Abstract
The functional screening of compounds is an important topic in chemistry and biomedicine that can uncover the essential properties of compounds and provide information concerning their correct use. In this study, we investigated the bioactive compounds reported in Selleckchem, which were assigned to 22 pathways. A computational method was proposed to identify the pathways of the bioactive compounds. Unlike most existing methods that only consider compound structural information, the proposed method adopted both the structural and interaction information from the compounds. The total accuracy achieved by our method was 61.79% based on jackknife analysis of a dataset of 1,832 bioactive compounds. Its performance was quite good compared with that of other machine learning algorithms (with total accuracies less than 46%). Finally, some of the false positives obtained by the method were analyzed to investigate the likelihood of compounds being annotated to new pathways.
Keywords: Bioactive compound, chemical-chemical interaction, chemical structure similarity, SMILES.
Combinatorial Chemistry & High Throughput Screening
Title:Prediction of Bioactive Compound Pathways Using Chemical Interaction and Structural Information
Volume: 19 Issue: 2
Author(s): Shiwen Cheng, Changming Zhu, Chen Chu, Tao Huang, Xiangyin Kong and LiuCun Zhu
Affiliation:
Keywords: Bioactive compound, chemical-chemical interaction, chemical structure similarity, SMILES.
Abstract: The functional screening of compounds is an important topic in chemistry and biomedicine that can uncover the essential properties of compounds and provide information concerning their correct use. In this study, we investigated the bioactive compounds reported in Selleckchem, which were assigned to 22 pathways. A computational method was proposed to identify the pathways of the bioactive compounds. Unlike most existing methods that only consider compound structural information, the proposed method adopted both the structural and interaction information from the compounds. The total accuracy achieved by our method was 61.79% based on jackknife analysis of a dataset of 1,832 bioactive compounds. Its performance was quite good compared with that of other machine learning algorithms (with total accuracies less than 46%). Finally, some of the false positives obtained by the method were analyzed to investigate the likelihood of compounds being annotated to new pathways.
Export Options
About this article
Cite this article as:
Cheng Shiwen, Zhu Changming, Chu Chen, Huang Tao, Kong Xiangyin and Zhu LiuCun, Prediction of Bioactive Compound Pathways Using Chemical Interaction and Structural Information, Combinatorial Chemistry & High Throughput Screening 2016; 19 (2) . https://dx.doi.org/10.2174/1386207319666151110123611
DOI https://dx.doi.org/10.2174/1386207319666151110123611 |
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
-
Endogenous and Exogenous Ligands of Aryl Hydrocarbon Receptor: Current State of Art
Current Drug Metabolism Novel Pulmonary Delivery of Antiviral Drugs for Treating COVID-19 in Patients with Parkinson’s Disease
Current Drug Delivery Neuroimaging Features of Acquired Metabolic and Toxic Encephalopathies
Current Medical Imaging BK Channel Modulators: A Comprehensive Overview
Current Medicinal Chemistry Astrocytes and Gliotransmitters: New Players in the Treatment of Major Depression?
Current Drug Targets Cell and Gene Therapies for Refractory Epilepsy
Current Neuropharmacology Recent Progress in Gene Therapy for Parkinson’s Disease
Current Molecular Medicine The Many Roles of Chemokine Receptors in Neurodegenerative Disorders: Emerging New Therapeutical Strategies
Current Medicinal Chemistry QSAR Studies on Blood-Brain Barrier Permeation
Current Computer-Aided Drug Design Pharmacological Chaperones that Protect Tetrahydrobiopterin Dependent Aromatic Amino Acid Hydroxylases Through Different Mechanisms
Current Drug Targets Putative Mechanisms of Action and Clinical Use of Lithium in Children and Adolescents: A Critical Review
Current Neuropharmacology Pharmacophore Based 3D-QSAR Modeling and Molecular Docking of Leucettines as Potent Dyrk1A Inhibitors
Letters in Drug Design & Discovery Stem Cells for the Treatment of Neurological Disorders
CNS & Neurological Disorders - Drug Targets Kinases as Targets for Parkinson's Disease: From Genetics to Therapy
CNS & Neurological Disorders - Drug Targets Clinical Analysis Methods of Voice Disorders
Current Bioinformatics The Endocannabinoid System in Peripheral Lymphocytes as a Mirror of Neuroinflammatory Diseases
Current Pharmaceutical Design MicroRNAs in CAG Trinucleotide Repeat Expansion Disorders: an Integrated Review of the Literature
CNS & Neurological Disorders - Drug Targets Psychobiological Model of Personality: Guidelines for Pharmacotherapy of Personality Disorder
Current Psychopharmacology Phenothiazines as Anti-Multi-Drug Resistant Tubercular Agents
Infectious Disorders - Drug Targets Harnessing the Potential of Long Non-coding RNAs to Manage Metabolic Diseases
Current Pharmaceutical Design