A structural census of the current population of protein sequences

We examine the occurrence of the ≈300 known protein folds in different groups of organisms. To do this, we characterize a large fraction of the currently known protein sequences (≈140,000) in structural terms, by matching them to known structures via sequence comparison (or by secondary-structure class prediction for those without structural homologues). Overall, we find that an appreciable fraction of the known folds are present in each of the major groups of organisms (e.g., bacteria and eukaryotes share 156 of 275 folds), and most of the common folds are associated with many families of nonhomologous sequences (i.e., >10 sequence families for each common fold). However, different groups of organisms have characteristically distinct distributions of folds. So, for instance, some of the most common folds in vertebrates, such as globins or zinc fingers, are rare or absent in bacteria. Many of these differences in fold usage are biologically reasonable, such as the folds of metabolic enzymes being common in bacteria and those associated with extracellular transport and communication being common in animals. They also have important implications for database-based methods for fold recognition, suggesting that an unknown sequence from a plant is more likely to have a certain fold (e.g., a TIM barrel) than an unknown sequence from an animal.

Prediction of protein folding class using global description of amino acid sequence.

We present a method for predicting protein folding class based on global protein chain description and a voting process. Selection of the best descriptors was achieved by a computer-simulated neural network trained on a data base consisting of 83 folding classes. Protein-chain descriptors include overall composition, transition, and distribution of amino acid attributes, such as relative hydrophobicity, predicted secondary structure, and predicted solvent exposure. Cross-validation testing was performed on 15 of the largest classes. The test shows that proteins were assigned to the correct class (correct positive prediction) with an average accuracy of 71.7%, whereas the inverse prediction of proteins as not belonging to a particular class (correct negative prediction) was 90-95% accurate. When tested on 254 structures used in this study, the top two predictions contained the correct class in 91% of the cases.

Intermediate-term earthquake prediction.

An earthquake of magnitude M and linear source dimension L(M) is preceded within a few years by certain patterns of seismicity in the magnitude range down to about (M - 3) in an area of linear dimension about 5L-10L. Prediction algorithms based on such patterns may allow one to predict approximately 80% of strong earthquakes with alarms occupying altogether 20-30% of the time-space considered. An area of alarm can be narrowed down to 2L-3L when observations include lower magnitudes, down to about (M - 4). In spite of their limited accuracy, such predictions open a possibility to prevent considerable damage. The following findings may provide for further development of prediction methods: (i) long-range correlations in fault system dynamics and accordingly large size of the areas over which different observed fields could be averaged and analyzed jointly, (ii) specific symptoms of an approaching strong earthquake, (iii) the partial similarity of these symptoms worldwide, (iv) the fact that some of them are not Earth specific: we probably encountered in seismicity the symptoms of instability common for a wide class of nonlinear systems.

beta2 knockout mice develop parenchymal iron overload: A putative role for class I genes of the major histocompatibility complex in iron metabolism.

Hemochromatosis (HC) is an inherited disorder of iron absorption, mapping within the human major histocompatibility complex (MHC). We have identified a multigene system in the murine MHC that contains excellent candidates for the murine equivalent of the human HC locus and implicate nonclassical class I genes in the control of iron absorption. This gene system is characterized by multiple copies of two head-to-head genes encoded on opposite strands and driven by one common regulatory motif. This regulatory motif has a striking homology to the promoter region of the beta-globin gene, a gene obviously involved in iron metabolism and hence termed beta-globin analogous promoter (betaGAP). Upstream of the betaGAP sequence are nonclassical class I genes. At least one of these nonclassical class I genes, Q2, is expressed in the gastrointestinal tract, the primary site of iron absorption. Also expressed in the gastrointestinal tract and downstream of the betaGAP motif is a second set of putative genes, termed Hephaestus (HEPH). Based on these observations, we hypothesized that the genes that seem to be controlled by the betaGAP regulatory motifs would be responsible for the control of Fe absorption. As a test of this hypothesis, we predicted that mice which have altered expression of class I gene products, the beta2-microglobulin knockout mice, [beta2m(-/-)], would develop Fe overload. This prediction was confirmed, and these results indicate beta2m-associated proteins are involved in the control of intestinal Fe absorption.