Structure prediction of an S-layer protein by the mean force method

S-layer proteins have a wide range of application potential due to their characteristic features concerning self-assembling, assembling on various surfaces, and forming of isoporous structures with functional groups located on the surface in an identical position and orientation. Although considerable knowledge has been experimentally accumulated on the structure, biochemistry, assemble characteristics, and genetics of S-layer proteins, no structural model at atomic resolution has been available so far. Therefore, neither the overall folding of the S-layer proteins-their tertiary structure-nor the exact amino acid or domain allocations in the lattices are known. In this paper, we describe the tertiary structure prediction for the S-layer protein SbsB from Geobacillus stearothermophilus PV72/p2. This calculation was based on its amino acid sequence using the mean force method (MF method) achieved by performing molecular dynamic simulations. This method includes mainly the thermodynamic aspects of protein folding as well as steric constraints of the amino acids and is therefore independent of experimental structure analysis problems resulting from biochemical properties of the S-layer proteins. Molecular dynamic simulations were performed in vacuum using the simulation software NAMD. The obtained tertiary structure of SbsB was systematically analyzed by using the mean force method, whereas the verification of the structure is based on calculating the global free energy minimum of the whole system. This corresponds to the potential of mean force, which is the thermodynamically most favorable conformation of the protein. Finally, an S-layer lattice was modeled graphically using CINEMA4D and compared with scanning force microscopy data down to a resolution of 1 nm. The results show that this approach leads to a thermodynamically favorable atomic model of the tertiary structure of the protein, which could be verified by both the MF Method and the lattice model.     

De novo and inverse folding predictions of protein structure and dynamics

Summary In the last two years, the use of simplified models has facilitated major progress in the globular protein folding problem, viz., the prediction of the three-dimensional (3D) structure of a globular protein from its amino acid sequence. A number of groups have addressed the inverse folding problem where one examines the compatibility of a given sequence with a given (and already determined) structure. A comparison of extant inverse protein-folding algorithms is presented, and methodologies for identifying sequences likely to adopt identical folding topologies, even when they lack sequence homology, are described. Extension to produce structural templates or fingerprints from idealized structures is discussed, and for eight-membered β-barrel proteins, it is shown that idealized fingerprints constructed from simple topology diagrams can correctly identify sequences having the appropriate topology. Furthermore, this inverse folding algorithm is generalized to predict elements of supersecondary structure including β-hairpins, helical hairpins and α/β/α fragments. Then, we describe a very high coordination number lattice model that can predict the 3D structure of a number of globular proteins de novo; i.e. using just the amino acid sequence. Applications to sequences designed by DeGrado and co-workers [Biophys. J., 61 (1992) A265] predict folding intermediates, native states and relative stabilities in accord with experiment. The methodology has also been applied to the four-helix bundle designed by Richardson and co-workers [Science, 249 (1990) 884] and a redesigned monomeric version of a naturally occurring four-helix dimer, rop. Based on comparison to the rop dimer, the simulations predict conformations with rms values of 3–4 ? from native. Furthermore, the de novo algorithms can asses the stability of the folds predicted from the inverse algorithm, while the inverse folding algorithms can assess the quality of the de novo models. Thus, the synergism of the de novo and inverse folding algorthhm approaches provides a set of complementary tools that will facilitate further progress on the protein-folding problem.     

Quantitative approach to conformations of proteins

A quantitative conformational theory of proteins is developed that enables one to predict the native structure of a protein from its amino acid sequence. The theory is based on the following principles: (1) the spatial structure and conformational properties of a protein are predetermined by its amino acid sequence; (2) the native conformation of a protein corresponds to the free energy minimum; (3) all interactions within a protein molecule are specified as short-, mediumy-, and long-range types, interactions of different types being consistent with each other. The role of the short-, medium-, and long-range interactions in the spatial organization of a protein globule is discussed, and a step-by-step analysis of amino acid sequences with gradually increasing lengths is presented. The proposed theory is based on a semiempirical computational method that involves quantitative evaluation of all pairwise atomic interactions within a protein molecule in an aqueous medium. Examples illustrating the suggested approach are presented.     

Multicanonical Monte Carlo calculation of the free‐energy map of the base–amino acid interaction

The specific interactions between base pairs and amino acids were studied by the multicanonical Monte Carlo method. We sampled numerous interaction configurations and side‐chain conformations of the amino acid by the multicanonical algorithm, and calculated the free energies of the interactions between an amino acid at given C_α positions and a fixed base pair. The contour maps of free energy derived from this calculation represent the preferred C_α position of the amino acid around the base, and these maps of various combinations of bases and amino acids can be used to quantify the specificity of intrinsic base–amino acid interactions. Similarly, enthalpy and entropy maps will provide further details of the specific interactions. We have also calculated the free‐energy map of the orientations of the C_α C_β bond vector, which indicates the preferential orientation of the amino acid against the base. We compared the results obtained by the multicanonical method with those of the exhaustive sampling and canonical Monte Carlo methods. The free‐energy map of the base–amino acid interaction obtained by the multicanonical simulation method was nearly identical to the accurate result derived from the exhaustive sampling method. This indicates that a single multicanonical Monte Carlo simulation can produce an accurate free‐energy map. Multicanonical Monte Carlo sampling produced free‐energy maps that were more accurate than those produced by canonical Monte Carlo sampling. Thus, the multicanonical Monte Carlo method can serve as a powerful tool for estimating the free‐energy landscape of base–amino acid interactions and for elucidating the mechanism by which amino acids of proteins recognize particular DNA base pairs. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 954–962, 2000     

Supersecondary structure prediction using Chou's pseudo amino acid composition

Supersecondary structures (SSSs) are the building blocks of protein 3D structures. Accurate prediction of SSSs can be one important step toward building a tertiary structure from the specified secondary structure. How to improve the accuracy of prediction of SSSs by effectively incorporating the sequence order effects is an important and challenging problem. Based on a different form of Chou's pseudo amino acid composition, a novel approach for feature representation of SSSs is proposed. Amino acid basic compositions, dipeptide components, and amino acid composition distribution are incorporated to represent the compositional features of proteins. Each supersecondary structural motif is characterized as a vector of 36 dimensions. In addition, we propose a novel prediction system by using SVM and IDQD algorithm as classifiers. Our method is trained and tested on ArchDB40 dataset containing 3088 proteins. The highest overall accuracy for the training dataset and the independent testing dataset are 77.7 and 69.4%, respectively. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011     

3D-Epitope-Explorer (3DEX): localization of conformational epitopes within three-dimensional structures of proteins

Neutralizing antibodies often recognize conformational, discontinuous epitopes. Linear peptides mimicking such conformational epitopes can be selected from phage display peptide libraries by screening with the respective antibodies. However, it is difficult to localize these "mimotopes" within the three-dimensional (3D) structures of the target proteins. Knowledge of conformational epitopes of neutralizing antibodies would help to design antigens able to elicit protective immune responses. Therefore, we provide here a software that allows to localize linear peptide sequences within 3D structures of proteins. The 3D-Epitope-Explorer (3DEX) software allows to map conformational epitopes in 3D protein structures based on an algorithm that takes into account the physicochemical neighborhood of C(alpha)- or C(beta)-atoms of individual amino acids. A given amino acid of a peptide sequence is localized within the protein and the software searches within predefined distances for the amino acids neighboring that amino acid in the peptide. Surface exposure of the amino acids can also be taken into consideration. The procedure is then repeated for the remaining amino acids of the peptide. The introduction of a joker function allows to map peptide mimotopes, which do not necessarily have 100% sequence homology to the protein. Using this software we were able to localize mimotopes selected from phage displayed peptide libraries with polyclonal antibodies from HIV-positive patient plasma within the 3D structure of gp120, the exterior glycoprotein of HIV-1. We also analyzed two recently published peptide sequences corresponding to known conformational epitopes to further confirm the integrity of 3DEX.     

Performance of density functional models to reproduce observed (13)C(alpha) chemical shifts of proteins in solution

The purpose of this work is to test several density functional models (namely, OPBE, O3LYP, OPW91, BPW91, OB98, BPBE, B971, OLYP, PBE1PBE, and B3LYP) to determine their accuracy and speed for computing (13)C(alpha) chemical shifts in proteins. The test is applied to 10 NMR-derived conformations of the 76-residue alpha/beta protein ubiquitin (protein data bank id 1D3Z). With each functional, the (13)C(alpha) shielding was computed for 760 amino acid residues by using a combination of approaches that includes, but is not limited to, treating each amino acid X in the sequence as a terminally blocked tripeptide with the sequence Ac-GXG-NMe in the conformation of the regularized experimental protein structure. As computation of the (13)C(alpha) chemical shifts, not their shielding, is the main goal of this work, a computation of the (13)C(alpha) shielding of the reference, namely, tetramethylsilane, is investigated here and an effective and a computed tetramethylsilane shielding value for each of the functionals is provided. Despite observed small differences among all functionals tested, the results indicate that four of them, namely, OPBE, OPW91, OB98, and OLYP, provide the most accurate functionals with which to reproduce observed (13)C(alpha) chemical shifts of proteins in solution, and are among the faster ones. This study also provides evidence for the applicability of these functionals to proteins of any size or class, and for the validation of our previous results and conclusions, obtained from calculations with the slower B3LYP functional.     

Simulation studies of the protein-water interface. I. Properties at the molecular resolution

We report molecular dynamics simulations of three globular proteins: ubiquitin, apo-calbindin D(9K), and the C-terminal SH2 domain of phospholipase C-gamma1 in explicit water. The proteins differ in their overall charge and fold type and were chosen to represent to some degree the structural variability found in medium-sized proteins. The length of each simulation was at least 15 ns, and larger than usual solvent boxes were used. We computed radial distribution functions, as well as orientational correlation functions about the surface residues. Two solvent shells could be clearly discerned about charged and polar amino acids. Near apolar amino acids the water density near such residues was almost devoid of structure. The mean residence time of water molecules was determined for water shells about the full protein, as well as for water layers about individual amino acids. In the dynamic properties, two solvent shells could be characterized as well. However, by comparison to simulations of pure water it could be shown that the influence of the protein reaches beyond 6 A, i.e., beyond the first two shells. In the first shell (r < or =3.5 A), the structural and dynamical properties of solvent waters varied considerably and depended primarily on the physicochemical properties of the closest amino acid side chain, with which the waters interact. By contrast, the solvent properties seem not to depend on the specifics of the protein studied (such as the net charge) or on the secondary structure element in which an amino acid is located. While differing considerably from the neat liquid, the properties of waters in the second solvation shell (3.5< r < or =6 A) are rather uniform; a direct influence from surface amino acids are already mostly shielded.     

Simple and effective application of the Wang-Landau method for multicanonical molecular dynamics simulation

We propose a novel application of the Wang-Landau method (WLM) for multicanonical molecular dynamics (McMD) simulations. Originally, WLM was developed for Monte Carlo (MC) simulations. Fundamentally, WLM remarkably reduces simulation efforts because it estimates the optimal multicanonical energy function automatically. When WLM is applied to McMD, not only the multicanonical energy but also energy gradient must be estimated adequately. However, because of the rugged multicanonical energy function at the early simulation stage, applications of WLM for MD simulations are difficult and require a smoothing procedure: simulation efforts such as cubic-spline extrapolation and gathering multiple preruns are utilized for smoothing. We propose a simple and effective smoothing method that requires only one additional equation and two time-dependent parameters. As a result, our method produced the correct multicanonical energy function and succeeded in the flat sampling of a small biomolecule with reduced simulation effort.     

Covalent Protein Labeling by Enzymatic Phosphocholination

We present a new protein labeling method based on the covalent enzymatic phosphocholination of a specific octapeptide amino acid sequence in intact proteins. The bacterial enzyme AnkX from Legionella pneumophila has been established to transfer functional phosphocholine moieties from synthetically produced CDP‐choline derivatives to N‐termini, C‐termini, and internal loop regions in proteins of interest. Furthermore, the covalent modification can be hydrolytically removed by the action of the Legionella enzyme Lem3. Only a short peptide sequence (eight amino acids) is required for efficient protein labeling and a small linker group (PEG‐phosphocholine) is introduced to attach the conjugated cargo.     

Absolute free energies of biomolecules from unperturbed ensembles

Computing the absolute free energy of a macromolecule's structural state, F, is a challenging problem of high relevance. This study presents a method that computes F using only information from an unperturbed simulation of the macromolecule in the relevant conformational state, ensemble, and environment. Absolute free energies produced by this method, dubbed V aluation of L ocal C onfiguration I ntegral with D ynamics (VALOCIDY), enable comparison of alternative states. For example, comparing explicitly solvated and vaporous states of amino acid side‐chain analogs produces solvation free energies in good agreement with experiments. Also, comparisons between alternative conformational states of model heptapeptides (including the unfolded state) produce free energy differences in agreement with data from μs molecular‐dynamics simulations and experimental propensities. The potential of using VALOCIDY in computational protein design is explored via a small design problem of stabilizing a β‐turn structure. When VALOCIDY‐based estimation of folding free energy is used as the design metric, the resulting sequence folds into the desired structure within the atomistic force field used in design. The VALOCIDY‐based approach also recognizes the distinct status of the native sequence regardless of minor details of the starting template structure, in stark contrast with a traditional fixed‐backbone approach. © 2013 Wiley Periodicals, Inc.     

Site-selective screening by NMR spectroscopy with labeled amino acid pairs

A new method for site-selective screening by NMR is presented. The core of the new method is the dual amino acid sequence specific labeling technique. Amino acid X is labeled with (13)C and amino acid Y is labeled with (15)N. Provided only one XY pair occurs in the amino acid sequence, only one signal in the 1D carbonyl (13)C spectrum will display a splitting due to the (1)J(C'N) coupling. Using this labeling strategy it is possible to screen selectively for binding to a selected epitope without the need for sequence specific assignments. An HNCO spectrum (1D or 2D) can be used either directly as a screening experiment or indirectly to identify what signals to monitor in a 2D (1)H-(15)N correlation spectrum. Chemical shift perturbations upon addition of a potential ligand are easily detected even for large proteins due to the reduced spectral complexity resulting from the use of a selectively labeled sample. The new technique is demonstrated on the human adipocyte fatty acid binding protein FABP-4. Due to the reduced spectral complexity, the method should be applicable to larger proteins than are conventional methods.     

Development of a database of amino acid sequences for human colon carcinoma proteins separated by two-dimensional polyacrylamide gel electrophoresis

The tandem use of preparative two-dimensional polyacrylamide gel electrophoresis (2-DE) and electroblotting onto polyvinylidene difluoride membranes has been employed to rapidly isolate a number of proteins from a crude cell extract of a human colon carcinoma cell line (LIM 1863). The immobilized proteins were located by staining with Coomassie Brilliant Blue R-250, and selected protein spots were excised and subjected to Edman degradation. Our results demonstrate that overall sequence yields in the 3-20 pmol range can be achieved on protein spots from four identical 2-DE gels; approximately 150-200 micrograms of total protein was applied to a single 2-DE gel. An approximate two-fold increase in sensitivity of phenylthiohydantoin-amino acid detection (subpicomole range) was achieved by fitting our commercial sequencers with a simple sample transfer device which permitted the analysis of the total phenylthiohydantoin-amino acid derivative. N-Terminal amino acid sequence data was obtained for thirteen electroblotted proteins. All of these sequences positively matched those of proteins of known structure listed in the available protein sequence databases. Approximately 40% of the electroblotted proteins did not yield N-terminal sequence information, presumably because they had blocked N-termini (either naturally or artifactually). Internal amino acid sequence information was obtained from three proteins isolated by preparative 2-DE. This was achieved by in situ digestion of the proteins in the gel matrix with Staphylococcus aureus V8 protease, electrophoresis of the generated peptides in a one-dimensional gel, electrotransfer of the peptides to a polyvinylidene difluoride membrane and microsequence analysis of the electroblotted peptides.     

Effect of single-point sequence alterations on the aggregation propensity of a model protein

Sequences of contemporary proteins are believed to have evolved through a process that optimized their overall fitness, including their resistance to deleterious aggregation. Biotechnological processing may expose therapeutic proteins to conditions that are much more conducive to aggregation than those encountered in a cellular environment. An important task of protein engineering is to identify alternative sequences that would protect proteins when processed at high concentrations without altering their native structure associated with specific biological function. Our computational studies exploit parallel tempering simulations of coarse-grained model proteins to demonstrate that isolated amino acid residue substitutions can result in significant changes in the aggregation resistance of the protein in a crowded environment while retaining protein structure in isolation. A thermodynamic analysis of protein clusters subject to competing processes of folding and association shows that moderate mutations can produce effects similar to those caused by changes in system conditions, including temperature, concentration, and solvent composition, that affect the aggregation propensity. The range of conditions where a protein can resist aggregation can therefore be tuned by sequence alterations, although the protein generally may retain its generic ability for aggregation.     

Recognition determinants in a T4 ← G4 mutant derived from a 5′-GCGTGGGCGT-3′ oligomer in a zinc finger 268–DNA complex.

The 5′-GCGTGGGCGT-3′ (T4) oligomer found in the zinc finger 268–DNA complex was mutated into the sequence 5′-GCGGGGGCGT-3′ (G4). A 3D model was constructed from the T4 sequence using an X-ray structure as a template. Molecular dynamics simulations were used to test the thermal stability of the model. A 500-ps trajectory was obtained for the fully charged complex in water using GROMOS87. The complex and the G4 sequence are found to have dynamically stationary behavior. Comparisons made with a previous T4 sequence molecular dynamics simulation show both systems have similar thermal stability. The structure of DNA appears to be maintained by its global interactions with the protein although the mutated site does not contribute with its full potential for binding. The protein structure shows some small differences compared to the T4 simulation. The simulation provided evidence for the role of a chloride ion interacting with the protein and helping in the recognition process. Received: 21 June 1999 / Accepted: 19 October 1999 / Published online: 14 March 2000     

Using pseudo amino acid composition to predict protein structural class: approached by incorporating 400 dipeptide components

The proteins structure can be mainly classified into four classes: all-alpha, all-beta, alpha/beta, and alpha + beta protein according to their chain fold topologies. For the purpose of predicting the protein structural class, a new predicting algorithm, in which the increment of diversity combines with Quadratic Discriminant analysis, is presented to study and predict protein structural class. On the basis of the concept of the pseudo amino acid composition (Chou, Proteins: Struct Funct Genet 2001, 43, 246; Erratum: Proteins Struct Funct Genet 2001, 44, 60), 400 dipeptide components and 20 amino acid composition are, respectively, selected as parameters of diversity source. Total of 204 nonhomologous proteins constructed by Chou (Chou, Biochem Biophys Res Commun 1999, 264, 216) are used for training and testing the predictive model. The predicted results by using the pseudo amino acids approach as proposed in this paper can remarkably improve the success rates, and hence the current method may play a complementary role to other existing methods for predicting protein structural classification.     

On the utility of predictive chromatography to complement mass spectrometry based intact protein identification

The amino acid sequence determines the individual protein three-dimensional structure and its functioning in an organism. Therefore, “reading” a protein sequence and determining its changes due to mutations or post-translational modifications is one of the objectives of proteomic experiments. The commonly utilized approach is gradient high-performance liquid chromatography (HPLC) in combination with tandem mass spectrometry. While serving as a way to simplify the protein mixture, the liquid chromatography may be an additional analytical tool providing complementary information about the protein structure. Previous attempts to develop “predictive” HPLC for large biomacromolecules were limited by empirically derived equations based purely on the adsorption mechanisms of the retention and applicable to relatively small polypeptide molecules. A mechanism of the large biomacromolecule retention in reversed-phase gradient HPLC was described recently in thermodynamics terms by the analytical model of liquid chromatography at critical conditions (BioLCCC). In this work, we applied the BioLCCC model to predict retention of the intact proteins as well as their large proteolytic peptides separated under different HPLC conditions. The specific aim of these proof-of-principle studies was to demonstrate the feasibility of using “predictive” HPLC as a complementary tool to support the analysis of identified intact proteins in top-down, middle-down, and/or targeted selected reaction monitoring (SRM)-based proteomic experiments.     

Strategies for internal amino acid sequence analysis of proteins separated by polyacrylamide gel electrophoresis

An evaluation has been made of various strategies for obtaining internal amino acid sequence data from electrophoretically separated proteins. Electroblotting, in situ proteolysis and extraction, and direct electroelution are compared. Electroblotting of protein or peptides from gels resulted in poor yields (typically, 1-7%). However, higher yields (3-67%) were achieved by in situ enzymatic cleavage followed by acid extraction of the peptides from the gel. Peptides extracted from the gel were separated by reversed-phase high-performance liquid chromatography (RP-HPLC), on short, small-bore columns (100 x 2.1 mm I.D.), to enable recovery of peptides in small volumes (ca. 50 microliters) suitable for microsequence analysis. Capillary zone electrophoresis under acidic conditions (pH 2.5) was used to assess peptide purity before sequence analysis. Cysteine residues were identified in unmodified proteins or peptides by a characteristic phenylthiohydantoin (PTH)-amino acid derivative during sequence analysis. This derivative does not co-chromatograph with any known PTH-amino acid. Direct electrophoretic elution of protein from gels yielded between 45-50% of applied protein. Proteins recovered from gels by electrophoretic elution required further purification by inverse-gradient RP-HPLC [R. J. Simpson, R. L. Moritz, E. C. Nice and B. Grego, Eur. J. Biochem., 165 (1987) 21] to remove sodium dodecylsulphate and acrylamide-related contaminants for sequence analysis.     

Unambiguous characterization and tissue localization of Pru P 3 peach allergen by electrospray mass spectrometry and MALDI imaging

The lipid transfer protein (LTP), Pru p 3, has been identified as the major allergen present in peach, and its sequence obtained by direct amino acid sequencing has been previously reported. However, several sequences, obtained from c‐DNA and available in databases, show differences among them and from the originally proposed structure. In this paper, we report the fast and unambiguous determination of the structure of Pru p 3 protein, extracted from three different varieties of peach, by electrospray ionization mass spectrometry (ESI‐MS), both coupled to single stage (quadrupole) or advanced (FT‐HRMS) analyzers. The structure was identical to one of the cDNA‐derived sequences and different in two positions from the previously reported structure obtained by amino acid sequencing. Moreover, the exclusive localization of the protein in the outer part of the fruits was assessed by Matrix‐Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI MSI). The results reported here demonstrate the full potential of mass spectrometry for rapidly obtaining high quality structural data of relevant food proteins. Copyright © 2009 John Wiley & Sons, Ltd.     

Periodic sequence distribution of product ion abundances in electron capture dissociation of amphipathic peptides and proteins

The rules for product ion formation in electron capture dissociation (ECD) mass spectrometry of peptides and proteins remain unclear. Random backbone cleavage probability and the nonspecific nature of ECD toward amino acid sequence have been reported, contrary to preferential channels of fragmentation in slow heating-based tandem mass spectrometry. Here we demonstrate that for amphipathic peptides and proteins, modulation of ECD product ion abundance (PIA) along the sequence is pronounced. Moreover, because of the specific primary (and presumably secondary) structure of amphipathic peptides, PIA in ECD demonstrates a clear and reproducible periodic sequence distribution. On the one hand, the period of ECD PIA corresponds to periodic distribution of spatially separated hydrophobic and hydrophilic domains within the peptide primary sequence. On the other hand, the same period correlates with secondary structure units, such as α-helical turns, known for solution-phase structure. Based on a number of examples, we formulate a set of characteristic features for ECD of amphipathic peptides and proteins: (1) periodic distribution of PIA is observed and is reproducible in a wide range of ECD parameters and on different experimental platforms; (2) local maxima of PIA are not necessarily located near the charged site; (3) ion activation before ECD not only extends product ion sequence coverage but also preserves ion yield modulation; (4) the most efficient cleavage (e.g. global maximum of ECD PIA distribution) can be remote from the charged site; (5) the number and location of PIA maxima correlate with amino acid hydrophobicity maxima generally to within a single amino acid displacement; and (6) preferential cleavage sites follow a selected hydrogen spine in an α-helical peptide segment. Presently proposed novel insights into ECD behavior are important for advancing understanding of the ECD mechanism, particularly the role of peptide sequence on PIA. An improved ECD model could facilitate protein sequencing and improve identification of unknown proteins in proteomics technologies. In structural biology, the periodic/preferential product ion yield in ECD of α-helical structures potentially opens the way toward de novo site-specific secondary structure determination of peptides and proteins in the gas phase and its correlation with solution-phase structure.