Measures of residue density in protein structures

A hierarchy of residue density assessments and packing properties in protein structures are contrasted, including a regular density, a variety of charge densities, a hydrophobic density, a polar density, and an aromatic density. These densities are investigated by alternative distance measures and also at the interface of multiunit structures. Amino acids are divided into nine structural categories according to three secondary structure states and three solvent accessibility levels. To take account of amino acid abundance differences across protein structures, we normalize the observed density by the expected density defining a density index. Solvent accessibility levels exert the predominant influence in determinations of the regular residue density. Explicitly, the regular density values vary approximately linearly with respect to solvent accessibility levels, the linearity parameters depending on the amino acid. The charge index reveals pronounced inequalities between lysine and arginine in their interactions with acidic residues. The aromatic density calculations in all structural categories parallel the regular density calculations, indicating that the aromatic residues are distributed as a random sample of all residues. Moreover, aromatic residues are found to be over-represented in the neighborhood of all amino acids. This result might be attributed to nucleation sites and protein stability being substantially associated with aromatic residues.

Sources of selection bias in evaluating social programs: An interpretation of conventional measures and evidence on the effectiveness of matching as a program evaluation method

This paper decomposes the conventional measure of selection bias in observational studies into three components. The first two components are due to differences in the distributions of characteristics between participant and nonparticipant (comparison) group members: the first arises from differences in the supports, and the second from differences in densities over the region of common support. The third component arises from selection bias precisely defined. Using data from a recent social experiment, we find that the component due to selection bias, precisely defined, is smaller than the first two components. However, selection bias still represents a substantial fraction of the experimental impact estimate. The empirical performance of matching methods of program evaluation is also examined. We find that matching based on the propensity score eliminates some but not all of the measured selection bias, with the remaining bias still a substantial fraction of the estimated impact. We find that the support of the distribution of propensity scores for the comparison group is typically only a small portion of the support for the participant group. For values outside the common support, it is impossible to reliably estimate the effect of program participation using matching methods. If the impact of participation depends on the propensity score, as we find in our data, the failure of the common support condition severely limits matching compared with random assignment as an evaluation estimator.