Secondary structure determines protein topology

Comparative studies on ion-pair energetic, distribution among three domains of life: Archaea, eubacteria, and eukarya

Salt-bridges play a unique role in the structural and functional stability of proteins, especially under harsh environments. How these salt-bridges contribute to the overall thermodynamic stability of protein structure and function across different domains of life is elusive still date. To address the issue, statistical analyses on the energies of salt-bridges, involved in proteins' structure and function, are performed across three domains of life, that is, archaea, eubacteria, and eukarya. Results show that although the majority of salt-bridges are stable and conserved, yet the stability of archaeal proteins (∆∆G_net = -5.06 ± 3.8) is much more than that of eubacteria (∆∆G_net = -3.7 ± 2.9) and eukarya (∆∆G_net = -3.54 ± 3.1). Unlike earlier study with archaea, in eukarya and eubacteria, not all buried salt-bridge in our dataset are stable. Buried salt-bridges play surprising role in protein stability, whose variations are clearly observed among these domains. Greater desolvation penalty of buried salt-bridges is compensated by stable network of salt-bridges apart from equal contribution of bridge and background energy terms. On the basis proteins' secondary structure, topology, and evolution, our observation shows that salt-bridges when present closer to each other in sequence tend to form a greater number. Overall, our comparative study provides insight into the role of specific electrostatic interactions in proteins from different domains of life, which we hope, would be useful for protein engineering and bioinformatics study.

Stability of the N-Terminal Helix and Its Role in Amyloid Formation of Serum Amyloid A

Colonic amyloidosis is the result of overexpression of the serum amyloid A (SAA) protein in inflammatory bowel disease or colon cancer. Crucial for amyloid formation are the first ten N-terminal residues, which in the crystal structure are a part of a 27-residue long helix. Here, we study this 27-residue N-terminal region of SAA by a multiexchange variant of replica exchange molecular dynamics. An ensemble of configurations is observed, dominated by three motifs: the single helix of the crystal structure, a helix-turn-helix configurations, and such where the residues 14-27 are the part of a helix but the first 13 residues form an extended and disordered segment that is prone to aggregation. The single point mutation E9A shifts the equilibrium to the latter motif, indicating the importance of interactions involving this residue for the stability of the SAA protein.

Synergistic effects of fibronectin and bone morphogenetic protein on the bioactivity of titanium metal

To improve the biological properties of bioactive titanium metal, recombinant human bone morphogenetic protein 2(rhBMP-2) and fibronectin (Fn) were adsorbed on its surface solely or contiguously to modify the anodic oxidized titanium (AO-Ti), acid-alkali-treated titanium (AA-Ti), and polished titanium (P-Ti). It is found that the different bioactive titanium surface structures had great influence on protein adsorption. The adsorption amounts of BMP adsorbed solely and Fn/BMP adsorbed contiguously were AA-Ti > P-Ti > AO-Ti, and that for Fn adsorbed solely was AA-Ti ≈ P-Ti > AO-Ti. The conformation of proteins was changed remarkably after the adsorption. For BMP, the α-helix decreased on AA-Ti and stabilized on P-Ti and AO-Ti. For Fn, the β-sheet on PT-Ti and AA-Ti increased significantly. For Fn/BMP, the percentage of β-sheet on AA-Ti increased, and that of α-helix on all samples was stable. MSCs showed greater adhesion and spreading on Fn/BMP groups. MTT and Elisa tests showed that the synergistic effects of proteins made the cells proliferate and differentiate faster. It indicated both the surface structure and the synergistic effects of proteins could influence the biological properties of titanium metals. It provides research foundation for improving the biological properties of bioactive titanium metals by simultaneous application of several proteins. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 105A: 2485-2498, 2017.

Salt-bridge energetics in halophilic proteins

Halophilic proteins have greater abundance of acidic over basic and very low bulky hydrophobic residues. Classical electrostatic stabilization was suggested as the key determinant for halophilic adaptation of protein. However, contribution of specific electrostatic interactions (i.e. salt-bridges) to overall stability of halophilic proteins is yet to be understood. To understand this, we use Adaptive-Poison-Boltzmann-Solver Methods along with our home-built automation to workout net as well as associated component energy terms such as desolvation energy, bridge energy and background energy for 275 salt-bridges from 20 extremely halophilic proteins. We then perform extensive statistical analysis on general and energetic attributes on these salt-bridges. On average, 8 salt-bridges per 150 residues protein were observed which is almost twice than earlier report. Overall contributions of salt-bridges are −3.0 kcal mol⁻¹. Majority (78%) of salt-bridges in our dataset are stable and conserved in nature. Although, average contributions of component energy terms are equal, their individual details vary greatly from one another indicating their sensitivity to local micro-environment. Notably, 35% of salt-bridges in our database are buried and stable. Greater desolvation penalty of these buried salt-bridges are counteracted by stable network salt-bridges apart from favorable equal contributions of bridge and background terms. Recruitment of extensive network salt-bridges (46%) with a net contribution of −5.0 kcal mol⁻¹ per salt-bridge, seems to be a halophilic design wherein favorable average contribution of background term (−10 kcal mol⁻¹) exceeds than that of bridge term (−7 kcal mol⁻¹). Interiors of proteins from halophiles are seen to possess relatively higher abundance of charge and polar side chains than that of mesophiles which seems to be satisfied by cooperative network salt-bridges. Overall, our theoretical analyses provide insight into halophilic signature in its specific electrostatic interactions which we hope would help in protein engineering and bioinformatics studies.

Principles for designing ideal protein structures

Unlike random heteropolymers, natural proteins fold into unique ordered structures. Understanding how these are encoded in amino-acid sequences is complicated by energetically unfavourable non-ideal features--for example kinked α-helices, bulged β-strands, strained loops and buried polar groups--that arise in proteins from evolutionary selection for biological function or from neutral drift. Here we describe an approach to designing ideal protein structures stabilized by completely consistent local and non-local interactions. The approach is based on a set of rules relating secondary structure patterns to protein tertiary motifs, which make possible the design of funnel-shaped protein folding energy landscapes leading into the target folded state. Guided by these rules, we designed sequences predicted to fold into ideal protein structures consisting of α-helices, β-strands and minimal loops. Designs for five different topologies were found to be monomeric and very stable and to adopt structures in solution nearly identical to the computational models. These results illuminate how the folding funnels of natural proteins arise and provide the foundation for engineering a new generation of functional proteins free from natural evolution.

Arginine and Lysine interactions with π residues in metalloproteins

Metalloproteins have many different functions in cells such as enzymes; signal transduction, transport and storage proteins. About one third of all proteins require metals to carry out their functions. In the present study we have analyzed the roles played by Arg and Lys (cationic side chains) interactions with π (Phe, Tyr or Trp) residues and their role in the structural stability of metalloproteins. These interactions might play an important role in the global conformational stability in metalloproteins. In spite of its lower natural occurrence (1.76%) the number of Trp residues involved in energetically significant interactions is higher in metalloproteins.

Reducing the dimensionality of the protein-folding search problem

How does a folding protein negotiate a vast, featureless conformational landscape and adopt its native structure in biological real time? Motivated by this search problem, we developed a novel algorithm to compare protein structures. Procedures to identify structural analogs are typically conducted in three-dimensional space: the tertiary structure of a target protein is matched against each candidate in a database of structures, and goodness of fit is evaluated by a distance-based measure, such as the root-mean-square distance between target and candidate. This is an expensive approach because three-dimensional space is complex. Here, we transform the problem into a simpler one-dimensional procedure. Specifically, we identify and label the 11 most populated residue basins in a database of high-resolution protein structures. Using this 11-letter alphabet, any protein's three-dimensional structure can be transformed into a one-dimensional string by mapping each residue onto its corresponding basin. Similarity between the resultant basin strings can then be evaluated by conventional sequence-based comparison. The disorder → order folding transition is abridged on both sides. At the onset, folding conditions necessitate formation of hydrogen-bonded scaffold elements on which proteins are assembled, severely restricting the magnitude of accessible conformational space. Near the end, chain topology is established prior to emergence of the close-packed native state. At this latter stage of folding, the chain remains molten, and residues populate natural basins that are approximated by the 11 basins derived here. In essence, our algorithm reduces the protein-folding search problem to mapping the amino acid sequence onto a restricted basin string.

Structural stability studies in adhesion molecules--role of cation-π interactions

Cell adhesion molecules are important for their various roles in many cellular events and responses. In the present study, we have analyzed the roles played by cation-π interactions in the structural stability of adhesion molecules. These interactions are mainly formed by long-range contacts. The occurrence of arginine is higher than lysine to form cation-π interactions. The secondary structure preferences of interacting residues are independent of amino acid class. Cation-π interactions might stabilize the interface between the terminus and core in this class of proteins. The results obtained in the present study will be useful in understanding the contribution of cation-π interactions to the overall stability of adhesion proteins.

Union of geometric constraint-based simulations with molecular dynamics for protein structure prediction

Although proteins are a fundamental unit in biology, the mechanism by which proteins fold into their native state is not well understood. In this work, we explore the assembly of secondary structure units via geometric constraint-based simulations and the effect of refinement of assembled structures using reservoir replica exchange molecular dynamics. Our approach uses two crucial features of these methods: i), geometric simulations speed up the search for nativelike topologies as there are no energy barriers to overcome; and ii), molecular dynamics identifies the low free energy structures and further refines these structures toward the actual native conformation. We use eight alpha-, beta-, and alpha/beta-proteins to test our method. The geometric simulations of our test set result in an average RMSD from native of 3.7 A and this further reduces to 2.7 A after refinement. We also explore the question of robustness of assembly for inaccurate (shifted and shortened) secondary structure. We find that the RMSD from native is highly dependent on the accuracy of secondary structure input, and even slightly shifting the location of secondary structure along the amino acid sequence can lead to a rapid decrease in RMSD to native due to incorrect packing.

Exploring protein structural dissimilarity to facilitate structure classification

BACKGROUND

Classification of newly resolved protein structures is important in understanding their architectural, evolutionary and functional relatedness to known protein structures. Among various efforts to improve the database of Structural Classification of Proteins (SCOP), automation has received particular attention. Herein, we predict the deepest SCOP structural level that an unclassified protein shares with classified proteins with an equal number of secondary structure elements (SSEs).

RESULTS

We compute a coefficient of dissimilarity (Omega) between proteins, based on structural and sequence-based descriptors characterising the respective constituent SSEs. For a set of 1,661 pairs of proteins with sequence identity up to 35%, the performance of Omega in predicting shared Class, Fold and Super-family levels is comparable to that of DaliLite Z score and shows a greater than four-fold increase in the true positive rate (TPR) for proteins sharing the Family level. On a larger set of 600 domains representing 200 families, the performance of Z score improves in predicting a shared Family, but still only achieves about half of the TPR of Omega. The TPR for structures sharing a Super-family is lower than in the first dataset, but Omega performs slightly better than Z score. Overall, the sensitivity of Omega in predicting common Fold level is higher than that of the DaliLite Z score.

CONCLUSION

Classification to a deeper level in the hierarchy is specific and difficult. So the efficiency of Omega may be attractive to the curators and the end-users of SCOP. We suggest Omega may be a better measure for structure classification than the DaliLite Z score, with the caveat that currently we are restricted to comparing structures with equal number of SSEs.

Structural selection of a native fold by peptide recognition. Insights into the thioredoxin folding mechanism

Thioredoxins (TRXs) are monomeric alpha/beta proteins with a fold characterized by a central twisted beta-sheet surrounded by alpha-helical elements. The interaction of the C-terminal alpha-helix 5 of TRX against the remainder of the protein involves a close packing of hydrophobic surfaces, offering the opportunity of studying a fine-tuned molecular recognition phenomenon with long-range consequences on the acquisition of tertiary structure. In this work, we focus on the significance of interactions involving residues L94, L99, E101, F102, L103 and L107 on the formation of the noncovalent complex between reduced TRX1-93 and TRX94-108. The conformational status of the system was assessed experimentally by circular dichroism, intrinsic fluorescence emission and enzymic activity; and theoretically by molecular dynamics simulations (MDS). Alterations in tertiary structure of the complexes, resulting as a consequence of site specific mutation, were also examined. To distinguish the effect of alanine scanning mutagenesis on secondary structure stability, the intrinsic helix-forming ability of the mutant peptides was monitored experimentally by far-UV CD spectroscopy upon the addition of 2,2,2-trifluoroethanol, and also theoretically by Monte Carlo conformational search and MDS. This evidence suggests a key role of residues L99, F102 and L103 on the stabilization of the secondary structure of alpha-helix 5, and on the acquisition of tertiary structure upon complex formation. We hypothesize that the transition between a partially folded and a native-like conformation of reduced TRX1-93 would fundamentally depend on the consolidation of a cooperative tertiary unit based on the interaction between alpha-helix 3 and alpha-helix 5.

Predicting peptide structures in native proteins from physical simulations of fragments

It has long been proposed that much of the information encoding how a protein folds is contained locally in the peptide chain. Here we present a large-scale simulation study designed to examine the extent to which conformations of peptide fragments in water predict native conformations in proteins. We perform replica exchange molecular dynamics (REMD) simulations of 872 8-mer, 12-mer, and 16-mer peptide fragments from 13 proteins using the AMBER 96 force field and the OBC implicit solvent model. To analyze the simulations, we compute various contact-based metrics, such as contact probability, and then apply Bayesian classifier methods to infer which metastable contacts are likely to be native vs. non-native. We find that a simple measure, the observed contact probability, is largely more predictive of a peptide's native structure in the protein than combinations of metrics or multi-body components. Our best classification model is a logistic regression model that can achieve up to 63% correct classifications for 8-mers, 71% for 12-mers, and 76% for 16-mers. We validate these results on fragments of a protein outside our training set. We conclude that local structure provides information to solve some but not all of the conformational search problem. These results help improve our understanding of folding mechanisms, and have implications for improving physics-based conformational sampling and structure prediction using all-atom molecular simulations.

Iterative assembly of helical proteins by optimal hydrophobic packing

We present a method for the computer-based iterative assembly of native-like tertiary structures of helical proteins from alpha-helical fragments. For any pair of helices, our method, called MATCHSTIX, first generates an ensemble of possible relative orientations of the helices with various ways to form hydrophobic contacts between them. Those conformations having steric clashes, or a large radius of gyration of hydrophobic residues, or with helices too far separated to be connected by the intervening linking region, are discarded. Then, we attempt to connect the two helical fragments by using a robotics-based loop-closure algorithm. When loop closure is feasible, the algorithm generates an ensemble of viable interconnecting loops. After energy minimization and clustering, we use a representative set of conformations for further assembly with the remaining helices, adding one helix at a time. To efficiently sample the conformational space, the order of assembly generally proceeds from the pair of helices connected by the shortest loop, followed by joining one of its adjacent helices, always proceeding with the shorter connecting loop. We tested MATCHSTIX on 28 helical proteins each containing up to 5 helices and found it to heavily sample native-like conformations. The average rmsd of the best conformations for the 17 helix-bundle proteins that have 2 or 3 helices is less than 2 A; errors increase somewhat for proteins containing more helices. Native-like states are even more densely sampled when disulfide bonds are known and imposed as restraints. We conclude that, at least for helical proteins, if the secondary structures are known, this rapid rigid-body maximization of hydrophobic interactions can lead to small ensembles of highly native-like structures. It may be useful for protein structure prediction.

Local alignment refinement using structural assessment

Homology modeling is the most commonly used technique to build a three-dimensional model for a protein sequence. It heavily relies on the quality of the sequence alignment between the protein to model and related proteins with a known three dimensional structure. Alignment quality can be assessed according to the physico-chemical properties of the three dimensional models it produces.

In this work, we introduce fifteen predictors designed to evaluate the properties of the models obtained for various alignments. They consist of an energy value obtained from different force fields (CHARMM, ProsaII or ANOLEA) computed on residue selected around misaligned regions. These predictors were evaluated on ten challenging test cases. For each target, all possible ungapped alignments are generated and their corresponding models are computed and evaluated.

The best predictor, retrieving the structural alignment for 9 out of 10 test cases, is based on the ANOLEA atomistic mean force potential and takes into account residues around misaligned secondary structure elements. The performance of the other predictors is significantly lower. This work shows that substantial improvement in local alignments can be obtained by careful assessment of the local structure of the resulting models.

A reexamination of the propensities of amino acids towards a particular secondary structure: classification of amino acids based on their chemical structure

The correlation between the primary and secondary structures of proteins was analysed using a large data set from the Protein Data Bank. Clear preferences of amino acids towards certain secondary structures classify amino acids into four groups: alpha-helix preferrers, strand preferrers, turn and bend preferrers, and His and Cys (the latter two amino acids show no clear preference for any secondary structure). Amino acids in the same group have similar structural characteristics at their Cbeta and Cgamma atoms that predicts their preference for a particular secondary structure. All alpha-helix preferrers have neither polar heteroatoms on Cbeta and Cgamma atoms, nor branching or aromatic group on the Cbeta atom. All strand preferrers have aromatic groups or branching groups on the Cbeta atom. All turn and bend preferrers have a polar heteroatom on the Cbeta or Cgamma atoms or do not have a Cbeta atom at all. These new rules could be helpful in making predictions about non-natural amino acids.

Properties of contact matrices induced by pairwise interactions in proteins

The properties of contact matrices ( C matrices) needed for native proteins to be the lowest-energy conformations are considered in relation to a contact energy matrix ( E matrix). The total conformational energy is assumed to consist of pairwise interaction energies between atoms or residues, each of which is expressed as a product of a conformation-dependent function (an element of the C matrix) and a sequence-dependent energy parameter (an element of the E matrix). Such pairwise interactions in proteins force native C matrices to be in a relationship as if the interactions are a Go-like potential [N. Go, Annu. Rev. Biophys. Bioeng. 12, 183 (1983)] for the native C matrix, because the lowest bound of the total energy function is equal to the total energy of the native conformation interacting in a Go-like pairwise potential. This relationship between C and E matrices corresponds to (a) a parallel relationship between the eigenvectors of the C and E matrices and a linear relationship between their eigenvalues and (b) a parallel relationship between a contact number vector and the principal eigenvectors of the C and E matrices, where the E matrix is expanded in a series of eigenspaces with an additional constant term. The additional constant term in the spectral expansion of the E matrix is indicated by the lowest bound of the total energy function to correspond to a threshold of contact energy that approximately separates native contacts from non-native ones. Inner products between the principal eigenvector of the C matrix, that of the E matrix, and a contact number vector have been examined for 182 proteins, each of which is a representative from each family of the SCOP database [Murzin, J. Mol. Biol. 247, 536 (1995)], and the results indicate the parallel tendencies between those vectors. A statistical contact potential [S. Miyazawa and R. L. Jernigan, Proteins 34, 49 (1999); S. Miyazawa and R. L. Jernigan, Proteins50, 35 (2003)] estimated from protein crystal structures was used to evaluate pairwise residue-residue interactions in the proteins. In addition, the spectral representation of C and E matrices reveals that pairwise residue-residue interactions, which depend only on the types of interacting amino acids, but not on other residues in a protein, are insufficient and other interactions including residue connectivities and steric hindrance are needed to make native structures unique lowest-energy conformations.

Structures, basins, and energies: a deconstruction of the Protein Coil Library

Globular proteins adopt complex folds, composed of organized assemblies of alpha-helix and beta-sheet together with irregular regions that interconnect these scaffold elements. Here, we seek to parse the irregular regions into their structural constituents and to rationalize their formative energetics. Toward this end, we dissected the Protein Coil Library, a structural database of protein segments that are neither alpha-helix nor beta-strand, extracted from high-resolution protein structures. The backbone dihedral angles of residues from coil library segments are distributed indiscriminately across the phi,psi map, but when contoured, seven distinct basins emerge clearly. The structures and energetics associated with the two least-studied basins are the primary focus of this article. Specifically, the structural motifs associated with these basins were characterized in detail and then assessed in simple simulations designed to capture their energetic determinants. It is found that conformational constraints imposed by excluded volume and hydrogen bonding are sufficient to reproduce the observed ,psi distributions of these motifs; no additional energy terms are required. These three motifs in conjunction with alpha-helices, strands of beta-sheet, canonical beta-turns, and polyproline II conformers comprise approximately 90% of all protein structure.

The beta-strand-loop-beta-strand conformation is marginally populated in beta2-microglobulin (20-41) peptide in solution as revealed by replica exchange molecular dynamics simulations

Solid-state NMR study shows that the 22-residue K3 peptide (Ser(20)-Lys(41)) from beta(2)-microglobulin (beta(2)m) adopts a beta-strand-loop-beta-strand conformation in its fibril state. Residue Pro(32) has a trans conformation in the fibril state of the peptide, while it adopts a cis conformation in the native state of full-length beta(2)m. To get insights into the structural properties of the K3 peptide, and determine whether the strand-loop-strand conformation is encoded at the monomeric level, we run all-atom explicit solvent replica exchange molecular dynamics on both the cis and trans variants. Our simulations show that the conformational space of the trans- and cis-K3 peptides is very different, with 1% of the sampled conformations in common at room temperature. In addition, both variants display only 0.3-0.5% of the conformations with beta-strand-loop-beta-strand character. This finding, compared to results on the Alzheimer's Abeta peptide, suggests that the biases toward aggregation leading to the beta-strand-loop-beta-strand conformation in fibrils are peptide-dependent.

Loop-closure principles in protein folding

Simple theoretical concepts and models have been helpful to understand the folding rates and routes of single-domain proteins. As reviewed in this article, a physical principle that appears to underly these models is loop closure.

Building native protein conformation from NMR backbone chemical shifts using Monte Carlo fragment assembly

We have been analyzing the extent to which protein secondary structure determines protein tertiary structure in simple protein folds. An earlier paper demonstrated that three-dimensional structure can be obtained successfully using only highly approximate backbone torsion angles for every residue. Here, the initial information is further diluted by introducing a realistic degree of experimental uncertainty into this process. In particular, we tackle the practical problem of determining three-dimensional structure solely from backbone chemical shifts, which can be measured directly by NMR and are known to be correlated with a protein's backbone torsion angles. Extending our previous algorithm to incorporate these experimentally determined data, clusters of structures compatible with the experimentally determined chemical shifts were generated by fragment assembly Monte Carlo. The cluster that corresponds to the native conformation was then identified based on four energy terms: steric clash, solvent-squeezing, hydrogen-bonding, and hydrophobic contact. Currently, the method has been applied successfully to five small proteins with simple topology. Although still under development, this approach offers promise for high-throughput NMR structure determination.

Protein knots and fold complexity: Some new twists

The current knowledge on topological knots in protein structure is reviewed, considering in turn, knots with three, four and five strand crossings. The latter is the most recent to be identified and has two distinct topological forms. The knot observed in the protein structure is the form that requires the least number of strand crossings to become un-knotted. The position of the chain termini must also correspond to a position that allows (un) knotting in one move. This is postulated as a general property of protein knots and other more complex knots with this property are proposed as the next most likely knots that might be found in a protein. It is also noted that the "Jelly-roll" fold found in some all-beta proteins would provide likely candidates. Alternative measures of knottedness and entanglement are reviewed, including the occurrence of slip-knots. These measures are related to the complexity of the protein fold and may provide useful filters for selecting predicted model structures.

A backbone-based theory of protein folding

Under physiological conditions, a protein undergoes a spontaneous disorder order transition called "folding." The protein polymer is highly flexible when unfolded but adopts its unique native, three-dimensional structure when folded. Current experimental knowledge comes primarily from thermodynamic measurements in solution or the structures of individual molecules, elucidated by either x-ray crystallography or NMR spectroscopy. From the former, we know the enthalpy, entropy, and free energy differences between the folded and unfolded forms of hundreds of proteins under a variety of solvent/cosolvent conditions. From the latter, we know the structures of approximately 35,000 proteins, which are built on scaffolds of hydrogen-bonded structural elements, alpha-helix and beta-sheet. Anfinsen showed that the amino acid sequence alone is sufficient to determine a protein's structure, but the molecular mechanism responsible for self-assembly remains an open question, probably the most fundamental open question in biochemistry. This perspective is a hybrid: partly review, partly proposal. First, we summarize key ideas regarding protein folding developed over the past half-century and culminating in the current mindset. In this view, the energetics of side-chain interactions dominate the folding process, driving the chain to self-organize under folding conditions. Next, having taken stock, we propose an alternative model that inverts the prevailing side-chain/backbone paradigm. Here, the energetics of backbone hydrogen bonds dominate the folding process, with preorganization in the unfolded state. Then, under folding conditions, the resultant fold is selected from a limited repertoire of structural possibilities, each corresponding to a distinct hydrogen-bonded arrangement of alpha-helices and/or strands of beta-sheet.