A wide variety of properties of amino acids have been investigated through a large number of experiments and theoretical studies. Each of these amino acid properties that can be represented by a set of 20 numerical values is referred to as an amino acid index. ( 1) collected 222 amino acid indices from published literature and investigated the relationships among them using hierarchical cluster analysis. They also released the amino acid indices as an online database. In 1996, Tomii and Kanehisa ( 2) further collected amino acid indices to enrich the database. Additionally, they also collected 42 amino acid substitution matrices from the literature and released the collection as AAindex2. The AAindex database is continuously updated by the present authors ( 3, 4).ĪAindex has been used in wide-ranging bioinformatics research on protein sequences, such as predicting protein subcellular localization ( 5), immunogenicity of MHC class I binding peptides ( 6), protein SUMO modification site ( 7) and coordinated substitutions in multiple alignments of protein sequences ( 8). Furthermore, there is a derivative database of AAindex (UMBC AAindex Database: ) and a web tool for visualizing relationships among AAindex entries ( 9). Given the examples cited here, AAindex has become a useful resource in bioinformatics. ( 10) compared 29 published matrices of protein pairwise contact potentials, i.e. energy functions that are obtained from statistical analysis of protein structures ( 10). These potentials have long been used to predict protein structures in silico. Pokarowski and coworkers elucidated that each of the contact potentials is similar to one of two popular matrices derived by Miyazawa and Jernigan ( 11). Recently, working on 29 mostly new amino acid substitution matrices and 5 contact potentials, the same team ( 12) obtained segregation of substitution matrices similar to Tomii and Kanehisa ( 2). Moreover, they found intermediate links between substitution matrices and contact potentials-matrices and potentials that exhibit mutual correlations of at least 0.8. In both works ( 10, 12), Pokarowski and coworkers approximated matrices by simple functions of amino acid indices, which allow us to comprehend better the exchangeability of amino acids as well as the residue–residue interactions in proteins. These relations between substitution matrices, contact potentials and amino acid indices provide motivation to extend the AAindex database. In the present work, we have compiled the data collected in the study on contact potentials ( 10) as a new section of AAindex database, named AAindex3. As a result we believe that the AAindex has increased its utility in the bioinformatics study of proteins. In this paper we report the current status of the three sections of AAindex. The AAIndex1 currently contains 544 amino acid indices. Each entry consists of an accession number, a short description of the index, the reference information and the numerical values for the properties of 20 amino acids. We have provided a link to the corresponding PubMed entries of each AAindex entry, instead of a link to the LitDB literature database ( 13) that we originally used. In addition, each entry contains cross-links to other entries with an absolute value for the correlation coefficient of 0.8 or larger. The links enable the users to identify a set of entries describing similar properties. In some instances the values are not reported for all 20 amino acids. To represent an overview of the relationships among current amino acids indices, we constructed the minimum spanning tree of amino acid indices by the procedure described by Tomii et al.
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