An integrated probabilistic model for functional prediction of proteins.

We develop an integrated probabilistic model to combine protein physical interactions, genetic interactions, highly correlated gene expression networks, protein complex data, and domain structures of individual proteins to predict protein functions. The model is an extension of our previous model for protein function prediction based on Markovian random field theory. The model is flexible in that other protein pairwise relationship information and features of individual proteins can be easily incorporated. Two features distinguish the integrated approach from other available methods for protein function prediction. One is that the integrated approach uses all available sources of information with different weights for different sources of data. It is a global approach that takes the whole network into consideration. The second feature is that the posterior probability that a protein has the function of interest is assigned. The posterior probability indicates how confident we are about assigning the function to the protein. We apply our integrated approach to predict functions of yeast proteins based upon MIPS protein function classifications and upon the interaction networks based on MIPS physical and genetic interactions, gene expression profiles, tandem affinity purification (TAP) protein complex data, and protein domain information. We study the recall and precision of the integrated approach using different sources of information by the leave-one-out approach. In contrast to using MIPS physical interactions only, the integrated approach combining all of the information increases the recall from 57% to 87% when the precision is set at 57%-an increase of 30%.     

Proteomic analysis of native metabotropic glutamate receptor 5 protein complexes reveals novel molecular constituents

We used a proteomic approach to identify novel proteins that may regulate metabotropic glutamate receptor 5 (mGluR5) responses by direct or indirect protein interactions. This approach does not rely on the heterologous expression of proteins and offers the advantage of identifying protein interactions in a native environment. The mGluR5 protein was immunoprecipitated from rat brain lysates; co-immunoprecipitating proteins were analyzed by mass spectrometry and identified peptides were matched to protein databases to determine the correlating parent proteins. This proteomic approach revealed the interaction of mGluR5 with known regulatory proteins, as well as novel proteins that reflect previously unidentified molecular constituents of the mGluR5-signaling complex. Immunoblot analysis confirmed the interaction of high confidence proteins, such as phosphofurin acidic cluster sorting protein 1, microtubule-associated protein 2a and dynamin 1, as mGluR5-interacting proteins. These studies show that a proteomic approach can be used to identify candidate interacting proteins. This approach may be particularly useful for neurobiology applications where distinct protein interactions within a signaling complex can dramatically alter the outcome of the response to neurotransmitter release, or the disruption of normal protein interactions can lead to severe neurological and psychiatric disorders.     

A new approach for extracting information from protein dynamics

Increased ability to predict protein structures is moving research focus towards understanding protein dynamics. A promising approach is to represent protein dynamics through networks and take advantage of well-developed methods from network science. Most studies build protein dynamics networks from correlation measures, an approach that only works under very specific conditions, instead of the more robust inverse approach. Thus, we apply the inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates, to avoid structural alignment. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable, robust, and relevant to the allosteric pathway sites. We further use our approach to detect dynamical differences, despite structural similarity, for Siglec-8 in the immune system, and the SARS-CoV-2 spike protein. Our study demonstrates that using the inverse approach to extract a network from protein dynamics yields important biophysical insights.     

Expression,purification, and characterization of proteins from high-quality combinatorial libraries of the mammalian calmodulin central linker

Combinatorial libraries offer an attractive approach towards exploring protein sequence, structure and function. Although several strategies introduce sequence diversity, the likelihood of identifying proteins with novel functions is increased when the library of genes encodes for folded and soluble structures. Here we present the first application of the binary patterning approach of combinatorial protein library design to the unique central linker region of the highly-conserved protein, calmodulin (CaM). We show that this high-quality approach translates very well to the CaM protein scaffold: All library members over-express and are functionally diverse, having a range of conformations in the presence and absence of calcium as determined by circular dichroism spectroscopy. Collectively, these data support that the binary patterning approach, when applied to the highly-conserved protein fold, can yield large collections of folded, soluble and highly-expressible proteins.     

Construction of a modular yeast two-hybrid cDNA library from human EST clones for the human genome protein linkage map

Identification of all human protein–protein interactions will lead to a global human protein linkage map that will provide important information for functional genomics studies. The yeast two-hybrid system is a powerful molecular genetic approach for studying protein–protein interactions. To apply this technology to generate a human protein linkage map, the first step is to construct two-hybrid cDNA libraries that cover the entire human genome. With a homologous recombination-mediated approach, we have constructed a modular human EST-derived yeast two-hybrid library in the Gal4 activation domain-based vector, pACT2. Quality analysis of this library indicated that the approach of constructing two-hybrid cDNA libraries from individually arrayed human EST clones is feasible, and such a two-hybrid library is suitable for detecting protein–protein interactions. This is also the first time that a comprehensive two-hybrid system cDNA library has been constructed from a collection of individually arrayed EST clones.     

Effective handling of induced-fit motion in flexible docking

For structure-based drug design, where various ligand structures need to be docked to a target protein structure, a docking method that can handle conformational flexibility of not only the ligand, but also the protein, is indispensable. We have developed a simple and effective approach for dealing with the local induced-fit motion of the target protein, and implemented it in our docking tool, ADAM. Our approach efficiently combines the following two strategies: a vdW-offset grid in which the protein cavity is enlarged uniformly, and structure optimization allowing the motion of ligand and protein atoms. To examine the effectiveness of our approach, we performed docking validation studies, including redocking in 18 test cases and foreign-docking, in which various ligands from foreign crystal structures of complexes are docked into a target protein structure, in 22 cases (on five target proteins). With the original ADAM, the correct docking modes (RMSD < 2.0 A) were not present among the top 20 models in one case of redocking and four cases of foreign-docking. When the handling of induced-fit motion was implemented, the correct solutions were acquired in all 40 test cases. In foreign-docking on thymidine kinase, the correct docking modes were obtained as the top-ranked solutions for all 10 test ligands by our combinatorial approach, and this appears to be the best result ever reported with any docking tool. The results of docking validation have thus confirmed the effectiveness of our approach, which can provide reliable docking models even in the case of foreign-docking, where conformational change of the target protein cannot be ignored. We expect that this approach will contribute substantially to actual drug design, including virtual screening.     

基于氨基酸序列预测蛋白质功能性点突变位点

突变是研究蛋白质结构和功能的重要方法。点突变实验中,突变位点的选择随机性大,若能对突变后蛋白质功能是否发生变化做出预测,将大大减少实验的盲目性。为此,作者设计了一个基于信号处理的单点替换突变预测模型,对序列上每个位点所有可能的氨基酸替换的效果进行估计。使用蛋白质突变数据库(Protein Mutant Database,PMD)里的11个蛋白共2600多个点突变的数据集,对以上模型进行了验证。结果表明正确率高达81.2%,并且推荐出的替换选择位点仅占所有可能替换突变的3.1%。在体外定点突变实验中,使用本模型推荐的高可能性功能突变位点将有助于提高实验的成功率。该模型使用蛋白质的氨基酸序列信息,特别是对未知结构的蛋白质同样适用。然而,由于缺乏足够的突变实验数据,本模型的应用仍需进一步完善和验证。     

New approach to evaluating the effects of a drug on protein complexes with quantitative proteomics,using the SILAC method and bioinformatic approach

ABSTRACT

Protein–protein interactions (PPIs) lead the formation of protein complexes that perform biochemical reactions that maintain the living state of the living cell. Although therapeutic drugs should influence the formation of protein complexes in addition to PPI network, the methodology analyzing such influences remain to be developed. Here, we demonstrate that a new approach combining HPLC (high performance liquid chromatography) for separating protein complexes, and the SILAC (stable isotope labeling using amino acids in cell culture) method for relative protein quantification, enable us to identify the protein complexes influenced by a drug. We applied this approach to the analysis of thalidomide action on HepG2 cells, assessed the identified proteins by clustering data analyses, and assigned 135 novel protein complexes affected by the drug. We propose that this approach is applicable to elucidating the mechanisms of actions of other therapeutic drugs on the PPI network, and the formation of protein complexes.     

Use of solution-IEF-fractionation leads to separation of 2673 mouse brain proteins including 255 hydrophobic structures

Analyzing complex protein mixtures on a single gel does not allow separation of many extracted proteins. Herein, we tried a prefractionation approach and mouse brain proteins were separated on a narrow pH range ZOOM-IEF Fractionator (MicroSol-IEF device) and run on two-dimensional gel electrophoresis. A total number of 2673 protein spots including 255 hydrophobic structures were successfully analyzed by mass spectrometry. This nonsophisticated approach to increase protein identification of a brain protein extract is a step forward in neurochemistry.     

On-line casein micelle disruption for downstream purification of recombinant human myelin basic protein produced in the milk of transgenic cows

Downstream purification of a model recombinant protein (human myelin basic protein) from milk of transgenic cows is described. The recombinant protein was expressed as a His tagged fusion protein in the milk of transgenic cows and was found associated with the casein micellar phase. While difficulties in obtaining good recoveries were found when employing conventional micelle disruption procedures, direct capture using the cation exchanger SP Sepharose Big Beads? was found successful in the extraction of the recombinant protein. Early breakthrough suggested a slow release of the recombinant protein from the micelles and dictated micelle disruption in order to obtain good yields. A new approach for deconstruction of the calcium core of the casein micelles, employing the interaction between the micellar calcium and the active sites of the cation exchanger resin was developed. Milk samples were loaded to the column in aliquots with a column washing step after each aliquot. This sequential loading approach successfully liberated the recombinant protein from the micelles and was found superior to the conventional sample loading approach. It increased the recovery by more than 25%, reduced fouling due to milk components and improved the column hydrodynamic properties as compared to the conventional sample loading approach. Hardware and software modifications to the chromatography system were necessary in order to keep the whole process automated. A second purification step using a Ni²⁺ affinity column was used to isolate the recombinant protein at purity more than 90% and a recovery percentage of 78%.     

Facile tethering of stable and unstable proteins for optical tweezers experiments

Single-molecule force spectroscopy with optical tweezers has emerged as a powerful tool for dissecting protein folding. The requirement to stably attach “molecular handles” to specific points in the protein of interest by preparative biochemical techniques is a limiting factor in applying this methodology, especially for large or unstable proteins that are difficult to produce and isolate. Here, we present a streamlined approach for creating stable and specific attachments using autocatalytic covalent tethering. The high specificity of coupling allowed us to tether ribosome-nascent chain complexes, demonstrating its suitability for investigating complex macromolecular assemblies. We combined this approach with cell-free protein synthesis, providing a facile means of preparing samples for single-molecule force spectroscopy. The workflow eliminates the need for biochemical protein purification during sample preparation for single-molecule measurements, making structurally unstable proteins amenable to investigation by this powerful single-molecule technique. We demonstrate the capabilities of this approach by carrying out pulling experiments with an unstructured domain of elongation factor G that had previously been refractory to analysis. Our approach expands the pool of proteins amenable to folding studies, which should help to reduce existing biases in the currently available set of protein folding models.     

Study and prediction of secondary structure for membrane proteins

In this paper we present a novel approach to membrane protein secondary structure prediction based on the statistical stepwise discriminant analysis method. A new aspect of our approach is the possibility to derive physical-chemical properties that may affect the formation of membrane protein secondary structure. The certain physical-chemical properties of protein chains can be used to clarify the formation of the secondary structure types under consideration. Another aspect of our approach is that the results of multiple sequence alignment, or the other kinds of sequence alignment, are not used in the frame of the method. Using our approach, we predicted the formation of three main secondary structure types (alpha-helix, beta-structure and coil) with high accuracy, that is Q(3) = 76%. Predicting the formation of alpha-helix and non-alpha-helix states we reached the accuracy which was measured as Q(2) = 86%. Also we have identified certain protein chain properties that affect the formation of membrane protein secondary structure. These protein properties include hydrophobic properties of amino acid residues, presence of Gly, Ala and Val amino acids, and the location of protein chain end.     

Isoform analysis of LC-MS/MS data from multidimensional fractionation of the serum proteome

We developed a visualization approach for the identification of protein isoforms, precursor/mature protein combinations, and fragments from LC-MS/MS analysis of multidimensional fractionation of serum and plasma proteins. We also describe a pattern recognition algorithm to automatically detect and flag potentially heterogeneous species of proteins in proteomic experiments that involve extensive fractionation and result in a large number of identified serum or plasma proteins in an experiment. Examples are given of proteins with known isoforms that validate our approach and present a subset of precursor/mature protein pairs that were detected with this approach. Potential applications include identification of differentially expressed isoforms in disease states.     

Structure-Based Druggability Assessment of the Mammalian Structural Proteome with Inclusion of Light Protein Flexibility

Advances reported over the last few years and the increasing availability of protein crystal structure data have greatly improved structure-based druggability approaches. However, in practice, nearly all druggability estimation methods are applied to protein crystal structures as rigid proteins, with protein flexibility often not directly addressed. The inclusion of protein flexibility is important in correctly identifying the druggability of pockets that would be missed by methods based solely on the rigid crystal structure. These include cryptic pockets and flexible pockets often found at protein-protein interaction interfaces. Here, we apply an approach that uses protein modeling in concert with druggability estimation to account for light protein backbone movement and protein side-chain flexibility in protein binding sites. We assess the advantages and limitations of this approach on widely-used protein druggability sets. Applying the approach to all mammalian protein crystal structures in the PDB results in identification of 69 proteins with potential druggable cryptic pockets.     

An approach for the assessment of the order of disruption of the elements of protein structure upon protein unfolding: A study of carbonic anhydrase B

An experimental approach named μ-analysis has been developed in order to elucidate the sequence of the loss of ordered structure by elements of a protein during the denaturation of the molecule. This approach is applicable for the analysis of proteins that fold (unfold) in a multistep process that involve the formation (destruction) of a range of intermediate states. The concept of the approach consists in systematic analysis of mutagenized forms of the protein with point substitutions of hydrophobic amino-acid residues and additional cysteine bridges. Importantly, the substitutions of the amino-acid residues must be localized to the same structural elements of the protein. Point substitutions of hydrophobic amino-acid residues mainly provide information on the structural elements of the protein that are disrupted at the final stages of protein denaturation. The addition of cysteine bridges to the surface of the protein molecule allows investigation of structural elements of the protein that are the first to unfold upon protein denaturation. Calorimetric studies of non-equilibrium melting of bovine carbonic anhydrase B yielded information on the rate constants of the unfolding of ten mutant forms of the protein. The analysis of the effects of mutations on the rates of different stages of protein unfolding allowed for elucidation of the order of disruption of structural elements of carbonic anhydrase B upon thermal denaturation.     

Non-parametric quantification of protein lysate arrays

MOTIVATION: Proteins play a crucial role in biological activity, so much can be learned from measuring protein expression and post-translational modification quantitatively. The reverse-phase protein lysate arrays allow us to quantify the relative expression levels of a protein in many different cellular samples simultaneously. Existing approaches to quantify protein arrays use parametric response curves fit to dilution series data. The results can be biased when the parametric function does not fit the data. RESULTS: We propose a non-parametric approach which adapts to any monotone response curve. The non-parametric approach is shown to be promising via both simulation and real data studies; it reduces the bias due to model misspecification and protects against outliers in the data. The non-parametric approach enables more reliable quantification of protein lysate arrays. AVAILABILITY: Code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/jhu/lysatearray-analysis/     

Multiple reaction monitoring to identify sites of protein phosphorylation with high sensitivity

Phosphorylation governs the activity of many proteins. Insight into molecular mechanisms in biology would be immensely improved by robust, sensitive methods for identifying precisely sites of phosphate addition. An approach to selective mapping of protein phosphorylation sites on a specific target protein of interest using LC-MS is described here. In this approach multiple reaction monitoring is used as an extremely sensitive MS survey scan for potential phosphopeptides from a known protein. This is automatically followed by peptide sequencing and subsequent location of the phosphorylation site; both of these steps occur in a single LC-MS run, providing greater efficiency of sample use. The method is capable of detecting and sequencing phosphopeptides at low femtomole levels with high selectivity. As proof of the value of this approach in an experimental setting, a key Schizosaccharomyces pombe cell cycle regulatory protein, Cyclin B, was purified, and associated proteins were identified. Phosphorylation sites on these proteins were located. The technique, which we have called multiple reaction monitoring-initiated detection and sequencing (MIDAS), is shown to be a highly sensitive approach to the determination of protein phosphorylation.     

Analysis of state-specific phosphorylation of proteins by two-dimensional gel electrophoresis approach

In this paper we focus on the detection of specific state of protein phosphorylation within a complex protein mixture separated by two-dimensional gel electrophoresis followed by immunoblotting. The availability of antibodies that specifically recognize the phosphorylated residue(s) of proteins make this approach feasible as exemplified by the study of the regulatory mechanisms of the cell cycle. The major advantage of the presented approach is its relative simplicity and sensitivity that allows specific detection of protein phosphorylation and distinguishes different phosphorylation sites of target protein. Current findings demonstrate that this method represents a reasonable alternative to the use of other tools to study protein phosphorylation.