Linear Protein Sequence Research Articles

Optimizing the cODC degron for Protein Control in Nematode Worms

Caenorhabditis elegans, a nematode worm, is a model multicellular organism for the study of development and disease. Current methods of controlling essential and pleiotropic gene product levels in C. elegans suffer from limitations, including incomplete penetrance, false negatives, and the inability to differentially control multiple genes with the same system simultaneously. Genetic control methods such as loss‐of‐function alleles and CRISPR‐Cas9 targeted genes have proved successful at deducing the relationship between gene function and phenotype; but they lack the ability to investigate genes essential for viability, fertility, and pleiotropic genes that have dissimilar roles in different tissues during the nematode’s lifespan. RNAi is an effective method for studying gene function in C. elegans, it is easy to deliver, can target virtually any sequence, and can be administered at any time during development. However, RNAi suffers from several limitations including: a significant portion of genes cannot be adequately silenced, RNAi cannot enter equally into all tissues, there is a risk of off‐target effects, and the observation that RNAi phenotypes may be delayed if existing proteins persist for long periods of time. Protein degradation methods can overcome many limitations of the genetic methods by genetic fusion of the gene of interest to an inducible protein degradation domain. Some protein control methods lack the ability to target control of protein degradation to specific tissues, while all current methods are limited by the use of a single input signal to control degradation. The overarching goal of this study is to develop a system for complex control of protein function in nematodes using the Latching Orthogonal Cage/Key pRoteins (LOCKR) system, a de novo‐designed protein Switch comprised of a Cage and a Latch that is capable of caging any linear protein sequence. To conditionally control protein levels in nematodes, we will fuse target genes to LOCKR with a cODC degron sequence encoded in the Latch. The interaction of the Cage with the Latch blocks the accessibility of the degron. Introducing a peptide Key releases the Latch, resulting in exposure of the degron sequence and degradation of fused proteins. Here we describe the development of a bacterially‐expressed LOCKR system suitable for in vitro degron optimization. The mEGFP‐degronLOCKR fusion expresses in bacteria and can be purified using immobilized metal affinity chromatography. We hypothesize that when Switch is activated by the Key and the degron is exposed, the mEGFP‐degronLOCKR construct will be degraded in C. elegans lysate. We further predict that various mutations in the degron will affect the rate of target protein degradation. This study will allow more detailed and complex studies of development and disease in C. elegans and may be applicable to other multicellular organisms.

Comprehensive Analysis of Constraint on the Spatial Distribution of Missense Variants in Human Protein Structures

The spatial distribution of genetic variation within proteins is shaped by evolutionary constraint and provides insight into the functional importance of protein regions and the potential pathogenicity of protein alterations. Here, we comprehensively evaluate the 3D spatial patterns of human germline and somatic variation in 6,604 experimentally derived protein structures and 33,144 computationally derived homology models covering 77% of all human proteins. Using a systematic approach, we quantify differences in the spatial distributions of neutral germline variants, disease-causing germline variants, and recurrent somatic variants. Neutral missense variants exhibit a general trend toward spatial dispersion, which is driven by constraint on core residues. In contrast, germline disease-causing variants are generally clustered in protein structures and form clusters more frequently than recurrent somatic variants identified from tumor sequencing. In total, we identify 215 proteins with significant spatial constraints on the distribution of disease-causing missense variants in experimentally derived protein structures, only 65 (30%) of which have been previously reported. This analysis identifies many clusters not detectable from sequence information alone; only 12% of proteins with significant clustering in 3D were identified from similar analyses of linear protein sequence. Furthermore, spatial analyses of mutations in homology-based structural models are highly correlated with those from experimentally derived structures, supporting the use of computationally derived models. Our approach highlights significant differences in the spatial constraints on different classes of mutations in protein structure and identifies regions of potential function within individual proteins.

Predicting physiologically relevant SH3 domain mediated protein-protein interactions in yeast.

Motivation: Many intracellular signaling processes are mediated by interactions involving peptide recognition modules such as SH3 domains. These domains bind to small, linear protein sequence motifs which can be identified using high-throughput experimental screens such as phage display. Binding motif patterns can then be used to computationally predict protein interactions mediated by these domains. While many protein–protein interaction prediction methods exist, most do not work with peptide recognition module mediated interactions or do not consider many of the known constraints governing physiologically relevant interactions between two proteins.Results: A novel method for predicting physiologically relevant SH3 domain-peptide mediated protein–protein interactions in S. cerevisae using phage display data is presented. Like some previous similar methods, this method uses position weight matrix models of protein linear motif preference for individual SH3 domains to scan the proteome for potential hits and then filters these hits using a range of evidence sources related to sequence-based and cellular constraints on protein interactions. The novelty of this approach is the large number of evidence sources used and the method of combination of sequence based and protein pair based evidence sources. By combining different peptide and protein features using multiple Bayesian models we are able to predict high confidence interactions with an overall accuracy of 0.97.Availability and implementation: Domain-Motif Mediated Interaction Prediction (DoMo-Pred) command line tool and all relevant datasets are available under GNU LGPL license for download from http://www.baderlab.org/Software/DoMo-Pred. The DoMo-Pred command line tool is implemented using Python 2.7 and C ++.Contact: gary.bader@utoronto.caSupplementary information: Supplementary data are available at Bioinformatics online.

Computational Prediction of Important Regions in Protein Sequences [Life Sciences

This column summarizes the main approaches for predicting protein functional sites from sequence information. Extracting functional regions from linear protein sequences has many similarities with prototypical problems in signal processing, and some of the methodologies used are taken from this discipline.

On silico peptide microarrays for high-resolution mapping of antibody epitopes and diverse protein-protein interactions

We have developed a novel, silicon-based peptide array for broad biological applications, including potential for development as a real-time point-of-care platform. We employed photolithography on silicon wafers to synthesize microarrays (Intel arrays), containing every possible overlapping peptide within a linear protein sequence covering the N-terminal tail of human histone H2B. Arrays also included peptides with acetylated and methylated lysine residues reflecting post-translational modifications of H2B. We defined minimum binding epitopes for commercial antibodies recognizing modified and unmodified H2B peptides. We further demonstrated that this platform is suitable for highly sensitive methyltransferase and kinase substrate characterization. Intel arrays also revealed specific H2B epitopes recognized by autoantibodies in individuals with systemic lupus erythematosus (SLE) that have increased disease severity. By combining emerging nonfluorescence-based detection methods with an underlying integrated circuit, we are now poised to create a truly transformative proteomics platform with applications in bioscience, drug development, and clinical diagnostics.

BetaSearch: a new method for querying β-residue motifs

BackgroundSearching for structural motifs across known protein structures can be useful for identifying unrelated proteins with similar function and characterising secondary structures such as β-sheets. This is infeasible using conventional sequence alignment because linear protein sequences do not contain spatial information. β-residue motifs are β-sheet substructures that can be represented as graphs and queried using existing graph indexing methods, however, these approaches are designed for general graphs that do not incorporate the inherent structural constraints of β-sheets and require computationally-expensive filtering and verification procedures. 3D substructure search methods, on the other hand, allow β-residue motifs to be queried in a three-dimensional context but at significant computational costs.FindingsWe developed a new method for querying β-residue motifs, called BetaSearch, which leverages the natural planar constraints of β-sheets by indexing them as 2D matrices, thus avoiding much of the computational complexities involved with structural and graph querying. BetaSearch exhibits faster filtering, verification, and overall query time than existing graph indexing approaches whilst producing comparable index sizes. Compared to 3D substructure search methods, BetaSearch achieves 33 and 240 times speedups over index-based and pairwise alignment-based approaches, respectively. Furthermore, we have presented case-studies to demonstrate its capability of motif matching in sequentially dissimilar proteins and described a method for using BetaSearch to predict β-strand pairing.ConclusionsWe have demonstrated that BetaSearch is a fast method for querying substructure motifs. The improvements in speed over existing approaches make it useful for efficiently performing high-volume exploratory querying of possible protein substructural motifs or conformations. BetaSearch was used to identify a nearly identical β-residue motif between an entirely synthetic (Top7) and a naturally-occurring protein (Charcot-Leyden crystal protein), as well as identifying structural similarities between biotin-binding domains of avidin, streptavidin and the lipocalin gamma subunit of human C8.

Peptides or Small Molecules? Different Approaches to Develop More Effective CDK Inhibitors

Cell cycle regulation involves processes crucial to the survival of a cell, including the detection and repair of genetic damage as well as the prevention of uncontrolled cell division. The molecular events that control cell cycle are ordered and directional. Cyclins and cyclin-dependent kinases (CDKs), determine cell progression through the cycle ensuring the orderly coordination of cellular events. Alterations of cell cycle controllers are among the main causes of cancer onset. In the past decades many efforts have been made to develop kinase inhibitors that are able to modulate cyclin and CDK complexes, either by mimicking the function of natural CDK inhibitors, such as p21, p16 and p27, or by modulating the cyclin-CDK complexes or their targets directly. The great debate is whether to use peptides or small molecules. Peptides are more selective being derived by the linear protein sequences, indeed they should mimic the catalytic or the regulatory subunits of the cell cycle controller complexes, but on the other side they usually present poorer pharmacokinetic characteristics. In contrast, small molecules have better pharmacokinetic features but lower specificity because many protein kinases show high sequence similarity within the active site. The purpose of this review article is to provide an overview of the main classes of CDK inhibitors focusing on structure-activity relationship (SAR) studies and discussing the pharmacological and therapeutic implications.

Large-Scale Discovery and Characterization of Protein Regulatory Motifs in Eukaryotes

The increasing ability to generate large-scale, quantitative proteomic data has brought with it the challenge of analyzing such data to discover the sequence elements that underlie systems-level protein behavior. Here we show that short, linear protein motifs can be efficiently recovered from proteome-scale datasets such as sub-cellular localization, molecular function, half-life, and protein abundance data using an information theoretic approach. Using this approach, we have identified many known protein motifs, such as phosphorylation sites and localization signals, and discovered a large number of candidate elements. We estimate that ∼80% of these are novel predictions in that they do not match a known motif in both sequence and biological context, suggesting that post-translational regulation of protein behavior is still largely unexplored. These predicted motifs, many of which display preferential association with specific biological pathways and non-random positioning in the linear protein sequence, provide focused hypotheses for experimental validation.

Analysis of the Intact Surface Layer of Caulobacter crescentus by Cryo-Electron Tomography

The surface layers (S layers) of those bacteria and archaea that elaborate these crystalline structures have been studied for 40 years. However, most structural analysis has been based on electron microscopy of negatively stained S-layer fragments separated from cells, which can introduce staining artifacts and allow rearrangement of structures prone to self-assemble. We present a quantitative analysis of the structure and organization of the S layer on intact growing cells of the Gram-negative bacterium Caulobacter crescentus using cryo-electron tomography (CET) and statistical image processing. Instead of the expected long-range order, we observed different regions with hexagonally organized subunits exhibiting short-range order and a broad distribution of periodicities. Also, areas of stacked double layers were found, and these increased in extent when the S-layer protein (RsaA) expression level was elevated by addition of multiple rsaA copies. Finally, we combined high-resolution amino acid residue-specific Nanogold labeling and subtomogram averaging of CET volumes to improve our understanding of the correlation between the linear protein sequence and the structure at the 2-nm level of resolution that is presently available. The results support the view that the U-shaped RsaA monomer predicted from negative-stain tomography proceeds from the N terminus at one vertex, corresponding to the axis of 3-fold symmetry, to the C terminus at the opposite vertex, which forms the prominent 6-fold symmetry axis. Such information will help future efforts to analyze subunit interactions and guide selection of internal sites for display of heterologous protein segments.

Estimation and efficient computation of the true probability of recurrence of short linear protein sequence motifs in unrelated proteins

BackgroundLarge datasets of protein interactions provide a rich resource for the discovery of Short Linear Motifs (SLiMs) that recur in unrelated proteins. However, existing methods for estimating the probability of motif recurrence may be biased by the size and composition of the search dataset, such that p-value estimates from different datasets, or from motifs containing different numbers of non-wildcard positions, are not strictly comparable. Here, we develop more exact methods and explore the potential biases of computationally efficient approximations.ResultsA widely used heuristic for the calculation of motif over-representation approximates motif probability by assuming that all proteins have the same length and composition. We introduce pv, which calculates the probability exactly. Secondly, the recently introduced SLiMFinder statistic Sig, accounts for multiple testing (across all possible motifs) in motif discovery. However, it approximates the probability of all other possible motifs, occurring with a score of p or less, as being equal to p. Here, we show that the exhaustive calculation of the probability of all possible motif occurrences that are as rare or rarer than the motif of interest, Sig', may be carried out efficiently by grouping motifs of a common probability (i.e. those which have permuted orders of the same residues). Sig'v, which corrects both approximations, is shown to be uniformly distributed in a random dataset when searching for non-ambiguous motifs, indicating that it is a robust significance measure.ConclusionsA method is presented to compute exactly the true probability of a non-ambiguous short protein sequence motif, and the utility of an approximate approach for novel motif discovery across a large number of datasets is demonstrated.

Coping with Viral Diversity in HIV Vaccine Design: A Response to Nickle et al.

Coping with Viral Diversity in HIV Vaccine Design: A Response to Nickle et al.

Construction of a Family of Cys2His2 Zinc Binding Sites in the Hydrophobic Core of Thioredoxin by Structure-Based Design

A semi-automated, rational design strategy has been used to introduce a family of seven single, mononuclear Cys2His2 zinc sites at various locations in the hydrophobic core of Escherichia colithioredoxin, a protein that is normally devoid of metal centers. The electronic absorption spectra of the CoII complexes show that five of these designed proteins bind metal with the intended tetrahedral geometry. The designed sites differ in their metal-binding constants and effects on protein stability. Since these designs are constructed within the same host protein framework, comparison of their behavior allows a qualitative evaluation of dominant factors that contribute to metal-binding and metal-mediated protein stabilization. Metal-binding constants are dominated by steric interactions between the buried, designed coordination sphere and the surrounding protein matrix. Metal-mediated stability is the consequence of differential binding to the native and unfolded states. Increased interactions with the unfolded state decrease the stabilizing effect of metal binding. The affinity for the unfolded state is dependent on the placement of the primary coordination sphere residues within the linear protein sequence. These results indicate that a protein fold can have a remarkably broad potential for accommodating metal-mediated cross-links and suggest strategies for engineering protein stability by constructing metal sites that maximize metal binding to the native state and minimize binding to the unfolded state.

Role of the A+ Helix in Heparin Binding to Protein C Inhibitor

Interactions between proteins and heparin(-like) structures involve electrostatic forces and structural features. Based on charge distributions in the linear sequence of protein C inhibitor (PCI), two positively charged regions of PCI were proposed as possible candidates for this interaction. The first region, the A+ helix, is located at the N-terminus (residues 1-11), whereas the second region, the H helix, is positioned between residues 264 and 280 of PCI. Competition experiments with synthetic peptides based on the sequence of these regions demonstrated that the H helix has the highest affinity for heparin. In contrast to previous observations we found that the A+ helix peptide competed for the interaction of PCI with heparin, but its affinity was much lower than that of the H helix peptide. Recombinant PCI was also used to investigate the role of the A+ helix in heparin binding. Full-length (wild-type) rPCI as well as an A+ helix deletion mutant of PCI (rPCI-delta 2-11) were expressed in baby hamster kidney cells and both had normal inhibition activity with activated protein C and thrombin. The interaction of the recombinant PCIs with heparin was investigated and compared to plasma PCI. The A+ helix deletion mutant showed a decreased affinity for heparin in inhibition reactions with activated protein C and thrombin, but had similar association constants compared to wild-type rPCI. The synthetic A+ helix peptide competed with rPCI-delta w-11 for binding to heparin. This indicated that the interaction between PCI and heparin is fairly non-specific and that the interaction is primarily based on electrostatic interactions. In summary, our data suggest that the H helix of PCI is the main heparin binding region of PCI, but the A+ helix increases the overall affinity for the PCI-heparin interaction by contributing a second positively charged region to the surface of PCI.