Dihedral angle

Abstract: Molecular mechanics is powerful for its speed in atomistic simulations, but an accurate force field is required. The Amber ff99SB force field improved protein secondary structure balance and dynamics from earlier force fields like ff99, but weaknesses in side chain rotamer and backbone secondary structure preferences have been identified. Here, we performed a complete refit of all amino acid side chain dihedral parameters, which had been carried over from ff94. The training set of conformations included multidimensional dihedral scans designed to improve transferability of the parameters. Improvement in all amino acids was obtained as compared to ff99SB. Parameters were also generated for alternate protonation states of ionizable side chains. Average errors in relative energies of pairs of conformations were under 1.0 kcal/mol as compared to QM, reduced 35% from ff99SB. We also took the opportunity to make empirical adjustments to the protein backbone dihedral parameters as compared to ff99SB. Multiple sm...

Abstract: The new program DYANA (DYnamics Algorithm for Nmr Applications) for efficient calculation of three-dimensional protein and nucleic acid structures from distance constraints and torsion angle constraints collected by nuclear magnetic resonance (NMR) experiments performs simulated annealing by molecular dynamics in torsion angle space and uses a fast recursive algorithm to integrate the equations of motions. Torsion angle dynamics can be more efficient than molecular dynamics in Cartesian coordinate space because of the reduced number of degrees of freedom and the concomitant absence of high-frequency bond and angle vibrations, which allows for the use of longer time-steps and/or higher temperatures in the structure calculation. It also represents a significant advance over the variable target function method in torsion angle space with the REDAC strategy used by the predecessor program DIANA. DYANA computation times per accepted conformer in the "bundle" used to represent the NMR structure compare favorably with those of other presently available structure calculation algorithms, and are of the order of 160 seconds for a protein of 165 amino acid residues when using a DEC Alpha 8400 5/300 computer. Test calculations starting from conformers with random torsion angle values further showed that DYANA is capable of efficient calculation of high-quality protein structures with up to 400 amino acid residues, and of nucleic acid structures.

Abstract: Analysis of neighboring aromatic groups in four biphenyl peptides or peptide analogs and 34 proteins reveals a specific aromatic-aromatic interaction. Aromatic pairs (less than 7 A between phenyl ring centroids) were analyzed for the frequency of pair type, their interaction geometry (separation and dihedral angle), their nonbonded interaction energy, the secondary structural locations of interacting residues, their environment, and their conservation in related molecules. The results indicate that on average about 60 percent of aromatic side chains in proteins are involved in aromatic pairs, 80 percent of which form networks of three or more interacting aromatic side chains. Phenyl ring centroids are separated by a preferential distance of between 4.5 and 7 A, and dihedral angles approaching 90 degrees are most common. Nonbonded potential energy calculations indicate that a typical aromatic-aromatic interaction has energy of between -1 and -2 kilocalories per mole. The free energy contribution of the interaction depends on the environment of the aromatic pair. Buried or partially buried pairs constitute 80 percent of the surveyed sample and contribute a free energy of between -0.6 and -1.3 kilocalories per mole to the stability of the protein's structure at physiologic temperature. Of the proteins surveyed, 80 percent of these energetically favorable interactions stabilize tertiary structure, and 20 percent stabilize quaternary structure. Conservation of the interaction in related molecules is particularly striking.

Abstract: A new coupling constant-torsion angle relation for the three-bond 1H-1H spin-spin coupling constant is formulated. The relation includes a correction for the electronegativity of substituents. The correction term is written as a function of the electronegativity, the H-C-C-H torsion angle, and the orientation of each substituent relative to the coupled protons. A dataset consisting of 315 experimental coupling constants was used to derive six empirical parameters by means of an iterative least-squares minimization procedure. The precision of the proposed equation, expressed as the root-mean-square deviation (0.48 Hz), is superior to any hitherto reported. It is shown that separate treatment of CH2CH2, CH2CH and CHCH fragments even improves this precision. An application in the field of monosubstituted cyclohexanes is given.

Abstract: Comparative protein structure prediction is limited mostly by the errors in alignment and loop modeling. We describe here a new automated modeling technique that significantly improves the accuracy of loop predictions in protein structures. The positions of all nonhydrogen atoms of the loop are optimized in a fixed environment with respect to a pseudo energy function. The energy is a sum of many spatial restraints that include the bond length, bond angle, and improper dihedral angle terms from the CHARMM-22 force field, statistical preferences for the main-chain and side-chain dihedral angles, and statistical preferences for nonbonded atomic contacts that depend on the two atom types, their distance through space, and separation in sequence. The energy function is optimized with the method of conjugate gradients combined with molecular dynamics and simulated annealing. Typically, the predicted loop conformation corresponds to the lowest energy conformation among 500 independent optimizations. Predictions were made for 40 loops of known structure at each length from 1 to 14 residues. The accuracy of loop predictions is evaluated as a function of thoroughness of conformational sampling, loop length, and structural properties of native loops. When accuracy is measured by local superposition of the model on the native loop, 100, 90, and 30% of 4-, 8-, and 12-residue loop predictions, respectively, had <2 A RMSD error for the mainchain N, C(alpha), C, and O atoms; the average accuracies were 0.59 +/- 0.05, 1.16 +/- 0.10, and 2.61 +/- 0.16 A, respectively. To simulate real comparative modeling problems, the method was also evaluated by predicting loops of known structure in only approximately correct environments with errors typical of comparative modeling without misalignment. When the RMSD distortion of the main-chain stem atoms is 2.5 A, the average loop prediction error increased by 180, 25, and 3% for 4-, 8-, and 12-residue loops, respectively. The accuracy of the lowest energy prediction for a given loop can be estimated from the structural variability among a number of low energy predictions. The relative value of the present method is gauged by (1) comparing it with one of the most successful previously described methods, and (2) describing its accuracy in recent blind predictions of protein structure. Finally, it is shown that the average accuracy of prediction is limited primarily by the accuracy of the energy function rather than by the extent of conformational sampling.