GPU-accelerated Chemical Similarity Assessment for Large Scale Databases

The assessment of chemical similarity between molecules is a basic operation in chemoinformatics, a computational area concerning with the manipulation of chemical structural information. Comparing molecules is the basis for a wide range of applications such as searching in chemical databases, training prediction models for virtual screening or aggregating clusters of similar compounds. However, currently available multimillion databases represent a challenge for conventional chemoinformatics algorithms raising the necessity for faster similarity methods. In this paper, we extensively analyze the advantages of using many-core architectures for calculating some commonly-used chemical similarity coefficients such as Tanimoto, Dice or Cosine. Our aim is to provide a wide-breath proof-of-concept regarding the usefulness of GPU architectures to chemoinformatics, a class of computing problems still uncovered. In our work, we present a general GPU algorithm for all-to-all chemical comparison...

• Type: Journal
• Year: 2011
• Where: PROCEDIA
• Authors: Marco Maggioni, Marco D. Santambrogio, Jie Liang
• Keywords: Chemical Similarity, Memory Accesses, Pattern Recognition, PROCEDIA 2011, Similarity Methods