Biomedical subjects

J A Given

Publications and source records attributed to J A Given.

5 recordsLinked to original sources

PubMed1999

Nucleic acid base-pairing and N-methylacetamide self-association in chloroform: affinity and conformation.

A recently developed computational method, 'mining minima', is used to examine the hydrogen-bonding interactions of nucleic acid base-pairs and of the N-methylacetamide homodimer in chloroform. The mining minima algorithm aggressively samples molecular conformations, identifies the most important local minima, and computes their contributions to the overall free energy of the system. Here, the CHARMM 98 parameter set is used for the potential energy and the generalized Born/surface area solvent model is used to account for the influence of the solvent. Good agreement with experiment is obtained for the non-covalent binding affinities of a series of complexes. The computational approach used here is applicable to a range of molecular systems.

Acetamides↗

PubMed1998

A hierarchical method for generating low-energy conformers of a protein-ligand complex.

A novel dynamical protocol for finding the low-energy conformations of a protein-ligand complex is described. The energy functions examined consist of an empirical force field with four different dielectric screening models; the generalized Born/surface area model also is examined. Application of the method to three complexes of known crystal structure provides insights into the energy functions used for selecting low-energy docked conformations and into the structure of the binding-energy surface. Evidence is presented that the local energy minima of a ligand in a binding site are arranged in a hierarchical fashion. This observation motivates the construction of a hierarchical docking algorithm that substantially enriches the population of ligand conformations close to the crystal conformation. The algorithm is also adapted to permit docking into a flexible binding site and preliminary tests of this method are presented.

Algorithms↗

PubMed1997

The statistical-thermodynamic basis for computation of binding affinities: a critical review.

Although the statistical thermodynamics of noncovalent binding has been considered in a number of theoretical papers, few methods of computing binding affinities are derived explicitly from this underlying theory. This has contributed to uncertainty and controversy in certain areas. This article therefore reviews and extends the connections of some important computational methods with the underlying statistical thermodynamics. A derivation of the standard free energy of binding forms the basis of this review. This derivation should be useful in formulating novel computational methods for predicting binding affinities. It also permits several important points to be established. For example, it is found that the double-annihilation method of computing binding energy does not yield the standard free energy of binding, but can be modified to yield this quantity. The derivation also makes it possible to define clearly the changes in translational, rotational, configurational, and solvent entropy upon binding. It is argued that molecular mass has a negligible effect upon the standard free energy of binding for biomolecular systems, and that the cratic entropy defined by Gurney is not a useful concept. In addition, the use of continuum models of the solvent in binding calculations is reviewed, and a formalism is presented for incorporating a limited number of solvent molecules explicitly.

Binding Sites↗

PubMed1997

A new class of models for computing receptor-ligand binding affinities.

Models for predicting the binding affinities of molecules in solution are either very detailed, making them computationally intensive and hard to test, or very simple, and thus less informative than one might wish. A new class of models that focus on the predominant states of the binding molecules promise to capture the essential physics of binding at modest computational cost.

Kinetics↗

PubMed1997

Chaos in protein dynamics.

MD simulations, currently the most detailed description of the dynamic evolution of proteins, are based on the repeated solution of a set of differential equations implementing Newton's second law. Many such systems are known to exhibit chaotic behavior, i.e., very small changes in initial conditions are amplified exponentially and lead to vastly different, inherently unpredictable behavior. We have investigated the response of a protein fragment in an explicit solvent environment to very small perturbations of the atomic positions (10(-3)-10(-9) A). Independent of the starting conformation (native-like, compact, extended), perturbed dynamics trajectories deviated rapidly, leading to conformations that differ by approximately 1 A RMSD within 1-2 ps. Furthermore, introducing the perturbation more than 1-2 ps before a significant conformational transition leads to a loss of the transition in the perturbed trajectories. We present evidence that the observed chaotic behavior reflects physical properties of the system rather than numerical instabilities of the calculation and discuss the implications for models of protein folding and the use of MD as a tool to analyze protein folding pathways.

Bacterial Proteins↗