Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation

Background  

Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm.     

人IL-6和TNF突变体重组融合蛋白表达质粒的构建及在大肠杆菌中的表达

本文利用PCR技术,对人肿瘤坏死因子α(hTNFα)基因进行了改造,并将其与人白细胞介素-6(hIL-6)成熟肽编码区cDNA进行融合,构建了5′IL-6-TNF△融合蛋白的表达质粒pBVIL6-TNFA△。DNA序列分析证明,PCR扩增片段核苷酸序列与引物设计序列及相应的cDNA序列完全一致;重组子用限制性内切酶酶切鉴定,含有正确的IL6-TNF△融合cDNA片段;表达产物经SDS-聚丙烯酰胺凝胶电泳,分子量约为37kD,与预计的相符合;生物学活性分析初步表明,该融合蛋白具有抗肿瘤活性。     

马铃薯人工种子的研究

本研究以虎头（Ｈ）、克四（Ｋ）和Ｆａｖｏｒｉｔａ（Ｆ）三个品种的马铃薯不定芽在液体培养条件下诱导生成的微型薯为试材,经筛选后获得的大小一致的微型薯经过适度的低温处理后,用４％的海藻酸钠和２％的氯化钙溶液,在附加一定的植物激素条件下,进行人。种皮包埋形成人工种子。在无菌条件下,三个品种的人工种子萌发率均达９０％以上。在土壤中,人工种子萌发率可达６０％以上,萌发的人工种子中８０％能够形成生长发育正常的完整植株。     

槟榔林冠穿透雨空间格局的时间稳定性

槟榔林是热带地区广泛种植典型经济林,独特的树冠结构改变了穿透雨的空间格局,但针对穿透雨空间格局的时间稳定性研究很少,影响对穿透雨生态效应的认识与调控。以海南岛槟榔林为研究对象,基于33场降雨数据,研究了穿透雨的空间格局及时间特性,结果显示:(1)槟榔树冠内不同位置穿透雨差异极显著(P<0.01),穿透雨率分别为:树干附近(85.6%)、冠幅中央(48.3%)、冠幅边缘(59.8%),穿透雨空间格局表现为向树干附近汇集的特点;不同方位的穿透雨率仅东面显著高于南面(P<0.1),表明风向对穿透雨空间格局具有一定影响。(2)槟榔树冠下各位点穿透雨时间变异程度大(65.7%),但槟榔树冠幅中央穿透雨时间稳定性较好(55.6%),而树干旁边和冠幅边缘穿透雨时间稳定性较差(25%、19.4%),各方位穿透雨的时间稳定性相差不大(约1/3)。(3)距树干距离和降雨量影响穿透雨的时间稳定性,距树干不同距离平均叶片倾斜角度的差异是造成穿透雨在时间上不稳定的关键因素,平均叶片倾斜角度与穿透雨时间不稳定程度呈现显著正相关关系(P<0.05);穿透雨时间稳定性在中等降雨条件下最差,随着降雨量...     

Effect of temperature,pH, dissolved oxygen,and hydrolysate on the formation of triple light chain antibodies in cell culture

THIOMABs are recombinant antibodies with reactive cysteine residues used for forming THIOMAB–drug conjugates (TDCs). We recently reported a new impurity associated with THIOMABs: one of the engineered cysteines forms a disulfide bond with an extra light chain (LC) to generate a triple light chain antibody (3LC). In our previous investigations, increased LC expression increased 3LC levels, whereas increased glutathione (GSH) production decreased 3LC levels. In this work, on three stably transfected CHO cell lines, we investigated the effects of temperature, pH, dissolved oxygen (DO), and hydrolysate on 3LC formation during THIOMAB fed‐batch cell culture production. Although pH between 6.8 and 7.0 had no significant impact on 3LC formation, temperature at 35°C instead of 33 or 31°C generated the lowest 3LC values for two cell lines. The decreased 3LC level correlated with increased GSH production. We implemented a 35°C temperature process for large‐scale (2,000 L) production of a THIOMAB. This process reduced 3LC levels by ～50% compared with a 33°C temperature process. By contrast, DO and hydrolysate had modest effect on 3LC levels for the model cell line studied. Overall, we did not find significant changes in LC expression under the conditions tested, whereas changes in GSH production were more evident. By investigating the impact of bioreactor process and medium conditions on 3LC levels, we identified strategies that reduced 3LC levels. © 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Partial purification of α-amylase from culture supernatant of <Emphasis Type="Italic">Bacillus subtilis</Emphasis> in aqueous two-phase systems

A study was made of the partition and purification of -amylase from a culture supernatant of Bacillus subtilis in the polyethylene glycol (PEG)—citrate aqueous two-phase system (ATPS). Factors that influenced the partition of the protein in this system, including the molecular weight of the PEG, the tie line length of ATPS, the pH value and the sodium chloride concentration, were investigated. Purification of -amylase was attained with a purification factor (PF) of 1.8 and 90% yield at pH 6.0 in a PEG1000-citrate ATPS with short tie line length. By utilizing the salt-out effect of neutral salt, the purification of -amylase was further improved to 2.0 of PF and 80% yield in a PEG3350-citrate ATPS with 4% sodium chloride.     

The institute for genomic research Osa1 rice genome annotation database

We have developed a rice (Oryza sativa) genome annotation database (Osa1) that provides structural and functional annotation for this emerging model species. Using the sequence of O. sativa subsp. japonica cv Nipponbare from the International Rice Genome Sequencing Project, pseudomolecules, or virtual contigs, of the 12 rice chromosomes were constructed. Our most recent release, version 3, represents our third build of the pseudomolecules and is composed of 98% finished sequence. Genes were identified using a series of computational methods developed for Arabidopsis (Arabidopsis thaliana) that were modified for use with the rice genome. In release 3 of our annotation, we identified 57,915 genes, of which 14,196 are related to transposable elements. Of these 43,719 non-transposable element-related genes, 18,545 (42.4%) were annotated with a putative function, 5,777 (13.2%) were annotated as encoding an expressed protein with no known function, and the remaining 19,397 (44.4%) were annotated as encoding a hypothetical protein. Multiple splice forms (5,873) were detected for 2,538 genes, resulting in a total of 61,250 gene models in the rice genome. We incorporated experimental evidence into 18,252 gene models to improve the quality of the structural annotation. A series of functional data types has been annotated for the rice genome that includes alignment with genetic markers, assignment of gene ontologies, identification of flanking sequence tags, alignment with homologs from related species, and syntenic mapping with other cereal species. All structural and functional annotation data are available through interactive search and display windows as well as through download of flat files. To integrate the data with other genome projects, the annotation data are available through a Distributed Annotation System and a Genome Browser. All data can be obtained through the project Web pages at http://rice.tigr.org.     

DNA microarray data imputation and significance analysis of differential expression

MOTIVATION: Significance analysis of differential expression in DNA microarray data is an important task. Much of the current research is focused on developing improved tests and software tools. The task is difficult not only owing to the high dimensionality of the data (number of genes), but also because of the often non-negligible presence of missing values. There is thus a great need to reliably impute these missing values prior to the statistical analyses. Many imputation methods have been developed for DNA microarray data, but their impact on statistical analyses has not been well studied. In this work we examine how missing values and their imputation affect significance analysis of differential expression. RESULTS: We develop a new imputation method (LinCmb) that is superior to the widely used methods in terms of normalized root mean squared error. Its estimates are the convex combinations of the estimates of existing methods. We find that LinCmb adapts to the structure of the data: If the data are heterogeneous or if there are few missing values, LinCmb puts more weight on local imputation methods; if the data are homogeneous or if there are many missing values, LinCmb puts more weight on global imputation methods. Thus, LinCmb is a useful tool to understand the merits of different imputation methods. We also demonstrate that missing values affect significance analysis. Two datasets, different amounts of missing values, different imputation methods, the standard t-test and the regularized t-test and ANOVA are employed in the simulations. We conclude that good imputation alleviates the impact of missing values and should be an integral part of microarray data analysis. The most competitive methods are LinCmb, GMC and BPCA. Popular imputation schemes such as SVD, row mean, and KNN all exhibit high variance and poor performance. The regularized t-test is less affected by missing values than the standard t-test. AVAILABILITY: Matlab code is available on request from the authors.