Relative stability of protein structures determined by X-ray crystallography or NMR spectroscopy: a molecular dynamics simulation study

Learning Protein Embedding to Improve Protein Fold Recognition Using Deep Metric Learning

Protein fold recognition refers to predicting the most likely fold type of the query protein and is a critical step of protein structure and function prediction. With the popularity of deep learning in bioinformatics, protein fold recognition has obtained impressive progress. In this study, to extract the fold-specific feature to improve protein fold recognition, we proposed a unified deep metric learning framework based on a joint loss function, termed NPCFold. In addition, we also proposed an integrated machine learning model based on the similarity of proteins in various properties, termed NPCFoldpro. Benchmark experiments show both NPCFold and NPCFoldpro outperform existing protein fold recognition methods at the fold level, indicating that our proposed strategies of fusing loss functions and fusing features could improve the fold recognition level.

Performing protein fold recognition by exploiting a stack convolutional neural network with the attention mechanism

Protein fold recognition is a critical step in protein structure and function prediction, and aims to ascertain the most likely fold type of the query protein. As a typical pattern recognition problem, designing a powerful feature extractor and metric function to extract relevant and representative fold-specific features from protein sequences is the key to improving protein fold recognition. In this study, we propose an effective sequence-based approach, called RattnetFold, to identify protein fold types. The basic concept of RattnetFold is to employ a stack convolutional neural network with the attention mechanism that acts as a feature extractor to extract fold-specific features from protein residue-residue contact maps. Moreover, based on the fold-specific features, we leverage metric learning to project fold-specific features into a subspace where similar proteins are closer together and name this approach RattnetFoldPro. Benchmarking experiments illustrate that RattnetFold and RattnetFoldPro enable the convolutional neural networks to efficiently learn the underlying subtle patterns in residue-residue contact maps, thereby improving the performance of protein fold recognition. An online web server of RattnetFold and the benchmark datasets are freely available at http://csbio.njust.edu.cn/bioinf/rattnetfold/.

Improving protein fold recognition using triplet network and ensemble deep learning

Protein fold recognition is a critical step toward protein structure and function prediction, aiming at providing the most likely fold type of the query protein. In recent years, the development of deep learning (DL) technique has led to massive advances in this important field, and accordingly, the sensitivity of protein fold recognition has been dramatically improved. Most DL-based methods take an intermediate bottleneck layer as the feature representation of proteins with new fold types. However, this strategy is indirect, inefficient and conditional on the hypothesis that the bottleneck layer's representation is assumed as a good representation of proteins with new fold types. To address the above problem, in this work, we develop a new computational framework by combining triplet network and ensemble DL. We first train a DL-based model, termed FoldNet, which employs triplet loss to train the deep convolutional network. FoldNet directly optimizes the protein fold embedding itself, making the proteins with the same fold types be closer to each other than those with different fold types in the new protein embedding space. Subsequently, using the trained FoldNet, we implement a new residue-residue contact-assisted predictor, termed FoldTR, which improves protein fold recognition. Furthermore, we propose a new ensemble DL method, termed FSD_XGBoost, which combines protein fold embedding with the other two discriminative fold-specific features extracted by two DL-based methods SSAfold and DeepFR. The Top 1 sensitivity of FSD_XGBoost increases to 74.8% at the fold level, which is ~9% higher than that of the state-of-the-art method. Together, the results suggest that fold-specific features extracted by different DL methods complement with each other, and their combination can further improve fold recognition at the fold level. The implemented web server of FoldTR and benchmark datasets are publicly available at http://csbio.njust.edu.cn/bioinf/foldtr/.

Algorithmic approaches to protein-protein interaction site prediction

Interaction sites on protein surfaces mediate virtually all biological activities, and their identification holds promise for disease treatment and drug design. Novel algorithmic approaches for the prediction of these sites have been produced at a rapid rate, and the field has seen significant advancement over the past decade. However, the most current methods have not yet been reviewed in a systematic and comprehensive fashion. Herein, we describe the intricacies of the biological theory, datasets, and features required for modern protein-protein interaction site (PPIS) prediction, and present an integrative analysis of the state-of-the-art algorithms and their performance. First, the major sources of data used by predictors are reviewed, including training sets, evaluation sets, and methods for their procurement. Then, the features employed and their importance in the biological characterization of PPISs are explored. This is followed by a discussion of the methodologies adopted in contemporary prediction programs, as well as their relative performance on the datasets most recently used for evaluation. In addition, the potential utility that PPIS identification holds for rational drug design, hotspot prediction, and computational molecular docking is described. Finally, an analysis of the most promising areas for future development of the field is presented.

An algorithm to enumerate all possible protein conformations verifying a set of distance constraints

BACKGROUND

The determination of protein structures satisfying distance constraints is an important problem in structural biology. Whereas the most common method currently employed is simulated annealing, there have been other methods previously proposed in the literature. Most of them, however, are designed to find one solution only.

RESULTS

In order to explore exhaustively the feasible conformational space, we propose here an interval Branch-and-Prune algorithm (iBP) to solve the Distance Geometry Problem (DGP) associated to protein structure determination. This algorithm is based on a discretization of the problem obtained by recursively constructing a search space having the structure of a tree, and by verifying whether the generated atomic positions are feasible or not by making use of pruning devices. The pruning devices used here are directly related to features of protein conformations.

CONCLUSIONS

We described the new algorithm iBP to generate protein conformations satisfying distance constraints, that would potentially allows a systematic exploration of the conformational space. The algorithm iBP has been applied on three α-helical peptides.

Long-range conformational transition of a photoswitchable allosteric protein: molecular dynamics simulation study

A local perturbation of a protein may lead to functional changes at some distal site. An example is the PDZ2 domain of human tyrosine phosphatase 1E, which shows an allosteric transition upon binding to a peptide ligand. Recently Buchli et al. presented a time-resolved study of this transition by covalently linking an azobenzene photoswitch across the binding groove and using a femtosecond laser pulse that triggers the cis-trans photoisomerization of azobenzene. To aid the interpretation of these experiments, in this work seven microsecond runs of all-atom molecular dynamics simulations each for the wild-type PDZ2 in the ligand-bound and -free state, as well as the photoswitchable protein (PDZ2S) in the cis and trans states of the photoswitch, in explicit water were conducted. First the theoretical model is validated by recalculating the available NMR data from the simulations. By comparing the results for PDZ2 and PDZ2S, it is analyzed to what extent the photoswitch indeed mimics the free-bound transition. A detailed description of the conformational rearrangement following the cis-trans photoisomerization of PDZ2S reveals a series of photoinduced structural changes that propagate from the anchor residues of the photoswitch via intermediate secondary structure segments to the C-terminus of PDZ2S. The changes of the conformational distribution of the C-terminal region is considered as the distal response of the isolated allosteric protein.

The structure of neuronal calcium sensor-1 in solution revealed by molecular dynamics simulations

Neuronal calcium sensor-1 (NCS-1) is a protein able to trigger signal transduction processes by binding a large number of substrates and re-shaping its structure depending on the environmental conditions. The X-ray crystal structure of the unmyristoilated NCS-1 shows a large solvent-exposed hydrophobic crevice (HC); this HC is partially occupied by the C-terminal tail and thus elusive to the surrounding solvent. We studied the native state of NCS-1 by performing room temperature molecular dynamics (MD) simulations starting from the crystal and the solution structures. We observe relaxation to a state independent of the initial structure, in which the C-terminal tail occupies the HC. We suggest that the C-terminal tail shields the HC binding pocket and modulates the affinity of NCS-1 for its natural targets. By analyzing the topology and nature of the inter-residue potential energy, we provide a compelling description of the interaction network that determines the three-dimensional organization of NCS-1.

Atomic resolution structures of the c-Src SH3 domain in complex with two high-affinity peptides from classes I and II

The atomic resolution crystal structures of complexes between the SH3 domain of the c-Src tyrosine kinase and two high-affinity peptides belonging to class I and class II have been solved. The crystals of the Thr98Asp and Thr98Glu mutants in complex with the APP12 peptide (APPLPPRNRPRL) belonged to the trigonal space group P3121 and in both cases the asymmetric unit was composed of one molecule of the SH3-APP12 complex. The crystals of the Thr98Glu mutant in complex with the VSL12 peptide (VSLARRPLPLP) belonged to the trigonal space group P3221 and the asymmetric unit was also composed of a single molecule of the SH3-VSL12 complex. All crystals were obtained in the presence of PEG 300 under the same conditions as reported for the intertwined dimeric structure of the c-Src SH3 domain, but the presence of the peptide stabilizes the monomeric form of the domain. These structures allow a detailed analysis of the role of salt bridges, cation-π interactions and hydrogen bonds in the binding of proline-rich motifs to the c-Src SH3 domain. Moreover, these crystallographic structures allow the role of water molecules in the binding of these motifs to the c-Src SH3 domain to be studied for the first time.

Resolution-by-proxy: a simple measure for assessing and comparing the overall quality of NMR protein structures

In protein X-ray crystallography, resolution is often used as a good indicator of structural quality. Diffraction resolution of protein crystals correlates well with the number of X-ray observables that are used in structure generation and, therefore, with protein coordinate errors. In protein NMR, there is no parameter identical to X-ray resolution. Instead, resolution is often used as a synonym of NMR model quality. Resolution of NMR structures is often deduced from ensemble precision, torsion angle normality and number of distance restraints per residue. The lack of common techniques to assess the resolution of X-ray and NMR structures complicates the comparison of structures solved by these two methods. This problem is sometimes approached by calculating "equivalent resolution" from structure quality metrics. However, existing protocols do not offer a comprehensive assessment of protein structure as they calculate equivalent resolution from a relatively small number (<5) of protein parameters. Here, we report a development of a protocol that calculates equivalent resolution from 25 measurable protein features. This new method offers better performance (correlation coefficient of 0.92, mean absolute error of 0.28 Å) than existing predictors of equivalent resolution. Because the method uses coordinate data as a proxy for X-ray diffraction data, we call this measure "Resolution-by-Proxy" or ResProx. We demonstrate that ResProx can be used to identify under-restrained, poorly refined or inaccurate NMR structures, and can discover structural defects that the other equivalent resolution methods cannot detect. The ResProx web server is available at http://www.resprox.ca.

Advances in automated NMR protein structure determination

Around half of all protein structures solved nowadays using solution-state nuclear magnetic resonance (NMR) spectroscopy have been because of automated data analysis. The pervasiveness of computational approaches in general hides, however, a more nuanced view in which the full variety and richness of the field appears. This review is structured around a comparison of methods associated with three NMR observables: classical nuclear Overhauser effect (NOE) constraint gathering in contrast with more recent chemical shift and residual dipole coupling (RDC) based protocols. In each case, the emphasis is placed on the latest research, covering mainly the past 5 years. By describing both general concepts and representative programs, the objective is to map out a field in which--through the very profusion of approaches--it is all too easy to lose one's bearings.

Modeling neuronal nicotinic and GABA receptors: important interface salt-links and protein dynamics

Protein motions in the Cys-loop ligand-gated ion receptors that govern the gating mechanism are still not well understood. The details as to how motions in the ligand-binding domain are translated to the transmembrane domain and how subunit rotations are linked to bring about the cooperative movements involved in gating are under investigation. Homology models of the alpha4beta2 nicotinic acetylcholine (nACh) and beta2alpha1gamma2 GABA receptors were constructed based on the torpedo neuromuscular-like nicotinic receptor structure. The template constructed for the full electron microscopy structure must be considered more reliable for structure-function studies due to the preservation of the E45-R209 salt-link. Many other salt-links are seen to transiently form, including switching off of the E45-R209 link, within a network of potential salt-links at the binding domain to the transmembrane domain interface region. Several potentially important intersubunit salt-links form in both the nAChR and GABAR structures during the simulation and appear conserved across many subunit combinations, such as the salt-link between alpha4.E262 and beta2.K255 in nAChR (beta2.E262 and alpha1.K263 in GABAR), at the top of the pore-lining M2 helices, and the intersubunit link of R210 on the M1-linker to E168 on the beta8-sheet of the adjacent subunit in the GABA receptor (E175-K46 being the structurally equivalent link in the nAChR, with reversed polarity). A network of other salt-links may be vital for transmitting the cooperative gating motions between subunits that become biased upon ligand binding. The changes seen in the simulations suggest that this network of salt-links helps to set limits and specific states for the conformational changes involved in gating of the receptor. We hope that these hypotheses will be tested experimentally in the near future.

X-ray vs. NMR structures as templates for computational protein design

Certain protein-design calculations involve using an experimentally determined high-resolution structure as a template to identify new sequences that can adopt the same fold. This approach has led to the successful design of many novel, well-folded, native-like proteins. Although any atomic-resolution structure can serve as a template in such calculations, most successful designs have used high-resolution crystal structures. Because there are many proteins for which crystal structures are not available, it is of interest whether nuclear magnetic resonance (NMR) templates are also appropriate. We have analyzed differences between using X-ray and NMR templates in side-chain repacking and design calculations. We assembled a database of 29 proteins for which both a high-resolution X-ray structure and an ensemble of NMR structures are available. Using these pairs, we compared the rotamericity, chi(1)-angle recovery, and native-sequence recovery of X-ray and NMR templates. We carried out design using RosettaDesign on both types of templates, and compared the energies and packing qualities of the resulting structures. Overall, the X-ray structures were better templates for use with Rosetta. However, for approximately 20% of proteins, a member of the reported NMR ensemble gave rise to designs with similar properties. Re-evaluating RosettaDesign structures with other energy functions indicated much smaller differences between the two types of templates. Ultimately, experiments are required to confirm the utility of particular X-ray and NMR templates. But our data suggest that the lack of a high-resolution X-ray structure should not preclude attempts at computational design if an NMR ensemble is available.

Heterogeneity and dynamics in villin headpiece crystal structures

The villin headpiece domain (HP67) is the C-terminal F-actin-binding motif that confers F-actin-bundling activity to villin, a component of the actin bundles that support the brush-border microvilli. It has been investigated extensively by both experimental and theoretical measurements. Our laboratory, for example, has determined both its NMR and its crystal structures. This study presents the structures of HP67 and its pH-stabilized mutant (H41Y) in a different crystal form and space group. For both constructs, two molecules are found in each asymmetric unit in the new space group P6(1). While one of the two structures (Mol A) is structurally similar to our previously determined structure (Mol X), the other (Mol B) has significant deviations, especially in the N-terminal subdomain, where lattice contacts do not appear to contribute to the difference. In addition, the structurally most different crystal structure, Mol B, is actually closer to the averaged NMR structure. Harmonic motions, as suggested by the B-factor profiles, differ between these crystal structures; crystal structures from the same space group share a similar pattern. Thus, heterogeneity and dynamics are observed in different crystal structures of the same protein even for a protein as small as villin headpiece.

Correlated motions and interactions at the onset of the DNA-induced partial unfolding of Ets-1

The binding of the Ets-1 transcription factor to its target DNA sequence is characterized by a highly unusual conformational change consisting of the unfolding of inhibitory helix 1 (HI-1). To probe the interactions that lead to this unfolding, we performed molecular dynamics simulations of the folded states of apo-Ets-1 and the Ets-1-DNA complex. The simulations showed large differences in correlated motions between helix 4 (H4) and HI-1. In apo-Ets-1, H4 and HI-1 moved in-phase and stabilized each other by hydrogen bonding and macrodipolar interactions, whereas in the DNA-bound state, the motion was out-of-phase, with a disruption of the stabilizing interactions. This change in motion was due to hydrogen-bonding interactions between helix 1 (H1) and the DNA. The dipolar energy between H1 and H4 was modulated by hydrogen bonds between H1 and DNA, and, in accordance with experiments, elimination of the hydrogen bonds increased the stability of HI-1. The simulations confirm that the hydrogen bonds between H1 and DNA act as a conformational switch and show that the presence of DNA is communicated from H1 to H4, destabilizing HI-1. The calculations reveal a critical role for correlated motions at the onset of the DNA-induced unfolding.

Interactions of the pleckstrin homology domain with phosphatidylinositol phosphate and membranes: characterization via molecular dynamics simulations

The mechanism of interaction of pleckstrin homology (PH) domains with phosphatidylinositol 4,5-bisphosphate (PIP 2)-containing lipid bilayers remains uncertain. While crystallographic studies have emphasized PH-inositol 1,4,5-trisphosphate (IP 3) interactions, biophysical studies indicate a degree of less specific protein-bilayer interactions. We have used molecular dynamics simulations to characterize the interactions of the PH domain from phospholipase C-delta1 with IP 3 and with PIP 2, the latter in lipid bilayers and in detergent micelles. Simulations of the PH domain in water reveal a reduction in protein flexibility when IP 3 is bound. Simulations of the PH domain bound to PIP 2 in lipid bilayers indicate a tightening of ligand-protein interactions relative to the PH-IP 3 complex, alongside formation of H-bonds between PH side chains and lipid (PC) headgroups, and a degree of penetration of hydrophobic side chains into the core of the bilayer. Comparison with simulations of the PH-bound domain to a PC bilayer in the absence of PIP 2 suggests that the presence of PIP 2 increases the extent of PH-membrane interactions. Thus, comparative molecular dynamics simulations reveal how a PI-binding domain undergoes changes in conformational dynamics on binding to a PIP 2-containing membrane and how interactions additional to those with the PI headgroup are formed.

Outer membrane proteins: comparing X-ray and NMR structures by MD simulations in lipid bilayers

The structures of three bacterial outer membrane proteins (OmpA, OmpX and PagP) have been determined by both X-ray diffraction and NMR. We have used multiple (7 x 15 ns) MD simulations to compare the conformational dynamics resulting from the X-ray versus the NMR structures, each protein being simulated in a lipid (DMPC) bilayer. Conformational drift was assessed via calculation of the root mean square deviation as a function of time. On this basis the 'quality' of the starting structure seems mainly to influence the simulation stability of the transmembrane beta-barrel domain. Root mean square fluctuations were used to compare simulation mobility as a function of residue number. The resultant residue mobility profiles were qualitatively similar for the corresponding X-ray and NMR structure-based simulations. However, all three proteins were generally more mobile in the NMR-based than in the X-ray simulations. Principal components analysis was used to identify the dominant motions within each simulation. The first two eigenvectors (which account for >50% of the protein motion) reveal that such motions are concentrated in the extracellular loops and, in the case of PagP, in the N-terminal alpha-helix. Residue profiles of the magnitude of motions corresponding to the first two eigenvectors are similar for the corresponding X-ray and NMR simulations, but the directions of these motions correlate poorly reflecting incomplete sampling on a approximately 10 ns timescale.

Effects of surface water on protein dynamics studied by a novel coarse-grained normal mode approach

Normal mode analysis (NMA) has received much attention as a direct approach to extract the collective motions of macromolecules. However, the stringent requirement of computational resources by classical all-atom NMA limits the size of the macromolecules to which the method is normally applied. We implemented a novel coarse-grained normal mode approach based on partitioning the all-atom Hessian matrix into relevant and nonrelevant parts. It is interesting to note that, using classical all-atom NMA results as a reference, we found that this method generates more accurate results than do other coarse-grained approaches, including elastic network model and block normal mode approaches. Moreover, this new method is effective in incorporating the energetic contributions from the nonrelevant atoms, including surface water molecules, into the coarse-grained protein motions. The importance of such improvements is demonstrated by the effect of surface water to shift vibrational modes to higher frequencies and by an increase in overlap of the coarse-grained eigenvector space (the motion directions) with that obtained from molecular dynamics simulations of solvated protein in a water box. These results not only confirm the quality of our method but also point out the importance of incorporating surface structural water in studying protein dynamics.

How sensitive are nanosecond molecular dynamics simulations of proteins to changes in the force field?

The sensitivity of molecular dynamics simulations to variations in the force field has been examined in relation to a set of 36 structures corresponding to 31 proteins simulated by using different versions of the GROMOS force field. The three parameter sets used (43a1, 53a5, and 53a6) differ significantly in regard to the nonbonded parameters for polar functional groups and their ability to reproduce the correct solvation and partitioning behavior of small molecular analogues of the amino acid side chains. Despite the differences in the force field parameters no major differences could be detected in a wide range of structural properties such as the root-mean-square deviation from the experimental structure, radii of gyration, solvent accessible surface, secondary structure, or hydrogen bond propensities on a 5 to 10 ns time scale. The small differences that were observed correlated primarily with the presence of charged residues as opposed to residues that differed most between the parameter sets. The work highlights the variation that can be observed in nanosecond simulations of protein systems and implications of this for force field validation, as well as for the analysis of protein simulations in general.

The conformational landscape of the ribosomal protein S15 and its influence on the protein interaction with 16S RNA

The interaction between the ribosomal protein S15 and its binding sites in the 16S RNA was examined from two points of view. First, the isolated protein S15 was studied by comparing NMR conformer sets, available in the PDB and recalculated using the CNS-ARIA protocol. Molecular dynamics (MD) trajectories were then recorded starting from a conformer of each set. The recalculation of the S15 NMR structure, as well as the recording of MD trajectories, reveals that several orientations of the N-terminal alpha-helix alpha1 with respect to the structure core are populated. MD trajectories of the complex between the ribosomal protein S15 and RNA were also recorded in the presence and absence of Mg(2+) ions. The Mg(2+) ions are hexacoordinated by water and RNA oxygens. The coordination spheres mainly interact with the RNA phosphodiester backbone, reducing the RNA mobility and inducing electrostatic screening. When the Mg(2+) ions are removed, the internal mobility of the RNA and of the protein increases at the interaction interface close to the RNA G-U/G-C motif as a result of a gap between the phosphate groups in the UUCG capping tetraloop and of the disruption of S15-RNA hydrogen bonds in that region. On the other hand, several S15-RNA hydrogen bonds are reinforced, and water bridges appear between the three-way junction region and S15. The network of hydrogen bonds observed in the loop between alpha1 and alpha2 is consequently reorganized. In the absence of Mg(2+), this network has the same pattern as the network observed in the isolated protein, where the helix alpha1 is mobile with respect to the protein core. The presence of Mg(2+) ions may thus play a role in stabilizing the orientation of the helix alpha1 of S15.

Cold-active enzymes studied by comparative molecular dynamics simulation

Enzymes from cold-adapted species are significantly more active at low temperatures, even those close to zero Celsius, but the rationale of this adaptation is complex and relatively poorly understood. It is commonly stated that there is a relationship between the flexibility of an enzyme and its catalytic activity at low temperature. This paper gives the results of a study using molecular dynamics simulations performed for five pairs of enzymes, each pair comprising a cold-active enzyme plus its mesophilic or thermophilic counterpart. The enzyme pairs included alpha-amylase, citrate synthase, malate dehydrogenase, alkaline protease and xylanase. Numerous sites with elevated flexibility were observed in all enzymes; however, differences in flexibilities were not striking. Nevertheless, amino acid residues common in both enzymes of a pair (not present in insertions of a structure alignment) are generally more flexible in the cold-active enzymes. The further application of principle component analysis to the protein dynamics revealed that there are differences in the rate and/or extent of opening and closing of the active sites. The results indicate that protein dynamics play an important role in catalytic processes where structural rearrangements, such as those required for active site access by substrate, are involved. They also support the notion that cold adaptation may have evolved by selective changes in regions of enzyme structure rather than in global change to the whole protein.

TASSER-based refinement of NMR structures

The TASSER structure prediction algorithm is employed to investigate whether NMR structures can be moved closer to their corresponding X-ray counterparts by automatic refinement procedures. The benchmark protein dataset includes 61 nonhomologous proteins whose structures have been determined by both NMR and X-ray experiments. Interestingly, by starting from NMR structures, the majority (79%) of TASSER refined models show a structural shift toward their X-ray structures. On average, the TASSER refined models have a root-mean-square-deviation (RMSD) from the X-ray structure of 1.785 A (1.556 A) over the entire chain (aligned region), while the average RMSD between NMR and X-ray structures (RMSD(NMR_X-ray)) is 2.080 A (1.731 A). For all proteins having a RMSD(NMR_X-ray) >2 A, the TASSER refined structures show consistent improvement. However, for the 34 proteins with a RMSD(NMR_X-ray) <2 A, there are only 21 cases (60%) where the TASSER model is closer to the X-ray structure than NMR, which may be due to the inherent resolution of TASSER. We also compare the TASSER models with 12 NMR models in the RECOORD database that have been recalculated recently by Nederveen et al. from original NMR restraints using the newest molecular dynamics tools. In 8 of 12 cases, TASSER models show a smaller RMSD to X-ray structures; in 3 of 12 cases, where RMSD(NMR_X-ray) <1 A, RECOORD does better than TASSER. These results suggest that TASSER can be a useful tool to improve the quality of NMR structures.

Mimicking the action of GroEL in molecular dynamics simulations: application to the refinement of protein structures

Bacterial chaperonin, GroEL, together with its co-chaperonin, GroES, facilitates the folding of a variety of polypeptides. Experiments suggest that GroEL stimulates protein folding by multiple cycles of binding and release. Misfolded proteins first bind to an exposed hydrophobic surface on GroEL. GroES then encapsulates the substrate and triggers its release into the central cavity of the GroEL/ES complex for folding. In this work, we investigate the possibility to facilitate protein folding in molecular dynamics simulations by mimicking the effects of GroEL/ES namely, repeated binding and release, together with spatial confinement. During the binding stage, the (metastable) partially folded proteins are allowed to attach spontaneously to a hydrophobic surface within the simulation box. This destabilizes the structures, which are then transferred into a spatially confined cavity for folding. The approach has been tested by attempting to refine protein structural models generated using the ROSETTA procedure for ab initio structure prediction. Dramatic improvements in regard to the deviation of protein models from the corresponding experimental structures were observed. The results suggest that the primary effects of the GroEL/ES system can be mimicked in a simple coarse-grained manner and be used to facilitate protein folding in molecular dynamics simulations. Furthermore, the results support the assumption that the spatial confinement in GroEL/ES assists the folding of encapsulated proteins.

Comparison of different torsion angle approaches for NMR structure determination

A new procedure for NMR structure determination, based on the Internal Coordinate Molecular Dynamics (ICMD) approach, is presented. The method finds biopolymer conformations that satisfy usual NMR-derived restraints by using high temperature dynamics in torsion angle space. A variable target function algorithm gradually increases the number of NOE-based restraints applied, with the treatment of ambiguous and floating restraints included. This soft procedure allows combining artificially high temperature with a general purpose force-field including Coulombic and Lennard-Jones non-bonded interactions, which improves the quality of the ensemble of conformations obtained in the gas-phase. The new method is compared to existing algorithms by using the structures of eight ribosomal proteins earlier obtained with state-of-the-art procedures and included into the RECOORD database [Nederveen, A., Doreleijers, J., Vranken, W., Miller, Z., Spronk, C., Nabuurs, S., Guntert, P., Livny, M., Markley, M., Nilges, M., Ulrich, E., Kaptein, R. and Bonvin, A.M. (2005) Proteins, 59, 662-672]. For the majority of tested proteins, the ICMD algorithm shows similar convergence and somewhat better quality Z scores for the phi, psi distributions. The new method is more computationally demanding although the overall load is reasonable.

Membrane protein structure quality in molecular dynamics simulation

Our goal was to assess the relationship between membrane protein quality, output from protein quality checkers and output from molecular dynamics (MD) simulations. Membrane transport proteins are essential for a wide range of cellular processes. Structural features of integral membrane proteins are still under-explored due to experimental limitations in structure determination. Computational techniques can be used to exploit biochemical and medium resolution structural data, as well as sequence homology to known structures, and enable us to explore the structure-function relationships in several transmembrane proteins. The quality of the models produced is vitally important to obtain reliable predictions. An examination of the relationship between model stability in molecular dynamics (MD) simulations derived from RMSD (root mean squared deviation) and structure quality assessment from various protein quality checkers was undertaken. The results were compared to membrane protein structures, solved at various resolution, by either X-ray or electron diffraction techniques. The checking programs could predict the potential success of MD in making functional conclusions. MD stability was shown to be a good indicator for the quality of structures. The quality was also shown to be dependent on the resolution at which the structures were determined.

Comparative study of generalized Born models: protein dynamics

In this work, we compare the results of molecular dynamics simulations involving the application of three generalized Born (GB) models to 10 different proteins. The three GB models, the Still, HCT, and modified analytical generalized Born models, were implemented in the computationally efficient gromacs package. The performance of each model was assessed from the backbone rms deviation from the native structure, the number of native hydrogen bonds retained in the simulation, and the experimental and calculated radius of gyration. Analysis of variance (ANOVA) was used to analyze the results of the simulations. The rms deviation measure was found to be unable to distinguish the quality of the results obtained with the three different GB models, whereas the number of native hydrogen bonds and radius of gyration yielded a statistically meaningful discrimination among models. Our results suggest that, of the three, modified analytical generalized Born yields the best agreement between calculated and experimentally derived structures. More generally, our study highlights the need both to evaluate the effects of different variables on the results of simulations and to verify that the results of molecular dynamics simulations are statistically meaningful.

Validation of the 53A6 GROMOS force field

The quality of biomolecular dynamics simulations relies critically on the force field that is used to describe the interactions between particles in the system. Force fields, which are generally parameterized using experimental data on small molecules, can only prove themselves in realistic simulations of relevant biomolecular systems. In this work, we begin the validation of the new 53A6 GROMOS parameter set by examining three test cases. Simulations of the well-studied 129 residue protein hen egg-white lysozyme, of the DNA dodecamer d(CGCGAATTCGCG)(2), and a proteinogenic beta(3)-dodecapeptide were performed and analysed. It was found that the new parameter set performs as well as the previous parameter sets in terms of protein (45A3) and DNA (45A4) stability and that it is better at describing the folding-unfolding balance of the peptide. The latter is a property that is directly associated with the free enthalpy of hydration, to which the 53A6 parameter set was parameterized.

The Role of Electrostatic Interaction in Triggering the Unraveling of Stable Helix 1 in Normal Prion Protein. A Molecular Dynamics Simulation Investigation

The conversion of normal prion protein (PrPC) into scrapie isoform (PrPSc) is a key event in the pathogenesis of prion diseases. However, the conversion mechanism has given rise to much controversy. For instance, there is much debate on the behavior of helix 1 (H1) in the conversion. A series of experiments demonstrated that H1 in isolated state was very stable under a variety of conditions. But, other experiments indicated that helices 2 and 3 rather than H1 were retained in PrPSc. In this paper, molecular dynamics (MD) simulation is employed to investigate the dynamic behavior of H1. It is revealed that although the helix 1 of Human PrPC (HuPrPC) is very stable in the isolated state, it becomes unstable when incorporated into native HuPrPC, which likely results from the long-range electrostatic interaction between Asp147 and Arg208 located in the helices 1 and 3, respectively. This explanation is supported by experimental evaluation and MD simulation on D147N mutant of HuPrPC that the mutant becomes a little more stable than the wild type HuPrPC. This finding not only help to reconcile the existing debate on the role of helix 1 in the PrPC-->PrPSc transition, but also reveals a possible mechanism for triggering the PrPC-->PrPSc conversion.

Predicting the signaling state of photoactive yellow protein

As a bacterial blue light sensor the photoactive yellow protein (PYP) undergoes conformational changes upon signal transduction. The absorption of a photon triggers a series of events that are initially localized around the protein chromophore, extends to encompass the whole protein within microseconds, and leads to the formation of the transient pB signaling state. We study the formation of this signaling state pB by molecular simulation and predict its solution structure. Conventional straightforward molecular dynamics is not able to address this formation process due to the long (microsecond) timescales involved, which are (partially) caused by the presence of free energy barriers between the metastable states. To overcome these barriers, we employed the parallel tempering (or replica exchange) method, thus enabling us to predict qualitatively the formation of the PYP signaling state pB. In contrast to the receptor state pG of PYP, the characteristics of this predicted pB structure include a wide open chromophore-binding pocket, with the chromophore and Glu(46) fully solvent-exposed. In addition, loss of alpha-helical structure occurs, caused by the opening motion of the chromophore-binding pocket and the disruptive interaction of the negatively charged Glu(46) with the backbone atoms in the hydrophobic core of the N-terminal cap. Recent NMR experiments agree very well with these predictions.

The folding and dimerization of HIV-1 protease: evidence for a stable monomer from simulations

HIV-1 protease (PR) is a major drug target in combating AIDS, as it plays a key role in maturation and replication of the virus. Six FDA-approved drugs are currently in clinical use, all designed to inhibit enzyme activity by blocking the active site, which exists only in the dimer. An alternative inhibition mode would be required to overcome the emergence of drug-resistance through the accumulation of mutations. This might involve inhibiting the formation of the dimer itself. Here, the folding of HIV-1 PR dimer is studied with several simulation models appropriate for folding mechanism studies. Simulations with an off-lattice Gō-model, which corresponds to a perfectly funneled energy landscape, indicate that the enzyme is formed by association of structured monomers. All-atom molecular dynamics simulations strongly support the stability of an isolated monomer. The conjunction of results from a model that focuses on the protein topology and a detailed all-atom force-field model suggests, in contradiction to some reported equilibrium denaturation experiments, that monomer folding and dimerization are decoupled. The simulation result is, however, in agreement with the recent NMR detection of folded monomers of HIV-1 PR mutants with a destabilized interface. Accordingly, the design of dimerization inhibitors should not focus only on the flexible N and C termini that constitute most of the dimer interface, but also on other structured regions of the monomer. In particular, the relatively high phi values for residues 23-35 and 79-87 in both the folding and binding transition states, together with their proximity to the interface, highlight them as good targets for inhibitor design.

DRESS: a database of REfined solution NMR structures

Several studies have shown that biomolecular NMR structures are often of lower quality when compared to crystal structures, and consequently they are often excluded from structural analyses. We present a publicly available database of re-refined NMR structures, exhibiting significantly improved quality. This database (available at http://www.cmbi.kun.nl/dress/) presents a uniformly refined and validated set of structural models that improves the value of these NMR structures as input for experimental and theoretical studies in many fields of research.

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.

Refinement of homology-based protein structures by molecular dynamics simulation techniques

The use of classical molecular dynamics simulations, performed in explicit water, for the refinement of structural models of proteins generated ab initio or based on homology has been investigated. The study involved a test set of 15 proteins that were previously used by Baker and coworkers to assess the efficiency of the ROSETTA method for ab initio protein structure prediction. For each protein, four models generated using the ROSETTA procedure were simulated for periods of between 5 and 400 nsec in explicit solvent, under identical conditions. In addition, the experimentally determined structure and the experimentally derived structure in which the side chains of all residues had been deleted and then regenerated using the WHATIF program were simulated and used as controls. A significant improvement in the deviation of the model structures from the experimentally determined structures was observed in several cases. In addition, it was found that in certain cases in which the experimental structure deviated rapidly from the initial structure in the simulations, indicating internal strain, the structures were more stable after regenerating the side-chain positions. Overall, the results indicate that molecular dynamics simulations on a tens to hundreds of nanoseconds time scale are useful for the refinement of homology or ab initio models of small to medium-size proteins.