4.3 Article

Characterizing the morphology of protein binding patches

Journal

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
Volume 80, Issue 12, Pages 2652-2665

Publisher

WILEY
DOI: 10.1002/prot.24144

Keywords

protein complex; binding patch; interface morphology; structural comparisons; voronoi models; shelling tree; tree edit distance; dynamic programming-based comparisons

Funding

  1. Computational Geometric Learning STREP project of the EC 7th Framework Programme [255827]

Ask authors/readers for more resources

Let the patch of a partner in a protein complex be the collection of atoms accounting for the interaction. To improve our understanding of the structurefunction relationship, we present a patch model decoupling the topological and geometric properties. While the geometry is classically encoded by the atomic positions, the topology is recorded in a graph encoding the relative position of concentric shells partitioning the interface atoms. The topologicalgeometric duality provides the basis of a generic dynamic programming-based algorithm comparing patches at the shell level, which may favor topological or geometric features. On the biological side, we address four questions, using 249 cocrystallized heterodimers organized in biological families. First, we dissect the morphology of binding patches and show that Nature enjoyed the topological and geometric degrees of freedom independently while retaining a finite set of qualitatively distinct topological signatures. Second, we argue that our shell-based comparison is effective to perform atomic-level comparisons and show that topological similarity is a less stringent than geometric similarity. We also use the topological versus geometric duality to exhibit topo-rigid patches, whose topology (but not geometry) remains stable upon docking. Third, we use our comparison algorithms to infer specificity-related information amidst a database of complexes. Finally, we exhibit a descriptor outperforming its contenders to predict the binding affinities of the affinity benchmark. The softwares developed with this article are available from http://team.inria.fr/abs/vorpatch_compatch/.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Review Biochemical Research Methods

Integrative methods for analyzing big data in precision medicine

Vladimir Gligorijevic, Noel Malod-Dognin, Natasa Przulj

PROTEOMICS (2016)

Editorial Material Multidisciplinary Sciences

Network analytics in the age of big data

Natasa Przulj, Noel Malod-Dognin

SCIENCE (2016)

Article Biochemical Research Methods

Higher-order molecular organization as a source of biological function

Thomas Gaudelet, Noel Malod-Dognin, Natasa Przulj

BIOINFORMATICS (2018)

Article Multidisciplinary Sciences

Unified Alignment of Protein-Protein Interaction Networks

Noel Malod-Dognin, Kristina Ban, Natasa Przulj

SCIENTIFIC REPORTS (2017)

Article Multidisciplinary Sciences

Towards a data-integrated cell

Noel Malod-Dognin, Julia Petschnigg, Sam F. L. Windels, Janez Povh, Harry Hemmingway, Robin Ketteler, Natasa Przulj

NATURE COMMUNICATIONS (2019)

Article Biochemical Research Methods

Graphlet Laplacians for topology-function and topology-disease relationships

Sam F. L. Windels, Noel Malod-Dognin, Natasa Przulj

BIOINFORMATICS (2019)

Correction Multidisciplinary Sciences

Towards a data-integrated cell (vol 10, 805, 2019)

Noel Malod-Dognin, Julia Petschnigg, Sam F. L. Windels, Janez Povh, Harry Hemingway, Robin Ketteler, Natasa Przulj

NATURE COMMUNICATIONS (2019)

Article Chemistry, Medicinal

Antiproliferative activity and mode of action analysis of novel amino and amido substituted phenantrene and naphtho[2,1-b]thiophene derivatives

Natasa Perin, Valentina Rep, Irena Sovic, Stefica Juricic, Danijel Selgrad, Marko Klobucar, Natasa Przulj, Chhedi Lal Gupta, Noel Malod-Dognin, Sandra Kraljevic Pavelic, Marijana Hranjec

EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY (2020)

Article Multidisciplinary Sciences

Unveiling new disease, pathway, and gene associations via multi-scale neural network

Thomas Gaudelet, Noel Malod-Dognin, Jon Sanchez-Valle, Vera Pancaldi, Alfonso Valencia, Nataga Przulj

PLOS ONE (2020)

Article Biochemical Research Methods

Chromatin network markers of leukemia

N. Malod-Dognin, V Pancaldi, A. Valencia, N. Przulj

BIOINFORMATICS (2020)

Article Biochemical Research Methods

Classification in biological networks with hypergraphlet kernels

Jose Lugo-Martinez, Daniel Zeiberg, Thomas Gaudelet, Noel Malod-Dognin, Natasa Przulj, Predrag Radivojac

Summary: This study introduces a hypergraph-based approach for modeling biological systems and formulates vertex classification, edge classification, and link prediction problems on (hyper)graphs. It also presents a novel kernel method on vertex- and edge-labeled hypergraphs for analysis and learning.

BIOINFORMATICS (2021)

Article Biochemical Research Methods

Probabilistic graphlets capture biological function in probabilistic molecular networks

Sergio Doria-Belenguer, Markus K. Youssef, Rene Bottcher, Noel Malod-Dognin, Natasa Przulj

BIOINFORMATICS (2020)

Article Biochemical Research Methods

Linear functional organization of the omic embedding space

A. Xenos, N. Malod-Dognin, S. Milinkovic, N. Przulj

Summary: This study introduces algorithms based on network embeddings to untangle the complexity of omics data and mine them for new biomedical information. By decomposing matrices with Nonnegative Matrix Tri-Factorization, the study demonstrates that genes with similar biological functions are embedded close in space and can extract new biomedical knowledge through linear operations on their vector representations. The method successfully predicts new genes participating in protein complexes and identifies cancer-related genes with potential clinical relevance based on cosine similarities between vector representations.

BIOINFORMATICS (2021)

Article Mathematical & Computational Biology

Omics Data Complementarity Underlines Functional Cross-Communication in Yeast

Noel Malod-Dognin, Natasa Przulj

JOURNAL OF INTEGRATIVE BIOINFORMATICS (2017)

Article Biochemical Research Methods

Rebuttal to the Letter to the Editor in response to the paper: proper evaluation of alignment-free network comparison methods

Omer Nebil Yaveroglu, Noel Malod-Dognin, Tijana Milenkovic, Natasa Przulj

BIOINFORMATICS (2017)

No Data Available