Estimating the probability for a protein to have a new fold: A statistical computational model

Structural genomics aims to solve a large number of protein structures that represent the protein space. Currently an exhaustive solution for all structures seems prohibitively expensive, so the challenge is to define a relatively small set of proteins with new, currently unknown folds. This paper presents a method that assigns each protein with a probability of having an unsolved fold. The method makes extensive use of protomap, a sequence-based classification, and scop, a structure-based classification. According to protomap, the protein space encodes the relationship among proteins as a graph whose vertices correspond to 13,354 clusters of proteins. A representative fold for a cluster with at least one solved protein is determined after superposition of all scop (release 1.37) folds onto protomap clusters. Distances within the protomap graph are computed from each representative fold to the neighboring folds. The distribution of these distances is used to create a statistical model for distances among those folds that are already known and those that have yet to be discovered. The distribution of distances for solved/unsolved proteins is significantly different. This difference makes it possible to use Bayes' rule to derive a statistical estimate that any protein has a yet undetermined fold. Proteins that score the highest probability to represent a new fold constitute the target list for structural determination. Our predicted probabilities for unsolved proteins correlate very well with the proportion of new folds among recently solved structures (new scop 1.39 records) that are disjoint from our original training set.

Computational method to reduce the search space for directed protein evolution

We introduce a computational method to optimize the in vitro evolution of proteins. Simulating evolution with a simple model that statistically describes the fitness landscape, we find that beneficial mutations tend to occur at amino acid positions that are tolerant to substitutions, in the limit of small libraries and low mutation rates. We transform this observation into a design strategy by applying mean-field theory to a structure-based computational model to calculate each residue's structural tolerance. Thermostabilizing and activity-increasing mutations accumulated during the experimental directed evolution of subtilisin E and T4 lysozyme are strongly directed to sites identified by using this computational approach. This method can be used to predict positions where mutations are likely to lead to improvement of specific protein properties.

The effect of 4,4′-diisothiocyanato-stilbene-2,2′-disulfonate on CO2 permeability of the red blood cell membrane

It has long been assumed that the red cell membrane is highly permeable to gases because the molecules of gases are small, uncharged, and soluble in lipids, such as those of a bilayer. The disappearance of 12C18O16O from a red cell suspension as the 18O exchanges between labeled CO2 + HCO3− and unlabeled HOH provides a measure of the carbonic anhydrase (CA) activity (acceleration, or A) inside the cell and of the membrane self-exchange permeability to HCO3− (Pm,HCO−3). To test this technique, we added sufficient 4,4′-diisothiocyanato-stilbene-2,2′-disulfonate (DIDS) to inhibit all the HCO3−/Cl− transport protein (Band III or capnophorin) in a red cell suspension. We found that DIDS reduced Pm,HCO−3 as expected, but also appeared to reduce intracellular A, although separate experiments showed it has no effect on CA activity in homogenous solution. A decrease in Pm,CO2 would explain this finding. With a more advanced computational model, which solves for CA activity and membrane permeabilities to both CO2 and HCO3−, we found that DIDS inhibited both Pm,HCO−3 and Pm,CO2, whereas intracellular CA activity remained unchanged. The mechanism by which DIDS reduces CO2 permeability may not be through an action on the lipid bilayer itself, but rather on a membrane transport protein, implying that this is a normal route for at least part of red cell CO2 exchange.

Theory for normal and impaired experience-dependent plasticity in neocortex of adult rats

We model experience-dependent plasticity in the cortical representation of whiskers (the barrel cortex) in normal adult rats, and in adult rats that were prenatally exposed to alcohol. Prenatal exposure to alcohol (PAE) caused marked deficits in experience-dependent plasticity in a cortical barrel-column. Cortical plasticity was induced by trimming all whiskers on one side of the face except two. This manipulation produces high activity from the intact whiskers that contrasts with low activity from the cut whiskers while avoiding any nerve damage. By a computational model, we show that the evolution of neuronal responses in a single barrel-column after this sensory bias is consistent with the synaptic modifications that follow the rules of the Bienenstock, Cooper, and Munro (BCM) theory. The BCM theory postulates that a neuron possesses a moving synaptic modification threshold, θM, that dictates whether the neuron's activity at any given instant will lead to strengthening or weakening of its input synapses. The current value of θM changes proportionally to the square of the neuron's activity averaged over some recent past. In the model of alcohol impaired cortex, the effective θM has been set to a level unattainable by the depressed levels of cortical activity leading to “impaired” synaptic plasticity that is consistent with experimental findings. Based on experimental and computational results, we discuss how elevated θM may be related to (i) reduced levels of neurotransmitters modulating plasticity, (ii) abnormally low expression of N-methyl-d-aspartate receptors (NMDARs), and (iii) the membrane translocation of Ca2+/calmodulin-dependent protein kinase II (CaMKII) in adult rat cortex subjected to prenatal alcohol exposure.

Faithful representation of similarities among three-dimensional shapes in human vision.

Efficient and reliable classification of visual stimuli requires that their representations reside a low-dimensional and, therefore, computationally manageable feature space. We investigated the ability of the human visual system to derive such representations from the sensory input-a highly nontrivial task, given the million or so dimensions of the visual signal at its entry point to the cortex. In a series of experiments, subjects were presented with sets of parametrically defined shapes; the points in the common high-dimensional parameter space corresponding to the individual shapes formed regular planar (two-dimensional) patterns such as a triangle, a square, etc. We then used multidimensional scaling to arrange the shapes in planar configurations, dictated by their experimentally determined perceived similarities. The resulting configurations closely resembled the original arrangements of the stimuli in the parameter space. This achievement of the human visual system was replicated by a computational model derived from a theory of object representation in the brain, according to which similarities between objects, and not the geometry of each object, need to be faithfully represented.

Designing safer chemicals: predicting the rates of metabolism of halogenated alkanes.

A computational model is presented that can be used as a tool in the design of safer chemicals. This model predicts the rate of hydrogen-atom abstraction by cytochrome P450 enzymes. Excellent correlations between biotransformation rates and the calculated activation energies (delta Hact) of the cytochrome P450-mediated hydrogen-atom abstractions were obtained for the in vitro biotransformation of six halogenated alkanes (1-fluoro-1,1,2,2-tetrachloroethane, 1,1-difluoro-1,2,2-trichloroethane, 1,1,1-trifluro-2,2-dichloroethane, 1,1,1,2-tetrafluoro-2-chloroethane, 1,1,1,2,2,-pentafluoroethane, and 2-bromo-2-chloro-1,1,1-trifluoroethane) with both rat and human enzyme preparations: In(rate, rat liver microsomes) = 44.99 - 1.79(delta Hact), r2 = 0.86; In(rate, human CYP2E1) = 46.99 - 1.77(delta Hact), r2 = 0.97 (rates are in nmol of product per min per nmol of cytochrome P450 and energies are in kcal/mol). Correlations were also obtained for five inhalation anesthetics (enflurane, sevoflurane, desflurane, methoxyflurane, and isoflurane) for both in vivo and in vitro metabolism by humans: In[F(-)]peak plasma = 42.87 - 1.57(delta Hact), r2 = 0.86. To our knowledge, these are the first in vivo human metabolic rates to be quantitatively predicted. Furthermore, this is one of the first examples where computational predictions and in vivo and in vitro data have been shown to agree in any species. The model presented herein provides an archetype for the methodology that may be used in the future design of safer chemicals, particularly hydrochlorofluorocarbons and inhalation anesthetics.

A neuronal model of a global workspace in effortful cognitive tasks

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

A model for individual and collective cell movement in Dictyostelium discoideum

The cellular slime mold Dictyostelium discoideum is a widely used model system for studying a variety of basic processes in development, including cell–cell signaling, signal transduction, pattern formation, cell motility, and the movement of tissue-like aggregates of cells. Many aspects of cell motion are poorly understood, including how individual cell behavior produces the collective motion of cells observed within the mound and slug. Herein, we describe a biologically realistic model for motile D. discoideum cells that can generate active forces, that interact via surface molecules, and that can detect and respond to chemotactic signals. We model the cells as deformable viscoelastic ellipsoids and incorporate signal transduction and cell–cell signaling by using a previously developed model. The shape constraint restricts the admissible deformations but makes the simulation of a large number of interacting cells feasible. Because the model is based on known processes, the parameters can be estimated or measured experimentally. We show that this model can reproduce the observations on the chemotactic behavior of single cells, streaming during aggregation, and the collective motion of an aggregate of cells driven by a small group of pacemakers. The model predicts that the motion of two-dimensional slugs [Bonner, J. T. (1998) Proc. Natl. Acad. Sci. USA 95, 9355–9359] results from the same behaviors that are exhibited by individual cells; it is not necessary to invoke different mechanisms or behaviors. Our computational experiments also suggest previously uncharacterized phenomena that may be experimentally observable.

GeneSplicer: a new computational method for splice site prediction

GeneSplicer is a new, flexible system for detecting splice sites in the genomic DNA of various eukaryotes. The system has been tested successfully using DNA from two reference organisms: the model plant Arabidopsis thaliana and human. It was compared to six programs representing the leading splice site detectors for each of these species: NetPlantGene, NetGene2, HSPL, NNSplice, GENIO and SpliceView. In each case GeneSplicer performed comparably to the best alternative, in terms of both accuracy and computational efficiency.

A model of multiplicative neural responses in parietal cortex.

Visual responses of neurons in parietal area 7a are modulated by a combined eye and head position signal in a multiplicative manner. Neurons with multiplicative responses can act as powerful computational elements in neural networks. In the case of parietal cortex, multiplicative gain modulation appears to play a crucial role in the transformation of object locations from retinal to body-centered coordinates. It has proven difficult to uncover single-neuron mechanisms that account for neuronal multiplication. Here we show that multiplicative responses can arise in a network model through population effects. Specifically, neurons in a recurrently connected network with excitatory connections between similarly tuned neurons and inhibitory connections between differently tuned neurons can perform a product operation on additive synaptic inputs. The results suggest that parietal responses may be based on this architecture.

Direct measurement of salt-bridge solvation energies using a peptide model system: implications for protein stability.

The solvation energies of salt bridges formed between the terminal carboxyl of the host pentapeptide AcWL- X-LL and the side chains of Arg or Lys in the guest (X) position have been measured. The energies were derived from octanol-to-buffer transfer free energies determined between pH 1 and pH 9. 13C NMR measurements show that the salt bridges form in the octanol phase, but not in the buffer phase, when the side chains and the terminal carboxyl group are charged. The free energy of salt-bridge formation in octanol is approximately -4 kcal/mol (1 cal = 4.184 J), which is equal to or slightly larger than the sum of the solvation energies of noninteracting pairs of charged side chains. This is about one-half the free energy that would result from replacing a charge pair in octanol with a pair of hydrophobic residues of moderate size. Therefore, salt bridging in octanol can change the favorable aqueous solvation energy of a pair of oppositely charged residues to neutral or slightly unfavorable but cannot provide the same free energy decrease as hydrophobic residues. This is consistent with recent computational and experimental studies of protein stability.