Assessment of epigenetic alterations and in silico analysis of mutation affecting
            PTEN
            expression among Indian cervical cancer patients

Background: Ce rvical cancer is the second leading cause of cancer in women, which necessitates safe and potential therapeutic agents. Objective: This study was designed to investigate the antiproliferative effect of ethanolic extract of Cissus quadrangularis L. (CQ) against human cervical adenocarcinoma HeLa cell line and in silico analysis of selected active agents against apoptosis executioner enzyme caspase-3. Methods: Cell viability was analyzed in HeLa cells at different concentrations (25-300 μg/ml) of CQ extract. Reactive oxygen species (ROS) generation, cellular apoptosis, cell cycle analysis and caspases-3 activation were evaluated. In silico structure-based virtual screening analysis was carried out using AutoDock Vina and iGEMDOCK. Results: Cell viability of HeLa cells was reduced significantly (p ˂ 0.05) in a dose-dependent manner, however, CQ extract showed non-toxic to normal kidney epithelial NRK-52E cells. CQ extract induced the intracellular ROS level, nuclear condensation and reduced the mitochondrial membrane potential (MMP) with the induction of annexin V-FITC positive cells. CQ extract arrested cells in G0/G1 and G2/M checkpoints and activated caspase-3 activity significantly in HeLa cells. The molecular docking study showed a strong binding affinity of CQ phytocomponents against the caspase-3 (PDB ID: 1GFW) protein of human apoptosis. PASS analyses of selected active components using Lipinski’s Rule of five showed promising results. Further, drug-likeness and toxicity assessment using OSIRIS Data Warrior V5.2.1 software exhibited the feasibility of phytocomponents as drug candidates with no predicted toxicity. Conclusion: This study suggested that active constituents in CQ extract can be considered as potential chemotherapeutic candidates in the management of cervical cancer.

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Identification of HPV16 in suspected cases of cervical lesions and docking Study of its L1 protein with some natural inhibitors.

10.21203/rs.2.23387/v1 ◽

2020 ◽

Author(s):

Yusuf Lukman ◽

Doro Aliyu Bala ◽

Kabir Imam Malik ◽

Abdulkadir Saidu ◽

Abdulhadi Sale Kumurya ◽

...

Keyword(s):

Cervical Cancer ◽

High Risk ◽

Prevalence Rate ◽

In Silico ◽

In Silico Analysis ◽

Low Grade ◽

Cervical Lesions ◽

Hpv 16 ◽

L1 Protein ◽

Silico Analysis

Abstract Background The Human papillomavirus (HPV) causes sexually transmitted diseases. Among several types of HPV variants, HPV 16 is listed as a high-risk group, the primary cervical cancer etiologic agent, which causes life-threatening disease among women worldwide. The presence of L1, E6 and E7 encoded oncoproteins are largely responsible for virulence and pathogenicity that leads to cervical lesions. This menace is required to be curbed by designing an anti-cancerous drugs. The protein receptor-inhibitor interaction adopted using in silico analysis is very important in drug designing. It was the objective of this study to identify HPV16 isolates from suspected cases of cervical cancer at SH Sokoto and SYMH Birnin Kebbi hospitals and also to identify potent HPV16’s L1 protein inhibitor using in silico analysis of Echinacoside, curcumin and Cichoric acid against the viral protein. Methods A total of 140 cervical smear samples consisting of 21 low grade squamous intraepithelial lesion, 6 high grade lesion and 117 negative pap smears were collected. The samples were subjected for molecular detection using PCR targeting E6 and L1 genes of the virus. Positive samples were sequenced using Sanger sequencing platform. All the sequencing data were analysed using bioedit software while data generated for the molecular prevalence was statistically analyzed using Chi-square. A comprehensive HPV L1 protein homology model was designed to predict the L1 protein interaction mechanism with natural inhibitory molecules using a structural drug design approach. AutoDock Vina was used to carry out the molecular docking. Results Out of the 140 samples, 24 samples were positive for the PCR representing 16.7% molecular prevalence rate. There is statistically significant association between cyto-diagnoses and presence of HPV16 ( P ˂0.05). The highest prevalence rate of 12(50% of positive sample) was recorded among women between 30-39 years old. Docking analysis showed that the Chicoric acid components of Echinacea purpurae have strong binding affinity to the L1 protein of the HPV. Conclusion This study provides data on HPV 16 epidemiology in northern Nigeria, High-risk type 16 HPV variant was identified and also provides novel evidence for consideration on certain interacting residues, when synthesizing Anti-HPV compounds in the wet lab.

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In silico analysis identifies neuropilin-1 as a potential therapeutic target for SARS-Cov-2 infected lung cancer patients

Aging ◽

10.18632/aging.203159 ◽

2021 ◽

Author(s):

Song Hu ◽

Zheyu Hu ◽

Jiajia Qin ◽

Chuwen Lin ◽

Xuan Jiang

Keyword(s):

Lung Cancer ◽

Cancer Patients ◽

Therapeutic Target ◽

In Silico ◽

In Silico Analysis ◽

Potential Therapeutic Target ◽

Lung Cancer Patients ◽

Neuropilin 1 ◽

Silico Analysis

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TP73 G4C14-A4T14 polymorphism and cancer susceptibility: evidence from 36 case–control studies

Bioscience Reports ◽

10.1042/bsr20181452 ◽

2018 ◽

Vol 38 (6) ◽

Cited By ~ 4

Author(s):

Jialin Meng ◽

Shuo Wang ◽

Meng Zhang ◽

Song Fan ◽

Li Zhang ◽

...

Keyword(s):

Colorectal Cancer ◽

Cervical Cancer ◽

In Silico ◽

Cancer Susceptibility ◽

Meta Analysis ◽

In Silico Analysis ◽

Case Control ◽

Genetic Models ◽

Case Control Studies ◽

Silico Analysis

G4C14-A4T14 polymorphism of TP73 gene has been reported with a potential association in cancer risks through affected cell homeostasis; however the results were not consistent. We performed a comprehensive meta-analysis to explore the associations between G4C14-A4T14 polymorphism and cancer susceptibility. Extensive retrieve was performed in PubMed, EMBASE, Google Scholar, Web of Science, Wanfang database and CNKI database up to May 20, 2018. Odds ratios (ORs) and 95% confidence intervals (CIs) were conducted to evaluate the overall strength of the associations in five genetic models, as well as in subgroup analyses. Q-test, false-positive report probability analysis and trial sequential analysis, Egger’s test and Begg’s funnel plot were applied to evaluate the robustness of the results. In silico analysis was managed to demonstrate the relationship of TP73 expression correlated with cancer tissues. Finally, 36 case–control studies with a total of 9493 cancer cases and 13,157 healthy controls were enrolled into the meta-analysis. The pooled results present a significantly higher risk of G4C14-A4T14 polymorphism in all the five genetic models, as well as in the subgroups of Caucasian, cervical cancer, colorectal cancer, H-B subgroup and comfort to Hardy–Weinberg equilibrium subgroup. In silico analysis revealed that the expression of TP73 in cervical cancer tissue is higher than it in corresponding normal tissue, as well as in cervical cancer. All in all, TP73 G4C14-A4T14 polymorphism causes an upgrade cancer risk, especially in Caucasian population. G4C14-A4T14 polymorphism might be a potential biomarker for judging the tumorigenesis of cervical cancer and colorectal cancer.

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A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

Seminars in Oncology ◽

10.1053/j.seminoncol.2020.02.012 ◽

2020 ◽

Vol 47 (6) ◽

pp. 398-408

Author(s):

Sonam Tulsyan ◽

Showket Hussain ◽

Balraj Mittal ◽

Sundeep Singh Saluja ◽

Pranay Tanwar ◽

...

Keyword(s):

Systematic Review ◽

Gallbladder Carcinoma ◽

In Silico ◽

In Silico Analysis ◽

Transcriptomic Profile ◽

Silico Analysis

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In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

10.1055/s-0039-1680245 ◽

2019 ◽

Author(s):

I. Farah ◽

A. El-Mubark ◽

M. Osman ◽

A. Soliman ◽

F. Ali ◽

...

Keyword(s):

Single Nucleotide Polymorphism ◽

In Silico ◽

In Silico Analysis ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Prothrombin Gene ◽

Silico Analysis

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Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

Current Medicinal Chemistry ◽

10.2174/0929867327666200727114410 ◽

2020 ◽

Vol 27 (38) ◽

pp. 6523-6535 ◽

Cited By ~ 3

Author(s):

Antreas Afantitis ◽

Andreas Tsoumanis ◽

Georgia Melagraki

Keyword(s):

Data Analysis ◽

Virtual Screening ◽

In Silico ◽

Model Development ◽

In Silico Analysis ◽

Material Design ◽

Efficient Solutions ◽

Biological Data ◽

Cost Efficient ◽

Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

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