Biomedical subjects

David A Cosgrove

Publications and source records attributed to David A Cosgrove.

4 recordsLinked to original sources

PubMed2006

Matched molecular pairs as a guide in the optimization of pharmaceutical properties; a study of aqueous solubility, plasma protein binding and oral exposure.

By identifying every pair of molecules that differ only by a particular, well-defined, structural transformation in a database of measured properties and computing the corresponding change in property, we obtain an overview of the effect that structural change has upon the property and set an expectation for what will happen when that transformation is applied elsewhere. The mean change indicates the expected magnitude of the change in the property and the number of cases in which the property increases give the probability that the structural transformation will cause the property to increase. Outliers indicate potential ways of avoiding the general trend. Comparing to changes in lipophilicity highlights structural transformations that have unusual effects, some of which can be explained by conformational changes. In this paper, we focus upon the effects on aqueous solubility, plasma protein binding and oral exposure of adding substituents to aromatic rings and methylating heteroatoms.

Administration, Oral↗

PubMed2004

Identification of compounds with nanomolar binding affinity for checkpoint kinase-1 using knowledge-based virtual screening.

A virtual screen of a subsection of the AstraZeneca compound collection was performed for checkpoint kinase-1 (Chk-1 kinase) using a knowledge-based strategy. This involved initial filtering of the compound collection by application of generic physical properties followed by removal of compounds with undesirable chemical functionality. Subsequently, a 3-D pharmacophore screen for compounds with kinase binding motifs was applied. A database of approximately 200K compounds remained for docking into the active site of Chk-1 kinase, using the FlexX-Pharm program. For each compound that docked successfully into the binding site, up to 100 poses were saved. These poses were then postfiltered using a customized consensus scoring scheme for a kinase, followed by visual inspection of a selection of the docked compounds. This resulted in 103 compounds being ordered for testing in the project assay, and 36 of these (corresponding to four chemical classes) were found to inhibit the enzyme in a dose-response fashion with IC(50) values ranging from 110 nM to 68 microM.

Amino Acid Motifs↗

PubMedDate not supplied

Lead hopping using SVM and 3D pharmacophore fingerprints.

The combination of 3D pharmacophore fingerprints and the support vector machine classification algorithm has been used to generate robust models that are able to classify compounds as active or inactive in a number of G-protein-coupled receptor assays. The models have been tested against progressively more challenging validation sets where steps are taken to ensure that compounds in the validation set are chemically and structurally distinct from the training set. In the most challenging example, we simulate a lead-hopping experiment by excluding an entire class of compounds (defined by a core substructure) from the training set. The left-out active compounds comprised approximately 40% of the actives. The model trained on the remaining compounds is able to recall 75% of the actives from the "new" lead series while correctly classifying >99% of the 5000 inactives included in the validation set.

Computer Simulation↗

PubMedDate not supplied

Scaffold hopping using clique detection applied to reduced graphs.

Similarity-based methods for virtual screening are widely used. However, conventional searching using 2D chemical fingerprints or 2D graphs may retrieve only compounds which are structurally very similar to the original target molecule. Of particular current interest then is scaffold hopping, that is, the ability to identify molecules that belong to different chemical series but which could form the same interactions with a receptor. Reduced graphs provide summary representations of chemical structures and, therefore, offer the potential to retrieve compounds that are similar in terms of their gross features rather than at the atom-bond level. Using only a fingerprint representation of such graphs, we have previously shown that actives retrieved were more diverse than those found using Daylight fingerprints. Maximum common substructures give an intuitively reasonable view of the similarity between two molecules. However, their calculation using graph-matching techniques is too time-consuming for use in practical similarity searching in larger data sets. In this work, we exploit the low cardinality of the reduced graph in graph-based similarity searching. We reinterpret the reduced graph as a fully connected graph using the bond-distance information of the original graph. We describe searches, using both the maximum common induced subgraph and maximum common edge subgraph formulations, on the fully connected reduced graphs and compare the results with those obtained using both conventional chemical and reduced graph fingerprints. We show that graph matching using fully connected reduced graphs is an effective retrieval method and that the actives retrieved are likely to be topologically different from those retrieved using conventional 2D methods.

Algorithms↗