An alphabetic code based atomic level molecular similarity search in databases.

ABSTRACT: Atomic level molecular similarity and diversity studies have gained considerable importance through their wide application in Bioinformatics and Chemo-informatics for drug design. The availability of large volumes of data on chemical compounds requires new methodologies for efficient and effective searching of its archives in less time with optimal computational power. We describe an alphabetic algorithm for similarity searching based on atom-atom bonding preference for ligands. We represented 170 cyclindependent kinase 2 inhibitors using strings of pre-defined alphabets for searching using known protein sequence alignment tools. Thus, a common pattern was extracted using this set of compounds for database searching to retrieve similar active compounds. Area under the receiver operating ch

SUBMITTER: Saranya N 

PROVIDER: S-EPMC3398777 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature