Surrogate data--a secure way to share corporate data.
J Comput Aided Mol Des
; 19(9-10): 749-64, 2005.
Article
em En
| MEDLINE
| ID: mdl-16267691
ABSTRACT
The privacy of chemical structure is of paramount importance for the industrial sector, in particular for the pharmaceutical industry. At the same time, companies handle large amounts of physico-chemical and biological data that could be shared in order to improve our molecular understanding of pharmacokinetic and toxicological properties, which could lead to improved predictivity and shorten the development time for drugs, in particular in the early phases of drug discovery. The current study provides some theoretical limits on the information required to produce reverse engineering of molecules from generated descriptors and demonstrates that the information content of molecules can be as low as less than one bit per atom. Thus theoretically just one descriptor can be used to completely disclose the molecular structure. Instead of sharing descriptors, we propose to share surrogate data. The sharing of surrogate data is nothing else but sharing of reliably predicted molecules. The use of surrogate data can provide the same information as the original set. We consider the practical application of this idea to predict lipophilicity of chemical compounds and we demonstrate that surrogate and real (original) data provides similar prediction ability. Thus, our proposed strategy makes it possible not only to share descriptors, but also complete collections of surrogate molecules without the danger of disclosing the underlying molecular structures.
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Temas:
ECOS
/
Estado_mercado_regulacao
Bases de dados:
MEDLINE
Assunto principal:
Bases de Dados Factuais
/
Segurança Computacional
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
J Comput Aided Mol Des
Assunto da revista:
BIOLOGIA MOLECULAR
/
ENGENHARIA BIOMEDICA
Ano de publicação:
2005
Tipo de documento:
Article
País de afiliação:
Ucrânia