93 research outputs found

    CHARMM-GUI Ligand Binder for Absolute Binding Free Energy Calculations and Its Application

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    Advanced free energy perturbation molecular dynamics (FEP/MD) simulation methods are available to accurately calculate absolute binding free energies of protein-ligand complexes. However, these methods rely on several sophisticated command scripts implementing various biasing energy restraints to enhance the convergence of the FEP/MD calculations, which must all be handled properly to yield correct results. Here, we present a user-friendly web interface, CHARMM-GUI Ligand Binder (http://www.charmm-gui.org/input/gbinding), to provide standardized CHARMM input files for calculations of absolute binding free energies using the FEP/MD simulations. A number of features are implemented to conveniently setup the FEP/MD simulations in highly customizable manners, thereby permitting an accelerated throughput of this important class of computations while decreasing the possibility of human errors. The interface and a series of input files generated by the interface are tested with illustrative calculations of absolute binding free energies of three non-polar aromatic ligands to the L99A mutant of T4 lysozyme and three FK506-related ligands to FKBP12. Statistical errors within individual calculations are found to be small (~1 kcal/mol), and the calculated binding free energies generally agree well with the experimental measurements and the previous computational studies (within ~2 kcal/mol). CHARMM-GUI Ligand Binder provides a convenient and reliable way to setup the ligand binding free energy calculations and can be applicable to pharmaceutically important protein-ligand systems

    Modeling the Binding of Neurotransmitter Transporter Inhibitors with Molecular Dynamics and Free Energy Calculations

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    The monoamine transporter (MAT) proteins responsible for the reuptake of the neurotransmitter substrates, dopamine, serotonin, and norepinephrine, are drug targets for the treatment of psychiatric disorders including depression, anxiety, and attention deficit hyperactivity disorder. Small molecules that inhibit these proteins can serve as useful therapeutic agents. However, some dopamine transporter (DAT) inhibitors, such as cocaine and methamphetamine, are highly addictive and abusable. Efforts have been made to develop small molecules that will inhibit the transporters and elucidate specific binding site interactions. This work provides knowledge of molecular interactions associated with MAT inhibitors by offering an atomistic perspective that can guide designs of new pharmacotherapeutics with enhanced activity. The work described herein evaluates intermolecular interactions using computational methods to reveal the mechanistic detail of inhibitors binding in the DAT. Because cocaine recognizes the extracellular-facing or outward-facing (OF) DAT conformation and benztropine recognizes the intracellular-facing or inward-facing (IF) conformation, it was postulated that behaviorally “typical” (abusable, locomotor psychostimulant) inhibitors stabilize the OF DAT and “atypical” (little or no abuse potential) inhibitors favor IF DAT. Indeed, behaviorally-atypical cocaine analogs have now been shown to prefer the OF DAT conformation. Specifically, the binding interactions of two cocaine analogs, LX10 and LX11, were studied in the OF DAT using molecular dynamics simulations. LX11 was able to interact with residues of transmembrane helix 8 and bind in a fashion that allowed for hydration of the primary binding site (S1) from the intracellular space, thus impacting the intracellular interaction network capable of regulating conformational transitions in DAT. Additionally, a novel serotonin transporter (SERT) inhibitor previously discovered through virtual screening at the SERT secondary binding site (S2) was studied. Intermolecular interactions between SM11 and SERT have been assessed using binding free energy calculations to predict the ligand-binding site and optimize ligand-binding interactions. Results indicate the addition of atoms to the 4-chlorobenzyl moiety were most energetically favorable. The simulations carried out in DAT and SERT were supported by experimental results. Furthermore, the co-crystal structures of DAT and SERT share similar ligand-binding interactions with the homology models used in this study

    Application of Binding Free Energy Calculations to Prediction of Binding Modes and Affinities of MDM2 and MDMX Inhibitors

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    Molecular docking is widely used to obtain binding modes and binding affinities of a molecule to a given target protein. Despite considerable efforts, however, prediction of both properties by docking remains challenging mainly due to protein’s structural flexibility and inaccuracy of scoring functions. Here, an integrated approach has been developed to improve the accuracy of binding mode and affinity prediction, and tested for small molecule MDM2 and MDMX antagonists. In this approach, initial candidate models selected from docking are subjected to equilibration MD simulations to further filter the models. Free energy perturbation molecular dynamics (FEP/MD) simulations are then applied to the filtered ligand models to enhance the ability in predicting the near-native ligand conformation. The calculated binding free energies for MDM2 complexes are overestimated compared to experimental measurements mainly due to the difficulties in sampling highly flexible apo-MDM2. Nonetheless, the FEP/MD binding free energy calculations are more promising for discriminating binders from nonbinders than docking scores. In particular, the comparison between the MDM2 and MDMX results suggests that apo-MDMX has lower flexibility than apo-MDM2. In addition, the FEP/MD calculations provide detailed information on the different energetic contributions to ligand binding, leading to a better understanding of the sensitivity and specificity of protein-ligand interactions

    Mechanism of homodimeric cytokine receptor activation and dysregulation by oncogenic mutations

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    Homodimeric class I cytokine receptors are assumed to exist as preformed dimers that are activated by ligand-induced conformational changes. We quantified the dimerization of three prototypic class I cytokine receptors in the plasma membrane of living cells by single-molecule fluorescence microscopy. Spatial and spatiotemporal correlation of individual receptor subunits showed ligand-induced dimerization and revealed that the associated Janus kinase 2 (JAK2) dimerizes through its pseudokinase domain. Oncogenic receptor and hyperactive JAK2 mutants promoted ligand-independent dimerization, highlighting the formation of receptor dimers as the switch responsible for signal activation. Atomistic modeling and molecular dynamics simulations based on a detailed energetic analysis of the interactions involved in dimerization yielded a mechanistic blueprint for homodimeric class I cytokine receptor activation and its dysregulation by individual mutations.</p

    Computational Studies of Glycan Conformations in Glycoproteins

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    N-glycans refer to oligosaccharide chains covalently attached to the side chain of asparagine (Asn) residues, and the majority of proteins synthesized in the endoplasmic reticulum (ER) are N-glycosylated. N-glycans can modulate the structural properties of proteins due to their close proximity to their parent proteins and their interactions between the glycan and the protein surface residues. In addition, N-glycans provide specific regions of recognition for cellular and molecular recognition. Despite their biological importance, the structural understanding of glycans and the impact of glycosylation to glycan or protein structure are lacking. I have explored the conformational freedom of glycans and their conformational preferences in different environments using structural databases and computer simulations. First, I have developed an algorithm to reliably annotate a given atomic structure of glycans. This algorithm is important because many glycan molecules in the crystal structure database are misannotated or contain errors. Using the algorithm, a database of glycans found in the PDB is constructed and available to the public. Second, the impact of glycosylation on the glycan conformation has been examined. Contrary to the common belief that the glycan conformations are independent to the protein structure, it appears that the protein structure can significantly affect the glycan structure upon glycosylation. This observation is significant because it may provide insight into protein-glycan interaction and opens up the possibility of a template-based glycan modeling approach. Third, the differences in conformational preference between glycans in solution and in glycoproteins has been examined. Using molecular dynamics (MD) simulations, the conformational preference of N-glycan pentassacharide in solution is exhaustively studied. Surprisingly, the conformational distribution is dominated by a single major conformational state and several minor conformational states. The dominant conformational state adopts a more extended conformation, thus it appears that entropy plays an important role in determining the conformational state. On the other hand, in glycoproteins, glycans can interact with surrounding protein side chains and, as a result, several conformational states are more equally populated. Based on these observations, a protocol is proposed for modeling the glycan portion of a known protein structure. It is typically more managable to acquire an atomic resolution structure or aglycoprotein (glycoprotein without glycan). In addition, the glycoform and the glycosylation site can be identified independently by mass spectrometry or NMR. The proposed modeling protocol assumes the glycosylation site, glycoform, and aglycoprotein structure are already known, and builds glycan structure models on top of the known aglycoprotein structure. The performance of the modeling protocol is greatly improved by using appropriate template structures. This protocol can be used to generate the initial model for MD simulations or refinement of low resolution models from experiments (small angle X-ray scattering and electron microscopy)
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