Size-distribution analysis of proteins by analytical ultracentrifugation: strategies and application to model systems.

Strategies for the deconvolution of diffusion in the determination of size-distributions from sedimentation velocity experiments were examined and developed. On the basis of four different model systems, we studied the differential apparent sedimentation coefficient distributions by the time-derivative method, g(s*), and by least-squares direct boundary modeling, ls-g*(s), the integral sedimentation coefficient distribution by the van Holde-Weischet method, G(s), and the previously introduced differential distribution of Lamm equation solutions, c(s). It is shown that the least-squares approach ls-g*(s) can be extrapolated to infinite time by considering area divisions analogous to boundary divisions in the van Holde-Weischet method, thus allowing the transformation of interference optical data into an integral sedimentation coefficient distribution G(s). However, despite the model-free approach of G(s), for the systems considered, the direct boundary modeling with a distribution of Lamm equation solutions c(s) exhibited the highest resolution and sensitivity. The c(s) approach requires an estimate for the size-dependent diffusion coefficients D(s), which is usually incorporated in the form of a weight-average frictional ratio of all species, or in the form of prior knowledge of the molar mass of the main species. We studied the influence of the weight-average frictional ratio on the quality of the fit, and found that it is well-determined by the data. As a direct boundary model, the calculated c(s) distribution can be combined with a nonlinear regression to optimize distribution parameters, such as the exact meniscus position, and the weight-average frictional ratio. Although c(s) is computationally the most complex, it has the potential for the highest resolution and sensitivity of the methods described.     

The construction in vitro of transducing derivatives of phage lambda

Summary Methods are described for the construction of plaque-forming, transducing derivatives of phage lambda, using appropriate receptor genomes and fragments of DNA generated by the restriction enzymes endo R.EcoRI and endo R.HindIII. The general properties of the transducing derivatives are described and discussed. Plaque-forming phages carrying the E. coli trp, his, cysB, thyA, supD, supE, supF, hsd, tna and lig genes have been isolated.     

Comparative flavonoid glycoside biochemistry as a chemotaxonomic tool in the subdivision of the classical ‘genus’ Lycopodium

A wide variety of novel flavone 5-O-glucosides has been isolated from Lycopodium scariosum. The predominance of tricin derivatives in this species is not in accord with earlier proposed chemotaxonomic definitions of the sub-groups within the classical genus Lycopodium L. cernuum is the first lycopod found to contain flavone C-glycosides and its suggested taxonomic separation from other members of the group is thus substantiated. Flavonoid glycosides appear to offer more definitive chemotaxonomic characters than do the previously used aglycones and modification of the chemical definitions of the sub-groups in these terms is necessary.     

Challenges in the design of insulin and relaxin/insulin-like peptide mimetics

Peptidomimetics are designed to overcome the poor pharmacokinetics and pharmacodynamics associated with the native peptide or protein on which they are based. The design of peptidomimetics starts from developing structure-activity relationships of the native ligand-target pair that identify the key residues that are responsible for the biological effect of the native peptide or protein. Then minimization of the structure and introduction of constraints are applied to create the core active site that can interact with the target with high affinity and selectivity. Developing peptidomimetics is not trivial and often challenging, particularly when peptides’ interaction mechanism with their target is complex. This review will discuss the challenges of developing peptidomimetics of therapeutically important insulin superfamily peptides, particularly those which have two chains (A and B) and three disulfide bonds and whose receptors are known, namely insulin, H2 relaxin, H3 relaxin, INSL3 and INSL5.     

From mutations to mechanisms and dysfunction via computation and mining of protein energy landscapes

Background

The protein energy landscape underscores the inherent nature of proteins as dynamic molecules interconverting between structures with varying energies. Reconstructing a protein’s energy landscape holds the key to characterizing a protein’s equilibrium conformational dynamics and its relationship to function. Many pathogenic mutations in protein sequences alter the equilibrium dynamics that regulates molecular interactions and thus protein function. In principle, reconstructing energy landscapes of a protein’s healthy and diseased variants is a central step to understanding how mutations impact dynamics, biological mechanisms, and function.

Results

Recent computational advances are yielding detailed, sample-based representations of protein energy landscapes. In this paper, we propose and describe two novel methods that leverage computed, sample-based representations of landscapes to reconstruct them and extract from them informative local structures that reveal the underlying organization of an energy landscape. Such structures constitute landscape features that, as we demonstrate here, can be utilized to detect alterations of landscapes upon mutation.

Conclusions

The proposed methods detect altered protein energy landscape features in response to sequence mutations. By doing so, the methods allow formulating hypotheses on the impact of mutations on specific biological activities of a protein. This work demonstrates that the availability of energy landscapes of healthy and diseased variants of a protein opens up new avenues to harness the quantitative information embedded in landscapes to summarize mechanisms via which mutations alter protein dynamics to percolate to dysfunction.

     

Sugar beet extract acts as a natural bio-stimulant for physio-biochemical attributes in water stressed wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

The present study investigated the role of sugar beet extract (SBE) as a bio-stimulant to ameliorate the adverse effects of drought on seed germination and growth of wheat (Triticum aestivum L.). Different concentrations of SBE (0, 10, 20, 30, 40 and 50%) were used for priming the wheat seeds. The experiment was conducted in laboratory (PEG-8000 was used to create water stress) as well as under natural environmental conditions (using soil with 100 and 60% field capacity). Significant ameliorating effects of seed priming with SBE were recorded on different germination attributes, i.e., time to 50% emergence (E₅₀), germination index (GI), mean emergence time (MET), germination percentage (G%), coefficient of uniformity of emergence (CUE) and germination energy (GE) under water stress. Without priming, the plants exhibited symptoms of water stress like decreased biomass, reduction in photosynthetic pigments, e.g., chlorophyll, carotenoids. Seed pre-conditioning with SBE improved the plant growth, photosynthetic pigments, antioxidants’ activities and nutrient homeostasis of plants facing water deficit and grown under well-watered conditions. The maximum increase in biomass, content of chlorophyll, carotenoids and activities of superoxide dismutase (SOD) and peroxidase (POD) was 13.4, 8.5, 11.9, 7.6, 13.6, 42.0, 19.8%, respectively, with SBE seed priming under water stress. In conclusion, SBE seed priming effectively reduced the negativities of water stress on seed germination which resulted in better plant growth in terms of enhanced biomass, photosynthetic pigments, antioxidant defense mechanism and better nutrient homeostasis. Overall, the findings suggest that seed pre-conditioning with SBE as a bio-stimulant will be helpful for better crop stand establishment under low field capacity, especially in semi-arid and arid agricultural fields.