Preferences Of Amino Acid Residues Research Articles

Innovative workflow for the identification of cathepsin K cleavage sites in type I collagen

Since the late 1990s, cathepsin K cleavage sites in type I collagen have been extensively studied due to its ability to release bone resorption biomarkers such as CTX and NTX. However, gel-based methods and N-sequencing used in these studies lack sensitivity, especially for small to medium peptides. In this work, we propose a degradomics mass spectrometry-based workflow that combines protein digestion, Nano-LC-UDMSE, and several software tools to identify cathepsin K cleavage sites. This workflow not only identified previously known cleavage sites, but also discovered new ones. Multiple cleavage hotspots were found and described in type I α1 and type I α2 collagen, many of which coincided with pyridinoline crosslinks, known to stabilize the triple helix. Our results allowed us to establish a chronology of digestion and conclude that cathepsin K preferentially cleaves the extremities of type I collagen before the helical part. We also found that cathepsin K preferentially cleaves amino acid residues with long and hydrophobic lateral chains at the beginning of digestion, whereas no preferred amino acid residues were identified later in the digestion. In conclusion, our workflow successfully identified new cleavage sites and can be easily applied to other proteins or proteases.

Isolation and Characterization of scFv Antibody against Internal Ribosomal Entry Site of Enterovirus A71.

Enterovirus A71 (EV-A71) is one of the causative agents of hand-foot-mouth disease, which can be associated with neurocomplications of the central nervous system. A limited understanding of the virus's biology and pathogenesis has led to the unavailability of effective anti-viral treatments. The EV-A71 RNA genome carries type I internal ribosomal entry site (IRES) at 5' UTR that plays an essential role in the viral genomic translation. However, the detailed mechanism of IRES-mediated translation has not been elucidated. In this study, sequence analysis revealed that the domains IV, V, and VI of EV-A71 IRES contained the structurally conserved regions. The selected region was transcribed in vitro and labeled with biotin to use as an antigen for selecting the single-chain variable fragment (scFv) antibody from the naïve phage display library. The so-obtained scFv, namely, scFv #16-3, binds specifically to EV-A71 IRES. The molecular docking showed that the interaction between scFv #16-3 and EV-A71 IRES was mediated by the preferences of amino acid residues, including serine, tyrosine, glycine, lysine, and arginine on the antigen-binding sites contacted the nucleotides on the IRES domains IV and V. The so-produced scFv has the potential to develop as a structural biology tool to study the biology of the EV-A71 RNA genome.

Local Backbone Geometry Plays a Critical Role in Determining Conformational Preferences of Amino Acid Residues in Proteins.

The definition of the structural basis of the conformational preferences of the genetically encoded amino acid residues is an important yet unresolved issue of structural biology. In order to gain insights into this intricate topic, we here determined and compared the amino acid propensity scales for different (φ, ψ) regions of the Ramachandran plot and for different secondary structure elements. These propensities were calculated using the Chou–Fasman approach on a database of non-redundant protein chains retrieved from the Protein Data Bank. Similarities between propensity scales were evaluated by linear regression analyses. One of the most striking and unexpected findings is that distant regions of the Ramachandran plot may exhibit significantly similar propensity scales. On the other hand, contiguous regions of the Ramachandran plot may present anticorrelated propensities. In order to provide an interpretative background to these results, we evaluated the role that the local variability of protein backbone geometry plays in this context. Our analysis indicates that (dis)similarities of propensity scales between different regions of the Ramachandran plot are coupled with (dis)similarities in the local geometry. The concept that similarities of the propensity scales are dictated by the similarity of the NCαC angle and not necessarily by the similarity of the (φ, ψ) conformation may have far-reaching implications in the field.

An integrated protein structure fitness scoring approach for identifying native-like model structures

The structural information of a protein is pivotal to comprehend its functions, protein–protein and protein–ligand interactions. There is a widening gap between the number of known protein sequences and that of experimentally determined structures. The protein structure prediction has emerged as an efficient alternative to deliver the reliable structural information of proteins. However, it remains a challenge to identify the best model among the many predicted by one or a few structure prediction methods. Here we report ProFitFun-Meta, a neural network based pure single model scoring method for assessing the quality of predicted model structures by an effective combination structural information of various backbone dihedral angle and residue surface accessibility preferences of amino acid residues with other spatial properties of protein structures. The performance of ProFitFun-Meta was validated and benchmarked against current state-of-the-art methods on the extensive datasets, comprising a Test Dataset (n = 26,604), an External Dataset (n = 40,000), and CASP14 Dataset (n = 1200). The comprehensive performance evaluation of ProFitFun-Meta demonstrated its reliability and efficiency in terms of Spearman’s (ρ) and Pearson’s (r) correlation coefficients, GDT-TS loss (g), and absolute loss (d). An improved performance over the current state-of-the-art methods and leading performers of CASP14 experiment in quality assessment category demonstrated its potential to become an integral component of computational pipelines for protein modeling and design. The minimal dependencies, high computational efficiency, and portability to various Linux and Windows OS provide an additional edge to ProFitFun-Meta for its easy implementation and applications in various regimes of computational protein folding.

Glycine in Water Favors the Polyproline II State.

Conformational preferences of amino acid residues in water are determined by the backbone and side-chain properties. Alanine is known for its high polyproline II (pPII) propensity. The question of relative contributions of the backbone and side chain to the conformational preferences of alanine and other amino acid residues in water is not fully resolved. Because glycine lacks a heavy-atom side chain, glycine-based peptides can be used to examine to which extent the backbone properties affect the conformational space. Here, we use published spectroscopic data for the central glycine residue of cationic triglycine in water to demonstrate that its conformational space is dominated by the pPII state. We assess three commonly used molecular dynamics (MD) force fields with respect to their ability to capture the conformational preferences of the central glycine residue in triglycine. We show that pPII is the mesostate that enables the functional backbone groups of the central residue to form the most hydrogen bonds with water. Our results indicate that the pPII propensity of the central glycine in GGG is comparable to that of alanine in GAG, implying that the water-backbone hydrogen bonding is responsible for the high pPII content of these residues.

Effect of Iron Oxide Nanoparticles on the Oxidation and Secondary Structure of Growth Hormone

Oxidation of therapeutic proteins (TPs) can lead to changes in their pharmacokinetics, biological activity and immunogenicity. Metal impurities such as iron are known to increase oxidation of TPs, but nanoparticulate metals have unique physical and chemical properties compared to the bulk material or free metal ions. Iron oxide nanoparticles (IONPs) may originate from equipment used in the manufacturing of TPs or from needles during injection. In this study, the impact of IONPs on oxidation of a model protein, rat growth hormone (rGH), was investigated under chemical stress. Hydrogen peroxide (H2O2)- and 2,2′-azobis (2-methylpropionamidine) dihydrochloride oxidized methionine residues of rGH, but unexpectedly, oxidation was suppressed in the presence of IONPs compared to a phosphate buffer control. Fourier transform infrared spectroscopy indicated splitting of the α-helical absorbance band in the presence of IONPs, whereas circular dichroism spectra showed a reduced α-helical contribution with increasing temperature for both rGH and rGH-IONP mixtures. The results collectively indicate that IONPs can increase the chemical stability of rGH by altering the kinetics and preference of amino acid residues that are oxidized, although the changes in protein secondary structure by IONPs may lead to alterations of physical stability.

Developments and Applications of Coil-Library-Based Residue-Specific Force Fields for Molecular Dynamics Simulations of Peptides and Proteins.

Molecular dynamics (MD) simulation has become a powerful tool for studying the structures and functional mechanisms of biomolecules, and its reliability crucially depends on the accuracy of underlying force fields. This perspective describes our recent efforts to develop more accurate protein force fields by improving the description of intrinsic conformational preferences of amino acid residues using residue-specific dihedral-angle-related parameters. Both backbone and side-chain conformational distributions and their coupling were optimized to fit those from a protein coil library. The resulting force fields RSFF1 and RSFF2 have been found to be more accurate than popular protein force fields, in reproducing experimental structural data of various peptides and proteins. They have also been successfully used in studying folding mechanisms and refinement of structure models. Further methodology developments related to intrinsically disordered proteins (RSFF2+) and a more universal implementation (RSFF2C) based on CMAP potentials are also described.

LabCaS for Ranking Potential Calpain Substrate Cleavage Sites from Amino Acid Sequence.

Calpains are a family of Ca2+-dependent cysteine proteases involved in many important biological processes, where they selectively cleave relevant substrates at specific cleavage sites to regulate the function of the substrate proteins. Presently, our knowledge about the function of calpains and the mechanism of substrate cleavage is still limited due to the fact that the experimental determination and validation on calpain bindings are usually laborious and expensive. This chapter describes LabCaS, an algorithm that is designed for predicting the calpain substrate cleavage sites from amino acid sequences. LabCaS is built on a conditional random field (CRF) statistic model, which trains the cleavage site prediction on multiple features of amino acid residue preference, solvent accessibility information, pair-wise alignment similarity score, secondary structure propensity, and physical-chemistry properties. Large-scale benchmark tests have shown that LabCaS can achieve a reliable recognition of the cleavage sites for most calpain proteins with an average AUC score of 0.862. Due to the fast speed and convenience of use, the protocol should find its usefulness in large-scale calpain-based function annotations of the newly sequenced proteins. The online web server of LabCaS is freely available at http://www.csbio.sjtu.edu.cn/bioinf/LabCaS .

Dihedral angle preferences of amino acid residues forming various non-local interactions in proteins.

In theory, a polypeptide chain can adopt a vast number of conformations, each corresponding to a set of backbone rotation angles. Many of these conformations are excluded due to steric overlaps. Ramachandran and coworkers were the first to look into this problem by plotting backbone dihedral angles in a two-dimensional plot. The conformational space in the Ramachandran map is further refined by considering the energetic contributions of various non-bonded interactions. Alternatively, the conformation adopted by a polypeptide chain may also be examined by investigating interactions between the residues. Since the Ramachandran map essentially focuses on local interactions (residues closer in sequence), out of interest, we have analyzed the dihedral angle preferences of residues that make non-local interactions (residues far away in sequence and closer in space) in the folded structures of proteins. The non-local interactions have been grouped into different types such as hydrogen bond, van der Waals interactions between hydrophobic groups, ion pairs (salt bridges), and ππ-stacking interactions. The results show the propensity of amino acid residues in proteins forming local and non-local interactions. Our results point to the vital role of different types of non-local interactions and their effect on dihedral angles in forming secondary and tertiary structural elements to adopt their native fold.

NIAS-Server: Neighbors Influence of Amino acids and Secondary Structures in Proteins.

The exponential growth in the number of experimentally determined three-dimensional protein structures provide a new and relevant knowledge about the conformation of amino acids in proteins. Only a few of probability densities of amino acids are publicly available for use in structure validation and prediction methods. NIAS (Neighbors Influence of Amino acids and Secondary structures) is a web-based tool used to extract information about conformational preferences of amino acid residues and secondary structures in experimental-determined protein templates. This information is useful, for example, to characterize folds and local motifs in proteins, molecular folding, and can help the solution of complex problems such as protein structure prediction, protein design, among others. The NIAS-Server and supplementary data are available at http://sbcb.inf.ufrgs.br/nias .

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.

Proteomic analysis of protein methylation in the yeast Saccharomyces cerevisiae.

In this paper, we presented the methylation by isotope labeled SAM (MILS) strategy for a highly-confident analysis of the methylproteome of the yeast S. cerevisiae and collected a comprehensive list of proteins methylated on a set of distinct residues (K, R, N, E, D, Q, H, C). Our study provided useful information about the amino acid residue preference and methylation state distributions on nitrogen centers of protein methylation in S. cerevisiae.

The inhibitory mechanism analysis of human chymase specific inhibitor TJK002

Chymase is a mast cell specific serine protease that is stored within secretory granules and released together with heparin and histamine in response to allergen challenge or other stimuli. Recent study have shown that chymase possess processing activity for biological peptides and cytokines implicated in a variety of diseases. For example, the chymases of primateds and dogs have highly specific angiotensin II generating activity, and the results of animal studies suggest the chymase contributes to the pathogenesis of cardiovascular diseases via Ang II generation. Based on the results of these studies, inhibition of chymase is expected to provide therapeutic means for the treatment of these diseases. Recently, we have developed some novel benzimidazole derived in human chymase inhibitors and the crystal structure of human chymase complexed with a nobel benzimidazole inhibitor TJK002 was obtained at 2.8A. TJK002 showed potent inhibitory activity (Ki value 2.24nM) with respect to human chymase. X-ray crystallographic structure showed that THK002 forms an anon-covalent interaction with the catalytic domain of human chymase. 4-methylbenzothiophen-3-yl moiety of TJK002 occupies the S1 pocket. The carboxylic acid for hydrogen bonds with the imidazole N (e) atom of H57 and O (g) atoms of Ser195 at the catalytic site. The binding mode of TJK002 is very unique and attractive compared other cymase inhibitors. It depends on the binding mode of TJK002 and reflects to its biological function. Because by site-directed mutagenesis, human mast cell chymase are responsible for an acidic amino acid residue preference in the P2' position of substrates. Chymase inhibitors besides TJK002 have negatively charged p2' moiety. But TJK002 doesn't have such a moiety which binds to S2' site, but it still has a strong incisory activity. We clarify its strong inhibitory mechanism of TJK002 by Fragment molecular orbital (FMO) calculation. We discovered the stacking interaction between the benzimidazole ring and His57 is quite effective for the inhibitory activity of TJK002.

Local order in the unfolded state: conformational biases and nearest neighbor interactions.

The discovery of Intrinsically Disordered Proteins, which contain significant levels of disorder yet perform complex biologically functions, as well as unwanted aggregation, has motivated numerous experimental and theoretical studies aimed at describing residue-level conformational ensembles. Multiple lines of evidence gathered over the last 15 years strongly suggest that amino acids residues display unique and restricted conformational preferences in the unfolded state of peptides and proteins, contrary to one of the basic assumptions of the canonical random coil model. To fully understand residue level order/disorder, however, one has to gain a quantitative, experimentally based picture of conformational distributions and to determine the physical basis underlying residue-level conformational biases. Here, we review the experimental, computational and bioinformatic evidence for conformational preferences of amino acid residues in (mostly short) peptides that can be utilized as suitable model systems for unfolded states of peptides and proteins. In this context particular attention is paid to the alleged high polyproline II preference of alanine. We discuss how these conformational propensities may be modulated by peptide solvent interactions and so called nearest-neighbor interactions. The relevance of conformational propensities for the protein folding problem and the understanding of IDPs is briefly discussed.

Role of Enthalpy–Entropy Compensation Interactions in Determining the Conformational Propensities of Amino Acid Residues in Unfolded Peptides.

The driving forces governing the unique and restricted conformational preferences of amino acid residues in the unfolded state are still not well understood. In this study, we experimentally determine the individual thermodynamic components underlying intrinsic conformational propensities of these residues. Thermodynamic analysis of ultraviolet-circular dichroism (UV-CD) and (1)H NMR data for a series of glycine capped amino acid residues (i.e., G-x-G peptides) reveals the existence of a nearly exact enthalpy-entropy compensation for the polyproline II-β strand equilibrium for all investigated residues. The respective ΔHβ, ΔSβ values exhibit a nearly perfect linear relationship with an apparent compensation temperature of 295 ± 2 K. Moreover, we identified iso-equilibrium points for two subsets of residues at 297 and 305 K. Thus, our data suggest that within this temperature regime, which is only slightly below physiological temperatures, the conformational ensembles of amino acid residues in the unfolded state differ solely with respect to their capability to adopt turn-like conformations. Such iso-equilibria are rarely observed, and their existence herein indicates a common physical origin behind conformational preferences, which we are able to assign to side-chain dependent backbone solvation. Conformational effects such as differences between the number of sterically allowed side chain rotamers can contribute to enthalpy and entropy but not to the Gibbs energy associated with conformational preferences. Interestingly, we found that alanine, aspartic acid, and threonine are the only residues which do not share these iso-equilbiria. The enthalpy-entropy compensation discovered as well as the iso-equilbrium and thermodynamics obtained for each amino acid residue provide a new and informative way of identifying the determinants of amino acid propensities in unfolded and disordered states.

Entropy reduction in unfolded peptides (and proteins) due to conformational preferences of amino acid residues.

As established by several groups over the last 20 years, amino acid residues in unfolded peptides and proteins do not exhibit the unspecific random distribution as assumed by the classical random coil model. Individual amino acid residues in small peptides were found to exhibit different conformational preferences. Here, we utilize recently obtained conformational distributions of guest amino acid residues in GxG peptides to estimate their conformational entropy, which we find to be significantly lower than the entropy of an assumed random coil like distribution. Only at high temperature do backbone entropies approach random coil like values. We utilized the obtained backbone entropies of the investigated amino acid residues to estimate the loss of conformational entropy caused by a coil → helix transition and identified two subsets of amino acid residues for which the thus calculated entropy losses correlate well with the respective Gibbs energy of helix formation obtained for alanine based host-guest systems. Calculated and experimentally derived entropic losses were found to be in good agreement. For most of the amino acid residues investigated entropic losses derived from our GxG distributions correlate very well with corresponding values recently obtained from MD simulations biased by conformational propensities derived from truncated coil libraries. Both, conformational entropy and the entropy of solvation exhibit a strong, residue specific temperature dependence, which can be expected to substantially affect the stability of unfolded states. Altogether, our results provide strong evidence for the notion that conformational preferences of amino acid residues matter with regard to the thermodynamics of peptide and protein folding.

Mutations in Arg143 and Lys192 of the Human Mast Cell Chymase Markedly Affect the Activity of Five Potent Human Chymase Inhibitors

Chymotrypsin-like serine proteases are found in high abundance in mast cell granules. By site-directed mutatgenesis, we have previously shown that basic amino acids in positions 143 and 192 (Arg and Lys respectively) of the human mast cell chymase are responsible for an acidic amino acid residue preference in the P2' position of substrates. In order to study the influence of these two residues in determining the specificity of chymase inhibitors, we have synthesized five different potent inhibitors of the human chymase. The inhibitory effects of these compounds were tested against the wild-type enzyme, against two single mutants Arg143Gln and Lys192Met and against a double mutant, Arg143Gln+Lys192Met. We observed a markedly reduced activity of all five inhibitors with the double mutant, indicating that these two basic residues are involved in conferring the specificity of these inhibitors. The single mutants showed an intermediate phenotype, with the strongest effect on the inhibitor by the mutation in Lys192. The Lys192 and the double mutations also affected the rate of cleavage of angiotensin I but did not seem to affect the specificity in the cleavage of the Tyr4-Ile5 bond. A more detailed knowledge about which amino acids that confer the specificity of an enzyme can prove to be of major importance for development of highly specific inhibitors for the human chymase and other medically important enzymes.

Influence of the sequence environment and properties of neighboring amino acids on amino-acetylation: Relevance for structure-function analysis

Proteins function is regulated by co-translational modifications and post-translational modifications (PTMs) such as phosphorylation, glycosylation, and acetylation, which induce proteins to perform multiple tasks in a specified environment. Acetylation takes place post-translationally on the ε-amino group of Lys in histone proteins, allowing regulation of gene expression. Furthermore, amino group acetylation also occurs co-translationally on Ser, Thr, Gly, Met, and Ala, possibly contributing to the stability of proteins. In this work, the influence of amino acids next to acetylated sites has been investigated by using MAPRes (Mining Association Patterns among preferred amino acid residues in the vicinity of amino acids targeted for PTMs). MAPRes was utilized to examine the sequence patterns vicinal to modified and non-modified residues, taking into account their charge and polarity. The PTMs data were further sub-divided according to their sub-cellular location (nuclear, mitochondrial, and cytoplasmic), and their association patterns were mined. The association patterns mined by MAPRes for acetylated and non-acetylated residues are consistent with the existing literature but also revealed novel patterns. These rules have been utilized to describe the acetylation and its effects on the protein structure-function relationship.

The intrinsic conformational features of amino acids from a protein coil library and their applications in force field development

The local conformational (φ, ψ, χ) preferences of amino acid residues remain an active research area, which are important for the development of protein force fields. In this perspective article, we first summarize spectroscopic studies of alanine-based short peptides in aqueous solution. While most studies indicate a preference for the P(II) conformation in the unfolded state over α and β conformations, significant variations are also observed. A statistical analysis from various coil libraries of high-resolution protein structures is then summarized, which gives a more coherent view of the local conformational features. The φ, ψ, χ distributions of the 20 amino acids have been obtained from a protein coil library, considering both backbone and side-chain conformational preferences. The intrinsic side-chain χ(1) rotamer preference and χ(1)-dependent Ramachandran plot can be generally understood by combining the interaction of the side-chain Cγ/Oγ atom with two neighboring backbone peptide groups. Current all-atom force fields such as AMBER ff99sb-ILDN, ff03 and OPLS-AA/L do not reproduce these distributions well. A method has been developed by combining the φ, ψ plot of alanine with the influence of side-chain χ(1) rotamers to derive the local conformational features of various amino acids. It has been further applied to improve the OPLS-AA force field. The modified force field (OPLS-AA/C) reproduces experimental (3)J coupling constants for various short peptides quite well. It also better reproduces the temperature-dependence of the helix-coil transition for alanine-based peptides. The new force field can fold a series of peptides and proteins with various secondary structures to their experimental structures. MD simulations of several globular proteins using the improved force field give significantly less deviation (RMSD) to experimental structures. The results indicate that the local conformational features from coil libraries are valuable for the development of balanced protein force fields.

The Role of RNA Sequence and Structure in RNA–Protein Interactions

We investigate the sequence and structural properties of RNA–protein interaction sites in 211 RNA–protein chain pairs, the largest set of RNA–protein complexes analyzed to date. Statistical analysis confirms and extends earlier analyses made on smaller data sets. There are 24.6% of hydrogen bonds between RNA and protein that are nucleobase specific, indicating the importance of both nucleobase-specific and -nonspecific interactions. While there is no significant difference between RNA base frequencies in protein-binding and non-binding regions, distinct preferences for RNA bases, RNA structural states, protein residues, and protein secondary structure emerge when nucleobase-specific and -nonspecific interactions are considered separately. Guanine nucleobase and unpaired RNA structural states are significantly preferred in nucleobase-specific interactions; however, nonspecific interactions disfavor guanine, while still favoring unpaired RNA structural states. The opposite preferences of nucleobase-specific and -nonspecific interactions for guanine may explain discrepancies between earlier studies with regard to base preferences in RNA–protein interaction regions. Preferences for amino acid residues differ significantly between nucleobase-specific and -nonspecific interactions, with nonspecific interactions showing the expected bias towards positively charged residues. Irregular protein structures are strongly favored in interactions with the protein backbone, whereas there is little preference for specific protein secondary structure in either nucleobase-specific interaction or -nonspecific interaction. Overall, this study shows strong preferences for both RNA bases and RNA structural states in protein–RNA interactions, indicating their mutual importance in protein recognition.