Can infrared spectroscopy provide information on protein–protein interactions?

2010 ◽  
Vol 38 (4) ◽  
pp. 940-946 ◽  
Author(s):  
Parvez I. Haris
Keyword(s):  
Infrared Spectroscopy ◽  
Ir Spectroscopy ◽  
Conformational Changes ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Physical Phenomenon ◽  
Interacting Proteins ◽  
Protein Protein Interactions ◽  
Large Shift ◽  
Amide Bonds

For most biophysical techniques, characterization of protein–protein interactions is challenging; this is especially true with methods that rely on a physical phenomenon that is common to both of the interacting proteins. Thus, for example, in IR spectroscopy, the carbonyl vibration (1600–1700 cm−1) associated with the amide bonds from both of the interacting proteins will overlap extensively, making the interpretation of spectral changes very complicated. Isotope-edited infrared spectroscopy, where one of the interacting proteins is uniformly labelled with 13C or 13C,15N has been introduced as a solution to this problem, enabling the study of protein–protein interactions using IR spectroscopy. The large shift of the amide I band (approx. 45 cm−1 towards lower frequency) upon 13C labelling of one of the proteins reveals the amide I band of the unlabelled protein, enabling it to be used as a probe for monitoring conformational changes. With site-specific isotopic labelling, structural resolution at the level of individual amino acid residues can be achieved. Furthermore, the ability to record IR spectra of proteins in diverse environments means that isotope-edited IR spectroscopy can be used to structurally characterize difficult systems such as protein–protein complexes bound to membranes or large insoluble peptide/protein aggregates. In the present article, examples of application of isotope-edited IR spectroscopy for studying protein–protein interactions are provided.

scholarly journals Contacts-based prediction of binding affinity in protein–protein complexes

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Anna Vangone ◽  
Alexandre MJJ Bonvin
Keyword(s):  
Binding Affinity ◽  
Conformational Changes ◽  
Protein Interactions ◽  
Prediction Accuracy ◽  
Protein Complexes ◽  
Structural Features ◽  
Specific Protein ◽  
Strong Impact ◽  
Protein Protein Interactions ◽  
Almost All

Almost all critical functions in cells rely on specific protein–protein interactions. Understanding these is therefore crucial in the investigation of biological systems. Despite all past efforts, we still lack a thorough understanding of the energetics of association of proteins. Here, we introduce a new and simple approach to predict binding affinity based on functional and structural features of the biological system, namely the network of interfacial contacts. We assess its performance against a protein–protein binding affinity benchmark and show that both experimental methods used for affinity measurements and conformational changes have a strong impact on prediction accuracy. Using a subset of complexes with reliable experimental binding affinities and combining our contacts and contact-types-based model with recent observations on the role of the non-interacting surface in protein–protein interactions, we reach a high prediction accuracy for such a diverse dataset outperforming all other tested methods.

scholarly journals Improved prediction of protein-protein interactions using AlphaFold2

2021 ◽  
Author(s):  
Patrick Bryant ◽  
Gabriele Pozzati ◽  
Arne Elofsson
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Interacting Proteins ◽  
Bacterial Protein ◽  
Protein Protein Interactions ◽  
Multiple Sequence ◽  
Test Set ◽  
Interacting Protein ◽  
Identification Rate ◽  
Homologous Sequences

Abstract Predicting the structure of interacting protein chains is fundamental for understanding the function of proteins. Here, we examine the use of AlphaFold2 (AF2) for predicting the structure of heterodimeric protein complexes. We find that using the default AF2 protocol, 44% of the models in a test set can be predicted accurately. However, by optimising the multiple sequence alignment, we can increase the accuracy to 59%. In comparison, the alternative fold-and-dock method RoseTTAFold is only successful in 10% of the cases on this set, template-based docking 35% and traditional docking methods 22%. We can distinguish acceptable (DockQ>0.23) from incorrect models with an AUC of 0.85 on the test set by analysing the predicted interfaces. The success is higher for bacterial protein pairs, pairs with large interaction areas consisting of helices or sheets, and many homologous sequences. Further, we test the possibility to distinguish interacting from non-interacting proteins and find that by analysing the predicted interfaces, we can separate truly interacting from non-interacting proteins with an AUC of 0.82 in the ROC curve, compared to 0.76 with a recently published method. In addition, when using a more realistic negative set, including mammalian proteins, the identification rate remains (AUC=0.83), resulting in that 27% of interactions can be identified at a 1% FPR. All scripts and tools to run our protocol are freely available at: https://gitlab.com/ElofssonLab/FoldDock.

scholarly journals Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Lei Yang ◽  
Xianglong Tang
Keyword(s):  
Gene Ontology ◽  
Protein Interactions ◽  
Protein Complexes ◽  
False Negative ◽  
Biological Database ◽  
Interacting Proteins ◽  
Ppi Network ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Biological Meaning

Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO) annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP) and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

scholarly journals Investigation of protein–protein interactions by isotope‒edited Fourier transformed infrared spectroscopy

2004 ◽  
Vol 18 (3) ◽  
pp. 397-406 ◽  
Author(s):  
Tiansheng Li
Keyword(s):  
Ftir Spectroscopy ◽  
Conformational Changes ◽  
Protein Interactions ◽  
Isotope Labeling ◽  
Structural Information ◽  
Protein Complexes ◽  
Secondary Structures ◽  
Receptor Complex ◽  
Protein Protein Interactions

Recent advance in FTIR spectroscopy has shown the usefulness of13C uniform isotope labeling in proteins to study protein–protein interactions.13C uniform isotope labeling can significantly resolve the spectral overlap in the amide I/I′ region in the spectra of protein–protein complexes, and therefore allows more accurate determination of secondary structures of individual protein component in the complex than does the conventional FTIR spectroscopy. Only a limited number of biophysical techniques can be used effectively to obtain structural information of large protein–protein complex in solution. Though X‒ray crystallography and NMR have been used to provide structural information of proteins at atomic resolution, they are limited either by the ability of protein to crystallize or the large molecular weight of protein. Vibrational spectroscopy, including FTIR and Raman spectroscopies, has been extensively employed to investigate secondary structures and conformational dynamics of protein–protein complexes. However, significant spectral overlap in the amide I/Iʹ region in the spectra of protein–protein complexes often hinders the utilization of vibrational spectroscopy in the study of protein–protein complex. In this review, we shall discuss our recent work involving the application of isotope labeled FTIR to the investigation of protein–protein complexes such as cytokine–receptor complexes. One of the examples involves G‒CSF/receptor complex. To determine unambiguously the conformations of G‒CSF and the receptor in the complex, we have prepared uniformly13C/15N isotope labeled G‒CSF to resolve its amide Iʹ band from that of its receptor in the IR spectrum of the complex. Conformational changes and structural stability of individual protein subunit in G‒CSF/receptor complex have then been investigated by using FTIR spectroscopy (Li et al.,Biochemistry29 (1997), 8849–8859). Another example involves BDNF/trkB complex in which13C/15N uniformly labeled BDNF is complexed with its receptor trkB (Li et al.,Biopolymers67(1) (2002), 10–19). Interactions of13C/15N uniformly labeled brain‒derived neurotrophic factor (BDNF) with the extracellular domain of its receptor, trkB, have been investigated by employing FTIR spectroscopy. Conformational changes and structural stability and dynamics of BDNF/trkB complex have been determined unambiguously by FTIR spectroscopy, since amide I/Iʹ bands of13C/15N labeled BDNF are resolved from those of the receptor. Together, those studies have shown that isotope edited FTIR spectroscopy can be successfully applied to the determination of protein secondary structures of protein complexes containing either the same or different types of secondary structures. It was observed that13C/15N uniform labeling also affects significantly the frequency of amide IIʹ band, which may permit the determination of hydrogen–deuterium exchange in individual subunit of protein–protein complexes.

scholarly journals Split-miniSOG for detecting and localizing intracellular protein-protein interactions: application to correlated light and electron microscopy

2018 ◽  
Author(s):  
Daniela Boassa ◽  
Sakina P. Lemieux ◽  
Varda Lev-Ram ◽  
Junru Hu ◽  
Qing Xiong ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Light And Electron Microscopy ◽  
Interacting Proteins ◽  
Protein Protein Interactions ◽  
Intracellular Protein ◽  
Fluorescence Light Microscopy ◽  
Fluorescence Light ◽  
Protein Complementation

AbstractA protein complementation assay (PCA) for detecting and localizing intracellular protein-protein interactions (PPIs) was built by bisection of miniSOG, a fluorescent flavoprotein derived from the light, oxygen, voltage (LOV)-2 domain of Arabidopsis phototropin. When brought together by interacting proteins, the fragments reconstitute a functional reporter that permits tagged protein complexes to be visualized by fluorescence light microscopy (LM), and then by standard as well as “multicolor” electron microscopy (EM) imaging methods via the photooxidation of 3-3’-diaminobenzidine (DAB) and its lanthanide-conjugated derivatives.

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

2019 ◽  
Vol 26 (21) ◽  
pp. 3890-3910 ◽  
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.

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

2020 ◽  
Vol 27 (37) ◽  
pp. 6306-6355 ◽  
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.

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

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.

scholarly journals POT1-TPP1 differentially regulates telomerase via POT1 His266 and as a function of single-stranded telomere DNA length

2019 ◽  
Vol 116 (47) ◽  
pp. 23527-23533 ◽  
Author(s):  
Mengyuan Xu ◽  
Janna Kiselar ◽  
Tawna L. Whited ◽  
Wilnelly Hernandez-Sanchez ◽  
Derek J. Taylor
Keyword(s):  
Conformational Changes ◽  
Protein Interactions ◽  
Environmental Changes ◽  
Lymphocytic Leukemia ◽  
Protein Protein Interactions ◽  
Cellular Environment ◽  
Multiple Protein ◽  
Linear Chromosomes ◽  
Hydroxyl Radical Footprinting ◽  
Regulate Telomere Length

Telomeres cap the ends of linear chromosomes and terminate in a single-stranded DNA (ssDNA) overhang recognized by POT1-TPP1 heterodimers to help regulate telomere length homeostasis. Here hydroxyl radical footprinting coupled with mass spectrometry was employed to probe protein–protein interactions and conformational changes involved in the assembly of telomere ssDNA substrates of differing lengths bound by POT1-TPP1 heterodimers. Our data identified environmental changes surrounding residue histidine 266 of POT1 that were dependent on telomere ssDNA substrate length. We further determined that the chronic lymphocytic leukemia-associated H266L substitution significantly reduced POT1-TPP1 binding to short ssDNA substrates; however, it only moderately impaired the heterodimer binding to long ssDNA substrates containing multiple protein binding sites. Additionally, we identified a telomerase inhibitory role when several native POT1-TPP1 proteins coat physiologically relevant lengths of telomere ssDNA. This POT1-TPP1 complex-mediated inhibition of telomerase is abrogated in the context of the POT1 H266L mutation, which leads to telomere overextension in a malignant cellular environment.

Quantitative analysis of the interactions between HIV-1 integrase and retroviral reverse transcriptases

2008 ◽  
Vol 412 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Alon Herschhorn ◽  
Iris Oz-Gleenberg ◽  
Amnon Hizi
Keyword(s):  
Conformational Changes ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Reaction Model ◽  
Protein Protein Interactions ◽  
Common Site ◽  
Leukaemia Virus ◽  
Reverse Transcriptases ◽  
Interaction Kinetics ◽  
Hiv 1

The RT (reverse transcriptase) of HIV-1 interacts with HIV-1 IN (integrase) and inhibits its enzymatic activities. However, the molecular mechanisms underling these interactions are not well understood. In order to study these mechanisms, we have analysed the interactions of HIV-1 IN with HIV-1 RT and with two other related RTs: those of HIV-2 and MLV (murine-leukaemia virus). All three RTs inhibited HIV-1 IN, albeit to a different extent, suggesting a common site of binding that could be slightly modified for each one of the studied RTs. Using surface plasmon resonance technology, which monitors direct protein–protein interactions, we performed kinetic analyses of the binding of HIV-1 IN to these three RTs and observed interesting binding patterns. The interaction of HIV-1 RT with HIV-1 IN was unique and followed a two-state reaction model. According to this model, the initial IN–RT complex formation was followed by a conformational change in the complex that led to an elevation of the total affinity between these two proteins. In contrast, HIV-2 and MLV RTs interacted with IN in a simple bi-molecular manner, without any apparent secondary conformational changes. Interestingly, HIV-1 and HIV-2 RTs were the most efficient inhibitors of HIV-1 IN activity, whereas HIV-1 and MLV RTs showed the highest affinity towards HIV-1 IN. These modes of direct protein interactions, along with the apparent rate constants calculated and the correlations of the interaction kinetics with the capacity of the RTs to inhibit IN activities, are all discussed.

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