Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

Distances and classification of amino acids for different protein secondary structures

Window profiles of amino acids in protein sequences are taken as a description of the amino acid environment. The relative entropy or Kullback-Leibler distance derived from profiles is used as a measure of dissimilarity for comparison of amino acids and secondary structure conformations. Distance matrices of amino acid pairs at different conformations are obtained, which display a non-negligible dependence of amino acid similarity on conformations. Based on the conformation specific distances clustering analysis for amino acids is conducted.Comment: 15 pages, 8 figure

Probing protein sequences as sources for encrypted antimicrobial peptides

Starting from the premise that a wealth of potentially biologically active peptides may lurk within proteins, we describe here a methodology to identify putative antimicrobial peptides encrypted in protein sequences. Candidate peptides were identified using a new screening procedure based on physicochemical criteria to reveal matching peptides within protein databases. Fifteen such peptides, along with a range of natural antimicrobial peptides, were examined using DSC and CD to characterize their interaction with phospholipid membranes. Principal component analysis of DSC data shows that the investigated peptides group according to their effects on the main phase transition of phospholipid vesicles, and that these effects correlate both to antimicrobial activity and to the changes in peptide secondary structure. Consequently, we have been able to identify novel antimicrobial peptides from larger proteins not hitherto associated with such activity, mimicking endogenous and/or exogenous microorganism enzymatic processing of parent proteins to smaller bioactive molecules. A biotechnological application for this methodology is explored. Soybean (Glycine max) plants, transformed to include a putative antimicrobial protein fragment encoded in its own genome were tested for tolerance against Phakopsora pachyrhizi, the causative agent of the Asian soybean rust. This procedure may represent an inventive alternative to the transgenic technology, since the genetic material to be used belongs to the host organism and not to exogenous sources

Structural prediction and in silico physicochemical characterization for mouse caltrin I and bovine caltrin proteins

It is known that caltrin (calcium transport inhibitor) protein binds to sperm cells during ejaculation and inhibits extracellular Ca2+ uptake. Although the sequence and some biological features of mouse caltrin I and bovine caltrin are known, their physicochemical properties and tertiary structure are mainly unknown. We predicted the 3D structures of mouse caltrin I and bovine caltrin by molecular homology modeling and threading. Surface electrostatic potentials and electric fields were calculated using the Poisson–Boltzmann equation. Several different bioinformatics tools and available web servers were used to thoroughly analyze the physicochemical characteristics of both proteins, such as their Kyte and Doolittle hydropathy scores and helical wheel projections. The results presented in this work significantly aid further understanding of the molecular mechanisms of caltrin proteins modulating physiological processes associated with fertilization.Fil: Grasso, Ernesto Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; ArgentinaFil: Sottile, Adolfo Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; ArgentinaFil: Coronel, Carlos Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentin

Empirical Potential Function for Simplified Protein Models: Combining Contact and Local Sequence-Structure Descriptors

An effective potential function is critical for protein structure prediction and folding simulation. Simplified protein models such as those requiring only $C_\alpha$ or backbone atoms are attractive because they enable efficient search of the conformational space. We show residue specific reduced discrete state models can represent the backbone conformations of proteins with small RMSD values. However, no potential functions exist that are designed for such simplified protein models. In this study, we develop optimal potential functions by combining contact interaction descriptors and local sequence-structure descriptors. The form of the potential function is a weighted linear sum of all descriptors, and the optimal weight coefficients are obtained through optimization using both native and decoy structures. The performance of the potential function in test of discriminating native protein structures from decoys is evaluated using several benchmark decoy sets. Our potential function requiring only backbone atoms or $C_\alpha$ atoms have comparable or better performance than several residue-based potential functions that require additional coordinates of side chain centers or coordinates of all side chain atoms. By reducing the residue alphabets down to size 5 for local structure-sequence relationship, the performance of the potential function can be further improved. Our results also suggest that local sequence-structure correlation may play important role in reducing the entropic cost of protein folding.Comment: 20 pages, 5 figures, 4 tables. In press, Protein

Electron capture dissociation product ion abundances at the X amino acid in RAAAA-X-AAAAK peptides correlate with amino acid polarity and radical stability

We present mechanistic studies aimed at improving the understanding of the product ion formation rules in electron capture dissociation (ECD) of peptides and proteins in Fourier transform ion cyclotron resonance mass spectrometry. In particular, we attempted to quantify the recently reported general correlation of ECD product ion abundance (PIA) with amino acid hydrophobicity. The results obtained on a series of model H-RAAAAXAAAAK-OH peptides confirm a direct correlation of ECD PIA with X amino acid hydrophobicity and polarity. The correlation factor (R) exceeds 0.9 for 12 amino acids (Ile, Val, His, Asn, Asp, Glu, Gln, Ser, Thr, Gly, Cys, and Ala). The deviation of ECD PIA for seven outliers (Pro is not taken into consideration) is explained by their specific radical stabilization properties (Phe, Trp, Tyr, Met, and Leu) and amino acid basicity (Lys, Arg). Phosphorylation of Ser, Thr, and Tyr decreases the efficiency of ECD around phosphorylated residues, as expected. The systematic arrangement of amino acids reported here indicates a possible route toward development of a predictive model for quantitative electron capture/transfer dissociation tandem mass spectrometry, with possible applications in proteomic

Prediction of protein motions from amino acid sequence and its application to protein-protein interaction

BACKGROUND: Structural flexibility is an important characteristic of proteins because it is often associated with their function. The movement of a polypeptide segment in a protein can be broken down into two types of motions: internal and external ones. The former is deformation of the segment itself, but the latter involves only rotational and translational motions as a rigid body. Normal Model Analysis (NMA) can derive these two motions, but its application remains limited because it necessitates the gathering of complete structural information. RESULTS: In this work, we present a novel method for predicting two kinds of protein motions in ordered structures. The prediction uses only information from the amino acid sequence. We prepared a dataset of the internal and external motions of segments in many proteins by application of NMA. Subsequently, we analyzed the relation between thermal motion assessed from X-ray crystallographic B-factor and internal/external motions calculated by NMA. Results show that attributes of amino acids related to the internal motion have different features from those related to the B-factors, although those related to the external motion are correlated strongly with the B-factors. Next, we developed a method to predict internal and external motions from amino acid sequences based on the Random Forest algorithm. The proposed method uses information associated with adjacent amino acid residues and secondary structures predicted from the amino acid sequence. The proposed method exhibited moderate correlation between predicted internal and external motions with those calculated by NMA. It has the highest prediction accuracy compared to a naïve model and three published predictors. CONCLUSIONS: Finally, we applied the proposed method predicting the internal motion to a set of 20 proteins that undergo large conformational change upon protein-protein interaction. Results show significant overlaps between the predicted high internal motion regions and the observed conformational change regions

Functional and Immunological Relevance of Anaplasma marginale Major Surface Protein 1a Sequence and Structural Analysis.

Bovine anaplasmosis is caused by cattle infection with the tick-borne bacterium, Anaplasma marginale. The major surface protein 1a (MSP1a) has been used as a genetic marker for identifying A. marginale strains based on N-terminal tandem repeats and a 5'-UTR microsatellite located in the msp1a gene. The MSP1a tandem repeats contain immune relevant elements and functional domains that bind to bovine erythrocytes and tick cells, thus providing information about the evolution of host-pathogen and vector-pathogen interactions. Here we propose one nomenclature for A. marginale strain classification based on MSP1a. All tandem repeats among A. marginale strains were classified and the amino acid variability/frequency in each position was determined. The sequence variation at immunodominant B cell epitopes was determined and the secondary (2D) structure of the tandem repeats was modeled. A total of 224 different strains of A. marginale were classified, showing 11 genotypes based on the 5'-UTR microsatellite and 193 different tandem repeats with high amino acid variability per position. Our results showed phylogenetic correlation between MSP1a sequence, secondary structure, B-cell epitope composition and tick transmissibility of A. marginale strains. The analysis of MSP1a sequences provides relevant information about the biology of A. marginale to design vaccines with a cross-protective capacity based on MSP1a B-cell epitopes

Interactions of Poly(amidoamine) Dendrimers with Human Serum Albumin: Binding Constants and Mechanisms

The interactions of nanomaterials with plasma proteins have a significant impact on their in vivo transport and fate in biological fluids. This article discusses the binding of human serum albumin (HSA) to poly(amidoamine) [PAMAM] dendrimers. We use protein-coated silica particles to measure the HSA binding constants (K_b) of a homologous series of 19 PAMAM dendrimers in aqueous solutions at physiological pH (7.4) as a function of dendrimer generation, terminal group, and core chemistry. To gain insight into the mechanisms of HSA binding to PAMAM dendrimers, we combined ^1H NMR, saturation transfer difference (STD) NMR, and NMR diffusion ordered spectroscopy (DOSY) of dendrimer−HSA complexes with atomistic molecular dynamics (MD) simulations of dendrimer conformation in aqueous solutions. The binding measurements show that the HSA binding constants (K_b) of PAMAM dendrimers depend on dendrimer size and terminal group chemistry. The NMR ^1H and DOSY experiments indicate that the interactions between HSA and PAMAM dendrimers are relatively weak. The ^1H NMR STD experiments and MD simulations suggest that the inner shell protons of the dendrimers groups interact more strongly with HSA proteins. These interactions, which are consistently observed for different dendrimer generations (G0-NH_2vs G4-NH_2) and terminal groups (G4-NH_2vs G4-OH with amidoethanol groups), suggest that PAMAM dendrimers adopt backfolded configurations as they form weak complexes with HSA proteins in aqueous solutions at physiological pH (7.4)