
AbstractA method is presented to model loops of protein to be used in homology modeling of proteins. This method employs the ESAP program of Higo et al. (Higo, J., Collura, V., & Garnier, J., 1992, Biopolymers 32, 33–43) and is based on a fast Monte Carlo simulation and a simulated annealing algorithm. The method is tested on different loops or peptide segments from immunoglobulin, bovine pancreatic trypsin inhibitor, and bovine trypsin. The predicted structure is obtained from the ensemble average of the coordinates of the Monte Carlo simulation at 300 K, which exhibits the lowest internal energy. The starting conformation of the loop prior to modeling is chosen to be completely extended, and a closing harmonic potential is applied to N, CA, C, and O atoms of the terminal residues. A rigid geometry potential of Robson and Platt (1986, J. Mol. Biol. 188, 259–281) with a united atom representation is used. This we demonstrate to yield a loop structure with good hydrogen bonding and torsion angles in the allowed regions of the Ramachandran map. The average accuracy of the modeling evaluated on the eight modeled loops is 1 Å root mean square deviation (rmsd) for the backbone atoms and 2.3 Å rmsd for all heavy atoms.
Models, Molecular, STRUCTURE, BIOCHIMIE, Protein Conformation, [SDV]Life Sciences [q-bio], Immunoglobulins, Hydrogen Bonding, Crystallography, X-Ray, [SDV] Life Sciences [q-bio], Trypsin Inhibitor, Kazal Pancreatic, Computer Simulation, Trypsin, Algorithms
Models, Molecular, STRUCTURE, BIOCHIMIE, Protein Conformation, [SDV]Life Sciences [q-bio], Immunoglobulins, Hydrogen Bonding, Crystallography, X-Ray, [SDV] Life Sciences [q-bio], Trypsin Inhibitor, Kazal Pancreatic, Computer Simulation, Trypsin, Algorithms
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 74 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
