scholarly journals Computational Identification of Stearic Acid as a Potential PDK1 Inhibitor and In Vitro Validation of Stearic Acid as Colon Cancer Therapeutic in Combination with 5-Fluorouracil

2021 ◽  
Vol 20 ◽  
pp. 117693512110659
Author(s):  
Jonathan Mitchel ◽  
Pratima Bajaj ◽  
Ketki Patil ◽  
Austin Gunnarson ◽  
Emilie Pourchet ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Drug Design ◽  
Stearic Acid ◽  
Mechanism Of Action ◽  
Colorectal Adenocarcinoma ◽  
Metabolic Reprogramming ◽  
Colorectal Cancers ◽  
Structure Based Drug Design ◽  
Computational Structure ◽  
Efficacious Treatment

Background: Colorectal cancer is the third largest cause of cancer-related mortality worldwide. Although current treatments with chemotherapeutics have allowed for management of colorectal cancer, additional novel treatments are essential. Intervening with the metabolic reprogramming observed in cancers called “Warburg Effect,” is one of the novel strategies considered to combat cancers. In the metabolic reprogramming pathway, pyruvate dehydrogenase kinase (PDK1) plays a pivotal role. Identification and characterization of a PDK1 inhibitor is of paramount importance. Further, for efficacious treatment of colorectal cancers, combinatorial regimens are essential. To this end, we opted to identify a PDK1 inhibitor using computational structure-based drug design FINDSITEcomb and perform combinatorial studies with 5-FU for efficacious treatment of colorectal cancers. Methods: Using computational structure-based drug design FINDSITEcomb, stearic acid (SA) was identified as a possible PDK1 inhibitor. Elucidation of the mechanism of action of SA was performed using flow cytometry, clonogenic assays. Results: When the growth inhibitory potential of SA was tested on colorectal adenocarcinoma (DLD-1) cells, a 50% inhibitory concentration (IC50) of 60 µM was recorded. Moreover, SA inhibited the proliferation potential of DLD-1 cells as shown by the clonogenic assay and there was a sustained response even after withdrawal of the compound. Elucidation of the mechanism of action revealed, that the inhibitory effect of SA was through the programmed cell death pathway. There was increase in the number of apoptotic and multicaspase positive cells. SA also impacted the levels of the cell survival protein Bcl-2. With the aim of achieving improved treatment for colorectal cancer, we opted to combine 5-fluorouracil (5-FU), the currently used drug in the clinic, with SA. Combining SA with 5-FU, revealed a synergistic effect in which the IC50 of 5-FU decreased from 25 to 6 µM upon combination with 60 µM SA. Further, SA did not inhibit non-tumorigenic NIH-3T3 proliferation. Conclusions: We envision that this significant decrease in the IC50 of 5-FU could translate into less side effects of 5-FU and increase the efficacy of the treatment due to the multifaceted action of SA. The data generated from the current studies on the inhibition of colorectal adenocarcinoma by SA discovered by the use of the computational program as well as synergistic action with 5-FU should open up novel therapeutic options for the management of colorectal adenocarcinomas.

scholarly journals G9a Is SETting the Stage for Colorectal Oncogenesis

Genes ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 616
Author(s):  
Christopher J. Bergin ◽  
Yannick D. Benoit
Keyword(s):  
Colorectal Cancer ◽  
Tumor Heterogeneity ◽  
Wnt Pathway ◽  
Target Gene ◽  
Colorectal Adenocarcinoma ◽  
Colorectal Cancers ◽  
Set Domain ◽  
Activating Mutations ◽  
Canonical Wnt Pathway ◽  
Canonical Wnt

Recently, Kato et al. reported recurrent activating mutations in the SET domain of histone methyltransferase G9a, driving an oncogenic cascade in melanoma. The authors also reported correlations between G9a expression and the regulation of the canonical WNT pathway. Although we could not observe such mutations in human colorectal adenocarcinoma, newly reported findings are of high relevance to colorectal cancer, as WNT target gene signatures were closely associated with G9a expression. Here, we put into perspective such new results on G9a expression in colorectal cancers and the potential relationship with tumor heterogeneity and acquisition of neoplastic stemness.

The structure of chitinases and prospects for structure-based drug design

1995 ◽  
Vol 73 (S1) ◽  
pp. 1142-1146 ◽  
Author(s):  
Jon D. Robertus ◽  
P. John Hart ◽  
Arthur F. Monzingo ◽  
Edward Marcotte ◽  
Thomas Hollis
Keyword(s):  
Drug Design ◽  
Small Molecules ◽  
Mechanism Of Action ◽  
Active Site ◽  
Antifungal Agents ◽  
Structure Based Drug Design ◽  
X Ray ◽  
Class Ii Chitinase ◽  
Transition State Geometry ◽  
Chitinase Inhibitors

Many fungi, including pathogenic strains, require proper chitin metabolism to assure normal cell wall replication. Chitinase hydrolyzes chitin; inhibition of endogenous chitinases or application of extracellular chitinases can disrupt fungal division. It is possible that chitinase inhibitors could be used as antifungal agents. We have solved the X-ray structure of a class II chitinase from barley and proposed a mechanism of action. The enzyme has a structural core similar to lysozyme and probably acts in a similar catalytic manner. The enzyme structure can, in principle, be used to identify small molecules that will bind avidly to the active site and act as inhibitors. Those inhibitors that embody transition state geometry are likely to be particularly effective. Key words: chitinase, mechanism of action, drug design.

Advances in Computational Structure-Based Drug Design and Application in Drug Discovery

2015 ◽  
Vol 16 (9) ◽  
pp. 901-916 ◽  
Author(s):  
Tao Wang ◽  
Mian-Bin Wu ◽  
Ri-Hao Zhang ◽  
Zheng-Jie Chen ◽  
Chen Hua ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Drug Design ◽  
Structure Based Drug Design ◽  
Computational Structure ◽  
Design And Application

scholarly journals Computational structure-based drug design: Predicting target flexibility

2018 ◽  
Vol 8 (5) ◽  
pp. e1367 ◽  
Author(s):  
Jelisa Iglesias ◽  
Suwipa Saen-oon ◽  
Robert Soliva ◽  
Victor Guallar
Keyword(s):  
Drug Design ◽  
Structure Based Drug Design ◽  
Computational Structure

Improving the Accuracy of Protein-Ligand Binding Affinity Prediction by Deep Learning Models: Benchmark and Model

2019 ◽  
Author(s):  
Mohammad Rezaei ◽  
Yanjun Li ◽  
Xiaolin Li ◽  
Chenglong Li
Keyword(s):  
Deep Learning ◽  
Drug Design ◽  
Binding Affinity ◽  
Benchmark Dataset ◽  
Rational Drug Design ◽  
Learning Models ◽  
Structure Based Drug Design ◽  
Binding Affinity Prediction ◽  
Affinity Prediction ◽  
Rational Drug

<b>Introduction:</b> The ability to discriminate among ligands binding to the same protein target in terms of their relative binding affinity lies at the heart of structure-based drug design. Any improvement in the accuracy and reliability of binding affinity prediction methods decreases the discrepancy between experimental and computational results.<br><b>Objectives:</b> The primary objectives were to find the most relevant features affecting binding affinity prediction, least use of manual feature engineering, and improving the reliability of binding affinity prediction using efficient deep learning models by tuning the model hyperparameters.<br><b>Methods:</b> The binding site of target proteins was represented as a grid box around their bound ligand. Both binary and distance-dependent occupancies were examined for how an atom affects its neighbor voxels in this grid. A combination of different features including ANOLEA, ligand elements, and Arpeggio atom types were used to represent the input. An efficient convolutional neural network (CNN) architecture, DeepAtom, was developed, trained and tested on the PDBbind v2016 dataset. Additionally an extended benchmark dataset was compiled to train and evaluate the models.<br><b>Results: </b>The best DeepAtom model showed an improved accuracy in the binding affinity prediction on PDBbind core subset (Pearson’s R=0.83) and is better than the recent state-of-the-art models in this field. In addition when the DeepAtom model was trained on our proposed benchmark dataset, it yields higher correlation compared to the baseline which confirms the value of our model.<br><b>Conclusions:</b> The promising results for the predicted binding affinities is expected to pave the way for embedding deep learning models in virtual screening and rational drug design fields.

Comparison of Co-Presence of Epstein-Barr Virus and High-Risk Human Papillomaviruses in Colorectal Cancers in the Middle East Region

2020 ◽  
Author(s):  
Karim Nagi ◽  
Ishita Gupta ◽  
Hamda A Al-Thawadi ◽  
Ayesha Jabeen ◽  
Mohammed I. Malk ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Epstein Barr Virus ◽  
Human Papillomaviruses ◽  
Colorectal Cancers ◽  
Barr Virus ◽  
Human Carcinomas ◽  
Epstein Barr ◽  
Invasive Carcinomas ◽  
High Risk Hpv

Background: Several studies have shown the presence of onco viral DNA in colorectal tumor tissues. Viral infection by onco-viruses such as Human papillomaviruses (HPVs) and Epstein–Barr virus (EBV) are well-known to be involved in the onset and/or progression of numerous human carcinomas. Methods: We explored the co-presence of high-risk HPVs and EBV in a cohort of colorectal cancer samples from Lebanon (94) and Syria (102) by PCR, immunohistochemistry and tissue microarray. Results: The results of the study point out that 54% of colorectal cancer cases in Syria are positive for high-risk HPVs, while 30% of the cases in Lebanon are positive for these viruses; the most frequent high-risk HPV types in these populations are 16, 18, 31, 33 and 35. Analysis of LMP1 showed similar results in both populations; 36% of Syrian and 31% of Lebanese samples. Additionally, we report that EBV and high-risk HPVs are co-present in these samples. In Syrian samples, EBV and HPVs are co-present in 16% of the population, however, in the Lebanese samples, 20% of the cases are positive for both EBV and HPVs; their co-presence is associated with high/intermediate grade invasive carcinomas. Conclusion: These data suggest that EBV and high-risk HPVs are co-present in human colorectal cancers where they can cooperate in the progression of these cancers. Nevertheless, further studies are needed to elucidate the role of those oncoviruses in the development of human colorectal carcinomas.

Sign in / Sign up

Export Citation Format

Share Document