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M Paul Gleeson

Publications and source records attributed to M Paul Gleeson.

4 recordsLinked to original sources
PubMed2007

Plasma protein binding affinity and its relationship to molecular structure: an in-silico analysis.

In-silico plasma protein binding (PPB) models have been generated on human and rat in-house datasets, and on a human dataset sourced from the literature. From the results reported herein, it is apparent that models built on datasets relevant to the chemotypes under investigation in lead optimization programs will perform considerably better in this role than those generated on diverse compounds sourced from the literature. The in-house human and rat partial least-squares regression (PLS) models have cross-validated q2 values of 0.53 and 0.42 on the training sets, respectively. On the independent test and validation sets, they display similar predictive ability, with logK prediction errors of approximately 0.5 log units. This compares to approximately 0.25 log units variability expected for experiment. Given the considerable interspecies PPB differences, the prediction of PPB in one species using measurements in the other is no better than a prediction from an in-silico model generated on that species.

Analysis of Variance↗
PubMed2006

In silico human and rat Vss quantitative structure-activity relationship models.

We present herein a QSAR tool enabling an entirely in silico prediction of human and rat steady-state volume of distribution (Vss), to be made prior to chemical synthesis, preceding detailed allometric or mechanistic assessment of Vss. Three different statistical methodologies, Bayesian neural networks (BNN), classification and regression trees (CART), and partial least squares (PLS) were employed to model human (N=199) and rat (N=2086) data sets. The results in prediction of an independent test set show the human model has an r2 of 0.60 and an rms error in prediction of 0.48. The corresponding rat model has an r2 of 0.53 and an rms error in prediction of 0.37, indicating both models could be very useful in the early stages of the drug discovery process. This is the first reported entirely in silico approach to the prediction of rat and human steady-state volume of distribution.

Animals↗
PubMed2004

Theoretical analysis of peptidyl alpha-ketoheterocyclic inhibitors of human neutrophil elastase: Insight into the mechanism of inhibition and the application of QM/MM calculations in structure-based drug design.

It has been suggested from QSAR data (P. D. Edwards, D. J. Wolanin, D.A. Andisik and M. W. Davis, J. Med. Chem., 1995, 38, 76) that the inhibition of elastase by peptidyl alpha-ketoheterocyclic inhibitors can occur in two ways, the less potent inhibitors forming a non-bonded Michaelis complex and the more potent set a covalently bonded enzyme-substrate intermediate. We report QM/MM studies of both binding and reactivity that confirm these findings, showing that the activity of the least potent set of inhibitors correlates with the calculated binding energy, and that of the more potent set correlates with the stability of the intermediate. These calculations show that QM/MM methods can be successfully employed to understand complicated structure-activity relationships and might be employed in the design and assessment of new inhibitors.

Cyclization↗