Functional restraints on the patterns of amino acid substitutions: application to sequence-structure homology recognition

Amino acid residues that are involved in functional interactions in proteins have strong evolutionary pressure to remain unchanged and consequently their substitution patterns are different from those that are noninteracting. To characterize and quantify the differences between amino acid substitution patterns due to structural restraints and those under functional restraints, we have made a comparative analysis of families of homologous proteins. Residues classified as having the same amino acid type, secondary structure, accessibility, and side-chain hydrogen bonds are shown to be better conserved if they are close to the active site. We have focused on enzyme families for this analysis since they have functional sites that are easily defined by their catalytic residues. We have derived new sets of environment-specific substitution tables, which we term function-dependent environment-specific substitution tables, where amino acid residues are classified according to their distance from the functional sites. The residues that are within a distance of 9 A from the active site have distinct amino acid substitution patterns when compared to the other sites. The function-dependent environment-specific substitution tables have been tested using the sequence-structure homology recognition program FUGUE and the results compared with the recognition performance obtained using the standard environment-specific substitution tables. Significant improvements are obtained in both recognition performance and alignment accuracy using the function-dependent environment-specific substitution tables (P-value = 0.02, according to the Wilcoxon signed rank test for alignment accuracy). The alignments near the active site are greatly improved with pronounced improvements at lower percentage identities (less than 30%).     

Quantifying Structural and Functional Restraints on Amino Acid Substitutions in Evolution of Proteins

One of Oleg Ptitsyn's most important papers (Shakhnovich, E., Abkevich, V., and Ptitsyn, O. (1996) Nature, 379, 96-98) describes how knowledge of structure and function can be used to understand better the nature of amino acid substitutions in families and superfamilies of proteins. The selective advantages of retaining structure and function during evolution can be expressed as restraints on the amino acid substitutions that are accepted.     

Urban and rural differences in mortality and causes of death in historical Poland

The purpose of this paper is to document and interpret urban-rural differences in mortality in the past. To this end, we used data on mortality in Wielkopolska, Poland, in the 19th century and at the beginning of the 20th century. The data on mortality in rural areas (N = 1,173,910 deceased), small towns (N = 573,903 deceased), and Poznań, the capital of the Wielkopolska region (N = 86,352 deceased), were gathered from original Prussian statistical yearbooks (Preussische Statistik). Causes of death were also analyzed (rural areas, N = 449,576 deceased; small towns, N = 238,365 deceased; Poznań, N = 61,512 deceased). Mortality measures such as crude death rate (CDR), infant death rate (IDR), and neonatal and postneonatal death rates were calculated. Life tables were constructed for both stationary and stable population models and measures of the opportunity for natural selection calculated (Crow's index I(m), potential gross reproduction rate R(pot), and biological state index I(bs)). Relative frequencies of leading causes of death were computed. Stratification depending on the place of residence was evident in all mortality measures as well as in the values of the life tables and the measures of the opportunity for natural selection, but it was reverse of what is observed today in developed countries. In Poznań (a large industrial city), the mortality situation was the least favorable. It was caused by large population density, lack of water supply and sewage systems (up to 1896), and bad working conditions. The values of CDR ranged between 26.89-31.46, and IDR between 190.6-280.5. Newborn life expectancy (for a stable population model) was 31.6 years, I(m) = 0.79, R(pot) = 0.85, and I(bs) = 0.47. The most common causes of death were tuberculosis, other diseases of the respiratory and circulatory systems, dysentery and diarrhea, and cancer. These diseases were less common in rural areas, so they had the most favorable values of mortality measures (CDR between 22.87-27.32, IDR between 181.8-219.4, life expectancy of newborn e(0) = 42.12, I(m) = 0.55, R(pot) = 0.93, I(bs) = 0.60). Infectious diseases (other than tuberculosis), frailty at birth, and frailty in old age were the most frequent causes of death in rural areas. Small towns (population <20,000) had a mortality intermediate between city and rural areas.     

Incorporating marginal covariate information in a nonparametric regression model for a sample of R x C tables

SUMMARY: Nonparametric regression models are proposed in the framework of ecological inference for exploratory modeling of disease prevalence rates adjusted for variables, such as age, ethnicity/race, and socio-economic status. Ecological inference is needed when a response variable and covariate are not available at the subject level because only summary statistics are available for the reporting unit, for example, in the form of R x C tables. In this article, only the marginal counts are assumed available in the sample of R x C contingency tables for modeling the joint distribution of counts. A general form for the ecological regression model is proposed, whereby certain covariates are included as a varying coefficient regression model, whereas others are included as a functional linear model. The nonparametric regression curves are modeled as splines fit by penalized weighted least squares. A data-driven selection of the smoothing parameter is proposed using the pointwise maximum squared bias computed from averaging kernels (explained by O'Sullivan, 1986, Statistical Science 1, 502-517). Analytic expressions for bias and variance are provided that could be used to study the rates of convergence of the estimators. Instead, this article focuses on demonstrating the utility of the estimators in a study of disparity in health outcomes by ethnicity/race.     

Raking Kappa: Describing Potential Impact of Marginal Distributions on Measures of Agreement

Several authors have noted the dependence of kappa measures of inter-rater agreement on the marginal distributions of contingency tables displaying the joint ratings. This paper introduces a smoothed version of kappa computed after raking the table to achieve pre-specified marginal distributions. A comparison of kappa with raked kappa for various margins can indicate the extent of the dependence on the margins, and can indicate how much of the lack of agreement is due to marginal heterogeneity.     

A More Powerful Simultaneous Test Procedure in Configural Frequency Analysis

In the Configural Frequency Analysis (CFA) of KRAUTH and LIENERT (1973 a, b), overfrequented (or underfrequented) cells in multivariate contingency tables are identified by simultaneous binomial tests. As an alternative, finite and asymptotic tests are proposed, which are derived from the (exact conditional) generalized hypergeometrical distribution of the cell frequencies. These tests allow for considerably more powerful decisions than do the conservative binomial tests.