A force field (MSXX) for molecular dynamics simulations of silicon nitride is derived using the Hessian biased technique from ab initio calculations on N(SiH3)3 and Si(NH2)4 clusters. This is used to model the nitrogen and silicon centers of the α and β forms of crystalline Si3N4 for prediction of crystal structures, lattice expansion parameters, elastic constants, phonon states, and thermodynamic properties. Experimental measurements on many of these important physical constants are lacking, so that these calculations provide the first reliable data on such fundamental properties of silicon nitride. This MSXX force field is expected to be useful for molecular dynamics simulations of dislocations and grain boundaries and for studying the reconstruction and energetics of clean, reduced, and oxidized surfaces.

A system for addressing in the construction of macromolecular assemblies can be based on the biospecificity of DNA (cytosine-5) methyltransferases and the capacity of these enzymes to form abortive covalent complexes at targeted 5-f luorocytosine residues in DNA. Using this system, macromolecular assemblies have been created using two representative methyltransferases: M⅐HhaI and M⅐MspI. When 5-f luorocytosine (F) is placed at the targeted cytosine in each recognition sequence in a synthetic oligodeoxynucleotide (GFGC for M⅐HhaI or FCGG for M⅐MspI), we show that the first recognition sequence becomes an address for M⅐HhaI, while the second sequence becomes an address for M⅐MspI. A chimeric enzyme containing a dodecapeptide antigen linked to the C terminus of M⅐HhaI retained its recognition specificity. That specificity served to address the linked peptide to the GFGC recognition site in DNA. With this assembly system components can be placed in a preselected order on the DNA helix. Axial spacing for adjacent addresses can be guided by the observed kinetic footprint of each methyltransferase. Axial rotation of the addressable protein can be guided by the screw axis of the DNA helix. The system has significant potential in the general construction of macromolecular assemblies. We anticipate that these assemblies will be useful in the construction of regular protein arrays for structural analysis, in the construction of protein-DNA systems as models of chromatin and the synaptonemal complex, and in the construction of macromolecular devices.Macromolecular assembly is easily approached with DNA. Branching through the formation of Watson-Crick paired duplexes in the shape of a Y or an X is now well known (1-4), and the feasibility of assembling 2-dimensional quadrilaterals and 3-dimensional cubes on which more extended structures can be based has been demonstrated (5, 6). However, the stable, site-directed attachment of labile enzymes and proteins to a DNA scaffold presents a formidable challenge in macromolecular fabrication. Candidate procedures in which the Watson-Crick base-pairing homology or triple-helix basepairing homology of an oligodeoxynucleotide is used to direct a tethered moiety to a preselected site in DNA (3, 4, 7-9) involve extremes of pH or temperature that can destroy the native structure of these proteins. Attachment systems based on antibodies directed against DNA are likely to lack specificity. On the other hand, antibodies to a hapten could be used to decorate a matrix depending on the pattern of haptens laid down during synthesis. The disadvantage here is that all hapten moieties are equivalent, and thus selective addressing would not be possible unless a series of haptens and antibodies directed to them could be developed. While a system of distinct haptens and antibodies is possible (3), it would be necessary to develop a set of hapten-phosphoramidites and the corresponding series of bifunctional antibodies to utilize this approach. Moreover, the use of noncovalent linkages sacrifice...

To help improve the accuracy of protein-ligand docking as a useful tool for drug discovery, we developed MPSim-Dock, which ensures a comprehensive sampling of diverse families of ligand conformations in the binding region followed by an enrichment of the good energy scoring families so that the energy scores of the sampled conformations can be reliably used to select the best conformation of the ligand. This combines elements of DOCK4.0 with molecular dynamics (MD) methods available in the software, MPSim. We test here the efficacy of MPSim-Dock to predict the 64 protein-ligand combinations formed by starting with eight trypsin cocrystals, and crossdocking the other seven ligands to each protein conformation. We consider this as a model for how well the method would work for one given target protein structure. Using as a criterion that the structures within 2 kcal/mol of the top scoring include a conformation within a coordinate root mean square (CRMS) of 1 A of the crystal structure, we find that 100% of the 64 cases are predicted correctly. This indicates that MPSim-Dock can be used reliably to identify strongly binding ligands, making it useful for virtual ligand screening.

We report the 3D structure predicted for the mouse MrgC11 (mMrgC11) receptor by using the MembStruk computational protocol, and the predicted binding site for the F-M-R-F-NH(2) neuropeptide together with four singly chirally modified ligands. We predicted that the R-F-NH(2) part of the tetrapeptide sticks down into the protein between the transmembrane (TM) domains 3, 4, 5, and 6. The Phe (F-NH(2)) interacted favorably with Tyr110 (TM3), while the Arg makes salt bridges to Asp161 (TM4) and Asp179 (TM5). We predicted that the Met extends from the binding site, but the terminal Phe residue sticks back into an aromatic/hydrophobic site flanked by Tyr237, Leu238, Leu240, and Tyr256 (TM6), and Trp162 (TM4). We carried out subsequent mutagenesis experiments followed by intracellular calcium-release assays that demonstrated the dramatic decrease in activity for the Tyr110Ala, Asp161Ala, and Asp179Ala substitutions, which was predicted by our model. These experiments provide strong evidence that our predicted G protein-coupled receptor (GPCR) structure is sufficiently accurate to identify binding sites for selective ligands. Similar studies were made with the mMrgA1 receptor, which did not bind the R-F-NH(2) dipeptide; we explain this to be due to the increased hydrophobic character of the binding pocket in mMrgA1.

Mrg receptors are orphan G protein-coupled receptors (GPCRs) located mainly at the specific set of sensory neurons in the dorsal root ganglia, suggesting a role in nociception. We report here the 3-D structure of rat MrgA (rMrgA) receptor [obtained from homology modeling to the recently validated predicted structures of mouse MrgA1 and MrgC11] and the structure of adenine (a known agonist, K i =18nM) bound to rMrgA. This predicted binding site is located within transmembrane helical domains (TMs) 3, 4, 5 and 6, with Asn residues in TM3 and TM4 identified as the key residues for adenine binding. Here the side chain of Asn88 (TM3) forms two pairs of hydrogen bonds with N3 and N9 of adenine while Asn146 (TM4) makes two pairs of hydrogen bonds with N1 and N6 of adenine. These interactions lock adenine tightly in the binding pocket. We also predict the binding site of guanine (not an agonist) and seven other derivatives. Guanine cannot make the hydrogen bond to Asn146 (TM4), leading to binding too weak to be observed experimentally. The predicted binding affinity for other adenine derivatives correlates with the availability of the hydrogen bonds to these two Asn residues. These results validate the predicted structure for rat MrgA and suggest mutation experiments that could further validate the structure. Moreover the predicted structure and binding site should be useful for seeking other small molecule agonists and antagonists.