Secondary Structure Information Research Articles

Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria.

We have determined refined multidimensional chemical shift ranges for intra-residue correlations ((13)C-(13)C, (15)N-(13)C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 (13)C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited "hand-picked" data sets, we show that ~94% of the (13)C NMR data and almost all (15)N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6% of the (13)C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. -2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra-residue cross peaks by inspection or by using a provided command-line Python script (PLUQin), which should be useful in protein structure determination. The refined chemical shift distributions are utilized in a simple quality test (SQAT) that should be applied to new protein NMR data before deposition in a databank, and they could benefit many other chemical-shift based tools.

A Novel Prediction Method of Protein Structural Classes Based on Protein Super-Secondary Structure

At present, the feature extraction of protein sequences is the most basic issue to predict protein structural classes and is also the key problem to decide the quality of prediction. In order to predict protein structural classes accurately, we construct a 14-dimensional feature vector based on protein secondary and super-secondary structure information to reflect the content and spatial ordering of the given protein sequences. Among the vector, seven features about -helix bundle, hairpin motifs, Rossman folds, -plaits and other super-secondary structure information are first proposed in our paper. Experiments show that our method improves overall accuracy of lower similarity datasets 1189 and 640 by 0.9% - 3.8% and 0.5% - 4.2% respectively compared with other methods and has a competitive advantage for predicting proteins in and classes.

Heteronuclear Multidimensional Protein NMR in a Teaching Laboratory

Heteronuclear multidimensional NMR techniques are commonly used to study protein structure, function, and dynamics, yet they are rarely taught at the undergraduate level. Here, we describe a senior undergraduate laboratory where students collect, process, and analyze heteronuclear multidimensional NMR experiments using an unstudied Ig domain (Ig2 of human obscurin) in order to sequence-specifically assign this domain. In this way, this project-oriented laboratory tries to simulate an authentic biomolecular NMR research experience. Through the semester, students gain a more thorough understanding of both the specific technical aspects of multidimensional NMR analysis and the process by which raw data are converted into sequence-specific secondary structural information.

Backbone assignment of the N-terminal 24-kDa fragment of Escherichia coli topoisomerase IV ParE subunit.

Bacterial DNA topoisomerases are important drug targets due to their importance in DNA replication and low homology to human topoisomerases. The N-terminal 24 kDa region of E. coli topoisomerase IV E subunit (eParE) contains the ATP binding pocket. Structure-based drug discovery has been proven to be an efficient way to develop potent ATP competitive inhibitors against ParEs. NMR spectroscopy is a powerful tool to understand protein and inhibitor interactions in solution. In this study, we report the backbone assignment for the N-terminal domain of E. coli ParE. The secondary structural information and the assignment will aid in structure-based antibacterial agents development targeting eParE.

Residual occurrence and energy property of proteins in HNP model**Project supported by the National Natural Science Foundation of China (Grant Nos. 21204078, 11304282, and 11202201) and the Natural Science Foundation of Zhejiang Province, China (Grant No. LY12B04003).

Four categories of globular proteins, including all-α, all-β, α + β, and α/β types, are simplified as the off-lattice HNP model involving the secondary-structural information of each protein. The propensity of three types of residues, i.e., H, N, and P to form a secondary structure is investigated based on 146 protein samples. We find that P residues are easy to form α-helices, whereas H residues have a higher tendency to construct β-sheets. The statistical analysis also indicates that the occurrence of P residues is invariably higher than that of H residues, which is independent of protein category. Changes in bond- and non-bonded potential energies of all protein samples under a wide temperature range are presented by coarse-grained molecular dynamics (MD) simulation. The simulation results clearly show a linear relationship between the bond-stretching/bending potential energy and the reduced temperature. The bond-torsional and non-bonded potential energies show distinct transitions with temperature. The bond-torsional energy increases to the maximum and then decreases with the increase of temperature, which is opposite to the change in non-bonded potential energy. The transition temperature of non-bonded potential energy is independent of the protein category, while that of bond-torsional energy is closely related to the protein secondary structure, i.e., α-helix or β-sheet. The quantitatively bonded- and semi-quantitatively non-bonded potential energy of 24 α + β and 23 α/β protein samples are successfully predicted according to the statistical results obtained from MD simulations.

Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction.

Despite the biological importance of non-coding RNA, their structural characterization remains challenging. Making use of the rapidly growing sequence databases, we analyze nucleotide coevolution across homologous sequences via Direct-Coupling Analysis to detect nucleotide-nucleotide contacts. For a representative set of riboswitches, we show that the results of Direct-Coupling Analysis in combination with a generalized Nussinov algorithm systematically improve the results of RNA secondary structure prediction beyond traditional covariance approaches based on mutual information. Even more importantly, we show that the results of Direct-Coupling Analysis are enriched in tertiary structure contacts. By integrating these predictions into molecular modeling tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone.

APTANI: a computational tool to select aptamers through sequence-structure motif analysis of HT-SELEX data.

Aptamers are synthetic nucleic acid molecules that can bind biological targets in virtue of both their sequence and three-dimensional structure. Aptamers are selected using SELEX, Systematic Evolution of Ligands by EXponential enrichment, a technique that exploits aptamer-target binding affinity. The SELEX procedure, coupled with high-throughput sequencing (HT-SELEX), creates billions of random sequences capable of binding different epitopes on specific targets. Since this technique produces enormous amounts of data, computational analysis represents a critical step to screen and select the most biologically relevant sequences. Here, we present APTANI, a computational tool to identify target-specific aptamers from HT-SELEX data and secondary structure information. APTANI builds on AptaMotif algorithm, originally implemented to analyze SELEX data; extends the applicability of AptaMotif to HT-SELEX data and introduces new functionalities, as the possibility to identify binding motifs, to cluster aptamer families or to compare output results from different HT-SELEX cycles. Tabular and graphical representations facilitate the downstream biological interpretation of results. APTANI is available at http://aptani.unimore.it. silvio.bicciato@unimore.it Supplementary data are available at Bioinformatics online.

Gobernabilidad del agua en Colombia: dimensiones y contexto

El presente documento busca establecer la condición de gobernabilidad hídrica nacional con base en eventos empíricos recientes que de al­guna manera se convierten en referentes de eva­luación en torno al desarrollo social. Su método cualitativo se sustenta en el protocolo del análisis global, el cual a su vez se fundamenta en las cua­lidades de la información secundaria presente en contenidos estructurales sobre el objeto de estu­dio, para de allí acercarse desde lo particular ha­cia lo general, y otorgarle al objeto un significado. Los resultados obtenidos desde las dimensiones social, económica, de capacidad política y am­biental evidencian que si bien se han dado avan­ces institucionales de importancia, aún el acceso y tenencia del agua en Colombia reviste proble­máticas que identifican a una gobernabilidad dé­bil, desconectada de la realidad social y la pers­pectiva de su desarrollo, y por consiguiente de una mejor calidad de vida individual o colectiva, desde patrones de equidad y solidaridad.

APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction

Tertiary protein structure prediction is one of the most challenging problems in structural bioinformatics. Despite the advances in algorithm development and computational strategies, predicting the folded structure of a protein only from its amino acid sequence remains as an unsolved problem. We present a new computational approach to predict the native-like three-dimensional structure of proteins. Conformational preferences of amino acid residues and secondary structure information were obtained from protein templates stored in the Protein Data Bank and represented as an Angle Probability List. Two knowledge-based prediction methods based on Genetic Algorithms and Particle Swarm Optimization were developed using this information. The proposed method has been tested with twenty-six case studies selected to validate our approach with different classes of proteins and folding patterns. Stereochemical and structural analysis were performed for each predicted three-dimensional structure. Results achieved suggest that the Angle Probability List can improve the effectiveness of metaheuristics used to predicted the three-dimensional structure of protein molecules by reducing its conformational search space.

Origin and higher-level diversification of acariform mites - evidence from nuclear ribosomal genes, extensive taxon sampling, and secondary structure alignment.

BackgroundAcariformes is the most species-rich and morphologically diverse radiation of chelicerate arthropods, known from the oldest terrestrial ecosystems. It is also a key lineage in understanding the evolution of this group, with the most vexing question whether mites, or Acari (Parasitiformes and Acariformes) is monophyletic. Previous molecular studies recovered Acari either as monophyletic or non-monophyletic, albeit with a limited taxon sampling. Similarly, relationships between basal acariform groups (include little-known, deep-soil 'endeostigmatan' mites) and major lineages of Acariformes (Sarcoptiformes, Prostigmata) are virtually unknown. We infer phylogeny of chelicerate arthropods, using a large and representative dataset, comprising all main in- and outgroups (228 taxa). Basal diversity of Acariformes is particularly well sampled. With this dataset, we conduct a series of phylogenetically explicit tests of chelicerate and acariform relationships and present a phylogenetic framework for internal relationships of acariform mites.ResultsOur molecular data strongly support a diphyletic Acari, with Acariformes as the sister group to Solifugae (PP =1.0; BP = 100), the so called Poecilophysidea. Among Acariformes, some representatives of the basal group Endeostigmata (mainly deep-soil mites) were recovered as sister-groups to the remaining Acariformes (i. e., Trombidiformes + and most of Sarcoptiformes). Desmonomatan oribatid mites (soil and litter mites) were recovered as the monophyletic sister group of Astigmata (e. g., stored product mites, house dust mites, mange mites, feather and fur mites). Trombidiformes (Sphaerolichida + Prostigmata) is strongly supported (PP =1.0; BP = 98–100). Labidostommatina was inferred as the basal lineage of Prostigmata. Eleutherengona (e. g., spider mites) and Parasitengona (e. g., chiggers, fresh water mites) were recovered as monophyletic. By contrast, Eupodina (e. g., snout mites and relatives) was not. Marine mites (Halacaridae) were traditionally regarded as the sister-group to Bdelloidea (Eupodina), but our analyses show their close relationships to Parasitengona.ConclusionsNon-trivial relationships recovered by our analyses with high support (i.e., basal arrangement of endeostigmatid lineages, the position of marine mites, polyphyly of Eupodina) had been proposed by previous underappreciated morphological studies. Thus, we update currently the accepted taxonomic classification to reflect these results: the superfamily Halacaroidea Murray, 1877 is moved from the infraorder Eupodina Krantz, 1978 to Anystina van der Hammen, 1972; and the subfamily Erythracarinae Oudemans, 1936 (formerly in Anystidae Oudemans, 1902) is elevated to family rank, Erythracaridae stat. ressur., leaving Anystidae only with the nominal subfamily. Our study also shows that a clade comprising early derivative Endeostigmata (Alycidae, Nanorchestidae, Nematalycidae, and maybe Alicorhagiidae) should be treated as a taxon with the same rank as Sarcoptiformes and Trombidiformes, and the scope of the superfamily Bdelloidea should be changed. Before turning those findings into nomenclatural changes, however, we consider that our study calls for (i) finding shared apomorphies of the early derivative Endeostigmata clade and the clade including the remaining Acariformes; (ii) a well-supported hypothesis for Alicorhagiidae placement; (iii) sampling the families Proterorhagiidae, Proteonematalycidae and Grandjeanicidae not yet included in molecular analyses; (iv) undertake a denser sampling of clades traditionally placed in Eupodina, Anystina (Trombidiformes) and Palaeosomata (Sarcoptiformes), since consensus networks and Internode certainty (IC) and IC All (ICA) indices indicate high levels of conflict in these tree regions. Our study shows that regions of ambiguous alignment may provide useful phylogenetic signal when secondary structure information is used to guide the alignment procedure and provides an R implementation to the Bayesian Relative Rates test.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-015-0458-2) contains supplementary material, which is available to authorized users.

Enhanced Protein Fold Prediction Method Through a Novel Feature Extraction Technique.

Information of protein 3-dimensional (3D) structures plays an essential role in molecular biology, cell biology, biomedicine, and drug design. Protein fold prediction is considered as an immediate step for deciphering the protein 3D structures. Therefore, protein fold prediction is one of fundamental problems in structural bioinformatics. Recently, numerous taxonomic methods have been developed for protein fold prediction. Unfortunately, the overall prediction accuracies achieved by existing taxonomic methods are not satisfactory although much progress has been made. To address this problem, we propose a novel taxonomic method, called PFPA, which is featured by combining a novel feature set through an ensemble classifier. Particularly, the sequential evolution information from the profiles of PSI-BLAST and the local and global secondary structure information from the profiles of PSI-PRED are combined to construct a comprehensive feature set. Experimental results demonstrate that PFPA outperforms the state-of-the-art predictors. To be specific, when tested on the independent testing set of a benchmark dataset, PFPA achieves an overall accuracy of 73.6%, which is the leading accuracy ever reported. Moreover, PFPA performs well without significant performance degradation on three updated large-scale datasets, indicating the robustness and generalization of PFPA. Currently, a webserver that implements PFPA is freely available on http://121.192.180.204:8080/PFPA/Index.html.

Cell-Membrane-Mimicking Lipid-Coated Nanoparticles Confer Raman Enhancement to Membrane Proteins and Reveal Membrane-Attached Amyloid-β Conformation.

Identifying the structures of membrane bound proteins is critical to understanding their function in healthy and diseased states. We introduce a surface enhanced Raman spectroscopy technique which can determine the conformation of membrane-bound proteins, at low micromolar concentrations, and also in the presence of a substantial membrane-free fraction. Unlike conventional surface enhanced Raman spectroscopy, our approach does not require immobilization of molecules, as it uses spontaneous binding of proteins to lipid bilayer-encapsulated Ag nanoparticles. We apply this technique to probe membrane-attached oligomers of Amyloid-β40 (Aβ40), whose conformation is keenly sought in the context of Alzheimer's disease. Isotope-shifts in the Raman spectra help us obtain secondary structure information at the level of individual residues. Our results show the presence of a β-turn, flanked by two β-sheet regions. We use solid-state NMR data to confirm the presence of the β-sheets in these regions. In the membrane-attached oligomer, we find a strongly contrasting and near-orthogonal orientation of the backbone H-bonds compared to what is found in the mature, less-toxic Aβ fibrils. Significantly, this allows a "porin" like β-barrel structure, providing a structural basis for proposed mechanisms of Aβ oligomer toxicity.

1H, 13C and 15N resonance assignments and second structure information of Fag s 1: Fagales allergen from Fagus sylvatica.

Fagales allergens belonging to the Bet v 1 family account responsible for the majority of spring pollinosis in the temperate climate zones in the Northern hemisphere. Among them, Fag s 1 from beech pollen is an important trigger of Fagales pollen associated allergic reactions. The protein shares high similarity with birch pollen Bet v 1, the best-characterized member of this allergen family. Of note, recent work on Bet v 1 and its homologues found in Fagales pollen demonstrated that not all allergenic members of this family have the capacity to induce allergic sensitization. Fag s 1 was shown to bind pre-existing IgE antibodies most likely primarily directed against other members of this multi-allergen family. Therefore, it is especially interesting to compare the structures of Bet v 1-like pollen allergens, which have the potential to induce allergic sensitization with allergens that are mainly cross-reactive. This in the end will help to identify allergy eliciting molecular pattern on Bet v 1-like allergens. In this work, we report the (1)H, (15)N and (13)C NMR assignment of beech pollen Fag s 1 as well as the secondary structure information based on backbone chemical shifts.

FASTR: A novel data format for concomitant representation of RNA sequence and secondary structure information.

Given the importance of RNA secondary structures in defining their biological role, it would be convenient for researchers seeking RNA data if both sequence and structural information pertaining to RNA molecules are made available together. Current nucleotide data repositories archive only RNA sequence data. Furthermore, storage formats which can frugally represent RNA sequence as well as structure data in a single file, are currently unavailable. This article proposes a novel storage format, 'FASTR', for concomitant representation of RNA sequence and structure. The storage efficiency of the proposed FASTR format has been evaluated using RNA data from various microorganisms. Results indicate that the size of FASTR formatted files (containing both RNA sequence as well as structure information) are equivalent to that of FASTA-format files, which contain only RNA sequence information. RNA secondary structure is typically represented using a combination of a string of nucleotide characters along with the corresponding dot-bracket notation indicating structural attributes. 'FASTR' - the novel storage format proposed in the present study enables a frugal representation of both RNA sequence and structural information in the form of a single string. In spite of having a relatively smaller storage footprint, the resultant 'fastr' string(s) retain all sequence as well as secondary structural information that could be stored using a dot-bracket notation. An implementation of the 'FASTR' methodology is available for download at http://metagenomics.atc.tcs.com/compression/fastr.

Novel protein weight matrix generated from amino acid indices.

In recent years, numerous protein weight matrices have been developed that include physical characteristics of proteins, such as local sequence-structure information, alpha-helix information, secondary structure information and solvent accessibility states. These protein weight matrices are shown to have generally improved protein sequence alignments over classical protein weight matrices, like Point Accepted Mutation (PAM), Blocks of Amino Acid Substitution (BLOSUM), and GONNET matrices, where important limitations have been observe in recent works. In this paper, a novel protein weight matrix is constructed and presented. This protein weight matrix is not considered based on the mutation rate, like PAM or BLOSUM matrices, but on the physicochemical properties of each amino acid. In the literature, over 500 amino acid indices exist, each one representing a unique biological protein feature. For this study, 25 amino acid indices were selected. These amino acid indices represent general and widely accepted features of the amino acids. By using the proposed protein weight matrix the following advantages can be obtained compared to the classical protein weight matrices. The proposed protein weight matrix is not biased to specific groups of protein sequences as the values are calculated from the amino acid indices, and not from the protein sequences. Additionally, for the proposed protein weight matrix, the same matrix can be considered regardless of the protein sequence's homology to be aligned or the mutation rate presented. A correlation to the physical characterisations of the amino acids that the protein weight matrix derived from can be achieved. Different similarity matrices can be generated when different physical characterisations of amino acids are considered.

ITS2 Secondary Structure Improves Discrimination between Medicinal "Mu Tong" Species when Using DNA Barcoding.

DNA barcoding is a promising species identification method, but it has proved difficult to find a standardized DNA marker in plant. Although the ITS/ITS2 RNA transcript has been proposed as the core barcode for seed plants, it has been criticized for being too conserved in some species to provide enough information or too variable in some species to align it within the different taxa ranks. We selected 30 individuals, representing 16 species and four families, to explore whether ITS2 can successfully resolve species in terms of secondary structure. Secondary structure was predicted using Mfold software and sequence-structure was aligned by MARNA. RNAstat software transformed the secondary structures into 28 symbol code data for maximum parsimony (MP) analysis. The results showed that the ITS2 structures in our samples had a common four-helix folding type with some shared motifs. This conserved structure facilitated the alignment of ambiguous sequences from divergent families. The structure alignment yielded a MP tree, in which most topological relationships were congruent with the tree constructed using nucleotide sequence data. When the data was combined, we obtained a well-resolved and highly supported phylogeny, in which individuals of a same species were clustered together into a monophyletic group. As a result, the different species that are often referred to as the herb “Mu tong” were successfully identified using short fragments of 250 bp ITS2 sequences, together with their secondary structure. Thus our analysis strengthens the potential of ITS2 as a promising DNA barcode because it incorporates valuable secondary structure information that will help improve discrimination between species.

A case study to estimate the applicability of secondary structures of SSU‐rRNA gene in taxonomy and phylogenetic analyses of ciliates

Phylogenetic studies of ciliates are mainly based on the primary structure information of the nuclear genes. Some regions of the small subunit ribosomal RNA (SSU‐rRNA) gene have distinctive secondary structures, which have demonstrated value as phylogenetic/taxonomic characters. In the current work, we predict the secondary structures of four variable regions (V2, V4, V7 and V9) in the SSU‐rRNA gene of 45 urostylids. Structure comparisons indicate that the V4 region is the most effective in revealing interspecific relationships, while the V9 region appears suitable at the family level or higher. The V2 region also offers some taxonomic information, but is too conserved to reflect phylogenetic relationships at the family or lower level, at least for urostylids. The V7 region is the least informative. We constructed several phylogenetic trees, based on the primary sequence alignment and based on an improved alignment according to the secondary structures. The results suggest that including secondary structure information in phylogenetic analyses provides additional insights into phylogenetic relationships. Using urostylid ciliates as an example, we show that secondary structure information results in a better understanding of their relationships, for example generic relationships within the family Pseudokeronopsidae.

ViralmiR: a support-vector-machine-based method for predicting viral microRNA precursors.

BackgroundmicroRNAs (miRNAs) play a vital role in development, oncogenesis, and apoptosis by binding to mRNAs to regulate the posttranscriptional level of coding genes in mammals, plants, and insects. Recent studies have demonstrated that the expression of viral miRNAs is associated with the ability of the virus to infect a host. Identifying potential viral miRNAs from experimental sequence data is valuable for deciphering virus-host interactions. Thus far, a specific predictive model for viral miRNA identification has yet to be developed.Methods and resultsHere, we present ViralmiR for identifying viral miRNA precursors on the basis of sequencing and structural information. We collected 263 experimentally validated miRNA precursors (pre-miRNAs) from 26 virus species and generated sequencing fragments from virus and human genomes as the negative dataset. Support vector machine and random forest models were established using 54 features from RNA sequences and secondary structural information. The results show that ViralmiR achieved a balanced accuracy higher than 83%, which is superior to that of previously developed tools for identifying pre-miRNAs.ConclusionsThe easy-to-use ViralmiR web interface has been provided as a helpful resource for researchers to use in analyzing and deciphering virus-host interactions. The web interface of ViralmiR can be accessed at http://csb.cse.yzu.edu.tw/viralmir/.

Chirality-assisted ring-like aggregation of aβ(1-40) at liquid-solid interfaces: a stereoselective two-step assembly process.

Molecular chirality is introduced at liquid-solid interfaces. A ring-like aggregation of amyloid Aβ(1-40) on N-isobutyryl-L-cysteine (L-NIBC)-modified gold substrate occurs at low Aβ(1-40) concentration, while D-NIBC modification only results in rod-like aggregation. Utilizing atomic force microscope controlled tip-enhanced Raman scattering, we directly observe the secondary structure information for Aβ(1-40) assembly in situ at the nanoscale. D- or L-NIBC on the surface can guide parallel or nonparallel alignment of β-hairpins through a two-step process based on electrostatic-interaction-enhanced adsorption and subsequent stereoselective recognition. Possible electrostatic interaction sites (R5 and K16) and a chiral recognition site (H14) of Aβ(1-40) are proposed, which may provide insight into the understanding of this effect.

Chirality‐Assisted Ring‐Like Aggregation of Aβ(1–40) at Liquid–Solid Interfaces: A Stereoselective Two‐Step Assembly Process

AbstractMolecular chirality is introduced at liquid–solid interfaces. A ring‐like aggregation of amyloid Aβ(1–40) on N‐isobutyryl‐L‐cysteine (L‐NIBC)‐modified gold substrate occurs at low Aβ(1–40) concentration, while D‐NIBC modification only results in rod‐like aggregation. Utilizing atomic force microscope controlled tip‐enhanced Raman scattering, we directly observe the secondary structure information for Aβ(1–40) assembly in situ at the nanoscale. D‐ or L‐NIBC on the surface can guide parallel or nonparallel alignment of β‐hairpins through a two‐step process based on electrostatic‐interaction‐enhanced adsorption and subsequent stereoselective recognition. Possible electrostatic interaction sites (R5 and K16) and a chiral recognition site (H14) of Aβ(1–40) are proposed, which may provide insight into the understanding of this effect.