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Bradbury M.W.,Mount Sinai School of Medicine | Bradbury M.W.,Lake Erie College | Stump D.,Mount Sinai School of Medicine | Guarnieri F.,Virginia Commonwealth University | And 4 more authors.
Journal of Molecular Biology | Year: 2011

Molecular interactions are necessary for proteins to perform their functions. The identification of a putative plasma membrane fatty acid transporter as mitochondrial aspartate aminotransferase (mAsp-AT) indicated that the protein must have a fatty acid binding site. Molecular modeling suggests that such a site exists in the form of a 500-Å 3 hydrophobic cleft on the surface of the molecule and identifies specific amino acid residues that are likely to be important for binding. The modeling and comparison with the cytosolic isoform indicated that two residues (Arg201 and Ala219) were likely to be important to the structure and function of the binding site. These residues were mutated to determine if they were essential to that function. Expression constructs with wild-type or mutated cDNAs were produced for bacteria and eukaryotic cells. Proteins expressed in Escherichia coli were tested for oleate binding affinity, which was decreased in the mutant proteins. 3T3 fibroblasts were transfected with expression constructs for both normal and mutated forms. Plasma membrane expression was documented by indirect immunofluorescence before [ 3H]oleic acid uptake kinetics were assayed. The V max for uptake was significantly increased by overexpression of the wild-type protein but changed little after transfection with mutated proteins, despite their presence on the plasma membrane. The hydrophobic cleft in mAsp-AT can serve as a fatty acid binding site. Specific residues are essential for normal fatty acid binding, without which fatty acid uptake is compromised. These results confirm the function of this protein as a fatty acid binding protein. © 2011 Elsevier Ltd. All rights reserved. Source

Kulp J.L.,U.S. Navy | Kulp J.L.,BioLeap Inc. | Pompliano D.L.,BioLeap Inc. | Guarnieri F.,BioLeap Inc. | And 2 more authors.
Journal of the American Chemical Society | Year: 2011

Simulated annealing of chemical potential located the highest affinity positions of eight organic probes and water on eight static structures of hen egg white lysozyme (HEWL) in various conformational states. In all HELW conformations, a diverse set of organic probes clustered in the known binding site (hot spot). Fragment clusters at other locations were excluded by tightly-bound waters so that only the hot-spot cluster remained in each case. The location of the hot spot was correctly predicted irrespective of the protein conformation and without accounting for protein flexibility during the simulations. Any one of the static structures could have been used to locate the hot spot. A site on a protein where a diversity of organic probes is calculated to cluster, but where water specifically does not bind, identifies a potential small-molecule binding site or protein-protein interaction hot spot. © 2011 American Chemical Society. Source

Boyer R.D.,BioLeap Inc. | Bryan R.L.,BioLeap Inc.
Journal of Physical Chemistry B | Year: 2012

The free energy of solvation can play an important or even dominant role in the accurate prediction of binding affinities and various other molecular-scale interaction phenomena critical to the study of biochemical processes. Many research applications for solvation modeling, such as fragment-based drug design, require algorithms that are both accurate and computationally inexpensive. We have developed a calculation of solvation free energy which runs fast enough for interactive applications, functions for a wide range of chemical species relevant to simulating molecules for biological and pharmaceutical applications, and is readily extended when data for new species becomes available. We have also demonstrated that the incorporation of ab initio data provides necessary access to sufficient reference data for a broad range of chemical features. Our empirical model, including an electrostatic term and a different set of atom types, demonstrates improvements over a previous, solvent-accessible surface area-only model by Wang et al.(1) when fit to identical training sets (mean absolute error of 0.513 kcal/mol versus the 0.538 kcal/mol reported by Wang). The incorporation of ab initio solvation free energies provides a significant increase in the breadth of chemical features for which the model can be applied by introducing classes of compounds for which little or no experimental data is available. The increased breadth and the speed of this solvation model allow for conformational minimization, conformational search, and ligand binding free energy calculations that economically account for the complex interplay of bonded, nonbonded, and solvation free energies as conformations with varying solvent-accessible surfaces are sampled. © 2012 American Chemical Society. Source

Kulp III J.L.,BioLeap Inc. | Blumenthal S.N.,BioLeap Inc. | Wang Q.,BioLeap Inc. | Bryan R.L.,BioLeap Inc. | Guarnieri F.,BioLeap Inc.
Journal of Computer-Aided Molecular Design | Year: 2012

The success of molecular fragment-based design depends critically on the ability to make predictions of binding poses and of affinity ranking for compounds assembled by linking fragments. The SAMPL3 Challenge provides a unique opportunity to evaluate the performance of a state-of-the-art fragment-based design methodology with respect to these requirements. In this article, we present results derived from linking fragments to predict affinity and pose in the SAMPL3 Challenge. The goal is to demonstrate how incorporating different aspects of modeling protein-ligand interactions impact the accuracy of the predictions, including protein dielectric models, charged versus neutral ligands, ΔΔGs solvation energies, and induced conformational stress. The core method is based on annealing of chemical potential in a Grand Canonical Monte Carlo (GC/MC) simulation. By imposing an initially very high chemical potential and then automatically running a sequence of simulations at successively decreasing chemical potentials, the GC/MC simulation efficiently discovers statistical distributions of bound fragment locations and orientations not found reliably without the annealing. This method accounts for configurational entropy, the role of bound water molecules, and results in a prediction of all the locations on the protein that have any affinity for the fragment. Disregarding any of these factors in affinity-rank prediction leads to significantly worse correlation with experimentally-determined free energies of binding. We relate three important conclusions from this challenge as applied to GC/MC: (1) modeling neutral ligands - regardless of the charged state in the active site - produced better affinity ranking than using charged ligands, although, in both cases, the poses were almost exactly overlaid; (2) simulating explicit water molecules in the GC/MC gave better affinity and pose predictions; and (3) applying a AAGs solvation correction further improved the ranking of the neutral ligands. Using the GC/MC method under a variety of parameters in the blinded SAMPL3 Challenge provided important insights to the relevant parameters and boundaries in predicting binding affinities using simulated annealing of chemical potential calculations. © Springer Science+Business Media B.V. 2012. Source

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