Abstract
BackgroundProtein-protein interaction plays a key role in a multitude of biological processes, such as signal transduction, de novo drug design, immune responses, and enzymatic activities. Gaining insights of various binding abilities can deepen our understanding of the interaction. It is of great interest to understand how proteins in a complex interact with each other. Many efficient methods have been developed for identifying protein-protein interface.ResultsIn this paper, we obtain the local information on protein-protein interface, through multi-scale local average block and hexagon structure construction. Given a pair of proteins, we use a trained support vector regression (SVR) model to select best configurations. On Benchmark v4.0, our method achieves average Irmsd value of 3.28Å and overall Fnat value of 63%, which improves upon Irmsd of 3.89Å and Fnat of 49% for ZRANK, and Irmsd of 3.99Å and Fnat of 46% for ClusPro. On CAPRI targets, our method achieves average Irmsd value of 3.45Å and overall Fnat value of 46%, which improves upon Irmsd of 4.18Å and Fnat of 40% for ZRANK, and Irmsd of 5.12Å and Fnat of 32% for ClusPro. The success rates by our method, FRODOCK 2.0, InterEvDock and SnapDock on Benchmark v4.0 are 41.5%, 29.0%, 29.4% and 37.0%, respectively.ConclusionExperiments show that our method performs better than some state-of-the-art methods, based on the prediction quality improved in terms of CAPRI evaluation criteria. All these results demonstrate that our method is a valuable technological tool for identifying protein-protein interface.
Highlights
Protein-protein interaction plays a key role in a multitude of biological processes, such as signal transduction, de novo drug design, immune responses, and enzymatic activities
Experiments show that our method performs better than some state-of-the-art methods on Benchmark v4.0 and the Critical Assessment of PRediction of Interactions (CAPRI) targets, based on the prediction quality improved in terms of CAPRI evaluation criteria
In rigid-body group, our method achieves average Irmsd value of 2.86Å and overall Fnat value of 69%, which improves upon Irmsd of 3.31Å and Fnat of 56% for ZRANK, and Irmsd of 3.33Å and Fnat of 55% for ClusPro
Summary
Protein-protein interaction plays a key role in a multitude of biological processes, such as signal transduction, de novo drug design, immune responses, and enzymatic activities. Gaining insights of various binding abilities can deepen our understanding of the interaction. It is of great interest to understand how proteins in a complex interact with each other. Many proteins carry out the special biological functions through protein-protein interactions, such as drug design and functional analysis. Gaining insights of various binding abilities can deepen our understanding on protein-protein interface. ProMate [16] creates the circle around each surface residue, which can be used to extract the statistical histogram of many features.
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