scholarly journals hu.MAP 2.0: Integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies

2020 ◽  
Author(s):  
Kevin Drew ◽  
John B. Wallingford ◽  
Edward M. Marcotte
Keyword(s):  
Machine Learning ◽  
Mass Spectrometry ◽  
Structural Biology ◽  
Self Assembly ◽  
Protein Complexes ◽  
The Self ◽  
Web Interface ◽  
Valuable Resource ◽  
Cellular Functions ◽  
Learning Framework

AbstractA general principle of biology is the self-assembly of proteins into functional complexes. Characterizing their composition is, therefore, required for our understanding of cellular functions. Unfortunately, we lack a comprehensive set of protein complexes for human cells. To address this gap, we developed a machine learning framework to identify protein complexes in over 15,000 mass spectrometry experiments which resulted in the identification of nearly 7,000 physical assemblies. We show our resource, hu.MAP 2.0, is more accurate and comprehensive than previous resources and gives rise to many new hypotheses, including for 274 completely uncharacterized proteins. Further, we identify 259 promiscuous proteins that participate in multiple complexes pointing to possible moonlighting roles. We have made hu.MAP 2.0 easily searchable in a web interface (http://humap2.proteincomplexes.org/), which will be a valuable resource for researchers across a broad range of interests including systems biology, structural biology, and molecular explanations of disease.

scholarly journals Lessons from equilibrium statistical physics regarding the assembly of protein complexes

2019 ◽  
Vol 117 (1) ◽  
pp. 114-120 ◽  
Author(s):  
Pablo Sartori ◽  
Stanislas Leibler
Keyword(s):  
Self Assembly ◽  
Statistical Physics ◽  
Liquid Mixture ◽  
Protein Complexes ◽  
Biological Evolution ◽  
Cellular Protein ◽  
Cellular Functions ◽  
Physical Constraints ◽  
Polypeptide Chains ◽  
Protein Complex Assembly

Cellular functions are established through biological evolution, but are constrained by the laws of physics. For instance, the physics of protein folding limits the lengths of cellular polypeptide chains. Consequently, many cellular functions are carried out not by long, isolated proteins, but rather by multiprotein complexes. Protein complexes themselves do not escape physical constraints, one of the most important being the difficulty of assembling reliably in the presence of cellular noise. In order to lay the foundation for a theory of reliable protein complex assembly, we study here an equilibrium thermodynamic model of self-assembly that exhibits 4 distinct assembly behaviors: diluted protein solution, liquid mixture, “chimeric assembly,” and “multifarious assembly.” In the latter regime, different protein complexes can coexist without forming erroneous chimeric structures. We show that 2 conditions have to be fulfilled to attain this regime: 1) The composition of the complexes needs to be sufficiently heterogeneous, and 2) the use of the set of components by the complexes has to be sparse. Our analysis of publicly available databases of protein complexes indicates that cellular protein systems might have indeed evolved so as to satisfy both of these conditions.

scholarly journals Mass spectrometry-based methods for analysing the mitochondrial interactome in mammalian cells

2019 ◽  
Vol 167 (3) ◽  
pp. 225-231 ◽  
Author(s):  
Takumi Koshiba ◽  
Hidetaka Kosako
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Mammalian Cells ◽  
Protein Complexes ◽  
Living Cells ◽  
Protein Protein Interactions ◽  
Cellular Functions ◽  
Protein Protein Interaction ◽  
Membrane Protein Complexes ◽  
Protein Protein Interaction Networks

Abstract Protein–protein interactions are essential biologic processes that occur at inter- and intracellular levels. To gain insight into the various complex cellular functions of these interactions, it is necessary to assess them under physiologic conditions. Recent advances in various proteomic technologies allow to investigate protein–protein interaction networks in living cells. The combination of proximity-dependent labelling and chemical cross-linking will greatly enhance our understanding of multi-protein complexes that are difficult to prepare, such as organelle-bound membrane proteins. In this review, we describe our current understanding of mass spectrometry-based proteomics mapping methods for elucidating organelle-bound membrane protein complexes in living cells, with a focus on protein–protein interactions in mitochondrial subcellular compartments.

scholarly journals A synthesis of over 9,000 mass spectrometry experiments reveals the core set of human protein complexes

2016 ◽  
Author(s):  
Kevin Drew ◽  
Chanjae Lee ◽  
Ryan L. Huizar ◽  
Fan Tu ◽  
Blake Borgeson ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Genetic Diseases ◽  
Intraflagellar Transport ◽  
Human Protein ◽  
Disease Genes ◽  
Cellular Functions ◽  
The Core

AbstractMacromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing >4,600 total complexes, >7,700 proteins and >56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k-cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations and the map overall shows improved coverage of many disease-associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease.

scholarly journals Prediction of Protein Complexes inTrypanosoma bruceiby Protein Correlation Profiling Mass Spectrometry and Machine Learning

2017 ◽  
Vol 16 (12) ◽  
pp. 2254-2267 ◽  
Author(s):  
Thomas W. M. Crozier ◽  
Michele Tinti ◽  
Mark Larance ◽  
Angus I. Lamond ◽  
Michael A. J. Ferguson
Keyword(s):  
Machine Learning ◽  
Mass Spectrometry ◽  
Protein Complexes

Ion mobility-mass spectrometry of charge-reduced protein complexes reveals general trends in the collisional ejection of compact subunits

The Analyst ◽  
2015 ◽  
Vol 140 (20) ◽  
pp. 7020-7029 ◽  
Author(s):  
Russell E. Bornschein ◽  
Brandon T. Ruotolo
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Total Protein ◽  
Quaternary Structure ◽  
Protein Complexes ◽  
Complex Mixtures ◽  
Ion Mobility Mass Spectrometry ◽  
Cellular Functions ◽  
Multiprotein Complexes ◽  
Wide Range

Multiprotein complexes have been shown to play critical roles across a wide range of cellular functions, but most probes of protein quaternary structure are limited in their ability to analyze complex mixtures and polydisperse structures using small amounts of total protein.

Investigation of the Self-Assembly Pathway of Pentanuclear Helicates by Electrospray Mass Spectrometry

1996 ◽  
Vol 2 (11) ◽  
pp. 1395-1398 ◽  
Author(s):  
Annie Marquis-Rigault ◽  
Annick Dupont-Gervais ◽  
Alain Van Dorsselaer ◽  
Jean-Marie Lehn
Keyword(s):  
Mass Spectrometry ◽  
Self Assembly ◽  
Electrospray Mass Spectrometry ◽  
The Self ◽  
Assembly Pathway
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