Abstract
Survival of cells and maintenance of genome depend on detection and repair of damaged DNA through intricate mechanisms. Cancer treatment relies on chemotherapy or radiation therapy that kills neoplastic cells by causing immense damage to the DNA. In many cases, escalated DNA repair mechanism leads to resistance against these therapies and therefore, there is a need to expand the interest in developing drugs that can sensitize the cells to such therapies by interfering with the DNA repair mechanism. Several studies have suggested a link between over expression of the primary mammalian enzyme, Apurinic/Apyrimidinic Endonuclease (APE1), responsible for abasic (or AP) site removal in the DNA and resistance of these cells to cancer therapy, whereas APE1 down-regulation sensitizes the cells to DNA damaging agents. Thus, the current treatment efficacy can be improved by aiding to selective sensitization of cancer cells and protection of normal cells. In the present study, we have used machine learning based approach by selecting assorted compounds with known activity for APE1 and constructed a range of in silico predictive classification models to discriminate between the inhibitors and non-inhibitors. These models can be applied to numerous other unscreened compounds to select the ones which are more likely to be the inhibitors for APE1. We have further found the common molecular substructures which were associated with the molecular activity of the compounds using a substructure search approach.
Keywords: Cancer, APE1, resistance, inhibitors, antagonists, machine learning, cheminformatics, DNA repair.
Combinatorial Chemistry & High Throughput Screening
Title:Resisting the Resistance in Cancer: Cheminformatics Studies on Short- Path Base Excision Repair Pathway Antagonists Using Supervised Learning Approaches
Volume: 18 Issue: 9
Author(s): Ritu Jain, Salma Jamal, Sukriti Goyal, Divya Wahi, Aditi Singh and Abhinav Grover
Affiliation:
Keywords: Cancer, APE1, resistance, inhibitors, antagonists, machine learning, cheminformatics, DNA repair.
Abstract: Survival of cells and maintenance of genome depend on detection and repair of damaged DNA through intricate mechanisms. Cancer treatment relies on chemotherapy or radiation therapy that kills neoplastic cells by causing immense damage to the DNA. In many cases, escalated DNA repair mechanism leads to resistance against these therapies and therefore, there is a need to expand the interest in developing drugs that can sensitize the cells to such therapies by interfering with the DNA repair mechanism. Several studies have suggested a link between over expression of the primary mammalian enzyme, Apurinic/Apyrimidinic Endonuclease (APE1), responsible for abasic (or AP) site removal in the DNA and resistance of these cells to cancer therapy, whereas APE1 down-regulation sensitizes the cells to DNA damaging agents. Thus, the current treatment efficacy can be improved by aiding to selective sensitization of cancer cells and protection of normal cells. In the present study, we have used machine learning based approach by selecting assorted compounds with known activity for APE1 and constructed a range of in silico predictive classification models to discriminate between the inhibitors and non-inhibitors. These models can be applied to numerous other unscreened compounds to select the ones which are more likely to be the inhibitors for APE1. We have further found the common molecular substructures which were associated with the molecular activity of the compounds using a substructure search approach.
Export Options
About this article
Cite this article as:
Jain Ritu, Jamal Salma, Goyal Sukriti, Wahi Divya, Singh Aditi and Grover Abhinav, Resisting the Resistance in Cancer: Cheminformatics Studies on Short- Path Base Excision Repair Pathway Antagonists Using Supervised Learning Approaches, Combinatorial Chemistry & High Throughput Screening 2015; 18 (9) . https://dx.doi.org/10.2174/1386207318666150626093648
DOI https://dx.doi.org/10.2174/1386207318666150626093648 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
Call for Papers in Thematic Issues
Artificial Intelligence Methods for Biomedical, Biochemical and Bioinformatics Problems
Recently, a large number of technologies based on artificial intelligence have been developed and applied to solve a diverse range of problems in the areas of biomedical, biochemical and bioinformatics problems. By utilizing powerful computing resources and massive amounts of data, methods based on artificial intelligence can significantly improve the ...read more
Eco-friendly Agents for Biological Control of Pathogenic Diseases
The discovery of an alternative biological approach to disease management includes work on medicinal products derived from natural sources as a starting point for the development of eco-friendly agents for these diseases and the injuries they cause, as well as reducing human contact with hazardous chemicals and their residues. We ...read more
Emerging trends in diseases mechanisms, noble drug targets and therapeutic strategies: focus on immunological and inflammatory disorders
Recently infectious and inflammatory diseases have been a key concern worldwide due to tremendous morbidity and mortality world Wide. Recent, nCOVID-9 pandemic is a good example for the emerging infectious disease outbreak. The world is facing many emerging and re-emerging diseases out breaks at present however, there is huge lack ...read more
Exploring Spectral Graph Theory in Combinatorial Chemistry
Scope of the Thematic Issue: Combinatorial chemistry involves the synthesis and analysis of a large number of diverse compounds simultaneously. Traditional methods rely on brute force experimentation, which can be time-consuming and resource-intensive. Spectral Graph Theory, a branch of mathematics dealing with the properties of graphs in relation to the ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
New Player on An Old Field; the Keap1/Nrf2 Pathway as a Target for Treatment of Type 2 Diabetes and Metabolic Syndrome
Current Diabetes Reviews The Shape of the Messenger: Using Protein Structure Information to Design Novel Cytokine-based Therapeutics
Current Pharmaceutical Design Pentacyclic Triterpenoids and Their Saponins with Apoptosis-Inducing Activity
Current Topics in Medicinal Chemistry Interleukin-15 in Gene Therapy of Cancer
Current Gene Therapy Dendritic Cell Immunotherapy for Melanoma
Reviews on Recent Clinical Trials Advanced Assessment of the Endogenous Hormone Level as a Potential Biomarker of the Urogenital Tract Cancer
Combinatorial Chemistry & High Throughput Screening New Platinum and Ruthenium Complexes - the Latest Class of Potential Chemotherapeutic Drugs - a Review of Recent Developments in the Field
Mini-Reviews in Medicinal Chemistry Phytochemicals in Anticancer Drug Development
Anti-Cancer Agents in Medicinal Chemistry Carbonic Anhydrase IX as a Target for Designing Novel Anticancer Drugs
Current Medicinal Chemistry Cytochrome P450 Drug Metabolizing Enzymes in Roma Population Samples: Systematic Review of the Literature
Current Medicinal Chemistry Ceramidases in Hematological Malignancies: Senseless or Neglected Target?
Anti-Cancer Agents in Medicinal Chemistry Use of Metallomics in Environmental Pollution Assessment Using Mice Mus musculus/Mus spretus as Bioindicators
Current Analytical Chemistry New Approaches to Photodynamic Therapy from Types I, II and III to Type IV Using One or More Photons
Anti-Cancer Agents in Medicinal Chemistry Current and Emerging Strategies in Bladder Cancer
Anti-Cancer Agents in Medicinal Chemistry Nano-Tetrandrine Efficiently Inhibits the Proliferation and Induces the Apoptosis of Hep2 Cells through a Mitochondrial Signaling Pathway
Current Signal Transduction Therapy DNA Methylation and Bladder Cancer: Where Genotype does not Predict Phenotype
Current Genomics Application of the Shortest Path Algorithm for the Discovery of Breast Cancer-Related Genes
Current Bioinformatics Genetic and Epigenetic Studies for Determining Molecular Targets of Natural Product Anticancer Agents
Current Cancer Drug Targets The Pharmacogenomics “Side-effect” of TP53/EGFR in Non-small Cell Lung Cancer Accompanied with Atorvastatin Therapy: A Functional Network Analysis
Anti-Cancer Agents in Medicinal Chemistry The Centrosome: A Target for Cancer Therapy
Current Cancer Drug Targets