersect of differentially expressed genes (DEGs) of GSE41666 and GSE15366. The hypoxia score was calculated using the gene set variation analysis (GSVA) function and validated on GSE18494. We collected five cohorts [The Cancer Genome Atlas (TCGA), GSE14520, GSE39791, GSE36376, GSE57957] for further analysis. First, we analyzed the effect of the hypoxia score on prognosis. Next, we systematically analyzed the potential hypoxia-related immune escape mechanisms and the effect of hypoxia upon immunotherapy. Then, we predicted and screened potential sensitive drugs for HCC patients with high hypoxia levels using machine learning and docking. Results: We constructed a novel HCC-specific hypoxia score and undertook further analysis in five cohorts (TCGA, GSE14520, GSE39791, GSE36376, GSE57957). We observed that patients with high hypoxia scores exhibited worse overall survival (OS) in TCGA and GSE14520. We also constructed a hypoxia-related nomogram that had good performance in predicting HCC patients' prognosis. Furthermore, patients with lower hypoxia scores had a lower risk of immune escape and thus may benefit from immunotherapy. Finally, we predicted and screened VLX600 as the candidate drug for HCC patients with high hypoxia scores. We further explored and elucidated why VLX600 was more sensitive in HCC patients with high hypoxia than with low hypoxia HCC patients using weighted gene co-expression network analysis (WGCNA). Conclusions: This study provides further evidence of the link between hypoxia and prognosis and immune escape in HCC patients. Moreover, our research screened VLX600 as a potential drug for HCC patients with high hypoxia levels and elucidated the potential mechanism.

Identifying the potential regulators of neutrophils recruitment in hepatocellular carcinoma using bioinformatics method.

BACKGROUND: Neutrophils play a crucial role in the development and progression of hepatocellular carcinoma (HCC); however, the mechanism underlying neutrophil recruitment is not fully understood. Therefore, we aimed to explore the potential genes or pathways related to neutrophil recruitment in the cancer microenvironment. METHODS: We downloaded TCGA HCC gene expression profiles, the abundance of 22 different immune cells in HCC patients, and patient survival information. We used Kaplan-Meier survival analysis to determine if neutrophils were related to survival. Next, we screened different expression genes (DEGs) between patients with high and low level of neutrophils. We then identified the transcription factor and its targets in the fence of DEGs. Then, we carried out enrichment analysis and gene set variation analysis (GSVA) for targets. Finally, we explored the potential mechanism of targets via calculating correlation scores. RESULTS: Our survival analysis results showed that neutrophils were significantly associated with patient survival. A total of 736 DEGs were screened. Next, we identified transcription factor larger E26 transformation-specific (ETS) homologous factor (EHF) and 702 targets of EHF from 736 DEGs. Among these targets, the level of FGD6 expression had the highest correlation with the level of EHF expression. Enrichment and GSVA analysis for FGD6 showed that the level of GO:0043547 had a positive regulatory effect on GTPase activity and the GO:0007010 cytoskeleton organization was significantly difference between the high and low neutrophils counts. By calculating the correlation between FGD6 and genes in GO:0043547 and GO:0007010, we identified RIC8B and SIPA1L3. CONCLUSIONS: These findings demonstrated that transcription factor EHF can influence recruitment of neutrophils by mediating the transcription of FGD6. Further investigations are needed to shed new light on EHF and its target FGD6.

Multi-omics integrative analysis and survival risk model construction of non-small cell lung cancer based on The Cancer Genome Atlas datasets.

Lung cancer is a major cause of cancer-associated mortality worldwide. However, the association between multi-omics data and survival in lung cancer is not fully understood. The present study investigated the performance of the methylation survival risk model in multi-platform integrative molecular subtypes and aimed to identify copy number (CN) variations and mutations that are associated with survival risk. The present study analyzed 439 lung adenocarcinoma cases based on DNA methylation, RNA, microRNA (miRNA), DNA copy number and mutations from The Cancer Genome Atlas datasets. First, six cancer subtypes were identified using integrating DNA methylation, RNA, miRNA and DNA copy number data. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to extract methylation sites of survival model and calculate the methylation-based survival risk indices for all patients. Survival for patients in the high-risk group was significantly lower compared with that for patients in the low-risk group (P<0.05). The present study also assessed methylation-based survival risks of the six subtypes and analyzed the association between survival risk and non-silent mutation rate, number of segments, fraction of segments altered, aneuploidy score, number of segments with loss of heterozygosity (LOH), fraction of segments with LOH and homologous repair deficiency. Finally, the specific copy number regions and mutant genes associated with the different subtypes were identified (P<0.01). Chromosome regions 17q24.3 and 11p15.5 were identified as those with the most survival risk-associated copy number variation regions, while a total of 29 mutant genes were significantly associated with survival (P<0.01).

3D-QSAR and Molecular Docking Studies on Design Anti-Prostate Cancer Curcumin Analogues.

BACKGROUND: Prostate cancer is one of the most common tumors in the world and the fifth leading cause of male cancer death. Although the treatment of localized androgen-dependent prostate cancer has been successful, the efficacy of androgen-independent metastatic disease is limited. Curcumin, a natural product, has been found to inhibit the proliferation of prostate cancer cells. OBJECTIVE: To design curcumin analogs with higher biological activity and lower toxicity and side effects for the treatment of prostate cancer. METHODS: In this study, the three dimensional-quantitative structure activity relationship (3DQSAR) and molecular docking studies were performed on 34 curcumin analogs as anti-prostate cancer compounds. We introduced OSIRIS Property Explorer to predict drug-related properties of newly designed compounds. RESULTS: The optimum CoMSIA model exhibited statistically significant results: the cross-validated correlation coefficient q2 is 0.540 and non-cross-validated R2 value is 0.984. The external predictive correlation coefficient Rext 2 is 0.792. The information of structure-activity relationship can be obtained from the CoMSIA contour maps. In addition, the molecular docking study of the compounds for 3ZK6 as the protein target revealed important interactions between active compounds and amino acids. CONCLUSION: Compound 28i may be a new type of anti-prostate cancer drug with higher biological activity and more promising development.