Abstract
Protein-Protein-Interactions (PPIs) are involved in almost all the cellular processes and understanding the structural basis of PPIs remains an important endeavor. The identification of the interface residues may shed light in many important aspects like drug development, elucidation of molecular pathways, generation of protein mimetics and understanding of disease mechanisms as well as development of docking methodologies to build structural models of protein complexes. Over the past few years, advances in high-throughput PPI identification techniques, such as yeast two-hybrid analysis and affinity purification coupled with mass spectrometry, have enabled the researchers to identify sets of interacting proteins in yeast, Drosophila and other organisms. Unfortunately, these experimental methods do not provide residue level insight into the structure of the interactions between the proteins. The uses of X-Ray crystallography and nuclear magnetic resonance (NMR) spectroscopy to determine the structural basis of an interaction are time consuming and overall expensive. In response to these difficulties, a number of different bioinformatics algorithms with varying degrees of accuracies have been developed that use a wide variety of data sources to predict PPIs and modes of binding between proteins. Machine learning techniques such as Support Vector Machines (SVMs) and Random Forests (RFs) have been used recently to solve problems such as prediction of catalytic residues and prediction and analysis of structure-based PPI interfaces. Previous machine learning approaches to the PPI interface prediction problems used features pertaining to evolutionary amino acid sequence conservation, phylogeny, and GO (Gene Ontology) protein annotation and, in most of the cases, protein structures. Till date there are very few computational methods available that are based solely on protein sequences.
Keywords: Docking, NMR, Protein-protein interactions, RF, SVM, X-ray crystallography.
Graphical Abstract
Current Chemical Biology
Title:An Overview of Protein-Protein Interaction
Volume: 9 Issue: 1
Author(s): Ananya Ali and Angshuman Bagchi
Affiliation:
Keywords: Docking, NMR, Protein-protein interactions, RF, SVM, X-ray crystallography.
Abstract: Protein-Protein-Interactions (PPIs) are involved in almost all the cellular processes and understanding the structural basis of PPIs remains an important endeavor. The identification of the interface residues may shed light in many important aspects like drug development, elucidation of molecular pathways, generation of protein mimetics and understanding of disease mechanisms as well as development of docking methodologies to build structural models of protein complexes. Over the past few years, advances in high-throughput PPI identification techniques, such as yeast two-hybrid analysis and affinity purification coupled with mass spectrometry, have enabled the researchers to identify sets of interacting proteins in yeast, Drosophila and other organisms. Unfortunately, these experimental methods do not provide residue level insight into the structure of the interactions between the proteins. The uses of X-Ray crystallography and nuclear magnetic resonance (NMR) spectroscopy to determine the structural basis of an interaction are time consuming and overall expensive. In response to these difficulties, a number of different bioinformatics algorithms with varying degrees of accuracies have been developed that use a wide variety of data sources to predict PPIs and modes of binding between proteins. Machine learning techniques such as Support Vector Machines (SVMs) and Random Forests (RFs) have been used recently to solve problems such as prediction of catalytic residues and prediction and analysis of structure-based PPI interfaces. Previous machine learning approaches to the PPI interface prediction problems used features pertaining to evolutionary amino acid sequence conservation, phylogeny, and GO (Gene Ontology) protein annotation and, in most of the cases, protein structures. Till date there are very few computational methods available that are based solely on protein sequences.
Export Options
About this article
Cite this article as:
Ali Ananya and Bagchi Angshuman, An Overview of Protein-Protein Interaction, Current Chemical Biology 2015; 9 (1) . https://dx.doi.org/10.2174/221279680901151109161126
DOI https://dx.doi.org/10.2174/221279680901151109161126 |
Print ISSN 2212-7968 |
Publisher Name Bentham Science Publisher |
Online ISSN 1872-3136 |

- Author Guidelines
- Bentham Author Support Services (BASS)
- 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
- Announcements
Related Articles
-
Mediterranean Diet and Longevity
Current Nutrition & Food Science Pain and Inflammation
Current Medicinal Chemistry Can IL-33 and Endocan be New Markers for Retinopathy of Prematurity?
Combinatorial Chemistry & High Throughput Screening New Insights into the Roles of NAD+-Poly(ADP-ribose) Metabolism and Poly(ADP-ribose) Glycohydrolase
Current Protein & Peptide Science Intraocular Inflammation and Systemic Immune-Mediated Diseases
Current Immunology Reviews (Discontinued) New Drugs for Immune Targeting
Immunology, Endocrine & Metabolic Agents in Medicinal Chemistry (Discontinued) Metformin, A New Era for an Old Drug in the Treatment of Immune Mediated Disease?
Current Drug Targets The Development of Stem Cell-Based Treatment for Liver Failure
Current Stem Cell Research & Therapy Regio- and Stereoselective Ring Opening of Allylic Epoxides
Current Organic Synthesis A Flash on Cell Therapy Strategies in Clinical Trials against SARS-CoV-2
Coronaviruses Airway Smooth Muscle Phenotype and Function: Interactions with Current Asthma Therapies
Current Drug Targets Current Gene Expression Studies in Esophageal Carcinoma
Current Genomics Circulating Meteorin-like Levels in Patients with Type 2 Diabetes Mellitus: A Meta-Analysis
Current Pharmaceutical Design Indolinones as Promising Scaffold as Kinase Inhibitors: A Review
Mini-Reviews in Medicinal Chemistry The Role of Neopterin in Atherogenesis and Cardiovascular Risk Assessment
Current Medicinal Chemistry CRISPR/Cas9 Genome Editing Tool: A Promising Tool for Therapeutic Applications on Respiratory Diseases
Current Gene Therapy TNF and TNF Receptors in TRAPS
Current Medicinal Chemistry - Anti-Inflammatory & Anti-Allergy Agents Microparticles: From Biogenesis to Biomarkers and Diagnostic Tools in Cardiovascular Disease
Current Stem Cell Research & Therapy New Molecular Avenues in Parkinson ’ s Disease Therapy
Current Topics in Medicinal Chemistry The Hypothalamic-Neurohypophyseal System: Current and Future Treatment of Vasopressin and Oxytocyn Related Disorders
Recent Patents on Endocrine, Metabolic & Immune Drug Discovery (Discontinued)