Library Of Protein Fragments Research Articles

Deconvolution of Multiple Rab Binding Domains Using the Batch Yeast2-Hybrid Method DEEPN.

A hallmark of functionally significant interactions between Rab proteins and their targets is whether that binding depends on the type of nucleotide bound to the Rab GTPase. A system that can directly compare those sets of interactions mediated by a Rab in its GTP-bound conformation versus its GDP bound conformation would provide a direct route to finding biologically relevant partners. Comprehensive large-scale yeast 2-hybrid assays allow a potential method to compare one interactome against another provided that the same set of potentiallyinteracting partners is interrogated between samples. Here we describe the use of such a yeast 2-hybrid system that lends itself toward comparing pairs of Rab mutants, locked in either their GTP or GDP conformation. Importantly, using a complex library of protein fragments as potential binding ("prey") partners, identification of interacting proteins as well as the domain(s) mediating those interactions can be determined using a series of sequence analyses and binary validation experiments.

Sequence assignment for low-resolution modelling of protein crystal structures.

The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for machine-learning-based docking of main-chain fragments to the sequence and for their sequence-independent connection using a dedicated library of protein fragments. The combined use of these new methods noticeably increases sequence coverage and reduces fragmentation of the protein models automatically built with ARP/wARP.

Interactions of CAF1-NOT complex components from Trypanosoma brucei

The CAF1-NOT complex of Trypanosoma brucei, like that of other eukaryotes, contains several NOT proteins (NOT1, NOT3, NOT3/5, NOT10, and NOT11), NOT9/CAF40, and the CAF1 deadenylase, which targets 3' poly(A) tails. Again like other eukaryotes, deadenylation is the first step in the degradation of most trypanosome mRNAs. In animal cells, destruction of unstable mRNAs is accelerated by proteins that bind the RNA in a sequence-specific fashion, and also recruit the CAF1-NOT complex. However, this has not yet been demonstrated for T. brucei. To find interaction partners for the trypanosome NOT complex, we did a genome-wide yeast two-hybrid screen, using a random shotgun protein fragment library, with the subunits CAF40, NOT2, NOT10 and NOT11 as baits. To assess interaction specificity, we compared the results with those from other trypanosome proteins, including the cyclin-F-box protein CFB1. The yeast 2-hybrid screen yielded four putatively interacting proteins for NOT2, eleven for NOT11, but only one for NOT9/CAF40. Both CFB1 and NOT10 had over a hundred potential interactions, indicating a lack of specificity. Nevertheless, a detected interaction between NOT10 and NOT11 is likely to be genuine. We also identified proteins that co-purify with affinity tagged NOT9/CAF40 by mass spectrometry. The co-purifying proteins did not include the 2-hybrid partner, but the results confirmed NOT9/CAF40 association with the CAF1-NOT complex, and suggested interactions with expression-repressing RNA-binding proteins (ZC3H8, ZC3H30, and ZC3H46) and the deadenylase PARN3.

FRAGSION: ultra-fast protein fragment library generation by IOHMM sampling.

Speed, accuracy and robustness of building protein fragment library have important implications in de novo protein structure prediction since fragment-based methods are one of the most successful approaches in template-free modeling (FM). Majority of the existing fragment detection methods rely on database-driven search strategies to identify candidate fragments, which are inherently time-consuming and often hinder the possibility to locate longer fragments due to the limited sizes of databases. Also, it is difficult to alleviate the effect of noisy sequence-based predicted features such as secondary structures on the quality of fragment. Here, we present FRAGSION, a database-free method to efficiently generate protein fragment library by sampling from an Input-Output Hidden Markov Model. FRAGSION offers some unique features compared to existing approaches in that it (i) is lightning-fast, consuming only few seconds of CPU time to generate fragment library for a protein of typical length (300 residues); (ii) can generate dynamic-size fragments of any length (even for the whole protein sequence) and (iii) offers ways to handle noise in predicted secondary structure during fragment sampling. On a FM dataset from the most recent Critical Assessment of Structure Prediction, we demonstrate that FGRAGSION provides advantages over the state-of-the-art fragment picking protocol of ROSETTA suite by speeding up computation by several orders of magnitude while achieving comparable performance in fragment quality. Source code and executable versions of FRAGSION for Linux and MacOS is freely available to non-commercial users at http://sysbio.rnet.missouri.edu/FRAGSION/ It is bundled with a manual and example data. chengji@missouri.edu Supplementary data are available at Bioinformatics online.

Structure determination of uniformly (13)C, (15)N labeled protein using qualitative distance restraints from MAS solid-state (13)C-NMR observed paramagnetic relaxation enhancement.

Magic angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) is a powerful method for structure determination of insoluble biomolecules. However, structure determination by MAS solid-state NMR remains challenging because it is difficult to obtain a sufficient amount of distance restraints owing to spectral complexity. Collection of distance restraints from paramagnetic relaxation enhancement (PRE) is a promising approach to alleviate this barrier. However, the precision of distance restraints provided by PRE is limited in solid-state NMR because of incomplete averaged interactions and intermolecular PREs. In this report, the backbone structure of the B1 domain of streptococcal protein G (GB1) has been successfully determined by combining the CS-Rosetta protocol and qualitative PRE restraints. The derived structure has a Cα RMSD of 1.49Å relative to the X-ray structure. It is noteworthy that our protocol can determine the correct structure from only three cysteine-EDTA-Mn(2+) mutants because this number of PRE sites is insufficient when using a conventional structure calculation method based on restrained molecular dynamics and simulated annealing. This study shows that qualitative PRE restraints can be employed effectively for protein structure determination from a limited conformational sampling space using a protein fragment library.

내부 알파탄소간 거리와 비네-코시 거리를 사용한 대규모 단백질 조각 라이브러리 구성

Representing protein three-dimensional structure by concatenating a sequence of protein fragments gives an efficient application in analysis, modeling, search, and prediction of protein structures. This paper investigated the effective combination of distance measures, which can exploit large protein structure database, in order to construct a protein fragment library representing native protein structures accurately. Clustering method was used to construct a protein fragment library. Initial clustering stage used inter alpha-carbon distance having low time complexity, and cluster extension stage used the combination of inter alpha-carbon distance, Binet-Cauchy distance, and root mean square deviation. Protein fragment library was constructed by leveraging large protein structure database using the proposed combination of distance measures. This library gives low root mean square deviation in the experiments representing protein structures with protein fragments.

HMM-Based Prediction for Protein Structural Motifs' Two Local Properties: Solvent Accessibility and Backbone Torsion Angles

Protein structure prediction is often assisted by predicting one-dimensional structural properties including relative solvent accessibility (RSA) surface and backbone torsion angles (BTA) of residues, and these two properties are continuously varying variables because proteins can move freely in a three-dimensional space. Instead of subdividing them into a few arbitrarily defined states that many popular approaches used, this paper proposes an integrated system for realvalue prediction of protein structural motifs' two local properties, based on the modified Hidden Markov Model that we previously presented. The model was used to capture the relevance of RSA and the dependency of BTA between adjacent residues along the local protein chain in motifs with definite probabilities. These two properties were predicted according to their own probability distribution. The method was applied to a protein fragment library. For nine different classes of motifs, real values of RSA were predicted with mean absolute error (MAE) of 0.122-0.175 and Pearson's correlation coefficient (PCC) of 0.623-0.714 between predicted and actual RSA. Meanwhile, real values of BTA were obtained with MAE of 8.5⁰-29.4⁰ for Φ angles, 11.2⁰-38.5⁰ for ψ angles and PCC of 0.601-0.716 for Φ, 0.597-0.713 for ψ. The results were compared with well-known Real-SPINE Server, and indicate the proposed method may at least serve as the foundation to obtain better local properties from structural motifs for protein structure prediction.

HMM-Based Prediction for Protein Structural Motifs’ Two Local Properties: Solvent Accessibility and Backbone Torsion Angles

Protein structure prediction is often assisted by predicting one-dimensional structural properties including relative solvent accessibility (RSA) surface and backbone torsion angles (BTA) of residues, and these two properties are continuously varying variables because proteins can move freely in a three-dimensional space. Instead of subdividing them into a few arbitrarily defined states that many popular approaches used, this paper proposes an integrated system for realvalue prediction of protein structural motifs’ two local properties, based on the modified Hidden Markov Model that we previously presented. The model was used to capture the relevance of RSA and the dependency of BTA between adjacent residues along the local protein chain in motifs with definite probabilities. These two properties were predicted according to their own probability distribution. The method was applied to a protein fragment library. For nine different classes of motifs, real values of RSA were predicted with mean absolute error (MAE) of 0.122-0.175 and Pearson’s correlation coefficient (PCC) of 0.623-0.714 between predicted and actual RSA. Meanwhile, real values of BTA were obtained with MAE of 8.50-29.40 for Φ angles, 11.20-38.50 for ψ angles and PCC of 0.601-0.716 for Φ, 0.597-0.713 for ψ. The results were compared with well-known Real-SPINE Server, and indicate the proposed method may at least serve as the foundation to obtain better local properties from structural motifs for protein structure prediction. Keywords: Protein structure predication, structural motifs, hidden Markov model, solvent accessibility surface, backbone torsion angles, directional statistics distribution

Multiplex epitope mapping using bacterial surface display reveals both linear and conformational epitopes.

As antibody-based diagnosis and therapy grow at an increased pace, there is a need for methods which rapidly and accurately determine antibody-antigen interactions. Here, we report a method for the multiplex determination of antibody epitopes using bacterial cell-surface display. A protein-fragment library with 107 cell clones, covering 60 clinically-relevant protein targets, was created and characterized with massively parallel sequencing. Using this multi-target fragment library we determined simultaneously epitopes of commercial monoclonal and polyclonal antibodies targeting PSMA, EGFR, and VEGF. Off-target binding was observed for one of the antibodies, which demonstrates the method´s ability to reveal cross-reactivity. We exemplify the detection of structural epitopes by mapping the therapeutic antibody Avastin. Based on our findings we suggest this method to be suitable for mapping linear and structural epitopes of monoclonal and polyclonal antibodies in a multiplex fashion and could find applicability in serum profiling as well as other protein-protein interaction studies.

Domain Structure and Protein Interactions of the Silent Information Regulator Sir3 Revealed by Screening a Nested Deletion Library of Protein Fragments

Transcriptional silencing in yeast is mediated by the interactions of silent information regulator (Sir) proteins with chromatin and with one another. The stable association of Sir3 with Sir4 is mediated by a C-terminal region of Sir3 that has additional functions including the dimerization of Sir3. We have developed a simple, robust expression screening methodology that allows for the unbiased identification of functional protein domains expressed from nested-deletion libraries of full-length genes. Using these methodologies, Sir3 dimerization was shown to be mediated by two separate domains. One of these domains also binds cooperatively to the C-terminal coiled-coil motif of Sir4 and dimerization further increases the affinity of Sir3 for Sir4. The resulting Sir3-Sir4 complexes form progressively higher order assemblies with increasing protein concentration, with implications for the mechanism of gene silencing.