Dissertation/Thesis Abstract

Computational Studies of Proteins: Dynamics and Interactions with Small Molecules
by Park, Min Sun, Ph.D., University of Rochester, 2011, 109; 3458547
Abstract (Summary)

Understanding protein dynamics is important for drug design. G proteins play an important role in cellular signal transduction and are involved in many processes. They are heterotrimers consisting of α, β, and γ subunits, and are maintained in an inactive state by association in a bound complex. In the standard model for signaling, the exchange of GDP for GTP on the Gα subunit leads a conformational change and a dissociation of the Gα subunit from the Gβγ subunits. The subunits are then free to interact with diverse binding partners for downstream signal transduction. To examine the role of protein flexibility in molecular recognition by Gβγ, TROSY-HSQC NMR studies with site-specific 15N labeling of Gβ tryptophan residue backbone and indole amines were performed. The NMR experiments of free G protein Gβγ heterodimer suggested that a particular tryptophan residue in the binding interface is highly mobile. Molecular Dynamics simulations of the unbound Gβγ heterodimer were performed showing that the GβW99 is significantly more mobile than the other tryptophans on the nanosecond timescale. Further, we performed nanosecond-timescale molecular dynamics simulations to investigate conformational changes and dynamics of Gβγ in the presence of several binding partners: a high-affinity peptide (SIGK), phosducin, and the GDP-bound α subunit, and interpreted these in conjunction with the NMR experiments.

Several studies have suggested that disrupting interactions of the G protein betagamma subunits with downstream binding partners might be a valuable study for pharmaceutical development. We examined several docking and scoring protocols for estimating binding affinities for a set of 830 ligands from the NCI diversity set to the Gβ1γ2 subunit and compared these with IC50s measured in a competition ELISA with a high-affinity peptidic ligand. The best-performing docking protocol used a consensus score and ensemble docking and resulted in a 6-fold enrichment of high-affinity compounds in the top-ranked 5% of the ligand data set.

To investigate the effects of multiple protonation states on protein-ligand recognition, we generated alternative protonation states for selected titratable groups of ligands and receptors. The selection of states was based on the predicted pK(a) of the unbound receptor and ligand and the proximity of titratable groups of the receptor to the binding site. Various ligand tautomer states were also considered. An independent docking calculation was run for each state. The accuracies of these approaches were compared, using a set of 176 protein-ligand complexes (15 receptors) for which crystal structures and measured binding affinities are available. The best agreement with experiment was obtained when ligand poses from experimental crystal structures were used. Generally, using an ensemble of all generated protonation states of the ligand and receptor gave the best correlation between calculated and measured affinities.

Indexing (document details)
Advisor: Stern, Harry A.
Commitee:
School: University of Rochester
School Location: United States -- New York
Source: DAI-B 72/08, Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Biochemistry, Biophysics
Keywords: G-proteins, Protein-protein interactions, Protonation state, Virtual screening
Publication Number: 3458547
ISBN: 978-1-124-65522-2
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