人白细胞介素－2第20位残基局部空间结构稳定位对活性的影响

用寡核苷酸诱导的基因定位突变法,将人白细胞介素－２（ＩＬ－２）第２０位Ａｓｐ分别突变为Ａｒｇ、Ｌｙｓ．和Ａｓｎ,比较第２０位残基碱性基因对ＩＬ－２活力的影响,结果２０Ａｓｐ突变为碱性残基时,ＩＬ－２活性急剧下降,但突变为Ａｒｇ时所导致的活性下降较突变为Ｌｙｓ严重３０００倍以上,从空间结构变化上对这２个碱性残基造成的如此大的活性差异进行了分析,发现２０Ａｒｇ突变后对。１２１Ｔｒｐ的微环境有极为显著的影响。结果提示２０Ａｓｐ在与β亚基作用的同时,其局部空间结构的稳定对维持ＩＬ－２的生物学活性也有重要作用。     

白细胞介素－2第17和20位残基在结构功能中的重要性研究

用基因定位突变法,将白细胞介素－２（ＩＬ－２）分子中１７Ｌｅｕ和２０Ａｓｐ进行一系列突变,并测定各突变体生物活性与空间结构的变化。分析结果表明１７Ｌｅｕ突变为Ａｓｐ时,ＩＬ－２的空间结构无明显变化。生物活性却显著下降;２０Ａｓｐ突变为Ｌｅｕ,以及１７Ｌｅｕ与２０Ａｓｐ对调后,均导致ＩＬ－２的空间结构发生变化,并严重影响其生物活性。上述结果说明１７Ｌｅｕ突变为Ａｓｐ后对活性的影响并非由空间结构变化所引起,而与残基本身性质有关：１７Ｌｅｕ与２０Ａｓｐ这两个重要的残基,必须位于各自特定的空间位置,才能发挥其生物作用。     

白细胞介素－2分子α螺旋B中的活性相关区域

根据人白细胞介素－２（ＩＬ－２）ａ螺旋Ｂ中氨基酸残基的空间分布选择性地突变了一些氨基酸残基,结果发现．５７Ｇｌｎ→Ｇｌｎ,６２Ｇｌｎ→Ｌｅｕ,６２Ｇｌｎ→Ａｒｇ和６５Ｐｒｏ→Ａｒｇ这些替换均使ＩＬ－２活性显著降低或丧失,而６３Ｌｅｕ→Ｓｅｒ或６４Ｌｙｓ→Ａｌａ对ＩＬ－２活性影响不大。从受体竞争抑制结合实验结果可知,上述不表现活性的突变体也同时丧失了与高亲和力受体的结合能力,这说明α螺旋Ｂ中这些位点对ＩＬ－２与受体结合有贡献,事实上,那些直接与受体β、γ亚基结合的残基所在螺旋为Ａ、Ｄ螺旋而非α螺旋Ｂ,由此我们认为α螺旋Ｂ虽不直接参与与受体β、γ亚基结合,但它在空间结构上对ＩＬ－２与受体β、γ亚基的结合产生了有利的影响,而５７Ｇｌｎ、６２Ｇｌｎ、６５Ｐｒｏ等残基则在此过程中发挥重要作用。     

人白细胞介素—2第20位残基局部空间结构稳定性对活性的影响

用寡核苷酸诱导的基因定位突变法,将人白细胞介素－２（ＩＬ－２）第２０位Ａｓｐ分别突变为Ａｒｇ,Ｌｙｓ和Ａｓｎ,比较第２０位残基碱性基团对ＩＬ－２活力的影响,结果＾２０Ａｓｐ突变为碱性残基时,ＩＬ－２活性急剧下降,但突变为Ａｒｇ时所导致的活性下降较突变为Ｌｙｓ时所导致的活性下降较突变为Ｌｙｓ严重３０００倍以上。从空间结构变化上对这２个碱性残基造成的如此大的活性差异进行了分析,发现＾２０Ａｒｇ突变后对     

白细胞介素—2第17和20位残基在结构功能中的重要性研究

用基因定位突变法,将白细胞介素－２分子中１７Ｌｅｕ和２０Ａｓｐ进行一系列突变,并测定各突变体生物活性与空间结构的变化。分析结果表明１７Ｌｅｕ突变为Ａｓｐ时,ＩＬ－２的空间结构无明显变化,生物活性却显著下降;２０Ａｓｐ突变的为Ｌｅｕ,以及１７Ｌｅｕ与２０Ａｓｐ对调后,均导致ＩＬ－２的空间结构发生变化,并严重影响其生物活性,上述结果说明１７Ｌｅｕ突变为Ａｓｐ后对活性的影响并非由空间结构变化所引起,而与     

白细胞介素－2镇痛功能位点的研究

白细胞介素-2(IL-2)是重要的免疫调节因子,近来发现还有中枢镇痛作用,用不同IL-2突变体测定其对大鼠痛阈的影响,发现完全丧失免疫刺激作用的20Leu-IL-2(20Asp→Leu)仍能显著提高大鼠的痛阈,其作用强度与天然IL-2无显著差异,而另一突变体45Val-IL-2(45Tyr→Val)虽保留免疫学活性却不能提高大鼠的痛阈.这些结果证明IL-2分子中具有镇痛作用与具有免疫作用的功能位点是相互独立的;IL-2分子中第45位Tyr对IL-2镇痛作用的发挥起重要作用.     

定点突变法对人白细胞介素～2C末端α螺旋的结构和功能研究

用寡核苷酸诱导的基因定位突变法,将人白细胞介素－2C末端两亲性α螺旋中125位和127位残基分别或同时突变为Pro,并测定其生物活性和空间结构。结果发现所得突变体的生物学活性均急剧下降,同时α螺旋含量以及C端螺旋中残基的空间位置也发生了不同程度的变化。结果提示,C端α螺旋尤其是其疏水面的完整性对维持白介素－2的生物活性有重要作用。     

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.     

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.     

Predicting the Functional Effect of Amino Acid Substitutions and Indels

As next-generation sequencing projects generate massive genome-wide sequence variation data, bioinformatics tools are being developed to provide computational predictions on the functional effects of sequence variations and narrow down the search of casual variants for disease phenotypes. Different classes of sequence variations at the nucleotide level are involved in human diseases, including substitutions, insertions, deletions, frameshifts, and non-sense mutations. Frameshifts and non-sense mutations are likely to cause a negative effect on protein function. Existing prediction tools primarily focus on studying the deleterious effects of single amino acid substitutions through examining amino acid conservation at the position of interest among related sequences, an approach that is not directly applicable to insertions or deletions. Here, we introduce a versatile alignment-based score as a new metric to predict the damaging effects of variations not limited to single amino acid substitutions but also in-frame insertions, deletions, and multiple amino acid substitutions. This alignment-based score measures the change in sequence similarity of a query sequence to a protein sequence homolog before and after the introduction of an amino acid variation to the query sequence. Our results showed that the scoring scheme performs well in separating disease-associated variants (n = 21,662) from common polymorphisms (n = 37,022) for UniProt human protein variations, and also in separating deleterious variants (n = 15,179) from neutral variants (n = 17,891) for UniProt non-human protein variations. In our approach, the area under the receiver operating characteristic curve (AUC) for the human and non-human protein variation datasets is ∼0.85. We also observed that the alignment-based score correlates with the deleteriousness of a sequence variation. In summary, we have developed a new algorithm, PROVEAN (Protein Variation Effect Analyzer), which provides a generalized approach to predict the functional effects of protein sequence variations including single or multiple amino acid substitutions, and in-frame insertions and deletions. The PROVEAN tool is available online at http://provean.jcvi.org.     

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.     

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.     

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/.     

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.     

The Effects of One Amino Acid Substitutions at the C-Terminal Region of Thermostable L2 Lipase by Computational and Experimental Approach

The substitutions of the amino acid at the predetermined critical point at the C-terminal of L2 lipase may increase its thermostability and enzymatic activity, or even otherwise speed up the unfolding of the protein structure. The C-terminal of most proteins is often flexible and disordered. However, some protein functions are directly related to flexibility and play significant role in enzyme reaction. The critical point for mutation of L2 lipase structure was predicted at the position 385 of the L2 sequence, and the best three mutants were determined based on I-Mutant2.0 software. The best three mutants were S385E, S385I and S385V. The effects of the substitution of the amino acids at the critical point were analysed with molecular dynamics simulation by using Yet Another Scientific Artificial Reality Application software. The predicted mutant L2 lipases were found to have lower root mean square deviation value as compared to L2 lipase. It was indicated that all the three mutants had higher compactness in the structure, consequently enhanced the stability. Root mean square fluctuation analysis showed that the flexibility of L2 lipase was reduced by mutations. Purified S385E lipase had an optimum temperature of 80 °C in Tris–HCl pH 8. The highest enzymatic activity of purified S385E lipase was obtained at 80 °C temperature in Tris–HCl pH 8, while for L2 lipase it was at 70 °C in Glycine–NaOH pH 9. The thermal stability of S385V lipase was enhanced as compared to other protein since that the melting point (T _m) value was at 85.96 °C. S385I lipase was more thermostable compared to recombinant L2 lipase and other mutants at temperature 60 °C within 16 h preincubation.