Defining protein-protein interactions (PPIs) in their native environment is crucial to understanding protein structure and function. Cross-linking-mass spectrometry (XL-MS) has proven effective in ...capturing PPIs in living cells; however, the proteome coverage remains limited. Here, we have developed a robust in vivo XL-MS platform to facilitate in-depth PPI mapping by integrating a multifunctional MS-cleavable cross-linker with sample preparation strategies and high-resolution MS. The advancement of click chemistry-based enrichment significantly enhanced the detection of cross-linked peptides for proteome-wide analyses. This platform enabled the identification of 13,904 unique lysine-lysine linkages from in vivo cross-linked HEK 293 cells, permitting construction of the largest in vivo PPI network to date, comprising 6,439 interactions among 2,484 proteins. These results allowed us to generate a highly detailed yet panoramic portrait of human interactomes associated with diverse cellular pathways. The strategy presented here signifies a technological advancement for in vivo PPI mapping at the systems level and can be generalized for charting protein interaction landscapes in any organisms.
Proximity‐dependent biotin identification (BioID) is a recently developed method that allows the identification of proteins in the close vicinity of a protein of interest in living cells. BioID ...relies on fusion of the protein of interest with a mutant form of the biotin ligase enzyme BirA (BirA*) that is capable of promiscuously biotinylating proximal proteins irrespective of whether these interact directly or indirectly with the fusion protein or are merely located in the same subcellular neighborhood. The covalent addition of biotin allows the labeled proteins to be purified from cell extracts on the basis of their affinity for streptavidin and identified by mass spectrometry. To date, BioID has been successfully applied to study a variety of proteins and processes in mammalian cells and unicellular eukaryotes and has been shown to be particularly suited to the study of insoluble or inaccessible cellular structures and for detecting weak or transient protein associations. Here, we provide an introduction to BioID, together with a detailed summary of where and how the method has been applied to date, and briefly discuss technical aspects involved in the planning and execution of a BioID study.
The HDOCK server (http://hdock.phys.hust.edu.cn/) is a highly integrated suite of homology search, template-based modeling, structure prediction, macromolecular docking, biological information ...incorporation and job management for robust and fast protein-protein docking. With input information for receptor and ligand molecules (either amino acid sequences or Protein Data Bank structures), the server automatically predicts their interaction through a hybrid algorithm of template-based and template-free docking. The HDOCK server distinguishes itself from similar docking servers in its ability to support amino acid sequences as input and a hybrid docking strategy in which experimental information about the protein-protein binding site and small-angle X-ray scattering can be incorporated during the docking and post-docking processes. Moreover, HDOCK also supports protein-RNA/DNA docking with an intrinsic scoring function. The server delivers both template- and docking-based binding models of two molecules and allows for download and interactive visualization. The HDOCK server is user friendly and has processed >30,000 docking jobs since its official release in 2017. The server can normally complete a docking job within 30 min.
The intrinsically disordered regions of eukaryotic proteomes are enriched in short linear motifs (SLiMs), which are of crucial relevance for cellular signaling and protein regulation; many mediate ...interactions by providing binding sites for peptide‐binding domains. The vast majority of SLiMs remain to be discovered highlighting the need for experimental methods for their large‐scale identification. We present a novel proteomic peptide phage display (ProP‐PD) library that displays peptides representing the disordered regions of the human proteome, allowing direct large‐scale interrogation of most potential binding SLiMs in the proteome. The performance of the ProP‐PD library was validated through selections against SLiM‐binding bait domains with distinct folds and binding preferences. The vast majority of identified binding peptides contained sequences that matched the known SLiM‐binding specificities of the bait proteins. For SHANK1 PDZ, we establish a novel consensus TxF motif for its non‐C‐terminal ligands. The binding peptides mostly represented novel target proteins, however, several previously validated protein–protein interactions (PPIs) were also discovered. We determined the affinities between the VHS domain of GGA1 and three identified ligands to 40–130 μm through isothermal titration calorimetry, and confirmed interactions through coimmunoprecipitation using full‐length proteins. Taken together, we outline a general pipeline for the design and construction of ProP‐PD libraries and the analysis of ProP‐PD‐derived, SLiM‐based PPIs. We demonstrated the methods potential to identify low affinity motif‐mediated interactions for modular domains with distinct binding preferences. The approach is a highly useful complement to the current toolbox of methods for PPI discovery.
The intrinsically disordered regions of eukaryotic proteomes are enriched in short linear motifs. These compact interfaces provide binding sites for peptide‐binding domains. We present a novel proteomic peptide phage display library that displays peptides directly mapping to disordered regions of the human proteome and validate its performance. This opens for large‐scale analysis of motif‐based interactions.
Negative protein–protein interaction datasets are needed for training and evaluation of interaction prediction methods, as well as validation of high-throughput interaction discovery experiments. In ...large-scale two-hybrid assays, the direct interaction of a large number of protein pairs is systematically probed. We present a simple method to harness two-hybrid data to obtain negative protein–protein interaction datasets, which we validated using other available experimental data. The method identifies interactions that were likely tested but not observed in a two-hybrid screen. For each negative interaction, a confidence score is defined as the shortest-path length between the two proteins in the interaction network derived from the two-hybrid experiment. We show that these high-quality negative datasets are particularly important when a specific biological context is considered, such as in the study of protein interaction specificity. We also illustrate the use of a negative dataset in the evaluation of the InterPreTS interaction prediction method.
Computational approaches aided by computer science have been used to predict essential proteins and are faster than expensive, time-consuming, laborious experimental approaches. However, the ...performance of such approaches is still poor, making practical applications of computational approaches difficult in some fields. Hence, the development of more suitable and efficient computing methods is necessary for identification of essential proteins.
In this paper, we propose a new method for predicting essential proteins in a protein interaction network, local interaction density combined with protein complexes (LIDC), based on statistical analyses of essential proteins and protein complexes. First, we introduce a new local topological centrality, local interaction density (LID), of the yeast PPI network; second, we discuss a new integration strategy for multiple bioinformatics. The LIDC method was then developed through a combination of LID and protein complex information based on our new integration strategy. The purpose of LIDC is discovery of important features of essential proteins with their neighbors in real protein complexes, thereby improving the efficiency of identification.
Experimental results based on three different PPI(protein-protein interaction) networks of Saccharomyces cerevisiae and Escherichia coli showed that LIDC outperformed classical topological centrality measures and some recent combinational methods. Moreover, when predicting MIPS datasets, the better improvement of performance obtained by LIDC is over all nine reference methods (i.e., DC, BC, NC, LID, PeC, CoEWC, WDC, ION, and UC).
LIDC is more effective for the prediction of essential proteins than other recently developed methods.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The design of inhibitors of intracellular protein–protein interactions (PPIs) remains a challenge in chemical biology and drug discovery. We propose a cyclized helix‐loop‐helix (cHLH) peptide as a ...scaffold for generating cell‐permeable PPI inhibitors through bifunctional grafting: epitope grafting to provide binding activity, and arginine grafting to endow cell‐permeability. To inhibit p53–HDM2 interactions, the p53 epitope was grafted onto the C‐terminal helix and six Arg residues were grafted onto another helix. The designed peptide cHLHp53‐R showed high inhibitory activity for this interaction, and computational analysis suggested a binding mode for HDM2. Confocal microscopy of cells treated with fluorescently labeled cHLHp53‐R revealed cell membrane penetration and cytosolic localization. The peptide inhibited the growth of HCT116 and LnCap cancer cells. This strategy of bifunctional grafting onto a well‐structured peptide scaffold could facilitate the generation of inhibitors for intracellular PPIs.
Hard graft: A cyclized helix‐loop‐helix peptide (cyan) was used as a scaffold to generate cell‐permeable PPI inhibitors through bifunctional grafting: epitope grafting for binding activity, and arginine grafting for cell permeability. To inhibit p53–HDM2 interactions, the p53 epitope was grafted onto the C‐terminal helix and six Arg residues were grafted onto the other helix. The resulting peptide showed cell membrane permeability and inhibitory activity for the intracellular PPI.
Protein-protein interactions (PPIs) are conveyed through binding interfaces or surface patches on proteins that become buried upon binding. Structural and biophysical analysis of many protein-protein ...interfaces revealed certain unique features of these surfaces that determine the energetics of interactions and play a critical role in protein evolution. One of the significant aspects of binding interfaces is the presence of binding hot spots, where mutations are highly deleterious for binding. Conversely, binding cold spots are positions occupied by suboptimal amino acids and several mutations in such positions could lead to affinity enhancement. While there are many software programs for identification of hot spot positions, there is currently a lack of software for cold spot detection.
In this paper, we present Cold Spot SCANNER, a Colab Notebook, which scans a PPI binding interface and identifies cold spots resulting from cavities, unfavorable charge-charge, and unfavorable charge-hydrophobic interactions. The software offers a Py3DMOL-based interface that allows users to visualize cold spots in the context of the protein structure and generates a zip file containing the results for easy download.
Cold spot identification is of great importance to protein engineering studies and provides a useful insight into protein evolution. Cold Spot SCANNER is open to all users without login requirements and can be accessible at: https://colab.
google.com/github/sagagugit/Cold-Spot-Scanner/blob/main/Cold_Spot_Scanner.ipynb .
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Linkers or spacers are short amino acid sequences created in nature to separate multiple domains in a single protein. Most of them are rigid and function to prohibit unwanted interactions between the ...discrete domains. However, Gly‐rich linkers are flexible, connecting various domains in a single protein without interfering with the function of each domain. The advent of recombinant DNA technology made it possible to fuse two interacting partners with the introduction of artificial linkers. Often, independent proteins may not exist as stable or structured proteins until they interact with their binding partner, following which they gain stability and the essential structural elements. Gly‐rich linkers have been proven useful for these types of unstable interactions, particularly where the interaction is weak and transient, by creating a covalent link between the proteins to form a stable protein–protein complex. Gly‐rich linkers are also employed to form stable covalently linked dimers, and to connect two independent domains that create a ligand‐binding site or recognition sequence. The lengths of linkers vary from 2 to 31 amino acids, optimized for each condition so that the linker does not impose any constraints on the conformation or interactions of the linked partners. Various structures of covalently linked protein complexes have been described using X‐ray crystallography, nuclear magnetic resonance and cryo‐electron microscopy techniques. In this review, we evaluate several structural studies where linkers have been used to improve protein quality, to produce stable protein–protein complexes, and to obtain protein dimers.
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