Database algorithm for generating protein backbone and side-chain co-ordinates from a C alpha trace application to model building and detection of co-ordinate errors

CAPS-DB: a structural classification of helix-capping motifs

The regions of the polypeptide chain immediately preceding or following an α-helix are known as Nt- and Ct cappings, respectively. Cappings play a central role stabilizing α-helices due to lack of intrahelical hydrogen bonds in the first and last turn. Sequence patterns of amino acid type preferences have been derived for cappings but the structural motifs associated to them are still unclassified. CAPS-DB is a database of clusters of structural patterns of different capping types. The clustering algorithm is based in the geometry and the (ϕ–ψ)-space conformation of these regions. CAPS-DB is a relational database that allows the user to search, browse, inspect and retrieve structural data associated to cappings. The contents of CAPS-DB might be of interest to a wide range of scientist covering different areas such as protein design and engineering, structural biology and bioinformatics. The database is accessible at: http://www.bioinsilico.org/CAPSDB.

RASP: rapid modeling of protein side chain conformations

MOTIVATION

Modeling of side chain conformations constitutes an indispensable effort in protein structure modeling, protein-protein docking and protein design. Thanks to an intensive attention to this field, many of the existing programs can achieve reasonably good and comparable prediction accuracy. Moreover, in our previous work on CIS-RR, we argued that the prediction with few atomic clashes can complement the current existing methods for subsequent analysis and refinement of protein structures. However, these recent efforts to enhance the quality of predicted side chains have been accompanied by a significant increase of computational cost.

RESULTS

In this study, by mainly focusing on improving the speed of side chain conformation prediction, we present a RApid Side-chain Predictor, called RASP. To achieve a much faster speed with a comparable accuracy to the best existing methods, we not only employ the clash elimination strategy of CIS-RR, but also carefully optimize energy terms and integrate different search algorithms. In comprehensive benchmark testings, RASP is over one order of magnitude faster (~ 40 times over CIS-RR) than the recently developed methods, while achieving comparable or even better accuracy.

PfMDR1: mechanisms of transport modulation by functional polymorphisms

ATP-Binding Cassette (ABC) transporters are efflux pumps frequently associated with multidrug resistance in many biological systems, including malaria. Antimalarial drug-resistance involves an ABC transporter, PfMDR1, a homologue of P-glycoprotein in humans. Twenty years of research have shown that several single nucleotide polymorphisms in pfmdr1 modulate in vivo and/or in vitro drug susceptibility. The underlying physiological mechanism of the effect of these mutations remains unclear. Here we develop structural models for PfMDR1 in different predicted conformations, enabling the study of transporter motion. Such analysis of functional polymorphisms allows determination of their potential role in transport and resistance. The bacterial MsbA ABC pump is a PfMDR1 homologue. MsbA crystals in different conformations were used to create PfMDR1 models with Modeller software. Sequences were aligned with ClustalW and analysed by Ali2D revealing a high level of secondary structure conservation. To validate a potential drug binding pocket we performed antimalarial docking simulations. Using aminoquinoline as probe drugs in PfMDR1 mutated parasites we evaluated the physiology underlying the mechanisms of resistance mediated by PfMDR1 polymorphisms. We focused on the analysis of well known functional polymorphisms in PfMDR1 amino acid residues 86, 184, 1034, 1042 and 1246. Our structural analysis suggested the existence of two different biophysical mechanisms of PfMDR1 drug resistance modulation. Polymorphisms in residues 86/184/1246 act by internal allosteric modulation and residues 1034 and 1042 interact directly in a drug pocket. Parasites containing mutated PfMDR1 variants had a significant altered aminoquinoline susceptibility that appears to be dependent on the aminoquinoline lipophobicity characteristics as well as vacuolar efflux by PfCRT. We previously described the in vivo selection of PfMDR1 polymorphisms under antimalarial drug pressure. Now, together with recent PfMDR1 functional reports, we contribute to the understanding of the specific structural role of these polymorphisms in parasite antimalarial drug response.

Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement

I-TASSER is an automated pipeline for protein tertiary structure prediction using multiple threading alignments and iterative structure assembly simulations. In CASP9 experiments, two new algorithms, QUARK and fragment-guided molecular dynamics (FG-MD), were added to the I-TASSER pipeline for improving the structural modeling accuracy. QUARK is a de novo structure prediction algorithm used for structure modeling of proteins that lack detectable template structures. For distantly homologous targets, QUARK models are found useful as a reference structure for selecting good threading alignments and guiding the I-TASSER structure assembly simulations. FG-MD is an atomic-level structural refinement program that uses structural fragments collected from the PDB structures to guide molecular dynamics simulation and improve the local structure of predicted model, including hydrogen-bonding networks, torsion angles, and steric clashes. Despite considerable progress in both the template-based and template-free structure modeling, significant improvements on protein target classification, domain parsing, model selection, and ab initio folding of β-proteins are still needed to further improve the I-TASSER pipeline.

Exploring the mechanical stability of the C2 domains in human synaptotagmin 1

Human synaptotagmin 1 (Syt1) plays a crucial role in the bending of the membrane during neurotransmitter release at the synapse. Hence, resolving the structural details of Syt1 that underlie its biological function is fundamental for providing mechanistic insights into the nature of the synaptic response. We explored the unfolding micromechanics of Syt1 by analyzing the free energy landscape of the whole molecule and its C2A and C2B domains. We employed a self-organized polymer (SOP) model of a protein chain to carry out pulling simulations, accelerated on graphics processing units (GPUs), under experimental force loads. To resolve the atomic-level details, we complemented the SOP model simulations with atomistic simulations. On the basis of the results obtained, we hypothesize that (1) isolated single domains C2A and C2B present similar mechanical resistance against an applied pulling force but unfold following different kinetic pathways and that (2) C2B is more mechanically resistant in the C2AB complex due to stabilizing interactions with other domains. These findings correlate well with recent atomic force microscopy (AFM) studies on the Syt1 molecule, in which the increase in the unfolding force for C2B was detected when this domain was joined with C2A. Our results also suggest that the linkers (I27 domains) used in the experimental setup can modulate the mechanical behavior of this synaptic protein complex and alter not only the critical force for unfolding but also the unfolding pathways for the C2 domains. Interestingly, the presence of the C2A-C2B domain interface in the C2AB complex confers mechanical stability to either of the C2 domains. Our findings provide new insights into the relative conformational variability of the C2 domains, which we believe to be modulated, to a large extent, by intermolecular coupling with other proteins.

Determinants of coupled transport and uncoupled current by the electrogenic SLC26 transporters

Members of the SLC26 family of anion transporters mediate the transport of diverse molecules ranging from halides to carboxylic acids and can function as coupled transporters or as channels. A unique feature of the two members of the family, Slc26a3 and Slc26a6, is that they can function as both obligate coupled and mediate an uncoupled current, in a channel-like mode, depending on the transported anion. To identify potential features that control the two modes of transport, we performed in silico modeling of Slc26a6, which suggested that the closest potential fold similarity of the Slc26a6 transmembrane domains is to the CLC transporters, despite their minimal sequence identity. Examining the predicted Slc26a6 fold identified a highly conserved glutamate (Glu⁻; Slc26a6(E357)) with the predicted spatial orientation similar to that of the CLC-ec1 E148, which determines coupled or uncoupled transport by CLC-ec1. This raised the question of whether the conserved Glu⁻ in Slc26a6(E357) and Slc26a3(E367) have a role in the unique transport modes by these transporters. Reversing the Glu⁻ charge in Slc26a3 and Slc26a6 resulted in the inhibition of all modes of transport. However, most notably, neutralizing the charge in Slc26a6(E357A) eliminated all forms of coupled transport without affecting the uncoupled current. The Slc26a3(E367A) mutation markedly reduced the coupled transport and converted the stoichiometry of the residual exchange from 2Cl⁻/1HCO₃⁻ to 1Cl⁻/1HCO₃⁻, while completely sparing the current. These findings suggest the possibility that similar structural motif may determine multiple functional modes of these transporters.

A multiscale approach to characterize the early aggregation steps of the amyloid-forming peptide GNNQQNY from the yeast prion sup-35

The self-organization of peptides into amyloidogenic oligomers is one of the key events for a wide range of molecular and degenerative diseases. Atomic-resolution characterization of the mechanisms responsible for the aggregation process and the resulting structures is thus a necessary step to improve our understanding of the determinants of these pathologies. To address this issue, we combine the accelerated sampling properties of replica exchange molecular dynamics simulations based on the OPEP coarse-grained potential with the atomic resolution description of interactions provided by all-atom MD simulations, and investigate the oligomerization process of the GNNQQNY for three system sizes: 3-mers, 12-mers and 20-mers. Results for our integrated simulations show a rich variety of structural arrangements for aggregates of all sizes. Elongated fibril-like structures can form transiently in the 20-mer case, but they are not stable and easily interconvert in more globular and disordered forms. Our extensive characterization of the intermediate structures and their physico-chemical determinants points to a high degree of polymorphism for the GNNQQNY sequence that can be reflected at the macroscopic scale. Detailed mechanisms and structures that underlie amyloid aggregation are also provided.

The formation of amyloid fibrils is associated with many neurodegenerative diseases such as Alzheimer's, Creutzfeld-Jakob, Parkinson's, the Prion disease and diabetes mellitus. In all cases, proteins misfold to form highly ordered insoluble aggregates called amyloid fibrils that deposit intra- and extracellularly and are resistant to proteases. All proteins are believed to have the instrinsic capability of forming amyloid fibrils that share common specific structural properties that have been observed by X-ray crystallography and by NMR. However, little is known about the aggregation dynamics of amyloid assemblies, and their toxicity mechanism is therefore poorly understood. It is believed that small amyloid oligomers, formed on the aggregation pathway of full amyloid fibrils, are the toxic species. A detailed atomic characterization of the oligomerization process is thus necessary to further our understanding of the amyloid oligomer's toxicity. Our approach here is to study the aggregation dynamics of a 7-residue amyloid peptide GNNQQNY through a combination of numerical techniques. Our results suggest that this amyloid sequence can form fibril-like structures and is polymorphic, which agrees with recent experimental observations. The ability to fully characterize and describe the aggregation pathway of amyloid sequences numerically is key to the development of future drugs to target amyloid oligomers.

Structural basis for dual-inhibition mechanism of a non-classical Kazal-type serine protease inhibitor from horseshoe crab in complex with subtilisin

Serine proteases play a crucial role in host-pathogen interactions. In the innate immune system of invertebrates, multi-domain protease inhibitors are important for the regulation of host-pathogen interactions and antimicrobial activities. Serine protease inhibitors, 9.3-kDa CrSPI isoforms 1 and 2, have been identified from the hepatopancreas of the horseshoe crab, Carcinoscorpius rotundicauda. The CrSPIs were biochemically active, especially CrSPI-1, which potently inhibited subtilisin (Ki = 1.43 nM). CrSPI has been grouped with the non-classical Kazal-type inhibitors due to its unusual cysteine distribution. Here we report the crystal structure of CrSPI-1 in complex with subtilisin at 2.6 Å resolution and the results of biophysical interaction studies. The CrSPI-1 molecule has two domains arranged in an extended conformation. These two domains act as heads that independently interact with two separate subtilisin molecules, resulting in the inhibition of subtilisin activity at a ratio of 1:2 (inhibitor to protease). Each subtilisin molecule interacts with the reactive site loop from each domain of CrSPI-1 through a standard canonical binding mode and forms a single ternary complex. In addition, we propose the substrate preferences of each domain of CrSPI-1. Domain 2 is specific towards the bacterial protease subtilisin, while domain 1 is likely to interact with the host protease, Furin. Elucidation of the structure of the CrSPI-1: subtilisin (1∶2) ternary complex increases our understanding of host-pathogen interactions in the innate immune system at the molecular level and provides new strategies for immunomodulation.

Crystal structures of RMI1 and RMI2, two OB-fold regulatory subunits of the BLM complex

Mutations in BLM, a RecQ-like helicase, are linked to the autosomal recessive cancer-prone disorder Bloom's syndrome. BLM associates with topoisomerase (Topo) IIIα, RMI1, and RMI2 to form the BLM complex that is essential for genome stability. The RMI1-RMI2 heterodimer stimulates the dissolution of double Holliday junction into non-crossover recombinants mediated by BLM-Topo IIIα and is essential for stabilizing the BLM complex. However, the molecular basis of these functions of RMI1 and RMI2 remains unclear. Here we report the crystal structures of multiple domains of RMI1-RMI2, providing direct confirmation of the existence of three oligonucleotide/oligosaccharide binding (OB)-folds in RMI1-RMI2. Our structural and biochemical analyses revealed an unexpected insertion motif in RMI1N-OB, which is important for stimulating the dHJ dissolution. We also revealed the structural basis of the interaction between RMI1C-OB and RMI2-OB and demonstrated the functional importance of the RMI1-RMI2 interaction in genome stability maintenance.

A probabilistic and continuous model of protein conformational space for template-free modeling

One of the major challenges with protein template-free modeling is an efficient sampling algorithm that can explore a huge conformation space quickly. The popular fragment assembly method constructs a conformation by stringing together short fragments extracted from the Protein Data Base (PDB). The discrete nature of this method may limit generated conformations to a subspace in which the native fold does not belong. Another worry is that a protein with really new fold may contain some fragments not in the PDB. This article presents a probabilistic model of protein conformational space to overcome the above two limitations. This probabilistic model employs directional statistics to model the distribution of backbone angles and 2(nd)-order Conditional Random Fields (CRFs) to describe sequence-angle relationship. Using this probabilistic model, we can sample protein conformations in a continuous space, as opposed to the widely used fragment assembly and lattice model methods that work in a discrete space. We show that when coupled with a simple energy function, this probabilistic method compares favorably with the fragment assembly method in the blind CASP8 evaluation, especially on alpha or small beta proteins. To our knowledge, this is the first probabilistic method that can search conformations in a continuous space and achieves favorable performance. Our method also generated three-dimensional (3D) models better than template-based methods for a couple of CASP8 hard targets. The method described in this article can also be applied to protein loop modeling, model refinement, and even RNA tertiary structure prediction.

A conserved motif within RAP1 has diversified roles in telomere protection and regulation in different organisms

Repressor activator protein 1 (RAP1) is the most highly conserved telomere protein. It is involved in protecting chromosome ends in fission yeast and promoting gene silencing in Saccharomyces cerevisiae, whereas it represses homology-directed recombination at telomeres in mammals. To understand how RAP1 has such diverse functions at telomeres, we solved the crystal or solution structures of the RAP1 C-terminal (RCT) domains of RAP1 from multiple organisms in complex with their respective protein-binding partners. Our analysis establishes RAP1(RCT) as an evolutionarily conserved protein-protein interaction module. In mammalian and fission yeast cells, this module interacts with TRF2 and Taz1, respectively, targeting RAP1 to chromosome ends for telomere protection. In contrast, S. cerevisiae RAP1 uses its RCT domain to recruit Sir3 to telomeres to mediate gene silencing. Together, our results show that, depending on the organism, the evolutionarily conserved RAP1 RCT motif has diverse functional roles at telomeres.

PCRPi-DB: a database of computationally annotated hot spots in protein interfaces

Protein–protein interactions are central to almost any cellular process. Although typically protein interfaces are large, it is well established that only a relatively small region, the so-called ‘hot spot’, contributes the most to the total binding energy. There is a clear interest in identifying hot spots because of its application in drug discovery and protein design. Presaging Critical Residues in Protein Interfaces Database (PCRPi-DB) is a public repository that archives computationally annotated hot spots in protein complexes for which the 3D structure is known. Hot spots have been annotated using a new and highly accurate computational method developed in the lab. PCRPi-DB is freely available to the scientific community at http://www.bioinsilico.org/PCRPIDB. Besides browsing and querying the contents of the database, extensive documentation and links to relevant on-line resources and contents are available to users. PCRPi-DB is updated on a weekly basis.

Structural bases of dimerization of yeast telomere protein Cdc13 and its interaction with the catalytic subunit of DNA polymerase α

Budding yeast Cdc13-Stn1-Ten1 (CST) complex plays an essential role in telomere protection and maintenance, and has been proposed to be a telomere-specific replication protein A (RPA)-like complex. Previous genetic and structural studies revealed a close resemblance between Stn1-Ten1 and RPA32-RPA14. However, the relationship between Cdc13 and RPA70, the largest subunit of RPA, has remained unclear. Here, we report the crystal structure of the N-terminal OB (oligonucleotide/oligosaccharide binding) fold of Cdc13. Although Cdc13 has an RPA70-like domain organization, the structures of Cdc13 OB folds are significantly different from their counterparts in RPA70, suggesting that they have distinct evolutionary origins. Furthermore, our structural and biochemical analyses revealed unexpected dimerization by the N-terminal OB fold and showed that homodimerization is probably a conserved feature of all Cdc13 proteins. We also uncovered the structural basis of the interaction between the Cdc13 N-terminal OB fold and the catalytic subunit of DNA polymerase α (Pol1), and demonstrated a role for Cdc13 dimerization in Pol1 binding. Analysis of the phenotypes of mutants defective in Cdc13 dimerization and Cdc13-Pol1 interaction revealed multiple mechanisms by which dimerization regulates telomere lengths in vivo. Collectively, our findings provide novel insights into the mechanisms and evolution of Cdc13.

Effect of ligand binding on the intraminimum dynamics of proteins

Effects of ligand binding on protein dynamics are studied via molecular dynamics (MD) simulations on two different enzymes, dihydrofolate reductase (DHFR) and triosephosphate isomerase (TIM), in their unliganded (free) and liganded states. Domain motions in MD trajectories are analyzed by collectivities and rotation angles along the principal components (PCs). DHFR in the free state has well-defined domain rotations, whereas rotations are slightly damped in the binary complex with nicotinamide adenine dinucleotide phosphate (NADPH), and remarkably distorted in the presence of NADP(+) , showing that NADP(+) is solely responsible for the loss of correlation of the domains in DHFR. Although mean square fluctuations of MD simulations in the same PC subspaces are similar for different ligation states, linear stochastic time series models show that backbone flexibility along the first five PCs is decreased upon NADPH and NADP(+) binding in subpicosecond scale. This shows that mobility of the protein along the PCs is closely related with intraminimum dynamics, and alterations in ligation states may change the intraminimum dynamics significantly. Low vibrational frequencies of the alpha-carbon atoms of DHFR are determined from the time series models of a larger number of low indexed PCs, and it is found that number of modes in the lowest frequencies is reduced upon ligand binding. A similar result is obtained for TIM in the unliganded and dihydroxyacetone phosphate bound states. We suggest that stochastic time series modeling is a promising method to be used in determining subtle perturbations in protein dynamics.

Spatio-temporal modeling of signaling protein recruitment to EGFR

Background

A stochastic simulator was implemented to study EGFR signal initiation in 3D with single molecule detail. The model considers previously unexplored contributions to receptor-adaptor coupling, such as receptor clustering and diffusive properties of both receptors and binding partners. The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors.

Results

The model was used to simulate recruitment of four different signaling molecules (Grb2, PLCγ1, Stat5, Shc) to the phosphorylated EGFR tail, with rules based on coarse-grained prediction of spatial constraints. Parameters were derived in part from quantitative immunoblotting, immunoprecipitation and electron microscopy data. Results demonstrate that receptor clustering increases the efficiency of individual adaptor retainment on activated EGFR, an effect that is overridden if crowding is imposed by receptor overexpression. Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering.

Conclusions

Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process.

PRIMO/PRIMONA: a coarse-grained model for proteins and nucleic acids that preserves near-atomistic accuracy

The new coarse graining model PRIMO/PRIMONA for proteins and nucleic acids is proposed. This model combines one to several heavy atoms into coarse-grained sites that are chosen to allow an analytical, high-resolution reconstruction of all-atom models based on molecular bonding geometry constraints. The accuracy of proposed reconstruction method in terms of structure and energetics is tested and compared with other popular reconstruction methods for a variety of protein and nucleic acid test sets.

Quality assessment of protein model-structures using evolutionary conservation

Motivation: Programs that evaluate the quality of a protein structural model are important both for validating the structure determination procedure and for guiding the model-building process. Such programs are based on properties of native structures that are generally not expected for faulty models. One such property, which is rarely used for automatic structure quality assessment, is the tendency for conserved residues to be located at the structural core and for variable residues to be located at the surface.

Results: We present ConQuass, a novel quality assessment program based on the consistency between the model structure and the protein's conservation pattern. We show that it can identify problematic structural models, and that the scores it assigns to the server models in CASP8 correlate with the similarity of the models to the native structure. We also show that when the conservation information is reliable, the method's performance is comparable and complementary to that of the other single-structure quality assessment methods that participated in CASP8 and that do not use additional structural information from homologs.

Availability: A perl implementation of the method, as well as the various perl and R scripts used for the analysis are available at http://bental.tau.ac.il/ConQuass/.

Contact:nirb@tauex.tau.ac.il

Supplementary information:Supplementary data are available at Bioinformatics online.

Structural basis of selective ubiquitination of TRF1 by SCFFbx4

TRF1 is a critical regulator of telomere length. As such, TRF1 levels are regulated by ubiquitin-dependent proteolysis via an SCF E3 ligase where Fbx4 contributes to substrate specification. Here, we report the crystal structure of the Fbx4-TRF1 complex at 2.4 A resolution. Fbx4 contains an unusual substrate-binding domain that adopts a small GTPase fold. Strikingly, this atypical GTPase domain of Fbx4 binds to a globular domain of TRF1 through an intermolecular beta sheet, instead of recognizing short peptides/degrons as often seen in other F-box protein-substrate complexes. Importantly, mutations in this interface abrogate Fbx4-dependent TRF1 binding and ubiquitination. Furthermore, the data demonstrate that recognition of TRF1 by SCF(Fbx4) is regulated by another telomere protein, TIN2. Our results reveal an atypical small GTPase domain within Fbx4 as a substrate-binding motif for SCF(Fbx4) and uncover a mechanism for selective ubiquitination and degradation of TRF1 in telomere homeostasis control.

I-TASSER: fully automated protein structure prediction in CASP8

The I-TASSER algorithm for 3D protein structure prediction was tested in CASP8, with the procedure fully automated in both the Server and Human sections. The quality of the server models is close to that of human ones but the human predictions incorporate more diverse templates from other servers which improve the human predictions in some of the distant homology targets. For the first time, the sequence-based contact predictions from machine learning techniques are found helpful for both template-based modeling (TBM) and template-free modeling (FM). In TBM, although the accuracy of the sequence based contact predictions is on average lower than that from template-based ones, the novel contacts in the sequence-based predictions, which are complementary to the threading templates in the weakly or unaligned regions, are important to improve the global and local packing in these regions. Moreover, the newly developed atomic structural refinement algorithm was tested in CASP8 and found to improve the hydrogen-bonding networks and the overall TM-score, which is mainly due to its ability of removing steric clashes so that the models can be generated from cluster centroids. Nevertheless, one of the major issues of the I-TASSER pipeline is the model selection where the best models could not be appropriately recognized when the correct templates are detected only by the minority of the threading algorithms. There are also problems related with domain-splitting and mirror image recognition which mainly influences the performance of I-TASSER modeling in the FM-based structure predictions.

Template-based protein structure modeling

Functional characterization of a protein is often facilitated by its 3D structure. However, the fraction of experimentally known 3D models is currently less than 1% due to the inherently time-consuming and complicated nature of structure determination techniques. Computational approaches are employed to bridge the gap between the number of known sequences and that of 3D models. Template-based protein structure modeling techniques rely on the study of principles that dictate the 3D structure of natural proteins from the theory of evolution viewpoint. Strategies for template-based structure modeling will be discussed with a focus on comparative modeling, by reviewing techniques available for all the major steps involved in the comparative modeling pipeline.

Stn1-Ten1 is an Rpa2-Rpa3-like complex at telomeres

In budding yeast, Cdc13, Stn1, and Ten1 form a heterotrimeric complex (CST) that is essential for telomere protection and maintenance. Previous bioinformatics analysis revealed a putative oligonucleotide/oligosaccharide-binding (OB) fold at the N terminus of Stn1 (Stn1N) that shows limited sequence similarity to the OB fold of Rpa2, a subunit of the eukaryotic ssDNA-binding protein complex replication protein A (RPA). Here we present functional and structural analyses of Stn1 and Ten1 from multiple budding and fission yeast. The crystal structure of the Candida tropicalis Stn1N complexed with Ten1 demonstrates an Rpa2N-Rpa3-like complex. In both structures, the OB folds of the two components pack against each other through interactions between two C-terminal helices. The structure of the C-terminal domain of Saccharomyces cerevisiae Stn1 (Stn1C) was found to comprise two related winged helix-turn-helix (WH) motifs, one of which is most similar to the WH motif at the C terminus of Rpa2, again supporting the notion that Stn1 resembles Rpa2. The crystal structure of the fission yeast Schizosaccharomyces pombe Stn1N-Ten1 complex exhibits a virtually identical architecture as the C. tropicalis Stn1N-Ten1. Functional analyses of the Candida albicans Stn1 and Ten1 proteins revealed critical roles for these proteins in suppressing aberrant telomerase and recombination activities at telomeres. Mutations that disrupt the Stn1-Ten1 interaction induce telomere uncapping and abolish the telomere localization of Ten1. Collectively, our structural and functional studies illustrate that, instead of being confined to budding yeast telomeres, the CST complex may represent an evolutionarily conserved RPA-like telomeric complex at the 3' overhangs that works in parallel with or instead of the well-characterized POT1-TPP1/TEBPalpha-beta complex.

REMO: A new protocol to refine full atomic protein models from C-alpha traces by optimizing hydrogen-bonding networks

Protein structure prediction approaches usually perform modeling simulations based on reduced representation of protein structures. For biological utilizations, it is an important step to construct full atomic models from the reduced structure decoys. Most of the current full atomic model reconstruction procedures have defects which either could not completely remove the steric clashes among backbone atoms or generate final atomic models with worse topology similarity relative to the native structures than the reduced models. In this work, we develop a new protocol, called REMO, to generate full atomic protein models by optimizing the hydrogen-bonding network with basic fragments matched from a newly constructed backbone isomer library of solved protein structures. The algorithm is benchmarked on 230 nonhomologous proteins with reduced structure decoys generated by I-TASSER simulations. The results show that REMO has a significant ability to remove steric clashes, and meanwhile retains good topology of the reduced model. The hydrogen-bonding network of the final models is dramatically improved during the procedure. The REMO algorithm has been exploited in the recent CASP8 experiment which demonstrated significant improvements of the I-TASSER models in both atomic-level structural refinement and hydrogen-bonding network construction.

Discriminative learning for protein conformation sampling

Protein structure prediction without using templates (i.e., ab initio folding) is one of the most challenging problems in structural biology. In particular, conformation sampling poses as a major bottleneck of ab initio folding. This article presents CRFSampler, an extensible protein conformation sampler, built on a probabilistic graphical model Conditional Random Fields (CRFs). Using a discriminative learning method, CRFSampler can automatically learn more than ten thousand parameters quantifying the relationship among primary sequence, secondary structure, and (pseudo) backbone angles. Using only compactness and self-avoiding constraints, CRFSampler can efficiently generate protein-like conformations from primary sequence and predicted secondary structure. CRFSampler is also very flexible in that a variety of model topologies and feature sets can be defined to model the sequence-structure relationship without worrying about parameter estimation. Our experimental results demonstrate that using a simple set of features, CRFSampler can generate decoys with much higher quality than the most recent HMM model.

Molecular simulations of peptides: a useful tool for the development of new drugs and for the study of molecular recognition

The study of the molecular recognition and self-organization properties of peptides has emerged in recent years as a very active and diverse field of research, ranging from biomedicine to biotechnology and even to material sciences. In the case of biomedicine, peptides can be used as ligands of biological receptors to gain insights into the structural, dynamical, and chemical determinants underlying the formation of complexes and identify new effectors of biological processes of interest. In the case of biotechnology and material science, short sequences have been used to understand the sequence determinants of the formation of ordered supra-molecular structures of nanoscale dimensions. In this work, we will describe our research activities in these two areas of modern chemical biology. In the first part, we will describe the development of a new, specific, potent, and selective anticancer peptide and its use to obtain the information needed to identify a non-peptidic small molecular lead to be used as an inhibitor of cancer growth. In the second part, we will describe the introduction of a new method for the description of the self-organization process at the basis of the growth of ordered supra-molecular structures held together by weak, non-covalent, yet specific interactions.

A Probabilistic Graphical Model for Ab Initio Folding

Despite significant progress in recent years, ab initio folding is still one of the most challenging problems in structural biology. This paper presents a probabilistic graphical model for ab initio folding, which employs Conditional Random Fields (CRFs) and directional statistics to model the relationship between the primary sequence of a protein and its three-dimensional structure. Different from the widely-used fragment assembly method and the lattice model for protein folding, our graphical model can explore protein conformations in a continuous space according to their probability. The probability of a protein conformation reflects its stability and is estimated from PSI-BLAST sequence profile and predicted secondary structure. Experimental results indicate that this new method compares favorably with the fragment assembly method and the lattice model.

Comparative protein structure modeling using MODELLER

Functional characterization of a protein sequence is a common goal in biology, and is usually facilitated by having an accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Comparative protein structure modeling using Modeller

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.

Backrub-like backbone simulation recapitulates natural protein conformational variability and improves mutant side-chain prediction

Incorporation of effective backbone sampling into protein simulation and design is an important step in increasing the accuracy of computational protein modeling. Recent analysis of high-resolution crystal structures has suggested a new model, termed backrub, to describe localized, hinge-like alternative backbone and side-chain conformations observed in the crystal lattice. The model involves internal backbone rotations about axes between C-alpha atoms. Based on this observation, we have implemented a backrub-inspired sampling method in the Rosetta structure prediction and design program. We evaluate this model of backbone flexibility using three different tests. First, we show that Rosetta backrub simulations recapitulate the correlation between backbone and side-chain conformations in the high-resolution crystal structures upon which the model was based. As a second test of backrub sampling, we show that backbone flexibility improves the accuracy of predicting point-mutant side-chain conformations over fixed backbone rotameric sampling alone. Finally, we show that backrub sampling of triosephosphate isomerase loop 6 can capture the millisecond/microsecond oscillation between the open and closed states observed in solution. Our results suggest that backrub sampling captures a sizable fraction of localized conformational changes that occur in natural proteins. Application of this simple model of backbone motions may significantly improve both protein design and atomistic simulations of localized protein flexibility.

Structure-based protein NMR assignments using native structural ensembles

An important step in NMR protein structure determination is the assignment of resonances and NOEs to corresponding nuclei. Structure-based assignment (SBA) uses a model structure ("template") for the target protein to expedite this process. Nuclear vector replacement (NVR) is an SBA framework that combines multiple sources of NMR data (chemical shifts, RDCs, sparse NOEs, amide exchange rates, TOCSY) and has high accuracy when the template is close to the target protein's structure (less than 2 A backbone RMSD). However, a close template may not always be available. We extend the circle of convergence of NVR for distant templates by using an ensemble of structures. This ensemble corresponds to the low-frequency perturbations of the given template and is obtained using normal mode analysis (NMA). Our algorithm assigns resonances and sparse NOEs using each of the structures in the ensemble separately, and aggregates the results using a voting scheme based on maximum bipartite matching. Experimental results on human ubiquitin, using four distant template structures show an increase in the assignment accuracy. Our algorithm also improves the robustness of NVR with respect to structural noise. We provide a confidence measure for each assignment using the percentage of the structures that agree on that assignment. We use this measure to assign a subset of the peaks with even higher accuracy. We further validate our algorithm on data for two additional proteins with NVR. We then show the general applicability of our approach by applying our NMA ensemble-based voting scheme to another SBA tool, MARS. For three test proteins with corresponding templates, including the 370-residue maltose binding protein, we increase the number of reliable assignments made by MARS. Finally, we show that our voting scheme is sound and optimal, by proving that it is a maximum likelihood estimator of the correct assignments.

A historical perspective of template-based protein structure prediction

This chapter presents a broad and a historical overview of the problem of protein structure prediction. Different structure prediction methods, including homology modeling, fold recognition (FR)/protein threading, ab initio/de novo approaches, and hybrid techniques involving multiple types of approaches, are introduced in a historical context. The progress of the field as a whole, especially in the threading/FR area, as reflected by the CASP/CAFASP contests, is reviewed. At the end of the chapter, we discuss the challenging issues ahead in the field of protein structure prediction.

Probing protein fold space with a simplified model

We probe the stability and near-native energy landscape of protein fold space using powerful conformational sampling methods together with simple reduced models and statistical potentials. Fold space is represented by a set of 280 protein domains spanning all topological classes and having a wide range of lengths (33-300 residues) amino acid composition and number of secondary structural elements. The degrees of freedom are taken as the loop torsion angles. This choice preserves the native secondary structure but allows the tertiary structure to change. The proteins are represented by three-point per residue, three-dimensional models with statistical potentials derived from a knowledge-based study of known protein structures. When this space is sampled by a combination of parallel tempering and equi-energy Monte Carlo, we find that the three-point model captures the known stability of protein native structures with stable energy basins that are near-native (all alpha: 4.77 A, all beta: 2.93 A, alpha/beta: 3.09 A, alpha+beta: 4.89 A on average and within 6 A for 71.41%, 92.85%, 94.29% and 64.28% for all-alpha, all-beta, alpha/beta and alpha+beta, classes, respectively). Denatured structures also occur and these have interesting structural properties that shed light on the different landscape characteristics of alpha and beta folds. We find that alpha/beta proteins with alternating alpha and beta segments (such as the beta-barrel) are more stable than proteins in other fold classes.

Evidence that the C-terminal PB2-binding region of the influenza A virus PB1 protein is a discrete alpha-helical domain

The influenza A virus RNA-dependent RNA polymerase is a heterotrimer composed of PB1, PB2 and PA subunits and essential for viral replication. However, little detailed structural information is available for this important enzyme. We show by circular dichroism spectroscopy that polypeptides from the C-terminus of PB1 that are capable of binding efficiently to PB2 fold into stable alpha-helical structures. Structure prediction analysis of this region of PB1 indicates that it likely consists of a three-helical bundle. Deletion of any of the helices abrogated transcriptional function. Thus, PB1 contains a C-terminal alpha-helical PB2-binding domain that is essential for nucleotide polymerization activity.

Backbone building from quadrilaterals: a fast and accurate algorithm for protein backbone reconstruction from alpha carbon coordinates

In this contribution, we present an algorithm for protein backbone reconstruction that comprises very high computational efficiency with high accuracy. Reconstruction of the main chain atomic coordinates from the alpha carbon trace is a common task in protein modeling, including de novo structure prediction, comparative modeling, and processing experimental data. The method employed in this work follows the main idea of some earlier approaches to the problem. The details and careful design of the present approach are new and lead to the algorithm that outperforms all commonly used earlier applications. BBQ (Backbone Building from Quadrilaterals) program has been extensively tested both on native structures as well as on near-native decoy models and compared with the different available existing methods. Obtained results provide a comprehensive benchmark of existing tools and evaluate their applicability to a large scale modeling using a reduced representation of protein conformational space. The BBQ package is available for downloading from our website at http://biocomp.chem.uw.edu.pl/services/BBQ/. This webpage also provides a user manual that describes BBQ functions in detail.

Web services at the European bioinformatics institute

We present a new version of the European Bioinformatics Institute Web Services, a complete suite of SOAP-based web tools for structural and functional analysis, with new and improved applications. New functionality has been added to most of the services already available, and an improved version of the underlying framework has allowed us to include more applications. Information on the EBI Web Services, tutorials and clients can be found at http://www.ebi.ac.uk/Tools/webservices.

Computational sidechain placement and protein mutagenesis with implicit solvent models

Structure prediction and computational protein design should benefit from accurate solvent models. We have applied implicit solvent models to two problems that are central to this area. First, we performed sidechain placement for 29 proteins, using a solvent model that combines a screened Coulomb term with an Accessible Surface Area term (CASA model). With optimized parameters, the prediction quality is comparable with earlier work that omitted electrostatics and solvation altogether. Second, we computed the stability changes associated with point mutations involving ionized sidechains. For over 1000 mutations, including many fully or partly buried positions, we compared CASA and two generalized Born models (GB) with a more accurate model, which solves the Poisson equation of continuum electrostatics numerically. CASA predicts the correct sign and order of magnitude of the stability change for 81% of the mutations, compared to 97% with the best GB. We also considered 140 mutations for which experimental data are available. Comparing to experiment requires additional assumptions about the unfolded protein structure, protein relaxation in response to the mutations, and contributions from the hydrophobic effect. With a simple, commonly-used unfolded state model, the mean unsigned error is 2.1 kcal/mol with both CASA and the best GB. Overall, the electrostatic model is not important for sidechain placement; CASA and GB are equivalent for surface mutations, while GB is far superior for fully or partly buried positions. Thus, for problems like protein design that involve all these aspects, the most recent GB models represent an important step forward. Along with the recent discovery of efficient, pairwise implementations of GB, this will open new possibilities for the computational engineering of proteins.

From coarse-grain to all-atom: Toward multiscale analysis of protein landscapes

Multiscale methods are becoming increasingly promising as a way to characterize the dynamics of large protein systems on biologically relevant time-scales. The underlying assumption in multiscale simulations is that it is possible to move reliably between different resolutions. We present a method that efficiently generates realistic all-atom protein structures starting from the C(alpha) atom positions, as obtained for instance from extensive coarse-grain simulations. The method, a reconstruction algorithm for coarse-grain structures (RACOGS), is validated by reconstructing ensembles of coarse-grain structures obtained during folding simulations of the proteins src-SH3 and S6. The results show that RACOGS consistently produces low energy, all-atom structures. A comparison of the free energy landscapes calculated using the coarse-grain structures versus the all-atom structures shows good correspondence and little distortion in the protein folding landscape.

Andante: reducing side-chain rotamer search space during comparative modeling using environment-specific substitution probabilities

MOTIVATION

The accurate placement of side chains in computational protein modeling and design involves the searching of vast numbers of rotamer combinations.

RESULTS

We have applied the information contained within structurally aligned homologous families, in the form of conserved chi angle conservation rules, to the problem of the comparative modeling. This allows the accurate borrowing of entire side-chain conformations and/or the restriction to high probability rotamer bins. The application of these rules consistently reduces the number of rotamer combinations that need to be searched to trivial values and also reduces the overall side-chain root mean square deviation (rmsd) of the final model. The approach is complementary to current side-chain placement algorithms that use the decomposition of interacting clusters to increase the speed of the placement process.

The POT1-TPP1 telomere complex is a telomerase processivity factor

Telomeres were originally defined as chromosome caps that prevent the natural ends of linear chromosomes from undergoing deleterious degradation and fusion events. POT1 (protection of telomeres) protein binds the single-stranded G-rich DNA overhangs at human chromosome ends and suppresses unwanted DNA repair activities. TPP1 is a previously identified binding partner of POT1 that has been proposed to form part of a six-protein shelterin complex at telomeres. Here, the crystal structure of a domain of human TPP1 reveals an oligonucleotide/oligosaccharide-binding fold that is structurally similar to the beta-subunit of the telomere end-binding protein of a ciliated protozoan, suggesting that TPP1 is the missing beta-subunit of human POT1 protein. Telomeric DNA end-binding proteins have generally been found to inhibit rather than stimulate the action of the chromosome end-replicating enzyme, telomerase. In contrast, we find that TPP1 and POT1 form a complex with telomeric DNA that increases the activity and processivity of the human telomerase core enzyme. We propose that POT1-TPP1 switches from inhibiting telomerase access to the telomere, as a component of shelterin, to serving as a processivity factor for telomerase during telomere extension.

SPINFAST: Using structure alignment profiles to enhance the accuracy and assess the reliability of protein side-chain modeling

We present a novel, knowledge-based method for the side-chain addition step in protein structure modeling. The foundation of the method is a conditional probability equation, which specifies the probability that a side-chain will occupy a specific rotamer state, given a set of evidence about the rotamer states adopted by the side-chains at aligned positions in structurally homologous crystal structures. We demonstrate that our method increases the accuracy of homology model side-chain addition when compared with the widely employed practice of preserving the side-chain conformation from the homology template to the target at conserved residue positions. Furthermore, we demonstrate that our method accurately estimates the probability that the correct rotamer state has been selected. This interesting result implies that our method can be used to understand the reliability of each and every side-chain in a protein homology model.

SABBAC: online Structural Alphabet-based protein BackBone reconstruction from Alpha-Carbon trace

SABBAC is an on-line service devoted to protein backbone reconstruction from alpha-carbon trace. It is based on the assembly of fragments taken from a library of reduced size, selected from the encoding of the protein trace in a hidden Markov model-derived structural alphabet. The assembly of the fragments is achieved by a greedy algorithm, using an energy-based scoring. Alpha-carbon coordinates remain unaffected. SABBAC simply positions the missing backbone atoms, no further refinement is performed. From our tests, SABBAC performs equal or better than other similar on-line approach and is robust to deviations on the alpha-carbon coordinates. It can be accessed at http://bioserv.rpbs.jussieu.fr/SABBAC.html.

Sampling realistic protein conformations using local structural bias

The prediction of protein structure from sequence remains a major unsolved problem in biology. The most successful protein structure prediction methods make use of a divide-and-conquer strategy to attack the problem: a conformational sampling method generates plausible candidate structures, which are subsequently accepted or rejected using an energy function. Conceptually, this often corresponds to separating local structural bias from the long-range interactions that stabilize the compact, native state. However, sampling protein conformations that are compatible with the local structural bias encoded in a given protein sequence is a long-standing open problem, especially in continuous space. We describe an elegant and mathematically rigorous method to do this, and show that it readily generates native-like protein conformations simply by enforcing compactness. Our results have far-reaching implications for protein structure prediction, determination, simulation, and design.

Protein structure prediction is one of the main unsolved problems in computational biology today. A common way to tackle the problem is to generate plausible protein conformations using a fairly inaccurate but fast method, and to evaluate the conformations using an accurate but slow method. The main bottleneck lies in the first step, that is, efficiently exploring protein conformational space. Currently, the best way to do this is to construct plausible structures by stringing together fragments from experimentally determined protein structures, a method called fragment assembly. Hamelryck, Kent, and Krogh present a new method that can efficiently generate protein conformations that are compatible with a given protein sequence. Unlike for existing methods, the generated conformations cover a continuous range and come with an associated probability. The method shows great promise for use in protein structure prediction, determination, simulation, and design.

Predicting the three-dimensional structure of human P-glycoprotein in absence of ATP by computational techniques embodying crosslinking data: insight into the mechanism of ligand migration and binding sites

P-glycoprotein is a membrane protein involved in the phenomenon of multidrug resistance. Its activity and transport function have been largely characterized by various biochemical studies and a low-resolution image has been obtained by electron microscopy. Obtaining a high-resolution structure is, however, still remote due to the inherent difficulties in the experimental determination of membrane protein structures. We present here a three-dimensional (3D) atomic model of P-glycoprotein in absence of ATP. This model was obtained using a combination of computational techniques including comparative modeling and rigid body dynamics simulations that embody all available cysteine disulfide crosslinking data characterizing the whole protein in absence of ATP. The model features rather well most of the experimental interresidue distances derived both in the transmembrane domains and in the nucleotide binding domains. The model is also in good agreement with electron microscopy data, particularly in terms of size and topology. It features a large cavity detected in the protein core into which seven ligands were successfully docked. Their predicted affinity correlates well with experimental values. Locations of docked ligands compare favorably with those suggested by cysteine-scanning data. The finding of different positions both for a single ligand and for different ligands corroborates the experimental evidence indicating the existence of multiple drug binding sites. The interactions identified between P-glycoprotein and the docked ligands reveal that different types of interactions such as H-bonds, pi-pi and cation-pi interactions occur in agreement with a recently proposed pharmacophore model of P-glycoprotein ligands. Furthermore, the model also displays a lateral opening located in the transmembrane domains connecting the lipid bilayer to the central cavity. This feature supports rather well the commonly admitted mechanism of substrate uptake from the lipid bilayer. We propose that this 3D model may be an important tool to understand the structure-function relationship of P-glycoprotein.

Characterization of the residual structure in the unfolded state of the Δ131Δ fragment of staphylococcal nuclease

The determination of the conformational preferences in unfolded states of proteins constitutes an important challenge in structural biology. We use inter-residue distances estimated from site-directed spin-labeling NMR experimental measurements as ensemble-averaged restraints in all-atom molecular dynamics simulations to characterise the residual structure of the Delta131Delta fragment of staphylococcal nuclease under physiological conditions. Our findings indicate that Delta131Delta under these conditions shows a tendency to form transiently hydrophobic clusters similar to those present in the native state of wild-type staphylococcal nuclease. Only rarely, however, all these interactions are simultaneously realized to generate conformations with an overall native topology.

Molecular dynamics simulations of E. coli MsbA transmembrane domain: formation of a semipore structure

The human P-glycoprotein (MDR1/P-gp) is an ATP-binding cassette (ABC) transporter involved in cellular response to chemical stress and failures of anticancer chemotherapy. In the absence of a high-resolution structure for P-gp, we were interested in the closest P-gp homolog for which a crystal structure is available: the bacterial ABC transporter MsbA. Here we present the molecular dynamics simulations performed on the transmembrane domain of the open-state MsbA in a bilayer composed of palmitoyl oleoyl phosphatidylethanolamine lipids. The system studied contained more than 90,000 atoms and was simulated for 50 ns. This simulation shows that the open-state structure of MsbA can be stable in a membrane environment and provides invaluable insights into the structural relationships between the protein and its surrounding lipids. This study reveals the formation of a semipore-like structure stabilized by two key phospholipids which interact with the hinge region of the protein during the entire simulation. Multiple sequence alignments of ABC transporters reveal that one of the residues involved in the interaction with these two phospholipids are under a strong selection pressure specifically applied on the bacterial homologs of MsbA. Hence, comparison of molecular dynamics simulation and phylogenetic data appears as a powerful approach to investigate the functional relevance of molecular events occurring during simulations.

Study of the Villin headpiece folding dynamics by combining coarse-grained Monte Carlo evolution and all-atom molecular dynamics

The folding mechanism of the Villin headpiece (HP36) is studied by means of a novel approach which entails an initial coarse-grained Monte Carlo (MC) scheme followed by all-atom molecular dynamics (MD) simulations in explicit solvent. The MC evolution occurs in a simplified free-energy landscape and allows an efficient selection of marginally-compact structures which are taken as viable initial conformations for the MD. The coarse-grained MC structural representation is connected to the one with atomic resolution through a "fine-graining" reconstruction algorithm. This two-stage strategy is used to select and follow the dynamics of seven different unrelated conformations of HP36. In a notable case the MD trajectory rapidly evolves towards the folded state, yielding a typical root-mean-square deviation (RMSD) of the core region of only 2.4 A from the closest NMR model (the typical RMSD over the whole structure being 4.0 A). The analysis of the various MC-MD trajectories provides valuable insight into the details of the folding and mis-folding mechanisms and particularly about the delicate influence of local and nonlocal interactions in steering the folding process.