Peptide design by artificial neural networks and computer-based evolutionary search

A technique for systematic peptide variation by a combination of rational and evolutionary approaches is presented. The design scheme consists of five consecutive steps: (i) identification of a “seed peptide” with a desired activity, (ii) generation of variants selected from a physicochemical space around the seed peptide, (iii) synthesis and testing of this biased library, (iv) modeling of a quantitative sequence-activity relationship by an artificial neural network, and (v) de novo design by a computer-based evolutionary search in sequence space using the trained neural network as the fitness function. This strategy was successfully applied to the identification of novel peptides that fully prevent the positive chronotropic effect of anti-β1-adrenoreceptor autoantibodies from the serum of patients with dilated cardiomyopathy. The seed peptide, comprising 10 residues, was derived by epitope mapping from an extracellular loop of human β1-adrenoreceptor. A set of 90 peptides was synthesized and tested to provide training data for neural network development. De novo design revealed peptides with desired activities that do not match the seed peptide sequence. These results demonstrate that computer-based evolutionary searches can generate novel peptides with substantial biological activity.

Simple neural networks for the amplification and utilization of small changes in neuron firing rates

I describe physiologically plausible “voter-coincidence” neural networks such that secondary “coincidence” neurons fire on the simultaneous receipt of sufficiently large sets of input pulses from primary sets of neurons. The networks operate such that the firing rate of the secondary, output neurons increases (or decreases) sharply when the mean firing rate of primary neurons increases (or decreases) to a much smaller degree. In certain sensory systems, signals that are generally smaller than the noise levels of individual primary detectors, are manifest in very small increases in the firing rates of sets of afferent neurons. For such systems, this kind of network can act to generate relatively large changes in the firing rate of secondary “coincidence” neurons. These differential amplification systems can be cascaded to generate sharp, “yes–no” spike signals that can direct behavioral responses.

The neural development and organization of letter recognition: Evidence from functional neuroimaging, computational modeling, and behavioral studies

Although much of the brain’s functional organization is genetically predetermined, it appears that some noninnate functions can come to depend on dedicated and segregated neural tissue. In this paper, we describe a series of experiments that have investigated the neural development and organization of one such noninnate function: letter recognition. Functional neuroimaging demonstrates that letter and digit recognition depend on different neural substrates in some literate adults. How could the processing of two stimulus categories that are distinguished solely by cultural conventions become segregated in the brain? One possibility is that correlation-based learning in the brain leads to a spatial organization in cortex that reflects the temporal and spatial clustering of letters with letters in the environment. Simulations confirm that environmental co-occurrence does indeed lead to spatial localization in a neural network that uses correlation-based learning. Furthermore, behavioral studies confirm one critical prediction of this co-occurrence hypothesis, namely, that subjects exposed to a visual environment in which letters and digits occur together rather than separately (postal workers who process letters and digits together in Canadian postal codes) do indeed show less behavioral evidence for segregated letter and digit processing.

Self-organized phase transitions in neural networks as a neural mechanism of information processing.

Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition. The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns. The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern. The reverse transition may be induced by the Hebbian unlearning process without input. The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input. To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stays near the critical state corresponding to the phase transition point.

Transforming neural computations and representing time

Motifs of neural circuitry seem surprisingly conserved over different areas of neocortex or of paleocortex, while performing quite different sensory processing tasks. This apparent paradox may be resolved by the fact that seemingly different problems in sensory information processing are related by transformations (changes of variables) that convert one problem into another. The same basic algorithm that is appropriate to the recognition of a known odor quality, independent of the strength of the odor, can be used to recognize a vocalization (e.g., a spoken syllable), independent of whether it is spoken quickly or slowly. To convert one problem into the other, a new representation of time sequences is needed. The time that has elapsed since a recent event must be represented in neural activity. The electrophysiological hallmarks of cells that are involved in generating such a representation of time are discussed. The anatomical relationships between olfactory and auditory pathways suggest relevant experiments. The neurophysiological mechanism for the psychophysical logarithmic encoding of time duration would be of direct use for interconverting olfactory and auditory processing problems. Such reuse of old algorithms in new settings and representations is related to the way that evolution develops new biochemistry.

Expression of the mouse cerberus-related gene, Cerr1, suggests a role in anterior neural induction and somitogenesis

The Xenopus cerberus gene encodes a secreted factor that is expressed in the anterior endomesoderm of gastrula stage embryos and can induce the formation of ectopic heads when its mRNA is injected into Xenopus embryos [Bouwmeester, T., Kim, S., Lu, B. & De Robertis, E. M. (1996) Nature (London) 382, 595–601]. Here we describe the existence of a cerberus-related gene, Cerr1, in the mouse. Cerr1 encodes a putative secreted protein that is 48% identical to cerberus over a 110-amino acid region. Analysis of a mouse interspecific backcross panel demonstrated that Cerr1 mapped to the central portion of mouse chromosome 4. In early gastrula stage mouse embryos, Cerr1 is expressed in the anterior visceral endoderm and in the anterior definitive endoderm. In somite stage embryos, Cerr1 expression is restricted to the most recently formed somites and in the anterior presomitic mesoderm. Germ layer explant recombination assays demonstrated that Cerr1-expressing somitic-presomitic mesoderm, but not older Cerr1-nonexpressing somitic mesoderm, was able to mimic the anterior neuralizing ability of anterior mesendoderm and maintain Otx2 expression in competent ectoderm. In most Lim1−/− headless embryos, Cerr1 expression in the anterior endoderm was weak or absent. These results suggest that Cerr1 may play a role in anterior neural induction and somite formation during mouse development.

Heterogeneity of subcellular localization and electrophoretic mobility of survival motor neuron (SMN) protein in mammalian neural cells and tissues

Spinal muscular atrophy is caused by defects in the survival motor neuron (SMN) gene. To better understand the patterns of expression of SMN in neuronal cells and tissues, we raised a polyclonal antibody (abSMN) against a synthetic oligopeptide from SMN exon 2. AbSMN immunostaining in neuroblastoma cells and mouse and human central nervous system (CNS) showed intense labeling of nuclear “gems,” along with prominent nucleolar immunoreactivity in mouse and human CNS tissues. Strong cytoplasmic labeling was observed in the perikarya and proximal dendrites of human spinal motor neurons but not in their axons. Immunoblot analysis revealed a 34-kDa species in the insoluble protein fractions from human SY5Y neuroblastoma cells, embryonic mouse spinal cord cultures, and human CNS tissue. By contrast, a 38-kDa species was detected in the cytosolic fraction of SY5Y cells. We conclude that SMN protein is expressed prominently in both the cytoplasm and nucleus in multiple types of neurons in brain and spinal cord, a finding consistent with a role for SMN as a determinant of neuronal viability.

Caspase-1 is activated in neural cells and tissue with amyotrophic lateral sclerosis-associated mutations in copper-zinc superoxide dismutase

The mechanism by which mutations in the superoxide dismutase (SOD1) gene cause motor neuron degeneration in familial amyotrophic lateral sclerosis (ALS) is unknown. Recent reports that neuronal death in SOD1-familial ALS is apoptotic have not documented activation of cell death genes. We present evidence that the enzyme caspase-1 is activated in neurons expressing mutant SOD1 protein. Proteolytic processing characteristic of caspase-1 activation is seen both in spinal cords of transgenic ALS mice and neurally differentiated neuroblastoma (line N2a) cells with SOD1 mutations. This activation of caspase-1 is enhanced by oxidative challenge (xanthine/xanthine oxidase), which triggers cleavage and secretion of the interleukin 1β converting enzyme substrate, pro-interleukin 1β, and induces apoptosis. This N2a culture system should be an instructive in vitro model for further investigation of the proapoptotic properties of mutant SOD1.

bcl-x is expressed in embryonic and postnatal neural tissues and functions to prevent neuronal cell death.

Previous studies have implicated the bcl-2 protooncogene as a potential regulator of neuronal survival. However, mice lacking functional bcl-2 exhibited normal development and maintenance of the central nervous system (CNS). Since bcl-2 appears dispensable for neuronal survival, we have examined the expression and function of bcl-x, another member of the bcl-2 family of death regulatory genes. Bcl-2 is expressed in neuronal tissues during embryonic development but is down-regulated in the adult CNS. In contrast, Bcl-xL expression is retained in neurons of the adult CNS. Two different forms of bcl-x mRNA and their corresponding products, Bcl-xL and Bcl-x beta, were expressed in embryonic and adult neurons of the CNS. Microinjection of bcl-xL and bcl-x beta cDNAs into primary sympathetic neurons inhibited their death induced by nerve growth factor withdrawal. Thus, Bcl-x proteins appear to play an important role in the regulation of neuronal survival in the adult CNS.