Distinguishing biological and crystallographic interfaces
Description: Classification of protein-protein interfaces using structural, energetic and machine learning approaches. Duration: 2017–2019 Affiliation: Utrecht University Role: Trainee
Overview
This project focused on the computational classification of protein-protein interfaces as biologically relevant or crystallographic artifacts. The work includes the development of a method for interface classification (Elez et al., 2018), its implementation as a fast and user-friendly web server for practical use (Jiménez-García et al., 2019), and a comprehensive review of computational approaches to interface classification, covering energy-based, empirical, and machine learning methods (Elez et al., 2020).
Key Contributions
Analyzed structural and energetic differences between biological and crystallographic interfaces.
Developed predictive models achieving high accuracy for interface classification.
Contributed to PRODIGY-CRYSTAL, a fast and accessible web tool for interface prediction.
Systematically reviewed computational methods for protein interface classification.
Background
Protein-protein interactions are central to cellular function, and their structural characterization is essential for understanding biological mechanisms. X-ray crystallography provides many protein complex structures, but crystallographic packing often introduces non-biological interfaces that must be distinguished from biologically relevant ones. This distinction is challenging due to overlapping structural and energetic features, motivating computational approaches for reliable interface classification.
Methodology
Analysis of intermolecular residue-residue contacts
Protein-protein interface refinement
Machine learning-based classification
Collaborators
Utrecht University: Anna Vangone, Brian Jiménez-García, Panagiotis I. Koukos, Alexandre M. J. J. Bonvin
References
2020
Biological vs. Crystallographic Protein Interfaces: An Overview of Computational Approaches for Their Classification
Katarina Elez, Alexandre M. J. J. Bonvin, and Anna Vangone
Complexes between proteins are at the basis of almost every process in cells. Their study, from a structural perspective, has a pivotal role in understanding biological functions and, importantly, in drug development. X-ray crystallography represents the broadest source for the experimental structural characterization of protein-protein complexes. Correctly identifying the biologically relevant interface from the crystallographic ones is, however, not trivial and can be prone to errors. Over the past two decades, computational methodologies have been developed to study the differences of those interfaces and automatically classify them as biological or crystallographic. Overall, protein-protein interfaces show differences in terms of composition, energetics and evolutionary conservation between biological and crystallographic ones. Based on those observations, a number of computational methods have been developed for this classification problem, which can be grouped into three main categories: Energy-, empirical knowledge- and machine learning-based approaches. In this review, we give a comprehensive overview of the training datasets and methods so far implemented, providing useful links and a brief description of each method.
@article{elez_biological_2020,title={Biological vs. {{Crystallographic Protein Interfaces}}: {{An Overview}} of {{Computational Approaches}} for {{Their Classification}}},shorttitle={Biological vs. {{Crystallographic Protein Interfaces}}},author={Elez, Katarina and Bonvin, Alexandre M. J. J. and Vangone, Anna},year={2020},journal={Crystals},volume={10},number={2},pages={114},publisher={Multidisciplinary Digital Publishing Institute},doi={10.3390/cryst10020114},altmetric=true,dimensions=true,bibtex_show=true,}
2019
PRODIGY-crystal: A Web-Tool for Classification of Biological Interfaces in Protein Complexes
Brian Jiménez-García, Katarina Elez, Panagiotis I Koukos, Alexandre M. J. J. Bonvin, and Anna Vangone
Distinguishing biologically relevant interfaces from crystallographic ones in biological complexes is fundamental in order to associate cellular functions to the correct macromolecular assemblies. Recently, we described a detailed study reporting the differences in the type of intermolecular residue–residue contacts between biological and crystallographic interfaces. Our findings allowed us to develop a fast predictor of biological interfaces reaching an accuracy of 0.92 and competitive to the current state of the art. Here we present its web-server implementation, PRODIGY-CRYSTAL, aimed at the classification of biological and crystallographic interfaces. PRODIGY-CRYSTAL has the advantage of being fast, accurate and simple. This, together with its user-friendly interface and user support forum, ensures its broad accessibility.PRODIGY-CRYSTAL is freely available without registration requirements at https://haddock.science.uu.nl/services/PRODIGY-CRYSTAL.
@article{jimenez-garcia_prodigycrystal_2019,title={{{PRODIGY-crystal}}: A Web-Tool for Classification of Biological Interfaces in Protein Complexes},shorttitle={{{PRODIGY-crystal}}},author={{Jim{\'e}nez-Garc{\'i}a}, Brian and Elez, Katarina and Koukos, Panagiotis I and Bonvin, Alexandre M. J. J. and Vangone, Anna},year={2019},journal={Bioinformatics},volume={35},number={22},pages={4821--4823},doi={10.1093/bioinformatics/btz437},altmetric=true,dimensions=true,bibtex_show=true,}
2018
Distinguishing Crystallographic from Biological Interfaces in Protein Complexes: Role of Intermolecular Contacts and Energetics for Classification
Katarina Elez, Alexandre M. J. J. Bonvin, and Anna Vangone
Study of macromolecular assemblies is fundamental to understand functions in cells. X-ray crystallography is the most common technique to solve their 3D structure at atomic resolution. In a crystal, however, both biologically-relevant interfaces and non-specific interfaces resulting from crystallographic packing are observed. Due to the complexity of the biological assemblies currently tackled, classifying those interfaces, i.e. distinguishing biological from crystal lattice interfaces, is not trivial and often prone to errors. In this context, analyzing the physico-chemical characteristics of biological/crystal interfaces can help researchers identify possible features that distinguish them and gain a better understanding of the systems.
@article{elez_distinguishing_2018,title={Distinguishing Crystallographic from Biological Interfaces in Protein Complexes: Role of Intermolecular Contacts and Energetics for Classification},shorttitle={Distinguishing Crystallographic from Biological Interfaces in Protein Complexes},author={Elez, Katarina and Bonvin, Alexandre M. J. J. and Vangone, Anna},year={2018},journal={BMC Bioinformatics},volume={19},number={15},pages={438},doi={10.1186/s12859-018-2414-9},altmetric=true,dimensions=true,bibtex_show=true,selected=true}
