169 research outputs found

    MM-GB(PB)SA Calculations of Protein-Ligand Binding Free Energies

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    Optical physic

    The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities

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    Introduction: The molecular mechanics energies combined with the Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods are popular approaches to estimate the free energy of the binding of small ligands to biological macromolecules. They are typically based on molecular dynamics simulations of the receptor-ligand complex and are therefore intermediate in both accuracy and computational effort between empirical scoring and strict alchemical perturbation methods. They have been applied to a large number of systems with varying success. Areas covered: The authors review the use of MM/PBSA and MM/GBSA methods to calculate ligand-binding affinities, with an emphasis on calibration, testing and validation, as well as attempts to improve the methods, rather than on specific applications. Expert opinion: MM/PBSA and MM/GBSA are attractive approaches owing to their modular nature and that they do not require calculations on a training set. They have been used successfully to reproduce and rationalize experimental findings and to improve the results of virtual screening and docking. However, they contain several crude and questionable approximations, for example, the lack of conformational entropy and information about the number and free energy of water molecules in the binding site. Moreover, there are many variants of the method and their performance varies strongly with the tested system. Likewise, most attempts to ameliorate the methods with more accurate approaches, for example, quantum-mechanical calculations, polarizable force fields or improved solvation have deteriorated the results

    Multi-scale Modelling of Allostery in Protein Homodimers

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    Allostery is a form of signalling within biomolecules such that ligand binding to a protein affects its activity at a second site. Allostery was described by early models to be driven by structural changes in the protein. However, more recently there has been increasing evidence that dynamics can contribute to or even drive allostery. The protein studied in this thesis, the Catabolite Activator Protein (CAP), is an allosteric protein homodimer that has been shown to exhibit negatively cooperative binding of the ligand cyclic Adenosine Monophosphate (cAMP) to each of its monomers. Interestingly, CAP is a protein whose allostery is believed to be driven by dynamics rather than a conformational change. In this thesis, a number of coarse grained models are employed to investigate this dynamic allostery in CAP. One family of models, termed Super Coarse Grained (SCG) models explore the global properties of the dynamics of the CAP dimer that cause it to exhibit negatively cooperative allostery. It is shown through these models that changes in protein interactions can provide a basis for changing cooperativity. A second family of coarse grained models called Elastic Network Models (ENM) are studied. These are used to show that adjusting the interactions between specific residues can affect cooperative binding of cAMP to CAP. A number of atomistic approaches are also used to study the cAMP-CAP system, including Molecular Dynamics (MD) and Normal Mode Analysis (NMA). The efficacy of using such approaches for studying the thermodynamics of the allostery in CAP is investigated. The motion observed within the protein is also studied closely to identify potential allosteric pathways. X-ray crystallography and Isothermal Titration Calorimetry (ITC) are finally used to investigate how accurately computational methods can describe the cooperative binding of cAMP to CAP. They are also used to try and determine whether the allostery in CAP can be manipulated experimentally without any observed changes to its structure

    The Normal-Mode Entropy in the MM/GBSA Method: Effect of System Truncation, Buffer Region, and Dielectric Constant

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    We have performed a systematic study of the entropy term in the MM/GBSA (molecular Mechanics combined with generalized Born and surface area solvation) approach to calculate ligand-binding affinities The entropies are calculated by a normal mode analysis of harmonic frequencies from minimized snapshots of molecular dynamics simulations. For computational reasons, these calculations have normally been performed on truncated systems. We have studied the binding of eight inhibitors of blood clotting factor Xa, nine ligands of ferritin, and two ligands of HIV-1 protease and show that removing protein residues with. distances. larger than 8-16 angstrom to the ligand, including a 4 angstrom shell of fixed protein residues and water molecules, change the absolute entropies by 1-5 kJ/mol on average. However, the change is systematic, so relative entropies for different ligands change by only 0.7-1.6 kJ/mol on average. Consequently, entropies from truncated systems give relative binding affinities that are identical to those obtained for the Whole protein within statistical uncertainty (172 kJ/mol). We have also tested to use a distance dependent dielectric constant in the minimization and. frequency calculation (epsilon = 4r), but it typically gives slightly different entropies and poorer binding, affinities. Therefore, we recommend entropies calculated with the smallest truncation radius (8 angstrom) and epsilon =1 Such an approach also gives an improved precision for the calculated binding free energies

    Molecular Mechanics Study of Protein Folding and Protein-Ligand Binding

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    In this dissertation, molecular dynamics (MD) simulations were applied to study the effect of single point mutations on protein folding free energy and the protein-ligand binding in the bifunctional protein dihydrofolate reductase-thymidylate synthase (TS-DHFR) in plasmodium falciparum (pf). The main goal of current computational studies is to have a deeper understanding of factors related to protein folding stability and protein-ligand binding. Chapter two aims to seek solutions for improving the accuracy of predicting changes of folding free energy upon single point mutations in proteins. While the importance of conformational sampling was adequately addressed, the diverse dielectric properties of proteins were also taken into consideration in this study. Through developing a three-dielectric-constant model and broadening conformational sampling, a method for predicting the effect of point mutations on protein folding free energy is described, and factors of affecting the prediction accuracy are addressed in this chapter. The following two chapters focus on the binding process and domain-domain interactions in the bifunctional protein pfDHFR-TS. This protein usually plays as the target of antimalarial drugs, but the drug resistance in this protein has caused lots of problems. In chapter three, the mechanism of the development of drug resistance was investigated. This study indicated that the accumulation of mutations in pfDHFR caused obvious changes of conformation and interactions among residues in the binding pocket, which further weakened the binding affinity between pfDHFR and the inhibitor drug. Furthermore, the high rigidity and significantly weakened communications among key residues in the protein binding pocket were exhibited in the pfDHFR quadruple mutant. The rigid binding site was associated with the failure of conformational reorganization upon the binding of pyrimethamine in the quadruple mutant. Chapter four investigated the effect of the N-terminus in pfDHFR-TS on enzyme activity and domain-domain communications. This is the first computational study that focuses on the full-length pfDHFR-TS dimer. This study provided computational evidence to support that remote mutations could disturb the interactions and conformations of the binding site through disrupting dynamic motions in pfDHFR-TS

    Doctor of Philosophy

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    dissertationAdvances in computer hardware have enabled routine MD simulations of systems with tens of thousands of atoms for up to microseconds (soon milliseconds). The key limiting factor in whether these simulations can advance hypothesis testing in active research is the accuracy of the force fields. In many ways, force fields for RNA are less mature than those for proteins. Yet even the current generation of force fields offers benefits to researchers as we demonstrate with our re-refinement effort on two RNA hairpins. Additionally, our simulation study of the binding of 2-aminobenzimidazole inhibitors to hepatitis C RNA offers a computational perspective on which of the two rather different published structures (one NMR, the other X-ray) is a more reasonable structure for future CADD efforts as well as which free energy methods are suited to these highly charged complexes. Finally, further effort on force field improvement is critical. We demonstrate an effective method to determine quantitative conformational population analysis of small RNAs using enhanced sampling methods. These efforts are allowing us to uncover force field pathologies and quickly test new modifications. In summary, this research serves to strengthen communication between experimental and theoretical methods in order produce mutual benefit
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