Energy minimizations of rubredoxin

Feero, Dino R.; McQueen, John E.; McCown, J.Tom; Hermans, Jan

doi:10.1016/0022-2836(80)90363-0

Cited by 39 publications

(18 citation statements)

References 42 publications

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“…Additional force fields used for protein simulations include MMFF, 194 CEDAR, 195,196 ENCAD,197,198 and CVFF, 21 among others. A more comprehensive list may be found it the recent review by Ponder and Case.…”

Section: Protein Force Fieldsmentioning

confidence: 99%

Empirical force fields for biological macromolecules: Overview and issues

2004

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Empirical force field-based studies of biological macromolecules are becoming a common tool for investigating their structure-activity relationships at an atomic level of detail. Such studies facilitate interpretation of experimental data and allow for information not readily accessible to experimental methods to be obtained. A large part of the success of empirical force field-based methods is the quality of the force fields combined with the algorithmic advances that allow for more accurate reproduction of experimental observables. Presented is an overview of the issues associated with the development and application of empirical force fields to biomolecular systems. This is followed by a summary of the force fields commonly applied to the different classes of biomolecules; proteins, nucleic acids, lipids, and carbohydrates. In addition, issues associated with computational studies on "heterogeneous" biomolecular systems and the transferability of force fields to a wide range of organic molecules of pharmacological interest are discussed.

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Section: Protein Force Fieldsmentioning

confidence: 99%

Empirical force fields for biological macromolecules: Overview and issues

2004

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“…This program uses a force field with nonbonded parameters that are the same as those of the GROMOS program (14) and a description of geometry and geometric deformations that was developed earlier (15). The SHAKE algorithm (16) was used to constrain all bond lengths in the simulations.…”

Section: Methodsmentioning

confidence: 99%

Thermodynamic parameters for the helix-coil transition of oligopeptides: molecular dynamics simulation with the peptide growth method.

Wang

O’Connell

Tropsha

et al. 1995

Proc. Natl. Acad. Sci. U.S.A.

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The helix-coil transition equilibrium of polypeptides in aqueous solution was studied by molecular dynamics simulation. The peptide growth simulation method was introduced to generate dynamic models of polypeptide chains in a statistical (random) coil or an a-helical conformation. The key element of this method is to build up a polypeptide chain during the course of a molecular transformation simulation, successively adding whole amino acid residues to the chain in a predefined conformation state (e.g., a-helical or statistical coil). Thus, oligopeptides of the same length and composition, but having different conformations, can be incrementally grown from a common precursor, and their relative conformational free energies can be calculated as the difference between the free energies for growing the individual peptides. This affords a straightforward calculation ofthe Zimm-Bragg a and s parameters for helix initiation and helix growth. The calculated r and s parameters for the polyalanine c-helix are in reasonable agreement with the experimental measurements. The peptide growth simulation method is an effective way to study quantitatively the thermodynamics of local protein folding.Polypeptide chains can assume a variety of regular structures, many of which are also found as structural elements of proteins. Several theories of the helix-coil transition have been developed to quantitate the relation between the random state of the unfolded peptide (statistical coil) and the helical conformation (1-3). According to these theories, each amino acid can adopt one of only two states, helix and coil, and the helix-coil transition consists of two processes, helix initiation and helix growth. The former is difficult, because several consecutive residues must simultaneously assume the helical conformation, which is associated with a large entropy loss without concomitant stabilization by intramolecular interactions such as hydrogen bonds. The treatment by Zimm and Bragg (1) introduces two equilibrium constants, one for helix initiation, a, and the other for helix growth, s. Reliable oa and s parameters have been evaluated for polypeptides (4, 5).Molecular dynamics simulations have been used to compute theoretical estimates of the free energy of helix formation; these calculations employed thermodynamic integration or umbrella sampling with forced conformation change (6-8). However, the substantial conformation changes associated with the helix-coil transition make such calculations computationally difficult for long peptides, and the description that has emerged from these earlier calculations remains incomplete.Recently, Tropsha et al. (9) have reported the peptide growth simulation (PGS) method, which affords calculation of conformational free energy differences without the need for conformational forcing. This approach is based on methods developed earlier for calculating free energy differences between different conformations of amino acid side chains (10). According to the PGS method, identical polypeptides i...

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“…Net atomic charges obtained by the Del Re method were used with a unit dielectric constant, and hydrogen bonding was represented by a modified H...O potential. This N..-N potential was part of a set specifically intended to meet the requirements of peptide and protein structures; it has recently been used to minimize the energy of the 54-residue protein rubredoxin (Ferro, McQueen, McCown & Hermans, 1980). This potential was not transferable to molecular nitrogen because it has an unreasonably deep potential well (-0.691 kJ mol -~) and yielded nearly twice the observed lattice energy and a lattice constant 6.5 % too small (Table 6).…”

Section: Aa(%)mentioning

confidence: 99%