3 resultados para distance measures
em National Center for Biotechnology Information - NCBI
Resumo:
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.
Resumo:
When many protein sequences are available for estimating the time of divergence between two species, it is customary to estimate the time for each protein separately and then use the average for all proteins as the final estimate. However, it can be shown that this estimate generally has an upward bias, and that an unbiased estimate is obtained by using distances based on concatenated sequences. We have shown that two concatenation-based distances, i.e., average gamma distance weighted with sequence length (d2) and multiprotein gamma distance (d3), generally give more satisfactory results than other concatenation-based distances. Using these two distance measures for 104 protein sequences, we estimated the time of divergence between mice and rats to be approximately 33 million years ago. Similarly, the time of divergence between humans and rodents was estimated to be approximately 96 million years ago. We also investigated the dependency of time estimates on statistical methods and various assumptions made by using sequence data from eubacteria, protists, plants, fungi, and animals. Our best estimates of the times of divergence between eubacteria and eukaryotes, between protists and other eukaryotes, and between plants, fungi, and animals were 3, 1.7, and 1.3 billion years ago, respectively. However, estimates of ancient divergence times are subject to a substantial amount of error caused by uncertainty of the molecular clock, horizontal gene transfer, errors in sequence alignments, etc.
Resumo:
We introduce a new genetic distance for microsatellite loci, incorporating features of the stepwise mutation model, and test its performance on microsatellite polymorphisms in humans, chimpanzees, and gorillas. We find that it performs well in determining the relations among the primates, but less well than other distance measures (not based on the stepwise mutation model) in determining the relations among closely related human populations. However, the deepest split in the human phylogeny seems to be accurately reconstructed by the new distance and separates African and non-African populations. The new distance is independent of population size and therefore allows direct estimation of divergence times if the mutation rate is known. Based on 30 microsatellite polymorphisms and a recently reported average mutation rate of 5.6 x 10(-4) at 15 dinucleotide microsatellites, we estimate that the deepest split in the human phylogeny occurred about 156,000 years ago. Unlike most previous estimates, ours requires no external calibration of the rate of molecular evolution. We can use such calibrations, however, to test our estimate.