Interior and surface of monomeric proteins

Layers: A molecular surface peeling algorithm and its applications to analyze protein structures

We present an algorithm 'Layers' to peel the atoms of proteins as layers. Using Layers we show an efficient way to transform protein structures into 2D pattern, named residue transition pattern (RTP), which is independent of molecular orientations. RTP explains the folding patterns of proteins and hence identification of similarity between proteins is simple and reliable using RTP than with the standard sequence or structure based methods. Moreover, Layers generates a fine-tunable coarse model for the molecular surface by using non-random sampling. The coarse model can be used for shape comparison, protein recognition and ligand design. Additionally, Layers can be used to develop biased initial configuration of molecules for protein folding simulations. We have developed a random forest classifier to predict the RTP of a given polypeptide sequence. Layers is a standalone application; however, it can be merged with other applications to reduce the computational load when working with large datasets of protein structures. Layers is available freely at http://www.csb.iitkgp.ernet.in/applications/mol_layers/main.

Sequence- and Temperature-Dependent Properties of Unfolded and Disordered Proteins from Atomistic Simulations

We use all-atom molecular simulation with explicit solvent to study the properties of selected intrinsically disordered proteins and unfolded states of foldable proteins, which include chain dimensions and shape, secondary structure propensity, solvent accessible surface area, and contact formation. We find that the qualitative scaling behavior of the chains matches expectations from theory under ambient conditions. In particular, unfolded globular proteins tend to be more collapsed under the same conditions than charged disordered sequences of the same length. However, inclusion of explicit solvent in addition naturally captures temperature-dependent solvation effects, which results in an initial collapse of the chains as temperature is increased, in qualitative agreement with experiment. There is a universal origin to the collapse, revealed in the change of hydration of individual residues as a function of temperature: namely, that the initial collapse is driven by unfavorable solvation free energy of individual residues, which in turn has a strong temperature dependence. We also observe that in unfolded globular proteins, increased temperature also initially favors formation of native-like (rather than non-native-like) structure. Our results help to establish how sequence encodes the degree of intrinsic disorder or order as well as its response to changes in environmental conditions.

Non-invasive high throughput approach for protein hydrophobicity determination based on surface tension

The surface hydrophobicity of a protein is an important factor for its interactions in solution and thus the outcome of its production process. Yet most of the methods are not able to evaluate the influence of these hydrophobic interactions under natural conditions. In the present work we have established a high resolution stalagmometric method for surface tension determination on a liquid handling station, which can cope with accuracy as well as high throughput requirements. Surface tensions could be derived with a low sample consumption (800 μL) and a high reproducibility (<0.1‰ for water) within a reasonable time (3.5 min per sample). This method was used as a non-invasive HTP compatible approach to determine surface tensions of protein solutions dependent on protein content. The protein influence on the solutions' surface tension was correlated to the hydrophobicity of lysozyme, human lysozyme, BSA, and α-lactalbumin. Differences in proteins' hydrophobic character depending on pH and species could be resolved. Within this work we have developed a pH dependent hydrophobicity ranking, which was found to be in good agreement with literature. For the studied pH range of 3-9 lysozyme from chicken egg white was identified to be the most hydrophilic. α-lactalbumin at pH 3 exhibited the most pronounced hydrophobic character. The stalagmometric method occurred to outclass the widely used spectrophotometric method with bromophenol blue sodium salt as it gave reasonable results without restrictions on pH and protein species.

Peptide Probes Reveal a Hydrophobic Steric Ratchet in the Anthrax Toxin Protective Antigen Translocase

Anthrax toxin is a tripartite virulence factor produced by Bacillus anthracis during infection. Under acidic endosomal pH conditions, the toxin's protective antigen (PA) component forms a transmembrane channel in host cells. The PA channel then translocates its two enzyme components, lethal factor and edema factor, into the host cytosol under the proton motive force. Protein translocation under a proton motive force is catalyzed by a series of nonspecific polypeptide binding sites, called clamps. A 10-residue guest/host peptide model system, KKKKKXXSXX, was used to functionally probe polypeptide-clamp interactions within wild-type PA channels. The guest residues were Thr, Ala, Leu, Phe, Tyr, and Trp. In steady-state translocation experiments, the channel blocked most tightly with peptides that had increasing amounts of nonpolar surface area. Cooperative peptide binding was observed in the Trp-containing peptide sequence but not the other tested sequences. Trp substitutions into a flexible, uncharged linker between the lethal factor amino-terminal domain and diphtheria toxin A chain expedited translocation. Therefore, peptide-clamp sites in translocase channels can sense large steric features (like tryptophan) in peptides, and while these steric interactions may make a peptide translocate poorly, in the context of folded domains, they can make the protein translocate more rapidly presumably via a hydrophobic steric ratchet mechanism.

Prediction of the optimal set of contacts to fold the smallest knotted protein

Knotted protein chains represent a new motif in protein folds. They have been linked to various diseases, and recent extensive analysis of the Protein Data Bank shows that they constitute 1.5% of all deposited protein structures. Despite thorough theoretical and experimental investigations, the role of knots in proteins still remains elusive. Nonetheless, it is believed that knots play an important role in mechanical and thermal stability of proteins. Here, we perform a comprehensive analysis of native, shadow-specific and non-native interactions which describe free energy landscape of the smallest knotted protein (PDB id 2efv). We show that the addition of shadow-specific contacts in the loop region greatly enhances folding kinetics, while the addition of shadow-specific contacts along the C-terminal region (H3 or H4) results in a new folding route with slower kinetics. By means of direct coupling analysis (DCA) we predict non-native contacts which also can accelerate kinetics. Next, we show that the length of the C-terminal knot tail is responsible for the shape of the free energy barrier, while the influence of the elongation of the N-terminus is not significant. Finally, we develop a concept of a minimal contact map sufficient for 2efv protein to fold and analyze properties of this protein using this map.

Structural modeling of the N-terminal signal-receiving domain of IκBα

The transcription factor nuclear factor-κB (NF-κB) exerts essential roles in many biological processes including cell growth, apoptosis and innate and adaptive immunity. The NF-κB inhibitor (IκBα) retains NF-κB in the cytoplasm and thus inhibits nuclear localization of NF-κB and its association with DNA. Recent protein crystal structures of the C-terminal part of IκBα in complex with NF-κB provided insights into the protein-protein interactions but could not reveal structural details about the N-terminal signal receiving domain (SRD). The SRD of IκBα contains a degron, formed following phosphorylation by IκB kinases (IKK). In current protein X-ray structures, however, the SRD is not resolved and assumed to be disordered. Here, we combined secondary structure annotation and domain threading followed by long molecular dynamics (MD) simulations and showed that the SRD possesses well-defined secondary structure elements. We show that the SRD contains 3 additional stable α-helices supplementing the six ARDs present in crystallized IκBα. The IκBα/NF-κB protein-protein complex remained intact and stable during the entire simulations. Also in solution, free IκBα retains its structural integrity. Differences in structural topology and dynamics were observed by comparing the structures of NF-κB free and NF-κB bound IκBα-complex. This study paves the way for investigating the signaling properties of the SRD in the IκBα degron. A detailed atomic scale understanding of molecular mechanism of NF-κB activation, regulation and the protein-protein interactions may assist to design and develop novel chronic inflammation modulators.

Deep Sequencing-guided Design of a High Affinity Dual Specificity Antibody to Target Two Angiogenic Factors in Neovascular Age-related Macular Degeneration

The development of dual targeting antibodies promises therapies with improved efficacy over mono-specific antibodies. Here, we engineered a Two-in-One VEGF/angiopoietin 2 antibody with dual action Fab (DAF) as a potential therapeutic for neovascular age-related macular degeneration. Crystal structures of the VEGF/angiopoietin 2 DAF in complex with its two antigens showed highly overlapping binding sites. To achieve sufficient affinity of the DAF to block both angiogenic factors, we turned to deep mutational scanning in the complementarity determining regions (CDRs). By mutating all three CDRs of each antibody chain simultaneously, we were able not only to identify affinity improving single mutations but also mutation pairs from different CDRs that synergistically improve both binding functions. Furthermore, insights into the cooperativity between mutations allowed us to identify fold-stabilizing mutations in the CDRs. The data obtained from deep mutational scanning reveal that the majority of the 52 CDR residues are utilized differently for the two antigen binding function and permit, for the first time, the engineering of several DAF variants with sub-nanomolar affinity against two structurally unrelated antigens. The improved variants show similar blocking activity of receptor binding as the high affinity mono-specific antibodies against these two proteins, demonstrating the feasibility of generating a dual specificity binding surface with comparable properties to individual high affinity mono-specific antibodies.

Solvent accessible surface area-based hot-spot detection methods for protein-protein and protein-nucleic acid interfaces

Due to the importance of hot-spots (HS) detection and the efficiency of computational methodologies, several HS detecting approaches have been developed. The current paper presents new models to predict HS for protein-protein and protein-nucleic acid interactions with better statistics compared with the ones currently reported in literature. These models are based on solvent accessible surface area (SASA) and genetic conservation features subjected to simple Bayes networks (protein-protein systems) and a more complex multi-objective genetic algorithm-support vector machine algorithms (protein-nucleic acid systems). The best models for these interactions have been implemented in two free Web tools.

A highly conserved program of neuronal microexons is misregulated in autistic brains

Alternative splicing (AS) generates vast transcriptomic and proteomic complexity. However, which of the myriad of detected AS events provide important biological functions is not well understood. Here, we define the largest program of functionally coordinated, neural-regulated AS described to date in mammals. Relative to all other types of AS within this program, 3-15 nucleotide "microexons" display the most striking evolutionary conservation and switch-like regulation. These microexons modulate the function of interaction domains of proteins involved in neurogenesis. Most neural microexons are regulated by the neuronal-specific splicing factor nSR100/SRRM4, through its binding to adjacent intronic enhancer motifs. Neural microexons are frequently misregulated in the brains of individuals with autism spectrum disorder, and this misregulation is associated with reduced levels of nSR100. The results thus reveal a highly conserved program of dynamic microexon regulation associated with the remodeling of protein-interaction networks during neurogenesis, the misregulation of which is linked to autism.

Quantitative protein topography analysis and high-resolution structure prediction using hydroxyl radical labeling and tandem-ion mass spectrometry (MS)

Hydroxyl radical footprinting based MS for protein structure assessment has the goal of understanding ligand induced conformational changes and macromolecular interactions, for example, protein tertiary and quaternary structure, but the structural resolution provided by typical peptide-level quantification is limiting. In this work, we present experimental strategies using tandem-MS fragmentation to increase the spatial resolution of the technique to the single residue level to provide a high precision tool for molecular biophysics research. Overall, in this study we demonstrated an eightfold increase in structural resolution compared with peptide level assessments. In addition, to provide a quantitative analysis of residue based solvent accessibility and protein topography as a basis for high-resolution structure prediction; we illustrate strategies of data transformation using the relative reactivity of side chains as a normalization strategy and predict side-chain surface area from the footprinting data. We tested the methods by examination of Ca(+2)-calmodulin showing highly significant correlations between surface area and side-chain contact predictions for individual side chains and the crystal structure. Tandem ion based hydroxyl radical footprinting-MS provides quantitative high-resolution protein topology information in solution that can fill existing gaps in structure determination for large proteins and macromolecular complexes.

Hapten-directed spontaneous disulfide shuffling: a universal technology for site-directed covalent coupling of payloads to antibodies

Humanized hapten-binding IgGs were designed with an accessible cysteine close to their binding pockets, for specific covalent payload attachment. Individual analyses of known structures of digoxigenin (Dig)- and fluorescein (Fluo) binding antibodies and a new structure of a biotin (Biot)-binder, revealed a “universal” coupling position (52⁺²) in proximity to binding pockets but without contributing to hapten interactions. Payloads that carry a free thiol are positioned on the antibody and covalently linked to it via disulfides. Covalent coupling is achieved and driven toward complete (95–100%) payload occupancy by spontaneous redox shuffling between antibody and payload. Attachment at the universal position works with different haptens, antibodies, and payloads. Examples are the haptens Fluo, Dig, and Biot combined with various fluorescent or peptidic payloads. Disulfide-bonded covalent antibody-payload complexes do not dissociate in vitro and in vivo. Coupling requires the designed cysteine and matching payload thiol because payload or antibody without the Cys/thiol are not linked (<5% nonspecific coupling). Hapten-mediated positioning is necessary as hapten-thiol-payload is only coupled to antibodies that bind matching haptens. Covalent complexes are more stable in vivo than noncovalent counterparts because digoxigeninylated or biotinylated fluorescent payloads without disulfide-linkage are cleared more rapidly in mice (approximately 50% reduced 48 hour serum levels) compared with their covalently linked counterparts. The coupling technology is applicable to many haptens and hapten binding antibodies (confirmed by automated analyses of the structures of 140 additional hapten binding antibodies) and can be applied to modulate the pharmacokinetics of small compounds or peptides. It is also suitable to link payloads in a reduction-releasable manner to tumor- or tissue-targeting delivery vehicles.—Dengl, S., Hoffmann, E., Grote, M., Wagner, C., Mundigl, O., Georges, G., Thorey, I., Stubenrauch, K.-G., Bujotzek, A., Josel, H.-P., Dziadek, S., Benz, J., Brinkmann, U. Hapten-directed spontaneous disulfide shuffling: a universal technology for site-directed covalent coupling of payloads to antibodies.

Non-native, N-terminal Hsp70 molecular motor recognition elements in transit peptides support plastid protein translocation

Previously, we identified the N-terminal domain of transit peptides (TPs) as a major determinant for the translocation step in plastid protein import. Analysis of Arabidopsis TP dataset revealed that this domain has two overlapping characteristics, highly uncharged and Hsp70-interacting. To investigate these two properties, we replaced the N-terminal domains of the TP of the small subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase and its reverse peptide with a series of unrelated peptides whose affinities to the chloroplast stromal Hsp70 have been determined. Bioinformatic analysis indicated that eight out of nine peptides in this series are not similar to the TP N terminus. Using in vivo and in vitro protein import assays, the majority of the precursors containing Hsp70-binding elements were targeted to plastids, whereas none of the chimeric precursors lacking an N-terminal Hsp70-binding element were targeted to the plastids. Moreover, a pulse-chase assay showed that two chimeric precursors with the most uncharged peptides failed to translocate into the stroma. The ability of multiple unrelated Hsp70-binding elements to support protein import verified that the majority of TPs utilize an N-terminal Hsp70-binding domain during translocation and expand the mechanistic view of the import process. This work also indicates that synthetic biology may be utilized to create de novo TPs that exceed the targeting activity of naturally occurring sequences.

Photonic activation of plasminogen induced by low dose UVB

Activation of plasminogen to its active form plasmin is essential for several key mechanisms, including the dissolution of blood clots. Activation occurs naturally via enzymatic proteolysis. We report that activation can be achieved with 280 nm light. A 2.6 fold increase in proteolytic activity was observed after 10 min illumination of human plasminogen. Irradiance levels used are in the same order of magnitude of the UVB solar irradiance. Activation is correlated with light induced disruption of disulphide bridges upon UVB excitation of the aromatic residues and with the formation of photochemical products, e.g. dityrosine and N-formylkynurenine. Most of the protein fold is maintained after 10 min illumination since no major changes are observed in the near-UV CD spectrum. Far-UV CD shows loss of secondary structure after illumination (33.4% signal loss at 206 nm). Thermal unfolding CD studies show that plasminogen retains a native like cooperative transition at ~70 ºC after UV-illumination. We propose that UVB activation of plasminogen occurs upon photo-cleavage of a functional allosteric disulphide bond, Cys737-Cys765, located in the catalytic domain and in van der Waals contact with Trp761 (4.3 Å). Such proximity makes its disruption very likely, which may occur upon electron transfer from excited Trp761. Reduction of Cys737-Cys765 will result in likely conformational changes in the catalytic site. Molecular dynamics simulations reveal that reduction of Cys737-Cys765 in plasminogen leads to an increase of the fluctuations of loop 760–765, the S1-entrance frame located close to the active site. These fluctuations affect the range of solvent exposure of the catalytic triad, particularly of Asp646 and Ser74, which acquire an exposure profile similar to the values in plasmin. The presented photonic mechanism of plasminogen activation has the potential to be used in clinical applications, possibly together with other enzymatic treatments for the elimination of blood clots.

Morphological diversity and polymorphism of self-assembling collagen peptides controlled by length of hydrophobic domains

Synthetic collagen mimetic peptides are used to probe the role of hydrophobic forces in mediating protein self-assembly. Higher order association is an integral property of natural collagens, which assemble into fibers and meshes that comprise the extracellular matrix of connective tissues. The unique triple-helix fold fully exposes two-thirds of positions in the protein to solvent, providing ample opportunities for engineering interaction sites. Inclusion of just a few hydrophobic groups in a minimal peptide promotes a rich variety of self-assembly behaviors, resulting in hundred-nanometer to micron size nanodiscs and nanofibers. Morphology depends primarily on the length of hydrophobic domains. Peptide discs contain lipophilic domains capable of sequestering small hydrophobic dyes. Combining multiple peptide types result in composite structures of discs and fibers ranging from stars to plates-on-a-string. These systems provide valuable tools to shed insight into the fundamental principles underlying hydrophobicity-driven higher order protein association that will facilitate the design of self-assembling systems in biomaterials and nanomedical applications.

Tri-peptide reference structures for the calculation of relative solvent accessible surface area in protein amino acid residues

Relative amino acid residue solvent accessibility values allow the quantitative comparison of atomic solvent-accessible surface areas in different residue types and physical environments in proteins and in protein structural alignments. Geometry-optimised tri-peptide structures in extended solvent-exposed reference conformations have been obtained for 43 amino acid residue types at a high level of quantum chemical theory. Significant increases in side-chain solvent accessibility, offset by reductions in main-chain atom solvent exposure, were observed for standard residue types in partially geometry-optimised structures when compared to non-minimised models built from identical sets of proper dihedral angles abstracted from the literature. Optimisation of proper dihedral angles led most notably to marked increases of up to 54% in proline main-chain atom solvent accessibility compared to literature values. Similar effects were observed for fully-optimised tri-peptides in implicit solvent. The relief of internal strain energy was associated with systematic variation in N, C(α) and C(β) atom solvent accessibility across all standard residue types. The results underline the importance of optimisation of 'hard' degrees of freedom (bond lengths and valence bond angles) and improper dihedral angle values from force field or other context-independent reference values, and impact on the use of standardised fixed internal co-ordinate geometry in sampling approaches to the determination of absolute values of protein amino acid residue solvent accessibility. Quantum chemical methods provide a useful and accurate alternative to molecular mechanics methods to perform energy minimisation of peptides containing non-standard (chemically modified) amino acid residues frequently present in experimental protein structure data sets, for which force field parameters may not be available. Reference tri-peptide atomic co-ordinate sets including hydrogen atoms are made freely available.

Peptide backbone effect on hydration free energies of amino acid side chains

We have studied the hydrophobicity of amino acid side chains by computing conditional solvation free energies that account for effects of the peptide backbone on the side chains' solvent environment. The free energies reported herein correspond to a gas-liquid transfer process, which mimics solvation of the side chain under the condition that the backbone has been solvated already, and have been obtained on the basis of free energy calculations with empirical force field models. We find that the peptide backbone strongly impacts the solvation of nonpolar side chains, while its effect on the polar side chains is less pronounced. The results indicate that, in the presence of the short peptide backbone, nonpolar amino acid side chains are less hydrophobic than what is expected based on small molecule (analogue) solvation data.

Interplay between E. coli DnaK, ClpB and GrpE during protein disaggregation

The DnaK/Hsp70 chaperone system and ClpB/Hsp104 collaboratively disaggregate protein aggregates and reactivate inactive proteins. The teamwork is specific: Escherichia coli DnaK interacts with E. coli ClpB and yeast Hsp70, Ssa1, interacts with yeast Hsp104. This interaction is between the middle domains of hexameric ClpB/Hsp104 and the DnaK/Hsp70 nucleotide-binding domain (NBD). To identify the site on E. coli DnaK that interacts with ClpB, we substituted amino acid residues throughout the DnaK NBD. We found that several variants with substitutions in subdomains IB and IIB of the DnaK NBD were defective in ClpB interaction in vivo in a bacterial two-hybrid assay and in vitro in a fluorescence anisotropy assay. The DnaK subdomain IIB mutants were also defective in the ability to disaggregate protein aggregates with ClpB, DnaJ and GrpE, although they retained some ability to reactivate proteins with DnaJ and GrpE in the absence of ClpB. We observed that GrpE, which also interacts with subdomains IB and IIB, inhibited the interaction between ClpB and DnaK in vitro, suggesting competition between ClpB and GrpE for binding DnaK. Computational modeling of the DnaK-ClpB hexamer complex indicated that one DnaK monomer contacts two adjacent ClpB protomers simultaneously. The model and the experiments support a common and mutually exclusive GrpE and ClpB interaction region on DnaK. Additionally, homologous substitutions in subdomains IB and IIB of Ssa1 caused defects in collaboration between Ssa1 and Hsp104. Altogether, these results provide insight into the molecular mechanism of collaboration between the DnaK/Hsp70 system and ClpB/Hsp104 for protein disaggregation.

Improved protocol to purify untagged amelogenin - Application to murine amelogenin containing the equivalent P70→T point mutation observed in human amelogenesis imperfecta

Amelogenin is the predominant extracellular protein responsible for converting carbonated hydroxyapatite into dental enamel, the hardest and most heavily mineralized tissue in vertebrates. Despite much effort, the precise mechanism by which amelogenin regulates enamel formation is not fully understood. To assist efforts aimed at understanding the biochemical mechanism of enamel formation, more facile protocols to purify recombinantly expressed amelogenin, ideally without any tag to assist affinity purification, are advantageous. Here we describe an improved method to purify milligram quantities of amelogenin that exploits its high solubility in 2% glacial acetic acid under conditions of low ionic strength. The method involves heating the frozen cell pellet for two 15min periods at ∼70°C with 2min of sonication in between, dialysis twice in 2% acetic acid (1:250 v/v), and reverse phase chromatography. A further improvement in yield is obtained by resuspending the frozen cell pellet in 6M guanidine hydrochloride in the first step. The acetic acid heating method is illustrated with a murine amelogenin containing the corresponding P70→T point mutation observed in an human amelogenin associated with amelogenesis imperfecta (P71T), while the guanidine hydrochloride heating method is illustrated with wild type murine amelogenin (M180). The self-assembly properties of P71T were probed by NMR chemical shift perturbation studies as a function of protein (0.1-1.8mM) and NaCl (0-367mM) concentration. Relative to similar studies with wild type murine amelogenin, P71T self-associates at lower protein or salt concentrations with the interactions initiated near the N-terminus.

Differential roles of tryptophan residues in the functional expression of human anion exchanger 1 (AE1, Band 3, SLC4A1)

Anion exchanger 1 (AE1) is a 95 kDa glycoprotein that facilitates Cl(-)=HCO(-)(3) exchange across the erythrocyte plasma membrane. This transport activity resides in the 52 kDa C-terminal membrane domain (Gly(361)-Val(911)) predicted to span the membrane 14 times. To explore the role of tryptophan (Trp) residues in AE1 function, the seven endogenous Trp residues in the membrane domain were mutated individually to alanine (Ala) and phenylalanine (Phe). Expression levels, cell surface abundance, inhibitor binding and transport activities of the mutants were measured upon expression in HEK-293 cells. The seven Trp residues divided into three classes according the impact of mutations on the functional expression of AE1: Class 1, dramatically decreased expression (Trp(492) and Trp(496)); Class 2, decreased expression by Ala substitution but not Phe (Trp(648), Trp(662) and Trp(723)); and Class 3, normal expression (Trp(831) and Trp(848)). The results indicate that Trp residues play differential roles in AE1 expression and function depending on their location in the protein and that Trp mutants with low expression are misfolded and retained in the endoplasmic reticulum.

Oxidation of an exposed methionine instigates the aggregation of glyceraldehyde-3-phosphate dehydrogenase

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a ubiquitous and abundant protein that participates in cellular energy production. GAPDH normally exists in a soluble form; however, following necrosis, GAPDH and numerous other intracellular proteins convert into an insoluble disulfide-cross-linked state via the process of "nucleocytoplasmic coagulation." Here, free radical-induced aggregation of GAPDH was studied as an in vitro model of nucleocytoplasmic coagulation. Despite the fact that disulfide cross-linking is a prominent feature of GAPDH aggregation, our data show that it is not a primary rate-determining step. To identify the true instigating event of GAPDH misfolding, we mapped the post-translational modifications that arise during its aggregation. Solvent accessibility and energy calculations of the mapped modifications within the context of the high resolution native GAPDH structure suggested that oxidation of methionine 46 may instigate aggregation. We confirmed this by mutating methionine 46 to leucine, which rendered GAPDH highly resistant to free radical-induced aggregation. Molecular dynamics simulations suggest that oxidation of methionine 46 triggers a local increase in the conformational plasticity of GAPDH that likely promotes further oxidation and eventual aggregation. Hence, methionine 46 represents a "linchpin" whereby its oxidation is a primary event permissive for the subsequent misfolding, aggregation, and disulfide cross-linking of GAPDH. A critical role for linchpin residues in nucleocytoplasmic coagulation and other forms of free radical-induced protein misfolding should now be investigated. Furthermore, because disulfide-cross-linked aggregates of GAPDH arise in many disorders and because methionine 46 is irrelevant to native GAPDH function, mutation of methionine 46 in models of disease should allow the unequivocal assessment of whether GAPDH aggregation influences disease progression.

Modeling the solvation of nonpolar amino acids in guanidinium chloride solutions

It is common to denature proteins by using high temperatures or by adding guanidinium chloride (GdmCl). However, the physical mechanism of denaturation is not well understood. Based on extensive experimental data, we developed a thermodynamic binding-polynomial model for the process of transferring nonpolar amino acids from water into GdmCl solutions, as a function of temperature and GdmCl concentration. To mimic nonpolar amino acids, we utilized the model compound, N-acetyl-tryptophanamide (NATA). We find that all nonpolar amino acids behave like NATA, with a scale factor linearly dependent on the surface area. Our model with three thermodynamic parameters fully captures the nonlinear dependencies on both the temperature and GdmCl concentration: binding the first guanidinium ion (Gdm(+)) to NATA has favorable entropy and unfavorable enthalpy of desolvation (ΔS = +11.7 cal/mol, ΔH = +3.9 kcal/mol), while cooperativity of binding a second Gdm(+) has a small contribution (K = 0.032 ± 0.003). This model may be useful for a better understanding of protein denaturation by temperature and GdmCl.

On the mechanism of cold denaturation

A theoretical rationalization of the occurrence of cold denaturation for globular proteins was devised, assuming that the effective size of water molecules depends upon temperature [G. Graziano, Phys. Chem. Chem. Phys., 2010, 12, 14245-14252]. In the present work, it is shown that the latter assumption is not necessary. By performing the same type of calculations in water, 40% (by weight) methanol, methanol, and carbon tetrachloride, it emerges that cold denaturation occurs only in water due to the special temperature dependence of its density and the small size of its molecules. These two coupled factors determine the magnitude and the temperature dependence of the stabilizing term that measures the gain in configurational/translational entropy of water molecules upon folding of the protein. This term has to be contrasted with the destabilizing contribution measuring the loss in conformational entropy of the polypeptide chain upon folding.

Assessment of protein side-chain conformation prediction methods in different residue environments

Computational prediction of side-chain conformation is an important component of protein structure prediction. Accurate side-chain prediction is crucial for practical applications of protein structure models that need atomic-detailed resolution such as protein and ligand design. We evaluated the accuracy of eight side-chain prediction methods in reproducing the side-chain conformations of experimentally solved structures deposited to the Protein Data Bank. Prediction accuracy was evaluated for a total of four different structural environments (buried, surface, interface, and membrane-spanning) in three different protein types (monomeric, multimeric, and membrane). Overall, the highest accuracy was observed for buried residues in monomeric and multimeric proteins. Notably, side-chains at protein interfaces and membrane-spanning regions were better predicted than surface residues even though the methods did not all use multimeric and membrane proteins for training. Thus, we conclude that the current methods are as practically useful for modeling protein docking interfaces and membrane-spanning regions as for modeling monomers.

Protein folding: understanding the role of water and the low Reynolds number environment as the peptide chain emerges from the ribosome and folds

The mechanism of protein folding during early stages of the process has three determinants. First, moving water molecules obey the rules of low Reynolds number physics without an inertial component. Molecular movement is instantaneous and size insensitive. Proteins emerging from the ribosome move and rotate without an external force if they change shape, forming and propagating helical structures that increases translocational efficiency. Forward motion ceases when the shape change or propelling force ceases. Second, application of quantum field theory to water structure predicts the spontaneous formation of low density coherent units of fixed size that expel dissolved atmospheric gases. Structured water layers with both coherent and non-coherent domains, form a sheath around the new protein. The surface of exposed hydrophobic amino acids is protected from water contact by small nanobubbles of dissolved atmospheric gases, 5 or 6 molecules on average, that vibrate, attracting even widely separated resonating nanobubbles. This force results from quantum effects, appearing only when the system is within and interacts with an oscillating electromagnetic field. The newly recognized quantum force sharply bends the peptide and is part of a dynamic field determining the pathway of protein folding. Third, the force initiating the tertiary folding of proteins arises from twists at the position of each hydrophobic amino acid, that minimizes surface exposure of the hydrophobic amino acids and propagates along the protein. When the total bend reaches 360°, the leading segment of water sheath intersects the trailing segment. This steric self-intersection expels water from overlapping segments of the sheath and by Newton׳s second law moves the polypeptide chain in an opposite direction. Consequently, with very few exceptions that we enumerate and discuss, tertiary structures are absent from proteins without hydrophobic amino acids, which control the early stages of protein folding and the overall shape of protein. Consequently, proteins only adopt a limited number of forms. The formation of quaternary structures is not necessarily prevented by the absence of hydrophobic amino acids.

Adsorption and catalytic activity of glucose oxidase accumulated on OTCE upon the application of external potential

This article describes the adsorption of glucose oxidase (GOx) onto optically transparent carbon electrodes (OTCE) under the effect of applied potential and the analysis of the enzymatic activity of the resulting GOx/OTCE substrates. In order to avoid electrochemical interferences with the enzyme redox center, control electrochemical experiments were performed using flavin adenine dinucleotide (FAD) and GOx/OTCE substrates. Then, the enzyme adsorption experiments were carried out as a function of the potential applied (ranged from the open circuit potential to +950mV), the pH solution, the concentration of enzyme, and the ionic strength on the environment. The experimental results demonstrated that an increase in the adsorbed amount of GOx on the OTCE can be achieved when the potential was applied. Although the increase in the adsorbed amount was examined as a function of the potential, a maximum enzymatic activity was observed in the GOx/OTCE substrate achieved at +800mV. These experiments suggest that although an increase in the amount of enzyme adsorbed can be obtained by the application of an external potential to the electrode, the magnitude of such potential can produce detrimental effects in the conformation of the adsorbed protein and should be carefully considered. As such, the article describes a simple and rational approach to increase the amount of enzyme adsorbed on a surface and can be applied to improve the sensitivity of a variety of biosensors.

CRF-based models of protein surfaces improve protein-protein interaction site predictions

Background

The identification of protein-protein interaction sites is a computationally challenging task and important for understanding the biology of protein complexes. There is a rich literature in this field. A broad class of approaches assign to each candidate residue a real-valued score that measures how likely it is that the residue belongs to the interface. The prediction is obtained by thresholding this score.

Some probabilistic models classify the residues on the basis of the posterior probabilities. In this paper, we introduce pairwise conditional random fields (pCRFs) in which edges are not restricted to the backbone as in the case of linear-chain CRFs utilized by Li et al. (2007). In fact, any 3D-neighborhood relation can be modeled. On grounds of a generalized Viterbi inference algorithm and a piecewise training process for pCRFs, we demonstrate how to utilize pCRFs to enhance a given residue-wise score-based protein-protein interface predictor on the surface of the protein under study. The features of the pCRF are solely based on the interface predictions scores of the predictor the performance of which shall be improved.

Results

We performed three sets of experiments with synthetic scores assigned to the surface residues of proteins taken from the data set PlaneDimers compiled by Zellner et al. (2011), from the list published by Keskin et al. (2004) and from the very recent data set due to Cukuroglu et al. (2014). That way we demonstrated that our pCRF-based enhancer is effective given the interface residue score distribution and the non-interface residue score are unimodal.

Moreover, the pCRF-based enhancer is also successfully applicable, if the distributions are only unimodal over a certain sub-domain. The improvement is then restricted to that domain. Thus we were able to improve the prediction of the PresCont server devised by Zellner et al. (2011) on PlaneDimers.

Conclusions

Our results strongly suggest that pCRFs form a methodological framework to improve residue-wise score-based protein-protein interface predictors given the scores are appropriately distributed. A prototypical implementation of our method is accessible at http://ppicrf.informatik.uni-goettingen.de/index.html.

Diverse and divergent protein post-translational modifications in two growth stages of a natural microbial community

Detailed characterization of post-translational modifications (PTMs) of proteins in microbial communities remains a significant challenge. Here we directly identify and quantify a broad range of PTMs (hydroxylation, methylation, citrullination, acetylation, phosphorylation, methylthiolation, S-nitrosylation and nitration) in a natural microbial community from an acid mine drainage site. Approximately 29% of the identified proteins of the dominant Leptospirillum group II bacteria are modified, and 43% of modified proteins carry multiple PTM types. Most PTM events, except S-nitrosylations, have low fractional occupancy. Notably, PTM events are detected on Cas proteins involved in antiviral defense, an aspect of Cas biochemistry not considered previously. Further, Cas PTM profiles from Leptospirillum group II differ in early versus mature biofilms. PTM patterns are divergent on orthologues of two closely related, but ecologically differentiated, Leptospirillum group II bacteria. Our results highlight the prevalence and dynamics of PTMs of proteins, with potential significance for ecological adaptation and microbial evolution.

Local packing density is the main structural determinant of the rate of protein sequence evolution at site level

Functional and biophysical constraints result in site-dependent patterns of protein sequence variability. It is commonly assumed that the key structural determinant of site-specific rates of evolution is the Relative Solvent Accessibility (RSA). However, a recent study found that amino acid substitution rates correlate better with two Local Packing Density (LPD) measures, the Weighted Contact Number (WCN) and the Contact Number (CN), than with RSA. This work aims at a more thorough assessment. To this end, in addition to substitution rates, we considered four other sequence variability scores, four measures of solvent accessibility (SA), and other CN measures. We compared all properties for each protein of a structurally and functionally diverse representative dataset of monomeric enzymes. We show that the best sequence variability measures take into account phylogenetic tree topology. More importantly, we show that both LPD measures (WCN and CN) correlate better than all of the SA measures, regardless of the sequence variability score used. Moreover, the independent contribution of the best LPD measure is approximately four times larger than that of the best SA measure. This study strongly supports the conclusion that a site's packing density rather than its solvent accessibility is the main structural determinant of its rate of evolution.

Moving gating charges through the gating pore in a Kv channel voltage sensor

Voltage sensor domains (VSDs) regulate ion channels and enzymes by transporting electrically charged residues across a hydrophobic VSD constriction called the gating pore or hydrophobic plug. How the gating pore controls the gating charge movement presently remains debated. Here, using saturation mutagenesis and detailed analysis of gating currents from gating pore mutations in the Shaker Kv channel, we identified statistically highly significant correlations between VSD function and physicochemical properties of gating pore residues. A necessary small residue at position S240 in S1 creates a "steric gap" that enables an intracellular access pathway for the transport of the S4 Arg residues. In addition, the stabilization of the depolarized VSD conformation, a hallmark for most Kv channels, requires large side chains at positions F290 in S2 and F244 in S1 acting as "molecular clamps," and a hydrophobic side chain at position I237 in S1 acting as a local intracellular hydrophobic barrier. Finally, both size and hydrophobicity of I287 are important to control the main VSD energy barrier underlying transitions between resting and active states. Taken together, our study emphasizes the contribution of several gating pore residues to catalyze the gating charge transfer. This work paves the way toward understanding physicochemical principles underlying conformational dynamics in voltage sensors.

Evidence of positive selection in mitochondrial complexes I and V of the African elephant

As species evolve, they become adapted to their local environments. Detecting the genetic signature of selection and connecting that to the phenotype of the organism, however, is challenging. Here we report using an integrative approach that combines DNA sequencing with structural biology analyses to assess the effect of selection on residues in the mitochondrial DNA of the two species of African elephants. We detected evidence of positive selection acting on residues in complexes I and V, and we used homology protein structure modeling to assess the effect of the biochemical properties of the selected residues on the enzyme structure. Given the role these enzymes play in oxidative phosphorylation, we propose that the selected residues may contribute to the metabolic adaptation of forest and savanna elephants to their unique habitats.

Practical aspects of NMR signal assignment in larger and challenging proteins

NMR has matured into a technique routinely employed for studying proteins in near physiological conditions. However, applications to larger proteins are impeded by the complexity of the various correlation maps necessary to assign NMR signals. This article reviews the data analysis techniques traditionally employed for resonance assignment and describes alternative protocols necessary for overcoming challenges in large protein spectra. In particular, simultaneous analysis of multiple spectra may help overcome ambiguities or may reveal correlations in an indirect manner. Similarly, visualization of orthogonal planes in a multidimensional spectrum can provide alternative assignment procedures. We describe examples of such strategies for assignment of backbone, methyl, and nOe resonances. We describe experimental aspects of data acquisition for the related experiments and provide guidelines for preliminary studies. Focus is placed on large folded monomeric proteins and examples are provided for 37, 48, 53, and 81 kDa proteins.

Distinct phenotype of a Wilson disease mutation reveals a novel trafficking determinant in the copper transporter ATP7B

Wilson disease (WD) is a monogenic autosomal-recessive disorder of copper accumulation that leads to liver failure and/or neurological deficits. WD is caused by mutations in ATP7B, a transporter that loads Cu(I) onto newly synthesized cupro-enzymes in the trans-Golgi network (TGN) and exports excess copper out of cells by trafficking from the TGN to the plasma membrane. To date, most WD mutations have been shown to disrupt ATP7B activity and/or stability. Using a multidisciplinary approach, including clinical analysis of patients, cell-based assays, and computational studies, we characterized a patient mutation, ATP7B(S653Y), which is stable, does not disrupt Cu(I) transport, yet renders the protein unable to exit the TGN. Bulky or charged substitutions at position 653 mimic the phenotype of the patient mutation. Molecular modeling and dynamic simulation suggest that the S653Y mutation induces local distortions within the transmembrane (TM) domain 1 and alter TM1 interaction with TM2. S653Y abolishes the trafficking-stimulating effects of a secondary mutation in the N-terminal apical targeting domain. This result indicates a role for TM1/TM2 in regulating conformations of cytosolic domains involved in ATP7B trafficking. Taken together, our experiments revealed an unexpected role for TM1/TM2 in copper-regulated trafficking of ATP7B and defined a unique class of WD mutants that are transport-competent but trafficking-defective. Understanding the precise consequences of WD-causing mutations will facilitate the development of advanced mutation-specific therapies.

Structure of allergens and structure based epitope predictions

The structure determination of major allergens is a prerequisite for analyzing surface exposed areas of the allergen and for mapping conformational epitopes. These may be determined by experimental methods including crystallographic and NMR-based approaches or predicted by computational methods. In this review we summarize the existing structural information on allergens and their classification in protein fold families. The currently available allergen-antibody complexes are described and the experimentally obtained epitopes compared. Furthermore we discuss established methods for linear and conformational epitope mapping, putting special emphasis on a recently developed approach, which uses the structural similarity of proteins in combination with the experimental cross-reactivity data for epitope prediction.

Improving the chances of successful protein structure determination with a random forest classifier

Obtaining diffraction quality crystals remains one of the major bottlenecks in structural biology. The ability to predict the chances of crystallization from the amino-acid sequence of the protein can, at least partly, address this problem by allowing a crystallographer to select homologs that are more likely to succeed and/or to modify the sequence of the target to avoid features that are detrimental to successful crystallization. In 2007, the now widely used XtalPred algorithm [Slabinski et al. (2007), Protein Sci. 16, 2472-2482] was developed. XtalPred classifies proteins into five `crystallization classes' based on a simple statistical analysis of the physicochemical features of a protein. Here, towards the same goal, advanced machine-learning methods are applied and, in addition, the predictive potential of additional protein features such as predicted surface ruggedness, hydrophobicity, side-chain entropy of surface residues and amino-acid composition of the predicted protein surface are tested. The new XtalPred-RF (random forest) achieves significant improvement of the prediction of crystallization success over the original XtalPred. To illustrate this, XtalPred-RF was tested by revisiting target selection from 271 Pfam families targeted by the Joint Center for Structural Genomics (JCSG) in PSI-2, and it was estimated that the number of targets entered into the protein-production and crystallization pipeline could have been reduced by 30% without lowering the number of families for which the first structures were solved. The prediction improvement depends on the subset of targets used as a testing set and reaches 100% (i.e. twofold) for the top class of predicted targets.

Atomic and dynamic insights into the beneficial effect of the 1,4-naphthoquinon-2-yl-L-tryptophan inhibitor on Alzheimer's Aβ1-42 dimer in terms of aggregation and toxicity

Aggregation of the amyloid β protein (Aβ) peptide with 40 or 42 residues is one key feature in Alzheimer's disease (AD). The 1,4-naphthoquinon-2-yl-L-tryptophan (NQTrp) molecule was reported to alter Aβ self-assembly and reduce toxicity. Though nuclear magnetic resonance experiments and various simulations provided atomic information about the interaction of NQTrp with Aβ peptides spanning the regions of residues 12-28 and 17-42, none of these studies were conducted on the full-length Aβ1-42 peptide. To this end, we performed extensive atomistic replica exchange molecular dynamics simulations of Aβ1-42 dimer with two NQTrp molecules in explicit solvent, by using a force field known to fold diverse proteins correctly. The interactions between NQTrp and Aβ1-42, which change the Aβ interface by reducing most of the intermolecular contacts, are found to be very dynamic and multiple, leading to many transient binding sites. The most favorable binding residues are Arg5, Asp7, Tyr10, His13, Lys16, Lys18, Phe19/Phe20, and Leu34/Met35, providing therefore a completely different picture from in vitro and in silico experiments with NQTrp with shorter Aβ fragments. Importantly, the 10 hot residues that we identified explain the beneficial effect of NQTrp in reducing both the level of Aβ1-42 aggregation and toxicity. Our results also indicate that there is room to design more efficient drugs targeting Aβ1-42 dimer against AD.

Rheostats and toggle switches for modulating protein function

The millions of protein sequences generated by genomics are expected to transform protein engineering and personalized medicine. To achieve these goals, tools for predicting outcomes of amino acid changes must be improved. Currently, advances are hampered by insufficient experimental data about nonconserved amino acid positions. Since the property “nonconserved” is identified using a sequence alignment, we designed experiments to recapitulate that context: Mutagenesis and functional characterization was carried out in 15 LacI/GalR homologs (rows) at 12 nonconserved positions (columns). Multiple substitutions were made at each position, to reveal how various amino acids of a nonconserved column were tolerated in each protein row. Results showed that amino acid preferences of nonconserved positions were highly context-dependent, had few correlations with physico-chemical similarities, and were not predictable from their occurrence in natural LacI/GalR sequences. Further, unlike the “toggle switch” behaviors of conserved positions, substitutions at nonconserved positions could be rank-ordered to show a “rheostatic”, progressive effect on function that spanned several orders of magnitude. Comparisons to various sequence analyses suggested that conserved and strongly co-evolving positions act as functional toggles, whereas other important, nonconserved positions serve as rheostats for modifying protein function. Both the presence of rheostat positions and the sequence analysis strategy appear to be generalizable to other protein families and should be considered when engineering protein modifications or predicting the impact of protein polymorphisms.

Exploring the composition of protein-ligand binding sites on a large scale

The residue composition of a ligand binding site determines the interactions available for diffusion-mediated ligand binding, and understanding general composition of these sites is of great importance if we are to gain insight into the functional diversity of the proteome. Many structure-based drug design methods utilize such heuristic information for improving prediction or characterization of ligand-binding sites in proteins of unknown function. The Binding MOAD database if one of the largest curated sets of protein-ligand complexes, and provides a source of diverse, high-quality data for establishing general trends of residue composition from currently available protein structures. We present an analysis of 3,295 non-redundant proteins with 9,114 non-redundant binding sites to identify residues over-represented in binding regions versus the rest of the protein surface. The Binding MOAD database delineates biologically-relevant “valid” ligands from “invalid” small-molecule ligands bound to the protein. Invalids are present in the crystallization medium and serve no known biological function. Contacts are found to differ between these classes of ligands, indicating that residue composition of biologically relevant binding sites is distinct not only from the rest of the protein surface, but also from surface regions capable of opportunistic binding of non-functional small molecules. To confirm these trends, we perform a rigorous analysis of the variation of residue propensity with respect to the size of the dataset and the content bias inherent in structure sets obtained from a large protein structure database. The optimal size of the dataset for establishing general trends of residue propensities, as well as strategies for assessing the significance of such trends, are suggested for future studies of binding-site composition.

Describing the general structure of protein binding sites is fundamentally important for guiding drug design and better understanding structure-function relationships. Here, we analyze small molecules bound to proteins within our large database, Binding MOAD (Mother of All Databases, pronounced like “mode” as a pun referring to ligand-binding modes). We focus on different contacts across the residues in the binding sites, and we normalize the data relative to the protein's entire surface. A key feature of this study is the use of a “control” where we compare real, functional binding sites to the random contacts seen for crystallographic additives against the protein surface. Controls are required in experimental biology, but they are ill-defined in many computational approaches. This allows us to describe how true binding sites are unique on the protein surface and distinct from random patches that attract common, small molecules.

Maximum allowed solvent accessibilites of residues in proteins

The relative solvent accessibility (RSA) of a residue in a protein measures the extent of burial or exposure of that residue in the 3D structure. RSA is frequently used to describe a protein's biophysical or evolutionary properties. To calculate RSA, a residue's solvent accessibility (ASA) needs to be normalized by a suitable reference value for the given amino acid; several normalization scales have previously been proposed. However, these scales do not provide tight upper bounds on ASA values frequently observed in empirical crystal structures. Instead, they underestimate the largest allowed ASA values, by up to 20%. As a result, many empirical crystal structures contain residues that seem to have RSA values in excess of one. Here, we derive a new normalization scale that does provide a tight upper bound on observed ASA values. We pursue two complementary strategies, one based on extensive analysis of empirical structures and one based on systematic enumeration of biophysically allowed tripeptides. Both approaches yield congruent results that consistently exceed published values. We conclude that previously published ASA normalization values were too small, primarily because the conformations that maximize ASA had not been correctly identified. As an application of our results, we show that empirically derived hydrophobicity scales are sensitive to accurate RSA calculation, and we derive new hydrophobicity scales that show increased correlation with experimentally measured scales.

Bulkiness or aromatic nature of tyrosine-143 of actin is important for the weak binding between F-actin and myosin-ADP-phosphate

Actin filaments (F-actin) interact with myosin and activate its ATPase to support force generation. By comparing crystal structures of G-actin and the quasi-atomic model of F-actin based on high-resolution cryo-electron microscopy, the tyrosine-143 was found to be exposed more than 60Å(2) to the solvent in F-actin. Because tyrosine-143 flanks the hydrophobic cleft near the hydrophobic helix that binds to myosin, the mutant actins, of which the tyrosine-143 was replaced with tryptophan, phenylalanine, or isoleucine, were generated using the Dictyostelium expression system. It polymerized significantly poorly when induced by NaCl, but almost normally by KCl. In the presence of phalloidin and KCl, the extents of the polymerization of all the mutant actins were comparable to that of the wild-type actin so that the actin-activated myosin ATPase activity could be reliably compared. The affinity of skeletal heavy meromyosin to F-actin and the maximum ATPase activity (Vmax) were estimated by a double reciprocal plot. The Tyr143Trp-actin showed the higher affinity (smaller Kapp) than that of the wild-type actin, with the Vmax being almost unchanged. The Kapp and Vmax of the Tyr143Phe-actin were similar to those of the wild-type actin. However, the activation by Tyr143Ile-actin was much smaller than the wild-type actin and the accurate determination of Kapp was difficult. Comparison of the myosin ATPase activated by the various mutant actins at the same concentration of F-actin showed that the extent of activation correlates well with the solvent-accessible surface areas (ASA) of the replaced amino acid molecule. Because 1/Kapp reflects the affinity of F-actin for the myosin-ADP-phosphate intermediate (M.ADP.Pi) through the weak binding, these data suggest that the bulkiness or the aromatic nature of the tyrosin-143 is important for the initial binding of the M.ADP.Pi intermediate with F-actin but not for later processes such as the phosphate release.

Solvent-accessible surface area: How well can be applied to hot-spot detection?

A detailed comprehension of protein-based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA-based features for their ability to correlate and differentiate hot- and null-spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot- and null-spots, while presenting low correlations. Residue standardization such as rel SASAi or rel/res SASAi , improved the features as a tool to predict ΔΔGbinding values. A new method using support machine learning algorithms was developed: SBHD (Sasa-Based Hot-spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set.

Lipid exposure prediction enhances the inference of rotational angles of transmembrane helices

Background

Since membrane protein structures are challenging to crystallize, computational approaches are essential for elucidating the sequence-to-structure relationships. Structural modeling of membrane proteins requires a multidimensional approach, and one critical geometric parameter is the rotational angle of transmembrane helices. Rotational angles of transmembrane helices are characterized by their folded structures and could be inferred by the hydrophobic moment; however, the folding mechanism of membrane proteins is not yet fully understood. The rotational angle of a transmembrane helix is related to the exposed surface of a transmembrane helix, since lipid exposure gives the degree of accessibility of each residue in lipid environment. To the best of our knowledge, there have been few advances in investigating whether an environment descriptor of lipid exposure could infer a geometric parameter of rotational angle.

Results

Here, we present an analysis of the relationship between rotational angles and lipid exposure and a support-vector-machine method, called TMexpo, for predicting both structural features from sequences. First, we observed from the development set of 89 protein chains that the lipid exposure, i.e., the relative accessible surface area (rASA) of residues in the lipid environment, generated from high-resolution protein structures could infer the rotational angles with a mean absolute angular error (MAAE) of 46.32˚. More importantly, the predicted rASA from TMexpo achieved an MAAE of 51.05˚, which is better than 71.47˚ obtained by the best of the compared hydrophobicity scales. Lastly, TMexpo outperformed the compared methods in rASA prediction on the independent test set of 21 protein chains and achieved an overall Matthew’s correlation coefficient, accuracy, sensitivity, specificity, and precision of 0.51, 75.26%, 81.30%, 69.15%, and 72.73%, respectively. TMexpo is publicly available at http://bio-cluster.iis.sinica.edu.tw/TMexpo.

Conclusions

TMexpo can better predict rASA and rotational angles than the compared methods. When rotational angles can be accurately predicted, free modeling of transmembrane protein structures in turn may benefit from a reduced complexity in ensembles with a significantly less number of packing arrangements. Furthermore, sequence-based prediction of both rotational angle and lipid exposure can provide essential information when high-resolution structures are unavailable and contribute to experimental design to elucidate transmembrane protein functions.