scholarly journals Modeling of protein complexes in CASP14 with emphasis on the interaction interface prediction

2021 ◽  
Author(s):  
Justas DapkŪnas ◽  
Kliment Olechnovič ◽  
česlovas Venclovas
Keyword(s):  
Protein Complexes ◽  
Interaction Interface ◽  
Interface Prediction

scholarly journals Modeling of protein complexes in CASP14 with emphasis on the interaction interface prediction

2021 ◽  
Author(s):  
Justas Dapkunas ◽  
Kliment Olechnovič ◽  
Česlovas Venclovas
Keyword(s):  
Protein Structure ◽  
Structure Prediction ◽  
Protein Complexes ◽  
Assessment Method ◽  
Protein Assemblies ◽  
Structure Quality ◽  
Interaction Interface ◽  
Quality Assessment Method ◽  
Interface Prediction ◽  
Antigen Interaction

The goal of CASP experiments is to monitor the progress in the protein structure prediction field. During the 14th CASP edition we aimed to test our capabilities of predicting structures of protein complexes. Our protocol for modeling protein assemblies included both template-based modeling and free docking. Structural templates were identified using sensitive sequence-based searches. If sequence-based searches failed, we performed structure-based template searches using selected CASP server models. In the absence of reliable templates we applied free docking starting from monomers generated by CASP servers. We evaluated and ranked models of protein complexes using an improved version of protein structure quality assessment method, VoroMQA, taking into account both interaction interface and global structure scores. If reliable templates could be identified, generally accurate models of protein assemblies were generated with the exception of an antibody-antigen interaction. The success of free docking mainly depended on the accuracy of initial subunit models and on the scoring of docking solutions. To put our overall results in perspective, we analyzed our performance in the context of other CASP groups. Although the subunits in our assembly models often were not of the top quality, these models had, overall, the best predicted interfaces according to several protein-protein interface accuracy measures. Since we did not use co-evolution-based prediction of inter-chain contacts, we attribute our relative success in predicting interfaces primarily to the emphasis on the interaction interface when modeling and scoring.

scholarly journals Protein-RNA Interaction Interface Prediction and Design

2012 ◽  
Vol 28 (10) ◽  
pp. 2390-2400
Author(s):  
HUANG Yang-Yu ◽  
◽  
YANG Xiu-Feng ◽  
LI Hao-Tian ◽  
JI Xiao-Feng ◽  
...  
Keyword(s):  
Interaction Interface ◽  
Interface Prediction ◽  
Rna Interaction

scholarly journals ProteinGLUE: A multi-task benchmark suite for self-supervised protein modeling.

2021 ◽  
Author(s):  
Henriette Capel ◽  
Robin Weiler ◽  
Maurits J.J. Dijkstra ◽  
Reinier Vleugels ◽  
Peter Bloem ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Protein Sequence ◽  
Sequence Data ◽  
Language Modeling ◽  
Performance Evaluations ◽  
Property Prediction ◽  
Interaction Interface ◽  
Protein Sequence Data ◽  
Benchmark Suite ◽  
Interface Prediction

Self-supervised language modeling is a rapidly developing approach for the analysis of protein sequence data. However, work in this area is heterogeneous and diverse, making comparison of models and methods difficult. Moreover, models are often evaluated only on one or two downstream tasks, making it unclear whether the models capture generally useful properties. We introduce the ProteinGLUE benchmark for the evaluation of protein representations: a set of seven tasks for evaluating learned protein representations. We also offer reference code, and we provide two baseline models with hyperparameters specifically trained for these benchmarks. Pre-training was done on two tasks, masked symbol prediction and next sentence prediction. We show that pre-training yields higher performance on a variety of downstream tasks such as secondary structure and protein interaction interface prediction, compared to no pre-training. However, the larger base model does not outperform the smaller medium. We expect the ProteinGLUE benchmark dataset introduced here, together with the two baseline pre-trained models and their performance evaluations, to be of great value to the field of protein sequence-based property prediction. Availability: code and datasets from https://github.com/ibivu/protein-glue

scholarly journals Patch-DCA: Improved Protein Interface Prediction by utilizing Structural Information and Clustering DCA scores

2019 ◽  
Author(s):  
Amir Vajdi ◽  
Kourosh Zarringhalam ◽  
Nurit Haspel
Keyword(s):  
Structural Information ◽  
Protein Complexes ◽  
Evolutionary Information ◽  
Sequence Information ◽  
Protein Interface ◽  
Residue Contacts ◽  
Interface Prediction ◽  
Sequential Information ◽  
The Individual ◽  
Protein Contact Maps

AbstractOver the past decade there have been impressive advances in determining the 3D structures of protein complexes. However, there are still many complexes with unknown structures, even when the structures of the individual proteins are known. The advent of protein sequence information provides an opportunity to leverage evolutionary information to enhance the accuracy of protein-protein interface prediction. To this end, several statistical and machine learning methods have been proposed. In particular, direct coupling analysis has recently emerged as a promising approach for identification of protein contact maps from sequential information. However, the ability of these methods to detect protein-protein inter-residue contacts remains relatively limited.In this work, we propose a method to integrate sequential and co-evolution information with structural and functional information to increase the performance of protein-protein interface prediction. Further, we present a post-processing clustering method that improves the average relative F1 score by 70 % and 24 % and the precision by 80 % and 36 % in comparison with two state-of-the-art methods PSICOV and GREMLIN.

scholarly journals Trans-toxin ion-sensitivity of charybdotoxin-blocked potassium-channels reveals unbinding transitional states

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Hans Moldenhauer ◽  
Ignacio Díaz-Franulic ◽  
Horacio Poblete ◽  
David Naranjo
Keyword(s):  
Conformational Changes ◽  
Molecular Mechanisms ◽  
Protein Complexes ◽  
Tight Binding ◽  
External Solution ◽  
Scorpion Venom ◽  
K Channels ◽  
Interaction Interface ◽  
Dynamic Stochastic

In silico and in vitro studies have made progress in understanding protein–protein complex formation; however, the molecular mechanisms for their dissociation are unclear. Protein–protein complexes, lasting from microseconds to years, often involve induced-fit, challenging computational or kinetic analysis. Charybdotoxin (CTX), a peptide from the Leiurus scorpion venom, blocks voltage-gated K+-channels in a unique example of binding/unbinding simplicity. CTX plugs the external mouth of K+-channels pore, stopping K+-ion conduction, without inducing conformational changes. Conflicting with a tight binding, we show that external permeant ions enhance CTX-dissociation, implying a path connecting the pore, in the toxin-bound channel, with the external solution. This sensitivity is explained if CTX wobbles between several bound conformations, producing transient events that restore the electrical and ionic trans-pore gradients. Wobbling may originate from a network of contacts in the interaction interface that are in dynamic stochastic equilibria. These partially-bound intermediates could lead to distinct, and potentially manipulable, dissociation pathways.

scholarly journals Patch-DCA: improved protein interface prediction by utilizing structural information and clustering DCA scores

2019 ◽  
Author(s):  
Amir Vajdi ◽  
Kourosh Zarringhalam ◽  
Nurit Haspel
Keyword(s):  
Structural Information ◽  
Protein Complexes ◽  
Supplementary Information ◽  
Evolutionary Information ◽  
Sequence Information ◽  
Protein Interface ◽  
Residue Contacts ◽  
Interface Prediction ◽  
Sequential Information ◽  
The Individual

Abstract Motivation Over the past decade, there have been impressive advances in determining the 3D structures of protein complexes. However, there are still many complexes with unknown structures, even when the structures of the individual proteins are known. The advent of protein sequence information provides an opportunity to leverage evolutionary information to enhance the accuracy of protein–protein interface prediction. To this end, several statistical and machine learning methods have been proposed. In particular, direct coupling analysis has recently emerged as a promising approach for identification of protein contact maps from sequential information. However, the ability of these methods to detect protein–protein inter-residue contacts remains relatively limited. Results In this work, we propose a method to integrate sequential and co-evolution information with structural and functional information to increase the performance of protein–protein interface prediction. Further, we present a post-processing clustering method that improves the average relative F1 score by 70% and 24% and the average relative precision by 80% and 36% in comparison with two state-of-the-art methods, PSICOV and GREMLIN. Availability and implementation https://github.com/BioMLBoston/PatchDCA Supplementary information Supplementary data are available at Bioinformatics online.

Electron Microscopy and image analysis of nucleo-protein complexes

1994 ◽  
Vol 52 ◽  
pp. 88-89
Author(s):  
E. H. Egelman ◽  
X. Yu
Keyword(s):  
Electron Microscopy ◽  
Image Analysis ◽  
Normal Cell ◽  
Genetic Recombination ◽  
Protein Complexes ◽  
Chromosomal Rearrangements ◽  
Reca Protein ◽  
E Coli ◽  
Helical Polymer ◽  
Specific Protease

The RecA protein of E. coli has been shown to mediate genetic recombination, regulate its own synthesis, control the expression of other genes, act as a specific protease, form a helical polymer and have an ATPase activity, among other observed properties. The unusual filament formed by the RecA protein on DNA has not previously been shown to exist outside of bacteria. Within this filament, the 36 Å pitch of B-form DNA is extended to about 95 Å, the pitch of the RecA helix. We have now establishedthat similar nucleo-protein complexes are formed by bacteriophage and yeast proteins, and availableevidence suggests that this structure is universal across all of biology, including humans. Thus, understanding the function of the RecA protein will reveal basic mechanisms, in existence inall organisms, that are at the foundation of general genetic recombination and repair.Recombination at this moment is assuming an importance far greater than just pure biology. The association between chromosomal rearrangements and neoplasms has become stronger and stronger, and these rearrangements are most likely products of the recombinatory apparatus of the normal cell. Further, damage to DNA appears to be a major cause of cancer.

Structure of contact sites between the outer and inner mitochondrial membranes investigated by HVEM tomography

1996 ◽  
Vol 54 ◽  
pp. 966-967
Author(s):  
C.A. Mannella ◽  
K.F. Buttle ◽  
K.A. O‘Farrell ◽  
A. Leith ◽  
M. Marko
Keyword(s):  
Liver Mitochondrion ◽  
Adenine Nucleotide ◽  
Protein Complexes ◽  
Mitochondrial Membranes ◽  
Electron Microscopic ◽  
Contact Sites ◽  
Transmission Electron ◽  
Precursor Proteins ◽  
Membrane Contacts ◽  
And Function

Early transmission electron microscopy of plastic-embedded, thin-sectioned mitochondria indicated that there are numerous junctions between the outer and inner membranes of this organelle. More recent studies have suggested that the mitochondrial membrane contacts may be the site of protein complexes engaged in specialized functions, e.g., import of mitochondrial precursor proteins, adenine nucleotide channeling, and even intermembrane signalling. It has been suggested that the intermembrane contacts may be sites of membrane fusion involving non-bilayer lipid domains in the two membranes. However, despite growing interest in the nature and function of intramitochondrial contact sites, little is known about their structure.We are using electron microscopic tomography with the Albany HVEM to determine the internal organization of mitochondria. We have reconstructed a 0.6-μm section through an isolated, plasticembedded rat-liver mitochondrion by combining 123 projections collected by tilting (+/- 70°) around two perpendicular tilt axes. The resulting 3-D image has confirmed the basic inner-membrane organization inferred from lower-resolution reconstructions obtained from single-axis tomography.

Reconstruction of Chitin-Protein Complexes Using Correlation Averaging Methods: Ovipositor of the Ichneumon Fly Megarhyssa

1980 ◽  
Vol 38 ◽  
pp. 38-39
Author(s):  
L. T. Germinario ◽  
J. Blackwell ◽  
J. Frank
Keyword(s):  
Protein Complexes ◽  
Hexagonal Lattice ◽  
Uranyl Acetate ◽  
Optical Diffraction ◽  
Insect Cuticle ◽  
High Dose ◽  
Wide Angle ◽  
X Ray ◽  
Averaging Methods ◽  
Digital Correlation

This report describes the use of digital correlation and averaging methods 1,2 for the reconstruction of high dose electron micrographs of the chitin-protein complex from Megarhyssa ovipositor. Electron microscopy of uranyl acetate stained insect cuticle has demonstrated a hexagonal array of unstained chitin monofibrils, 2.4−3.0 nm in diameter, in a stained protein matrix3,4. Optical diffraction Indicated a hexagonal lattice with a = 5.1-8.3 nm3 A particularly well ordered complex is found in the ovipositor of the ichneumon fly Megarhyssa: the small angle x-ray data gives a = 7.25 nm, and the wide angle pattern shows that the protein consists of subunits arranged in a 61 helix, with an axial repeat of 3.06 nm5.

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