Abstract
The goal of computational protein structure prediction is to provide three-dimensional (3D) structures with resolution comparable to experimental results. Comparative modeling, which predicts the 3D structure of a protein based on its sequence similarity to homologous structures, is the most accurate computational method for structure prediction. In the last two decades, significant progress has been made on comparative modeling methods. Using the large number of protein structures deposited in the Protein Data Bank (∼65,000), automatic prediction pipelines are generating a tremendous number of models (∼1.9 million) for sequences whose structures have not been experimentally determined. Accurate models are suitable for a wide range of applications, such as prediction of protein binding sites, prediction of the effect of protein mutations, and structure-guided virtual screening. In particular, comparative modeling has enabled structure-based drug design against protein targets with unknown structures. In this review, we describe the theoretical basis of comparative modeling, the available automatic methods and databases, and the algorithms to evaluate the accuracy of predicted structures. Finally, we discuss relevant applications in the prediction of important drug target proteins, focusing on the G protein-coupled receptor (GPCR) and protein kinase families.
Keywords: Protein structure prediction, comparative modeling, sequence alignment, homology, drug target, drug design, 3D structure, Protein Data Bank, G protein-coupled receptor, protein kinase families, Comparative Modeling Method
Combinatorial Chemistry & High Throughput Screening
Title: Comparative Modeling: The State of the Art and Protein Drug Target Structure Prediction
Volume: 14 Issue: 6
Author(s): Tianyun Liu, Grace W. Tang and Emidio Capriotti
Affiliation:
Keywords: Protein structure prediction, comparative modeling, sequence alignment, homology, drug target, drug design, 3D structure, Protein Data Bank, G protein-coupled receptor, protein kinase families, Comparative Modeling Method
Abstract: The goal of computational protein structure prediction is to provide three-dimensional (3D) structures with resolution comparable to experimental results. Comparative modeling, which predicts the 3D structure of a protein based on its sequence similarity to homologous structures, is the most accurate computational method for structure prediction. In the last two decades, significant progress has been made on comparative modeling methods. Using the large number of protein structures deposited in the Protein Data Bank (∼65,000), automatic prediction pipelines are generating a tremendous number of models (∼1.9 million) for sequences whose structures have not been experimentally determined. Accurate models are suitable for a wide range of applications, such as prediction of protein binding sites, prediction of the effect of protein mutations, and structure-guided virtual screening. In particular, comparative modeling has enabled structure-based drug design against protein targets with unknown structures. In this review, we describe the theoretical basis of comparative modeling, the available automatic methods and databases, and the algorithms to evaluate the accuracy of predicted structures. Finally, we discuss relevant applications in the prediction of important drug target proteins, focusing on the G protein-coupled receptor (GPCR) and protein kinase families.
Export Options
About this article
Cite this article as:
Liu Tianyun, W. Tang Grace and Capriotti Emidio, Comparative Modeling: The State of the Art and Protein Drug Target Structure Prediction, Combinatorial Chemistry & High Throughput Screening 2011; 14 (6) . https://dx.doi.org/10.2174/138620711795767811
DOI https://dx.doi.org/10.2174/138620711795767811 |
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
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
Integrating Network Pharmacology and Traditional Medicine: A New Perspective in Drug Mechanism Research
Network pharmacology is a network construction and network topology analysis strategy that combines pharmacology and pharmacodynamics. In recent years, network pharmacology has emerged as a powerful tool that can be integrated with pharmacology. Natural products commonly function in multicomponent, multitarget, and multipathway systems. Some examples encompass Ayurveda, traditional Chinese medicines ...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
-
Azo Reductase- Activated Colon- Targeting Prodrugs of Aminosalicylates for Inflammatory Bowel Disease: Preparation, Pharmacokinetic and Pharmacodynamic Profile
Inflammation & Allergy - Drug Targets (Discontinued) Synthesis and Antitumor Evaluation of Thiophene Analogs of Kigelinone
Letters in Organic Chemistry In vivo Cancer Imaging with Semiconductor Quantum Dots
Current Pharmaceutical Analysis An Updated Review of ISCOMSTM and ISCOMATRIXTM Vaccines
Current Pharmaceutical Design Antibodies Against Muscarinic Receptors in Breast Cancer: Agonizing Tumor Growth
Current Immunology Reviews (Discontinued) Tubulin Maytansine Site Binding Ligands and their Applications as MTAs and ADCs for Cancer Therapy
Current Medicinal Chemistry Helicase Domain Containing Proteins in Human Disorders
Current Genomics Cytochrome P450 and the Biological Clock in Mammals
Current Drug Metabolism Ceramide Transfer Protein and Cancer
Anti-Cancer Agents in Medicinal Chemistry Looking Beyond Inhibition of VEGF/mTOR: Emerging Targets for Renal Cell Carcinoma Drug Development
Current Clinical Pharmacology Teaching Pharmacogenetics in Low and Middle Income Countries (LMICs): An Empirical Study of the Lessons Learned
Current Pharmacogenomics and Personalized Medicine Dose and Sequence Dependent Synergism from the Combination of Oxaliplatin with Emetine and Patulin Against Colorectal Cancer
Anti-Cancer Agents in Medicinal Chemistry Recent Patents on Anti-Telomerase Cancer Therapy
Recent Patents on Anti-Cancer Drug Discovery Genomic and Cellular Pathology of Lung Cancer
Current Respiratory Medicine Reviews Patent Annotations
Recent Patents on Endocrine, Metabolic & Immune Drug Discovery Inhibiting the Interaction of cMET and IGF-1R with FAK Effectively Reduces Growth of Pancreatic Cancer Cells in vitro and in vivo
Anti-Cancer Agents in Medicinal Chemistry Recent efforts toward the development of peptide secondary structure mimetics at Molecumetics Ltd. for the discoveries of new drug candidates utilizing combinatorial chemistry with solid phase synthesis are described
Combinatorial Chemistry & High Throughput Screening Heptahelical Receptors for Lysolipids in Lymphocytes as Targets for Therapeutic Intervention
Drug Design Reviews - Online (Discontinued) Association of GRP78, HIF-1α and BAG3 Expression with the Severity of Chronic Lymphocytic Leukemia
Anti-Cancer Agents in Medicinal Chemistry Caffeic Acid Phenethyl Ester Restores Adipocyte Gene Profile Expression Following Lipopolysaccharide Treatment
Letters in Drug Design & Discovery