Challenges at the frontiers of structural biology

Mass Spectrometry- and Computational Structural Biology-Based Investigation of Proteins and Peptides

Recent developments of mass spectrometry (MS) allow us to identify, estimate, and characterize proteins and protein complexes. At the same time, structural biology helps to determine the protein structure and its structure-function relationship. Together, they aid to understand the protein structure, property, function, protein-complex assembly, protein-protein interaction, and dynamics. The present chapter is organized with illustrative results to demonstrate how experimental mass spectrometry can be combined with computational structural biology for detailed studies of protein's structures. We have used tumor differentiation factor protein/peptide as ligand and Hsp70/Hsp90 as receptor protein as examples to study ligand-protein interaction. To investigate possible protein conformation, we will describe two proteins-lysozyme and myoglobin. As an application of MS-based assignment of disulfide bridges, the case of the spider venom polypeptide Phα1β will also be discussed.

In Situ Imaging and Structure Determination of Bacterial Toxin Delivery Systems Using Electron Cryotomography

Determining the three-dimensional structure of biomacromolecules at high resolution in their native cellular environment is a major challenge for structural biology. Toward this end, electron cryotomography (ECT) allows large bio-macromolecular assemblies to be imaged directly in their hydrated physiological milieu to ~4 nm resolution. Combining ECT with other techniques like fluorescent imaging, immunogold labeling, and genetic manipulation has allowed the in situ investigation of complex biological processes at macromolecular resolution. Furthermore, the advent of cryogenic focused ion beam (FIB) milling has extended the domain of ECT to include regions even deep within thick eukaryotic cells. Anticipating two audiences (scientists who just want to understand the potential and general workflow involved and scientists who are learning how to do the work themselves), here we present both a broad overview of this kind of work and a step-by-step example protocol for ECT and subtomogram averaging using the Legionella pneumophila Dot/Icm type IV secretion system (T4SS) as a case study. While the general workflow is presented in step-by-step detail, we refer to online tutorials, user's manuals, and other training materials for the essential background understanding needed to perform each step.

Induced fit docking, pharmacophore modeling, and molecular dynamic simulations on thiazolidinedione derivatives to explore key interactions with Tyr48 in polyol pathway

To obtain a scientific thought and expedition to explore key interactions with Tyr48 in aldose reductase (ALR), combined study of pharmacophore modeling, induced fit docking, and dynamics studies were performed on ALR. A stereo chemically and energetically valid model of ALR-NADP+ complex was developed using homology modeling technique. Statistically a significant five point pharmacophore model was designed on a set of 54 thiazolidinedione derivatives with good external and internal predictive ability. Rigid and induced fit docking protocols were applied on ALR protein for both with and without NADP+ cofactor to identify a suitable binding mode that facilitates the key hydrogen bond interactions with Tyr48. Docking of thiazolidinedione derivatives into ALR-NADP+ complex gave more promising results by reducing false positive binding of inhibitors into the co-factor binding site. Structural changes within Try48 and Asp43 during the binding process in enzyme inhibitor complex were analyzed using molecular dynamics (MD) simulations. The results obtained from dynamic simulations emphasized the role of Tyr48 in maintaining inter or intra molecular hydrogen bond interaction with the protein or inhibitor respectively. New molecules were designed and checked for their binding interactions and showed improved results compared to existing thiazolidinediones derivatives. Hence, these combined protocols will be helpful and cooperative to design and optimize molecules with better inhibitory activity against the biologically active target.

Utility of computational structural biology in mass spectrometry

Recent developments of mass spectrometry (MS) allow us to identify, estimate, and characterize proteins and protein complexes. At the same time, structural biology helps to determine the protein structure and its structure-function relationship. Together, they aid to understand the protein structure, property, function, protein-complex assembly, protein-protein interaction and dynamics. The present chapter is organized with illustrative results to demonstrate how experimental mass spectrometry can be combined with computational structural biology for detailed studies of protein's structures. We have used tumor differentiation factor protein/peptide as ligand and Hsp70/Hsp90 as receptor protein as examples to study ligand-protein interaction. To investigate possible protein conformation we will describe two proteins, lysozyme and myoglobin.

Constructing and validating initial Cα models from subnanometer resolution density maps with pathwalking

A significant number of macromolecular structures solved by electron cryo-microscopy and X-ray crystallography obtain resolutions of 3.5-6Å, at which direct atomistic interpretation is difficult. To address this, we developed pathwalking, a semi-automated protocol to enumerate reasonable Cα models from near-atomic resolution density maps without a structural template or sequence-structure correspondence. Pathwalking uses an approach derived from the Traveling Salesman Problem to rapidly generate an ensemble of initial models for individual proteins, which can later be optimized to produce full atomic models. Pathwalking can also be used to validate and identify potential structural ambiguities in models generated from near-atomic resolution density maps. In this work, examples from the EMDB and PDB are used to assess the broad applicability and accuracy of our method. With the growing number of near-atomic resolution density maps from cryo-EM and X-ray crystallography, pathwalking can become an important tool in modeling protein structures.

Modeling protein structure at near atomic resolutions with Gorgon

Electron cryo-microscopy (cryo-EM) has played an increasingly important role in elucidating the structure and function of macromolecular assemblies in near native solution conditions. Typically, however, only non-atomic resolution reconstructions have been obtained for these large complexes, necessitating computational tools for integrating and extracting structural details. With recent advances in cryo-EM, maps at near-atomic resolutions have been achieved for several macromolecular assemblies from which models have been manually constructed. In this work, we describe a new interactive modeling toolkit called Gorgon targeted at intermediate to near-atomic resolution density maps (10-3.5 Å), particularly from cryo-EM. Gorgon's de novo modeling procedure couples sequence-based secondary structure prediction with feature detection and geometric modeling techniques to generate initial protein backbone models. Beyond model building, Gorgon is an extensible interactive visualization platform with a variety of computational tools for annotating a wide variety of 3D volumes. Examples from cryo-EM maps of Rotavirus and Rice Dwarf Virus are used to demonstrate its applicability to modeling protein structure.

Integrating diverse data for structure determination of macromolecular assemblies

To understand the cell, we need to determine the macromolecular assembly structures, which may consist of tens to hundreds of components. First, we review the varied experimental data that characterize the assemblies at several levels of resolution. We then describe computational methods for generating the structures using these data. To maximize completeness, resolution, accuracy, precision, and efficiency of the structure determination, a computational approach is required that uses spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. This approach is illustrated by determining the configuration of the 456 proteins in the nuclear pore complex (NPC) from baker's yeast. With these tools, we are poised to integrate structural information gathered at multiple levels of the biological hierarchy--from atoms to cells--into a common framework.

Identification of atherosclerosis-associated conformational heat shock protein 60 epitopes by phage display and structural alignment

Autoimmune reactions to HSP60 are believed to play a key role during development of early atherosclerosis. Due to the high degree of phylogenetic conservation between microbial and human HSP60, bacterial infections might be responsible for inducing cross-reactivity to self HSP60, which is expressed on the surface of arterial endothelial cells stressed by classical atherosclerosis risk factors. Conformational epitopes recognized by polyclonal anti-mycobacterial HSP60 antibodies from subjects with atherosclerosis were identified using a phage displayed random library of cyclic constrained 7mer peptides. After five rounds of selection, DNA sequencing of strongly binding clones revealed that one peptide motif (CIGSPSTNC) was present in 64% of all clones, and a second motif (CSFHYQNRC) in 14%. Using a newly developed method for structural alignment of small constrained peptides onto a protein surface, we located the motif present in 14% of all clones on the surface of mycobacterial HSP60. The motif present in 64% of all clones was found on the surface of mycobacterial HSP60 as well as in the homologous region of human HSP60, which makes this epitope a promising candidate for further investigations on cross-reactive epitopes involved in early atherogenesis.

NdPASA: a novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities

Sequence alignment has become one of the essential bioinformatics tools in biomedical research. Existing sequence alignment methods can produce reliable alignments for homologous proteins sharing a high percentage of sequence identity. The performance of these methods deteriorates sharply for the sequence pairs sharing less than 25% sequence identity. We report here a new method, NdPASA, for pairwise sequence alignment. This method employs neighbor-dependent propensities of amino acids as a unique parameter for alignment. The values of neighbor-dependent propensity measure the preference of an amino acid pair adopting a particular secondary structure conformation. NdPASA optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. Using superpositions of homologous proteins derived from the PSI-BLAST analysis and the Structural Classification of Proteins (SCOP) classification of a nonredundant Protein Data Bank (PDB) database as a gold standard, we show that NdPASA has improved pairwise alignment. Statistical analyses of the performance of NdPASA indicate that the introduction of sequence patterns of secondary structure derived from neighbor-dependent sequence analysis clearly improves alignment performance for sequence pairs sharing less than 20% sequence identity. For sequence pairs sharing 13-21% sequence identity, NdPASA improves the accuracy of alignment over the conventional global alignment (GA) algorithm using the BLOSUM62 by an average of 8.6%. NdPASA is most effective for aligning query sequences with template sequences whose structure is known. NdPASA can be accessed online at http://astro.temple.edu/feng/Servers/BioinformaticServers.htm.

Refinement of Protein Structures by Iterative Comparative Modeling and CryoEM Density Fitting

We developed a method for structure characterization of assembly components by iterative comparative protein structure modeling and fitting into cryo-electron microscopy (cryoEM) density maps. Specifically, we calculate a comparative model of a given component by considering many alternative alignments between the target sequence and a related template structure while optimizing the fit of a model into the corresponding density map. The method relies on the previously developed Moulder protocol that iterates over alignment, model building, and model assessment. The protocol was benchmarked using 20 varied target-template pairs of known structures with less than 30% sequence identity and corresponding simulated density maps at resolutions from 5A to 25A. Relative to the models based on the best existing sequence profile alignment methods, the percentage of C(alpha) atoms that are within 5A of the corresponding C(alpha) atoms in the superposed native structure increases on average from 52% to 66%, which is half-way between the starting models and the models from the best possible alignments (82%). The test also reveals that despite the improvements in the accuracy of the fitness function, this function is still the bottleneck in reducing the remaining errors. To demonstrate the usefulness of the protocol, we applied it to the upper domain of the P8 capsid protein of rice dwarf virus that has been studied by cryoEM at 6.8A. The C(alpha) root-mean-square deviation of the model based on the remotely related template, bluetongue virus VP7, improved from 8.7A to 6.0A, while the best possible model has a C(alpha) RMSD value of 5.3A. Moreover, the resulting model fits better into the cryoEM density map than the initial template structure. The method is being implemented in our program MODELLER for protein structure modeling by satisfaction of spatial restraints and will be applicable to the rapidly increasing number of cryoEM density maps of macromolecular assemblies.

Correlating sequential homology of Mce1A, Mce2A, Mce3A and Mce4A with their possible functions in mammalian cell entry of Mycobacterium tuberculosis performing homology modeling

OBJECTIVE

The striking homology of the Mycobacterium tuberculosis mammalian cell entry operons (mce1, mce2, mce3 and mce4) with other mycobacterial species and the proposed role of the mammalian cell entry protein 1A (Mce1A) of M. tuberculosis to facilitate invasion of host cells have led us to look into the finer details of these proteins in order to better understand their structure-function relationship.

DESIGN

We performed sequential alignments and secondary structure predictions of Mce1A, Mce2A, Mce3A and Mce4A, and compared these results with results from homology modeling by fold prediction and threading.

RESULTS

Sequential alignments showed that Mce1A and Mce2A are highly homologous, close to 70%, while the other combinations gave only about 30% similarities. The major parts of the proteins aligned without gaps and there were striking similarities by secondary structure predictions indicating that the proteins would have similar folds and to be alpha/beta proteins like the previously reported Mce1A model based on Colicin N. Fold prediction showed that the best templates for Mce2A were substrate-binding domain of DnaK and slow processing precursor penicillin acylase from Escherichia coli while the alpha-domains of Mce3A and Mce4A could both be modeled using the cytoplasmic domain of serine chemotaxis receptor as template.

CONCLUSION

Although different templates had to be used to model the MceA proteins, functional information may be derived that is relevant for their overall function in M. tuberculosis. The beta-domain is probably involved in binding with the receptors on target cells while the alpha-domain is more likely to be involved in pore formation. As predicted from the folds, Mce3A and Mce4A model structures indicate a lipid bound conformation and therefore may be required in signaling events of the mammalian cell entry process.

Combining electron microscopy and comparative protein structure modeling

Recently, advances have been made in methods and applications that integrate electron microscopy density maps and comparative modeling to produce atomic structures of macromolecular assemblies. Electron microscopy can benefit from comparative modeling through the fitting of comparative models into electron microscopy density maps. Also, comparative modeling can benefit from electron microscopy through the use of intermediate-resolution density maps in fold recognition, template selection and sequence-structure alignment.

Prediction of Multimolecular Assemblies by Multiple Docking

The majority of proteins function when associated in multimolecular assemblies. Yet, prediction of the structures of multimolecular complexes has largely not been addressed, probably due to the magnitude of the combinatorial complexity of the problem. Docking applications have traditionally been used to predict pairwise interactions between molecules. We have developed an algorithm that extends the application of docking to multimolecular assemblies. We apply it to predict quaternary structures of both oligomers and multi-protein complexes. The algorithm predicted well a near-native arrangement of the input subunits for all cases in our data set, where the number of the subunits of the different target complexes varied from three to ten. In order to simulate a more realistic scenario, unbound cases were tested. In these cases the input conformations of the subunits are either unbound conformations of the subunits or a model obtained by a homology modeling technique. The successful predictions of the unbound cases, where the input conformations of the subunits are different from their conformations within the target complex, suggest that the algorithm is robust. We expect that this type of algorithm should be particularly useful to predict the structures of large macromolecular assemblies, which are difficult to solve by experimental structure determination.

Structural characterization of components of protein assemblies by comparative modeling and electron cryo-microscopy

We explore structural characterization of protein assemblies by a combination of electron cryo-microscopy (cryoEM) and comparative protein structure modeling. Specifically, our method finds an optimal atomic model of a given assembly subunit and its position within an assembly by fitting alternative comparative models into a cryoEM map. The alternative models are calculated by MODELLER [J. Mol. Biol. 234 (1993) 313] from different sequence alignments between the modeled protein and its template structures. The fitting of these models into a cryoEM density map is performed either by FOLDHUNTER [J. Mol. Biol. 308 (2001) 1033] or by a new density fitting module of MODELLER (Mod-EM). Identification of the most accurate model is based on the correlation between the model accuracy and the quality of fit into the cryoEM density map. To quantify this correlation, we created a benchmark consisting of eight proteins of different structural folds with corresponding density maps simulated at five resolutions from 5 to 15 angstroms, with three noise levels each. Each of the proteins in the set was modeled based on 300 different alignments to their remotely related templates (12-32% sequence identity), spanning the range from entirely inaccurate to essentially accurate alignments. The benchmark revealed that one of the most accurate models can usually be identified by the quality of its fit into the cryoEM density map, even for noisy maps at 15 angstroms resolution. Therefore, a cryoEM density map can be helpful in improving the accuracy of a comparative model. Moreover, a pseudo-atomic model of a component in an assembly may be built better with comparative models of the native subunit sequences than with experimentally determined structures of their homologs.

A structural perspective on protein-protein interactions

Structures of macromolecular complexes are necessary for a mechanistic description of biochemical and cellular processes. They can be solved by experimental methods, such as X-ray crystallography, NMR spectroscopy and electron microscopy, as well as by computational protein structure prediction, docking and bioinformatics. Recent advances and applications of these methods emphasize the need for hybrid approaches that combine a variety of data to achieve better efficiency, accuracy, resolution and completeness.

Predicted molecular structure of the mammalian cell entry protein Mce1A of Mycobacterium tuberculosis

The proposed role of the mammalian cell entry protein 1A (Mce1A) of Mycobacterium tuberculosis is to facilitate invasion of host cells. The structure of Mce1A was modelled on the basis of the crystal structure of Colicin N of Escherichia coli by fold prediction and threading. Mce1A, as the model predicts, is an alpha/beta protein consisting of two major (alpha and beta) domains, connected by a long alpha helix. The model further revealed that the protein contains 12 helices, 9 strands, and 1 turn. The final model of Mce1A was verified through the program VERIFY 3D and more than 90% of the residues were in the favourable region. A mouse monoclonal antibody, TB1-5 76C, is directed to an epitope within a 60-mer peptide that has been shown to promote uptake of bacteria in mammalian cells. We show here that the epitope could be narrowed down to a core of 4 amino acids, TPKD. Upstream flanking residues, KRR also contributed to binding. Mce2A does not promote uptake in mammalian cells and sequence comparison of Mce1A and Mce2A indicates that the epitope mediates uptake. The epitope was located at the surface of the Mce1A model at the distal beta strand-loop region in the beta domain. The localization of this epitope in the model confirms its potential role in promoting uptake of M. tuberculosis in host cells.

Modularity and homology: modelling of the titin type I modules and their interfaces

Titin is a giant muscle protein with a highly modular architecture consisting of multiple repeats of two sequence motifs, named type I and type II. Type I motifs are homologous to members of the fibronectin type 3 (Fn3) superfamily, one of the motifs most widespread in modular proteins. Fn3 domains are thought to mediate protein-protein interactions and to act as spacers. In titin, Fn3 modules are present in two different super-repeated patterns, likely to be involved in sarcomere assembly through interactions with A-band proteins. Here, we discuss results from homology modelling the whole family of Fn3 domains in titin. Homology modelling is a powerful tool that will play an increasingly important role in the post-genomic era. It is particularly useful for extending experimental structure determinations of parts of multidomain proteins that contain multiple copies of the same motif. The 3D structures of a representative titin type I domain and of other extracellular Fn3 modules were used as a template to model the structures of the 132 copies in titin. The resulting models suggest residues that contribute to the fold stability and allow us to distinguish these from residues likely to have functional importance. In particular, analysis of the models and mapping of the consensus sequence onto the 3D structure suggest putative surfaces of interaction with other proteins. From the structures of isolated modules and the pattern of conservation in the multiple alignment of the whole titin Ig and Fn3 families, it is possible to address the question of how tandem modules are assembled. Our predictions can be validated experimentally.