scholarly journals Bioinformatics and in-silico findings reveal medical features and pharmacological targets of biochanin A against colorectal cancer and COVID-19

Bioengineered ◽  
2021 ◽  
Author(s):  
Jingru Qin ◽  
Chao Guo ◽  
Lu Yang ◽  
Xiao Liang ◽  
Aijun Jiao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
In Silico ◽  
Biochanin A ◽  
Pharmacological Targets

Free Fatty Acid Receptors as New Potential Targets in Colorectal Cancer

2020 ◽  
Vol 21 (14) ◽  
pp. 1397-1404
Author(s):  
Adrian Bartoszek ◽  
Jakub Fichna ◽  
Aleksandra Tarasiuk ◽  
Agata Binienda ◽  
Adam Fabisiak ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Fatty Acid ◽  
Free Fatty Acid ◽  
Current Knowledge ◽  
Developed Countries ◽  
Future Directions ◽  
Screening Programs ◽  
Pharmacological Targets ◽  
The Family ◽  
Free Fatty Acid Receptors

Colorectal cancer (CRC) is one of the most common cancers worldwide. In developed countries, its mortality remains high, yet the prevalence has established owing to effective screening programs; however due to the westernization of lifestyle, the incidences in many other countries have increased. Although the treatment of CRC has improved in the last few years, the side effects of these approaches cannot be neglected. Recently, members of the family of free fatty acid receptors (FFARs) have become attractive pharmacological targets in many diseases, including asthma; studies also point to their role in carcinogenesis. Here, we discuss current knowledge and future directions in FFAR research related to CRC. Contradictory results of FFARs modulation may derive from the pleiotropic effects of FFAR ligands, receptor distribution and different signal transduction. Hence, we indicate directions of further studies to fully use the potential of FFARs in CRC.

scholarly journals Methylation Status of Corticotropin-Releasing Factor (CRF) Receptor Genes in Colorectal Cancer

2021 ◽  
Vol 10 (12) ◽  
pp. 2680
Author(s):  
Maria Panagopoulou ◽  
Antonia Cheretaki ◽  
Makrina Karaglani ◽  
Ioanna Balgkouranidou ◽  
Eirini Biziota ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
In Silico ◽  
Methylation Status ◽  
Prognostic Significance ◽  
In Silico Analysis ◽  
Clinicopathological Characteristics ◽  
Corticotropin Releasing Factor ◽  
Altered Expression ◽  
High Performing ◽  
Methylation Patterns

The corticotropin-releasing factor (CRF) system has been strongly associated with gastrointestinal pathophysiology, including colorectal cancer (CRC). We previously showed that altered expression of CRF receptors (CRFRs) in the colon critically affects CRC progression and aggressiveness through regulation of colonic inflammation. Here, we aimed to assess the potential of CRFR methylation levels as putative biomarkers in CRC. In silico methylation analysis of CRF receptor 1 (CRFR1) and CRF receptor 2 (CRFR2) was performed using methylome data derived by CRC and Crohn’s disease (CD) tissues and CRC-derived circulating cell-free DNAs (ccfDNAs). In total, 32 and 33 differentially methylated sites of CpGs (DMCs) emerged in CRFR1 and CRFR2, respectively, between healthy and diseased tissues. The methylation patterns were verified in patient-derived ccfDNA samples by qMSP and associated with clinicopathological characteristics. An automated machine learning (AutoML) technology was applied to ccfDNA samples for classification analysis. In silico analysis revealed increased methylation of both CRFRs in CRC tissue and ccfDNA-derived datasets. CRFR1 hypermethylation was also noticed in gene body DMCs of CD patients. CRFR1 hypermethylation was further validated in CRC adjuvant-derived ccfDNA samples, whereas CRFR1 hypomethylation, observed in metastasis-derived ccfDNAs, was correlated to disease aggressiveness and adverse prognostic characteristics. AutoML analysis based on CRFRs methylation status revealed a three-feature high-performing biosignature for CRC diagnosis with an estimated AUC of 0.929. Monitoring of CRFRs methylation-based signature in CRC tissues and ccfDNAs may be of high diagnostic and prognostic significance in CRC.

Serum Micrornas can Detect Colorectal Cancer; two Validation Study after In-Silico Analysis

2017 ◽  
Vol 152 (5) ◽  
pp. S1018
Author(s):  
Hiroyuki Takamaru ◽  
Yutaka Saito ◽  
Taku Sakamoto ◽  
Seiichiro Abe ◽  
Masayoshi Yamada ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Validation Study ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis ◽  
Serum Micrornas

In silico insights on tankyrase protein: A potential target for colorectal cancer

2018 ◽  
Vol 37 (14) ◽  
pp. 3637-3648 ◽  
Author(s):  
Lakshmanan Loganathan ◽  
Karthikeyan Muthusamy ◽  
John Marshal Jayaraj ◽  
Afrinrilwana Kajamaideen ◽  
Josephine Julia Balthasar
Keyword(s):  
Colorectal Cancer ◽  
In Silico ◽  
Protein A ◽  
Potential Target

scholarly journals Betatrophin/Lipasin/C19orf80: In Silico Approach for Protein-Based Biomaterial Marker in Metabolic Syndrome and Colorectal Cancer Through Computational-Based Study

2019 ◽  
Vol 515 ◽  
pp. 012094
Author(s):  
Hendra Susanto ◽  
Dwi Listyorini ◽  
Ahmad Taufiq ◽  
Viol Dhea Kharisma ◽  
Adeodatus Yuda Handaya ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Metabolic Syndrome ◽  
In Silico

Identification of MicroRNAs as Biomarkers in Colorectal Cancer Diagnostics: An In silico approach

2020 ◽  
Vol 34 (S1) ◽  
pp. 1-1 ◽  
Author(s):  
Adewale Oluwaseun Fadaka ◽  
Ashley Pretorius ◽  
Ashwil Klein
Keyword(s):  
Colorectal Cancer ◽  
In Silico ◽  
Cancer Diagnostics

scholarly journals THE POTENTIAL OF ROBUSTA COFFEE (COFFEA CANEPHORA) AS A COLORECTAL CANCER THERAPY MODALITY: AN IN SILICO STUDY

2021 ◽  
pp. 83-87
Author(s):  
DESSY AGUSTINI ◽  
LEO VERNADESLY ◽  
DELVIANA ◽  
THEODORUS
Keyword(s):  
Colorectal Cancer ◽  
In Silico ◽  
Hydrophobic Interactions ◽  
Binding Energies ◽  
In Vivo Studies ◽  
Discovery Studio ◽  
Robusta Coffee ◽  
In Silico Study

Objectives: This research aims to determine the efficacy of compounds in robusta coffee against colorectal cancer through the inhibition of the T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) receptor. Methods: This in silico study has been conducted in computing platform from June to August 2021. The selected test compounds would go through the Lipinski rule screening through the SwissADME website and the compounds that met these regulations would be docked to the TIGIT protein using AutoDock Tools and AutoDock Vina. The interactions with the highest binding energies were visualized using BIOVIA Discovery Studio 2020. The test compounds then underwent a toxicity profile analysis on the admetSAR 2.0 website. Results: All test compounds complied with the Lipinski rule. The molecular docking results showed the highest binding energy in kahweol and cafestol (−8.1 kcal/mol) compared to OMC (−7.9 kcal/mol), chlorogenic acid (−7.8 kcal/mol), caffeic acid (−6.3 kcal/mol), caffeine (−6.1 kcal/mol), trigonelline (−5.3 kcal/mol), HMF (−5.1 kcal/mol), furfuryl alcohol (−4.4 kcal/mol), and 5-fluorouracil as the comparator drug (−5.3 kcal/mol). Kahweol, cafestol, and 5-fluorouracil revealed the hydrophobic interactions and hydrogen bonds with amino acid residues in TIGIT. Kahweol and cafestol unveiled minimal toxicity prediction Conclusion: Kahweol and cafestol demonstrated the best results in inhibiting the TIGIT protein which played a role in colorectal cancer. In vitro and in vivo studies are needed to strengthen the findings of this research.

scholarly journals Andean Berry (Vaccinium meridionale Swartz) Juice in Combination With Aspirin Modulated Apoptotic Signaling in Colon Cancer In Vitro and In Vivo

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 261-261
Author(s):  
Sandra Arango-Varela ◽  
Ivan Luzardo ◽  
Maria Maldonado-Celis
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
In Silico ◽  
Aberrant Crypt Foci ◽  
Apoptotic Signaling ◽  
Polyphenolic Composition ◽  
Apoptotic Effects ◽  
The Impact

Abstract Objectives This research aimed to assess the impact of Andean Berry (Vaccinium meridionale Swartz) juice (ABJ) in combination with Aspirin in the apoptotic signaling in colon cancer in vitro and in vivo. We hypothesized that ABJ + Aspirin would produce the most effective anti-proliferative and pro-apoptotic effects in vitro and in vivo. Methods The polyphenolic composition of ABJ was carried out by HPLC-DAD. ABJ (0–30% v/v), Aspirin (0–20 mM), and their mixture were evaluated for their pro-apoptotic effects in human SW480 colorectal cancer cells, followed by human apoptosis proteomic and bioinformatic analysis and in silico docking potential between ABJ components and selected pro-apoptotic targets. For the in vivo assays, colorectal cancer was induced with two injections (separated 1 week each) of azoxymethane (AOM: 15 mg/kg body weight, BW), and treatments were evaluated for its chemopreventive and chemoprotective effects. Hence, 30 male and female Balb/c mice were randomly divided in 5 groups: negative control (basal diet, BD); and four AOM-induced groups: positive control (BD), Aspirin (25 mg/kg BW + BD), ABJ (30% v/v in drinking water ABJ + BD), and ABJ + Aspirin (30% v/v ABJ + 25 mg/kg BW Aspirin + BD). Macroscopic and histopathological parameters were evaluated in vivo. Results The mixture displayed the highest antiproliferative effects (+46%), arrested cell cycle at the G2/M phase, decreased cloning efficiency, but reduced Caspase 3/7 activity, suggesting an alternative apoptotic pathway, compared to untreated SW480 cells. Several pro-apoptotic (cytochrome C, TNFRSF1A, Bax, and Bad) and anti-apoptotic (Hsp70/Hsp32) proteins were decreased. ABJ flavonoids (rutin and kaempferol) exhibited the highest in silico affinity with proteins like TRAILR2 or Catalase. Both chemopreventive and chemoprotective approaches showed similar body/liver weight outcomes, but the mixture displayed the strongest aberrant crypt foci reduction in vivo. The chemopreventive approach was more effective in protecting the colon from AOM. Conclusions Results suggested the potential of ABJ to reduce Aspirin use in the alleviation of colorectal cancer markers in vitro and in vivo, modulating alternate pro-apoptotic signaling. Funding Sources The funding provided by COLCIENCIAS and DGAPA-CTIC-UNAM is appreciated.

scholarly journals Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction

2020 ◽  
Vol 21 (19) ◽  
pp. 7102
Author(s):  
Fabian Mayr ◽  
Gabriele Möller ◽  
Ulrike Garscha ◽  
Jana Fischer ◽  
Patricia Rodríguez Castaño ◽  
...  
Keyword(s):  
Natural Products ◽  
In Silico ◽  
Large Scale ◽  
Target Prediction ◽  
Innovative Drug ◽  
Protein Targets ◽  
Modern Computer ◽  
Cyclooxygenase 1 ◽  
Pharmacological Targets ◽  
Drug Leads

Natural products comprise a rich reservoir for innovative drug leads and are a constant source of bioactive compounds. To find pharmacological targets for new or already known natural products using modern computer-aided methods is a current endeavor in drug discovery. Nature’s treasures, however, could be used more effectively. Yet, reliable pipelines for the large-scale target prediction of natural products are still rare. We developed an in silico workflow consisting of four independent, stand-alone target prediction tools and evaluated its performance on dihydrochalcones (DHCs)—a well-known class of natural products. Thereby, we revealed four previously unreported protein targets for DHCs, namely 5-lipoxygenase, cyclooxygenase-1, 17β-hydroxysteroid dehydrogenase 3, and aldo-keto reductase 1C3. Moreover, we provide a thorough strategy on how to perform computational target predictions and guidance on using the respective tools.

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