A statistical physics perspective on alignment-independent protein sequence comparison.

Motivation: Within bioinformatics, the textual alignment of amino acid sequences has long dominated the determination of similarity between proteins, with all that implies for shared structure, function, and evolutionary descent. Despite the relative success of modern-day sequence alignment algorithms, so-called alignment-free approaches offer a complementary means of determining and expressing similarity, with potential benefits in certain key applications, such as regression analysis of protein structure-function studies, where alignment-base similarity has performed poorly. Results: Here, we offer a fresh, statistical physics-based perspective focusing on the question of alignment-free comparison, in the process adapting results from “first passage probability distribution” to summarize statistics of ensemble averaged amino acid propensity values. In this paper, we introduce and elaborate this approach.

β-amyloid plaques:Stages in life history or independent origin?

Several types of discrete β-amyloid (Aβ) deposit or senile plaque have been identified in the brains of individuals with Alzheimer's disease and Down's syndrome. The majority of these plaques can be classified into four morphological types: diffuse, primitive, classic and compact. Two hypotheses have been proposed to account for these plaques. Firstly, that the diffuse, primitive, classic and compact plaques develop in sequence and represent stages in the life history of a single plaque type. Secondly, that the different Aβ plaques develop independently and therefore, unique factors are involved in the formation of each type. To attempt to distinguish between these hypotheses, the morphology, ultrastructure, composition, and spatial distribution in the brain of the four types of plaque were compared. Although some primitive plaques may develop from diffuse plaques, the evidence suggests that a unique combination of factors is involved in the pathogenesis of each plaque type and, therefore, supports the hypothesis that the major types of Aβ plaque develop independently.

Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties

Subunit vaccine discovery is an accepted clinical priority. The empirical approach is time- and labor-consuming and can often end in failure. Rational information-driven approaches can overcome these limitations in a fast and efficient manner. However, informatics solutions require reliable algorithms for antigen identification. All known algorithms use sequence similarity to identify antigens. However, antigenicity may be encoded subtly in a sequence and may not be directly identifiable by sequence alignment. We propose a new alignment-independent method for antigen recognition based on the principal chemical properties of protein amino acid sequences. The method is tested by cross-validation on a training set of bacterial antigens and external validation on a test set of known antigens. The prediction accuracy is 83% for the cross-validation and 80% for the external test set. Our approach is accurate and robust, and provides a potent tool for the in silico discovery of medically relevant subunit vaccines.