Biomedical subjects

J Pitera

Publications and source records attributed to J Pitera.

3 recordsLinked to original sources

PubMed2001

Assessing the effect of conformational averaging on the measured values of observables.

Experiment and computer simulation are two complementary tools to understand the dynamics and behavior of biopolymers in solution. One particular area of interest is the ensemble of conformations populated by a particular molecule in solution. For example, what fraction of a protein sample exists in its folded conformation? How often does a particular peptide form an alpha helix versus a beta hairpin? To address these questions, it is important to determine the sensitivity of a particular experiment to changes in the distribution of molecular conformations. Consequently, a general analytic formalism is proposed to determine the sensitivity of a spectroscopic observable to the underlying distribution of conformations. A particular strength of the approach is that it provides an expression for a weighted average across conformational substates that is independent of the averaging function used. The formalism is described and applied to experimental and simulated nuclear Overhauser enhancement (NOE) and 3J-coupling data on peptides in solution.

Computer Simulation↗

PubMed1999

Prediction of the binding free energies of new TIBO-like HIV-1 reverse transcriptase inhibitors using a combination of PROFEC, PB/SA, CMC/MD, and free energy calculations.

We have ranked 13 different TIBO derivatives with respect to their relative free energies of binding using two approximate computational methods: adaptive chemical Monte Carlo/molecular dynamics (CMC/MD) and Poisson-Boltzmann/solvent accessibility (PB/SA) calculations. Eight of these derivatives have experimentally determined binding affinities. The remaining new derivatives were constructed based on contour maps around R86183 (8Cl-TIBO), generated with the program PROFEC (pictorial representation of free energy changes). The rank order among the derivatives with known binding affinity was in good agreement with experimental results for both methods, with average errors in the binding free energies of 1. 0 kcal/mol for CMC/MD and 1.3 kcal/mol for the PB/SA method. With both methods, we found that one of the new derivatives was predicted to bind 1-2 kcal/mol better than R86183, which is the hitherto most tightly binding derivative. This result was subsequently supported by the most rigorous free energy computational methods: free energy perturbation (FEP) and thermodynamic integration (TI). The strategy we have used here should be generally useful in structure-based drug optimization. An initial ligand is derivatized based on PROFEC suggestions, and the derivatives are ranked with CMC/MD and PB/SA to identify promising compounds. Since these two methods rely on different sets of approximations, they serve as a good complement to each other. Predictions of the improved affinity can be reinforced with FEP or TI and the best compounds synthesized and tested. Such a computational strategy would allow many different derivatives to be tested in a reasonable time, focusing synthetic efforts on the most promising modifications.

Algorithms↗

PubMed1997

Graphical visualization of mean hydration from molecular dynamics simulations.

How does one characterize water solvating a complex solute? Specific hydration of proteins and nucleic acids plays a key role in many biological processes. However, traditional pairwise descriptions of solvent structure (radial distribution functions, etc.) are incapable of adequately describing the hydration of these complex solutes. We have developed methods to visualize the average three-dimensional water structure surrounding a solute, as seen in a molecular dynamics (MD) simulation. Applications to simple solutes [sodium ion, N-methyl acetamide, 18-crown-6, (hydroxymethyl)phenols] are presented, and the extension of the method to larger molecules of biochemical interest is discussed.

Acetamides↗