Identification of native protein folds amongst a large number of incorrect models. The calculation of low energy conformations from potentials of mean force

We present an approach that is able to detect native folds amongst a large number of non-native conformations. The method is based on the compilation of potentials of mean force of the interactions of the C beta atoms of all amino acid pairs from a database of known three-dimensional protein structures. These potentials are used to calculate the conformational energy of amino acid sequences in a number of different folds. For a substantial number of proteins we find that the conformational energy of the native state is lowest amongst the alternatives. Exceptions are proteins containing large prosthetic groups, Fe-S clusters or polypeptide chains that do not adopt globular folds. We discuss briefly potential applications in various fields of protein structural research.     

How a Spatial Arrangement of Secondary Structure Elements Is Dispersed in the Universe of Protein Folds

It has been known that topologically different proteins of the same class sometimes share the same spatial arrangement of secondary structure elements (SSEs). However, the frequency by which topologically different structures share the same spatial arrangement of SSEs is unclear. It is important to estimate this frequency because it provides both a deeper understanding of the geometry of protein folds and a valuable suggestion for predicting protein structures with novel folds. Here we clarified the frequency with which protein folds share the same SSE packing arrangement with other folds, the types of spatial arrangement of SSEs that are frequently observed across different folds, and the diversity of protein folds that share the same spatial arrangement of SSEs with a given fold, using a protein structure alignment program MICAN, which we have been developing. By performing comprehensive structural comparison of SCOP fold representatives, we found that approximately 80% of protein folds share the same spatial arrangement of SSEs with other folds. We also observed that many protein pairs that share the same spatial arrangement of SSEs belong to the different classes, often with an opposing N- to C-terminal direction of the polypeptide chain. The most frequently observed spatial arrangement of SSEs was the 2-layer α/β packing arrangement and it was dispersed among as many as 27% of SCOP fold representatives. These results suggest that the same spatial arrangements of SSEs are adopted by a wide variety of different folds and that the spatial arrangement of SSEs is highly robust against the N- to C-terminal direction of the polypeptide chain.     

Role of the ribosome in protein folding

In all organisms, the ribosome synthesizes and folds full length polypeptide chains into active three-dimensional conformations. The nascent protein goes through two major interactions, first with the ribosome which synthesizes the polypeptide chain and holds it for a considerable length of time, and then with the chaperones. Some of the chaperones are found in solution as well as associated to the ribosome. A number of in vitro and in vivo experiments revealed that the nascent protein folds through specific interactions of some amino acids with the nucleotides in the peptidyl transferase center (PTC) in the large ribosomal subunit. The mechanism of this folding differs from self-folding. In this article, we highlight the folding of nascent proteins on the ribosome and the influence of chaperones etc. on protein folding.     

Emergence of highly designable protein-backbone conformations in an off-lattice model

Despite the variety of protein sizes, shapes, and backbone configurations found in nature, the design of novel protein folds remains an open problem. Within simple lattice models it has been shown that all structures are not equally suitable for design. Rather, certain structures are distinguished by unusually high designability: the number of amino acid sequences for which they represent the unique lowest energy state; sequences associated with such structures possess both robustness to mutation and thermodynamic stability. Here we report that highly designable backbone conformations also emerge in a realistic off-lattice model. The highly designable conformations of a chain of 23 amino acids are identified and found to be remarkably insensitive to model parameters. Although some of these conformations correspond closely to known natural protein folds, such as the zinc finger and the helix-turn-helix motifs, others do not resemble known folds and may be candidates for novel fold design.     

Statistical mechanics of protein folding with separable energy functions

We have initiated an entirely new approach to statistical mechanical models of strongly interacting systems where the configurational parameters and the potential energy function are both constructed so that the canonical partition function can be evaluated analytically. For a simplified model of proteins consisting of a single, fairly short polypeptide chain without cross-links, we can adjust the energy parameters to favor the experimentally determined native state of seven proteins having diverse types of folds. Then 497 test proteins are predicted to have stable native folds, even though they are also structurally diverse, and 480 of them have no significant sequence similarity to any of the training proteins.     

Computational exploration of the network of sequence flow between protein structures

We investigate small sequence adjustments (of one or a few amino acids) that induce large conformational transitions between distinct and stable folds of proteins. Such transitions are intriguing from evolutionary and protein‐design perspectives. They make it possible to search for ancient protein structures or to design protein switches that flip between folds and functions. A network of sequence flow between protein folds is computed for representative structures of the Protein Data Bank. The computed network is dense, on an average each structure is connected to tens of other folds. Proteins that attract sequences from a higher than expected number of neighboring folds are more likely to be enzymes and alpha/beta fold. The large number of connections between folds may reflect the need of enzymes to adjust their structures for alternative substrates. The network of the Cro family is discussed, and we speculate that capacity is an important factor (but not the only one) that determines protein evolution. The experimentally observed flip from all alpha to alpha + beta fold is examined by the network tools. A kinetic model for the transition of sequences between the folds (with only protein stability in mind) is proposed. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Dynamic polyhedral models of globular proteins

We have devised several mechanical models of globular proteins by approximating them to various polyhedra (dodecahedron, truncated octahedron, icosahedron, truncated icosahedron). The models comprise hollow blocks linked together in a flexible chain. Between blocks there is a set of several reversible, weak magnetic interactions such that when the chain is agitated, it will fold into a stable polyhedral structure about the size of a hand. Folding may be followed in real time with a video camera. Key to the success of the folding process is the lightness of the chain. Several side chains may also be added to the blocks such that they come together to create a polyhedral core when the chain folds. The models have a number of similarities to globular proteins: each chain folds into a unique, but dynamic, three-dimensional structure; the instructions that determine this structure are built into the configuration of blocks; and it is difficult to predict this structure given the unfolded block configuration. Furthermore, the chains fold quickly, generally in less than a minute, several pathways are involved, and these pathways progress through elements of "native" structure. In particular, the models emphasize the importance of restricted conformational mobility in assisting the chain to fold, and also in eliminating undesirable interactions. Because of these similarities to globular proteins, we believe that the polyhedral models will, with continued development, be helpful in understanding the protein folding process, while at the same time acting as valuable educational visual aids. They might also inspire the construction of new types of microscopic, self-assembling devices.     

Mechanism of insulin chain combination. Asymmetric roles of A-chain alpha-helices in disulfide pairing

The A and B chains of insulin combine to form native disulfide bridges without detectable isomers. The fidelity of chain combination thus recapitulates the folding of proinsulin, a precursor protein in which the two chains are tethered by a disordered connecting peptide. We have recently shown that chain combination is blocked by seemingly conservative substitutions in the C-terminal alpha-helix of the A chain. Such analogs, once formed, nevertheless retain high biological activity. By contrast, we demonstrate here that chain combination is robust to non-conservative substitutions in the N-terminal alpha-helix. Introduction of multiple glycine substitutions into the N-terminal segment of the A chain (residues A1-A5) yields analogs that are less stable than native insulin and essentially without biological activity. (1)H NMR studies of a representative analog lacking invariant side chains Ile(A2) and Val(A3) (A chain sequence GGGEQCCTSICSLYQLENYCN; substitutions are italicized and cysteines are underlined) demonstrate local unfolding of the A1-A5 segment in an otherwise native-like structure. That this and related partial folds retain efficient disulfide pairing suggests that the native N-terminal alpha-helix does not participate in the transition state of the reaction. Implications for the hierarchical folding mechanisms of proinsulin and insulin-like growth factors are discussed.     

Estimating the total number of protein folds.

Many seemingly unrelated protein families share common folds. Theoretical models based on structure designability have suggested that a few folds should be very common while many others have low probability. In agreement with the predictions of these models, we show that the distribution of observed protein families over different folds can be modeled with a highly-stretched exponential. Our results suggest that there are approximately 4,000 possible folds, some so unlikely that only approximately 2,000 folds existing among naturally-occurring proteins. Due to the large number of extremely rare folds, constructing a comprehensive database of all existent folds would be difficult. Constructing a database of the most-likely folds representing the vast majority of protein families would be considerably easier.     

Solution NMR structures of IgG binding domains with artificially evolved high levels of sequence identity but different folds

We describe here the solution NMR structures of two IgG binding domains with highly homologous sequences but different three-dimensional structures. The proteins, G311 and A219, are derived from the IgG binding domains of their wild-type counterparts, protein G and protein A, respectively. Through a series of site-directed mutations and phage display selections, the sequences of G311 and A219 were designed to converge to a point of high-level sequence identity while keeping their respective wild-type tertiary folds. Structures of both artificially evolved sequences were determined by NMR spectroscopy. The main chain fold of G311 can be superimposed on the wild-type alpha/beta protein G structure with a backbone rmsd of 1.4 A, and the A219 structure can be overlaid on the wild-type three-alpha-helix protein A fold also with a backbone rmsd of 1.4 A. The structure of G311, in particular, accommodates a large number of mutational changes without undergoing a change in the overall fold of the main chain. The structural differences are maintained despite a high level (59%) of sequence identity. These proteins serve as starting points for further experiments that will probe basic concepts of protein folding and conformational switching.     

Monte Carlo estimation of the number of possible protein folds: effects of sampling bias and folds distributions

The estimation of the number of protein folds in nature is a matter of considerable interest. In this study, a Monte Carlo method employing the broken stick model is used to assign a given number of proteins into a given number of folds. Subsequently, random, integer, non-repeating numbers are generated in order to simulate the process of fold discovery. With this conceptual framework at hand, the effects of two factors upon the fold identification process were investigated: (1) the nature of folds distributions and (2) preferential sampling bias of previously identified folds. Depending on the type of distribution, dividing 100,000 proteins into 1,000 folds resulted in 10-30% of the folds having 10 proteins or less per fold, approximately 10% of the folds having 10-20 proteins per fold, 31-45% having 20-100 proteins per fold, and >30% of the folds having more than 100 proteins per fold. After randomly sampling one tenth of the proteins, 68-96% of the folds were identified. These percentages depend both on folds distribution and biased/non-biased sampling. Only upon increasing the sampling bias for previously identified folds to 1,000, did the model result in a reduction of the number of proteins identified by an order of magnitude (approximately 9%). Thus, assuming the structures of one tenth of the population of proteins in nature have been solved, the results of the Monte Carlo simulation are more consistent with recent lower estimates of the number of folds, 相似文献   

使用图像特征构建快速有效的蛋白质折叠识别方法

蛋白质结构自动分类是探索蛋白质结构- 功能关系的一种重要研究手段。首先将蛋白质折叠子三维空间结构映射成为二维距离矩阵,并将距离矩阵视作灰度图像。然后基于灰度直方图和灰度共生矩阵提出了一种计算简单的折叠子结构特征提取方法,得到了低维且能够反映折叠结构特点的特征,并进一步阐明了直方图中零灰度孤峰形成原因,深入分析了共生矩阵特征中灰度分布、不同角度和像素距离对应的结构意义。最后应用于27类折叠子分类,对独立集测试的精度达到了71.95 %,对所有数据进行10 交叉验证的精度为78.94 %。与多个基于序列和结构的折叠识别方法的对比结果表明,此方法不仅具有低维和简洁的特征,而且无需复杂的分类系统,能够有效和高效地实现多类折叠子识别。     

Prediction of loop regions in protein sequence

We suggest an algorithm that inputs a protein sequence and outputs a decomposition of the protein chain into a regular part including secondary structures and a nonregular part corresponding to loop regions. We have analyzed loop regions in a protein dataset of 3,769 globular domains and defined the optimal parameters for this prediction: the threshold between regular and nonregular regions and the optimal window size for averaging procedures using the scale of the expected number of contacts in a globular state and entropy scale as the number of degrees of freedom for the angles phi, psi, and chi for each amino acid. Comparison with known methods demonstrates that our method gives the same results as the well-known ALB method based on physical properties of amino acids (the percentage of true predictions is 64% against 66%), and worse prediction for regular and nonregular regions than PSIPRED (Protein Structure Prediction Server) without alignment of homologous proteins (the percentage of true predictions is 73%). The potential advantage of the suggested approach is that the predicted set of loops can be used to find patterns of rigid and flexible loops as possible candidates to play a structure/function role as well as a role of antigenic determinants.     

How many fold types of protein are there in nature?

Many protein structures have now been determined and reveal that protein molecules can adopt the same fold despite having very different sequences. It has been suggested that, owing to different stereochemical constraints, the number of ways that a sequence can fold may be limited. Therefore, it is reasonable to ask how many fold types exist in nature. Several groups have tackled this problem with very different results. In the present study, a novel statistical sampling approach is used to reestimate this number. The results suggest that the number of protein folds in nature is probably several hundreds. © 1996 Wiley-Liss, Inc.     

Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges

Environmental heterogeneity is considered to be one of the main factors associated with biodiversity given that areas with highly heterogeneous environments can host more species due to their higher number of available niches. In this view, spatial variability extracted from remotely sensed images has been used as a proxy of species diversity, as these data provide an inexpensive means of deriving environmental information for large areas in a consistent and regular manner. The aim of this review is to provide an overview of the state of the art in the use of spectral heterogeneity for estimating species diversity. We will examine a number of issues related to this theme, dealing with: i) the main sensors used for biodiversity monitoring, ii) scale matching problems between remotely sensed and field diversity data, iii) spectral heterogeneity measurement techniques, iv) types of species taxonomic diversity measures and how they influence the relationship between spectral and species diversity, v) spectral versus genetic diversity, and vi) modeling procedures for relating spectral and species diversity. Our review suggests that remotely sensed spectral heterogeneity information provides a crucial baseline for rapid estimation or prediction of biodiversity attributes and hotspots in space and time.     

The YefM antitoxin defines a family of natively unfolded proteins: implications as a novel antibacterial target

Although natively unfolded proteins are being observed increasingly, their physiological role is not well understood. Here, we demonstrate that the Escherichia coli YefM protein is a natively unfolded antitoxin, lacking secondary structure even at low temperature or in the presence of a stabilizing agent. This conformation of the protein is suggested to have a key role in its physiological regulatory activity. Because of the unfolded state of the protein, a linear determinant rather than a conformational one is presumably being recognized by its toxin partner, YoeB. A peptide array technology allowed the identification and validation of such a determinant. This recognition element may provide a novel antibacterial target. Indeed, a pair-constrained bioinformatic analysis facilitated the definite determination of novel YefM-YoeB toxin-antitoxin systems in a large number of bacteria including major pathogens such as Staphylococcus aureus, Streptococcus pneumoniae, and Mycobacterium tuberculosis. Taken together, the YefM protein defines a new family of natively unfolded proteins. The existence of a large and conserved group of proteins with a clear physiologically relevant unfolded state serves as a paradigm to understand the structural basis of this state.