Abstract
Transmembrane protein topology prediction methods play important roles in structural biology, because the structure determination of these types of proteins is extremely difficult by the common biophysical, biochemical and molecular biological methods. The need for accurate prediction methods is high, as the number of known membrane protein structures fall far behind the estimated number of these proteins in various genomes. The accuracy of these prediction methods appears to be higher than most prediction methods applied on globular proteins, however it decreases slightly with the increasing number of structures. Unfortunately, most prediction algorithms use common machine learning techniques, and they do not reveal why topologies are predicted with such a high success rate and which biophysical or biochemical properties are important to achieve this level of accuracy. Incorporating topology data determined so far into the prediction methods as constraints helps us to reach even higher prediction accuracy, therefore collection of such topology data is also an important issue.
Keywords: Transmembrane protein, topology prediction, machine learning algorithm, hidden Markov model, support vector machine, Helical, Lipid bilayers, PDBTM database, Protein Data Bank, INTEGRAL MEMBRANE PROTEINS, Proline kinks, bacteriorhodopsin, lutropin/ choriogo-nadotropin receptor, Transmembrane Folds, immuno-localization, molecular biology modifications of proteins, fusion proteins, Escherichia coli, Proteins with Ambiguous Orientation, Globular Proteins, Saccharomyces cerevisiae, SVMtop, Signal Peptide Predictions, Topography Predictions, Dense Alignment Surface (DAS), latent semantic analysis, higher order statistics, evidence-theoretic K-nearest neighbor prediction algorithm, Consensus prediction methods, Benchmark Sets, prediction accu-racies, SwissProt annotations, per segment, per protein, Reentrant Loop Predictions, Constrained Predictions, Genome Wide Topology Predictions
Current Protein & Peptide Science
Title: Topology Prediction of Helical Transmembrane Proteins: How Far Have We Reached?
Volume: 11 Issue: 7
Author(s): Gabor E. Tusnady and Istvan Simon
Affiliation:
Keywords: Transmembrane protein, topology prediction, machine learning algorithm, hidden Markov model, support vector machine, Helical, Lipid bilayers, PDBTM database, Protein Data Bank, INTEGRAL MEMBRANE PROTEINS, Proline kinks, bacteriorhodopsin, lutropin/ choriogo-nadotropin receptor, Transmembrane Folds, immuno-localization, molecular biology modifications of proteins, fusion proteins, Escherichia coli, Proteins with Ambiguous Orientation, Globular Proteins, Saccharomyces cerevisiae, SVMtop, Signal Peptide Predictions, Topography Predictions, Dense Alignment Surface (DAS), latent semantic analysis, higher order statistics, evidence-theoretic K-nearest neighbor prediction algorithm, Consensus prediction methods, Benchmark Sets, prediction accu-racies, SwissProt annotations, per segment, per protein, Reentrant Loop Predictions, Constrained Predictions, Genome Wide Topology Predictions
Abstract: Transmembrane protein topology prediction methods play important roles in structural biology, because the structure determination of these types of proteins is extremely difficult by the common biophysical, biochemical and molecular biological methods. The need for accurate prediction methods is high, as the number of known membrane protein structures fall far behind the estimated number of these proteins in various genomes. The accuracy of these prediction methods appears to be higher than most prediction methods applied on globular proteins, however it decreases slightly with the increasing number of structures. Unfortunately, most prediction algorithms use common machine learning techniques, and they do not reveal why topologies are predicted with such a high success rate and which biophysical or biochemical properties are important to achieve this level of accuracy. Incorporating topology data determined so far into the prediction methods as constraints helps us to reach even higher prediction accuracy, therefore collection of such topology data is also an important issue.
Export Options
About this article
Cite this article as:
E. Tusnady Gabor and Simon Istvan, Topology Prediction of Helical Transmembrane Proteins: How Far Have We Reached?, Current Protein & Peptide Science 2010; 11 (7) . https://dx.doi.org/10.2174/138920310794109184
DOI https://dx.doi.org/10.2174/138920310794109184 |
Print ISSN 1389-2037 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5550 |
Call for Papers in Thematic Issues
Advancements in Proteomic and Peptidomic Approaches in Cancer Immunotherapy: Unveiling the Immune Microenvironment
The scope of this thematic issue centers on the integration of proteomic and peptidomic technologies into the field of cancer immunotherapy, with a particular emphasis on exploring the tumor immune microenvironment. This issue aims to gather contributions that illustrate the application of these advanced methodologies in unveiling the complex interplay ...read more
Artificial Intelligence for Protein Research
Protein research, essential for understanding biological processes and creating therapeutics, faces challenges due to the intricate nature of protein structures and functions. Traditional methods are limited in exploring the vast protein sequence space efficiently. Artificial intelligence (AI) and machine learning (ML) offer promising solutions by improving predictions and speeding up ...read more
Nutrition and Metabolism in Musculoskeletal Diseases
The musculoskeletal system consists mainly of cartilage, bone, muscles, tendons, connective tissue and ligaments. Balanced metabolism is of vital importance for the homeostasis of the musculoskeletal system. A series of musculoskeletal diseases (for example, sarcopenia, osteoporosis) are resulted from the dysregulated metabolism of the musculoskeletal system. Furthermore, metabolic diseases (such ...read more
Protein Folding, Aggregation and Liquid-Liquid Phase Separation
Protein folding, misfolding and aggregation remain one of the main problems of interdisciplinary science not only because many questions are still open, but also because they are important from the point of view of practical application. Protein aggregation and formation of fibrillar structures, for example, is a hallmark of a ...read more
Related Journals
- 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
-
Meet Our Editorial Board Member
Current Alzheimer Research Insulin Resistance, Obesity and the Metabolic Syndrome. Is there a Therapeutic Role for Endothelin-1 Antagonists?
Current Vascular Pharmacology Non-Selective Inhibition of Cyclooxygenase Enzymes by Aminoacetylenic Isoindoline 1,3-Diones
Inflammation & Allergy - Drug Targets (Discontinued) Interleukin-15 in Gene Therapy of Cancer
Current Gene Therapy Relationship between Fatty Acid Habitual Intake and Early Inflammation Biomarkers in Individuals with and without Type 2 Diabetes in Mexico
Endocrine, Metabolic & Immune Disorders - Drug Targets Molecular, Cellular, and Epigenetic Signatures of Prostaglandin E2 in Endometriosis
Current Women`s Health Reviews Cordycepin and its Nucleoside Analogs for the Treatment of Systemic COVID-19 Infection
Coronaviruses Vascular Abnormalities in Essential Hypertension
Current Pharmaceutical Design Altering the Sphingosine-1-Phosphate/Ceramide Balance: A Promising Approach for Tumor Therapy
Current Pharmaceutical Design Cisplatin Is a DNA-Damaging Antitumour Compound Triggering Multifactorial Biochemical Responses in Cancer Cells: Importance of Apoptotic Pathways
Current Medicinal Chemistry - Anti-Cancer Agents Allograft-Induced Proliferation of Vascular Smooth Muscle Cells: Potential Targets for Treating Transplant Vasculopathy
Current Vascular Pharmacology B Cells Compartment in Centenarian Offspring and Old People
Current Pharmaceutical Design Anti-adhesion Molecules in IBD: Does Gut Selectivity Really Make the Difference?
Current Pharmaceutical Design Nanotechnological Advances in the Treatment of Epilepsy
CNS & Neurological Disorders - Drug Targets The Isoprostanes - Unique Products of Arachidonate Peroxidation: Their Role as Mediators of Oxidant Stress
Current Pharmaceutical Design Bacterial Conjunctivitis in Childhood: Etiology, Clinical Manifestations, Diagnosis, and Management
Recent Patents on Inflammation & Allergy Drug Discovery Possible Therapeutic Targets in Cardiac Myocyte Apoptosis
Current Pharmaceutical Design Computer Aided Drug Design Approaches to Develop Cyclooxygenase Based Novel Anti-Inflammatory and Anti-Cancer Drugs
Current Pharmaceutical Design Mitogen-Activated Protein Kinases: New Molecular Targets for Pharmacological Treatment of Inflammatory Lung Diseases
Current Medicinal Chemistry - Anti-Inflammatory & Anti-Allergy Agents Association of Growth Differentiation Factor 15 with Arterial Stiffness and Endothelial Function in Subpopulations of Patients with Coronary Artery Disease: A Proof-of-Concept Study
Recent Advances in Inflammation & Allergy Drug Discovery