Literature DB >> 26678650

Privacy-preserving search for chemical compound databases.

Kana Shimizu, Koji Nuida, Hiromi Arai, Shigeo Mitsunari, Nuttapong Attrapadung, Michiaki Hamada, Koji Tsuda, Takatsugu Hirokawa, Jun Sakuma, Goichiro Hanaoka, Kiyoshi Asai.   

Abstract

BACKGROUND: Searching for similar compounds in a database is the most important process for in-silico drug screening. Since a query compound is an important starting point for the new drug, a query holder, who is afraid of the query being monitored by the database server, usually downloads all the records in the database and uses them in a closed network. However, a serious dilemma arises when the database holder also wants to output no information except for the search results, and such a dilemma prevents the use of many important data resources.
RESULTS: In order to overcome this dilemma, we developed a novel cryptographic protocol that enables database searching while keeping both the query holder's privacy and database holder's privacy. Generally, the application of cryptographic techniques to practical problems is difficult because versatile techniques are computationally expensive while computationally inexpensive techniques can perform only trivial computation tasks. In this study, our protocol is successfully built only from an additive-homomorphic cryptosystem, which allows only addition performed on encrypted values but is computationally efficient compared with versatile techniques such as general purpose multi-party computation. In an experiment searching ChEMBL, which consists of more than 1,200,000 compounds, the proposed method was 36,900 times faster in CPU time and 12,000 times as efficient in communication size compared with general purpose multi-party computation.
CONCLUSION: We proposed a novel privacy-preserving protocol for searching chemical compound databases. The proposed method, easily scaling for large-scale databases, may help to accelerate drug discovery research by making full use of unused but valuable data that includes sensitive information.

Entities:  

Mesh:

Year:  2015        PMID: 26678650      PMCID: PMC4704467          DOI: 10.1186/1471-2105-16-S18-S6

Source DB:  PubMed          Journal:  BMC Bioinformatics        ISSN: 1471-2105            Impact factor:   3.169


  7 in total

1.  Do structurally similar molecules have similar biological activity?

Authors:  Yvonne C Martin; James L Kofron; Linda M Traphagen
Journal:  J Med Chem       Date:  2002-09-12       Impact factor: 7.446

Review 2.  Chemical database techniques in drug discovery.

Authors:  Mitchell A Miller
Journal:  Nat Rev Drug Discov       Date:  2002-03       Impact factor: 84.694

Review 3.  Open PHACTS: semantic interoperability for drug discovery.

Authors:  Antony J Williams; Lee Harland; Paul Groth; Stephen Pettifer; Christine Chichester; Egon L Willighagen; Chris T Evelo; Niklas Blomberg; Gerhard Ecker; Carole Goble; Barend Mons
Journal:  Drug Discov Today       Date:  2012-06-07       Impact factor: 7.851

Review 4.  Recent developments in focused library design: targeting gene-families.

Authors:  Jennifer L Miller
Journal:  Curr Top Med Chem       Date:  2006       Impact factor: 3.295

5.  Flawed arithmetic on drug development costs.

Authors:  Nidhi Subbaraman
Journal:  Nat Biotechnol       Date:  2011-05       Impact factor: 54.908

6.  Unpublished results hide the decline effect.

Authors:  Jonathan Schooler
Journal:  Nature       Date:  2011-02-24       Impact factor: 49.962

7.  ChEMBL: a large-scale bioactivity database for drug discovery.

Authors:  Anna Gaulton; Louisa J Bellis; A Patricia Bento; Jon Chambers; Mark Davies; Anne Hersey; Yvonne Light; Shaun McGlinchey; David Michalovich; Bissan Al-Lazikani; John P Overington
Journal:  Nucleic Acids Res       Date:  2011-09-23       Impact factor: 16.971

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.