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Biomedical subjects

David S Goodsell

Publications and source records attributed to David S Goodsell.

At least 37 records · Page 2Linked to original sources
PubMed2004

The cAMP binding domain: an ancient signaling module.

cAMP-binding domains from several different proteins were analyzed to determine the properties and interactions of this recognition motif. Systematic computational analyses, including structure-based sequence comparison, surface matching, affinity grid analysis, and analyses of the ligand protein interactions were carried out. These analyses show distinctive roles of the sugar phosphate and the adenine in the cAMP-binding module. We propose that the cAMP-binding regulatory proteins function by providing an allosteric system in which the presence or absence of cAMP produces a substantial structural change through the loss of hydrophobic interactions with the adenine ring and consequent repositioning of the C helix. The modified positioning of the helix in turn is recognized by a protein-binding event, completing the allostery.

Amino Acid Sequence↗
PubMed2003

Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling.

The W191G cavity of cytochrome c peroxidase is useful as a model system for introducing small molecule oxidation in an artificially created cavity. A set of small, cyclic, organic cations was previously shown to bind in the buried, solvent-filled pocket created by the W191G mutation. We docked these ligands and a set of non-binders in the W191G cavity using AutoDock 3.0. For the ligands, we compared docking predictions with experimentally determined binding energies and X-ray crystal structure complexes. For the ligands, predicted binding energies differed from measured values by +/- 0.8 kcal/mol. For most ligands, the docking simulation clearly predicted a single binding mode that matched the crystallographic binding mode within 1.0 A RMSD. For 2 ligands, where the docking procedure yielded an ambiguous result, solutions matching the crystallographic result could be obtained by including an additional crystallographically observed water molecule in the protein model. For the remaining 2 ligands, docking indicated multiple binding modes, consistent with the original electron density, suggesting disordered binding of these ligands. Visual inspection of the atomic affinity grid maps used in docking calculations revealed two patches of high affinity for hydrogen bond donating groups. Multiple solutions are predicted as these two sites compete for polar hydrogens in the ligand during the docking simulation. Ligands could be distinguished, to some extent, from non-binders using a combination of two trends: predicted binding energy and level of clustering. In summary, AutoDock 3.0 appears to be useful in predicting key structural and energetic features of ligand binding in the W191G cavity.

Automation↗