MISC

2008年9月

Design of potent aspartic protease inhibitors to treat various diseases

ARCHIV DER PHARMAZIE
  • Jeffrey-Tri Nguyen
  • ,
  • Yoshio Hamada
  • ,
  • Tooru Kimura
  • ,
  • Yoshiaki Kiso

341
9
開始ページ
523
終了ページ
535
記述言語
英語
掲載種別
書評論文,書評,文献紹介等
DOI
10.1002/ardp.200700267
出版者・発行元
WILEY-V C H VERLAG GMBH

In this retrospective, personal review covering our research from the late 1980s until 2007, we outline nearly two-decade worth of our own work on several aspartic protease inhibitors including those affecting renin, HIV-1 protease, plasmepsins, beta-secretase, and HTLV-I protease and we report on aspartic protease inhibitors as potential drugs to treat hypertension, AIDS, malaria, Alzheimer's disease and adult T-cell leukemia, HTLV-I associated myelopathy / tropical spastic paraparesis, and various, respectively, associated diseases. Herein, we describe our methods for rational substrate-based drug design of peptidomimetics that potently inhibit the activity of renin, HIV-1 protease, plasmepsins, beta-secretase, and HTLV-I protease accordingly, using an appropriately selected inhibitory residue that contained a hydroxymethylcarbonyl isostere. Although this non-hydrolyzable isostere mimics the transition state that is formed during protein cleavage of a substrate, the isostere-containing inhibitor is not cleaved. We highlight our optimization studies in which we used various techniques and tools such as truncation studies, natural and non-natural amino acid substitution studies, various moieties to promote chemical and pharmacological stability, X-ray crystallography, computer-assisted docking and dynamic simulations, quantitative structure-activity relationship studies, and various other methods that this review can barely mention.

リンク情報
DOI
https://doi.org/10.1002/ardp.200700267
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000259522000002&DestApp=WOS_CPL
ID情報
  • DOI : 10.1002/ardp.200700267
  • ISSN : 0365-6233
  • Web of Science ID : WOS:000259522000002

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