Simulation and Neutron Diffraction Studies of Small Biomolecules in Water

Modern biophysics has benefited greatly from the use of X-ray and neutron diffraction from ordered single crystals of proteins and other macromolecules to give highly detailed pictures of these molecules in the solid state. However, the most biologically relevant environments for these molecules are liquid solutions, and their liquid state properties are sensitive to details of the liquid structuring. The best experimental method for studying such structuring is also neutron diffraction, but of course, the inherent disorder of the liquid state means that these experiments cannot hope to achieve the level of informational detail available from single crystal diffraction. Nonetheless, recent advances in neutron beam intensity, beam stability, and detector sensitivity mean that it should be possible, at least in principle, to use such measurements to extract information about structuring in much more complex systems than have previously been studied. We describe a series of neutron diffraction studies of isotopically labeled molecules in aqueous solution which, when combined with results from computer simulations, can be used to extract conformational information of the hydration of the molecules themselves, essentially opening up new avenues of investigation in structural biology.     

Molecular modelling of MHC class I carbohydrates

In this article we present the results of molecular modelling of four complex carbohydrates which have been found in the MHC class I proteins. Though these proteins show diversity in their sequences, the glycosylation sites are highly conserved indicating a possible structural/functional role of the glycan chain. Similar glycan chains have been found linked with other proteins of completely different function, such as IgG, and erythropoeitin. Thus, the molecular modelling of these carbohydrates will not only provide structural/dynamic information of these complex molecules but will also provide conformational information which can be utilised to build the glycoprotein models. The results presented here indicate that although several linkages show less conformational flexibility, terminal linkages can be quite flexible.     

Molecular dynamics simulations of glycoclusters and glycodendrimers

Protein-carbohydrate recognition plays a crucial role in a wide range of biological processes, required both for normal physiological functions and the onset of disease. Nature uses multivalency in carbohydrate-protein interactions as a strategy to overcome the low affinity found for singular binding of an individual saccharide epitope to a single carbohydrate recognition domain of a lectin. To mimic the complex multi-branched oligosaccharides found in glycoconjugates, which form the structural basis of multivalent carbohydrate-protein interactions, so-called glycoclusters and glycodendrimers have been designed to serve as high-affinity ligands of the respective receptor proteins. To allow a rational design of glycodendrimer-type molecules with regard to the receptor structures involved in carbohydrate recognition, a deeper knowledge of the dynamics of such molecules is desirable. Most glycodendrimers have to be considered highly flexible molecules with their conformational preferences most difficult to elucidate by experimental methods. Longtime molecular dynamics (MD) simulations with inclusion of explicit solvent molecules are suited to explore the conformational space accessible to glycodendrimers. Here, a detailed geometric and conformational analysis of 15 glycodendrimers and glycoclusters has been accomplished, which differ with regard to their core moieties, spacer characteristics and the type of terminal carbohydrate units. It is shown that the accessible conformational space depends strongly on the structural features of the core and spacer moieties and even on the type of terminating sugars. The obtained knowledge about possible spatial distributions of the sugar epitopes exposed on the investigated hyperbranched neoglycoconjugates is detailed for all examples and forms important information for the interpretation and prediction of affinity data, which can be deduced from biological testing of these multivalent neoglycoconjugates.     

Low-resolution docking: Prediction of complexes for underdetermined structures

One of the most fundamental questions concerning ligand-receptor interaction is whether such a process of intermolecular association is generally determined by local structural elements of the participating molecules, or whether there are also large-scale motifs in molecule structures that facilitate complex formation. From the point of view of practical docking computations, the elaborate character of local structural details in ligand-receptor interaction creates a large number of false-positive matches, which interfere with determination of the best fit. Another significant obstacle in protein docking is the problem of structural data inaccuracy (poor structure resolution, conformational changes upon complex formation, etc.). Our study [Vakser (1995) Protein Eng., 8, 371–377], based on ultralow (∼7 Å resolution) representation of molecular structures, allowes to average all high-resolution structural details, and still predict most of the structural features of the ligand-receptor complex. The approach dramatically improves the signal-to-noise ratio in determination of the best fit, and moves the structure inaccuracy tolerance to the range of the macrostructure. In the present paper, we describe a further validation of the main principles of this approach and a detailed analysis of the low-resolution docking results. This includes clustering of ligand positions around the receptor molecule and cross-validation of ligands and receptors from different complexes. We also discuss the important implications of the approach to the multiple-minima problem and a possible role of different structural elements in the recognition mechanism. © 1996 John Wiley & Sons, Inc.     

Structural characterization of the ceruloplasmin: lactoferrin complex in solution

Ceruloplasmin is a copper protein found in vertebrate plasma, which belongs to the family of multicopper oxidases. Like transferrin of the blood plasma, lactoferrin, the iron-containing protein of human milk, saliva, tears, seminal plasma and of neutrophilic leukocytes tightly binds two ferric ions. Human lactoferrin and ceruloplasmin have been previously shown to interact both in vivo and in vitro forming a complex. Here we describe a study of the conformation of the human lactoferrin/ceruloplasmin complex in solution using small angle X-ray scattering. Our ab initio structural analysis shows that the complex has a 1:1 stoichiometry and suggests that complex formation occurs without major conformational rearrangements of either protein. Rigid-body modeling of the mutual arrangement of proteins in the complex essentially yields two families of solutions. Final discrimination is possible when integrating in the modeling process extra information translating into structural constraints on the interaction between the two partners.     

Determination of structural fluctuations of proteins from structure-based calculations of residual dipolar couplings

Residual dipolar couplings (RDCs) have the potential of providing detailed information about the conformational fluctuations of proteins. It is very challenging, however, to extract such information because of the complex relationship between RDCs and protein structures. A promising approach to decode this relationship involves structure-based calculations of the alignment tensors of protein conformations. By implementing this strategy to generate structural restraints in molecular dynamics simulations we show that it is possible to extract effectively the information provided by RDCs about the conformational fluctuations in the native states of proteins. The approach that we present can be used in a wide range of alignment media, including Pf1, charged bicelles and gels. The accuracy of the method is demonstrated by the analysis of the Q factors for RDCs not used as restraints in the calculations, which are significantly lower than those corresponding to existing high-resolution structures and structural ensembles, hence showing that we capture effectively the contributions to RDCs from conformational fluctuations.     

Understanding protein flexibility through dimensionality reduction.

This work shows how to decrease the complexity of modeling flexibility in proteins by reducing the number of dimensions necessary to model important macromolecular motions such as the induced-fit process. Induced fit occurs during the binding of a protein to other proteins, nucleic acids, or small molecules (ligands) and is a critical part of protein function. It is now widely accepted that conformational changes of proteins can affect their ability to bind other molecules and that any progress in modeling protein motion and flexibility will contribute to the understanding of key biological functions. However, modeling protein flexibility has proven a very difficult task. Experimental laboratory methods, such as x-ray crystallography, produce rather limited information, while computational methods such as molecular dynamics are too slow for routine use with large systems. In this work, we show how to use the principal component analysis method, a dimensionality reduction technique, to transform the original high-dimensional representation of protein motion into a lower dimensional representation that captures the dominant modes of motions of proteins. For a medium-sized protein, this corresponds to reducing a problem with a few thousand degrees of freedom to one with less than fifty. Although there is inevitably some loss in accuracy, we show that we can obtain conformations that have been observed in laboratory experiments, starting from different initial conformations and working in a drastically reduced search space.     

Effect of self-association on the structural organization of partially folded proteins: inactivated actin

The propensity to associate or aggregate is one of the characteristic properties of many nonnative proteins. The aggregation of proteins is responsible for a number of human diseases and is a significant problem in biotechnology. Despite this, little is currently known about the effect of self-association on the structural properties and conformational stability of partially folded protein molecules. G-actin is shown to form equilibrium unfolding intermediate in the vicinity of 1.5 M guanidinium chloride (GdmCl). Refolding from the GdmCl unfolded state is terminated at the stage of formation of the same intermediate state. An analogous form, known as inactivated actin, can be obtained by heat treatment, or at moderate urea concentration, or by the release of Ca(2+). In all cases actin forms specific associates comprising partially folded protein molecules. The structural properties and conformational stability of inactivated actin were studied over a wide range of protein concentrations, and it was established that the process of self-association is rather specific. We have also shown that inactivated actin, being denatured, is characterized by a relatively rigid microenvironment of aromatic residues and exhibits a considerable limitation in the internal mobility of tryptophans. This means that specific self-association can play an important structure-forming role for the partially folded protein molecules.     

Structural heterogeneity in protein crystals

Extensive conformational heterogeneity is reported in highly refined crystallographic models for the proteins crambin, erabutoxin, myohemerythrin, and lamprey hemoglobin. From 6% to 13% of the amino acid side chains of these four proteins are seen in multiple, discrete conformations. Most common are flexible side chains on the molecular surface, but structural heterogeneity occasionally extends to buried side chains or to the polypeptide backbone. A few instances of sequence heterogeneity are also very clear. Numerous solvent sites are multiplets, and at high resolution, multiple, mutually exclusive solvent networks are observed. The proteins have been studied with X-ray diffraction data extending to spacings of from 0.945 to 2.0 A. The extensive heterogeneity observed here provides detailed, accurate structures for conformational substates of these molecules and sets a lower bound on the number of substates accessible to each protein molecule in solution. Electron density is missing or very weak for only a few side chains in these protein crystals, revealing a strong preference for discrete over continuous conformational perturbations. The results at very high resolution further suggest that even rather small conformational fluctuations produce discrete substates and that unresolved conformers are accommodated in increased atomic thermal parameters.     

Conformational dynamics of the molecular chaperone Hsp90

The ubiquitous molecular chaperone Hsp90 makes up 1-2% of cytosolic proteins and is required for viability in eukaryotes. Hsp90 affects the folding and activation of a wide variety of substrate proteins including many involved in signaling and regulatory processes. Some of these substrates are implicated in cancer and other diseases, making Hsp90 an attractive drug target. Structural analyses have shown that Hsp90 is a highly dynamic and flexible molecule that can adopt a wide variety of structurally distinct states. One driving force for these rearrangements is the intrinsic ATPase activity of Hsp90, as seen with other chaperones. However, unlike other chaperones, studies have shown that the ATPase cycle of Hsp90 is not conformationally deterministic. That is, rather than dictating the conformational state, ATP binding and hydrolysis only shift the equilibria between a pre-existing set of conformational states. For bacterial, yeast and human Hsp90, there is a conserved three-state (apo-ATP-ADP) conformational cycle; however; the equilibria between states are species specific. In eukaryotes, cytosolic co-chaperones regulate the in vivo dynamic behavior of Hsp90 by shifting conformational equilibria and affecting the kinetics of structural changes and ATP hydrolysis. In this review, we discuss the structural and biochemical studies leading to our current understanding of the conformational dynamics of Hsp90, as well as the roles that nucleotide, co-chaperones, post-translational modification and substrates play. This view of Hsp90's conformational dynamics was enabled by the use of multiple complementary structural methods including, crystallography, small-angle X-ray scattering (SAXS), electron microscopy, F?rster resonance energy transfer (FRET) and NMR. Finally, we discuss the effects of Hsp90 inhibitors on conformation and the potential for developing small molecules that inhibit Hsp90 by disrupting the conformational dynamics.     

The Bacillus subtilis spore coat protein interaction network

Bacterial spores are surrounded by a morphologically complex, mechanically flexible protein coat, which protects the spore from toxic molecules. The interactions among the over 50 proteins that make up the coat remain poorly understood. We have used cell biological and protein biochemical approaches to identify novel coat proteins in Bacillus subtilis and describe the network of their interactions, in order to understand coat assembly and the molecular basis of its protective functions and mechanical properties. Our analysis characterizes the interactions between 32 coat proteins. This detailed view reveals a complex interaction network. A key feature of the network is the importance of a small subset of proteins that direct the assembly of most of the coat. From an analysis of the network topology, we propose a model in which low-affinity interactions are abundant in the coat and account, to a significant degree, for the coat's mechanical properties as well as structural variation between spores.     

The minimum number of mutations in an evolutionary network

The problem when given an evolutionary network representing the ancestral relationships between either a set of proteins, or a set of RNA molecules, is to determine the numbers of mutations along the single branches of the network in such a way that their sum, i.e. the number of mutations in the complete network, is as small as possible. In case of proteins either amino acid substitutions, or nucleotide substitutions may be considered. It is shown that such problems are equivalent to an integer linear programming problem which generally has multiple solutions. In fact, the numbers of mutations along the single branches of the network may not uniquely be determined by sequence data and network topology. However, their sum is unique and is a measure for the probability to describe evolution properly, assigned to this network by the maximum parsimony hypothesis.