Predicting HLA Class I Non-Permissive Amino Acid Residues Substitutions

Prediction of peptide binding to human leukocyte antigen (HLA) molecules is essential to a wide range of clinical entities from vaccine design to stem cell transplant compatibility. Here we present a new structure-based methodology that applies robust computational tools to model peptide-HLA (p-HLA) binding interactions. The method leverages the structural conservation observed in p-HLA complexes to significantly reduce the search space and calculate the system's binding free energy. This approach is benchmarked against existing p-HLA complexes and the prediction performance is measured against a library of experimentally validated peptides. The effect on binding activity across a large set of high-affinity peptides is used to investigate amino acid mismatches reported as high-risk factors in hematopoietic stem cell transplantation.     

Quantifying Structural and Functional Restraints on Amino Acid Substitutions in Evolution of Proteins

One of Oleg Ptitsyn's most important papers (Shakhnovich, E., Abkevich, V., and Ptitsyn, O. (1996) Nature, 379, 96-98) describes how knowledge of structure and function can be used to understand better the nature of amino acid substitutions in families and superfamilies of proteins. The selective advantages of retaining structure and function during evolution can be expressed as restraints on the amino acid substitutions that are accepted.     

Functional Significance May Underlie the Taxonomic Utility of Single Amino Acid Substitutions in Conserved Proteins

We hypothesized that some amino acid substitutions in conserved proteins that are strongly fixed by critical functional roles would show lineage-specific distributions. As an example of an archetypal conserved eukaryotic protein we considered the active site of β-tubulin. Our analysis identified one amino acid substitution—β-tubulin F224—which was highly lineage specific. Investigation of β-tubulin for other phylogenetically restricted amino acids identified several with apparent specificity for well-defined phylogenetic groups. Intriguingly, none showed specificity for “supergroups” other than the unikonts. To understand why, we analysed the β-tubulin Neighbor-Net and demonstrated a fundamental division between core β-tubulins (plant-like) and divergent β-tubulins (animal and fungal). F224 was almost completely restricted to the core β-tubulins, while divergent β-tubulins possessed Y224. Thus, our specific example offers insight into the restrictions associated with the co-evolution of β-tubulin during the radiation of eukaryotes, underlining a fundamental dichotomy between F-type, core β-tubulins and Y-type, divergent β-tubulins. More broadly our study provides proof of principle for the taxonomic utility of critical amino acids in the active sites of conserved proteins.     

Effect of Substitutions in Surface Amino Acid on Energy Profile of Apomyoglobin

Studies on the process of spontaneous protein folding into a unique native state are an important issue of molecular biology. Apomyoglobin from the sperm whale is a convenient model for these studies in vitro. Here, we present the results of equilibrium and kinetic experiments carried out in a study on the folding and unfolding of eight mutant apomyoglobin forms of with hydrophobic amino acid substitutions on the protein surface. Calculated values of apparent constants of folding/unfolding rates, as well as the data on equilibrium conformational transitions in the urea concentration range of 0–6 M at 11°C are given. Based on the obtained information on the kinetic properties of the studied proteins, a Φ-value analysis of the transition state has been performed and values of urea concentrations corresponding to the midpoint of the transition from the native to intermediate state have been determined for the given forms of mutant apomyoglobin. It has been found that a significant increase in the stability of the native state can be achieved by a small number of amino acid substitutions on the protein surface. It has been shown that the substitution of only one amino acid residue exclusively affects the height of the energy barrier that separates different states of apomyoglobin.     

Identification of Single Amino Acid Substitutions in Proteogenomics

An important aim of proteogenomics, which combines data of high throughput nucleic acid and protein analysis, is to reliably identify single amino acid substitutions representing a main type of coding genome variants. Exact knowledge of deviations from the consensus genome can be utilized in several biomedical fields, such as studies of expression of mutated proteins in cancer, deciphering heterozygosity mechanisms, identification of neoantigens in anticancer vaccine production, search for RNA editing sites at the level of the proteome, etc. Generation of this new knowledge requires processing of large data arrays from high–resolution mass spectrometry, where information on single–point protein variation is often difficult to extract. Accordingly, a significant problem in proteogenomic analysis is the presence of high levels of false positive results for variant–containing peptides in the produced results. Here we review recently suggested approaches of high quality proteomics data processing that may provide more reliable identification of single amino acid substitutions, especially contrary to residue modifications occurring in vitro and in vivo. Optimized methods for assessment of false discovery rate save instrumental and computational time spent for validation of interesting findings of amino acid polymorphism by orthogonal methods.     

FunSAV: Predicting the Functional Effect of Single Amino Acid Variants Using a Two-Stage Random Forest Model

Single amino acid variants (SAVs) are the most abundant form of known genetic variations associated with human disease. Successful prediction of the functional impact of SAVs from sequences can thus lead to an improved understanding of the underlying mechanisms of why a SAV may be associated with certain disease. In this work, we constructed a high-quality structural dataset that contained 679 high-quality protein structures with 2,048 SAVs by collecting the human genetic variant data from multiple resources and dividing them into two categories, i.e., disease-associated and neutral variants. We built a two-stage random forest (RF) model, termed as FunSAV, to predict the functional effect of SAVs by combining sequence, structure and residue-contact network features with other additional features that were not explored in previous studies. Importantly, a two-step feature selection procedure was proposed to select the most important and informative features that contribute to the prediction of disease association of SAVs. In cross-validation experiments on the benchmark dataset, FunSAV achieved a good prediction performance with the area under the curve (AUC) of 0.882, which is competitive with and in some cases better than other existing tools including SIFT, SNAP, Polyphen2, PANTHER, nsSNPAnalyzer and PhD-SNP. The sourcecodes of FunSAV and the datasets can be downloaded at http://sunflower.kuicr.kyoto-u.ac.jp/sjn/FunSAV.     

ENTPRISE: An Algorithm for Predicting Human Disease-Associated Amino Acid Substitutions from Sequence Entropy and Predicted Protein Structures

The advance of next-generation sequencing technologies has made exome sequencing rapid and relatively inexpensive. A major application of exome sequencing is the identification of genetic variations likely to cause Mendelian diseases. This requires processing large amounts of sequence information and therefore computational approaches that can accurately and efficiently identify the subset of disease-associated variations are needed. The accuracy and high false positive rates of existing computational tools leave much room for improvement. Here, we develop a boosted tree regression machine-learning approach to predict human disease-associated amino acid variations by utilizing a comprehensive combination of protein sequence and structure features. On comparing our method, ENTPRISE, to the state-of-the-art methods SIFT, PolyPhen-2, MUTATIONASSESSOR, MUTATIONTASTER, FATHMM, ENTPRISE exhibits significant improvement. In particular, on a testing dataset consisting of only proteins with balanced disease-associated and neutral variations defined as having the ratio of neutral/disease-associated variations between 0.3 and 3, the Mathews Correlation Coefficient by ENTPRISE is 0.493 as compared to 0.432 by PPH2-HumVar, 0.406 by SIFT, 0.403 by MUTATIONASSESSOR, 0.402 by PPH2-HumDiv, 0.305 by MUTATIONTASTER, and 0.181 by FATHMM. ENTPRISE is then applied to nucleic acid binding proteins in the human proteome. Disease-associated predictions are shown to be highly correlated with the number of protein-protein interactions. Both these predictions and the ENTPRISE server are freely available for academic users as a web service at http://cssb.biology.gatech.edu/entprise/.     

Effects of Hydrophobic Amino Acid Substitutions on Antimicrobial Peptide Behavior

Antimicrobial peptides (AMPs) are naturally occurring components of the immune system that act against bacteria in a variety of organisms throughout the evolutionary hierarchy. There have been many studies focused on the activity of AMPs using biophysical and microbiological techniques; however, a clear and predictive mechanism toward determining if a peptide will exhibit antimicrobial activity is still elusive, in addition to the fact that the mechanism of action of AMPs has been shown to vary between peptides, targets, and experimental conditions. Nonetheless, the majority of AMPs contain hydrophobic amino acids to facilitate partitioning into bacterial membranes and a net cationic charge to promote selective binding to the anionic surfaces of bacteria over the zwitterionic host cell surfaces. This study explores the role of hydrophobic amino acids using the peptide C18G as a model system. These changes were evaluated for the effects on antimicrobial activity, peptide-lipid interactions using Trp fluorescence spectroscopy, peptide secondary structure formation, and bacterial membrane permeabilization. The results show that while secondary structure formation was not significantly impacted by the substitutions, antibacterial activity and binding to model lipid membranes were well correlated. The variants containing Leu or Phe as the sole hydrophobic groups bound bilayers with highest affinity and were most effective at inhibiting bacterial growth. Peptides with Ile exhibited intermediate behavior while those with Val or α-aminoisobutyric acid (Aib) showed poor binding and activity. The Leu, Phe, and Ile peptides demonstrated a clear preference for anionic bilayers, exhibiting significant emission spectrum shifts upon binding. Similarly, the Leu, Phe, and Ile peptides demonstrated greater ability to disrupt lipid vesicles and bacterial membranes. In total, the data indicate that hydrophobic moieties in the AMP sequence play a significant role in the binding and ability of the peptide to exhibit antibacterial activity.     

Limited Predictability of Amino Acid Substitutions in Seasonal Influenza Viruses

Seasonal influenza viruses repeatedly infect humans in part because they rapidly change their antigenic properties and evade host immune responses, necessitating frequent updates of the vaccine composition. Accurate predictions of strains circulating in the future could therefore improve the vaccine match. Here, we studied the predictability of frequency dynamics and fixation of amino acid substitutions. Current frequency was the strongest predictor of eventual fixation, as expected in neutral evolution. Other properties, such as occurrence in previously characterized epitopes or high Local Branching Index (LBI) had little predictive power. Parallel evolution was found to be moderately predictive of fixation. Although the LBI had little power to predict frequency dynamics, it was still successful at picking strains representative of future populations. The latter is due to a tendency of the LBI to be high for consensus-like sequences that are closer to the future than the average sequence. Simulations of models of adapting populations, in contrast, show clear signals of predictability. This indicates that the evolution of influenza HA and NA, while driven by strong selection pressure to change, is poorly described by common models of directional selection such as traveling fitness waves.     

Correlated Mutations: A Hallmark of Phenotypic Amino Acid Substitutions

Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/.     

白细胞介素－2中某些残基替换对活性的影响

用基因定点突变法研究了白细胞介素－２（ＩＬ－２）中某些氨基酸对生物活性的影响。将ＩＬ－２中３９Ｍｅｔ和４３Ｌｙｓ分别改为Ｐｒｏ,企图破坏此处α螺旋,突变体的ＣＤ图谱和生物活性均,不变,说明此处可能原来就不存在α螺旋．而将５２Ｇｌｕ．５３Ｌｅｕ,５４Ｌｙｓ分别改为Ｐｒｏ后,ＣＤ谱发生了变化,生物活性也显著下降。表明这些氨基酸处在α螺旋中,将它们改为Ｐｒｏ后,影响了ＩＬ－２的结构,并导致活性下降     

Positive Selection on Nucleotide Substitutions and Indels in Accessory Gland Proteins of the Drosophila pseudoobscura Subgroup

Genes encoding reproductive proteins often diverge rapidly due to positive selection on nucleotide substitutions. While this general pattern is well established, the extent to which specific reproductive genes experience similar selection in different clades has been little explored, nor have possible targets of positive selection other than nucleotide substitutions, such as indels, received much attention. Here, we inspect for the signature of positive selection in the genes encoding five accessory gland proteins (Acps) (Acp26Aa, Acp32CD, Acp53Ea, Acp62F, and Acp70A) originally described from Drosophila melanogaster but with recognizable orthologues in the D. pseudoobscura subgroup. We compare patterns of selection within the D. psuedoobscura subgroup to those in the D. melanogaster subgroup. Similar patterns of positive selection were found in Acp26Aa and Acp62F in the two subgroups, while Acp53Ea and Acp70A experienced purifying selection in both subgroups. These proteins have thus remained targets for similar types of selection over long (>21-MY) periods of time. We also found several indel substitutions and polymorphisms in Acp26Aa and Acp32CD. These indels occur in the same regions as positively selected nucleotide substitutions for Acp26Aa in the D. pseudoobscura subgroup but not in the D. melanogaster subgroup. Rates of indel substitution within Acp26Aa in the D. pseudoobscura subgroup were up to several times those in noncoding regions of the Drosophila genome. This suggests that indel substitutions may be under positive selection and may play a key role in the divergence of some Acps. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. [Reviewing Editor: Dr. Willis Swanson]     

Amino Acid Substitutions of MagA in Klebsiella pneumoniae Affect the Biosynthesis of the Capsular Polysaccharide

Mucoviscosity-associated gene A (magA) of Klebsiella pneumoniae contributes to K1 capsular polysaccharide (CPS) biosynthesis. Based on sequence homology and gene alignment, the magA gene has been predicted to encode a Wzy-type CPS polymerase. Sequence alignment with the Wzy_C and RfaL protein families (which catalyze CPS or lipopolysaccharide (LPS) biosynthesis) and topological analysis has suggested that eight highly conserved residues, including G308, G310, G334, G337, R290, P305, H323, and N324, were located in a hypothetical loop region. Therefore, we used site-directed mutagenesis to study the role of these residues in CPS production, and to observe the consequent phenotypes such as mucoviscosity, serum and phagocytosis resistance, and virulence (as assessed in mice) in pyogenic liver abscess strain NTUH-K2044. Alanine substitutions at R290 or H323 abolished all of these properties. The G308A mutant was severely impaired for these functions. The G334A mutant remained mucoid with decreased CPS production, but its virulence was significantly reduced in vivo. No phenotypic change was observed for strains harboring magA G310A, G337A, P305A, or N324A mutations. Therefore, R290, G308, H323, and G334 are functionally important residues of the MagA (Wzy) protein of K. pneumoniae NTUH-K2044, capsular type K1. These amino acids are also likely to be important for the function of Wzy in other capsular types in K. pneumoniae and other species bearing Wzy_C family proteins.     

从氨基酸序列预测蛋白质折叠速率

蛋白质折叠速率预测是当今生物物理学最具挑战性的课题之一．近年来,许多科研工作者开展了大量的研究工作来探索折叠速率的决定因素,许多参数和方法被相继提出．但氨基酸残基间的相互作用、氨基酸的序列顺序等信息对折叠速率的影响从未被提及．采用伪氨基酸组成的方法提取氨基酸的序列顺序信息,利用蒙特卡洛方法选择最佳特征因子,建立线性回归模型进行折叠速率预测．该方法能在不需要任何(显示)结构信息的情况下,直接从蛋白质的氨基酸序列出发对折叠速率进行预测．在Jackknife交互检验方法的验证下,对含有99个蛋白质的数据集,发现折叠速率的预测值与实验值有很好的相关性,相关系数能达到0.81,预测误差仅为2.54．这一精度明显优于其他基于序列的方法,充分说明蛋白质的序列顺序信息是影响蛋白质折叠速率的重要因素．     

Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

Background

Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information.

Results

AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins.

Conclusion

AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains.     

Single Amino Acid Substitutions in the Chemotactic Sequence of Urokinase Receptor Modulate Cell Migration and Invasion

The receptor for urokinase-type plasminogen activator (uPAR) plays an important role in controlling cell migration. uPAR binds urokinase and vitronectin extracellular ligands, and signals in complex with transmembrane receptors such as Formyl-peptide Receptors (FPR)s and integrins. Previous work from this laboratory has shown that synthetic peptides, corresponding to the uPAR_88–92 chemotactic sequence, when carrying the S90P or S90E substitutions, up- or down-regulate cell migration, respectively. To gain mechanistic insights into these opposite cell responses, the functional consequences of S90P and S90E mutations in full-length uPAR were evaluated. First, (HEK)-293 embryonic kidney cells expressing uPAR^S90P exhibit enhanced FPR activation, increased random and directional cell migration, long-lasting Akt phosphorylation, and increased adhesion to vitronectin, as well as uPAR/vitronectin receptor association. In contrast, the S90E substitution prevents agonist-triggered FPR activation and internalization, decreases binding and adhesion to vitronectin, and inhibits uPAR/vitronectin receptor association. Also, 293/uPAR^S90P cells appear quite elongated and their cytoskeleton well organized, whereas 293/uPAR^S90E cells assume a large flattened morphology, with random orientation of actin filaments. Interestingly, when HT1080 cells co-express wild type uPAR with uPAR S90E, the latter behaves as a dominant-negative, impairing uPAR-mediated signaling and reducing cell wound repair as well as lung metastasis in nude mice. In contrast, signaling, wound repair and in vivo lung metastasis of HT1080 cells bearing wild type uPAR are enhanced when they co-express uPAR^S90P. In conclusion, our findings indicate that Ser⁹⁰ is a critical residue for uPAR signaling and that the S90P and S90E exert opposite effects on uPAR activities. These findings may be accommodated in a molecular model, in which uPAR^S90E and uPAR^S90P are forced into inactive and active forms, respectively, suggesting important implications for the development of novel drugs targeting uPAR function.     

Effects of Specific Amino Acid Substitutions on Activities of Dinitrogenase Reductase-Activating Glycohydrolase from Rhodospirillum rubrum

Site-directed mutagenesis of the draG gene was used to generate altered forms of dinitrogenase reductase-activating glycohydrolase (DRAG) with D123A, H142L, H158N, D243G, and E279R substitutions. The amino acid residues H142 and E279 are not required either for the coordination to the metal center or for catalysis since the variants H142L and E279R retained both catalytic and electron paramagnetic resonance spectral properties similar to those of the wild-type enzyme. Since DRAG-H158N and DRAG-D243G variants lost their ability to bind Mn(II) and to catalyze the hydrolysis of the substrate, H158 and D243 residues could be involved in the coordination of the binuclear Mn(II) center in DRAG.     

Polymorphism Due to Multiple Amino Acid Substitutions at a Codon Site Within Ciona savignyi

We compared two haploid genotypes of one Ciona savignyi individual and identified codons at which these genotypes differ by two nonsynonymous substitutions. Using the C. intestinalis genome as an outgroup, we showed that both substitutions tend to occur in the same genotype. Only in 53 (34.4%) of 154 codons, one substitution occurred in each of the two genotypes, although 77 (50%) of such codons are to be expected if substitutions were independent. We considered two feasible evolutionary causes for the observed pattern: substitutions driven by positive selection and compensatory substitutions, as well as several potential biases. However, none of these explanations is fully compelling, and data on multiple genotypes of C. savignyi would help to elucidate the causes of this pattern.     

氨基酸口服制剂中游离氨基酸的检测与营养、功能评价

对目前市场上销售的 1 2种氨基酸口服制剂中游离氨基酸进行了测试 ,通过对各种制剂中氨基酸种类和组成的分析 ,将其分为营养型、治疗型和载体型三类 ,以FAO的氨基酸模式及化学评分 ,评价了营养型保健制剂的营养价值 ,有些制剂存在着配比不合理的问题 ,限制性氨基酸主要是蛋氨酸和异亮氨酸 ;同时对治疗型和载体型制剂的功能也作出了评价。