Exhaustive enumeration of protein conformations using experimental restraints.

We present an efficient new algorithm that enumerates all possible conformations of a protein that satisfy a given set of distance restraints. Rapid growth of all possible self-avoiding conformations on the diamond lattice provides construction of alpha-carbon representations of a protein fold. We investigated the dependence of the number of conformations on pairwise distance restraints for the proteins crambin, pancreatic trypsin inhibitor, and ubiquitin. Knowledge of between one and two contacts per monomer is shown to be sufficient to restrict the number of candidate structures to approximately 1,000 conformations. Pairwise RMS deviations of atomic position comparisons between pairs of these 1,000 structures revealed that these conformations can be grouped into about 25 families of structures. These results suggest a new approach to assessing alternative protein folds given a very limited number of distance restraints. Such restraints are available from several experimental techniques such as NMR, NOESY, energy transfer fluorescence spectroscopy, and crosslinking experiments. This work focuses on exhaustive enumeration of protein structures with emphasis on the possible use of NOESY-determined distance restraints.     

Interactions between two sheets of a bilayer membrane and its internal lateral pressure

We have modelled a phospholipid bilayer as two monolayer sheets which interact with each other by a coupling which depends upon the states of the lipid hydrocarbon chains in each sheet. We make use of a model (Georgallas and Pink 1982a) and its parameters, already used to study monolayer phase changes at the LC-LE transition, in order to study the lipid main transition. Although the monolayer coexistence curve can be calculated exactly, we have made use of high-temperature series expansions to calculate the critical point of the bilayer. We also present the results of computer simulations on triangular lattices for the pressure-area isotherms. We find: (i) the interaction between the sheets of a DPPC bilayer is about 1.5–2% of the maximum interaction within the plane of each sheet; (ii) the internal lateral pressure of a DPPC bilayer is about 30.5 dyne/cm; (iii) the bilayer transition enthalpy depends sensitively upon the coupling between the sheets. Should this coupling vary from sample to sample (due, possibly, to its preparation) then very different values of transition enthalpy may be measured. (iv) We present a rough rule-of-thumb for estimating the internal lateral pressure of a bilayer from a knowledge of the corresponding monolayer pressure-area isotherms.Abbreviations LC-LE liquid condensed — liquid expanded - DPPC dipalmitoylphosphatidylcholine - Q transition enthalpy Work supported in part by the Natural Sciences and Engineering Research Council of Canada     

A model for population regulation with density- and frequency-dependent selection

The life-cycle of a species with separate generations is divided into a reproduction phase and a growing-up phase. In the reproduction phase we assume random mating and selection due to genotype differences in fecundity of the parents and viability of the offspring. During the growing-up phase we assume a (deterministic) death process in continuous time with death rates for the genotypes which increase linearly with the genotype population sizes.In the absence of genotype differences the model gives logistic population regulation. With genotype differences the model generalizes the usual separate generations selection patterns. In addition to these we exhibit cases with three polymorphic equilibria or with a stable cycle.     

基于源-库互反馈的温室青椒坐果时空动态模拟

基于源-库互反馈的温室青椒坐果时空动态模拟     

Allometric Models for Predicting Aboveground Biomass in Two Widespread Woody Plants in Hawaii

Allometric models are important for quantifying biomass and carbon storage in terrestrial ecosystems. Generalized allometry exists for tropical trees, but species‐ and site‐specific models are more accurate. We developed species‐specific models to predict aboveground biomass in two of the most ubiquitous natives in Hawaiian forests and shrublands, Metrosideros polymorpha and Dodonaea viscosa. The utility of the M. polymorpha allometry for predicting biomass across a range of sites was explored by comparing size structure (diameter at breast height vs. tree height) of the trees used to develop the models against trees from four M. polymorpha‐dominated forests along a precipitation gradient (1630–2380 mm). We also compared individual tree biomass estimated with the M. polymorpha model against existing generalized equations, and the D. viscosa model with an existing species‐specific model. Our models were highly significant and displayed minimal bias. Metrosideros polymorpha size structures from the three highest precipitation sites fell well within the 95% confidence intervals for the harvested trees, indicating that the models are applicable at these sites. However, size structure in the area with the lowest precipitation differed from those in the higher rainfall sites, emphasizing that care should be taken in applying the models too widely. Existing generalized allometry differed from the M. polymorpha model by up to 88 percent, particularly at the extremes of the data range examined, underestimating biomass in small trees and overestimating in large trees. The existing D. viscosa model underestimated biomass across all sizes by a mean of 43 percent compared to our model. The species‐specific models presented here should enable more accurate estimates of biomass and carbon sequestration in Hawaiian forests and shrublands.     

Proteomic profiling of the hypothalamus in two mouse models of narcolepsy

Narcolepsy is a disabling neurological disorder of sleepiness linked to the loss of neurons producing orexin neuropeptides in the hypothalamus. Two well‐characterized phenotypic mouse models of narcolepsy, loss‐of‐function (orexin‐knockout), and progressive loss of orexin (orexin/ataxin‐3) exist. The open question is whether the proteomics signatures of the hypothalamus would be different between the two models. To address this gap, we utilized a label‐free proteomics approach and conducted a hypothalamic proteome analysis by comparing each disease model to that of wild type. Following data processing and statistical analysis, 14 484 peptides mapping to 2282 nonredundant proteins were identified, of which 39 proteins showed significant differences in protein expression across groups. Altered proteins in both models showed commonalties in pathways for mitochondrial dysfunction and neuronal degeneration, as well as altered proteins related to inflammatory demyelination, insulin resistance, metabolic responses, and the dopaminergic and monoaminergic systems. Model‐specific alterations in insulin degraded enzyme (IDE) and synaptosomal‐associated protein‐25 were unique to orexin‐KO and orexin/ataxin‐3, respectively. For both models, proteomics not only identified clinically suspected consequences of orexin loss on energy homeostasis and neurotransmitter systems, but also identified commonalities in inflammation and degeneration despite the entirely different genetic basis of the two mouse models.     

Structural understanding of stabilization patterns in engineered bispecific Ig‐like antibody molecules

Bispecific immunoglobulin‐like antibodies capable of engaging multiple antigens represent a promising new class of therapeutic agents. Engineering of these molecules requires optimization of the molecular properties of one of the domain components. Here, we present a detailed crystallographic and computational characterization of the stabilization patterns in the lymphotoxin‐beta receptor (LTβR) binding Fv domain of an anti‐LTβR/anti‐TNF‐related apoptosis inducing ligand receptor‐2 (TRAIL‐R2) bispecific immunoglobulin‐like antibody. We further describe a new hierarchical structure‐guided approach toward engineering of antibody‐like molecules to enhance their thermal and chemical stability. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data‐model integration

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data‐model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model‐data benchmarking; and data assimilation and ecological forecasting. This community‐driven approach is a key to meeting the pressing needs of science and society in the 21st century.