Abstract
The study of protein-protein interactions (PPIs) has been growing for some years now, mainly as a result of easy access to high-throughput experimental data. Several computational approaches have been presented throughout the years as means to infer PPIs not only within the same species, but also between different species (e.g., host-pathogen interactions). The importance of unveiling the human protein interaction network is undeniable, particularly in the biological, biomedical and pharmacological research areas. Even though protein interaction networks evolve over time and can suffer spontaneous alterations, occasional shifts are often associated with disease conditions. These disorders may be caused by external pathogens, such as bacteria and viruses, or by intrinsic factors, such as auto-immune disorders and neurological impairment. Therefore, having the knowledge of how proteins interact with each other will provide a great opportunity to understand pathogenesis mechanisms, and subsequently support the development of drugs focused on very specific disease pathways and re-targeting already commercialized drugs to new gene products. Computational methods for PPI prediction have been highlighted as an interesting option for interactome mapping. In this paper we review the techniques and strategies used for both experimental identification and computational inference of PPIs. We will then discuss how this knowledge can be used to create protein interaction networks (PINs) and the various methodologies applied to characterize and predict the so-called “disease genes” and “disease networks”. This will be followed by an overview of the strategies employed to predict drug targets.
Keywords: Protein-Protein interaction, Disease networks, Drug targets, Drug design.
Current Topics in Medicinal Chemistry
Title:From Protein-Protein Interactions to Rational Drug Design: Are Computational Methods Up to the Challenge?
Volume: 13 Issue: 5
Author(s): Edgar D. Coelho, Joel P. Arrais and Jose Luis Oliveira
Affiliation:
Keywords: Protein-Protein interaction, Disease networks, Drug targets, Drug design.
Abstract: The study of protein-protein interactions (PPIs) has been growing for some years now, mainly as a result of easy access to high-throughput experimental data. Several computational approaches have been presented throughout the years as means to infer PPIs not only within the same species, but also between different species (e.g., host-pathogen interactions). The importance of unveiling the human protein interaction network is undeniable, particularly in the biological, biomedical and pharmacological research areas. Even though protein interaction networks evolve over time and can suffer spontaneous alterations, occasional shifts are often associated with disease conditions. These disorders may be caused by external pathogens, such as bacteria and viruses, or by intrinsic factors, such as auto-immune disorders and neurological impairment. Therefore, having the knowledge of how proteins interact with each other will provide a great opportunity to understand pathogenesis mechanisms, and subsequently support the development of drugs focused on very specific disease pathways and re-targeting already commercialized drugs to new gene products. Computational methods for PPI prediction have been highlighted as an interesting option for interactome mapping. In this paper we review the techniques and strategies used for both experimental identification and computational inference of PPIs. We will then discuss how this knowledge can be used to create protein interaction networks (PINs) and the various methodologies applied to characterize and predict the so-called “disease genes” and “disease networks”. This will be followed by an overview of the strategies employed to predict drug targets.
Export Options
About this article
Cite this article as:
D. Coelho Edgar, P. Arrais Joel and Luis Oliveira Jose, From Protein-Protein Interactions to Rational Drug Design: Are Computational Methods Up to the Challenge?, Current Topics in Medicinal Chemistry 2013; 13 (5) . https://dx.doi.org/10.2174/1568026611313050005
DOI https://dx.doi.org/10.2174/1568026611313050005 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |
Call for Papers in Thematic Issues
AlphaFold in Medicinal Chemistry: Opportunities and Challenges
AlphaFold, a groundbreaking AI tool for protein structure prediction, is revolutionizing drug discovery. Its near-atomic accuracy unlocks new avenues for designing targeted drugs and performing efficient virtual screening. However, AlphaFold's static predictions lack the dynamic nature of proteins, crucial for understanding drug action. This is especially true for multi-domain proteins, ...read more
Artificial intelligence for Natural Products Discovery and Development
Our approach involves using computational methods to predict the potential therapeutic benefits of natural products by considering factors such as drug structure, targets, and interactions. We also employ multitarget analysis to understand the role of drug targets in disease pathways. We advocate for the use of artificial intelligence in predicting ...read more
Chemistry Based on Natural Products for Therapeutic Purposes
The development of new pharmaceuticals for a wide range of medical conditions has long relied on the identification of promising natural products (NPs). There are over sixty percent of cancer, infectious illness, and CNS disease medications that include an NP pharmacophore, according to the Food and Drug Administration. Since NP ...read more
Current Trends in Drug Discovery Based on Artificial Intelligence and Computer-Aided Drug Design
Drug development discovery has faced several challenges over the years. In fact, the evolution of classical approaches to modern methods using computational methods, or Computer-Aided Drug Design (CADD), has shown promising and essential results in any drug discovery campaign. Among these methods, molecular docking is one of the most notable ...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
- Announcements
Related Articles
-
Phosphodiesterase 3 (PDE3): Structure, Localization and Function
Cardiovascular & Hematological Agents in Medicinal Chemistry Estrogen-Induced Genetic Alterations and Their Role in Carcinogenicity
Current Genomics Potential and Cytotoxicity of cis-Platinum Complex with Anti-tumor Activity in Combination Therapy
Recent Patents on Anti-Cancer Drug Discovery MicroRNA Key to Angiogenesis Regulation: MiRNA Biology and Therapy
Current Cancer Drug Targets Small Molecule Drugs and Targeted Therapy for Melanoma: Current Strategies and Future Directions
Current Medicinal Chemistry Role of the Akt Pathway in Prostate Cancer
Current Cancer Drug Targets Meet Our Editorial Board Member
Current Pharmaceutical Biotechnology MDM2 Increases Drug Resistance in Cancer Cells by Inducing EMT Independent of p53
Current Medicinal Chemistry Current Phthalocyanines Delivery Systems in Photodynamic Therapy: An Updated Review
Current Medicinal Chemistry Anti-Cancer Phytometabolites Targeting Cancer Stem Cells
Current Genomics Targeted Therapies in the Treatment of Advanced Renal Cell Carcinoma
Recent Patents on Anti-Cancer Drug Discovery The Possible Involvement of Glycogen Synthase Kinase-3 (GSK-3) in Diabetes, Cancer and Central Nervous System Diseases
Current Pharmaceutical Design Direct Targeting of the Ras GTPase Superfamily Through Structure- Based Design
Current Topics in Medicinal Chemistry Immunotherapy in Patients with Recurrent and Metastatic Squamous Cell Carcinoma of the Head and Neck
Anti-Cancer Agents in Medicinal Chemistry Therapeutic Use of Brentuximab Vedotin in CD30+ Hematologic Malignancies
Anti-Cancer Agents in Medicinal Chemistry Transforming Growth Factor-β: A Molecular Target for the Future Therapy of Glioblastoma
Current Pharmaceutical Design Roles of Laminin-332 and α6β4 Integrin in Tumor Progression
Mini-Reviews in Medicinal Chemistry Antibody-Based Targeted Interventions for the Diagnosis and Treatment of Skin Cancers
Anti-Cancer Agents in Medicinal Chemistry Angiogenesis Inhibitors: Current & Future Directions
Current Pharmaceutical Design Chemistry and Health Effects of Bioactive Compounds in Selected Culinary Aromatic Herbs
Current Nutrition & Food Science