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Abstract Background Knowledge of the structure of proteins bound to known or potential ligands is crucial for biological understanding and drug design. Often the 3D structure of the protein is available in some conformation, but binding the ligand of interest may involve a large scale conformational change which is difficult to predict with existing methods. Results We describe how to generate ligand binding conformations of proteins that move by hinge bending, the largest class of motions. First, we predict the location of the hinge between domains. Second, we apply an Euler rotation to one of the domains about the hinge point. Third, we compute a short-time dynamical trajectory using Molecular Dynamics to equilibrate the protein and ligand and correct unnatural atomic positions. Fourth, we score the generated structures using a novel fitness function which favors closed or holo structures. By iterating the second through fourth steps we systematically minimize the fitness function, thus predicting the conformational change required for small ligand binding for five well studied proteins. Conclusions We demonstrate that the method in most cases successfully predicts the holo conformation given only an apo structure.

Abstract Background Protein motions play an essential role in catalysis and protein-ligand interactions, but are difficult to observe directly. A substantial fraction of protein motions involve hinge bending. For these proteins, the accurate identification of flexible hinges connecting rigid domains would provide significant insight into motion. Programs such as GNM and FIRST have made global flexibility predictions available at low computational cost, but are not designed specifically for finding hinge points. Results Here we present the novel FlexOracle hinge prediction approach based on the ideas that energetic interactions are stronger within structural domains than between them, and that fragments generated by cleaving the protein at the hinge site are independently stable. We implement this as a tool within the Database of Macromolecular Motions, MolMovDB.org. For a given structure, we generate pairs of fragments based on scanning all possible cleavage points on the protein chain, compute the energy of the fragments compared with the undivided protein, and predict hinges where this quantity is minimal. We present three specific implementations of this approach. In the first, we consider only pairs of fragments generated by cutting at a single location on the protein chain and then use a standard molecular mechanics force field to calculate the enthalpies of the two fragments. In the second, we generate fragments in the same way but instead compute their free energies using a knowledge based force field. In the third, we generate fragment pairs by cutting at two points on the protein chain and then calculate their free energies. Conclusion Quantitative results demonstrate our method's ability to predict known hinges from the Database of Macromolecular Motions.

Abstract Background Relating features of protein sequences to structural hinges is important for identifying domain boundaries, understanding structure-function relationships, and designing flexibility into proteins. Efforts in this field have been hampered by the lack of a proper dataset for studying characteristics of hinges. Results Using the Molecular Motions Database we have created a Hinge Atlas of manually annotated hinges and a statistical formalism for calculating the enrichment of various types of residues in these hinges. Conclusion We found various correlations between hinges and sequence features. Some of these are expected; for instance, we found that hinges tend to occur on the surface and in coils and turns and to be enriched with small and hydrophilic residues. Others are less obvious and intuitive. In particular, we found that hinges tend to coincide with active sites, but unlike the latter they are not at all conserved in evolution. We evaluate the potential for hinge prediction based on sequence. Motions play an important role in catalysis and protein-ligand interactions. Hinge bending motions comprise the largest class of known motions. Therefore it is important to relate the hinge location to sequence features such as residue type, physicochemical class, secondary structure, solvent exposure, evolutionary conservation, and proximity to active sites. To do this, we first generated the Hinge Atlas, a set of protein motions with the hinge locations manually annotated, and then studied the coincidence of these features with the hinge location. We found that all of the features have bearing on the hinge location. Most interestingly, we found that hinges tend to occur at or near active sites and yet unlike the latter are not conserved. Less surprisingly, we found that hinge residues tend to be small, not hydrophobic or aliphatic, and occur in turns and random coils on the surface. A functional sequence based hinge predictor was made which uses some of the data generated in this study. The Hinge Atlas is made available to the community for further flexibility studies.

The mechanism of exchange proteins directly activated by cAMP (Epac) activation is delineated by examining the conformational and structural dynamic states of Epac by using amide hydrogen--deuterium (H--D) exchange coupled with Fourier transform infrared spectroscopy (FT-IR). The results have predicted that during Epac activation the first [beta]-strand of the switchboard switches its conformation to a [alpha]-helix, which folds back to the [beta]-barrel core of the cAMP binding domain and interacts directly with cAMP to form the base of the cAMP-binding pocket.

A birchirped coherent-control scenario is introduced and the feasibility of coherently controlling the femtosecond primary event of vision as modeled by an empirical Hamiltonian that properly describes the underlying reaction speed and efficiency is investigated. The result shows that the coupling between the reaction coordinate and the stretching mode of the polyene chain in the retinal chromophore induces decoherence within a time scale comparable to the reaction time.

We show that a small biotin-binding RNA aptamer that folds into a pseudoknot structure acts as a substrate for bacterial RNase P RNA (RPR) with and without the RNase P C5 protein. Cleavage in the single-stranded region in loop 1 was shown to depend on the presence of a RCCA-motif at the 3' end of the substrate. The nucleobase and the 2'hydroxyl at the position immediately 5' of the cleavage site contribute to both cleavage efficiency and site selection, where C at this position induces significant cleavage at an alternative site, one base upstream of the main cleavage site. The frequencies of cleavage at these two sites and Mg 2+ binding change upon altering the structural topology in the vicinity of the cleavage site as well as by replacing Mg 2+ with other divalent metal ions. Modelling studies of RPR in complex with the pseudoknot substrates suggest alternative structural topologies for cleavage at the main and the alternative site and a shift in positioning of Mg 2+ that activates the H 2 O nucleophile. Together, our data are consistent with a model where the organization of the active site structure and positioning of Mg 2+ is influenced by the identities of residues at and in the vicinity of the site of cleavage.

Despite the importance of 3D structure to understand the myriad functions of RNAs in cells, most RNA molecules remain out of reach of crystallographic and NMR methods. However, certain structural information such as base pairing and some tertiary contacts can be determined readily for many RNAs by bioinformatics or relatively low cost experiments. Further, because RNA structure is highly modular, it is possible to deduce local 3D structure from the solved structures of evolutionarily related RNAs or even unrelated RNAs that share the same module. RNABuilder is a software package that generates model RNA structures by treating the kinematics and forces at separate, multiple levels of resolution. Kinematically, bonds in bases, certain stretches of residues, and some entire molecules are rigid while other bonds remain flexible. Forces act on the rigid bases and selected individual atoms. Here we use RNABuilder to predict the structure of the 200-nucleotide Azoarcus group I intron by homology modeling against fragments of the distantly-related Twort and Tetrahymena group I introns and by incorporating base pairing forces where necessary. In the absence of any information from the solved Azoarcus intron crystal structure, the model accurately depicts the global topology, secondary and tertiary connections, and gives an overall RMSD value of 4.6 A relative to the crystal structure. The accuracy of the model is even higher in the intron core (RMSD = 3.5 A), whereas deviations are modestly larger for peripheral regions that differ more substantially between the different introns. These results lay the groundwork for using this approach for larger and more diverse group I introns, as well for still larger RNAs and RNA-protein complexes such as group II introns and the ribosomal subunits.