Biomedical subjects

D M Standley

Publications and source records attributed to D M Standley.

4 recordsLinked to original sources

PubMed1999

Prediction of protein tertiary structure to low resolution: performance for a large and structurally diverse test set.

We report the tertiary structure predictions for 95 proteins ranging in size from 17 to 160 residues starting from known secondary structure. Predictions are obtained from global minimization of an empirical potential function followed by the application of a refined atomic overlap potential. The minimization strategy employed represents a variant of the Monte Carlo plus minimization scheme of Li and Scheraga applied to a reduced model of the protein chain. For all of the cases except beta-proteins larger than 75 residues, a native-like structure, usually 4-6 A root-mean-square deviation from the native, is located. For beta-proteins larger than 75 residues, the energy gap between native-like structures and the lowest energy structures produced in the simulation is large, so that low RMSD structures are not generated starting from an unfolded state. This is attributed to the lack of an explicit hydrogen bond term in the potential function, which we hypothesize is necessary to stabilize large assemblies of beta-strands.

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PubMed1999

Protein tertiary structure prediction using a branch and bound algorithm.

We report a new method for predicting protein tertiary structure from sequence and secondary structure information. The predictions result from global optimization of a potential energy function, including van der Waals, hydrophobic, and excluded volume terms. The optimization algorithm, which is based on the alphaBB method developed by Floudas and coworkers (Costas and Floudas, J Chem Phys 1994;100:1247-1261), uses a reduced model of the protein and is implemented in both distance and dihedral angle space, enabling a side-by-side comparison of methodologies. For a set of eight small proteins, representing the three basic types--all alpha, all beta, and mixed alpha/beta--the algorithm locates low-energy native-like structures (less than 6A root mean square deviation from the native coordinates) starting from an unfolded state. Serial and parallel implementations of this methodology are discussed.

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PubMed1999

A branch and bound algorithm for protein structure refinement from sparse NMR data sets.

We describe new methods for predicting protein tertiary structures to low resolution given the specification of secondary structure and a limited set of long-range NMR distance constraints. The NMR data sets are derived from a realistic protocol involving completely deuterated 15N and 13C-labeled samples. A global optimization method, based upon a modification of the alphaBB (branch and bound) algorithm of Floudas and co-workers, is employed to minimize an objective function combining the NMR distance restraints with a residue-based protein folding potential containing hydrophobicity, excluded volume, and van der Waals interactions. To assess the efficacy of the new methodology, results are compared with benchmark calculations performed via the X-PLOR program of Brünger and co-workers using standard distance geometry/molecular dynamics (DGMD) calculations. Seven mixed alpha/beta proteins are examined, up to a size of 183 residues, which our methods are able to treat with a relatively modest computational effort, considering the size of the conformational space. In all cases, our new approach provides substantial improvement in root-mean-square deviation from the native structure over the DGMD results; in many cases, the DGMD results are qualitatively in error, whereas the new method uniformly produces high quality low-resolution structures. The DGMD structures, for example, are systematically non-compact, which probably results from the lack of a hydrophobic term in the X-PLOR energy function. These results are highly encouraging as to the possibility of developing computational/NMR protocols for accelerating structure determination in larger proteins, where data sets are often underconstrained.

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PubMed1998

Tertiary structure prediction of mixed alpha/beta proteins via energy minimization.

We describe an improved algorithm for protein structure prediction, assuming that the location of secondary structural elements is known, with particular focus on prediction for proteins containing beta-strands. Hydrogen bonding terms are incorporated into the potential function, supplementing our previously developed residue-residue potential which is based on a combination of database statistics and an excluded volume term. Two small mixed alpha/beta proteins, 1-CTF and BPTI, are studied. In order to obtain native-like structures, it is necessary to allow the beta-strands in BPTI to distort substantially from an ideal geometry, and an automated algorithm to carry this out efficiently is presented. Simulated annealing Monte Carlo methods, which contain a genetic algorithm component as well, are used to produce an ensemble of low-energy structures. For both proteins, a cluster of structures with low RMS deviation from the native structure is generated and the energetic ranking of this cluster is in the top 2 or 3 clusters obtained from simulations. These results are encouraging with regard to the possibility of constructing a robust procedure for tertiary folding which is applicable to beta-strand containing proteins.

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