Special Feature

User Panel

My Panel

My Panel

Bookmark Science Articles

Recent News
Bookmark / Share This Science Site

Predicting key example compounds in competitors' patent applications using structural information alone.

Predicting key example compounds in competitors' patent applications using structural information alone. Research Abstract Details 

Research Abstract Table of Contents

Jump to the:

  • Abstract Text of This Paper
  • Journal Published
  • MeSH Keywords of This Abstract
  • Chemicals and Substances Used in this Paper
  • Grants and Granting Agency of this Research
  • Database Accession Numbers Used in this Paper
  • Related Papers
  • Related Research Tags
  • Rate this Research Paper
  • Predicting key example compounds in competitors' patent applications using structural information alone. Abstract Text:

    kazunari hattoriKazunari Hattori,hiroaki wakabayashiHiroaki Wakabayashi,kenta tamakiKenta Tamaki,kazunari hattoriKazunari Hattori,hiroaki wakabayashiHiroaki Wakabayashi,kenta tamakiKenta Tamaki,

    In drug discovery programs, predicting key example compounds in competitors' patent applications is important work for scientists working in the same or in related research areas. In general, medicinal chemists are responsible for this work, and they attempt to guess the identity of key compounds based on information provided in patent applications, such as biological data, scale of reaction, and/or optimization of the salt form for a particular compound. However, this is sometimes made difficult by the lack of such information. This paper describes a method for predicting key compounds in competitors' patent applications by using only structural information of example compounds. Based on the assumption that medicinal chemists usually carry out extensive structure-activity relationship (SAR) studies around key compounds, the method identifies compounds located at the centers of densely populated regions in the patent examples' chemical space, as represented by Extended Connectivity Fingerprints (ECFPs). For the validation of the method, a total of 30 patents containing structures of launched drugs were selected to test whether or not the method is able to predict key compounds (the launched drugs). In 17 out of the 30 patents (57%), the method was able to successfully predict the key compounds. The result indicates that our method could provide an alternative approach to predicting key compounds in cases where the conventional medicinal chemist's approach does not work well. This method could also be used as a complement to the traditional medicinal chemist's approach.

    Predicting key example compounds in competitors' patent applications using structural information alone. Publishing Authors By Initials

    k hattoriK Hattori,h wakabayashiH Wakabayashi,k tamakiK Tamaki,k hattoriK Hattori,h wakabayashiH Wakabayashi,k tamakiK Tamaki,

    For similar abstracts research abstracts see: abstracts research

    PUBMED ID PMID:

    MEDLINE DATE: 2008 Jan-Feb

    Predicting key example compounds in competitors' patent applications using structural information alone. Journal Published:

    PUBLICATION TYPE: Journal Article

    Journal: Journal of chemical information and modeling

    VOLUME: 48

    Page Numbers: 135-42

    Journal Abbreviation:

    ISSN: 1549-9596

    DAY: 5

    MONTH: 01

    YEAR: 2008

    Predicting key example compounds in competitors' patent applications using structural information alone. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 101230060

    Predicting key example compounds in competitors' patent applications using structural information alone. Keywords Mesh Terms:

    KEYWORDS:

    MESH TERMS:

    Chemical & Substance for Abstract: Predicting key example compounds in competitors' patent applications using structural information alone. Information

    Substance Name:

    Registry Number:

    Grant and Affiliation Information for Predicting key example compounds in competitors' patent applications using structural information alone.

    AFFILIATION: Medicinal Chemistry Technologies and Research Informatics, Pfizer Global Research and Development, Nagoya Laboratories, Pfizer Inc., 5-2 Taketoyo, Aichi 470-2393, Japan.

    Country: United States

    United States Research PublicationUnited States Research Publication

    AGENCY:

    GRANT:

    ACRONYM:

    MEDLINETA: J Chem Inf Model

    REFSOURCE:

    DATABASENAME:

    ACCESSION NUMBER:

    Number Hits: 0

    Predicting key example compounds in competitors' patent applications using structural information alone Related Publications

     

    Molecular Station USER Menu

    Welcome to Molecular Station!

    You have to register before you can post on our forums or use our advanced features. Register Now! Its Free and Fast!

    Already registered? Login now below.

    User Name:

    Password:

    Already registered and Forgot your password? Click below to recover it.

    Recover Lost Password

    Join now - it's fast and free!

    Molecular Station is THE largest network of researchers, scientists and science lovers anywhere!

    Research Terms of Usage and Disclaimer
    Home
    Features

    Protocols

    DNA Forum

    Science Forum

    DNA Forum
    Biology Forum

    Science News


    [CaRP] XML error: Invalid document end at line 2

    For more click here:Science News