ABSTRACT
The 3-dimensional fold of an RNA molecule is largely determined by patterns of intramolecular hydrogen bonds between bases. Predicting the base pairing network from the sequence, also referred to as RNA secondary structure prediction or RNA folding, is a nondeterministic polynomial-time (NP)-complete computational problem. The structure of the molecule is strongly predictive of its functions and biochemical properties, and therefore the ability to accurately predict the structure is a crucial tool for biochemists. Many methods have been proposed to efficiently sample possible secondary structure patterns. Classic approaches employ dynamic programming, and recent studies have explored approaches inspired by evolutionary and machine learning algorithms. This work demonstrates leveraging quantum computing hardware to predict the secondary structure of RNA. A Hamiltonian written in the form of a Binary Quadratic Model (BQM) is derived to drive the system toward maximizing the number of consecutive base pairs while jointly maximizing the average length of the stems. A Quantum Annealer (QA) is compared to a Replica Exchange Monte Carlo (REMC) algorithm programmed with the same objective function, with the QA being shown to be highly competitive at rapidly identifying low energy solutions. The method proposed in this study was compared to three algorithms from literature and, despite its simplicity, was found to be competitive on a test set containing known structures with pseudoknots.
Subject(s)
Computing Methodologies , RNA Folding , Algorithms , Computational Biology/methods , Computers , Nucleic Acid Conformation , Quantum Theory , RNA/geneticsABSTRACT
CRISPR-Cas9 has become a facile genome editing technology, yet the structural and mechanistic features underlying its function are unclear. Here, we perform extensive molecular simulations in an enhanced sampling regime, using a Gaussian-accelerated molecular dynamics (GaMD) methodology, which probes displacements over hundreds of microseconds to milliseconds, to reveal the conformational dynamics of the endonuclease Cas9 during its activation toward catalysis. We disclose the conformational transition of Cas9 from its apo form to the RNA-bound form, suggesting a mechanism for RNA recruitment in which the domain relocations cause the formation of a positively charged cavity for nucleic acid binding. GaMD also reveals the conformation of a catalytically competent Cas9, which is prone for catalysis and whose experimental characterization is still limited. We show that, upon DNA binding, the conformational dynamics of the HNH domain triggers the formation of the active state, explaining how the HNH domain exerts a conformational control domain over DNA cleavage [Sternberg SH et al. (2015) Nature, 527, 110-113]. These results provide atomic-level information on the molecular mechanism of CRISPR-Cas9 that will inspire future experimental investigations aimed at fully clarifying the biophysics of this unique genome editing machinery and at developing new tools for nucleic acid manipulation based on CRISPR-Cas9.
Subject(s)
CRISPR-Cas Systems , Gene Editing , Molecular Dynamics Simulation , Bacterial Proteins/metabolism , Crystallography, X-Ray , Fluorescence Resonance Energy Transfer , Gene Expression Regulation , Normal Distribution , Nucleic Acid Conformation , Nucleic Acids/chemistry , Protein Domains , Proteins/chemistry , RNA/chemistry , RNA, Guide, Kinetoplastida/metabolism , Streptococcus pyogenes/metabolism , ThermodynamicsABSTRACT
Beta-secretase 1 (BACE-1) is an aspartyl protease implicated in the overproduction of ß-amyloid fibrils responsible for Alzheimer disease. The process of ß-amyloid genesis is known to be pH dependent, with an activity peak between solution pH of 3.5 and 5.5. We have studied the pH-dependent dynamics of BACE-1 to better understand the pH dependent mechanism. We have implemented support for graphics processor unit (GPU) accelerated constant pH molecular dynamics within the AMBER molecular dynamics software package and employed this to determine the relative population of different aspartyl dyad protonation states in the pH range of greatest ß-amyloid production, followed by conventional molecular dynamics to explore the differences among the various aspartyl dyad protonation states. We observed a difference in dynamics between double-protonated, mono-protonated, and double-deprotonated states over the known pH range of higher activity. These differences include Tyr 71-aspartyl dyad proximity and active water lifetime. This work indicates that Tyr 71 stabilizes catalytic water in the aspartyl dyad active site, enabling BACE-1 activity.
Subject(s)
Amyloid Precursor Protein Secretases/chemistry , Aspartic Acid Endopeptidases/chemistry , Tyrosine/chemistry , Catalysis , Catalytic Domain , Enzyme Stability , Humans , Hydrogen-Ion Concentration , Models, Molecular , Molecular Dynamics Simulation , Protein Conformation , Software , Water/chemistryABSTRACT
It is important to determine the binding pathways and mechanisms of ligand molecules to target proteins to effectively design therapeutic drugs. Molecular dynamics (MD) is a promising computational tool that allows us to simulate protein-drug binding at an atomistic level. However, the gap between the time scales of current simulations and those of many drug binding processes has limited the usage of conventional MD, which has been reflected in studies of the HIV protease. Here, we have applied a robust enhanced simulation method, Gaussian accelerated molecular dynamics (GaMD), to sample binding pathways of the XK263 ligand and associated protein conformational changes in the HIV protease. During two of 10 independent GaMD simulations performed over 500-2500 ns, the ligand was observed to successfully bind to the protein active site. Although GaMD-derived free energy profiles were not fully converged because of insufficient sampling of the complex system, the simulations still allowed us to identify relatively low-energy intermediate conformational states during binding of the ligand to the HIV protease. Relative to the X-ray crystal structure, the XK263 ligand reached a minimum root-mean-square deviation (RMSD) of 2.26 Å during 2.5 µs of GaMD simulation. In comparison, the ligand RMSD reached a minimum of only â¼5.73 Å during an earlier 14 µs conventional MD simulation. This work highlights the enhanced sampling power of the GaMD approach and demonstrates its wide applicability to studies of drug-receptor interactions for the HIV protease and by extension many other target proteins.
Subject(s)
HIV Protease/chemistry , HIV Protease/metabolism , Catalytic Domain , Crystallography, X-Ray , Ligands , Models, Chemical , Molecular Dynamics Simulation , Protein Conformation , ThermodynamicsABSTRACT
Alchemical free energy (AFE) calculations based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD-based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER. © 2018 Wiley Periodicals, Inc.
Subject(s)
Algorithms , Molecular Dynamics Simulation , Organic Chemicals/chemistry , Thermodynamics , Binding SitesABSTRACT
We report progress in graphics processing unit (GPU)-accelerated molecular dynamics and free energy methods in Amber18. Of particular interest is the development of alchemical free energy algorithms, including free energy perturbation and thermodynamic integration methods with support for nonlinear soft-core potential and parameter interpolation transformation pathways. These methods can be used in conjunction with enhanced sampling techniques such as replica exchange, constant-pH molecular dynamics, and new 12-6-4 potentials for metal ions. Additional performance enhancements have been made that enable appreciable speed-up on GPUs relative to the previous software release.
Subject(s)
Molecular Dynamics Simulation , Software , Algorithms , Computer Graphics , Hydrogen-Ion Concentration , ThermodynamicsABSTRACT
With the drive toward high throughput molecular dynamics (MD) simulations involving ever-greater numbers of simulation replicates run for longer, biologically relevant timescales (microseconds), the need for improved computational methods that facilitate fully automated MD workflows gains more importance. Here we report the development of an automated workflow tool to perform AMBER GPU MD simulations. Our workflow tool capitalizes on the capabilities of the Kepler platform to deliver a flexible, intuitive, and user-friendly environment and the AMBER GPU code for a robust and high-performance simulation engine. Additionally, the workflow tool reduces user input time by automating repetitive processes and facilitates access to GPU clusters, whose high-performance processing power makes simulations of large numerical scale possible. The presented workflow tool facilitates the management and deployment of large sets of MD simulations on heterogeneous computing resources. The workflow tool also performs systematic analysis on the simulation outputs and enhances simulation reproducibility, execution scalability, and MD method development including benchmarking and validation.
Subject(s)
Molecular Dynamics Simulation , Software , Computer Graphics , Electronic Data Processing , Humans , Internet , Principal Component Analysis , Tumor Suppressor Protein p53/metabolism , WorkflowABSTRACT
Cytochrome c oxidase (CcO) is a vital enzyme that catalyzes the reduction of molecular oxygen to water and pumps protons across mitochondrial and bacterial membranes. While proton uptake channels as well as water exit channels have been identified for A-type CcOs, the means by which water and protons exit B-type CcOs remain unclear. In this work, we investigate potential mechanisms for proton transport above the dinuclear center (DNC) in ba3-type CcO of Thermus thermophilus. Using long-time scale, all-atom molecular dynamics (MD) simulations for several relevant protonation states, we identify a potential mechanism for proton transport that involves propionate A of the active site heme a3 and residues Asp372, His376 and Glu126(II), with residue His376 acting as the proton-loading site. The proposed proton transport process involves a rotation of residue His376 and is in line with experimental findings. We also demonstrate how the strength of the salt bridge between residues Arg225 and Asp287 depends on the protonation state and that this salt bridge is unlikely to act as a simple electrostatic gate that prevents proton backflow. We identify two water exit pathways that connect the water pool above the DNC to the outer P-side of the membrane, which can potentially also act as proton exit transport pathways. Importantly, these water exit pathways can be blocked by narrowing the entrance channel between residues Gln151(II) and Arg449/Arg450 or by obstructing the entrance through a conformational change of residue Tyr136, respectively, both of which seem to be affected by protonation of residue His376.
Subject(s)
Electron Transport Complex IV/chemistry , Molecular Dynamics Simulation , Protons , Water/chemistry , Proton PumpsABSTRACT
Combined quantum mechanical molecular mechanics (QM/MM) calculations have become a popular methodology for efficient and accurate description of large molecular systems. In this work we introduce our development of a QM/MM framework based on two well-known codes-NWChem and AMBER. As an initial application area we are focused on excited state properties of small molecules in an aqueous phase using an analogue of the green fluorescent protein (GFP) chromophore as a particular test case. Our approach incorporates high level coupled cluster theory for the analysis of excited states providing a reliable theoretical analysis of effects of an aqueous solvation environment on the photochemical properties of the GFP chromophore. Using a systematic approach, which involves comparison of gas phase and aqueous phase results for different protonation states and conformations, we resolve existing uncertainties regarding the theoretical interpretation of experimental data. We observe that the impact of aqueous environment on charged states generally results in blue shifts of the absorption spectra, but the magnitude of the effect is sensitive to both protonation state and conformation and can be rationalized based on charge movement into the area of higher/lower external electrostatic potentials. At neutral pH levels the experimentally observed absorption signal is most likely coming from the phenol protonated form. Our results also show that the high level electron correlated method is essential for a proper description of excited states of GFP. © 2017 Wiley Periodicals, Inc.
Subject(s)
Density Functional Theory , Green Fluorescent Proteins/chemistry , Quantum Theory , Solutions , Water/chemistryABSTRACT
Mammalian cell surfaces are decorated with a variety of glycan chains that orchestrate development and defense and are exploited by pathogens for cellular attachment and entry. While glycosidic linkages are, in principle, flexible, the conformational space that a given glycan can sample is subject to spatial and electrostatic restrictions imposed by its overall chemical structure. Here, we show how the glycan moiety of the GM1 ganglioside, a branched, monosialylated pentasaccharide that serves as a ligand for various proteins, undergoes differential conformational selection in its interactions with different lectins. Using STD NMR and X-ray crystallography, we found that the innate immune regulator complement Factor H (FH) binds a previously not reported GM1 conformation that is not compatible with the GM1-binding sites of other structurally characterized GM1-binding lectins such as the Simian Virus 40 (SV40) capsid. Molecular dynamics simulations of the free glycan in explicit solvent on the 10 µs timescale reveal that the FH-bound conformation nevertheless corresponds to a minimum in the Gibbs free energy plot. In contrast to the GM1 conformation recognized by SV40, the FH-bound GM1 conformation is associated with poor NOE restraints, explaining how it escaped(1)H-(1)H NOE-restrained modeling in the past and highlighting the necessity for ensemble representations of glycan structures.
Subject(s)
Capsid/chemistry , Complement Factor H/chemistry , G(M1) Ganglioside/analogs & derivatives , Molecular Dynamics Simulation , Simian virus 40/chemistry , Capsid/metabolism , Complement Factor H/metabolism , G(M1) Ganglioside/chemistry , G(M1) Ganglioside/metabolism , Humans , Simian virus 40/metabolismABSTRACT
The expulsion of water from surfaces upon molecular recognition and nonspecific association makes a major contribution to the free energy changes of these processes. In order to facilitate the characterization of water structure and thermodynamics on surfaces, we have incorporated Grid Inhomogeneous Solvation Theory (GIST) into the CPPTRAJ toolset of AmberTools. GIST is a grid-based implementation of Inhomogeneous Fluid Solvation Theory, which analyzes the output from molecular dynamics simulations to map out solvation thermodynamic and structural properties on a high-resolution, three-dimensional grid. The CPPTRAJ implementation, called GIST-cpptraj, has a simple, easy-to-use command line interface, and is open source and freely distributed. We have also developed a set of open-source tools, called GISTPP, which facilitate the analysis of GIST output grids. Tutorials for both GIST-cpptraj and GISTPP can be found at ambermd.org. © 2016 Wiley Periodicals, Inc.
Subject(s)
Molecular Dynamics Simulation , Proteins/chemistry , Thermodynamics , Water/chemistry , Algorithms , Solubility , Surface PropertiesABSTRACT
Broken-symmetry density functional calculations have been performed on the [Fea3, CuB] dinuclear center (DNC) of ba3 cytochrome c oxidase from Thermus thermophilus in the states of [Fea3(3+)-(HO2)(-)-CuB(2+), Tyr237(-)] and [Fea3(4+)[double bond, length as m-dash]O(2-), OH(-)-CuB(2+), Tyr237Ë], using both PW91-D3 and OLYP-D3 functionals. Tyr237 is a special tyrosine cross-linked to His233, a ligand of CuB. The calculations have shown that the DNC in these states strongly favors the protonation of His376, which is above propionate-A, but not of the carboxylate group of propionate-A. The energies of the structures obtained by constrained geometry optimizations along the O-O bond cleavage pathway between [Fea3(3+)-(O-OH)(-)-CuB(2+), Tyr237(-)] and [Fea3(4+)[double bond, length as m-dash]O(2-)HO(-)-CuB(2+), Tyr237Ë] have also been calculated. The transition of [Fea3(3+)-(O-OH)(-)-CuB(2+), Tyr237(-)] â [Fea3(4+)[double bond, length as m-dash]O(2-)HO(-)-CuB(2+), Tyr237Ë] shows a very small barrier, which is less than 3.0/2.0 kcal mol(-1) in PW91-D3/OLYP-D3 calculations. The protonation state of His376 does not affect this O-O cleavage barrier. The rate limiting step of the transition from state A (in which O2 binds to Fea3(2+)) to state PM ([Fea3(4+)[double bond, length as m-dash]O(2-), OH(-)-CuB(2+), Tyr237Ë], where the O-O bond is cleaved) in the catalytic cycle is, therefore, the proton transfer originating from Tyr237 to O-O to form the hydroperoxo [Fea3(3+)-(O-OH)(-)-CuB(2+), Tyr237(-)] state. The importance of His376 in proton uptake and the function of propionate-A/neutral-Asp372 as a gate to prevent the proton from back-flowing to the DNC are also shown.
ABSTRACT
In this manuscript we expand significantly on our earlier communication by investigating the bilayer self-assembly of eight different types of phospholipids in unbiased molecular dynamics (MD) simulations using three widely used all-atom lipid force fields. Irrespective of the underlying force field, the lipids are shown to spontaneously form stable lamellar bilayer structures within 1 microsecond, the majority of which display properties in satisfactory agreement with the experimental data. The lipids self-assemble via the same general mechanism, though at formation rates that differ both between lipid types, force fields and even repeats on the same lipid/force field combination. In addition to zwitterionic phosphatidylcholine (PC) and phosphatidylethanolamine (PE) lipids, anionic phosphatidylserine (PS) and phosphatidylglycerol (PG) lipids are represented. To our knowledge this is the first time bilayer self-assembly of phospholipids with negatively charged head groups is demonstrated in all-atom MD simulations.
Subject(s)
Lipid Bilayers/chemistry , Phospholipids/chemistry , Molecular Dynamics SimulationABSTRACT
Adequate sampling of conformation space remains challenging in atomistic simulations, especially if the solvent is treated explicitly. Implicit-solvent simulations can speed up conformational sampling significantly. We compare the speed of conformational sampling between two commonly used methods of each class: the explicit-solvent particle mesh Ewald (PME) with TIP3P water model and a popular generalized Born (GB) implicit-solvent model, as implemented in the AMBER package. We systematically investigate small (dihedral angle flips in a protein), large (nucleosome tail collapse and DNA unwrapping), and mixed (folding of a miniprotein) conformational changes, with nominal simulation times ranging from nanoseconds to microseconds depending on system size. The speedups in conformational sampling for GB relative to PME simulations, are highly system- and problem-dependent. Where the simulation temperatures for PME and GB are the same, the corresponding speedups are approximately onefold (small conformational changes), between â¼1- and â¼100-fold (large changes), and approximately sevenfold (mixed case). The effects of temperature on speedup and free-energy landscapes, which may differ substantially between the solvent models, are discussed in detail for the case of miniprotein folding. In addition to speeding up conformational sampling, due to algorithmic differences, the implicit solvent model can be computationally faster for small systems or slower for large systems, depending on the number of solute and solvent atoms. For the conformational changes considered here, the combined speedups are approximately twofold, â¼1- to 60-fold, and â¼50-fold, respectively, in the low solvent viscosity regime afforded by the implicit solvent. For all the systems studied, 1) conformational sampling speedup increases as Langevin collision frequency (effective viscosity) decreases; and 2) conformational sampling speedup is mainly due to reduction in solvent viscosity rather than possible differences in free-energy landscapes between the solvent models.
Subject(s)
Algorithms , Molecular Dynamics Simulation , Solvents/chemistry , DNA/chemistry , Kinetics , Nucleosomes/chemistry , Oligopeptides/chemistry , Temperature , ViscosityABSTRACT
While adaptive mutations can bestow new functions on proteins via the introduction or optimization of reactive centers, or other structural changes, a role for the optimization of protein dynamics also seems likely but has been more difficult to evaluate. Antibody (Ab) affinity maturation is an example of adaptive evolution wherein the adaptive mutations may be identified and Abs may be raised to specific targets that facilitate the characterization of protein dynamics. Here, we report the characterization of three affinity matured Abs that evolved from a common germline precursor to bind the chromophoric antigen (Ag), 8-methoxypyrene-1,3,6-trisulfonate (MPTS). In addition to characterizing the sequence, molecular recognition, and structure of each Ab, we characterized the dynamics of each complex by determining their mechanical response to an applied force via three-pulse photon echo peak shift (3PEPS) spectroscopy and deconvoluting the response into elastic, anelastic, and plastic components. We find that for one Ab, affinity maturation was accomplished via the introduction of a single functional group that mediates a direct contact with MPTS and results in a complex with little anelasticity or plasticity. In the other two cases, more mutations were introduced but none directly contact MPTS, and while their effects on structure are subtle, their effects on anelasticity and plasticity are significant, with the level of plasticity correlated with specificity, suggesting that the optimization of protein dynamics may have contributed to affinity maturation. A similar optimization of structure and dynamics may contribute to the evolution of other proteins.
Subject(s)
Antibodies, Monoclonal/chemistry , Antibody Specificity , Evolution, Molecular , Immunoglobulin G/chemistry , Models, Immunological , Models, Molecular , Mutation , Amino Acid Substitution , Animals , Antibodies, Monoclonal/genetics , Antibodies, Monoclonal/metabolism , Antibody Affinity , Binding Sites, Antibody , Fluorescent Dyes/chemistry , Fluorescent Dyes/metabolism , Hybridomas , Hydrogen Bonding , Immunoglobulin G/genetics , Immunoglobulin G/metabolism , Kinetics , Mice , Protein Conformation , Protein Folding , Protein Stability , Pyrenes/antagonists & inhibitors , Pyrenes/chemistry , Pyrenes/metabolismABSTRACT
The generation of bond, angle, and torsion parameters for classical molecular dynamics force fields typically requires fitting parameters such that classical properties such as energies and gradients match precalculated quantum data for structures that scan the value of interest. We present a program, Paramfit, distributed as part of the AmberTools software package that automates and extends this fitting process, allowing for simplified parameter generation for applications ranging from single molecules to entire force fields. Paramfit implements a novel combination of a genetic and simplex algorithm to find the optimal set of parameters that replicate either quantum energy or force data. The program allows for the derivation of multiple parameters simultaneously using significantly fewer quantum calculations than previous methods, and can also fit parameters across multiple molecules with applications to force field development. Paramfit has been applied successfully to systems with a sparse number of structures, and has already proven crucial in the development of the Assisted Model Building with Energy Refinement Lipid14 force field.
ABSTRACT
The implementation and validation of the adaptive buffered force (AdBF) quantum-mechanics/molecular-mechanics (QM/MM) method in two popular packages, CP2K and AMBER are presented. The implementations build on the existing QM/MM functionality in each code, extending it to allow for redefinition of the QM and MM regions during the simulation and reducing QM-MM interface errors by discarding forces near the boundary according to the buffered force-mixing approach. New adaptive thermostats, needed by force-mixing methods, are also implemented. Different variants of the method are benchmarked by simulating the structure of bulk water, water autoprotolysis in the presence of zinc and dimethyl-phosphate hydrolysis using various semiempirical Hamiltonians and density functional theory as the QM model. It is shown that with suitable parameters, based on force convergence tests, the AdBF QM/MM scheme can provide an accurate approximation of the structure in the dynamical QM region matching the corresponding fully QM simulations, as well as reproducing the correct energetics in all cases. Adaptive unbuffered force-mixing and adaptive conventional QM/MM methods also provide reasonable results for some systems, but are more likely to suffer from instabilities and inaccuracies.
Subject(s)
Software , Computer Simulation , Hydrolysis , Molecular Structure , Organophosphorus Compounds/chemistry , Quantum Theory , Thermometers , Water/chemistry , Zinc/chemistryABSTRACT
We present an extensible interface between the AMBER molecular dynamics (MD) software package and electronic structure software packages for quantum mechanical (QM) and mixed QM and classical molecular mechanical (MM) MD simulations within both mechanical and electronic embedding schemes. With this interface, ab initio wave function theory and density functional theory methods, as available in the supported electronic structure software packages, become available for QM/MM MD simulations with AMBER. The interface has been written in a modular fashion that allows straight forward extensions to support additional QM software packages and can easily be ported to other MD software. Data exchange between the MD and QM software is implemented by means of files and system calls or the message passing interface standard. Based on extensive tests, default settings for the supported QM packages are provided such that energy is conserved for typical QM/MM MD simulations in the microcanonical ensemble. Results for the free energy of binding of calcium ions to aspartate in aqueous solution comparing semiempirical and density functional Hamiltonians are shown to demonstrate features of this interface.
Subject(s)
Aspartic Acid/chemistry , Calcium/chemistry , Molecular Dynamics Simulation , Software , Water/chemistry , Cations, Divalent , Hydrogen Bonding , Quantum Theory , Solutions , ThermodynamicsABSTRACT
The Src family of tyrosine kinases (SFKs) regulate numerous aspects of cell growth and differentiation and are under the principal control of the C-terminal Src Kinase (Csk). Csk and SFKs share a modular design with the kinase domain downstream of the N-terminal SH2 and SH3 domains that regulate catalytic function and membrane localization. While the function of interfacial segments in these multidomain kinases are well-investigated, little is known about how surface sites and long-range, allosteric coupling control protein dynamics and catalytic function. The SH2 domain of Csk is an essential component for the down-regulation of all SFKs. A unique feature of the SH2 domain of Csk is the tight turn in place of the canonical CD loop in a surface site far removed from kinase domain interactions. In this study, we used a combination of experimental and computational methods to probe the importance of this difference by constructing a Csk variant with a longer SH2 CD loop to mimic the flexibility found in homologous kinase SH2 domains. Our results indicate that while the fold and function of the isolated domain and the full-length kinase are not affected by loop elongation, native protein dynamics that are essential for efficient catalysis are perturbed. We also identify key motifs and routes through which the distal SH2 site might influence catalysis at the active site. This study underscores the sensitivity of intramolecular signaling and catalysis to native protein dynamics that arise from modest changes in allosteric regions while providing a potential strategy to alter intrinsic activity and signaling modulation.
Subject(s)
src-Family Kinases/metabolism , Amino Acid Sequence , Biocatalysis , Mass Spectrometry , Models, Molecular , Molecular Sequence Data , Nuclear Magnetic Resonance, Biomolecular , Sequence Homology, Amino Acid , src Homology Domains , src-Family Kinases/chemistryABSTRACT
After a summary of the problem of coupling electron and proton transfer to proton pumping in cytochrome c oxidase, we present the results of our earlier and recent density functional theory calculations for the dinuclear Fe-a3-CuB reaction center in this enzyme. A specific catalytic reaction wheel diagram is constructed from the calculations, based on the structures and relative energies of the intermediate states of the reaction cycle. A larger family of tautomers/protonation states is generated compared to our earlier work, and a new lowest-energy pathway is proposed. The entire reaction cycle is calculated for the new smaller model (about 185-190 atoms), and two selected arcs of the wheel are chosen for calculations using a larger model (about 205 atoms). We compare the structural and redox energetics and protonation calculations with available experimental data. The reaction cycle map that we have built is positioned for further improvement and testing against experiment.