Computational study of novel natural inhibitors targeting Kirsten rat sarcoma viral oncogene homolog G12C.

Lung adenocarcinoma is one of the most aggressive and rapidly fatal types of malignant lung tumor. Molecular docking and virtual screening were effectively and systematically used to identify specific targets in malignant tumors and screen potential drugs. Here, we screen perfect leading compounds from a medicate library (ZINC15 database) and analyze their properties (conveyance, absorption, metabolism, excretion, and harmless forecasts) with potential inhibition of Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS) G12C. Further results demonstrated that ZINC000013817014 and ZINC000004098458 were screened out from the ZINC15 database and were identified to have a much better binding affinity and more favorable interaction vitality binding with KRAS G12C and less rat carcinogenicity, Ames mutagenicity, way better dissolvability in water and noninhibition with cytochrome P-450 2D6. Molecular dynamics simulation analysis indicated that the binding capacity of these two compounds and KRAS G12C, ZINC000013817014-KRAS G12C, and ZINC000004098458-KRAS G12C is stable in the natural environment. Our findings reveal that ZINC000013817014 and ZINC000004098458 were perfect leading compounds to be inhibitors binding with KRAS G12C, which were selected as safe drug candidates and a cornerstone for KRAS G12C-related medicine plan and improvement. What is more, we have conducted a Cell Counting Kit-8 to verify the exactly inhibitory effects of the two selected drugs on Lung adenocarcinoma. This study establishes a solid framework for systematic anticancer medication research and development.

Identification of novel natural inhibitors targeting AKT Serine/Threonine Kinase 1 (AKT1) by computational study.

Despite great progress, the current cancer treatments often have obvious toxicity and side effects. and a poor prognosis (some patients). One of the reasons for the poor prognosis is that certain enzymes prevent anticancer drugs from killing tumor cells. AKT1 is involved in regulating PI3K/AKT/mTOR, a tumor-generating pathway. Ipatasertib, a highly selective inhibitor of AKT1, is widely used in the treatment of tumors. In this study, many structural and biochemical methodswere used to find better AKT1(Threonine Kinase 1) inhibitors, which laid a foundation for the further development of AKT1 inhibitors and provided new drugs for the treatment of tumors. ZINC15 database and Discovery Studio 4.5, a computer-aided drug screening software with many modules (LibDock for virtual screening, ADME (Absorption, Distribution, Metabolism, Excretion) and TOPKAT (toxicity prediction module) for the toxicity and properties analysis, and MD simulation for stability prediction), were employed. CCK8 assay, ELISA assay genicity and higher tolerance to cytochrome P4502D6. MD simulations indicated they could bind with AKT1 stably in the natural environment. The cell experiment and specific assay for AKT1 inhibition showed they could inhibit the proliferation and AKT1 expression of MG63 cells (Osteosarcoma cells). Moreover, these novel compounds with structural modifications can be potential contributors that lead to further rational drug design for targeting AKT1.AbbreviationAKT1, AKT Serine/Threonine Kinase 1; ADME, absorption, distribution, metabolism, excretion; TOPKAT, toxicity prediction by Computer assisted technology; CCK8, Cell Counting Kit 8; ELISA, Enzyme-linked immunosorbent assay; CYP2D6, cytochrome P4502D6 inhibition; GBM, Glioblastoma; AGC kinase, protein kinase A, G, and C families (PKA, PKC, PKG); PKB, protein kinase B; PAM pathway, PI3K/AKT/mTOR pathway; OS, overall survival; PFS, progression-free survival; LD50, lethal dose half in rats; LOAEL, lowest observed adverse effect level; NPT, normal pressure and temperature; PME, particle mesh Ewald; LINCS, linear constraint solver; RMSD, root-mean-square deviation; BBB, blood-brain barrier; DS, Discovery Studio; DTP, Developmental toxicity potential; PPB, Plasma protein binding; MTD, Maximum Tolerated Dosage; AB, Aerobic Biodegradability; NTP, US. National Toxicology Program; DTP, developmental toxicity potential.

Identification of key pathways and genes in vestibular schwannoma using bioinformatics analysis.

The aim of the present study is to identify novel promising marks and targets of diagnosis, therapy and prognosis for patients with vestibular schwannoma at the molecular level. The gene expression profiles of GSE54934, GSE39645 and GSE56597 datasets were obtained respectively from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified by comparing between gene expression profiles of the vestibular schwannoma tissues and normal tissues. Subsequently, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein-protein interaction (PPI) network analysis were performed. The function and pathway enrichment analysis were performed for DEGs with DAVID. Reverse transcription-quantitative PCR were conducted to confirm the expression of BCL2, AGT, IL6 and ITGA2 in human Schwann cells and vestibular schwannoma cells. A total of 4,025, 1,1291 and 1,513 DEGs were identified from GSE54934, GSE56597 and GSE39645 datasets, respectively. GO and KEGG analysis showed that the mutual upregulated genes were mainly enriched in cell division, mitotic nuclear division, and transition of mitotic cell cycle, whilst mutual downregulated genes were enriched in chemical synaptic transmission, neurotransmitter transport, and synaptic vesicle membrane. Subsequently, 20 genes, including BCL2, AGT, IL6 and ITGA2 were selected as hub genes with high degrees after PPI network analysis. The significant differential expression of those genes were detected among vestibular schwannoma tissues compared with normal nerve tissues. In conclusion, BCL2, AGT, IL6 and ITGA2 are significantly higher expressed in vestibular schwannoma tissues compared with human Schwann tissues. The DEGs identified in the present study provide novel targets for the diagnosis and treatment of vestibular schwannoma.

Potential Pathogenic Genes and Mechanism of Ankylosing Spondylitis: A Study Based on WGCNA and Bioinformatics Analysis.

OBJECTIVE: The purpose of this study is to explore the high-risk pathogenic driver genes for the occurrence and development of ankylosing spondylitis (AS) based on the bioinformatics method at the molecular level, to further elaborate the molecular mechanism of the pathogenesis of AS, and to provide potential biological targets for the diagnosis and treatment of clinical AS. METHODS: The gene expression profile data GSE16879 were downloaded from the GEO (Gene Expression Omnibus) database, and weighted gene coexpression network analysis was performed. Highly correlated genes were divided into 14 modules, and 582 genes contained in the yellow (classic module) and 59 genes contained in grey60 (hematologic module) modules had the strongest correlation with AS. After protein-protein interaction (PPI) analysis, the top 20 genes with the highest scores were obtained from classic module and hematologic module, respectively. The DAVID (Database for Annotation, Visualization, and Integrated Discovery) database was used for Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes analysis to analyze the biological functions of high-risk genes related to AS. RESULTS: The results showed that the process of signal recognition particle-dependent cotranslational protein targeting to membrane, ribosome, nicotinamide adenine diphosphate hydride dehydrogenase (ubiquinone) activity, platelet activation, integrin complex, and extracellular matrix binding were enriched. CONCLUSIONS: In this study, weighted gene coexpression network analysis, an efficient system biology algorithm, was used to analyze the high-risk pathogenic driver gene of AS. We provide new targets for the diagnosis and treatment of clinical AS and new ideas for further study.

Computational study of effective matrix metalloproteinase 9 (MMP9) targeting natural inhibitors.

OBJECT: The present study screened ideal lead natural compounds that could target and inhibit matrix metalloproteinase 9 (MMP9) protein from the ZINC database to develop drugs for clear cell renal cell carcinoma (CCRCC)-targeted treatment. METHODS: Discovery Studio 4.5 was used to compare and screen the ligands with the reference drug, solasodine, to identify ideal candidate compounds that could inhibit MMP9. The LibDock module was used to analyze compounds that could strongly bind to MMP9, and the top 20 compounds determined by the LibDock score were selected for further research. ADME and TOPKAT modules were used to choose the safe compounds from these 20 compounds. The selected compounds were analyzed using the CDOCKER module for molecular docking and feature mapping for pharmacophore prediction. The stability of these compound-MMP9 complexes was analyzed by molecular dynamic simulation. Cell counting kit-8, colony-forming, and scratch assays were used to analyze the anti-CCRCC effects of these ligands. RESULTS: Strong binding to MMP9 was exhibited by 6,762 ligands. Among the top 20 compounds, sappanol and sventenin exhibited nearly undefined blood-brain barrier level and lower aqueous solubility, carcinogenicity, and hepatotoxicity than the positive control drug, solasodine. Additionally, these compounds exhibited lower potential energies with MMP9, and the ligand-MMP9 complexes were stable in the natural environment. Furthermore, sappanol inhibited CCRCC cell migration and proliferation. CONCLUSION: Sappanol and sventenin are safe and reliable compounds to target and inhibit MMP9. Sappanol can CCRCC cell migration and proliferation. These two compounds may give new thought to the targeted therapy for patients with CCRCC.

Computational study on novel natural inhibitors targeting c-MET.

ABSTRACT: This study was designed to select ideal lead compounds and preclinical drug candidates http://dict.youdao.com/w/eng/preclinical_drug_candidate/javascript:void (0); with inhibitory effect on c-MET from the drug library (ZINC database).A battery of computer-aided virtual techniques was used to identify possible inhibitors of c-MET. A total of 17,931 ligands were screened from the ZINC15 database. LibDock is applied for structure-based screening followed by absorption, distribution, metabolic, and excretion, and toxicity prediction. Molecular docking was conducted to confirm the binding affinity mechanism between the ligand and c-MET. Molecular dynamics simulations were used to assess the stability of ligand-c-MET complexes.Two new natural compounds ZINC000005879645 and ZINC000002528509 were found to bind to c-MET in the ZINC database, showing higher binding affinity. In addition, they were predicted to have lower rodent carcinogenicity, Ames mutagenicity, developmental toxicity potential, and high tolerance to cytochrome P4502D6. Molecular dynamics simulation shows that ZINC000005879645 and ZINC000002528509 have more favorable potential energies with c-MET, which could exist stably in the natural environment.This study suggests that ZINC000005879645 and ZINC000002528509 are ideal latent inhibitors of c-MET targeting. As drug candidates, these 2 compounds have low cytotoxicity and hepatotoxicity as well as important implications for the design and improvement of c-MET target drugs.

Identification of effective natural PIK3CA H1047R inhibitors by computational study.

Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer with a poor prognosis and a high recurrence rate. PIK3CA gene is frequently mutated in breast cancer, with PIK3CA H1047R as the hotspot mutation reported in TNBC. We used the ZINC database to screen natural compounds that could be structurally modified to develop drugs targeting the PIK3CA H1047R mutant protein in the PI3K pathway. The LibDock module showed that 2,749 compounds could strongly bind to the PIK3CA H1047R protein. Ultimately, the top 20 natural ligands with high LibDock scores were used for further analyses including assessment of ADME (absorption, distribution, metabolism, and excretion), toxicity, stability, and binding affinity. ZINC000004098448 and ZINC000014715656 were selected as the safest drug candidates with strong binding affinity to PIK3CA H1047R, no hepatotoxicity, less carcinogenicity, better plasma protein binding (PPB) properties, and enhanced intestinal permeability and absorption than the two reference drugs, PKI-402 and wortmannin. Moreover, their lower potential energies than those of PIK3CA H1047R confirmed the stability of the ligand-receptor complex under physiological conditions. ZINC000004098448 and ZINC000014715656 are thus safe and stable leads for designing drugs against PIK3CA H1047R as part of a targeted therapeutic approach for patients with TNBC.

Novel natural inhibitors targeting B-RAF(V600E) by computational study.

The aim of this research was to screen the ZINC15 database to select lead compounds and drug candidates which can inhibit B-RAF (V600E). In order to identify drugs potentially inhibited B-RAF (V600E), numerous modules of Discovery Studio 4.5 were employed. Structure-based screening using LibDock was carried out followed by ADME (absorption, distribution, metabolism, excretion) and toxicity prediction. CDOCKER was performed to demonstrate the binding affinity and mechanism between ligands and B-RAF(V600E). To evaluate whether ligand-receptor complexes were stable, molecular dynamics were employed. Two novel natural compounds (ZINC000100168592 and ZINC000049784088) from ZINC15 database were found binding to B-RAF(V600E) with more favorable interaction energy in comparison with the reference drug Vemurafenib. Also, they were predicted with less ames mutagenicity, rodent carcinogenicity, non-developmental toxic potential and tolerance to cytochrome P450 2D6 (CYP2D6). The molecular dynamics simulation analysis indicated that the compound-B-RAF(V600E) complexes had more favorable potential energy compared with Vemurafenib and they can exist in natural environments stably. The result of this study shows that ZINC000100168592 and ZINC000049784088 are ideal leading potential compounds to inhibit B-RAF(V600E). The findings of this study and these selected drug candidates greatly contributed to the medication design and improvement of B-RAF(V600E) and other proteins.

Computational study on novel natural inhibitors targeting BCL2.

Ideal lead compounds and candidate drugs with inhibitory effect on BCL2 were screened from ZINC database, which laid a foundation for drug development and compound improvement of drug treatment for diffuse large B-cell lymphoma (DLCBL). Identification of potential BCL2 inhibitors by computer-aided virtual screening. Libdock was applied to 17,931 compounds and the top 20 were selected for further analysis. Selected compounds were performed absorption, distribution, metabolism, and excretion (ADME) and toxicity prediction. The binding affinity between the selected ligands and BCL2 was confirmed by Molecular docking. The new natural compounds, ZINC00000255131 and ZINC00013298233, were found to bind closely with BCL2. Furthermore, they all scored lower in ames-induced mutagenicity, rodent carcinogenicity, non-developmental toxicity potential, and cytochrome P4502D6 tolerance. Molecular dynamics simulation shows that the combinations of ZINC00000255131 and ZINC00013298233 with BCL2 in the natural environment are more stable. Two new compounds, ZINC00000255131 and ZINC00013298233, were found to be potential inhibitors of BCL2. These compounds have been proved to be safe, which is of great significance for the development and improvement of DLCBL drugs.

Identification of driver genes and key pathways of non-functional pituitary adenomas predicts the therapeutic effect of STO-609.

OBJECTIVE: Our study is to identify DEGs (Differentially Expressed Genes), comprehensively investigate hub genes, annotate enrichment functions and key pathways of Non-functional pituitary adenomas (NFPAs), and also to verify STO-609 therapeutic effect. METHODS: The gene expression level of NFPA and normal tissues were compared to identify the DEGs (Differential expressed genes) based on gene expression profiles (GSE2175, GSE26966 and GSE51618). Enrichment functions, pathways and key genes were identified by carrying out GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis and PPI (Protein-Protein Interation) network analysis. Moreover, experiments in vitro were conducted to verify the anti-NFPAs effects of STO-609. RESULTS: 169 over-expression genes and 182 low expression genes were identified among 3 datasets. Dopaminergic synapse and vibrio cholerae infection pathways have distinctly changed in NFPA tissues. The Ca2+/CaM pathway played important roles in NFPA. Four hub proteins encoded by genes CALM1, PRDM10, RIPK4 and MAD2L1 were recognized as hub proteins. In vitro, assays showed that STO-609 induced apoptosis of NFPA cells to inhibit the hypophysoma cellular viability, diffusion and migration. CONCLUSION: Four hub proteins, encoded by gene CALM1, PRDM10, RIPK4 and MAD2L1, played important roles in NFPA development. The Ca2+/CaM signaling pathway had significant alternations during NFPA forming process, the STO-609, a selective CaM-KK inhibitor, inhibited NFPA cellular viability, proliferation and migration. Meanwhile, NFPA was closely related to parkinson's disease (PD) in many aspects.

T5224, RSPO2 and AZD5363 are novel drugs against functional pituitary adenoma.

We tested whether the drugs T5224, RSPO2, and AZD5363 exert therapeutic effects against functioning pituitary adenoma (FPA). We analysed the gene expression profiles of four FPA mRNA microarray datasets (GSE2175, GSE26966, GSE36314, and GSE37153) from the Gene Expression Omnibus database and identified genes differentially expressed in FPA vs control tissues. We then carried out Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction network analyses. We also measured the difference in expression of hub genes between human normal pituitary cells and FPA cells using qRT-PCR. Our in vitro colony-formation and MTT assays showed that cell viability, number, and the size of clonogenicities were all lower in the presence of T5224, RSPO2, or AZD536 than in controls. Moreover, flow cytometry experiments showed that the incidence of apoptosis was higher in the presence of T5224, RSPO2, or AZD5363 than among controls, and was increased by increasing the doses of the drugs. This suggests these drugs could be used as therapeutic agents to treat FPA. Finally, we found that cFos, WNT5A, NCAM1, JUP, AKT3, and ADCY1 are abnormally expressed in FPA cells compared to controls, which highlights these genes as potential prognostic and/or therapeutic targets.

Identification of Driver Genes and Key Pathways of Ependymoma.

AIM: Objective: To identify ependymoma (EPN) driver genes and key pathways, and also to illuminate the connection between prognosis of EPN patients and expression levels of driver genes. MATERIAL AND METHODS: Methods: The gene expression profiles of GSE50161, GSE66354, GSE74195, and GSE86574 were analyzed to figure out the differentially expressed genes (DEGs) between tissue of EPN and normal brain samples. To harvest the enrichment functions, pathways and hub genes, the Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein-protein interaction (PPI) network analysis were made. Subsquently, survival analysis was performed in 325 patients to illuminate the connection between prognosis of EPN and expression levels of hub genes. RESULTS: Results: 20 functions and 10 pathways which were up- or downregulated between the EPN and normal samples were revealed applying GO and KEGG analysis. Mutual hub genes were TP53, TOP2A, CDK1, PCNA, and ACTA2. The pathways of Hedgehog and notch signaling, mismatch repair (MMR), and retrograde endocannabinoid were significantly abnormally regulated in EPN tissue. Survival analysis revealed favorable progression-free (PFS) and overall (OS) survival in EPN patients with low expression of TOP2A, CDK1, PCNA, and ACTA2 (P 0.05). CONCLUSION: Conclusion: Patients with lower expression of TOP2A, CDK1, PCNA, and ACTA2 had a longer OS and PFS. The differential expressed genes identified and the key pathways selected in this research provided unprecedented and promising targets for diagnosis and treatment of EPN patients.