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ABSTRACT: Membrane targeting proteins are recruited to specific membranes during cell signaling events, including signals at the leading edge of chemotaxing cells. Recognition and binding to specific lipids play a central role in targeting reactions, but it remains difficult to analyze the molecular features of such protein-lipid interactions. We propose that the surface diffusion constant of peripheral membrane-bound proteins contains useful information about protein-lipid contacts and membrane dynamics. To test this hypothesis, we use single-molecule fluorescence microscopy to probe the effects of lipid binding stoichiometry on the diffusion constants of engineered proteins containing one to three pleckstrin homology domains coupled by flexible linkers. Within error, the lateral diffusion constants of these engineered constructs are inversely proportional to the number of tightly bound phosphatidylinositol-(3,4,5)-trisphosphate lipids. The same trend is observed in coarse-grained molecular dynamics simulations and hydrodynamic bead calculations of lipid multimers connected by model tethers. Overall, single molecule diffusion measurements are found to provide molecular information about protein-lipid interactions. Moreover, the experimental and computational results independently indicate that the frictional contributions of multiple, coupled but well-separated lipids are additive, analogous to the free-draining limit for isotropic fluids--an insight with significant implications for theoretical description of bilayer lipid dynamics.
Biophysical Journal 11/2010; 99(9):2879-87. · 3.65 Impact Factor
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ABSTRACT: In structure-based drug discovery, researchers would like to identify all possible scaffolds for a given target. However, techniques that push the boundaries of chemical space could lead to many false positives or inhibitors that lack specificity for the target. Is it possible to broadly identify the appropriate chemical space for the inhibitors and yet maintain target specificity? To address this question, we have turned to dihydrofolate reductase (DHFR), a well-studied metabolic enzyme of pharmacological relevance. We have extended our multiple protein structure (MPS) method for receptor-based pharmacophore models to use multiple X-ray crystallographic structures. Models were created for DHFR from human and Pneumocystis carinii. These models incorporate a fair degree of protein flexibility and are highly selective for known DHFR inhibitors over drug-like non-inhibitors. Despite sharing a highly conserved active site, the pharmacophore models reflect subtle differences between the human and P. carinii forms, which identify species-specific, high-affinity inhibitors. We also use structures of DHFR from Candida albicans as a counter example. The available crystal structures show little flexibility, and the resulting models give poorer performance in identifying species-specific inhibitors. Therapeutic success for this system may depend on achieving species specificity between the related human host and these key fungal targets. The MPS technique is a promising advance for structure-based drug discovery for DHFR and other proteins of biomedical interest.
Journal of the American Chemical Society 04/2007; 129(12):3634-40. · 9.91 Impact Factor
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ABSTRACT: Developing methods to incorporate protein flexibility into structure-based drug design is an important challenge. Our approach uses multiple protein structures (MPS) to create a receptor-based pharmacophore model of the desired target. We have previously demonstrated the success of the method by applying it to human immunodeficiency virus-1 protease (HIV-1p). Our models, based on an apo structure, discriminated known HIV-1p inhibitors from druglike inactive compounds and also accurately identified bound conformations of known inhibitors. Here, we test the method by applying it to all three unbound crystal structures of HIV-1p. We have also improved our method with denser probe mapping of the binding site and refined our selection criteria for pharmacophore elements. Our improved protocol has led to the development of a consistent 8-site pharmacophore model for HIV-1p, which is independent of starting structure, and a robust MPS pharmacophore method that is more amenable to automation.
Journal of Medicinal Chemistry 07/2006; 49(12):3478-84. · 5.25 Impact Factor
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ABSTRACT: Binding MOAD (Mother of All Databases) is the largest collection of high-quality, protein-ligand complexes available from the Protein Data Bank. At this time, Binding MOAD contains 5331 protein-ligand complexes comprised of 1780 unique protein families and 2630 unique ligands. We have searched the crystallography papers for all 5000+ structures and compiled binding data for 1375 (26%) of the protein-ligand complexes. The binding-affinity data ranges 13 orders of magnitude. This is the largest collection of binding data reported to date in the literature. We have also addressed the issue of redundancy in the data. To create a nonredundant dataset, one protein from each of the 1780 protein families was chosen as a representative. Representatives were chosen by tightest binding, best resolution, etc. For the 1780 "best" complexes that comprise the nonredundant version of Binding MOAD, 475 (27%) have binding data. This significant collection of protein-ligand complexes will be very useful in elucidating the biophysical patterns of molecular recognition and enzymatic regulation. The complexes with binding-affinity data will help in the development of improved scoring functions and structure-based drug discovery techniques. The dataset can be accessed at http://www.BindingMOAD.org.
Proteins Structure Function and Bioinformatics 09/2005; 60(3):333-40. · 3.39 Impact Factor
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ABSTRACT: Escherichia coli dihydrofolate reductase (DHFR) is a long-standing target for enzyme studies. The influence of protein motion on its catalytic cycle is significant, and the conformation of the M20 loop is of particular interest. We present receptor-based pharmacophore models-an equivalent of solvent-mapping of binding hotspots-based on ensembles of protein conformations from molecular dynamics simulations of DHFR.NADPH in both the closed and open conformation of the M20 loop. The optimal models identify DHFR inhibitors over druglike non-inhibitors; furthermore, high-affinity inhibitors of E. coli DHFR are preferentially identified over general DHFR inhibitors. As expected, models resulting from simulations with DHFR in the productive conformation with a closed M20 loop have better performance than those from the open-loop simulations. Model performance improves with increased dynamic sampling, indicating that including a greater degree of protein flexibility can enhance the quest for potent inhibitors. This was compared to the limited conformational sampling seen in crystal structures, which were suboptimal for this application.
Journal of Chemical Information and Modeling 47(6):2358-65. · 4.68 Impact Factor
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Michael G. Lerner
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ABSTRACT: Dihydrofolate reductase (DHFR) catalyzes the NADPH-dependent reduction of dihydrofolate to tetrahydrofolate. As the only source of tetrahydrofolate (an important precursor in the biosynthesis of purines, thymidylate, and several amino acids), it has been a long-standing anti-cancer target and a classic system for structure-based drug design (SBDD). Escherichia coli DHFR (ecDHFR) is a canonical system for studying enzyme structure, dynamics, and catalysis. Protein flexibility and dynamics are of utmost importance in understanding the structure and mechanism of DHFR. This has been well investigated computationally and experimentally. The conformation of the M20 loop is particularly important to the catalytic cycle, as its three major conformations (open, closed, and occluded) are known to regulate ligand affinity and turnover. In addition to these static conformational differences, correlated dynamics are known to be of primary importance, showing distinct changes during different stages of the catalytic cycle. The dynamics have been used to explain the effects of distal mutations. We have performed two 10-ns molecular dynamics simulations of the ecDHFR•NADPH complex. We discovered transient, sub-nanosecond, correlated dynamics that correspond to correlations found in the catalytically active state. These dynamics involve both the protein and the cofactor. We found conformational changes that clearly indicate preorganization of the binding site related to folate binding. We have also discovered a potential new allosteric site, supported by extensive computational work as well as by crystallographic and mutagenesis results in the literature. Traditional SBDD techniques focus on static structures. In 1999, Carlson and coworkers introduced the MPS (multiple protein structure) method as a way of incorporating protein flexibility into SBDD. The extreme importance of flexibility for DHFR makes the MPS method particularly appropriate. To improve the method, we developed new techniques for flooding and automatically clustering the solvent-mapping probes used in the procedure. We generated models from simulations starting with the M20 loop in both open and closed conformations. The MPS models preferentially identified high-affinity inhibitors over drug-like non-inhibitors. Ph.D. Biophysics University of Michigan, Horace H. Rackham School of Graduate Studies http://deepblue.lib.umich.edu/bitstream/2027.42/58475/1/mlerner_1.pdf
