Shorter side chains optimize helix-helix packing

A systematic study of helix-helix packing in a comprehensive database of protein structures revealed that the side chains inside helix-helix interfaces on average are shorter than those in the noninterface parts of the helices. The study follows our earlier study of this effect in transmembrane helices. The results obtained on the entire database of protein structures are consistent with those obtained on the transmembrane helices. The difference in the length of interface and noninterface side chains is small but statistically significant. It indicates that helices, if viewed along their main axis, statistically are not circular, but have a flattened interface. This effect brings the helices closer to each other and creates a tighter structural packing. The results provide an interesting insight into the aspects of protein structure and folding.     

PackHelix: a tool for helix-sheet packing during protein structure prediction

The three‐dimensional structure of a protein is organized around the packing of its secondary structure elements. Predicting the topology and constructing the geometry of structural motifs involving α‐helices and/or β‐strands are therefore key steps for accurate prediction of protein structure. While many efforts have focused on how to pack helices and on how to sample exhaustively the topologies and geometries of multiple strands forming a β‐sheet in a protein, there has been little progress on generating native‐like packings of helices on sheets. We describe a method that can generate the packing of multiple helices on a given β‐sheet for αβα sandwich type protein folds. This method mines the results of a statistical analysis of the conformations of αβ₂ motifs in protein structures to provide input values for the geometric attributes of the packing of a helix on a sheet. It then proceeds with a geometric builder that generates multiple arrangements of the helices on the sheet of interest by sampling through these values and performing consistency checks that guarantee proper loop geometry between the helices and the strands, minimal number of collisions between the helices, and proper formation of a hydrophobic core. The method is implemented as a module of ProteinShop. Our results show that it produces structures that are within 4–6 Å RMSD of the native one, regardless of the number of helices that need to be packed, though this number may increase if the protein has several helices between two consecutive strands in the sequence that pack on the sheet formed by these two strands. Proteins 2011; Published 2011 Wiley‐Liss, Inc.     

An amino acid code to define a protein's tertiary packing surface

One difficult aspect of the protein‐folding problem is characterizing the nonspecific interactions that define packing in protein tertiary structure. To better understand tertiary structure, this work extends the knob‐socket model by classifying the interactions of a single knob residue packed into a set of contiguous sockets, or a pocket made up of 4 or more residues. The knob‐socket construct allows for a symbolic two‐dimensional mapping of pockets. The two‐dimensional mapping of pockets provides a simple method to investigate the variety of pocket shapes to understand the geometry of protein tertiary surfaces. The diversity of pocket geometries can be organized into groups of pockets that share a common core, which suggests that some interactions in pockets are ancillary to packing. Further analysis of pocket geometries displays a preferred configuration that is right‐handed in α‐helices and left‐handed in β‐sheets. The amino acid composition of pockets illustrates the importance of nonpolar amino acids in packing as well as position specificity. As expected, all pocket shapes prefer to pack with hydrophobic knobs; however, knobs are not selective for the pockets they pack. Investigating side‐chain rotamer preferences for certain pocket shapes uncovers no strong correlations. These findings allow a simple vocabulary based on knobs and sockets to describe protein tertiary packing that supports improved analysis, design, and prediction of protein structure. Proteins 2016; 84:201–216. © 2015 Wiley Periodicals, Inc.     

Analysis of anisotropic side-chain packing in proteins and application to high-resolution structure prediction

pi-pi, Cation-pi, and hydrophobic packing interactions contribute specificity to protein folding and stability to the native state. As a step towards developing improved models of these interactions in proteins, we compare the side-chain packing arrangements in native proteins to those found in compact decoys produced by the Rosetta de novo structure prediction method. We find enrichments in the native distributions for T-shaped and parallel offset arrangements of aromatic residue pairs, in parallel stacked arrangements of cation-aromatic pairs, in parallel stacked pairs involving proline residues, and in parallel offset arrangements for aliphatic residue pairs. We then investigate the extent to which the distinctive features of native packing can be explained using Lennard-Jones and electrostatics models. Finally, we derive orientation-dependent pi-pi, cation-pi and hydrophobic interaction potentials based on the differences between the native and compact decoy distributions and investigate their efficacy for high-resolution protein structure prediction. Surprisingly, the orientation-dependent potential derived from the packing arrangements of aliphatic side-chain pairs distinguishes the native structure from compact decoys better than the orientation-dependent potentials describing pi-pi and cation-pi interactions.     

An energy-based approach to packing the 7-helix bundle of bacteriorhodopsin.

Based on the heavy-atom coordinates determined by the electron microscopy for the seven main helical regions of bacteriorhodopsin with the all-trans retinal isomer, energy optimizations were carried out for helix bundles containing the all-trans retinal and 13-cis retinal chromophores, respectively. A combination of simulated annealing and energy minimization was utilized during the process of energy optimization. It was found that the 7-helix bundle containing the all-trans isomer is about 10 kcal/mol lower in conformational energy than that containing the 13-cis isomer. An energetic analysis indicates that such a difference in energy is consistent with the observation that absorption of a 570-nm proton is required for the conversion of a bacteriorhodopsin from its all-trans to 13-cis form. It was also found that the above conversion process is accompanied by a significant conformational perturbation around the chromophore, as reflected by the fact that the beta-ionone ring of retinal moves about 5.6 A along the direction perpendicular to the membrane plane. This is consistent with the observation by Fodor et al. (Fodor, S.P.A., Ames, J.B., Gebhard, R., van der Berg, E.M.M., Stoeckenius, W., Lugtenburg, J., & Mathies, R.A., 1988, Biochemistry 27, 7097-7101). Furthermore, it is interesting to observe that although the retinal chromophore undergoes a significant change in its spatial position, the orientation of its transition dipole changes only slightly, in accord with experimental observations. In other words, even though orientation of the retinal transition dipole is very restricted, there is sufficient room, and degrees of freedom, for the retinal chromophore to readjust its position considerably. This finding provides new insight into the subtle change of the retinal microenvironment, which may be important for revealing the proton-pumping mechanism of bacteriorhodopsin. The importance of electrostatic and nonbonded interactions in stabilizing the 7-helix bundle structure has also been analyzed. Electrostatic interactions favor an antiparallel arrangement among adjacent helices. Nonbonded interactions, however, drive most of the closely packed helices into an arrangement in which the packing angles lie around -160 degrees, a value very near the -154 degrees value computed earlier as the most favorable packing arrangement of two poly(Ala) alpha-helices (Chou, K.-C., Némethy, G., & Scheraga, H.A., 1983, J. Phys. Chem. 87, 2869-2881). The structural features of the 7-helix bundle and their relationship to those found in typical 4-helix bundle proteins are also discussed.(ABSTRACT TRUNCATED AT 400 WORDS)     

Analysis of interactive packing of secondary structural elements in alpha/beta units in proteins

An alpha-helix and a beta-strand are said to be interactively packed if at least one residue in each of the secondary structural elements loses 10% of its solvent accessible contact area on association with the other secondary structural element. An analysis of all such 5,975 nonidentical alpha/beta units in protein structures, defined at < or = 2.5 A resolution, shows that the interaxial distance between the alpha-helix and the beta-strand is linearly correlated with the residue-dependent function, log[(V/nda)/n-int], where V is the volume of amino acid residues in the packing interface, nda is the normalized difference in solvent accessible contact area of the residues in packed and unpacked secondary structural elements, and n-int is the number of residues in the packing interface. The beta-sheet unit (beta u), defined as a pair of adjacent parallel or antiparallel hydrogen-bonded beta-strands, packing with an alpha-helix shows a better correlation between the interaxial distance and log(V/nda) for the residues in the packing interface. This packing relationship is shown to be useful in the prediction of interaxial distances in alpha/beta units using the interacting residue information of equivalent alpha/beta units of homologous proteins. It is, therefore, of value in comparative modeling of protein structures.     

基于遗传算法的蛋白质结构预测方法

遗传算法源于自然界的进化规律,是一种自适应启发式概率性迭代式全局搜索算法。本文主要介绍了GA的基本原理,算法及优点;总结GA在蛋白质结构预测中建立模型和执行策略,以及多种算法相互结合预测蛋白质结构的研究进展。     

A rapid protein structure alignment algorithm based on a text modeling technique

Structural alignment of proteins is widely used in various fields of structural biology. In order to further improve the quality of alignment, we describe an algorithm for structural alignment based on text modelling techniques. The technique firstly superimposes secondary structure elements of two proteins and then, models the 3D-structure of the protein in a sequence of alphabets. These sequences are utilized by a step-by-step sequence alignment procedure to align two protein structures. A benchmark test was organized on a set of 200 non-homologous proteins to evaluate the program and compare it to state of the art programs, e.g. CE, SAL, TM-align and 3D-BLAST. On average, the results of all-against-all structure comparison by the program have a competitive accuracy with CE and TM-align where the algorithm has a high running speed like 3D-BLAST.     

A new pairwise folding potential based on improved decoy generation and side-chain packing

A new force field for pairwise residue interactions as a function of C(alpha) to C(alpha) distances is presented. The force field was developed through the solution of a linear programming formulation with large sets of constraints. The constraints are based on the construction of >80,000 low-energy decoys for a set of proteins and requiring the decoy energies for each protein system to be higher than the native conformation of that particular protein. The generation of a robust force field was facilitated by the use of a novel decoy generation process, which involved the rational selection of proteins to add to the training set and included a significant energy minimization of the decoys. The force field was tested on a large set of decoys for various proteins not included in the training set and shown to perform well compared with a leading force field in identifying the native conformation for these proteins.     

基于遗传算法预测2D三向的蛋白质结构

本文基于范德华力势能预测2D三向的蛋白质结构。首先,将蛋白质结构预测这一生物问题转化为数学问题,并建立基于范德华力势能函数的数学模型。其次,使用遗传算法对数学模型进行求解,为了提高蛋白质结构预测效率,我们在标准遗传算法的基础上引入了调整算子这一概念,改进了遗传算法。最后,进行数值模拟实验。实验的结果表明范德华力势能函数模型是可行的,同时,和规范遗传算法相比,改进后的遗传算法能够较大幅度提高算法的搜索效率,并且遗传算法在蛋白质结构预测问题上有巨大潜力。     

基于深度学习的蛋白质建模与设计

随着蛋白质序列及结构数据的大量累积,在获得了大量描述性信息之后如何有效利用海量数据,从已有数据中高效提取信息并且应用到下游任务当中就成为了研究者亟待解决的问题。蛋白质的设计可使新蛋白的研发不再受限于实验条件,这对药物靶点预测、新药研发和材料设计等领域具有重要意义。深度学习作为一种高效的数据特征提取方法,可以通过它对蛋白质数据进行建模,进而加入先验信息对蛋白质进行设计。故此基于深度学习的蛋白质设计就成为一个具有广阔前景的研究领域。文中主要阐述基于深度学习的蛋白质序列与结构数据的建模和设计方法。详述该方法的策略、原理、适用范围、应用实例。讨论了深度学习方法在本领域的应用前景及局限性,以期为相关研究提供参考。     

Prediction of protein secondary structure based on residue pair types and conformational states using dynamic programming algorithm

We have used a statistical approach for protein secondary structure prediction based on information theory and simultaneously taking into consideration pairwise residue types and conformational states. Since the prediction of residue secondary structure by one residue window sliding make ambiguity in state prediction, we used a dynamic programming algorithm to find the path with maximum score. A score system for residue pairs in particular conformations is derived for adjacent neighbors up to ten residue apart in sequence. The three state overall per-residue accuracy, Q3, of this method in a jackknife test with dataset created from PDBSELECT is more than 70%.     

A proposed structural model of domain 1 of fasciclin III neural cell adhesion protein based on an inverse folding algorithm.

Fasciclin III is an integral membrane protein expressed on a subset of axons in the developing Drosophila nervous system. It consists of an intracellular domain, a transmembrane region, and an extracellular region composed of three domains, each predicted to form an immunoglobulin-like fold. The most N-terminal of these domains is expected to be important in mediating cell-cell recognition events during nervous system development. To learn more about the structure/function relationships in this cellular recognition molecule, a model structure of this domain was built. A sequence-to-structure alignment algorithm was used to align the protein sequence of the fasciclin III first domain to the immunoglobulin McPC603 structure. Based on this alignment, a model of the domain was built using standard homology modeling techniques. Side-chain conformations were automatically modeled using a rotamer search algorithm and the model was minimized to relax atomic overlaps. The resulting model is compact and has chemical characteristics consistent with related globular protein structures. This model is a de novo test of the sequence-to-structure alignment algorithm and is currently being used as the basis for mutagenesis experiments to discern the parts of the fasciclin III protein that are necessary for homophilic molecular recognition in the developing Drosophila nervous system.     

Construction of hypothetical three-dimensional structure of P2Y1 receptor based on Fourier transform analysis

G protein-coupled receptors constitute a large family of homologous transmembrane proteins that represents one of the most important classes of confirmed drug targets. For novel drug discovery, the 3D structure of target protein is indispensable. To construct hypothetical 3D structures of G protein-coupled receptors, several prediction methods have been proposed. But none of the them has confirmed a correct ligand binding site. In this study we constructed the 3D structure of bovine rhodopsin using the prediction method proposed by Donnelly et al., with some modification. We found that our 3D model showed a good agreement with the reported retinal binding site. Using the similar method, we constructed the 3D structure of the P2Y₁ receptor; one of the G protein-coupled receptors, and showed a binding site of an endogenous ligand, ADP, on the basis of the 3D model and in vitro experimental data. These results should be valuable for design of a specific antagonist for P2Y₁ receptor.     

Bioinformatics methods to predict protein structure and function. A practical approach

Protein structure prediction by using bioinformatics can involve sequence similarity searches, multiple sequence alignments, identification and characterization of domains, secondary structure prediction, solvent accessibility prediction, automatic protein fold recognition, constructing three-dimensional models to atomic detail, and model validation. Not all protein structure prediction projects involve the use of all these techniques. A central part of a typical protein structure prediction is the identification of a suitable structural target from which to extrapolate three-dimensional information for a query sequence. The way in which this is done defines three types of projects. The first involves the use of standard and well-understood techniques. If a structural template remains elusive, a second approach using nontrivial methods is required. If a target fold cannot be reliably identified because inconsistent results have been obtained from nontrivial data analyses, the project falls into the third type of project and will be virtually impossible to complete with any degree of reliability. In this article, a set of protocols to predict protein structure from sequence is presented and distinctions among the three types of project are given. These methods, if used appropriately, can provide valuable indicators of protein structure and function.     

Protein structure refinement based on paramagnetic NMR shifts: applications to wild-type and mutant forms of cytochrome c.

A new approach to NMR solution structure refinement is introduced that uses paramagnetic effects on nuclear chemical shifts as constraints in energy minimization or molecular dynamics calculations. Chemical shift differences between oxidized and reduced forms of horse cytochrome c for more than 300 protons were used as constraints to refine the structure of the wild-type protein in solution and to define the structural changes induced by a Leu 94 to Val mutation. A single round of constrained minimization, using the crystal structure as the starting point, converged to a low-energy structure with an RMS deviation between calculated and observed pseudo-contact shifts of 0.045 ppm, 7.5-fold lower than the starting structure. At the same time, the procedure provided stereospecific assignments for more than 45 pairs of methylene protons and methyl groups. Structural changes caused by the mutation were determined to a precision of better than 0.3 A. Structure determination based on dipolar paramagnetic (pseudocontact) shifts is applicable to molecules containing anisotropic paramagnetic centers with short electronic relaxation times, including numerous naturally occurring metalloproteins, as well as proteins or nucleic acids to which a paramagnetic metal ion or ligand may be attached. The long range of paramagnetic shift effects (up to 20 A from the iron in the case of cytochrome c) provides global structural constraints, which, in conjunction with conventional NMR distance and dihedral angle constraints, will enhance the precision of NMR solution structure determination.     

Human ficolin-2 recognition versatility extended: An update on the binding of ficolin-2 to sulfated/phosphated carbohydrates

Ficolin-2 has been reported to bind to DNA and heparin, but the mechanism involved has not been thoroughly investigated. X-ray studies of the ficolin-2 fibrinogen-like domain in complex with several new ligands now show that sulfate and phosphate groups are prone to bind to the S3 binding site of the protein. Composed of Arg132, Asp133, Thr136 and Lys221, the S3 site was previously shown to mainly bind N-acetyl groups. Furthermore, DNA and heparin compete for binding to ficolin-2. Mutagenesis studies reveal that Arg132, and to a lesser extent Asp133, are important for this binding property. The versatility of the S3 site in binding N-acetyl, sulfate and phosphate groups is discussed through comparisons with homologous fibrinogen-like recognition proteins.     

The dominant role of side-chain backbone interactions in structural realization of amino acid code. ChiRotor: a side-chain prediction algorithm based on side-chain backbone interactions

The basic differences between the 20 natural amino acid residues are due to differences in their side-chain structures. This characteristic design of protein building blocks implies that side-chain-side-chain interactions play an important, even dominant role in 3D-structural realization of amino acid codes. Here we present the results of a comparative analysis of the contributions of side-chain-side-chain (s-s) and side-chain-backbone (s-b) interactions to the stabilization of folded protein structures within the framework of the CHARMm molecular data model. Contrary to intuition, our results suggest that side-chain-backbone interactions play the major role in side-chain packing, in stabilizing the folded structures, and in differentiating the folded structures from the unfolded or misfolded structures, while the interactions between side chains have a secondary effect. An additional analysis of electrostatic energies suggests that combinatorial dominance of the interactions between opposite charges makes the electrostatic interactions act as an unspecific folding force that stabilizes not only native structure, but also compact random conformations. This observation is in agreement with experimental findings that, in the denatured state, the charge-charge interactions stabilize more compact conformations. Taking advantage of the dominant role of side-chain-backbone interactions in side-chain packing to reduce the combinatorial problem, we developed a new algorithm, ChiRotor, for rapid prediction of side-chain conformations. We present the results of a validation study of the method based on a set of high resolution X-ray structures.     

Studies of the zein-like α-prolamins based on an analysis of amino acid sequences: Implications for their evolution and three-dimensional structure

α-Prolamins are the major seed storage proteins of species of the grass tribe Andropogonea. They are unusually rich in glutamine, proline, alanine, and leucine residues and their sequences show a series of tandem repeats presumed to be the result of multiple intragenic duplication. Two new sequences of α-prolamin clones from Coix (pBCX25.12 and pBCX25.10) are compared with similar clones from maize and Sorghum in order to investigate evolutionary relationships between the repeat motifs and to propose a schematic model for their three-dimensional structure based on hydrophobic membrane-helix propensities and helical “wheels.” A scheme is proposed for the most recent events in the evolution of the central part of the molecule (repeats 3 to 8) which involves two partial intragenic duplications and in which contemporary odd-numbered and even-numbered repeats arise from common ancestors, respectively. Each pair of repeats is proposed to form an antiparallel α-helical hairpin and that the helices of the molecule as a whole are arranged on a hexagonal net. The majority of helices show six faces of alternating hydrophobic and polar residues, which give rise to intersticial holes around each helix which alternate in chemical character. The model is consistent with proteins which contain different numbers of repeats, with oligomerization and with the dense packaging of α-prolamins within the protein body of the seed endosperm. © 1993 Wiley-Liss, Inc.     

Using a strategy based on the concept of convergent evolution to identify residue substitutions responsible for thermal adaptation

Factors that are related to thermostability of proteins have been extensively studied in recent years, especially by comparing thermophiles and mesophiles. However, most of them are global characters. It is still not clear how to identify specific residues or fragments which may be more relevant to protein thermostability. Moreover, some of the differences among the thermophiles and mesophiles may be due to phylogenetic differences instead of thermal adaptation. To resolve these problems, I adopted a strategy to identify residue substitutions evolved convergently in thermophiles or mesophiles. These residues may therefore be responsible for thermal adaptation. Four classes of genomes were utilized in this study, including thermophilic archaea, mesophilic archaea, thermophilic bacteria, and mesophilic bacteria. For most clusters of orthologous groups (COGs) with sequences from all of these four classes of genomes, I can identify specific residues or fragments that may potentially be responsible for thermal adaptation. Functional or structural constraints (represented as sequence conservation) were suggested to have higher impact on thermal adaptation than secondary structure or solvent accessibility does. I further compared thermophilic archaea and mesophilic bacteria, and found that the most diverged fragments may not necessarily correspond to the thermostability-determining ones. The usual approach to compare thermophiles and mesophiles without considering phylogenetic relationships may roughly identify sequence features contributing to thermostability; however, to specifically identify residue substitutions responsible for thermal adaptation, one should take sequence evolution into consideration.