scholarly journals FrustratometeR: an R-package to compute Local frustration in protein structures, point mutants and MD simulations

2020 ◽  
Author(s):  
Atilio O. Rausch ◽  
Maria I. Freiberger ◽  
Cesar O. Leonetti ◽  
Diego M. Luna ◽  
Leandro G. Radusky ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Protein Structures ◽  
Md Simulations ◽  
R Package ◽  
Protein Protein Interactions ◽  
Large Scale Analysis ◽  
Functional Aspects ◽  
Catalytic Sites ◽  
Polypeptide Chains

Once folded natural protein molecules have few energetic conflicts within their polypeptide chains. Many protein structures do however contain regions where energetic conflicts remain after folding, i.e. they have highly frustrated regions. These regions, kept in place over evolutionary and physiological timescales, are related to several functional aspects of natural proteins such as protein-protein interactions, small ligand recognition, catalytic sites and allostery. Here we present FrustratometeR, an R package that easily computes local energetic frustration on a personal computer or a cluster. This package facilitates large scale analysis of local frustration, point mutants and MD trajectories, allowing straightforward integration of local frustration analysis in to pipelines for protein structural analysis.Availability and implementation: https://github.com/proteinphysiologylab/frustratometeR

scholarly journals Human mitochondrial protein complexes revealed by large-scale coevolution analysis and deep learning-based structure modeling

2021 ◽  
Author(s):  
Jimin Pei ◽  
Jing Zhang ◽  
Qian Cong
Keyword(s):  
Deep Learning ◽  
Protein Interactions ◽  
Large Scale ◽  
Protein Complexes ◽  
Mitochondrial Protein ◽  
Protein Structures ◽  
Complex Structures ◽  
Protein Protein Interactions ◽  
Learning Methods ◽  
Contact Probability

AbstractRecent development of deep-learning methods has led to a breakthrough in the prediction accuracy of 3-dimensional protein structures. Extending these methods to protein pairs is expected to allow large-scale detection of protein-protein interactions and modeling protein complexes at the proteome level. We applied RoseTTAFold and AlphaFold2, two of the latest deep-learning methods for structure predictions, to analyze coevolution of human proteins residing in mitochondria, an organelle of vital importance in many cellular processes including energy production, metabolism, cell death, and antiviral response. Variations in mitochondrial proteins have been linked to a plethora of human diseases and genetic conditions. RoseTTAFold, with high computational speed, was used to predict the coevolution of about 95% of mitochondrial protein pairs. Top-ranked pairs were further subject to the modeling of the complex structures by AlphaFold2, which also produced contact probability with high precision and in many cases consistent with RoseTTAFold. Most of the top ranked pairs with high contact probability were supported by known protein-protein interactions and/or similarities to experimental structural complexes. For high-scoring pairs without experimental complex structures, our coevolution analyses and structural models shed light on the details of their interfaces, including CHCHD4-AIFM1, MTERF3-TRUB2, FMC1-ATPAF2, ECSIT-NDUFAF1 and COQ7-COQ9, among others. We also identified novel PPIs (PYURF-NDUFAF5, LYRM1-MTRF1L and COA8-COX10) for several proteins without experimentally characterized interaction partners, leading to predictions of their molecular functions and the biological processes they are involved in.

scholarly journals Reliable identification of protein-protein interactions by crosslinking mass spectrometry

2020 ◽  
Author(s):  
Swantje Lenz ◽  
Ludwig R. Sinn ◽  
Francis J. O’Reilly ◽  
Lutz Fischer ◽  
Fritz Wegner ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Large Scale ◽  
Protein Complexes ◽  
Estimation Procedure ◽  
Scale Analysis ◽  
Protein Protein Interactions ◽  
False Discovery ◽  
Large Scale Analysis ◽  
False Discovery Rate Estimation

Crosslinking mass spectrometry is widening its scope from structural analyzes of purified multi-protein complexes towards systems-wide analyzes of protein-protein interactions. Assessing the error in these large datasets is currently a challenge. Using a controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate a reliable false-discovery rate estimation procedure for protein-protein interactions identified by crosslinking mass spectrometry.

scholarly journals A Large Scale Analysis of Protein-Protein Interactions in the Nitrogen-fixing Bacterium Mesorhizobium loti

DNA Research ◽  
2008 ◽  
Vol 15 (1) ◽  
pp. 13-23 ◽  
Author(s):  
Y. Shimoda ◽  
S. Shinpo ◽  
M. Kohara ◽  
Y. Nakamura ◽  
S. Tabata ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Scale Analysis ◽  
Nitrogen Fixing ◽  
Protein Protein Interactions ◽  
Mesorhizobium Loti ◽  
Large Scale Analysis

scholarly journals Development of a compact alkynyl-enrichable crosslinker for in-depth in-vivo crosslinking analysis

2021 ◽  
Author(s):  
Hang Gao ◽  
Li Li Zhao ◽  
Qun Zhao ◽  
Hua Li Zhang ◽  
Feng Bao Zhao ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
High Efficiency ◽  
Protein Complexes ◽  
Protein Structures ◽  
High Sensitivity ◽  
Protein Protein Interactions ◽  
Cross Links ◽  
First Time

Chemical crosslinking coupled with mass spectrometry (CXMS) has emerged as a powerful technique to capture the dynamic information of protein complexes with high sensitivity, throughput and sample universality. To advance the study of in-vivo protein structures and protein-protein interactions on the large scale, a new alkynyl-enrichable crosslinker was developed with high efficiency of membrane penetration, reactivity and enrichment. The crosslinker was successfully used for in-vivo crosslinking of intact human cells, resulting in 6820 non-redundant crosslinks identified at a false discovery rate (FDR) of 1% using pLink 2.0, which 4898 (71.8%) of the cross-links were assigned as intraprotein and 1922 (28.2%) were interprotein links. To our knowledge, this is also the first time to realize the in-vivo crosslinking with a non-cleavable cross-linker for homo species cells.

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