The role of metal ions in substrate recognition and stability of concanavalin A: a molecular dynamics study

The binding of carbohydrate substrates to concanavalin A (Canavalia ensiformis agglutinin (ConA)) is essential for its interaction with various glycoproteins. Even though metal ions are known to control the sugar binding ability of legume lectins, the interplay between sugar and metal ion binding to ConA has not been elucidated in a detailed manner at the atomic level. We have carried out long, explicit solvent molecular dynamics simulations for tetrameric, dimeric, and monomeric forms of ConA in both the presence and absence of trimannoside and metal ions. Detailed analyses of these trajectories for various oligomeric forms under different environmental conditions have revealed dynamic conformational changes associated with the demetalization of ConA. We found that demetalization of ConA leads to large conformational changes in the ion binding loop, with some of the loop residues moving as far as 17 Å with respect to their positions in the native trimannoside and metal ion-bound crystal structure. However, the β-sheet core of the protein remains relatively unperturbed. In addition, the high mobility of the ion binding loop results in drifting of the substrates in the absence of bound metal ions. These simulations provide a theoretical rationale for previous experimental observations regarding the abolition of the sugar binding ability upon demetalization. We also found that the amino acid stretches of ConA, having high B-factor values in the crystal structure, show relatively greater mobility in the simulations. The overall agreement of the results of our simulations with various experimental studies suggests that the force field parameters and length of simulations used in our study are adequate to mimic the dynamic structural changes in the ConA protein.     

Investigating the Structure and Dynamics of the PIK3CA Wild-Type and H1047R Oncogenic Mutant

The PIK3CA gene is one of the most frequently mutated oncogenes in human cancers. It encodes p110α, the catalytic subunit of phosphatidylinositol 3-kinase alpha (PI3Kα), which activates signaling cascades leading to cell proliferation, survival, and cell growth. The most frequent mutation in PIK3CA is H1047R, which results in enzymatic overactivation. Understanding how the H1047R mutation causes the enhanced activity of the protein in atomic detail is central to developing mutant-specific therapeutics for cancer. To this end, Surface Plasmon Resonance (SPR) experiments and Molecular Dynamics (MD) simulations were carried out for both wild-type (WT) and H1047R mutant proteins. An expanded positive charge distribution on the membrane binding regions of the mutant with respect to the WT protein is observed through MD simulations, which justifies the increased ability of the mutated protein variant to bind to membranes rich in anionic lipids in our SPR experiments. Our results further support an auto-inhibitory role of the C-terminal tail in the WT protein, which is abolished in the mutant protein due to loss of crucial intermolecular interactions. Moreover, Functional Mode Analysis reveals that the H1047R mutation alters the twisting motion of the N-lobe of the kinase domain with respect to the C-lobe and shifts the position of the conserved P-loop residues in the vicinity of the active site. These findings demonstrate the dynamical and structural differences of the two proteins in atomic detail and propose a mechanism of overactivation for the mutant protein. The results may be further utilized for the design of mutant-specific PI3Kα inhibitors that exploit the altered mutant conformation.     

A Practical Implicit Membrane Potential for NMR Structure Calculations of Membrane Proteins

The highly anisotropic environment of the lipid bilayer membrane imposes significant constraints on the structures and functions of membrane proteins. However, NMR structure calculations typically use a simple repulsive potential that neglects the effects of solvation and electrostatics, because explicit atomic representation of the solvent and lipid molecules is computationally expensive and impractical for routine NMR-restrained calculations that start from completely extended polypeptide templates. Here, we describe the extension of a previously described implicit solvation potential, eefxPot, to include a membrane model for NMR-restrained calculations of membrane protein structures in XPLOR-NIH. The key components of eefxPot are an energy term for solvation free energy that works together with other nonbonded energy functions, a dedicated force field for conformational and nonbonded protein interaction parameters, and a membrane function that modulates the solvation free energy and dielectric screening as a function of the atomic distance from the membrane center, relative to the membrane thickness. Initial results obtained for membrane proteins with structures determined experimentally in lipid bilayer membranes show that eefxPot affords significant improvements in structural quality, accuracy, and precision. Calculations with eefxPot are straightforward to implement and can be used to both fold and refine structures, as well as to run unrestrained molecular-dynamics simulations. The potential is entirely compatible with the full range of experimental restraints measured by various techniques. Overall, it provides a useful and practical way to calculate membrane protein structures in a physically realistic environment.     

Reconstruction and Stability of Secondary Structure Elements in the Context of Protein Structure Prediction

Efficient and accurate reconstruction of secondary structure elements in the context of protein structure prediction is the major focus of this work. We present a novel approach capable of reconstructing α-helices and β-sheets in atomic detail. The method is based on Metropolis Monte Carlo simulations in a force field of empirical potentials that are designed to stabilize secondary structure elements in room-temperature simulations. Particular attention is paid to lateral side-chain interactions in β-sheets and between the turns of α-helices, as well as backbone hydrogen bonding. The force constants are optimized using contrastive divergence, a novel machine learning technique, from a data set of known structures. Using this approach, we demonstrate the applicability of the framework to the problem of reconstructing the overall protein fold for a number of commonly studied small proteins, based on only predicted secondary structure and contact map. For protein G and chymotrypsin inhibitor 2, we are able to reconstruct the secondary structure elements in atomic detail and the overall protein folds with a root mean-square deviation of <10 Å. For cold-shock protein and the SH3 domain, we accurately reproduce the secondary structure elements and the topology of the 5-stranded β-sheets, but not the barrel structure. The importance of high-quality secondary structure and contact map prediction is discussed.     

Backbone relaxation coupled to the ionization of internal groups in proteins: a self-guided Langevin dynamics study

Pathways of structural relaxation triggered by ionization of internal groups in staphylococcal nuclease (SNase) were studied through multiple self-guided Langevin dynamics (SGLD) simulations. Circular dichroism, steady-state Trp fluorescence, and nuclear magnetic resonance spectroscopy have shown previously that variants of SNase with internal Glu, Asp, and Lys at positions 66 or 92, and Arg at position 66, exhibit local reorganization or global unfolding when the internal ionizable group is charged. Except for Arg-66, these internal ionizable groups have unusual pK_a values and are neutral at physiological pH. The structural trends observed in the simulations are in general agreement with experimental observations. The I92D variant, which unfolds globally upon ionization of Asp-92, in simulations often exhibits extensive hydration of the protein core, and sometimes also significant perturbations of the β-barrel. In the crystal structure of the V66R variant, the β1 strand from the β-barrel is domain-swapped; in the simulations, the β1 strand is sometimes partially released. The V66K variant, which in solutions shows reorganization of six residues at the C-terminus of helix α1 and perturbations in the β-barrel structure, exhibits fraying of three residues of helix α1 in one simulation, and perturbations and partial unfolding of three β-strands in a few other simulations. In sharp contrast, very small structural changes were observed in simulations of the wild-type protein. The simulations indicate that charging of internal groups frequently triggers penetration of water into the protein interior. The pK_a values of Asp-92 and Arg-66 calculated with continuum methods on SGLD-relaxed structures reached the normal values in most simulations. Detailed analysis of accuracy and performance of SGLD demonstrates that SGLD outperforms LD in sampling of alternative protein conformations without loss of the accuracy and level of detail characteristic of regular LD.     

Fluctuations and correlations in crystalline protein dynamics: a simulation analysis of staphylococcal nuclease

Understanding collective motions in protein crystals is likely to furnish insight into functional protein dynamics and will improve models for refinement against diffraction data. Here, four 10 ns molecular dynamics simulations of crystalline Staphylococcal nuclease are reported and analyzed in terms of fluctuations and correlations in atomic motion. The simulation-derived fluctuations strongly correlate with, but are slightly higher than, the values derived from the experimental B-factors. Approximately 70% of the atomic fluctuations are due to internal protein motion. For 65% of the protein atoms the internal fluctuations converge on the nanosecond timescale. Convergence is much slower for the elements of the interatomic displacement correlation matrix--of these, >80% converge within 1 ns for interatomic distances less, approximately <6 A, but only 10% for separations approximately =12 A. Those collective motions that converged on the nanosecond timescale involve mostly correlations within the beta-barrel or between alpha-helices of the protein. The R-factor with the experimental x-ray diffuse scattering for the crystal, which is determined by the displacement variance-covariance matrix, decreases to 8% after 10 ns simulation. Both the number of converged correlation matrix elements and the R-factor depend logarithmically on time, consistent with a model in which the number of energy minima sampled depends exponentially on the maximum energy barrier crossed. The logarithmic dependence is also extrapolated to predict a convergence time for the whole variance-covariance matrix of approximately 1 micros.     

Generalized correlation for biomolecular dynamics

Correlated motions in biomolecules are often essential for their function, e.g., allosteric signal transduction or mechanical/thermodynamic energy transport. Because correlated motions in biomolecules remain difficult to access experimentally, molecular dynamics (MD) simulations are particular useful for their analysis. The established method to quantify correlations from MD simulations via calculation of the covariance matrix, however, is restricted to linear correlations and therefore misses part of the correlations in the atomic fluctuations. Herein, we propose a general statistical mechanics approach to detect and quantify any correlated motion from MD trajectories. This generalized correlation measure is contrasted with correlations obtained from covariance matrices for the B1 domain of protein G and T4 lysozyme. The new method successfully quantifies correlations and provides a valuable global overview over the functionally relevant collective motions of lysozyme. In particular, correlated motions of helix 1 together with the two main lobes of lysozyme are detected, which are not seen by the conventional covariance matrix. Overall, the established method misses more than 50% of the correlation. This failure is attributed to both, an interfering and unnecessary dependence on mutual orientations of the atomic fluctuations and, to a lesser extent, attributed to nonlinear correlations. Our generalized correlation measure overcomes these problems and, moreover, allows for an improved understanding of the conformational dynamics by separating linear and nonlinear contributions of the correlation.     

Application of biasing‐potential replica‐exchange simulations for loop modeling and refinement of proteins in explicit solvent

Comparative or homology modeling of a target protein based on sequence similarity to a protein with known structure is widely used to provide structural models of proteins. Depending on the target‐template similarity these model structures may contain regions of limited structural accuracy. In principle, molecular dynamics (MD) simulations can be used to refine protein model structures and also to model loop regions that connect structurally conserved regions but it is limited by the currently accessible simulation time scales. A recently developed biasing potential replica exchange (BP‐REMD) method was used to refine loops and complete decoy protein structures at atomic resolution including explicit solvent. In standard REMD simulations several replicas of a system are run in parallel at different temperatures allowing exchanges at preset time intervals. In a BP‐REMD simulation replicas are controlled by various levels of a biasing potential to reduce the energy barriers associated with peptide backbone dihedral transitions. The method requires much fewer replicas for efficient sampling compared with T‐REMD. Application of the approach to several protein loops indicated improved conformational sampling of backbone dihedral angle of loop residues compared to conventional MD simulations. BP‐REMD refinement simulations on several test cases starting from decoy structures deviating significantly from the native structure resulted in final structures in much closer agreement with experiment compared to conventional MD simulations. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Structural changes induced by substitution of amino acid 129 in the coat protein of Cucumber mosaic virus

Cucumber mosaic virus infection leads to mosaic symptoms on a broad range of crop plants. Mutation at positions 129 in the coat protein of virus causes alterations in the severity of symptoms caused by the viral infection. In our investigation, we performed long term molecular dynamics simulations to elucidate the effect of different amino acid substitutes (infectious and non-infectious) at position 129 in the coat protein of Cucumber mosaic virus using various structural parameters. We found that the contagious mutants displayed more flexibility at loops βE-αEF (129–136) and βF-βG loop (155–163) as compared to the non-infectious and native structures. This specific study at the atomic level yields innovative ideas for designing new therapeutic agents against the pathogen, which would further pave the path for researchers to control this devastating plant virus.     

Residual structure in a peptide fragment of the outer membrane protein X under denaturing conditions: a molecular dynamics study

The Escherichia coli outer membrane protein X (OmpX) contains two polypeptide segments that present nonrandom residual structure in 8 M aqueous urea, whereas the remainder of the protein is in a flexibly disordered conformation (Tafer et al. in Biochemistry 43:860–869, 2004). In the present study, the results of two long-timescale (0.4 μs) unrestrained explicit-solvent molecular dynamics (MD) simulations of a tetradecapeptide representative of one of these two segments in 8 M aqueous urea are reported and analyzed. The two simulations were initiated either from the conformation of the corresponding segment in an NMR model structure of the unfolded protein or from an entirely extended configuration. The sampled conformational ensembles agree qualitatively with the experimentally observed NOEs, but not quantitatively, suggesting that a number of relevant configurations were not visited on the 2 × 0.4 μs timescale. Major conformational transitions occur on the 0.1 μs timescale, and the ensembles corresponding to the two independent simulations overlap only to a limited extent. However, both simulations show in multiple events the reversible formation and disruption of α-helical secondary structure (characteristic of the urea-denatured state) and β-turn secondary structure (characteristic of the native state). Events of helix formation are correlated with the appearance of hydrogen bonds between two side chains (Asp75–Ser78) and of a persistent hydrophobic contact (Trp76–Tyr80). They also evidence a peculiar helix stabilization and N-terminal capping role for a negatively charged residue (Asp75). These features are in good qualitative agreement with the NMR model for the structured state of the corresponding segment in the urea-denatured protein. The analysis of the simulations provides a detailed picture of the structural and dynamic features of the considered peptide at atomic resolution that is of high relevance in the understanding of the OmpX folding process.     

Structure of the K-turn U4 RNA: a combined NMR and SANS study

K-turn motifs are universal RNA structural elements providing a binding platform for proteins in several cellular contexts. Their characteristic is a sharp kink in the phosphate backbone that puts the two helical stems of the protein-bound RNA at an angle of 60°. However, to date no high-resolution structure of a naked K-turn motif is available. Here, we present the first structural investigation at atomic resolution of an unbound K-turn RNA (the spliceosomal U4-Kt RNA) by a combination of NMR and small-angle neutron scattering data. With this study, we wish to address the question whether the K-turn structural motif assumes the sharply kinked conformation in the absence of protein binders and divalent cations. Previous studies have addressed this question by fluorescence resonance energy transfer, biochemical assays and molecular dynamics simulations, suggesting that the K-turn RNAs exist in equilibrium between a kinked conformation, which is competent for protein binding, and a more extended conformation, with the population distribution depending on the concentration of divalent cations. Our data shows that the U4-Kt RNA predominantly assumes the more extended conformation in the absence of proteins and divalent cations. The internal loop region is well structured but adopts a different conformation from the one observed in complex with proteins. Our data suggests that the K-turn consensus sequence does not per se code for the kinked conformation; instead the sharp backbone kink requires to be stabilized by protein binders.     

REMO: A new protocol to refine full atomic protein models from C‐alpha traces by optimizing hydrogen‐bonding networks

Protein structure prediction approaches usually perform modeling simulations based on reduced representation of protein structures. For biological utilizations, it is an important step to construct full atomic models from the reduced structure decoys. Most of the current full atomic model reconstruction procedures have defects which either could not completely remove the steric clashes among backbone atoms or generate final atomic models with worse topology similarity relative to the native structures than the reduced models. In this work, we develop a new protocol, called REMO, to generate full atomic protein models by optimizing the hydrogen‐bonding network with basic fragments matched from a newly constructed backbone isomer library of solved protein structures. The algorithm is benchmarked on 230 nonhomologous proteins with reduced structure decoys generated by I‐TASSER simulations. The results show that REMO has a significant ability to remove steric clashes, and meanwhile retains good topology of the reduced model. The hydrogen‐bonding network of the final models is dramatically improved during the procedure. The REMO algorithm has been exploited in the recent CASP8 experiment which demonstrated significant improvements of the I‐TASSER models in both atomic‐level structural refinement and hydrogen‐bonding network construction. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Utilizing a Dynamical Description of IspH to Aid in the Development of Novel Antimicrobial Drugs

The nonmevalonate pathway is responsible for isoprenoid production in microbes, including H. pylori, M. tuberculosis and P. falciparum, but is nonexistent in humans, thus providing a desirable route for antibacterial and antimalarial drug discovery. We coordinate a structural study of IspH, a [4Fe-4S] protein responsible for converting HMBPP to IPP and DMAPP in the ultimate step in the nonmevalonate pathway. By performing accelerated molecular dynamics simulations on both substrate-free and HMBPP-bound [Fe₄S₄]²⁺ IspH, we elucidate how substrate binding alters the dynamics of the protein. Using principal component analysis, we note that while substrate-free IspH samples various open and closed conformations, the closed conformation observed experimentally for HMBPP-bound IspH is inaccessible in the absence of HMBPP. In contrast, simulations with HMBPP bound are restricted from accessing the open states sampled by the substrate-free simulations. Further investigation of the substrate-free simulations reveals large fluctuations in the HMBPP binding pocket, as well as allosteric pocket openings – both of which are achieved through the hinge motions of the individual domains in IspH. Coupling these findings with solvent mapping and various structural analyses reveals alternative druggable sites that may be exploited in future drug design efforts.     

The role of short-range Cys171-Cys178 disulfide bond in maintaining cutinase active site integrity: A molecular dynamics simulation

Understanding structural determinants in enzyme active site integrity can provide a good knowledge to design efficient novel catalytic machineries. Fusarium solani pisi cutinase with classic triad Ser-His-Asp is a promising enzyme to scrutinize these structural determinants. We performed two MD simulations: one, with the native structure, and the other with the broken Cys171-Cys178 disulfide bond. This disulfide bond stabilizes a turn in active site on which catalytic Asp175 is located. Functionally important H-bonds and atomic fluctuations in catalytic pocket have been changed. We proposed that this disulfide bond within active site can be considered as an important determinant of cutinase active site structural integrity.     

Molecular simulations of protein dynamics: new windows on mechanisms in biology

Recent advances in computer hardware and software have led to the development of increasingly successful molecular simulations of protein structural dynamics that are intrinsic to biological processes. These simulations have resulted in models that increasingly agree with experimental observations, suggest new experiments and provide insights into biological mechanisms. Used in combination with data obtained with sophisticated experimental techniques, simulations are helping us to understand biological complexity at the atomic and molecular levels and are giving promising insights into the genetic, thermodynamic and functional/mechanistic behaviour of biological processes. Here, we highlight some examples of such approaches that illustrate the current state and potential of the field of molecular simulation.     

Coarse-grained normal mode analysis in structural biology

The realization that experimentally observed functional motions of proteins can be predicted by coarse-grained normal mode analysis has renewed interest in applications to structural biology. Notable applications include the prediction of biologically relevant motions of proteins and supramolecular structures driven by their structure-encoded collective dynamics; the refinement of low-resolution structures, including those determined by cryo-electron microscopy; and the identification of conserved dynamic patterns and mechanically key regions within protein families. Additionally, hybrid methods that couple atomic simulations with deformations derived from coarse-grained normal mode analysis are able to sample collective motions beyond the range of conventional molecular dynamics simulations. Such applications have provided great insight into the underlying principles linking protein structures to their dynamics and their dynamics to their functions.     

Submillisecond Elastic Recoil Reveals Molecular Origins of Fibrin Fiber Mechanics

Fibrin fibers form the structural scaffold of blood clots. Thus, their mechanical properties are of central importance to understanding hemostasis and thrombotic disease. Recent studies have revealed that fibrin fibers are elastomeric despite their high degree of molecular ordering. These results have inspired a variety of molecular models for fibrin’s elasticity, ranging from reversible protein unfolding to rubber-like elasticity. An important property that has not been explored is the timescale of elastic recoil, a parameter that is critical for fibrin’s mechanical function and places a temporal constraint on molecular models of fiber elasticity. Using high-frame-rate imaging and atomic force microscopy-based nanomanipulation, we measured the recoil dynamics of individual fibrin fibers and found that the recoil was orders of magnitude faster than anticipated from models involving protein refolding. We also performed steered discrete molecular-dynamics simulations to investigate the molecular origins of the observed recoil. Our results point to the unstructured αC regions of the otherwise structured fibrin molecule as being responsible for the elastic recoil of the fibers.     

Computational protein design and large-scale assessment by I-TASSER structure assembly simulations

Protein design aims at designing new protein molecules of desired structure and functionality. One of the major obstacles to large-scale protein design are the extensive time and manpower requirements for experimental validation of designed sequences. Recent advances in protein structure prediction have provided potentials for an automated assessment of the designed sequences via folding simulations. We present a new protocol for protein design and validation. The sequence space is initially searched by Monte Carlo sampling guided by a public atomic potential, with candidate sequences selected by the clustering of sequence decoys. The designed sequences are then assessed by I-TASSER folding simulations, which generate full-length atomic structural models by the iterative assembly of threading fragments. The protocol is tested on 52 nonhomologous single-domain proteins, with an average sequence identity of 24% between the designed sequences and the native sequences. Despite this low sequence identity, three-dimensional models predicted for the first designed sequence have an RMSD of < 2 Å to the target structure in 62% of cases. This percentage increases to 77% if we consider the three-dimensional models from the top 10 designed sequences. Such a striking consistency between the target structure and the structural prediction from nonhomologous sequences, despite the fact that the design and folding algorithms adopt completely different force fields, indicates that the design algorithm captures the features essential to the global fold of the target. On average, the designed sequences have a free energy that is 0.39 kcal/(mol residue) lower than in the native sequences, potentially affording a greater stability to synthesized target folds.