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Protein Design is a Key Factor for Subunit-subunit Association
Abstract
Fundamental questions about role of the quaternary structures are addressed by using a statistical mechanics off-lattice model of a dimer protein. The model, in spite of its simplicity, captures key features of the monomer-monomer interactions revealed by atomic force experiments. Force curves during association and dissociation processes are characterized by sudden jumps followed by smooth behavior and form hysteresis loops. Furthermore, the process is reversible in a finite range of temperature stabilizing the dimer, and the width of the hysteresis loop increases as the design procedure improves: i.e., stabilizes the dimer more. It is shown that, in the interface between the two monomeric subunits, the design procedure naturally favors those amino acids whose mutual interaction is stronger.
... Tyrosine nitration in proteins does not occur randomly. Most proteins contain tyrosine residues (natural abundance: 3.2%) [24], and tyrosine is often surface-exposed in proteins (only 15% of tyrosine residues are at least 95% buried) and should be easily nitrated [1,25]. However, not all exposed tyrosine residues and not all proteins are nitrated. ...
Models for exploring tyrosine nitration in proteins have been created based on 3D structural features of 20 proteins for which high-resolution X-ray crystallographic or NMR data are available and for which nitration of 35 total tyrosines has been experimentally proven under oxidative stress. Factors suggested in previous work to enhance nitration were examined with quantitative structural descriptors. The role of neighboring acidic and basic residues is complex: for the majority of tyrosines that are nitrated the distance to the heteroatom of the closest charged side chain corresponds to the distance needed for suspected nitrating species to form hydrogen bond bridges between the tyrosine and that charged amino acid. This suggests that such bridges play a very important role in tyrosine nitration. Nitration is generally hindered for tyrosines that are buried and for those tyrosines for which there is insufficient space for the nitro group. For in vitro nitration, closed environments with nearby heteroatoms or unsaturated centers that can stabilize radicals are somewhat favored. Four quantitative structure-based models, depending on the conditions of nitration, have been developed for predicting site-specific tyrosine nitration. The best model, relevant for both in vitro and in vivo cases, predicts 30 of 35 tyrosine nitrations (positive predictive value) and has a sensitivity of 60/71 (11 false positives).
The free radical-mediated damage to proteins results in the modification of amino acid residues, cross-linking of side chains and fragmentation. L-tyrosine and protein bound tyrosine are prone to attack by various mediators and reactive nitrogen intermediates to form 3-nitrotyrosine (3-NT). Activated macrophages produce superoxide (O2(._)) and NO, which are converted to peroxynitrite (ONO2(_)). 3-NT formation is also catalyzed by a class of peroxidases utilizing nitrite and hydrogen peroxide as substrates. Evidence supports the formation of 3-NT in vivo in diverse pathologic conditions and 3-NT is thought to be a relatively specific marker of oxidative damage mediated by peroxynitrite. Free/protein-bound tyrosines are attacked by various RNS, including peroxynitrite, to form free/protein-bound 3-NT, which may provide insight into the etiopathogenesis of autoimmune conditions. The formation of nitrotyrosine represents a specific peroxynitrite-mediated protein modification; thus, detection of nitrotyrosine in proteins is considered as a biomarker for endogenous peroxynitrite activity. The peroxynitrite-driven oxidation and nitration of biomolecules may lead to autoimmune diseases such as systemic lupus. The subsequent release of altered proteins may enable them to act as antigen-inducing antibodies against self-proteins. Hence, tyrosine nitrated proteins can act as neoantigens and lead to the generation of autoantibodies against self proteins in various autoimmune disorders.
Including solvation effects (in the Poisson−Boltzmann continuum solvent approximation) we report ab initio quantum mechanical calculations (HF/6-31G**) on the conformational energies for adding alanine to the amino or carboxyl terminus of a polyalanine α-helix as a function of helix length N. We find that extending the length of an α-helix increasingly favors the α-helix conformation for adding an additional residue, even in hydrophobic environment. Thus, α-helix formation is a cooperative process. Using charges from the QM calculations, we find that the electrostatic energy dominates the QM results, showing that this increasing preference for α-helix formation results from dipole−dipole interaction within the α-helix. These results provide quantitative preferences and insight into the conformational preferences and kinetics of protein folding.
Protein tyrosine nitration (PTN) is a post-translational modification of proteins associated with a number of inflammatory diseases. While PTN is rather selective (not all proteins are modified and within a protein, only certain tyrosines are subject to nitration), no consensus sequence has been identified. Since PTN is a low-abundance post-translational modification, it is necessary to enrich modified proteins and/or to detect them with high selectivity and sensitivity. Until now this has been mostly accomplished with anti-nitrotyrosine antibodies in combination with two-dimensional gel electrophoresis and mass spectrometry. We propose a chemical labeling approach designed to allow enrichment of tyrosine-nitrated peptides independent of the sequence context, which is a potential shortcoming of antibody-based approaches. In this procedure, all amines are blocked by acetylation followed by conversion of nitrotyrosine to aminotyrosine and biotinylation of aminotyrosine. The entire reaction sequence is performed in a single buffer with no need for sample cleanup or pH changes thereby reducing sample loss. Free biotin is subsequently removed with a strong cation exchanger, the labeled peptides are enriched on an immobilized avidin column and the enriched peptides analyzed by LC-MS/MS. As a proof of concept, this method was successfully applied to the enrichment of tyrosine-nitrated angiotensin II in a tryptic digest of bovine serum albumin (BSA). The approach presented here is well adapted to peptide analysis, for instance in shotgun proteomics.
Protein tyrosine nitration (PTN) is a post-translational modification occurring under the action of a nitrating agent. Tyrosine is modified in the 3-position of the phenolic ring through the addition of a nitro group (NO2). In the present article, we review the main nitration reactions and elucidate why nitration is not a random chemical process. The particular physical and chemical properties of 3-nitrotyrosine (e.g., pKa, spectrophotometric properties, reduction to aminotyrosine) will be discussed, and the biological consequences of PTN (e.g., modification of enzymatic activity, sensitivity to proteolytic degradation, impact on protein phosphorylation, immunogenicity and implication in disease) will be reviewed. Recent data indicate the possibility of an in vivo denitration process, which will be discussed with respect to the different reaction mechanisms that have been proposed. The second part of this review article focuses on analytical methods to determine this post-translational modification in complex proteomes, which remains a major challenge.
Stable isotope labeling (SIL) in combination with liquid chromatography-mass spectrometry is one of the most widely used quantitative analytical methods due to its sensitivity and ability to deal with extremely complex biological samples. However, SIL methods for metabolite analysis are still often limited in terms of multiplexing, the chromatographic properties of the derivatized analytes, or their ionization efficiency. Here we describe a new family of reagents for the SIL of primary amine-containing compounds based on pentafluorophenyl-activated esters of 13C-containing poly(ethylene glycol) chains (PEG) that addresses these shortcomings. A sequential buildup of the PEG chain allowed the introduction of various numbers of 13C atoms opening extended multiplexing possibilities. The PEG derivatives of rather hydrophilic molecules such as amino acids and glutathione were successfully retained on a standard C18 reversed-phase column, and their identification was facilitated based on m/z values and retention times using extracted ion chromatograms. The mass increase due to PEG derivatization moved low molecular weight metabolite signals out of the often noisy, low m/z region of the mass spectra, which resulted in enhanced overall sensitivity and selectivity. Furthermore, elution at increased retention times resulted in efficient electrospray ionization due to the higher acetonitrile content in the mobile phase. The method was successfully applied to the quantification of intracellular amino acids and glutathione in a cellular model of human lung epithelium exposed to cigarette smoke-induced oxidative stress. It was shown that the concentration of most amino acids increased upon exposure of A549 cells to gas-phase cigarette smoke with respect to air control and cigarette smoke extract and that free thiol-containing species (e.g., glutathione) decreased although disulfide bond formation was not increased. These labeling reagents should also prove useful for the labeling of peptides and other compounds containing primary amine functionalities.
The introduction of functional imaging tools and techniques that operate at molecular-length scales has provided investigators with unique approaches to characterizing biomolecular structure and function relationships. Recent advances in the field of scanning probe techniques and, in particular, atomic force microscopy have yielded tantalizing insights into the dynamics of protein self-assembly and the mechanics of protein unfolding.
For many protein multimers, association and dissociation reactions fail to reach the same end point; there is hysteresis preventing one and/or the other reaction from equilibrating. We have studied in vitro assembly of dimeric hepatitis B virus (HBV) capsid protein and dissociation of the resulting T = 4 icosahedral capsids. Empty HBV capsids composed of 120 capsid protein dimers were more resistant to dissociation by dilution or denaturants than anticipated from assembly experiments. Using intrinsic fluorescence, circular dichroism, and size exclusion chromatography, we showed that denaturants dissociate the HBV capsids without unfolding the capsid protein; unfolding of dimer only occurred at higher denaturant concentrations. The apparent energy of interaction between dimers measured in dissociation experiments was much stronger than when measured in assembly studies. Unlike assembly, capsid dissociation did not have the concentration dependence expected for a 120-subunit complex; consequently the apparent association energy systematically varied with reactant concentration. These data are evidence of hysteresis for HBV capsid dissociation. Simulations of capsid assembly and dissociation reactions recapitulate and provide an explanation for the observed behavior; these results are also applicable to oligomeric and multidomain proteins. In our calculations, we find that dissociation is impeded by temporally elevated concentrations of intermediates; this has the paradoxical effect of favoring re-assembly of those intermediates despite the global trend toward dissociation. Hysteresis masks all but the most dramatic decreases in contact energy. In contrast, assembly reactions rapidly approach equilibrium. These results provide the first rigorous explanation of how virus capsids can remain intact under extreme conditions but are still capable of "breathing." A biological implication of enhanced stability is that a triggering event may be required to initiate virus uncoating.
Understanding the forces and dynamics of insulin dissociation is critical for devising formulations for the treatment of insulin-dependent diabetes. In earlier work, we applied AFM-based force spectroscopy to covalently tethered and oriented insulin monomers to assess the effect of molecular orientation on insulin-insulin binding forces. We report here on steered molecular dynamics simulations of the insulin dissociation force spectroscopy experiment. Consistent with our experiments, our simulation results suggest that insulin dimer dissociation occurs near the limit of extensibility of the B-chain. We have also found that the forced dissociation of the insulin dimer is a rate-dependent process, involving significant conformational changes to the monomer(s). The insulin dimer dissociation pathway also depends on the relative strength of the inter-monomer interactions across the antiparallel beta-sheet interface and the intra-monomer interactions of residues A1 and A30 with the insulin B-chain. Our simulation results strongly support the design of bioactive insulin analogues that involves altering hydrogen bonding and hydrophobic interactions across the beta-sheet dimer interface.
Elastin is a structural insoluble protein which gives elasticity to tissues and organs. Although its hydrophobic and highly cross-linked nature makes it a very durable polymer, degradation of elastin in relation with several pathological conditions, such as pulmonary emphysema, has been documented. Since different enzymes may be involved in elastolysis, it is of interest to determine which enzyme is responsible for the degradative effects observed in a certain disease. The aim of this work was to study elastin degradation by proteases from different families (serine, cysteine, and metalloproteases) using liquid chromatography coupled to mass spectrometry to characterize the elastin-derived peptides. Incubation of insoluble human elastin with different elastases revealed that, indeed, each protease degrades elastin in a preferential way giving rise to specific peptide patterns. This opens the possibility of using a given set of peptides as biomarkers for disease-related elastolysis.
N-hydroxysuccinimide (NHS) esters are derivatizing agents that target primary amine groups. However, even a small molar excess of NHS may lead to acylation of hydroxyl-containing amino acids as a side reaction. We report a straightforward method for the selective removal of ester-linked acyl groups after NHS ester-mediated acylation of peptides and proteins. It is based on incubation in a boiling water bath and does not require a change in pH or the addition of chemicals. It is therefore particularly suited for proteomics samples that are often small in volume and contain low amounts of peptides. The method was optimized and evaluated with two peptides and one protein that were acetylated at a high excess of NHS-acetate. While the large molar excess resulted in complete acylation of all primary amines, hydroxyl-containing amino acids were shown to react as well. By incubating the peptide or protein solutions in a boiling water bath, acetyl-ester bonds were hydrolyzed, whereas acetyl-amide bonds remained stable. The reaction was also performed in 6 M guanidine-HCl, which prevented protein precipitation. In conclusion, the present method allows the selective acylation of primary amines by NHS esters and constitutes a valuable alternative to the treatment with hydroxylamine under alkaline conditions.
Implantable biochips have the potential to be used in a wide range of applications such as medicine (for rapid diagnostics), surveillance (for detection and monitoring of environmental biological and chemical concentrations) and in defence and security (wearable intelligence for body condition monitoring). In this paper, we introduce an algorithm for use in these implantable biochips. This algorithm will be able to predict a protein's new structural conformation, which will be of use in in-vivo monitoring and diagnosis of abnormal biological events. The algorithm could also be used for drug discovery and design, which will be of use in the defence and security field.
These lectures will address two questions. Is there a simple variational principle underlying the existence of secondary motifs in the native state of proteins? Is there a general approach which can qualitatively capture the salient features of the folding process and which may be useful for interpreting and guiding experiments? Here, we present three different approaches to the first question, which demonstrate the key role played by the topology of the native state of proteins. The second question pertaining to the folding dynamics of proteins remains a challenging problem -- a detailed description capturing the interactions between amino acids among each other and with the solvent is a daunting task. We address this issue building on the lessons learned in tackling the first question and apply the resulting method to the folding of various proteins including HIV protease and membrane proteins. The results that will be presented open a fascinating perspective: the two questions appear to be intimately related. The variety of results reported here all provide evidence in favour of the special criteria adopted by nature in the selection of viable protein folds, ranging from optimal compactness to maximum dynamical and geometrical accessibility of the native states.
Drug resistance to HIV-1 Protease involves accumulation of multiple mutations in the protein. Here we investigate the role of these mutations by using molecular dynamics simulations which exploit the influence of the native-state topology in the folding process. Our calculations show that sites contributing to phenotypic resistance of FDA-approved drugs are among the most sensitive positions for the stability of partially folded states and should play a relevant role in the folding process. Furthermore, associations between amino acid sites mutating under drug treatment are shown to be statistically correlated. The striking correlation between clinical data and our calculations suggest a novel approach to the design of drugs tailored to bind regions crucial not only for protein function but also for folding.
The standard theory of fluctuations in thermodynamic variables in various ensembles is generalized to nonthermodynamic variables: e.g., the mean-square fluctuations of the kinetic energy K in a classical microcanonical ensemble at fixed energy E is given, for large systems, by 〈(δK)2〉/〈K〉=T[1-3/2C), where T is the temperature (corresponding to the energy E) and C is the specific heat per particle (in units of Boltzmann's constant). The general results may be expressed in terms of the asymptotic behavior of the Ursell functions in various ensembles. Applications are made to molecular dynamic computations where time averages correspond (via ergodicity) to phase averages in an ensemble with fixed energy and momentum. The results are also useful for time-dependent correlations.
Second and revised edition
Understanding Molecular Simulation: From Algorithms to Applications explains the physics behind the "recipes" of molecular simulation for materials science. Computer simulators are continuously confronted with questions concerning the choice of a particular technique for a given application. A wide variety of tools exist, so the choice of technique requires a good understanding of the basic principles. More importantly, such understanding may greatly improve the efficiency of a simulation program. The implementation of simulation methods is illustrated in pseudocodes and their practical use in the case studies used in the text.
Since the first edition only five years ago, the simulation world has changed significantly -- current techniques have matured and new ones have appeared. This new edition deals with these new developments; in particular, there are sections on:
· Transition path sampling and diffusive barrier crossing to simulaterare events
· Dissipative particle dynamic as a course-grained simulation technique
· Novel schemes to compute the long-ranged forces
· Hamiltonian and non-Hamiltonian dynamics in the context constant-temperature and constant-pressure molecular dynamics simulations
· Multiple-time step algorithms as an alternative for constraints
· Defects in solids
· The pruned-enriched Rosenbluth sampling, recoil-growth, and concerted rotations for complex molecules
· Parallel tempering for glassy Hamiltonians
Examples are included that highlight current applications and the codes of case studies are available on the World Wide Web. Several new examples have been added since the first edition to illustrate recent applications. Questions are included in this new edition. No prior knowledge of computer simulation is assumed.
A numerical algorithm integrating the 3N Cartesian equations of motion of a system of N points subject to holonomic constraints is formulated. The relations of constraint remain perfectly fulfilled at each step of the trajectory despite the approximate character of numerical integration. The method is applied to a molecular dynamics simulation of a liquid of 64 n-butane molecules and compared to a simulation using generalized coordinates. The method should be useful for molecular dynamics calculations on large molecules with internal degrees of freedom.
A lattice model of protein folding is developed to distinguish between amino acid sequences that do and do not fold into unique conformations. Although Monte Carlo simulations provide insights into the long-time processes involved in protein folding, these simulations cannot systematically chart the conformational energy surface that enables folding. By assuming that protein folding occurs after chain collapse, a kinetic map of important pathways on this surface is constructed through the use of an analytical theory of probability flow. Convergent kinetic pathways, or "folding funnels," guide folding to a unique, stable, native conformation. Solution of the probability flow equations is facilitated by limiting treatment to diffusion between geometrically similar collapsed conformers. Similarity is measured in terms of a reconfigurational distance. Two specific amino acid sequences are deemed foldable and nonfoldable because one gives rise to a single, large folding funnel leading to a native conformation and the other has multiple pathways leading to several stable conformers. Monte Carlo simulations demonstrate that folding funnel calculations accurately predict the fact of and the pathways involved in folding-specific sequences. The existence of folding funnels for specific sequences suggests that geometrically related families of stable, collapsed conformers fulfill kinetic and thermodynamic requirements of protein folding.
Experimental information on the structure and dynamics of molten globules gives estimates for the energy landscape's characteristics for folding highly helical proteins, when supplemented by a theory of the helix-coil transition in collapsed heteropolymers. A law of corresponding states relating simulations on small lattice models to real proteins possessing many more degrees of freedom results. This correspondence reveals parallels between "minimalist" lattice results and recent experimental results for the degree of native character of the folding transition state and molten globule and also pinpoints the needs of further experiments.
Interaction forces between single strands of DNA were measured with the atomic force microscope by a procedure in which DNA
oligonucleotides were covalently attached to a spherical probe and surface. Adhesive forces measured between complementary
20-base strands fell into three distinct distributions centered at 1.52, 1.11, and 0.83 nano-newtons, which are associated
with the rupture of the interchain interaction between a single pair of molecules involving 20, 16, and 12 base pairs, respectively.
When a third long DNA molecule was coupled between complementary surfaces, both intra- and interchain forces were observed.
The intrachain interaction resulting from the molecule's elasticity manifested itself as a long-range cohesive force.
A methodology has been developed for the study of molecular recognition at the level of single events and for the localization of sites on biosurfaces, in combining force microscopy with molecular recognition by specific ligands. For this goal, a sensor was designed by covalently linking an antibody (anti-human serum albumin, polyclonal) via a flexible spacer to the tip of a force microscope. This sensor permitted detection of single antibody-antigen recognition events by force signals of unique shape with an unbinding force of 244 +/- 22 pN. Analysis revealed that observed unbinding forces originate from the dissociation of individual Fab fragments from a human serum albumin molecule. The two Fab fragments of the antibody were found to bind independently and with equal probability. The flexible linkage provided the antibody with a 6-nm dynamical reach for binding, rendering binding probability high, 0.5 for encounter times of 60 ms. This permitted fast and reliable detection of antigenic sites during lateral scans with a positional accuracy of 1.5 nm. It is indicated that this methodology has promise for characterizing rate constants and kinetics of molecular recognition complexes and for molecular mapping of biosurfaces such as membranes.
The energy landscape theory of protein folding is a statistical description of a protein's potential surface. It assumes that folding occurs through organizing an ensemble of structures rather than through only a few uniquely defined structural intermediates. It suggests that the most realistic model of a protein is a minimally frustrated heteropolymer with a rugged funnel-like landscape biased toward the native structure. This statistical description has been developed using tools from the statistical mechanics of disordered systems, polymers, and phase transitions of finite systems. We review here its analytical background and contrast the phenomena in homopolymers, random heteropolymers, and protein-like heteropolymers that are kinetically and thermodynamically capable of folding. The connection between these statistical concepts and the results of minimalist models used in computer simulations is discussed. The review concludes with a brief discussion of how the theory helps in the interpretation of results from fast folding experiments and in the practical task of protein structure prediction.
Retroviral protease (PR) from the human immunodeficiency virus type 1 (HIV-1) was identified over a decade ago as a potential target for structure-based drug design. This effort was very successful. Four drugs are already approved, and others are undergoing clinical trials. The techniques utilized in this remarkable example of structure-assisted drug design included crystallography, NMR, computational studies, and advanced chemical synthesis. The development of these drugs is discussed in detail. Other approaches to designing HIV-1 PR inhibitors, based on the concepts of symmetry and on the replacement of a water molecule that had been found tetrahedrally coordinated between the enzyme and the inhibitors, are also discussed. The emergence of drug-induced mutations of HIV-1 PR leads to rapid loss of potency of the existing drugs and to the need to continue the development process. The structural basis of drug resistance and the ways of overcoming this phenomenon are mentioned.
We present the results of a self-consistent, unified molecular dynamics study of simple model heteropolymers in the continuum with emphasis on folding, sequence design and the determination of the interaction parameters of the effective potential between the amino acids from the knowledge of the native states of the designed sequences. PACS numbers: 87.15.By, 87.10.+e 1 A fundamental problem in molecular biology is that of protein folding. In a coarsegrained description, a protein may be thought of as a heteropolymer made up of amino acids, twenty kinds of which occur in nature. Broadly speaking, there are several issues that are of vital importance. One of these is the direct folding problem: given the effective interactions between amino acids and an amino acid sequence, what is its native state conformation or ground state structure? This is a crucial question because the functionality of a protein is controlled by its native state structure. A second issue is that of inverse-folding or the design problem: again given the effective interactions, what is the sequence of amino acids that
The quantitative description of model protein folding kinetics using a diffusive collective reaction coordinate is examined. Direct folding kinetics, diffusional coefficients and free energy profiles are determined from Monte Carlo simulations of a 27-mer, 3 letter code lattice model, which corresponds roughly to a small helical protein. Analytic folding calculations, using simple diffusive rate theory, agree extremely well with the full simulation results. Folding in this system is best seen as a diffusive, funnel-like process. Comment: LaTeX 12 pages, figures included
The factors responsible for fast folding and stable 2D lattice proteins are studied by Monte Carlo kinetic simulations and by full enumeration. For weak effective coupling between residues ( i.e., high temperatures) the folding time is mainly controlled by the free energy gradient. When this coupling is strong, entrapment in local minima plays a major role. The energy gap separating the native state from the remaining conformations shows some correlation to the folding and unfolding times for a variety of sequences. These concepts are related to the ratio Tf/Tg proposed by Bryngelson and Wolynes. One source of local minima are strong, non‐native (hindering) contacts. An exclusive increase in hindering contacts shows a strong correlation between the energy gap and the folding/unfolding times. Other local minima results from several native contacts that, if formed prematurely, interfere with the formation of others. To study these factors, we use a semispecific model characterized by attractive interactions between similar residues. A procedure to design stabler sequences with smoother landscapes is discussed. By comparing this model to the hydrophobic HP model, we show how higher potential heterogeneity can be used to improve folding. © 1995 American Institute of Physics.
Effective interresidue contact energies for proteins in solution are estimated from the numbers of residue-residue contacts observed in crystal structures of globular proteins by means of the quasi-chemical approximation with an approximate treatment of the effects of chain connectivity. Employing a lattice model, each residue of a protein is assumed to occupy a site in a lattice and vacant sites are regarded to be occupied by an effective solvent molecule whose size is equal to the average size of a residue. A basic assumption is that the average characteristics of residue-residue contacts formed in a large number of protein crystal structures reflect actual differences of interactions among residues, as if there were no significant contribution from the specific amino acid sequence in each protein as well as intraresidue and short-range interactions. Then, taking account of the effects of the chain connectivity only as imposing a limit to the size of the system, i.e., the number of lattice sites or the number of effective solvent molecules in the system, the system is regarded to be the mixture of unconnected residues and effective solvent molecules. The quasi-chemical approximation, that contact pair formation resembles a chemical reaction, is applied to this system to obtain formulas that relate the statistical averages of the numbers of contacts to the contact energies. The number of effective solvent molecules for each protein is chosen to yield the total number of residue-residue contacts equal to its expected value for the hypothetical case of hard sphere interactions among residues and effective solvent molecules; the expected number of residue-residue contacts at this condition has been crudely estimated by means of a freely jointed chain distribution and an expansion originating in hard sphere interactions. Each residue is represented by the center of its side chain atom positions, and contacts among residues and effective solvent molecules are defined to be those pairs within 6.5 Å, a distance that has been chosen on the basis of the observed radial distribution of residues; nearest-neighbor pairs along a chain are explicitly excluded in counting contacts. Coordination numbers, for each type of residue as well as for solvent molecules, are estimated from the mean volume of each type of residue and used to evaluate the numbers of residue-solvent and solvent-solvent contacts from the numbers of residue-residue contacts. The estimated values of contact energies have reasonable residue-type dependences, reflecting residue distributions in protein crystals; nonpolar-residue-in and polar-residue-out are seen as well as the segregation of those residue groups. In addition, there is a linear relationship between the average contact energies for nonpolar residues and their hydrophobicities reported by Nozaki and Tanford; however, the magnitudes on average are about twice as large. The relevance of results to protein folding and other applications are discussed.
An algorithm, called RATTLE, for integrating the equations of motion in molecular dynamics calculations for molecular models with internal constraints is presented. The algorithm is similar to SHAKE, which is one of the standard methods for performing such calculations. RATTLE calculates the positions and velocities at the next time from the positions and velocities at the present time step, without requiring information about the earlier history. Like SHAKE, it is based on the Verlet algorithm and retains the simplicity of using Cartesian coordinates for each of the atoms to describe the configuration of a molecule with internal constraints. RATTLE guarantees that the coordinates and velocities of the atoms in a molecule satisfy the internal constraints at each time step. RATTLE has two advantages over SHAKE. On computers of fixed precision, it is of higher precision than SHAKE. Since it deals directly with the velocities, it is easier to modify RATTLE for use with the recently developed constant temperature and constant pressure molecular dynamics methods and with the nonequilibrium molecular dynamics methods that make use of rescaling of the atomic velocities.
Computer simulation techniques have become almost essential in the study of the macro-molecular phenomena and phase behavior on the molecular level. As these techniques become increasingly important, it is necessaryto realize that they are useful tools, but are not the goals of research. With this important distinction in mind, Understanding Molecular Simulation describes simulation techniques along with the physics behind the phenomena that these techniques simulate. Each chapter is comprised of three components: the general theoretical basis, an outline of the necessary computer code, and a few applications which illustrate the use of the technique demonstrated. The chapters also include examples of the typical practical problems that could be solved using each technique. Key Features * Gives a unified presentation of computational tools used to study molecular systems in the equilibrium state * Describes simulation techniques and physics behind the phenomena simulated * Emphasizes important topics of phase behavior and computer simulation of macro-molecular (polymer-type) substances * Includes references to the authors home page where additional information from the authors can be found.
Direct measurement of the forces involved in protein-protein and protein-receptor interactions can, in principle, provide insight necessary for the advancement of structural biology, molecular biology, and the development of therapeutic proteins. The protein insulin is illustrative in this respect as the mechanisms of insulin dimer dissociation and insulin-insulin receptor binding are crucial to the efficacy of insulin medications for the control of diabetes. Insulin molecules, modified with a photochemically active azido functionality on specific residues, were attached to force microscope tips and opposing mica surfaces in configurations that would either favor or disfavor dimer formation. Force curve measurements performed in buffer solution revealed the complexity of the insulin monomer-monomer interaction with multiple unbinding events occurring upon tip retraction, suggesting disruption of discrete molecular bonds at the monomer-monomer interface. Furthermore, the force curves exhibit long-range unbinding events, consistent with considerable elongation of the insulin molecule prior to dissociation. The unbinding forces observed in this study are the result of a combination of molecular disentanglement and dimer dissociation processes.
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Kinetic studies have been carried out of the monomer-dimer interaction of insulin, beta-lactoglobulin, and alpha-chymotrypsin using stopped-flow and temperature-jump techniques. The pH indicators bromothymol blue, bromophenol blue, and phenol red were used to monitor pH changes associated with the monomer-dimer interaction. In all three cases a kinetic process was observed which could be attributed to a simple monomer-dimer equilibrium, and association (k1) and dissociation (k-1) rate constants were determined. The results obtained are as follows: for insulin at 23 degrees C, pH 6.8, 0.125 M KNO3, k1 = 1.14 X 10(8) M-1 s-1, k-1 - 1.48 X 10(4)s(-1); for beta-lactoglobulin AB at 35 degrees C, pH 3.7, 0.025 M KNO3, d1 = 4.7 X 10(4) M-1 s-1, k-1 = 2.1 s-1; for alpha-chymotrypsin at 25 degreesC, pH 4.3, 0.05 M KNO3 k1 - 3.7 X 10(3) M-1 s-1, k-1 - 0.68 s-1. The kinetic behavior of the separated beta-lactoglobulin A and B was similar to that of the mixture. In the case of chymotrypsin, bromophenol blue was found to activate the enzyme catalyzed hydrolysis of p-nitrophenyl acetate, and a rate process was observed with the temperature jump which could be attributed to a conformational change of the indicator-protein complex. The association rate constant for dimer formation of insulin approaches the value expected for a diffusion-controlled process, while the values obtained for the other two proteins are below those expected for a diffusion-controlled reaction unless unusally large steric and electrostatic effects are present.
With the assumption that individual amino acids are independently distributed into naturally occurring polypeptide chains, it is shown that amino acid pairs with 0–2 arbitrary intervening residues are also independently distributed, with a few possible exceptions. This is not true of N- and C-terminal amino acids.
A series of molecular dynamics simulations have been used to investigate the nature of monomeric and dimeric insulin in aqueous solution. It is shown that in the absence of crystal contacts both monomeric and dimeric insulin have a high degree of intrinsic flexibility. Neither of the two monomer conformations of 2Zn crystalline insulin appears to be favored in solution nor is the asymmetry of the crystal dimer reduced in the absence of crystal contacts. A shift is observed in the relative positions of molecules 1 and 2 in the dimer compared with that found in the crystal, which may have consequences for the prediction of the effects of mutants in the monomer-monomer interface designed to alter the self-association properties of insulin.
Production of milk is a specific mammalian adaptation and milk is unique in being an almost complete natural food. The unique significance of milk proteins in mammalian nutrition and their immunological role alone justifies the study of the chemistry of these proteins. However, they possess physicochemical properties that make them of great importance in protein chemistry. In this chapter, special attention is given to these physicochemical properties and attention is drawn to the pitfalls involved in their study. The significance of the problems in the study of proteins in general is emphasized in the chapter. Subsequently, new techniques have enabled the detection of genetic variants of a protein where there are only one or two amino acid residue differences in the chain. Some of the whey proteins are amenable to detailed X-ray crystal structure analysis. This can be achieved only if search is made for appropriate heavy metal derivatives.
The association constant for insulin dimerization calculated from concentration-dependent circular dichroic (CD) spectra of insulin, K12 = 7.5 X 10(5) M-1, is used along with other association constants (K24, K46, and K26) in an attempt to decipher the complex association behavior in solution and in crystal of this protein hormone. The free-energy change associated with dimerization, -RT ln K12, is -8.01 kcal mol-1, a value which is used to test a semiquantitative thermodynamic model of the process based in part on the X-ray crystallographic data of insulin. By delineation of the hydrophobic core on the surface of insulin, which is implicated in the dimer formation, the free energy of association, delta G degrees assoc, is estimated as -8.27 kcal mol-1 by using the thermodynamic parameters of Némethy & Scheraga [Némethy, G., & Scheraga, H. A. (1962) J Phys. Chem. 66, 1773-1789] and as -10.27 kcal mol-1 by using the values of Nozaki & Tanford [Nozaki, Y., & Tanford, C. (1971) J. Biol. Chem. 246, 2211-2217]. The role of hydrophobic bonding in the dimerization of insulin is discussed, and the calculated values of free energy of association are compared with the experimental value. The importance of this thermodynamic model is delineated in regard to both hormone-hormone and hormone-receptor interactions.
The understanding, and even the description of protein folding is impeded by the complexity of the process. Much of this complexity can be described and understood by taking a statistical approach to the energetics of protein conformation, that is, to the energy landscape. The statistical energy landscape approach explains when and why unique behaviors, such as specific folding pathways, occur in some proteins and more generally explains the distinction between folding processes common to all sequences and those peculiar to individual sequences. This approach also gives new, quantitative insights into the interpretation of experiments and simulations of protein folding thermodynamics and kinetics. Specifically, the picture provides simple explanations for folding as a two-state first-order phase transition, for the origin of metastable collapsed unfolded states and for the curved Arrhenius plots observed in both laboratory experiments and discrete lattice simulations. The relation of these quantitative ideas to folding pathways, to uniexponential vs. multiexponential behavior in protein folding experiments and to the effect of mutations on folding is also discussed. The success of energy landscape ideas in protein structure prediction is also described. The use of the energy landscape approach for analyzing data is illustrated with a quantitative analysis of some recent simulations, and a qualitative analysis of experiments on the folding of three proteins. The work unifies several previously proposed ideas concerning the mechanism protein folding and delimits the regions of validity of these ideas under different thermodynamic conditions.
The recognition mechanisms and dissociation pathways of the avidin-biotin complex and of actin monomers in actin filaments were investigated. The unbinding forces of discrete complexes of avidin or streptavidin with biotin analogs are proportional to the enthalpy change of the complex formation but independent of changes in the free energy. This result indicates that the unbinding process is adiabatic and that entropic changes occur after unbinding. On the basis of the measured forces and binding energies, an effective rupture length of 9.5 +/- 1 angstroms was calculated for all biotin-avidin pairs and approximately 1 to 3 angstroms for the actin monomer-monomer interaction. A model for the correlation among binding forces, intermolecular potential, and molecular function is proposed.
The adhesion force between the tip of an atomic force microscope cantilever derivatized with avidin and agarose beads functionalized
with biotin, desthiobiotin, or iminobiotin was measured. Under conditions that allowed only a limited number of molecular
pairs to interact, the force required to separate tip and bead was found to be quantized in integer multiples of 160 +/- 20
piconewtons for biotin and 85 +/- 15 piconewtons for iminobiotin. The measured force quanta are interpreted as the unbinding
forces of individual molecular pairs.
Attractive inter-residue contact energies for proteins have been re-evaluated with the same assumptions and approximations used originally by us in 1985, but with a significantly larger set of protein crystal structures. An additional repulsive packing energy term, operative at higher densities to prevent overpacking, has also been estimated for all 20 amino acids as a function of the number of contacting residues, based on their observed distributions. The two terms of opposite sign are intended to be used together to provide an estimate of the overall energies of inter-residue interactions in simplified proteins without atomic details. To overcome the problem of how to utilize the many homologous proteins in the Protein Data Bank, a new scheme has been devised to assign different weights to each protein, based on similarities among amino acid sequences. A total of 1168 protein structures containing 1661 subunit sequences are actually used here. After the sequence weights have been applied, these correspond to an effective number of residue-residue contacts of 113,914, or about six times more than were used in the old analysis. Remarkably, the new attractive contact energies are nearly identical to the old ones, except for those with Leu and the rarer amino acids Trp and Met. The largest change found for Leu is surprising. The estimates of hydrophobicity from the contact energies for non-polar side-chains agree well with the experimental values. In an application of these contact energies, the sequences of 88 structurally distinct proteins in the Protein Data Bank are threaded at all possible positions without gaps into 189 different folds of proteins whose sequences differ from each other by at least 35% sequence identity. The native structures for 73 of 88 proteins, excluding 15 exceptional proteins such as membrane proteins, are all demonstrated to have the lowest alignment energies.
An atomic force microscope (AFM) has been used to directly monitor specific interactions between antibodies and antigens employed in an immunoassay system. Results were achieved using AFM probes functionalized with ferritin, and monitoring the adhesive forces between the probe and anti-ferritin antibody-coated substrates. Analysis of the force distribution data suggests a quantization of the forces, with a period of 49 +/- 10 pN. This periodic force may be attributed to single unbinding events between individual antigen and antibody molecules. These results demonstrate that the AFM could be employed as an analytical tool to study the interactions between the molecules involved in biosensor systems. The potential of the technique to provide information relating to the manner in which the antibody molecule binds to its specific antigen is also discussed.
A full quantitative understanding of the protein folding problem is now becoming possible with the help of the energy landscape theory and the protein folding funnel concept. Good folding sequences have a landscape that resembles a rough funnel where the energy bias towards the native state is larger than its ruggedness. Such a landscape leads not only to fast folding and stable native conformations but, more importantly, to sequences that are robust to variations in the protein environment and to sequence mutations. In this paper, an off-lattice model of sequences that fold into a beta-barrel native structure is used to describe a framework that can quantitatively distinguish good and bad folders. The two sequences analyzed have the same native structure, but one of them is minimally frustrated whereas the other one exhibits a high degree of frustration.
Insulin's natural tendency to form dimers and hexamers is significantly reduced in a mutant insulin B28 Pro --> Asp, which has been designed as a monomeric, rapid-acting hormone for therapeutic purposes. This molecule can be induced to form zinc hexamers in the presence of small phenolic derivatives which are routinely used as antimicrobial agents in insulin preparations. Two structures of B28 Asp insulin have been determined from crystals grown in the presence of phenol and m-cresol. In these crystals, insulin exists as R6 zinc hexamers containing a number of phenol or m-cresol molecules associated with aromatic side chains at the dimer-dimer interfaces. At the monomer-monomer interfaces, the B28 Pro --> Asp mutation leads to increased conformational flexibility in the B chain C termini, resulting in the loss of important intermolecular van der Waals contacts, thus explaining the monomeric character of B28 Asp insulin. The structure of a cross-linked derivative of B28 Asp insulin, containing an Ala-Lys dipeptide linker between residues B30 Ala and A1 Gly, has also determined. This forms an R6 zinc hexamer containing several m-cresol molecules. Of particular interest in this structure are two m-cresol molecules whose binding disrupted the beta-strand in one of the dimers. This observation suggests that the cross-link introduces mechanical strain on the B chain C terminus, thereby weakening the monomer-monomer interactions.
Copper, zinc superoxide dismutase is a dimeric enzyme, and it has been shown that no cooperativity between the two subunits of the dimer is operative. The substitution of two hydrophobic residues, Phe 50 and Gly 51, with two Glu's at the interface region has disrupted the quaternary structure of the protein, thus producing a soluble monomeric form. However, this monomeric form was found to have an activity lower than that of the native dimeric species (10%). To answer the fundamental question of the role of the quaternary structure in the catalytic process of superoxide dismutase, we have determined the solution structure of the reduced monomeric mutant through NMR spectroscopy. Another fundamental issue with respect to the enzymatic mechanism is the coordination of reduced copper, which is the active center. The three-dimensional solution structure of this 153-residue monomeric form of SOD (16 kDa) has been determined using distance and dihedral angle constraints obtained from 13C, 15N triple-resonance NMR experiments. The solution structure is represented by a family of 36 structures, with a backbone rmsd of 0.81 +/- 0.13 A over residues 3-150 and of 0.56 +/- 0.08 A over residues 3-49 and 70-150. This structure has been compared with the available X-ray structures of reduced SODs as well as with the oxidized form of human and bovine isoenzymes. The structure contains the classical eight-stranded Greek key beta-barrel. In general, the backbone and the metal sites are not affected much by the monomerization, except in the region involved in the subunit-subunit interface in the dimeric protein, where a large disorder is present. Significative changes are observed in the conformation of the electrostatic loop, which forms one side of the active site channel and which is fundamental in determining the optimal electrostatic potential for driving the superoxide anions to the copper site which is the rate-limiting step of the enymatic reaction under nonsaturating conditions. In the present monomer, its conformation is less favorable for the diffusion of the substrate to the reaction site. The structure of the copper center is well-defined; copper(I) is coordinated to three histidines, at variance with copper(II) which is bound to four histidines. The hydrogen atom which binds the histidine nitrogen detached from copper(I) is structurally identified.
- J D Bryngelson
- J N Onuchic
- P G Wolynes
Bryngelson, J. D., Onuchic, J. N. & Wolynes, P. G. (1995) Proteins
Struct. Funct. Genet. 21, 167-195.
- S Allen
- X Chen
- J Davies
- M C Davies
- A C Dawkes
- J C Edwards
- C J Roberts
- J Sefton
- S J B Tendler
- P M Willimans
Allen, S., Chen, X., Davies, J., Davies, M. C., Dawkes, A. C.,
Edwards, J. C., Roberts, C. J., Sefton, J., Tendler, S. J. B. &
Willimans, P. M. (1997) Biochemistry 36, 7457-7463.
- S Miyazawa
- R L Jernigan
Miyazawa, S. & Jernigan, R. L. (1985) Macromolecules 18,
534-552.
- S Miyazawa
- R L Jernigan
Miyazawa, S. & Jernigan, R. L. (1996) J. Mol. Biol. 256, 623–644.
- W Kabsch
Kabsch, W. (1978) Acta Crystallogr. A 34, 827-828.
- A Wlodawer
- J Vondrasek
Wlodawer, A. & Vondrasek, J. (1998) Annu. Rev. Biophys.
Biomol. Struct. 27, 249-284.
- W Kabsch
Kabsch, W. (1976) Acta Crystallogr. A 32, 922–923.
- A E Mark
- H J C Berendsen
- W F Van Gusteren
Mark, A. E., Berendsen, H. J. C. & van Gusteren, W. F. (1991)
Biochemistry 30, 10866-10872.
- M H Klapper
Klapper, M. H. (1977) Biochem. Biophys. Res. Commun. 78,
1018-1024.
- J N Onuchic
- P G Wolynes
- Z Luthey-Schulten
- N D Socci
Onuchic, J. N., Wolynes, P. G., Luthey-Schulten, Z. & Socci,
N. D. (1995) Proc. Natl. Acad. Sci. USA 92, 3626-3630.
- V T Moy
- E L Florin
- H E Gaub
Moy, V. T., Florin, E. L. & Gaub, H. E. (1994) Science 266,
257-259.
- G U Lee
- L A Chrisey
- R J Colton
Lee, G. U., Chrisey, L. A. & Colton, R. J. (1994) Science 266,
771-773.