The number of solved structures of macromolecules that have the same fold and thus exhibit some degree of conformational variability is rapidly increasing. It is consequently advantageous to develop a standardized terminology for describing this variability and automated systems for processing protein structures in different conformations. We have developed such a system as a `front-end' server to our database of macromolecular motions. Our system attempts to describe a protein motion as a rigid-body rotation of a small `core' relative to a larger one, using a set of hinges. The motion is placed in a standardized coordinate system so that all statistics between any two motions are directly comparable. We find that while this model can accommodate most protein motions, it cannot accommodate all; the degree to which a motion can be accommodated provides an aid in classifying it. Furthermore, we perform an adiabatic mapping (a restrained interpolation) between every two conformations. This gives some indication of the extent of the energetic barriers that need to be surmounted in the motion, and as a by-product results in a `morph movie'. We make these movies available over the Web to aid in visualization. Many instances of conformational variability occur between proteins with somewhat different sequences. We can accommodate these differences in a rough fashion, generating an `evolutionary morph'. Users have already submitted hundreds of examples of protein motions to our server, producing a comprehensive set of statistics. So far the statistics show that the median submitted motion has a rotation of ~10 and a maximum C# displacement of 17 . Almost all involve at least one large torsion angle change of >140. The server is accessible at http://bioinfo.mbb.yale.edu/MolMovDB...

ABSTRACT We develop a computationally efficient method to simulate the transition of a protein between two conformations. Our method is based on a coarse-grained elastic network model in which distances between spatially proximal amino acids are interpolated between the values specified by the two end conformations. The computational speed of this method depends strongly on the choice of cutoff distance used to define interactions as measured by the density of entries of the constant linking/contact matrix. To circumvent this problem we introduce the concept of using a cutoff based on a maximum number of nearest neighbors. This generates linking matrices that are both sparse and uniform, hence allowing for efficient computations that are independent of the arbitrariness of cutoff distance choices. Simulation results demonstrate that the method developed here reliably generates feasible intermediate conformations, because our method observes steric constraints and produces monotonic changes in virtual bond and torsion angles. Applications are readily made to large proteins, and we demonstrate our method on lactate dehydrogenase, citrate synthase, and lactoferrin. We also illustrate how this framework can be used to complement experimental techniques that partially observe protein motions.

ABSTRACT We present a rigid-body-based technique (called rigid-cluster elastic network interpolation) to generate feasible transition pathways between two distinct conformations of a macromolecular assembly. Many biological molecules and assemblies consist of domains which act more or less as rigid bodies during large conformational changes. These collective motions are thought to be strongly related with the functions of a system. This fact encourages us to simply model a macromolecule or assembly as a set of rigid bodies which are interconnected with distance constraints. In previous articles, we developed coarsegrained elastic network interpolation (ENI) in which, for example, only C a atoms are selected as representatives in each residue of a protein. We interpolate distance differences of two conformations in ENI by using a simple quadratic cost function, and the feasible conformations are generated without steric conflicts. Rigid-cluster interpolation is an extension of the ENI method with rigid-clusters replacing point masses. Now the intermediate conformations in an anharmonic pathway can be determined by the translational and rotational displacements of large clusters in such a way that distance constraints are observed. We present the derivation of the rigid-cluster model and apply it to a variety of macromolecular assemblies. Rigid-cluster ENI is then modified for a hybrid model represented by a mixture of rigid clusters and point masses. Simulation results show that both rigid-cluster and hybrid ENI methods generate sterically feasible pathways of large systems in a very short time. For example, the HK97 virus capsid is an icosahedral symmetric assembly composed of 60 identical asymmetric units. Its original Hessian matrix size for a C a coarsegrained model is.(300,000) 2. However, it reduces to (84) 2 when we apply the rigid-cluster model with icosahedral symmetry

The Escherichia coli chaperonin system, GroEL–GroES, facilitates folding of substrate proteins (SPs) that are otherwise destined to aggregate. The iterative annealing mechanism suggests that the allostery-driven GroEL transitions leading to changes in the microenvironment of the SP constitutes the annealing action of chaperonins. To describe the molecular basis for the changes in the nature of SP–GroEL interactions we use the crystal structures of GroEL (T state), GroEL–ATP (R state) and the GroEL–GroES–(ADP) 7 (R0state) complex to determine the residue-specific changes in the accessible surface area and the number of tertiary contacts as a result of the T™R™R0 transitions. We find large changes in the accessible area in many residues in the apical domain, but relatively smaller changes are associated with residues in the equatorial domain. In the course of the T™R transition the microenvironment of the SP changes which suggests that GroEL is an annealing machine even without GroES. This is reflected in the exposure of Glu386 which loses six contacts in the T™R transition. We also evaluate the conservation of residues that participate in the various chaperonin functions. Multiple sequence alignments and chemical sequence entropy calculations reveal that, to a large extent, only the chemical identities and not the residues themselves important for the nominal functions (peptide binding, nucleotide binding, GroESand substrate protein release) are strongly conserved. Using chemical sequence entropy, which is computed by classifying aminoacids into four types

This un-edited manuscript has been accepted for publication in Biophysical Journal and is freely available on BioFAST at www.biophysj.org. The final copyedited version of the paper may be found at www.biophysj.org.

Co-chaperonins from diverse organisms exhibit mobile loops which fold into a β hairpin conformation upon binding to the chaperonin. GroES, Gp31, and human Hsp10 mobile loops exhibit a preference for the β hairpin conformation in the free co-chaperonins, and the conformational dynamics of the human Hsp10 mobile loop appear to be restricted by nascent hairpin formation. Backbone conformational entropy must weigh against binding of cochaperonins to chaperonins, and thus the conformational preferences of the loops may strongly influence chaperonin-binding affinity. Indeed, subtle mutations in the loops change GroEL-binding affinity and cause defects in chaperonin function, and these defects can be suppressed by mutations in GroEL which compensate for the changes in affinity. The fact that high-affinity co-chaperonin binding impairs chaperonin function has implications for the mechanism of chaperonin-assisted protein folding.

Elastic network models (ENMs) and, in particular, the Gaussian Network Model (GNM) have been widely used in recent years to gain insights into the machinery of proteins. The extension of ENMs to supramolecular assemblies presents computational challenges, because of the difficulty in retaining atomic details in mode decomposition of large protein dynamics. Here, we present a novel approach to address this problem. We rely on the premise that, all the residues of the protein machinery (network) must communicate with each other and operate in a coordinated manner to perform their function successfully. To gain insight into the mechanism of information transfer between residues, we study a Markov model of network communication. Using the Markov chain perspective, we map the full-atom network representation into a hierarchy of ENMs of decreasing resolution, perform analysis of dominant communication (or dynamic) patterns in reduced space(s) and reconstruct the detailed models with minimal loss of information. The communication properties at different levels of the hierarchy are intrinsically defined by the network topology. This new representation has several features, including: soft clustering of the protein structure into stochastically coherent regions thus providing a useful assessment of elements serving as hubs and/or transmitters in propagating information/interaction; automatic computation of the contact matrices for ENMs at each level of the hierarchy to facilitate computation of both Gaussian and anisotropic fluctuation dynamics. We illustrate the utility of the hierarchical decomposition in providing an insightful description of the supramolecular machinery by applying the methodology to the chaperonin GroEL–GroES. Key words: information propagation, Markov process, network model. 1.

Abstract. Previously the hexapeptide motif FXNPXY 807 in the cytoplasmic tail of the LDL receptor was shown to be essential for clustering in clathrincoated pits. We used nuclear magnetic resonance linebroadening and transferred nuclear Overhauser effect measurements to identify the molecule in the clathrin lattice that interacts with this hexapeptide, and determined the structure of the bound motif. The wild-type peptide bound in a single conformation with a reverse turn at residues NPVY. Tyr 807Ser, a peptide that harbors a mutation that disrupts receptor clustering, displayed markedly reduced interactions. Clustering motif peptides interacted with clathrin cages assembled in the presence or absence of AP2, with recombinant clathrin terminal domains, but not with clathrin hubs. The identification

Global viewing of protein–protein interactions (PPIs) is a useful way to assign biological roles to large numbers of proteins predicted by complete genome sequence. Here, we systematically analyzed PPIs in the nitrogen-fixing soil bacterium Mesorhizobium loti using a modified high-throughput yeast two-hybrid system. The aims of this study are primarily on the providing functional clues to M. loti proteins that are relevant to symbiotic nitrogen fixation and conserved in other rhizobium species, especially proteins with regulatory functions and unannotated proteins. By the screening of 1542 genes as bait, 3121 independent interactions involving 1804 proteins (24 % of the total protein coding genes) were identified and each interaction was evaluated using an interaction generality (IG) measure and the general features of the interacting partners. Most PPIs detected in this study are novel interactions revealing potential functional relationships between genes for symbiotic nitrogen fixation and signal transduction. Furthermore, we have predicted the putative functions of unannotated proteins through their interactions with known proteins. The results described here represent new insight into protein network of M. loti and provide useful experimental clues to elucidate the biological function of rhizobial genes that can not be assigned directly from their genomic sequence. Key words: Mesorhizobium loti; Protein–protein interaction; Yeast two-hybrid system 1.

Abstract not found