Cryo-EM Structure of the Photosynthetic LH1-RC Complex from Rhodospirillum rubrum

We present a cryo-EM structure of the light-harvesting-reaction center (LH1-RC) core complex from purple phototrophic bacterium Rhodospirillum (Rsp.) rubrum at 2.76 Å resolution. The LH1 complex forms a closed, slightly elliptical ring structure with 16 αβ-polypeptides surrounding the RC. Our biochemical analysis detected rhodoquinone (RQ) molecules in the purified LH1-RC, and the cryo-EM density map specifically positions RQ at the QA site in the RC. The geranylgeraniol sidechains of bacteriochlorophyll (BChl) aG coordinated by LH1 β-polypeptides exhibit a highly homologous tail-up conformation that allows for interactions with the bacteriochlorin rings of nearby LH1 α-associated BChls aG. The structure also revealed key protein–protein interactions in both N- and C-terminal regions of the LH1 αβ-polypeptides, mainly within a face-to-face structural subunit. Our findings enable to evaluate past experimental and computational results obtained with this widely used organism and provide crucial information for more detailed exploration of light-energy conversion, quinone transport, and structure—function relationships in pigment-protein complexes.

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Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

Current Medicinal Chemistry ◽

10.2174/0929867325666180214113704 ◽

2019 ◽

Vol 26 (21) ◽

pp. 3890-3910 ◽

Cited By ~ 6

Author(s):

Branislava Gemovic ◽

Neven Sumonja ◽

Radoslav Davidovic ◽

Vladimir Perovic ◽

Nevena Veljkovic

Keyword(s):

Drug Discovery ◽

Protein Interactions ◽

Protein Complexes ◽

Experimental Studies ◽

Protein Protein Interactions ◽

Web Based ◽

Prediction Tools ◽

Physiological Processes ◽

Modern Drug ◽

Ppi Prediction

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology. Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions. Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions. Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs. Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.

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Protein Interaction Domains and Post-Translational Modifications: Structural Features and Drug Discovery Applications

Current Medicinal Chemistry ◽

10.2174/0929867326666190620101637 ◽

2020 ◽

Vol 27 (37) ◽

pp. 6306-6355 ◽

Cited By ~ 2

Author(s):

Marian Vincenzi ◽

Flavia Anna Mercurio ◽

Marilisa Leone

Keyword(s):

Drug Discovery ◽

Protein Interaction ◽

Protein Interactions ◽

Structural Information ◽

Protein Complexes ◽

Structural Features ◽

Protein Protein Interactions ◽

Modular Architecture ◽

Post Translational Modifications ◽

Interaction Domains

Background:: Many pathways regarding healthy cells and/or linked to diseases onset and progression depend on large assemblies including multi-protein complexes. Protein-protein interactions may occur through a vast array of modules known as protein interaction domains (PIDs). Objective:: This review concerns with PIDs recognizing post-translationally modified peptide sequences and intends to provide the scientific community with state of art knowledge on their 3D structures, binding topologies and potential applications in the drug discovery field. Method:: Several databases, such as the Pfam (Protein family), the SMART (Simple Modular Architecture Research Tool) and the PDB (Protein Data Bank), were searched to look for different domain families and gain structural information on protein complexes in which particular PIDs are involved. Recent literature on PIDs and related drug discovery campaigns was retrieved through Pubmed and analyzed. Results and Conclusion:: PIDs are rather versatile as concerning their binding preferences. Many of them recognize specifically only determined amino acid stretches with post-translational modifications, a few others are able to interact with several post-translationally modified sequences or with unmodified ones. Many PIDs can be linked to different diseases including cancer. The tremendous amount of available structural data led to the structure-based design of several molecules targeting protein-protein interactions mediated by PIDs, including peptides, peptidomimetics and small compounds. More studies are needed to fully role out, among different families, PIDs that can be considered reliable therapeutic targets, however, attacking PIDs rather than catalytic domains of a particular protein may represent a route to obtain selective inhibitors.

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Frequent assembly of chimeric complexes in the protein interaction network of an interspecies yeast hybrid

Molecular Biology and Evolution ◽

10.1093/molbev/msaa298 ◽

2020 ◽

Author(s):

Rohan Dandage ◽

Caroline M Berger ◽

Isabelle Gagnon-Arsenault ◽

Kyung-Mee Moon ◽

Richard Greg Stacey ◽

...

Keyword(s):

Protein Interactions ◽

Molecular Level ◽

Yeast Species ◽

Protein Complexes ◽

Mitochondrial Protein ◽

Chimeric Protein ◽

Interaction Network ◽

Protein Protein Interactions ◽

Extreme Phenotypes ◽

Yeast Hybrid

Abstract Hybrids between species often show extreme phenotypes, including some that take place at the molecular level. In this study, we investigated the phenotypes of an interspecies diploid hybrid in terms of protein-protein interactions inferred from protein correlation profiling. We used two yeast species, Saccharomyces cerevisiae and Saccharomyces uvarum, which are interfertile, but yet have proteins diverged enough to be differentiated using mass spectrometry. Most of the protein-protein interactions are similar between hybrid and parents, and are consistent with the assembly of chimeric complexes, which we validated using an orthogonal approach for the prefoldin complex. We also identified instances of altered protein-protein interactions in the hybrid, for instance in complexes related to proteostasis and in mitochondrial protein complexes. Overall, this study uncovers the likely frequent occurrence of chimeric protein complexes with few exceptions, which may result from incompatibilities or imbalances between the parental proteins.

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Mass spectrometry-based cross-linking study shows that the Psb28 protein binds to cytochrome b559 in Photosystem II

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1620360114 ◽

2017 ◽

Vol 114 (9) ◽

pp. 2224-2229 ◽

Cited By ~ 18

Author(s):

Daniel A. Weisz ◽

Haijun Liu ◽

Hao Zhang ◽

Sundarapandian Thangapandian ◽

Emad Tajkhorshid ◽

...

Keyword(s):

Mass Spectrometry ◽

Photosystem Ii ◽

Protein Interactions ◽

Protein Complexes ◽

Protein Docking ◽

Cross Linking ◽

Protein Protein Interactions ◽

Cytochrome B559 ◽

Reaction Center Complex ◽

Assembly Intermediate

Photosystem II (PSII), a large pigment protein complex, undergoes rapid turnover under natural conditions. During assembly of PSII, oxidative damage to vulnerable assembly intermediate complexes must be prevented. Psb28, the only cytoplasmic extrinsic protein in PSII, protects the RC47 assembly intermediate of PSII and assists its efficient conversion into functional PSII. Its role is particularly important under stress conditions when PSII damage occurs frequently. Psb28 is not found, however, in any PSII crystal structure, and its structural location has remained unknown. In this study, we used chemical cross-linking combined with mass spectrometry to capture the transient interaction of Psb28 with PSII. We detected three cross-links between Psb28 and the α- and β-subunits of cytochrome b559, an essential component of the PSII reaction-center complex. These distance restraints enable us to position Psb28 on the cytosolic surface of PSII directly above cytochrome b559, in close proximity to the QB site. Protein–protein docking results also support Psb28 binding in this region. Determination of the Psb28 binding site and other biochemical evidence allow us to propose a mechanism by which Psb28 exerts its protective effect on the RC47 intermediate. This study also shows that isotope-encoded cross-linking with the “mass tags” selection criteria allows confident identification of more cross-linked peptides in PSII than has been previously reported. This approach thus holds promise to identify other transient protein–protein interactions in membrane protein complexes.

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Metallocluster transactions: dynamic protein interactions guide the biosynthesis of Fe–S clusters in bacteria

Biochemical Society Transactions ◽

10.1042/bst20180365 ◽

2018 ◽

Vol 46 (6) ◽

pp. 1593-1603 ◽

Cited By ~ 9

Author(s):

Chenkang Zheng ◽

Patricia C. Dos Santos

Keyword(s):

Protein Interactions ◽

Protein Complexes ◽

Specific Protein ◽

Biological Synthesis ◽

Cluster Assembly ◽

Sequence Motifs ◽

Protein Protein Interactions ◽

Cysteine Desulfurase ◽

Wide Range ◽

Domains Of Life

Iron–sulfur (Fe–S) clusters are ubiquitous cofactors present in all domains of life. The chemistries catalyzed by these inorganic cofactors are diverse and their associated enzymes are involved in many cellular processes. Despite the wide range of structures reported for Fe–S clusters inserted into proteins, the biological synthesis of all Fe–S clusters starts with the assembly of simple units of 2Fe–2S and 4Fe–4S clusters. Several systems have been associated with the formation of Fe–S clusters in bacteria with varying phylogenetic origins and number of biosynthetic and regulatory components. All systems, however, construct Fe–S clusters through a similar biosynthetic scheme involving three main steps: (1) sulfur activation by a cysteine desulfurase, (2) cluster assembly by a scaffold protein, and (3) guided delivery of Fe–S units to either final acceptors or biosynthetic enzymes involved in the formation of complex metalloclusters. Another unifying feature on the biological formation of Fe–S clusters in bacteria is that these systems are tightly regulated by a network of protein interactions. Thus, the formation of transient protein complexes among biosynthetic components allows for the direct transfer of reactive sulfur and Fe–S intermediates preventing oxygen damage and reactions with non-physiological targets. Recent studies revealed the importance of reciprocal signature sequence motifs that enable specific protein–protein interactions and consequently guide the transactions between physiological donors and acceptors. Such findings provide insights into strategies used by bacteria to regulate the flow of reactive intermediates and provide protein barcodes to uncover yet-unidentified cellular components involved in Fe–S metabolism.

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A computational interactome and functional annotation for the human proteome

eLife ◽

10.7554/elife.18715 ◽

2016 ◽

Vol 5 ◽

Cited By ~ 32

Author(s):

José Ignacio Garzón ◽

Lei Deng ◽

Diana Murray ◽

Sagi Shapira ◽

Donald Petrey ◽

...

Keyword(s):

Protein Interactions ◽

Protein Complexes ◽

Enrichment Analysis ◽

Human Proteome ◽

Gene Set Enrichment Analysis ◽

Protein Protein Interactions ◽

Functional Relationships ◽

Structural Relationships ◽

Human Proteins ◽

Validation Tests

We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein’s function. We provide annotations for most human proteins, including many annotated as having unknown function.

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Interfacial Peptides as Affinity Modulating Agents of Protein-Protein Interactions

Biomolecules ◽

10.3390/biom12010106 ◽

2022 ◽

Vol 12 (1) ◽

pp. 106

Author(s):

Pavel V. Ershov ◽

Yuri V. Mezentsev ◽

Alexis S. Ivanov

Keyword(s):

Protein Interactions ◽

Targeted Delivery ◽

Protein Complexes ◽

Protein Protein Interactions ◽

Good Efficiency ◽

Cellular Targets ◽

Proteolytic Stability ◽

Clinically Significant

The identification of disease-related protein-protein interactions (PPIs) creates objective conditions for their pharmacological modulation. The contact area (interfaces) of the vast majority of PPIs has some features, such as geometrical and biochemical complementarities, “hot spots”, as well as an extremely low mutation rate that give us key knowledge to influence these PPIs. Exogenous regulation of PPIs is aimed at both inhibiting the assembly and/or destabilization of protein complexes. Often, the design of such modulators is associated with some specific problems in targeted delivery, cell penetration and proteolytic stability, as well as selective binding to cellular targets. Recent progress in interfacial peptide design has been achieved in solving all these difficulties and has provided a good efficiency in preclinical models (in vitro and in vivo). The most promising peptide-containing therapeutic formulations are under investigation in clinical trials. In this review, we update the current state-of-the-art in the field of interfacial peptides as potent modulators of a number of disease-related PPIs. Over the past years, the scientific interest has been focused on following clinically significant heterodimeric PPIs MDM2/p53, PD-1/PD-L1, HIF/HIF, NRF2/KEAP1, RbAp48/MTA1, HSP90/CDC37, BIRC5/CRM1, BIRC5/XIAP, YAP/TAZ–TEAD, TWEAK/FN14, Bcl-2/Bax, YY1/AKT, CD40/CD40L and MINT2/APP.

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Characterization of major chromatin assembly proteins in tetrahymena thermophile using proeomic and molecular evolutionary analyses

10.32920/ryerson.14668284.v1 ◽

2021 ◽

Author(s):

Syed N Shah

Keyword(s):

Protein Interactions ◽

Protein Complexes ◽

Affinity Purification ◽

Regulation Of Gene Expression ◽

Chromatin Assembly ◽

Histone Chaperones ◽

Protein Protein Interactions ◽

Selective Forces ◽

Assembly Proteins

Histones H3/H4 are deposited onto DNA in a replication-dependent or independent fashion by the CAF1 and HIRA protein complexes. Despite the identification of these protein complexes, mechanistic details remain unclear. Recently, we showed that in T. thermophila histone chaperones Nrp1, Asf1 and the Impβ6 importin function together to transport newly synthesized H3/H4 from the cytoplasm to the nucleus. To characterize chromatin assembly proteins in T.thermophila, I used affinity purification combined with mass spectrometry to identify protein-protein interactions of Nrp1, Cac2 subunit of CAF1, HIRA and histone modifying Hat1-complex in T. thermophila. I found that the three-subunit T.thermophila CAF1 complex interacts with Casein Kinase 2 (CKII), possibly accounting for previously reported human CAF1phosphorylation. I also found that Hat2 subunit of HAT1 complex is also shared by CAF1 complex as its Cac3 subunit. This suggests that Hat2/Cac3 might exist in two separate pools of protein complexes. Remarkably, proteomic analysis of Hat2/Cac3 in turn revealed that it forms several complexes with other proteins including SIN3, RXT3, LIN9 and TESMIN, all of which have known roles in the regulation of gene expression. Finally, I asked how selective forces might have impacted on the function of proteins involved in H3/H4 transport. Focusing on NASP which possesses several TPR motifs, I showed that its protein-protein interactions are conserved in T. thermophila. Using molecular evolutionary methods I show that different TPRs in NASP evolve at different rates possibly accounting for the functional diversity observed among different family members.

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Protein-protein docking using learned three-dimensional representations

10.1101/738690 ◽

2019 ◽

Cited By ~ 1

Author(s):

Georgy Derevyanko ◽

Guillaume Lamoureux

Keyword(s):

Protein Interactions ◽

Network Architecture ◽

Protein Complexes ◽

Three Dimensional ◽

Spatial Arrangement ◽

Protein Docking ◽

Protein Protein Interactions ◽

Translational Invariance ◽

Shape Complementarity ◽

Spatial Features

AbstractProtein-protein interactions are determined by a number of hard-to-capture features related to shape complementarity, electrostatics, and hydrophobicity. These features may be intrinsic to the protein or induced by the presence of a partner. A conventional approach to protein-protein docking consists in engineering a small number of spatial features for each protein, and in minimizing the sum of their correlations with respect to the spatial arrangement of the two proteins. To generalize this approach, we introduce a deep neural network architecture that transforms the raw atomic densities of each protein into complex three-dimensional representations. Each point in the volume containing the protein is described by 48 learned features, which are correlated and combined with the features of a second protein to produce a score dependent on the relative position and orientation of the two proteins. The architecture is based on multiple layers of SE(3)-equivariant convolutional neural networks, which provide built-in rotational and translational invariance of the score with respect to the structure of the complex. The model is trained end-to-end on a set of decoy conformations generated from 851 nonredundant protein-protein complexes and is tested on data from the Protein-Protein Docking Benchmark Version 4.0.

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