Detecting the native ligand orientation by interfacial rigidity: SiteInterlock

Understanding the physical attributes of protein‐ligand interfaces, the source of most biological activity, is a fundamental problem in biophysics. Knowing the characteristic features of interfaces also enables the design of molecules with potent and selective interactions. Prediction of native protein‐ligand interactions has traditionally focused on the development of physics‐based potential energy functions, empirical scoring functions that are fit to binding data, and knowledge‐based potentials that assess the likelihood of pairwise interactions. Here we explore a new approach, testing the hypothesis that protein‐ligand binding results in computationally detectable rigidification of the protein‐ligand interface. Our SiteInterlock approach uses rigidity theory to efficiently measure the relative interfacial rigidity of a series of small‐molecule ligand orientations and conformations for a number of protein complexes. In the majority of cases, SiteInterlock detects a near‐native binding mode as being the most rigid, with particularly robust performance relative to other methods when the ligand‐free conformation of the protein is provided. The interfacial rigidification of both the protein and ligand prove to be important characteristics of the native binding mode. This measure of rigidity is also sensitive to the spatial coupling of interactions and bond‐rotational degrees of freedom in the interface. While the predictive performance of SiteInterlock is competitive with the best of the five other scoring functions tested, its measure of rigidity encompasses cooperative rather than just additive binding interactions, providing novel information for detecting native‐like complexes. SiteInterlock shows special strength in enhancing the prediction of native complexes by ruling out inaccurate poses. Proteins 2016; 84:1888–1901. © 2016 Wiley Periodicals, Inc.     

Circadian variations in self-monitoring,a component of executive functions

The objective of this study was to identify circadian rhythms in self-monitoring, a component of executive functions. Participants were 10 undergraduate students, age: 18.5 ± 2.68 years, two male and eight female. They were recorded on a 30-h constant routine protocol; rectal temperature was recorded every minute and performance on a tracking task was assessed every 100 min. Self-monitoring indicators were adjustments of responses to random changes of speed and trajectory of a circle moving on the computer screen. Participants showed better accuracy during the afternoon, with decreases in the morning (06:20 and 08:00 h). These variations showed a phase delay of 2:29 ± 2:19 h with respect to the circadian rhythm of body temperature. In conclusion, there are circadian variations in self-monitoring. The decline in this component of executive functions could cause serious accidents among people working or studying during a morning shift, as well as commuting to and from work or school.     

Population Dynamics and Damage Potential of Meloidogyne hapla to Rose Rootstock Species

The relationship between initial population densities (Pi) of Meloidogyne hapla on growth of three rose rootstocks (Rosa corymbifera ‘Laxa’, R. multiflora and R. canina ‘Inermis’) and nematode population development was studied. Each plant species was inoculated with ranges of nematode densities of 0, 0.062, 0.125, 0.25, 0.50, 1, 2, 4, 8, 16, 32, 64 and 128 second‐stage juvenile/g soil and were allowed to grow for 9 weeks. Seinhorst yield model was fitted to total fresh biomass data of the rootstocks. The tolerance limits (T) were 0.04, 0.09 and 0.01 J2/g soil and the minimum yield (m) 0.65, 0.47 and 0.43 for R. corymbifera ‘Laxa’, R. multiflora and R. canina ‘Inermis’, respectively. The reproductive factor (Pf/Pi) was highest at low initial nematode densities for all rootstocks and then decreased to below maintenance level with increasing initial population densities. Root gall severity consistently increased with initial nematode population density. Furthermore, number of root galling showed a strong positive relationship with final nematode population per gram root fresh weight. The relation between Pi and Pf was also fitted to the Seinhorst population model (Pf = (M*Pi)/Pi + M/a). Rosa multiflora supported the population of M. hapla to a maximum population density (M) of 27.53 J2/g soil with an estimated average maximum multiplication rate (a) of 24.39. For R. corymbifera ‘Laxa’ and R. canina, the maximum multiplication rate was 4.34 and 3.62 and the maximum population density 6.08 and 4.78 J2/g dry soil, respectively. Hence, it was demonstrated that all three rootstocks were susceptible to even low initial nematode densities and therefore are considered good hosts for M. hapla.     

Adaptive neuro-fuzzy inference system: Estimation of soil aggregates stability

In present study, the capabilities of multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions (PTFs) for estimating geometric mean diameter (GMD) and mean weight diameter (MWD), from routine soil properties and combination of routine soil properties and fractal dimension of aggregates were evaluated. For this reason 101 samples were collected form the Northwest of Iran and some their properties such as soil texture, pH, cation exchange capacity (CEC), and organic matter (OM), fractal dimension of aggregates between number-diameter (Dn), mass-diameter (Dmt), and bulk density-diameter (Dmy) were determined and used as an input variables for determining of mean weight diameter (MWD) and geometric mean diameter (GMD) by MLR and ANFIS PTFs. Results showed that the application of fractal dimension of aggregates as a predictor in two methods improved the accuracy of PTFs. As well as, results showed that ANFIS have greater potential for determination of the relationships between soil aggregate stability indices and other soil properties in compared with MLR. Therefore using of adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions is recommended.     

Influence of N-glycosylation on effector functions and thermal stability of glycoengineered IgG1 monoclonal antibody with homogeneous glycoforms

Glycosylation of the conserved asparagine residue in each heavy chain of IgG in the CH2 domain is known as N-glycosylation. It is one of the most common post-translational modifications and important critical quality attributes of monoclonal antibody (mAb) therapeutics. Various studies have demonstrated the effects of the Fc N-glycosylation on safety, Fc effector functions, and pharmacokinetics, both dependent and independent of neonatal Fc receptor (FcRn) pathway. However, separation of various glycoforms to investigate the biological and functional relevance of glycosylation is a major challenge, and existing studies often discuss the overall impact of N-glycans, without considering the individual contributions of each glycoform when evaluating mAbs with highly heterogeneous distributions. In this study, chemoenzymatic glycoengineering incorporating an endo-β-N-acetylglucosaminidase (ENGase) EndoS2 and its mutant with transglycosylation activity was used to generate mAb glycoforms with highly homogeneous and well-defined N-glycans to better understand and precisely evaluate the effect of each N-glycan structure on Fc effector functions and protein stability. We demonstrated that the core fucosylation, non-reducing terminal galactosylation, sialylation, and mannosylation of IgG1 mAb N-glycans impact not only on FcγRIIIa binding, antibody-dependent cell-mediated cytotoxicity, and C1q binding, but also FcRn binding, thermal stability and propensity for protein aggregation.     

In vivo glyco-engineered antibody with improved lytic potential produced by an innovative non-mammalian expression system

Recent studies have demonstrated that the reduction of the core fucosylation on N-glycans of human IgGs is responsible for a clearly enhanced antibody-dependent cellular cytotoxicity (ADCC). This finding might give access to improved active therapeutic antibodies. Here, the expression of the tumor antigen-specific antibody IGN311 was performed in a glyco-optimized strain of the moss Physcomitrella patens. Removal of plant specific N-glycan structures in this plant expression host was achieved by targeted knockout of corresponding genes and included quantitative elimination of core fucosylation. Antibodies transiently expressed and secreted by such genetically modified moss protoplasts assembled correctly, showed an unaltered antigen-binding affinity and, in extensive tests, revealed an up to 40-fold enhanced ADCC. Thus, the glyco-engineered moss-based transient expression platform combines a rapid technology with the subsequent analysis of glycooptimized therapeutics with regard to advanced properties.     

植物M/MLD类受体蛋白激酶及其生物学功能的研究进展北大核心CSCD

植物受体蛋白激酶通过与胞外信号结合感知和接收外部信号传递,在植物各个生理过程及生物代谢中发挥着重大的作用。其中M/MLD类受体蛋白激酶是一类植物特有的具有Malectin-like结构域的受体蛋白激酶。研究表明,M/MLD-RLKs亚家族参与植物发育过程及生物/非生物胁迫调控。该研究对近年来国内外有关植物M/MLD-RLKs的发现、结构特点以及生物学功能等方面的研究进展进行综述,并重点阐述其在调控植物根系、叶片、花发育及响应多种胁迫过程中的作用,为深入研究M/MLD-RLKs在植物生长发育过程中的生理功能提供参考。     

土壤原生生物多样性及其生态功能研究进展

原生生物广泛分布在土壤和不同生境中, 其数量庞大、种类繁多, 在生态系统物质循环和能量流动以及维持土壤和植物健康中起着举足轻重的作用。与土壤其他生物类群相比, 原生生物分类体系和生态类型复杂, 分类鉴定困难且分子检测技术不够成熟, 目前对原生生物的认识相对不足。本文对当前原生生物的相关研究进展进行了总结和梳理, 系统阐述了原生生物的分类系统和营养功能群特征、土壤原生生物的多样性分布特征及影响因子, 重点介绍了原生生物群落在参与土壤养分循环、维持土壤和植物健康等中的功能作用, 并对未来的研究方向与应用前景进行了展望。对土壤原生生物的研究有助于我们深入认识土壤生物多样性资源, 并进行保护性地开发和利用, 维护土壤和生态系统健康。     

Selection for novel metabolic capabilities in Salmonella enterica

Bacteria are known to display extensive metabolic diversity and many studies have shown that they can use an extensive repertoire of small molecules as carbon‐ and energy sources. However, it is less clear to what extent a bacterium can expand its existing metabolic capabilities by acquiring mutations that, for example, rewire its metabolic pathways. To investigate this capability and potential for evolution of novel phenotypes, we sampled large populations of mutagenized Salmonella enterica to select very rare mutants that can grow on minimal media containing 124 low molecular weight compounds as sole carbon sources. We found mutants growing on 18 of these novel carbon sources, and identified the causal mutations that allowed growth for four of them. Mutations that relieve physiological constraints or increase expression of existing pathways were found to be important contributors to the novel phenotypes. For the remaining 14 novel phenotypes, whole genome sequencing of independent mutants and genetic analysis suggested that these novel metabolic phenotypes result from a combination of multiple mutations. This work, by virtue of identifying the genetic and mechanistic basis for new metabolic capabilities, sheds light on the properties of adaptive landscapes underlying the evolution of novel phenotypes.