Prediction of protein loop geometries in solution

The ability to determine the structure of a protein in solution is a critical tool for structural biology, as proteins in their native state are found in aqueous environments. Using a physical chemistry based prediction protocol, we demonstrate the ability to reproduce protein loop geometries in experimentally derived solution structures. Predictions were run on loops drawn from (1)NMR entries in the Protein Databank (PDB), and from (2) the RECOORD database in which NMR entries from the PDB have been standardized and re-refined in explicit solvent. The predicted structures are validated by comparison with experimental distance restraints, a test of structural quality as defined by the WHAT IF structure validation program, root mean square deviation (RMSD) of the predicted loops to the original structural models, and comparison of precision of the original and predicted ensembles. Results show that for the RECOORD ensembles, the predicted loops are consistent with an average of 95%, 91%, and 87% of experimental restraints for the short, medium and long loops respectively. Prediction accuracy is strongly affected by the quality of the original models, with increases in the percentage of experimental restraints violated of 2% for the short loops, and 9% for both the medium and long loops in the PDB derived ensembles. We anticipate the application of our protocol to theoretical modeling of protein structures, such as fold recognition methods; as well as to experimental determination of protein structures, or segments, for which only sparse NMR restraint data is available.     

Investigation of the utility of selective methyl protonation for determination of membrane protein structures

Polytopic alpha-helical membrane proteins present one of the final frontiers for protein structural biology, with significant challenges causing severe under-representation in the protein structure databank. However, with the advent of hardware and methodology geared to the study of large molecular weight complexes, solution NMR is being increasingly considered as a tool for structural studies of these types of membrane proteins. One method that has the potential to facilitate these studies utilizes uniformly deuterated samples with protons reintroduced at one or two methyl groups of leucine, valine and isoleucine. In this work we demonstrate that in spite of the increased proportion of these amino acids in membrane proteins, the quality of structures that can be obtained from this strategy is similar to that obtained for all alpha-helical water soluble proteins. This is partly attributed to the observation that NOEs between residues within the transmembrane helix did not have an impact on structure quality. Instead the most important factors controlling structure accuracy were the strength of dihedral angle restraints imposed and the number of unique inter-helical pairs of residues constrained by NOEs. Overall these results suggest that the most accurate structures will arise from accurate identification of helical segments and utilization of inter-helical distance restraints from various sources to maximize the distribution of long-range restraints.     

Structure in solution of a four-helix lipid binding protein.

Because of the low solubility of lipids in water, intercellular and intracellular pathways of lipid transfer are necessary, e.g., for membrane formation. The mechanism by which lipids in vivo are transported from their site of biogenesis (endoplasmatic reticulum and the chloroplasts) to their place of action is unknown. Several small plant proteins with the ability to mediate transfer of radiolabeled phospholipids in vitro from liposomal donor membranes to mitochondrial and chloroplast acceptor membranes have been isolated, and a protein with this ability, the nonspecific lipid transfer protein (nsLTP) isolated from barley seeds (bLTP), has been studied here. The structure and the protein lipid interactions of lipid transfer proteins are relevant for the understanding of their function, and here we present the three-dimensional structure in solution of bLTP as determined by NMR spectroscopy. The 1H NMR spectrum of the 91-residue protein was assigned for more than 97% of the protein 1H atoms, and the structure was calculated on the basis of 813 distance restraints from 1H-1H nuclear Overhauser effects, four disulfide bond restraints, from dihedral angle restraints for 66 phi-angles, 61 chi 1 angles, and 2 chi 2 angles, and from 31 sets of hydrogen bond restraints. The solution structure of bLTP consists of four well-defined alpha-helices A-D (A, Cys 3-Gly 19; B, Gly 25-Ala 38; C, Arg 44-Gly 57; D, Leu 63-Cys 73), separated by three short loops that are less well defined and concluded by a well defined C-terminal peptide segment with no observable regular secondary structure. For the 17 structures that are used to represent the solution structure of bLTP, the RMS deviation to an average structure is 0.63 A +/- 0.04 A for backbone atoms and 0.93 A +/- 0.06 A for all heavy atoms. The secondary structure elements and their locations in the sequence resemble those of nsLTP from two other plant species, wheat and maize, whose structures were previously determined (Gincel E et al, 1995, Eur J Biochem 226:413-422; Shin DH et al, 1995, Structure 3:189-199). In bLTP, the residues analogous to those in maize nsLTP that constitute the palmitate binding site are forming a similar hydrophobic cavity and a potential acyl group binding site. Analysis of the solution structure of bLTP and bLTP in complex with a ligand might provide information on the conformational changes in the protein upon ligand binding and subsequently provide information on the mode of ligand uptake and release. In this work, we hope to establish a foundation for further work of determining the solution structure of bLTP in complex with palmitoyl coenzyme A, which is a suitable ligand, and subsequently to outline the mode of ligand binding.     

A refinement protocol to determine structure,topology, and depth of insertion of membrane proteins using hybrid solution and solid-state NMR restraints

To fully describe the fold space and ultimately the biological function of membrane proteins, it is necessary to determine the specific interactions of the protein with the membrane. This property of membrane proteins that we refer to as structural topology cannot be resolved using X-ray crystallography or solution NMR alone. In this article, we incorporate into XPLOR-NIH a hybrid objective function for membrane protein structure determination that utilizes solution and solid-state NMR restraints, simultaneously defining structure, topology, and depth of insertion. Distance and angular restraints obtained from solution NMR of membrane proteins solubilized in detergent micelles are combined with backbone orientational restraints (chemical shift anisotropy and dipolar couplings) derived from solid-state NMR in aligned lipid bilayers. In addition, a supplementary knowledge-based potential, E _z (insertion depth potential), is used to ensure the correct positioning of secondary structural elements with respect to a virtual membrane. The hybrid objective function is minimized using a simulated annealing protocol implemented into XPLOR-NIH software for general use. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Molecular docking of thiamine reveals similarity in binding properties between the prion protein and other thiamine-binding proteins

Prion-induced diseases are a global health concern. The lack of effective therapy and 100 % mortality rates for such diseases have made the prion protein an important target for drug discovery. Previous NMR experimental work revealed that thiamine and its derivatives bind the prion protein in a pocket near the N-terminal loop of helix 1, and conserved intermolecular interactions were noted between thiamine and other thiamine-binding proteins. Furthermore, water-mediated interactions were observed in all of the X-ray crystallographic structures of thiamine-binding proteins, but were not observed in the thiamine–prion NMR study. To better understand the potential role of water in thiamine–prion binding, a docking study was employed using structural X-ray solvent. Before energy minimization, docked thiamine assumed a “V” shape similar to some of the known thiamine-dependent proteins. Following minimization with NMR-derived restraints, the “F” conformation was observed. Our findings confirmed that water is involved in ligand stabilization and phosphate group interaction. The resulting refined structure of thiamine bound to the prion protein allowed the 4-aminopyrimidine ring of thiamine to π-stack with Tyr150, and facilitated hydrogen bonding between Asp147 and the amino group of 4-aminopyrimidine. Investigation of the π-stacking interaction through mutation of the tyrosine residue further revealed its importance in ligand placement. The resulting refined structure is in good agreement with previous experimental restraints, and is consistent with the pharmacophore model of thiamine-binding proteins.     

Assessment of molecular structure using frame-independent orientational restraints derived from residual dipolar couplings

Residual dipolar couplings measured in weakly aligning liquid-crystalline solvent contain valuable information on the structure of biomolecules in solution. Here we demonstrate that dipolar couplings (DCs) can be used to derive a comprehensive set of pairwise angular restraints that do not depend on the orientation of the alignment tensor principal axes. These restraints can be used to assess the agreement between a trial protein structure and a set of experimental dipolar couplings by means of a graphic representation termed a `DC consistency map'. Importantly, these maps can be used to recognize structural elements consistent with the experimental DC data and to identify structural parameters that require further refinement, which could prove important for the success of DC-based structure calculations. This approach is illustrated for the 42 kDa maltodextrin-binding protein.     

Modeling of the three-dimensional structure of polypeptides in solution using potential-scaled/hot-solute molecular dynamics.

We present here an efficient and accurate procedure for modeling of the three-dimensional structures of polypeptides in the explicit solvent water based on molecular dynamics calculations. Using the toxic domain analog of heat-stable enterotoxin as a model peptide, we examined the utilities of two molecular dynamics techniques with the system containing the explicit solvent. One is the potential-scaled molecular dynamics that had been designed for effective conformational analyses of biomolecules with the explicit solvent water by partially scaling down the potential energies involved in the solute molecules. The other is the variation of Berendsen's weak coupling method (referred to as "hot-solute" method), in which only the solute of the system is heated to a high temperature while the solvent is kept at a normal temperature. Each method successfully increased the rate of folding of the peptides, and the most effective was a combination of the two methods. Moreover, the final structure obtained via cooling process successfully reproduced the experimentally known structure from the extended amino acid sequence using only the distance restraints representing three disulfide bonds in the peptide. Additional distance restraints derived from some of the NOE cross peaks accelerated the folding of the peptide, but gave almost the same structure as in the case without these additional restraints. Because a similar calculation without the explicit solvent could not reproduce the known structure, it is suggested that the explicit solvent water could play an important role in the modeling. The methods presented here have the potential for accurate modeling even when less experimental information was available.     

PaleAle 5.0: prediction of protein relative solvent accessibility by deep learning

Predicting the three-dimensional structure of proteins is a long-standing challenge of computational biology, as the structure (or lack of a rigid structure) is well known to determine a protein’s function. Predicting relative solvent accessibility (RSA) of amino acids within a protein is a significant step towards resolving the protein structure prediction challenge especially in cases in which structural information about a protein is not available by homology transfer. Today, arguably the core of the most powerful prediction methods for predicting RSA and other structural features of proteins is some form of deep learning, and all the state-of-the-art protein structure prediction tools rely on some machine learning algorithm. In this article we present a deep neural network architecture composed of stacks of bidirectional recurrent neural networks and convolutional layers which is capable of mining information from long-range interactions within a protein sequence and apply it to the prediction of protein RSA using a novel encoding method that we shall call “clipped”. The final system we present, PaleAle 5.0, which is available as a public server, predicts RSA into two, three and four classes at an accuracy exceeding 80% in two classes, surpassing the performances of all the other predictors we have benchmarked.

     

Mimicking the action of folding chaperones in molecular dynamics simulations: Application to the refinement of homology-based protein structures

A novel method for the refinement of misfolded protein structures is proposed in which the properties of the solvent environment are oscillated in order to mimic some aspects of the role of molecular chaperones play in protein folding in vivo. Specifically, the hydrophobicity of the solvent is cycled by repetitively altering the partial charges on solvent molecules (water) during a molecular dynamics simulation. During periods when the hydrophobicity of the solvent is increased, intramolecular hydrogen bonding and secondary structure formation are promoted. During periods of increased solvent polarity, poorly packed regions of secondary structures are destabilized, promoting structural rearrangement. By cycling between these two extremes, the aim is to minimize the formation of long-lived intermediates. The approach has been applied to the refinement of structural models of three proteins generated by using the ROSETTA procedure for ab initio structure prediction. A significant improvement in the deviation of the model structures from the corresponding experimental structures was observed. Although preliminary, the results indicate computationally mimicking some functions of molecular chaperones in molecular dynamics simulations can promote the correct formation of secondary structure and thus be of general use in protein folding simulations and in the refinement of structural models of small- to medium-size proteins.     

Ensemble modeling of protein disordered states: Experimental restraint contributions and validation

Disordered states of proteins include the biologically functional intrinsically disordered proteins and the unfolded states of normally folded proteins. In recent years, ensemble‐modeling strategies using various experimental measurements as restraints have emerged as powerful means for structurally characterizing disordered states. However, these methods are still in their infancy compared with the structural determination of folded proteins. Here, we have addressed several issues important to ensemble modeling using our ENSEMBLE methodology. First, we assessed how calculating ensembles containing different numbers of conformers affects their structural properties. We find that larger ensembles have very similar properties to smaller ensembles fit to the same experimental restraints, thus allowing a considerable speed improvement in our calculations. In addition, we analyzed the contributions of different experimental restraints to the structural properties of calculated ensembles, enabling us to make recommendations about the experimental measurements that should be made for optimal ensemble modeling. The effects of different restraints, most significantly from chemical shifts, paramagnetic relaxation enhancements and small‐angle X‐ray scattering, but also from other data, underscore the importance of utilizing multiple sources of experimental data. Finally, we validate our ENSEMBLE methodology using both cross‐validation and synthetic experimental restraints calculated from simulated ensembles. Our results suggest that secondary structure and molecular size distribution can generally be modeled very accurately, whereas the accuracy of calculated tertiary structure is dependent on the number of distance restraints used. Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Structural and Functional Restraints on the Occurrence of Single Amino Acid Variations in Human Proteins

Human genetic variation is the incarnation of diverse evolutionary history, which reflects both selectively advantageous and selectively neutral change. In this study, we catalogue structural and functional features of proteins that restrain genetic variation leading to single amino acid substitutions. Our variation dataset is divided into three categories: i) Mendelian disease-related variants, ii) neutral polymorphisms and iii) cancer somatic mutations. We characterize structural environments of the amino acid variants by the following properties: i) side-chain solvent accessibility, ii) main-chain secondary structure, and iii) hydrogen bonds from a side chain to a main chain or other side chains. To address functional restraints, amino acid substitutions in proteins are examined to see whether they are located at functionally important sites involved in protein-protein interactions, protein-ligand interactions or catalytic activity of enzymes. We also measure the likelihood of amino acid substitutions and the degree of residue conservation where variants occur. We show that various types of variants are under different degrees of structural and functional restraints, which affect their occurrence in human proteome.     

NMR structures of paramagnetic metalloproteins

Metalloproteins represent a large share of the proteome and many of them contain paramagnetic metal ions. The knowledge, at atomic resolution, of their structure in solution is important to understand processes in which they are involved, such as electron transfer mechanisms, enzymatic reactions, metal homeostasis and metal trafficking, as well as interactions with their partners. Formerly considered as unfeasible, the first structure in solution by nuclear magnetic resonance (NMR) of a paramagnetic protein was obtained in 1994. Methodological and instrumental advancements pursued over the last decade are such that NMR structure of paramagnetic proteins may be now routinely obtained. We focus here on approaches and problems related to the structure determination of paramagnetic proteins in solution through NMR spectroscopy. After a survey of the background theory, we show how the effects produced by the presence of a paramagnetic metal ion on the NMR parameters, which are in many cases deleterious for the detection of NMR spectra, can be overcome and turned into an additional source of structural restraints. We also briefly address features and perspectives given by the use of 13C-detected protonless NMR spectroscopy for proteins in solution. The structural information obtained through the exploitation of a paramagnetic center are discussed for some Cu2+ -binding proteins and for Ca2+ -binding proteins, where the replacement of a diamagnetic metal ion with suitable paramagnetic metal ions suggests novel approaches to the structural characterization of proteins containing diamagnetic and NMR-silent metal ions.     

MUFOLD: A new solution for protein 3D structure prediction

There have been steady improvements in protein structure prediction during the past 2 decades. However, current methods are still far from consistently predicting structural models accurately with computing power accessible to common users. Toward achieving more accurate and efficient structure prediction, we developed a number of novel methods and integrated them into a software package, MUFOLD. First, a systematic protocol was developed to identify useful templates and fragments from Protein Data Bank for a given target protein. Then, an efficient process was applied for iterative coarse‐grain model generation and evaluation at the Cα or backbone level. In this process, we construct models using interresidue spatial restraints derived from alignments by multidimensional scaling, evaluate and select models through clustering and static scoring functions, and iteratively improve the selected models by integrating spatial restraints and previous models. Finally, the full‐atom models were evaluated using molecular dynamics simulations based on structural changes under simulated heating. We have continuously improved the performance of MUFOLD by using a benchmark of 200 proteins from the Astral database, where no template with >25% sequence identity to any target protein is included. The average root‐mean‐square deviation of the best models from the native structures is 4.28 Å, which shows significant and systematic improvement over our previous methods. The computing time of MUFOLD is much shorter than many other tools, such as Rosetta. MUFOLD demonstrated some success in the 2008 community‐wide experiment for protein structure prediction CASP8. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Distinguishing structural and functional restraints in evolution in order to identify interaction sites

Structural genomics projects are producing many three-dimensional structures of proteins that have been identified only from their gene sequences. It is therefore important to develop computational methods that will predict sites involved in productive intermolecular interactions that might give clues about functions. Techniques based on evolutionary conservation of amino acids have the advantage over physiochemical methods in that they are more general. However, the majority of techniques neither use all available structural and sequence information, nor are able to distinguish between evolutionary restraints that arise from the need to maintain structure and those that arise from function. Three methods to identify evolutionary restraints on protein sequence and structure are described here. The first identifies those residues that have a higher degree of conservation than expected: this is achieved by comparing for each amino acid position the sequence conservation observed in the homologous family of proteins with the degree of conservation predicted on the basis of amino acid type and local environment. The second uses information theory to identify those positions where environment-specific substitution tables make poor predictions of the overall amino acid substitution pattern. The third method identifies those residues that have highly conserved positions when three-dimensional structures of proteins in a homologous family are superposed. The scores derived from these methods are mapped onto the protein three-dimensional structures and contoured, allowing identification clusters of residues with strong evolutionary restraints that are sites of interaction in proteins involved in a variety of functions. Our method differs from other published techniques by making use of structural information to identify restraints that arise from the structure of the protein and differentiating these restraints from others that derive from intermolecular interactions that mediate functions in the whole organism.     

Discarding functional residues from the substitution table improves predictions of active sites within three-dimensional structures

Substitutions of individual amino acids in proteins may be under very different evolutionary restraints depending on their structural and functional roles. The Environment Specific Substitution Table (ESST) describes the pattern of substitutions in terms of amino acid location within elements of secondary structure, solvent accessibility, and the existence of hydrogen bonds between side chains and neighbouring amino acid residues. Clearly amino acids that have very different local environments in their functional state compared to those in the protein analysed will give rise to inconsistencies in the calculation of amino acid substitution tables. Here, we describe how the calculation of ESSTs can be improved by discarding the functional residues from the calculation of substitution tables. Four categories of functions are examined in this study: protein–protein interactions, protein–nucleic acid interactions, protein–ligand interactions, and catalytic activity of enzymes. Their contributions to residue conservation are measured and investigated. We test our new ESSTs using the program CRESCENDO, designed to predict functional residues by exploiting knowledge of amino acid substitutions, and compare the benchmark results with proteins whose functions have been defined experimentally. The new methodology increases the Z-score by 98% at the active site residues and finds 16% more active sites compared with the old ESST. We also find that discarding amino acids responsible for protein–protein interactions helps in the prediction of those residues although they are not as conserved as the residues of active sites. Our methodology can make the substitution tables better reflect and describe the substitution patterns of amino acids that are under structural restraints only.     

Recoverable one-dimensional encoding of three-dimensional protein structures

One-dimensional (1D) structures of proteins such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it is still not clear whether a given set of 1D structures contains sufficient information for recovering the underlying 3D structure. Here we show that the 3D structure of a protein can be recovered from a set of three types of 1D structures, namely, secondary structure, contact number and residue-wise contact order which is introduced here for the first time. Using simulated annealing molecular dynamics simulations, the structures satisfying the given native 1D structural restraints were sought for 16 proteins of various structural classes and of sizes ranging from 56 to 146 residues. By selecting the structures best satisfying the restraints, all the proteins showed a coordinate RMS deviation of <4 A from the native structure, and, for most of them, the deviation was even <2 A. The present result opens a new possibility to protein structure prediction and our understanding of the sequence-structure relationship.     

Water structure in vitamin B12 coenzyme crystals. II. Structural characteristics of the solvent networks.

The geometrical details of the solvent structure in vitamin B12 coenzyme crystals with respect to hydrogen bonding and nonbonded contacts, are described. The individual H-bond geometries varied over wide ranges, similar to those observed in small molecule structures. Large deviations from tetrahedral coordination were found around a majority of the waters. The mutual positions and orientations of the water molecules could not be adequately explained in terms of the H-bonding relationships present in the structure. However, additional investigations, which focused on the short range nonbonded contacts around water positions in a variety of crystal hydrates, revealed several structural regularities (Savage, 1986b). These features relate to the nonbonded O...O, H...O, and H...H interactions, and give rise to a set of repulsive restrictions that are seen to be very much stronger stereochemical restraints than those associated with H-bonding. The short-range restrictions appear largely to govern the local orientational correlations and packing arrangements of the water structure within the coenzyme (and other hydrate) crystals. In more general terms, the inclusion of the nonbonding relationships as well as the attractive H-bonding interactions, leads to a significant increase in our understanding of water structure(s). The repulsive restrictions can be used as stereochemical restraints in the interpretation and refinement of solvent structures within larger hydrate systems, such as protein crystals. They may also be included in potential functions used to simulate solvent structures in aqueous solutions and hydrate systems.     

An improved structural characterisation of reduced French bean plastocyanin based on NMR data and local-elevation molecular dynamics simulation

Deriving structural information about a protein from NMR experimental data is still a non-trivial challenge to computational biochemistry. This is because of the low ratio of the number of independent observables to the number of molecular degrees of freedom, the approximations involved in the different relationships between particular observable quantities and molecular conformation, and the averaged character of the experimental data. For example, protein (3)J-coupling data are seldom used for structure refinement because of the multiple-valuedness and limited accuracy of the Karplus relationship linking a (3)J-coupling to a torsional angle. Moreover, sampling of the large conformational space is still problematic. Using the 99-residue protein plastocyanin as an example we investigated whether use of a thermodynamically calibrated force field, inclusion of solvent degrees of freedom, and application of adaptive local-elevation sampling that accounts for conformational averaging produces a more realistic representation of the ensemble of protein conformations than standard single-structure refinement in a non-explicit solvent using restraints that do not account for averaging and are partly based on non-observed data. Yielding better agreement with observed experimental data, the protein conformational ensemble is less restricted than when using standard single-structure refinement techniques, which are likely to yield a picture of the protein which is too rigid.     

Modeling the structure of agitoxin in complex with the Shaker K+ channel: a computational approach based on experimental distance restraints extracted from thermodynamic mutant cycles

Computational methods are used to determine the three-dimensional structure of the Agitoxin (AgTx2)-Shaker complex. In a first stage, a large number of models of the complex are generated using high temperature molecular dynamics, accounting for side chain flexibility with distance restraints deduced from thermodynamic analysis of double mutant cycles. Four plausible binding mode candidates are found using this procedure. In a second stage, the quality and validity of the resulting complexes is assessed by examining the stability of the binding modes during molecular dynamics simulations with explicit water molecules and by calculating the binding free energies of mutant proteins using a continuum solvent representation and comparing with experimental data. The docking protocol and the continuum solvent model are validated using the Barstar-Barnase and the lysozyme-antibody D1.2 complexes, for which there are high-resolution structures as well as double mutant data. This combination of computational methods permits the identification of two possible structural models of AgTx2 in complex with the Shaker K+ channel, additional structural analysis providing further evidence in favor of a single model. In this final complex, the toxin is bound to the extracellular entrance of the channel along the pore axis via a combination of hydrophobic, hydrogen bonding, and electrostatic interactions. The magnitude of the buried solvent accessible area corresponding to the protein-protein contact is on the order of 1000 A with roughly similar contributions from each of the four subunits. Some side chains of the toxin adopt different conformation than in the experimental solution structure, indicating the importance of an induced-fit upon the formation of the complex. In particular, the side chain of Lys-27, a residue highly conserved among scorpion toxins, points deep into the pore with its positively charge amino group positioned at the outer binding site for K+. Specific site-directed mutagenesis experiments are suggested to verify and confirm the structure of the toxin-channel complex.