Protein structure prediction by all-atom free-energy refinement

Background  

The reliable prediction of protein tertiary structure from the amino acid sequence remains challenging even for small proteins. We have developed an all-atom free-energy protein forcefield (PFF01) that we could use to fold several small proteins from completely extended conformations. Because the computational cost of de-novo folding studies rises steeply with system size, this approach is unsuitable for structure prediction purposes. We therefore investigate here a low-cost free-energy relaxation protocol for protein structure prediction that combines heuristic methods for model generation with all-atom free-energy relaxation in PFF01.     

Inter-residue distances derived from fold contact propensities correlate with evolutionary substitution costs

Background  

The wealth of information on protein structure has led to a variety of statistical analyses of the role played by individual amino acid types in the protein fold. In particular, the contact propensities between the various amino acids can be converted into folding energies that have proved useful in structure prediction. The present study addresses the relationship of protein folding propensities to the evolutionary relationship between residues.     

GANDivAWeb: A web server for detecting early folding units ("foldons") from protein 3D structures

Background  

It has long been known that small regions of proteins tend to fold independently and are then stabilized by interactions between these distinct subunits or modules. Such units, also known as autonomous folding units (AFUs) or"foldons" play a key role in protein folding. A knowledge of such early folding units has diverse applications in protein engineering as well as in developing an understanding of the protein folding process. Such AFUs can also be used as model systems in order to study the structural organization of proteins.     

Functional evolution of two subtly different (similar) folds

Background

The function of proteins is a direct consequence of their three-dimensional structure. The structural classification of proteins describes the ways of folding patterns all proteins could adopt. Although, the protein folds were described in many ways the functional properties of individual folds were not studied.

Results

We have analyzed two β-barrel folds generally adopted by small proteins to be looking similar but have different topology. On the basis of the topology they could be divided into two different folds named SH3-fold and OB-fold. There was no sequence homology between any of the proteins considered. The sequence diversity and loop variability was found to be important for various binding functions.

Conclusions

The function of Oligonucleotide/oligosaccharide-binding (OB) fold proteins was restricted to either DNA/RNA binding or sugar binding whereas the Src homology 3 (SH3) domain like proteins bind to a variety of ligands through loop modulations. A question was raised whether the evolution of these two folds was through DNA shuffling.     

A fast SCOP fold classification system using content-based E-Predict algorithm

Background  

Domain experts manually construct the Structural Classification of Protein (SCOP) database to categorize and compare protein structures. Even though using the SCOP database is believed to be more reliable than classification results from other methods, it is labor intensive. To mimic human classification processes, we develop an automatic SCOP fold classification system to assign possible known SCOP folds and recognize novel folds for newly-discovered proteins.     

Sequence based residue depth prediction using evolutionary information and predicted secondary structure

Background  

Residue depth allows determining how deeply a given residue is buried, in contrast to the solvent accessibility that differentiates between buried and solvent-exposed residues. When compared with the solvent accessibility, the depth allows studying deep-level structures and functional sites, and formation of the protein folding nucleus. Accurate prediction of residue depth would provide valuable information for fold recognition, prediction of functional sites, and protein design.     

Implications from a network-based topological analysis of ubiquitin unfolding simulations

Background

The architectural organization of protein structures has been the focus of intense research since it can hopefully lead to an understanding of how proteins fold. In earlier works we had attempted to identify the inherent structural organization in proteins through a study of protein topology. We obtained a modular partitioning of protein structures with the modules correlating well with experimental evidence of early folding units or “foldons”. Residues that connect different modules were shown to be those that were protected during the transition phase of folding.

Methodology/Principal Findings

In this work, we follow the topological path of ubiquitin through molecular dynamics unfolding simulations. We observed that the use of recurrence quantification analysis (RQA) could lead to the identification of the transition state during unfolding. Additionally, our earlier contention that the modules uncovered through our graph partitioning approach correlated well with early folding units was vindicated through our simulations. Moreover, residues identified from native structure as connector hubs and which had been shown to be those that were protected during the transition phase of folding were indeed more stable (less flexible) well beyond the transition state. Further analysis of the topological pathway suggests that the all pairs shortest path in a protein is minimized during folding.

Conclusions

We observed that treating a protein native structure as a network by having amino acid residues as nodes and the non-covalent interactions among them as links allows for the rationalization of many aspects of the folding process. The possibility to derive this information directly from 3D structure opens the way to the prediction of important residues in proteins, while the confirmation of the minimization of APSP for folding allows for the establishment of a potentially useful proxy for kinetic optimality in the validation of sequence-structure predictions.     

A pairwise residue contact area-based mean force potential for discrimination of native protein structure

Background  

Considering energy function to detect a correct protein fold from incorrect ones is very important for protein structure prediction and protein folding. Knowledge-based mean force potentials are certainly the most popular type of interaction function for protein threading. They are derived from statistical analyses of interacting groups in experimentally determined protein structures. These potentials are developed at the atom or the amino acid level. Based on orientation dependent contact area, a new type of knowledge-based mean force potential has been developed.     

Vertical decomposition with Genetic Algorithm for Multiple Sequence Alignment

Background

Mapping protein primary sequences to their three dimensional folds referred to as the 'second genetic code' remains an unsolved scientific problem. A crucial part of the problem concerns the geometrical specificity in side chain association leading to densely packed protein cores, a hallmark of correctly folded native structures. Thus, any model of packing within proteins should constitute an indispensable component of protein folding and design.

Results

In this study an attempt has been made to find, characterize and classify recurring patterns in the packing of side chain atoms within a protein which sustains its native fold. The interaction of side chain atoms within the protein core has been represented as a contact network based on the surface complementarity and overlap between associating side chain surfaces. Some network topologies definitely appear to be preferred and they have been termed 'packing motifs', analogous to super secondary structures in proteins. Study of the distribution of these motifs reveals the ubiquitous presence of typical smaller graphs, which appear to get linked or coalesce to give larger graphs, reminiscent of the nucleation-condensation model in protein folding. One such frequently occurring motif, also envisaged as the unit of clustering, the three residue clique was invariably found in regions of dense packing. Finally, topological measures based on surface contact networks appeared to be effective in discriminating sequences native to a specific fold amongst a set of decoys.

Conclusions

Out of innumerable topological possibilities, only a finite number of specific packing motifs are actually realized in proteins. This small number of motifs could serve as a basis set in the construction of larger networks. Of these, the triplet clique exhibits distinct preference both in terms of composition and geometry.     

Smooth Functional Transition along a Mutational Pathway with an Abrupt Protein Fold Switch

Recent protein design experiments have demonstrated that proteins can migrate between folds through the accumulation of substitution mutations without visiting disordered or nonfunctional points in sequence space. To explore the biophysical mechanism underlying such transitions we use a three-letter continuous protein model with seven atoms per amino acid to provide realistic sequence-structure and sequence-function mappings through explicit simulation of the folding and interaction of model sequences. We start from two 16-amino-acid sequences folding into an α-helix and a β-hairpin, respectively, each of which has a preferred binding partner with 35 amino acids. We identify a mutational pathway between the two folds, which features a sharp fold switch. By contrast, we find that the transition in function is smooth. Moreover, the switch in preferred binding partner does not coincide with the fold switch. Discovery of new folds in evolution might therefore be facilitated by following fitness slopes in sequence space underpinned by binding-induced conformational switching.     

TIM-Finder: A new method for identifying TIM-barrel proteins

Background  

The triosephosphate isomerase (TIM)-barrel fold occurs frequently in the proteomes of different organisms, and the known TIM-barrel proteins have been found to play diverse functional roles. To accelerate the exploration of the sequence-structure protein landscape in the TIM-barrel fold, a computational tool that allows sensitive detection of TIM-barrel proteins is required.     

Type II restriction endonuclease R.Hpy188I belongs to the GIY-YIG nuclease superfamily,but exhibits an unusual active site

Background  

Catalytic domains of Type II restriction endonucleases (REases) belong to a few unrelated three-dimensional folds. While the PD-(D/E)XK fold is most common among these enzymes, crystal structures have been also determined for single representatives of two other folds: PLD (R.BfiI) and half-pipe (R.PabI). Bioinformatics analyses supported by mutagenesis experiments suggested that some REases belong to the HNH fold (e.g. R.KpnI), and that a small group represented by R.Eco29kI belongs to the GIY-YIG fold. However, for a large fraction of REases with known sequences, the three-dimensional fold and the architecture of the active site remain unknown, mostly due to extreme sequence divergence that hampers detection of homology to enzymes with known folds.     

A comprehensive analysis of non-sequential alignments between all protein structures

Background  

The majority of relations between proteins can be represented as a conventional sequential alignment. Nevertheless, unusual non-sequential alignments with different connectivity of the aligned fragments in compared proteins have been reported by many researchers. It is interesting to understand those non-sequential alignments; are they unique, sporadic cases or they occur frequently; do they belong to a few specific folds or spread among many different folds, as a common feature of protein structure. We present here a comprehensive large-scale study of non-sequential alignments between available protein structures in Protein Data Bank.     

Contribution to the Prediction of the Fold Code: Application to Immunoglobulin and Flavodoxin Cases

Background

Folding nucleus of globular proteins formation starts by the mutual interaction of a group of hydrophobic amino acids whose close contacts allow subsequent formation and stability of the 3D structure. These early steps can be predicted by simulation of the folding process through a Monte Carlo (MC) coarse grain model in a discrete space. We previously defined MIRs (Most Interacting Residues), as the set of residues presenting a large number of non-covalent neighbour interactions during such simulation. MIRs are good candidates to define the minimal number of residues giving rise to a given fold instead of another one, although their proportion is rather high, typically [15-20]% of the sequences. Having in mind experiments with two sequences of very high levels of sequence identity (up to 90%) but different folds, we combined the MIR method, which takes sequence as single input, with the “fuzzy oil drop” (FOD) model that requires a 3D structure, in order to estimate the residues coding for the fold. FOD assumes that a globular protein follows an idealised 3D Gaussian distribution of hydrophobicity density, with the maximum in the centre and minima at the surface of the “drop”. If the actual local density of hydrophobicity around a given amino acid is as high as the ideal one, then this amino acid is assigned to the core of the globular protein, and it is assumed to follow the FOD model. Therefore one obtains a distribution of the amino acids of a protein according to their agreement or rejection with the FOD model.

Results

We compared and combined MIR and FOD methods to define the minimal nucleus, or keystone, of two populated folds: immunoglobulin-like (Ig) and flavodoxins (Flav). The combination of these two approaches defines some positions both predicted as a MIR and assigned as accordant with the FOD model. It is shown here that for these two folds, the intersection of the predicted sets of residues significantly differs from random selection. It reduces the number of selected residues by each individual method and allows a reasonable agreement with experimentally determined key residues coding for the particular fold. In addition, the intersection of the two methods significantly increases the specificity of the prediction, providing a robust set of residues that constitute the folding nucleus.     

Ab initio modeling of small proteins by iterative TASSER simulations

Background  

Predicting 3-dimensional protein structures from amino-acid sequences is an important unsolved problem in computational structural biology. The problem becomes relatively easier if close homologous proteins have been solved, as high-resolution models can be built by aligning target sequences to the solved homologous structures. However, for sequences without similar folds in the Protein Data Bank (PDB) library, the models have to be predicted from scratch. Progress in the ab initio structure modeling is slow. The aim of this study was to extend the TASSER (threading/assembly/refinement) method for the ab initio modeling and examine systemically its ability to fold small single-domain proteins.     

Structural and mechanistic investigations on Salmonella typhimurium acetate kinase (AckA): identification of a putative ligand binding pocket at the dimeric interface

Background

A large number of studies have been carried out to obtain amino acid propensities for ??-helices and ??-sheets. The obtained propensities for ??-helices are consistent with each other, and the pair-wise correlation coefficient is frequently high. On the other hand, the ??-sheet propensities obtained by several studies differed significantly, indicating that the context significantly affects ??-sheet propensity.

Results

We calculated amino acid propensities for ??-helices and ??-sheets for 39 and 24 protein folds, respectively, and addressed whether they correlate with the fold. The propensities were also calculated for exposed and buried sites, respectively. Results showed that ??-helix propensities do not differ significantly by fold, but ??-sheet propensities are diverse and depend on the fold. The propensities calculated for exposed sites and buried sites are similar for ??-helix, but such is not the case for the ??-sheet propensities. We also found some fold dependence on amino acid frequency in ??-strands. Folds with a high Ser, Thr and Asn content at exposed sites in ??-strands tend to have a low Leu, Ile, Glu, Lys and Arg content (correlation coefficient = ?0.90) and to have flat ??-sheets. At buried sites in ??-strands, the content of Tyr, Trp, Gln and Ser correlates negatively with the content of Val, Ile and Leu (correlation coefficient = ?0.93). "All-??" proteins tend to have a higher content of Tyr, Trp, Gln and Ser, whereas "??/??" proteins tend to have a higher content of Val, Ile and Leu.

Conclusions

The ??-helix propensities are similar for all folds and for exposed and buried residues. However, ??-sheet propensities calculated for exposed residues differ from those for buried residues, indicating that the exposed-residue fraction is one of the major factors governing amino acid composition in ??-strands. Furthermore, the correlations we detected suggest that amino acid composition is related to folding properties such as the twist of a ??-strand or association between two ?? sheets.     

Effects of Topology and Sequence in Protein Folding Linked via Conformational Fluctuations

Experiments have compared the folding of proteins with different amino acid sequences but the same basic structure, or fold. Results indicate that folding is robust to sequence variations for proteins with some nonlocal folds, such as all-β, whereas the folding of more local, all-α proteins typically exhibits a stronger sequence dependence. Here, we use a coarse-grained model to systematically study how variations in sequence perturb the folding energy landscapes of three model sequences with 3α, 4β + α, and β-barrel folds, respectively. These three proteins exhibit folding features in line with experiments, including expected rank order in the cooperativity of the folding transition and stability-dependent shifts in the location of the free-energy barrier to folding. Using a generalized-ensemble simulation approach, we determine the thermodynamics of around 2000 sequence variants representing all possible hydrophobic or polar single- and double-point mutations. From an analysis of the subset of stability-neutral mutations, we find that folding is perturbed in a topology-dependent manner, with the β-barrel protein being the most robust. Our analysis shows, in particular, that the magnitude of mutational perturbations of the transition state is controlled in part by the size or “width” of the underlying conformational ensemble. This result suggests that the mutational robustness of the folding of the β-barrel protein is underpinned by its conformationally restricted transition state ensemble, revealing a link between sequence and topological effects in protein folding.