蛋白质结构确定领域中的几种矩阵填充算法的对比评估

目的 目前,如何从核磁共振(nuclear magnetic resonance,NMR)光谱实验中准确地确定蛋白质的三维结构是生物物理学中的一个热门课题,因为蛋白质是生物体的重要组成成分,了解蛋白质的空间结构对研究其功能至关重要,然而由于实验数据的严重缺乏使其成为一个很大的挑战。方法 在本文中,通过恢复距离矩阵的矩阵填充(matrix completion,MC)算法来解决蛋白质结构确定问题。首先,初始距离矩阵模型被建立,由于实验数据的缺乏,此时的初始距离矩阵为不完整矩阵,随后通过MC算法恢复初始距离矩阵的缺失数据,从而获得整个蛋白质三维结构。为了进一步测试算法的性能,本文选取了4种不同拓扑结构的蛋白质和6种现有的MC算法进行了测试,探究了算法在不同的采样率以及不同程度噪声的情况下算法的恢复效果。结果 通过分析均方根偏差(root-mean-square deviation,RMSD)和计算时间这两个重要指标的平均值及标准差评估了算法的性能,结果显示当采样率和噪声因子控制在一定范围内时,RMSD值和标准差都能达到很小的值。另外本文更加具体地比较了不同算法的特点和优势,在精确采样情况下...     

Structure prediction of protein complexes by an NMR-based protein docking algorithm

Protein docking algorithms can be used to study the driving forces and reaction mechanisms of docking processes. They are also able to speed up the lengthy process of experimental structure elucidation of protein complexes by proposing potential structures. In this paper, we are discussing a variant of the protein-protein docking problem, where the input consists of the tertiary structures of proteins A and B plus an unassigned one-dimensional ¹H-NMR spectrum of the complex AB. We present a new scoring function for evaluating and ranking potential complex structures produced by a docking algorithm. The scoring function computes a `theoretical' ¹H-NMR spectrum for each tentative complex structure and subtracts the calculated spectrum from the experimental one. The absolute areas of the difference spectra are then used to rank the potential complex structures. In contrast to formerly published approaches (e.g. [Morelli et al. (2000) Biochemistry, 39, 2530–2537]) we do not use distance constraints (intermolecular NOE constraints). We have tested the approach with four protein complexes whose three-dimensional structures are stored in the PDB data bank [Bernstein et al. (1977)] and whose ¹H-NMR shift assignments are available from the BMRB database. The best result was obtained for an example, where all standard scoring functions failed completely. Here, our new scoring function achieved an almost perfect separation between good approximations of the true complex structure and false positives.     

On the relevance of precision autophagy flux control in vivo – Points of departure for clinical translation

ABSTRACT

Macroautophagy (which we will call autophagy hereafter) is a critical intracellular bulk degradation system that is active at basal rates in eukaryotic cells. This process is embedded in the homeostasis of nutrient availability and cellular metabolic demands, degrading primarily long-lived proteins and specific organelles.. Autophagy is perturbed in many pathologies, and its manipulation to enhance or inhibit this pathway therapeutically has received considerable attention. Although better probes are being developed for a more precise readout of autophagic activity in vitro and increasingly in vivo, many questions remain. These center in particular around the accurate measurement of autophagic flux and its translation from the in vitro to the in vivo environment as well as its clinical application. In this review, we highlight key aspects that appear to contribute to stumbling blocks on the road toward clinical translation and discuss points of departure for reaching some of the desired goals. We discuss techniques that are well aligned with achieving desirable spatiotemporal resolution to gather data on autophagic flux in a multi-scale fashion, to better apply the existing tools that are based on single-cell analysis and to use them in the living organism. We assess how current techniques may be used for the establishment of autophagic flux standards or reference points and consider strategies for a conceptual approach on titrating autophagy inducers based on their effect on autophagic flux . Finally, we discuss potential solutions for inherent controls for autophagy analysis, so as to better discern systemic and tissue-specific autophagic flux in future clinical applications.

Abbreviations: GFP: Green fluorescent protein; J: Flux; MAP1LC3/LC3: Microtubule-associated protein 1 light chain 3; n_A: Number of autophagosomes; TEM: Transmission electron microscopy; τ: Transition time     

Comparative Analysis of Docking Motifs in MAP-Kinases and Nuclear Receptors

Abstract

Nuclear receptor (NR) agonists induce activation of mitogen-activated protein kinases (MAPK) through an yet unknown rapid non-genomic mechanism. Vice versa, NR are targets for phosphorylation by MAPK. By multiple alignment of the amino acid sequences and comparative analysis of the secondary and tertiary structures we identified four peptides in MAPK with similarity to bona fide protein-protein-interaction motifs in NR. In both molecule species, these motifs mediate selective docking to dimerization partners, coregulators or phosphoacceptors. We therefore propose that similar motifs may direct the site-specific association of NR with MAPK. Based on mutual allosteric interactions within a kinase-receptor complex, we discuss a novel principle how NR-agonists may regulate kinase activity and thus expression of hormone-dependent genes.     

Condensed Representations of Protein Secondary Structure Sequences and Their Application

Abstract

In this paper, we propose a nongraphical representation for protein secondary structures. By counting the frequency of occurrence of all possible four-tuples (i.e., four-letter words) of a protein secondary structure sequence, we construct a set of 3 × 3 matrices for the corresponding protein secondary structure sequence. Furthermore, the leading eigenvalues of these matrices are computed and considered as invariants for the protein secondary structure sequences. To illustrate the utility of our approach, we apply it to a set of real data to distinguish protein structural classes. The result indicates that it can be used to complement the classification of protein secondary structures.     

Recruiting machine learning methods for molecular simulations of proteins

Abstract

Molecular dynamics (MD) simulations are critical to understanding the movements of proteins in time. Yet, MD simulations are limited due to the availability of high-resolution protein structures, accuracy of the underlying force-field, computational expense, and difficulty in analysing big data-sets. Machine learning algorithms are now routinely used to circumvent many of these limitations and computational biophysicists are continuously making progress in developing novel applications. Here, we discuss some of these methods, varying from traditional dimensionality reduction approaches to more recent abstractions such as transfer learning and reinforcement learning, and how they have been used to deal with the challenges in MD. We conclude with the prospective issues in the application of machine learning methods in MD, to increase accuracy and efficiency of protein dynamics studies in general.     

L-Asparaginase from E. chrysanthemi expressed in glycoswitch®: effect of His-Tag fusion on the extracellular expression

Abstract

L-Asparaginase (L-ASNase) is an important enzyme used to treat acute lymphoblastic leukemia, recombinantly produced in a prokaryotic expression system. Exploration of alternatives production systems like as extracellular expression in microorganisms generally recognized as safe (such as Pichia pastoris Glycoswitch^®) could be advantageous, in particular, if this system is able to produce homogeneous glycosylation. Here, we evaluated extracellular expression into Glycoswitch^® using two different strains constructions containing the asnB gene coding for Erwinia chrysanthemi L-ASNase (with and without His-tag), in order to find the best system for producing the extracellular and biologically active protein. When the His-tag was absent, both cell expression and protein secretion processes were considerably improved. Three-dimensional modeling of the protein suggests that additional structures (His-tag) could adversely affect native conformation and folding from L-ASNase and therefore the expression and cell secretion of this enzyme.     

Amino acid sequence and structural repeats in schistosome paramyosin match those of myosin

The cDNA encoding about half of an antigenic non-surface schistosome parasite protein of M _r 97 K has recently been cloned and sequenced (Lanar, Pearce, James and Sher (1986)Science 234:593–596). Analysis of this sequence, together with the properties of the native protein, reveals that this protein is paramyosin, the hitherto unsequenced core protein of myosin filaments in invertebrate muscle. In this report we analyze in more detail the partial amino acid sequence of schistosome paramyosin and describe electron microscope studies of the native protein and its aggregates. We show a close correspondence between the structures of paramyosin and the myosin rod that is required for these proteins to assemble together in muscle thick filaments.     

tRNA-dependent Cysteine Biosynthetic Pathway Represents a Strategy to Increase Cysteine Contents by Preventing it from Thermal Degradation: Thermal Adaptation of Methanogenic Archaea Ancestor

Abstract

Although cysteine (Cys) is beneficial to stabilize protein structures, it is not prevalent in ther-mophiles. For instance, the Cys contents in most thermophilic archaea are only around 0.7%. However, methanogenic archaea, no matter thermophilic or not, contain relatively abundant Cys, which remains elusive for a long time. Recently, Klipcan et al. correlated this intriguing property of methanogenic archaea with their unique tRNA-dependent Cys biosynthetic pathway. But, the deep reasons underlying the correlation are ambiguous. Considering the facts that free Cys is thermally labile and the tRNA-dependent Cys biosynthesis avoids the use of free Cys, we speculate that the unique Cys biosynthetic pathway represents a strategy to increase Cys contents by preventing it from thermal degradation, which may be relevant to the thermal adaptation of methanogenic archaeza ancestor.     

Localization and translation control of slam in Drosophila cellularization

ABSTRACT

In this extra view, we comment on our recent work concerning the mRNA localization of the gene slow as molasses (slam). slam is a gene essential for the polarized invagination of the plasma membrane and separation of basal and lateral cortical domains during cellularization as well as for germ cell migration in later embryogenesis. We have demonstrated an intimate relationship between slam RNA and its encoded protein. Slam RNA co-localizes and forms a complex with its encoded protein. Slam mRNA localization not only is required for reaching full levels of functional Slam protein but also depends on Slam protein. The translation of slam mRNA is subject to tight spatio-temporal regulation leading to a rapid accumulation of Slam protein and zygotic slam RNA at the furrow canal. In this extra view, we first discuss the mechanism controlling localization and translation of slam RNA. In addition, we document in detail the maternal and zygotic expression of slam RNA and protein and provide data for a function in membrane stabilization. Furthermore, we mapped the region of Slam protein mediating cortical localization in cultured cells.     

基于点云卷积神经网络的蛋白质柔性预测

目的 蛋白质的柔性运动对生物体各种反应有着重要意义,基于蛋白质的空间结构预测其柔性运动是蛋白质结构-功能关系领域的重要问题.卷积神经网络(convolutional neural network,CNN)在蛋白质结构-功能关系研究中已有成功应用.方法 本研究借鉴计算机视觉研究中PointNet方法的思想,提出了一种蛋白...     

Prediction of Protein Structure by Simulating Coarse-grained Folding Pathways: A Preliminary Report

Abstract

A set of software tools designed to study protein structure and kinetics has been developed. The core of these tools is a program called Folding Machine (FM) which is able to generate low resolution folding pathways using modest computational resources. The FM is based on a coarse-grained kinetic ab initio Monte-Carlo sampler that can optionally use information extracted from secondary structure prediction servers or from fragment libraries of local structure. The model underpinning this algorithm contains two novel elements: (a) the conformational space is discretized using the Ramachandran basins defined in the local φ-ψ energy maps; and (b) the solvent is treated implicitly by rescaling the pairwise terms of the non-bonded energy function according to the local solvent environments. The purpose of this hybrid ab initio/knowledge-based approach is threefold: to cover the long time scales of folding, to generate useful 3-dimensional models of protein structures, and to gain insight on the protein folding kinetics. Even though the algorithm is not yet fully developed, it has been used in a recent blind test of protein structure prediction (CASP5). The FM generated models within 6 Å backbone rmsd for fragments of about 60–70 residues of a-helical proteins. For a CASP5 target that turned out to be natively unfolded, the trajectory obtained for this sequence uniquely failed to converge. Also, a new measure to evaluate structure predictions is presented and used along the standard CASP assessment methods. Finally, recent improvements in the prediction of β-sheet structures are briefly described.     

Shotgun Crystallization Strategy for Structural Genomics II: Crystallization Conditions that Produce High Resolution Structures for T. maritima Proteins

Currently, 119 high resolution structures of Thermotoga maritima proteins have been determined by the Joint Center for Structural Genomics (JCSG, www.jcsg.org). Sixty-seven of these were solved using the first implementation of the multi-tiered crystallization strategy at the JCSG for the efficient crystallization of large numbers of protein targets. Previously, we reported the analysis of all proteins crystallized using this multi-tiered strategy [Lesley, S.A. et al. (2002) Proc. Natl. Acad. Sci. USA 99, 11664–11669; Page, R. et al. (2003) Acta Crystallogr. D Biol. Crystallogr. 59, 1028–1037]. Here, we extend the analysis and describe the crystallization characteristics of those proteins that produced diffraction quality crystals, ultimately resulting in high resolution structures. First, we found that over 77% (52) of the crystals used for structure determination were produced directly from high-throughput coarse screens, indicating that less than one quarter of the crystals (15) required fine screening. In addition, as observed for the proteome screen [Page, R. et al. (2003) Acta Crystallogr. D Biol. Crystallogr. 59, 1028–1037], the majority of conditions that produced crystals for natively expressed proteins, whose structures have been determined, were distinct from those of their more extensively purified and selenomethionine-labeled counterparts. Finally, 99% of the proteins whose structures were solved crystallized in conditions contained in the JCSG Minimal Core Screen [Page, R. et al. (2003) Acta Crystallogr. D Biol. Crystallogr. 59, 1028–1037; Page, R. and Stevens, R.C. (2004) Methods 34, 373–389], a set of 67 conditions previously identified as those most likely to produce crystals of a diverse set of proteins, confirming its success for rapid identification of proteins with a natural propensity to crystallize.     

CLUSS: Clustering of protein sequences based on a new similarity measure

Background  

The rapid burgeoning of available protein data makes the use of clustering within families of proteins increasingly important. The challenge is to identify subfamilies of evolutionarily related sequences. This identification reveals phylogenetic relationships, which provide prior knowledge to help researchers understand biological phenomena. A good evolutionary model is essential to achieve a clustering that reflects the biological reality, and an accurate estimate of protein sequence similarity is crucial to the building of such a model. Most existing algorithms estimate this similarity using techniques that are not necessarily biologically plausible, especially for hard-to-align sequences such as proteins with different domain structures, which cause many difficulties for the alignment-dependent algorithms. In this paper, we propose a novel similarity measure based on matching amino acid subsequences. This measure, named SMS for Substitution Matching Similarity, is especially designed for application to non-aligned protein sequences. It allows us to develop a new alignment-free algorithm, named CLUSS, for clustering protein families. To the best of our knowledge, this is the first alignment-free algorithm for clustering protein sequences. Unlike other clustering algorithms, CLUSS is effective on both alignable and non-alignable protein families. In the rest of the paper, we use the term "phylogenetic" in the sense of "relatedness of biological functions".     

Energy Minimization for Tertiary Structure Prediction of Homologous Proteins: α1-purothionin and Viscotoxin A3 Models from Crambin

Abstract

Homologous proteins may fold into similar three-dimensional structures. Spectroscopic evidence suggests this is true for the cereal grain thionins, the mistletoe toxins, and for crambin, three classes of plant proteins. We have combined primary sequence homology and energy minimization to predict the structures α₁-purothionin (from Durum wheat) and viscotoxin A3 (from Viscum album, European mistletoe) from the high resolution (0.945 Å) crystal structure of crambin (from Crambe abyssinica). Our predictions will be verifiable because we have diffraction-quality crystals of α₁-purothionin whose structure we are have predicted. The potential energy minimizations for each protein were performed both with and without harmonic constraints to its initial backbone to explore the existence of local minima for the predicted proteins. Crambin was run as a control to examine the effects of the potential energy minimization on a protein with a well-known structure. Only α₁-purothionin which has one fewer residue in a turn region shows a significant difference for the two minimization paths. The results of these predictions suggest that α₁-purothionin and viscotoxin are amphipathic proteins, and this character may relate to the mechanism of action for these proteins. Both are mildly membrane-active and their amphipathic character is well suited for interaction with a lipid bilayer.     

Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS

Novel algorithms are presented for automated NOESY peak picking and NOE signal identification in homonuclear 2D and heteronuclear-resolved 3D [¹H,¹H]-NOESY spectra during de novoprotein structure determination by NMR, which have been implemented in the new software ATNOS (automated NOESY peak picking). The input for ATNOS consists of the amino acid sequence of the protein, chemical shift lists from the sequence-specific resonance assignment, and one or several 2D or 3D NOESY spectra. In the present implementation, ATNOS performs multiple cycles of NOE peak identification in concert with automated NOE assignment with the software CANDID and protein structure calculation with the program DYANA. In the second and subsequent cycles, the intermediate protein structures are used as an additional guide for the interpretation of the NOESY spectra. By incorporating the analysis of the raw NMR data into the process of automated de novoprotein NMR structure determination, ATNOS enables direct feedback between the protein structure, the NOE assignments and the experimental NOESY spectra. The main elements of the algorithms for NOESY spectral analysis are techniques for local baseline correction and evaluation of local noise level amplitudes, automated determination of spectrum-specific threshold parameters, the use of symmetry relations, and the inclusion of the chemical shift information and the intermediate protein structures in the process of distinguishing between NOE peaks and artifacts. The ATNOS procedure has been validated with experimental NMR data sets of three proteins, for which high-quality NMR structures had previously been obtained by interactive interpretation of the NOESY spectra. The ATNOS-based structures coincide closely with those obtained with interactive peak picking. Overall, we present the algorithms used in this paper as a further important step towards objective and efficient de novoprotein structure determination by NMR.     

Don't pull the plug! the Drosophila mating plug preserves fertility

ABSTRACT

Mating plugs are hardened structures—typically a coagulation of seminal fluid components—that are transferred to, or formed within, the female reproductive tract of numerous animal species (both mammals and insects). Analysis of the role(s) of the mating plug in reproduction has been conducted in a wide array of diverse species. These structures have been proposed to have a multitude of functions, which include altering female re-mating rate, acting as a barrier to re-mating and being required for sperm storage or sperm movement to occur in mated females. A recent analysis of the Drosophila melanogaster mating plug has shown that proper formation of the structure is required for optimal fertility in flies: the Drosophila mating plug is required to retain the ejaculate within the female reproductive tract once mating has terminated. Here, we discuss the possible implications of the Drosophila mating plug in the fertility of this species in light of these new results.     

Redox-dependent conformational changes in eukaryotic cytochromes revealed by paramagnetic NMR spectroscopy

Cytochrome c (Cc) is a soluble electron carrier protein, transferring reducing equivalents between Cc reductase and Cc oxidase in eukaryotes. In this work, we assessed the structural differences between reduced and oxidized Cc in solution by paramagnetic NMR spectroscopy. First, we have obtained nearly-complete backbone NMR resonance assignments for iso-1-yeast Cc and horse Cc in both oxidation states. These were further used to derive pseudocontact shifts (PCSs) arising from the paramagnetic haem group. Then, an extensive dataset comprising over 450 measured PCSs and high-resolution X-ray and solution NMR structures of both proteins were used to define the anisotropic magnetic susceptibility tensor, Δχ. For most nuclei, the PCSs back-calculated from the Δχ tensor are in excellent agreement with the experimental PCS values. However, several contiguous stretches—clustered around G41, N52, and A81—exhibit large deviations both in yeast and horse Cc. This behaviour is indicative of redox-dependent structural changes, the extent of which is likely conserved in the protein family. We propose that the observed discrepancies arise from the changes in protein dynamics and discuss possible functional implications.     

Origins of structural diversity within sequentially identical hexapeptides

Efforts to predict protein secondary structure have been hampered by the apparent structural plasticity of local amino acid sequences. Kabsch and Sander (1984, Proc. Natl. Acad. Sci. USA 81, 1075–1078) articulated this problem by demonstrating that identical pentapeptide sequences can adopt distinct structures in different proteins. With the increased size of the protein structure database and the availability of new methods to characterize structural environments, we revisit this observation of structural plasticity. Within a set of proteins with less than 50% sequence identity, 59 pairs of identical hexapeptide sequences were identified. These local structures were compared and their surrounding structural environments examined. Within a protein structural class (α/α, β/β, α/β, α + β), the structural similarity of sequentially identical hexapeptides usually is preserved. This study finds eight pairs of identical hexapeptide sequences that adopt β-strand structure in one protein and α-helical structure in the other. In none of the eight cases do the members of these sequence pairs come from proteins within the same folding class. These results have implications for class dependent secondary structure prediction algorithms.     

Identification of a Potential Lead Structure for Designing New Antimicrobials to Treat Infections Caused by Staphylococcus epidermidis-Resistant Strains

Bacterial infections are a significant cause of morbidity and mortality among critically ill patients. The increase of antibiotic resistance in bacteria from human microbiota—such as Staphylococcus epidermidis, an important nosocomial pathogen that affects immunocompromised patients or those with indwelling devices—increased the desire for new antibiotics. In this study we designed, synthesized, and determined the antimicrobial activity of 27 thieno[2,3-b]pyridines (1, 2, 2a–2m, 3, 3a–3m) derivatives against a drug-resistant clinical S. epidermidis strain. In addition, we performed a structure-activity relationship analysis using a molecular modeling approach, and discuss the drug absorption, distribution, metabolism, excretion, and toxicity profile and Lipinski’s “rule of five,” which are tools to assess the relationship between structures and drug-like properties of active compounds. Our results showed that compound 3b (5-(1H-tetrazol-5-yl)-4-(3`-methylphenylamino)thieno[2,3-b]pyridine) was as active as oxacillin and chloramphenicol but with lower theoretical toxicity risks and a better drug likeness and drug score potential than chloramphenicol. All molecular modeling and biological results reinforced the promising profile of 3b for further experimental investigation and development of new antibacterial drugs. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.