1,721,072 research outputs found
A rational route to probing membrane proteins
No full textA recent report describes the design of short peptides that bind specifically to transmembrane regions of integrins, providing an exciting tool for probing the biology of membrane proteins
AVID: An integrative framework for discovering functional relationships among proteins
No full textBackground: Determining the functions of uncharacterized proteins is one of the most pressing problems in the post-genomic era. Large scale protein-protein interaction assays, global mRNA expression analyses and systematic protein localization studies provide experimental information that can be used for this purpose. The data from such experiments contain many false positives and false negatives, but can be processed using computational methods to provide reliable information about protein-protein relationships and protein function. An outstanding and important goal is to predict detailed functional annotation for all uncharacterized proteins that is reliable enough to effectively guide experiments. Results: We present AVID, a computational method that uses a multi-stage learning framework to integrate experimental results with sequence information, generating networks reflecting functional similarities among proteins. We illustrate use of the networks by making predictions of detailed Gene Ontology (GO) annotations in three categories: molecular function, biological process, and cellular component. Applied to the yeast Saccharomyces cerevisiae, AVID provides 37,451 pair-wise functional linkages between 4,191 proteins. These relationships are ~65–78% accurate, as assessed by cross-validation testing. Assignments of highly detailed functional descriptors to proteins, based on the networks, are estimated to be ~67% accurate for GO categories describing molecular function and cellular component and ~52% accurate for terms describing biological process. The predictions cover 1,490 proteins with no previous annotation in GO and also assign more detailed functions to many proteins annotated only with less descriptive terms. Predictions made by AVID are largely distinct from those made by other methods. Out of 37,451 predicted pair-wise relationships, the greatest number shared in common with another method is 3,413. Conclusion: AVID provides three networks reflecting functional associations among proteins. We use these networks to generate new, highly detailed functional predictions for roughly half of the yeast proteome that are reliable enough to drive targeted experimental investigations. The predictions suggest many specific, testable hypotheses. All of the data are available as downloadable files as well as through an interactive website at http://web.mit.edu/biology/keating/AVID. Thus, AVID will be a valuable resource for experimental biologists.National Science Foundation (U.S.) (CAREER award MCB-0347203)Massachusetts Institute of Technolog
Networks of bZIP Protein-Protein Interactions Diversified Over a Billion Years of Evolution
No full textDifferences in biomolecular sequence and function underlie dramatic ranges of appearance and behavior among species. We studied the basic region-leucine zipper (bZIP) transcription factors and quantified bZIP dimerization networks for five metazoan and two single-cell species, measuring interactions in vitro for 2891 protein pairs. Metazoans have a higher proportion of heteromeric bZIP interactions and more network complexity than the single-cell species. The metazoan bZIP interactomes have broadly similar structures, but there has been extensive rewiring of connections compared to the last common ancestor, and each species network is highly distinct. Many metazoan bZIP orthologs and paralogs have strikingly different interaction specificities, and some differences arise from minor sequence changes. Our data show that a shifting landscape of biochemical functions related to signaling and gene expression contributes to species diversity.National Institutes of Health (U.S.) (Award GM067681
Predicting specificity in bZIP coiled-coil protein interactions
Get PDFWe present a method for predicting protein-protein interactions mediated by the coiled-coil motif. When tested on interactions between nearly all human and yeast bZIP proteins, our method identifies 70% of strong interactions while maintaining that 92% of predictions are correct. Furthermore, cross-validation testing shows that including the bZIP experimental data significantly improves performance. Our method can be used to predict bZIP interactions in other genomes and is a promising approach for predicting coiled-coil interactions more generally
Protein binding specificity versus promiscuity
Get PDFInteractions between macromolecules in general, and between proteins in particular, are essential for any life process. Examples include transfer of information, inhibition or activation of function, molecular recognition as in the immune system, assembly of macromolecular structures and molecular machines, and more. Proteins interact with affinities ranging from millimolar to femtomolar and, because affinity determines the concentration required to obtain 50% binding, the amount of different complexes formed is very much related to local concentrations. Although the concentration of a specific binding partner is usually quite low in the cell (nanomolar to micromolar), the total concentration of other macromolecules is very high, allowing weak and non-specific interactions to play important roles. In this review we address the question of binding specificity, that is, how do some proteins maintain monogamous relations while others are clearly polygamous. We examine recent work that addresses the molecular and structural basis for specificity versus promiscuity. We show through examples how multiple solutions exist to achieve binding via similar interfaces and how protein specificity can be tuned using both positive and negative selection (specificity by demand). Binding of a protein to numerous partners can be promoted through variation in which residues are used for binding, conformational plasticity and/or post-translational modification. Natively unstructured regions represent the extreme case in which structure is obtained only upon binding. Many natively unstructured proteins serve as hubs in protein–protein interaction networks and such promiscuity can be of functional importance in biology.National Institutes of Health (U.S.) (Award GM084181)National Institutes of Health (U.S.) (Award GM067681
Generating High-Accuracy Peptide-Binding Data in High Throughput with Yeast Surface Display and SORTCERY
Get PDFLibrary methods are widely used to study protein-protein interactions, and high-throughput screening or selection followed by sequencing can identify a large number of peptide ligands for a protein target. In this chapter, we describe a procedure called "SORTCERY" that can rank the affinities of library members for a target with high accuracy. SORTCERY follows a three-step protocol. First, fluorescence-activated cell sorting (FACS) is used to sort a library of yeast-displayed peptide ligands according to their affinities for a target. Second, all sorted pools are deep sequenced. Third, the resulting data are analyzed to create a ranking. We demonstrate an application of SORTCERY to the problem of ranking peptide ligands for the anti-apoptotic regulator Bcl-xL.National Institute of General Medical Sciences (U.S.) (Award GM096466
SORTCERY—A High–Throughput Method to Affinity Rank Peptide Ligands
No full textUncovering the relationships between peptide and protein sequences and binding properties is critical for successfully predicting, re-designing and inhibiting protein–protein interactions. Systematically collected data that link protein sequence to binding are valuable for elucidating determinants of protein interaction but are rare in the literature because such data are experimentally difficult to generate. Here we describe SORTCERY, a high-throughput method that we have used to rank hundreds of yeast-displayed peptides according to their affinities for a target interaction partner. The procedure involves fluorescence-activated cell sorting of a library, deep sequencing of sorted pools and downstream computational analysis. We have developed theoretical models and statistical tools that assist in planning these stages. We demonstrate SORTCERY's utility by ranking 1026 BH3 (Bcl-2 homology 3) peptides with respect to their affinities for the anti-apoptotic protein Bcl-x[subscript L]. Our results are in striking agreement with measured affinities for 19 individual peptides with dissociation constants ranging from 0.1 to 60 nM. High-resolution ranking can be used to improve our understanding of sequence–function relationships and to support the development of computational models for predicting and designing novel interactions.National Institutes of Health (U.S.) (Award GM096466)German Academic Scholarship Foundation (Grant RE 3111/1-1
SYNZIP Protein Interaction Toolbox: in Vitro and in Vivo Specifications of Heterospecific Coiled-Coil Interaction Domains
Get PDFThe synthetic biology toolkit contains a growing number of parts for regulating transcription and translation, but very few that can be used to control protein association. Here we report characterization of 22 previously published heterospecific synthetic coiled-coil peptides called SYNZIPs. We present biophysical analysis of the oligomerization states, helix orientations, and affinities of 27 SYNZIP pairs. SYNZIP pairs were also tested for interaction in two cell-based assays. In a yeast two-hybrid screen, >85% of 253 comparable interactions were consistent with prior in vitro measurements made using coiled-coil microarrays. In a yeast-signaling assay controlled by coiled-coil mediated scaffolding, 12 SYNZIP pairs were successfully used to down-regulate the expression of a reporter gene following treatment with α-factor. Characterization of these interaction modules dramatically increases the number of available protein interaction parts for synthetic biology and should facilitate a wide range of molecular engineering applications. Summary characteristics of 27 SYNZIP peptide pairs are reported in specification sheets available in the Supporting Information and at the SYNZIP Web site [http://keatingweb.mit.edu/SYNZIP/].National Science Foundation (U.S.) (NSF award MCB 0950233)National Institutes of Health (U.S.) (grant RO1 GM55040)National Institutes of Health (U.S.) (grant PN2 EY016546)National Institutes of Health (U.S.) (grant P50 GMO81879)National Science Foundation (U.S.). Synthetic Biology Engineering Research CenterHoward Hughes Medical Institut
In-silico and in-vitro elucidation of BH3 binding specificity towards Bcl-2
No full textInteractions between Bcl-2-like proteins and BH3 domains play a key role in the regulation of apoptosis. Despite the overall structural similarity of their interaction with helical BH3 domains, Bcl-2-like proteins exhibit an intricate spectrum of binding specificities whose underlying basis is not well understood. Here, we characterize these interactions using Rosetta FlexPepBind, a protocol for the prediction of peptide binding specificity that evaluates the binding potential of different peptides based on structural models of the corresponding peptide–receptor complexes. For two prominent players, Bcl-xL and Mcl-1, we obtain good agreement with a large set of experimental SPOT array measurements and recapitulate the binding specificity of peptides derived by yeast display in a previous study. We extend our approach to a third member of this family, Bcl-2: we test our blind prediction of the binding of 180 BIM-derived peptides with a corresponding experimental SPOT array. Both prediction and experiment reveal a Bcl-2 binding specificity pattern that resembles that of Bcl-xL. Finally, we extend this application to accurately predict the specificity pattern of additional human BH3-only derived peptides. This study characterizes the distinct patterns of binding specificity of BH3-only derived peptides for the Bcl-2 like proteins Bcl-xL, Mcl-1, and Bcl-2 and provides insight into the structural basis of determinants of specificity.National Institutes of Health (U.S.) (R01GM84181
Structure-Based Redesign of the Binding Specificity of Anti-Apoptotic Bcl-x[subscript L]
No full textMany native proteins are multi-specific and interact with numerous partners, which can confound analysis of their functions. Protein design provides a potential route to generating synthetic variants of native proteins with more selective binding profiles. Redesigned proteins could be used as research tools, diagnostics or therapeutics. In this work, we used a library screening approach to reengineer the multi-specific anti-apoptotic protein Bcl-x[subscript L] to remove its interactions with many of its binding partners, making it a high-affinity and selective binder of the BH3 region of pro-apoptotic protein Bad. To overcome the enormity of the potential Bcl-x[subscript L] sequence space, we developed and applied a computational/experimental framework that used protein structure information to generate focused combinatorial libraries. Sequence features were identified using structure-based modeling, and an optimization algorithm based on integer programming was used to select degenerate codons that maximally covered these features. A constraint on library size was used to ensure thorough sampling. Using yeast surface display to screen a designed library of Bcl-x[subscript L] variants, we successfully identified a protein with ~ 1000-fold improvement in binding specificity for the BH3 region of Bad over the BH3 region of Bim. Although negative design was targeted only against the BH3 region of Bim, the best redesigned protein was globally specific against binding to 10 other peptides corresponding to native BH3 motifs. Our design framework demonstrates an efficient route to highly specific protein binders and may readily be adapted for application to other design problems.National Institutes of Health (U.S.) (Award GM084181
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