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DeepInterface: Protein-protein interface validation using 3D Convolutional Neural Networks

https://doi.org/10.1101/617506
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/pmic.201100217openalex-snapshot
Feature‐based classification of native and non‐native protein–protein interactions: Comparing supervised and semi‐supervised learning approaches
inferredcites →https://doi.org/10.1002/pro.5560071211openalex-snapshot
Empirical solvent‐mediated potentials hold for both intra‐molecular and inter‐molecular inter‐residue interactions
inferredcites →https://doi.org/10.1002/prot.10381openalex-snapshot
CAPRI: A Critical Assessment of PRedicted Interactions
inferredcites →https://doi.org/10.1002/prot.10389openalex-snapshot
ZDOCK: An initial‐stage protein‐docking algorithm
inferredcites →https://doi.org/10.1002/prot.20514openalex-snapshot
Prediction of interface residues in protein–protein complexes by a consensus neural network method: Test against NMR data
inferredcites →https://doi.org/10.1002/prot.22252openalex-snapshot
Consensus scoring for enriching near‐native structures from protein–protein docking decoys
inferredcites →https://doi.org/10.1002/prot.25007openalex-snapshot
Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: A CASP‐CAPRI experiment
inferredcites →https://doi.org/10.1006/jmbi.1997.1234openalex-snapshot
Analysis of protein-protein interaction sites using surface patches 1 1Edited by G.Von Heijne
inferredcites →https://doi.org/10.1016/j.cels.2017.11.014openalex-snapshot
Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1016/j.jmb.2004.09.051openalex-snapshot
Protein–Protein Interactions: Hot Spots and Structurally Conserved Residues often Locate in Complemented Pockets that Pre-organized in the Unbound States: Implications for Docking
inferredcites →https://doi.org/10.1016/j.jmb.2008.04.071openalex-snapshot
Architectures and Functional Coverage of Protein–Protein Interfaces
inferredcites →https://doi.org/10.1016/j.jsb.2012.04.009openalex-snapshot
Protein interactions in 3D: From interface evolution to drug discovery
inferredcites →https://doi.org/10.1021/acs.jcim.5b00372openalex-snapshot
Knowledge of Native Protein–Protein Interfaces Is Sufficient To Construct Predictive Models for the Selection of Binding Candidates
inferredcites →https://doi.org/10.1021/cr040409xopenalex-snapshot
Principles of Protein−Protein Interactions: What are the Preferred Ways For Proteins To Interact?
inferredcites →https://doi.org/10.1038/nprot.2011.367openalex-snapshot
Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM
inferredcites →https://doi.org/10.1073/pnas.1200678109openalex-snapshot
Templates are available to model nearly all complexes of structurally characterized proteins
inferredcites →https://doi.org/10.1093/bioinformatics/bti443openalex-snapshot
Prediction of protein-protein interactions by combining structure and sequence conservation in protein interfaces
inferredcites →https://doi.org/10.1093/bioinformatics/btn497openalex-snapshot
D ockground protein–protein docking decoy set
inferredcites →https://doi.org/10.1093/bioinformatics/btt260openalex-snapshot
InterEvScore: a novel coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution
inferredcites →https://doi.org/10.1093/bioinformatics/btw533openalex-snapshot
PPI4DOCK: large scale assessment of the use of homology models in free docking over more than 1000 realistic targets
inferredcites →https://doi.org/10.1093/bioinformatics/btx350openalex-snapshot
DeepSite: protein-binding site predictor using 3D-convolutional neural networks
inferredcites →https://doi.org/10.1093/bioinformatics/btx584openalex-snapshot
Protein–protein interaction specificity is captured by contact preferences and interface composition
inferredcites →https://doi.org/10.1093/bioinformatics/btx781openalex-snapshot
DNCON2: improved protein contact prediction using two-level deep convolutional neural networks
inferredcites →https://doi.org/10.1093/bioinformatics/bty585openalex-snapshot
Learning structural motif representations for efficient protein structure search
inferredcites →https://doi.org/10.1093/nar/gki585openalex-snapshot
PRISM: protein interactions by structural matching
inferredcites →https://doi.org/10.1093/nar/gkl206openalex-snapshot
GRAMM-X public web server for protein-protein docking
inferredcites →https://doi.org/10.1093/nar/gkq1059openalex-snapshot
The protein common interface database (ProtCID)--a comprehensive database of interactions of homologous proteins in multiple crystal forms
inferredcites →https://doi.org/10.1093/nar/gku397openalex-snapshot
PRISM: a web server and repository for prediction of protein–protein interactions and modeling their 3D complexes
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/iccv.2015.123openalex-snapshot
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
inferredcites →https://doi.org/10.1137/141000671openalex-snapshot
Julia: A Fresh Approach to Numerical Computing
inferredcites →https://doi.org/10.1186/1471-2105-13-41openalex-snapshot
Predicting protein-protein interface residues using local surface structural similarity
inferredcites →https://doi.org/10.1186/s12859-017-1702-0openalex-snapshot
3D deep convolutional neural networks for amino acid environment similarity analysis
inferredcites →https://doi.org/10.1371/journal.pone.0086738openalex-snapshot
Non-Redundant Unique Interface Structures as Templates for Modeling Protein Interactions
inferredcites →https://doi.org/10.2174/138920108783955191openalex-snapshot
Characterization and Prediction of Protein Interfaces to Infer Protein-Protein Interaction Networks
inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot
AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)
inferredcites →https://doi.org/10.57702/o9raffedopenalex-snapshot
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/cac2.12330openalex-snapshot
Antibody variable region engineering for improving cancer immunotherapy
inferred← citeshttps://doi.org/10.1007/978-3-030-57821-3_27openalex-snapshot
Deep Learning Approach with Rotate-Shift Invariant Input to Predict Protein Homodimer Structure
inferred← citeshttps://doi.org/10.1016/j.sbi.2022.102328openalex-snapshot
Artificial intelligence approaches to human-microbiome protein–protein interactions
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c01788openalex-snapshot
ProInterVal: Validation of Protein–Protein Interfaces through Learned Interface Representations
inferred← citeshttps://doi.org/10.1038/s42256-023-00715-4openalex-snapshot
Evaluating protein binding interfaces with transformer networks
inferred← citeshttps://doi.org/10.1093/bioadv/vbad012openalex-snapshot
Improving classification of correct and incorrect protein–protein docking models by augmenting the training set
inferred← citeshttps://doi.org/10.1101/2023.01.03.522623openalex-snapshot
PIsToN: Evaluating Protein Binding Interfaces with Transformer Networks
inferred← citeshttps://doi.org/10.3390/antib9020012openalex-snapshot
A Review of Deep Learning Methods for Antibodies
inferred← citeshttps://doi.org/10.3390/bioengineering11020185openalex-snapshot
Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions
inferred← citeshttps://doi.org/10.48550/arxiv.2103.03724openalex-snapshot
Sequence-based deep learning antibody design for in silico antibody affinity maturation
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