Natural product libraries to accelerate the high-throughput discovery of therapeutic leads.

Autor: Johnson TA; Department of Nutritional Sciences & Toxicology, University of California, Berkeley, California 94720, USA. taj_ucb@berkeley.edu, Sohn J, Inman WD, Estee SA, Loveridge ST, Vervoort HC, Tenney K, Liu J, Ang KK, Ratnam J, Bray WM, Gassner NC, Shen YY, Lokey RS, McKerrow JH, Boundy-Mills K, Nukanto A, Kanti A, Julistiono H, Kardono LB, Bjeldanes LF, Crews P
Jazyk: angličtina
Zdroj: Journal of natural products [J Nat Prod] 2011 Dec 27; Vol. 74 (12), pp. 2545-55. Date of Electronic Publication: 2011 Nov 30.
DOI: 10.1021/np200673b
Abstrakt: A high-throughput (HT) paradigm generating LC-MS-UV-ELSD-based natural product libraries to discover compounds with new bioactivities and or molecular structures is presented. To validate this methodology, an extract of the Indo-Pacific marine sponge Cacospongia mycofijiensis was evaluated using assays involving cytoskeletal profiling, tumor cell lines, and parasites. Twelve known compounds were identified including latrunculins (1-4, 10), fijianolides (5, 8, 9), mycothiazole (11), aignopsanes (6, 7), and sacrotride A (13). Compounds 1-5 and 8-11 exhibited bioactivity not previously reported against the parasite T. brucei, while 11 showed selectivity for lymphoma (U937) tumor cell lines. Four new compounds were also discovered including aignopsanoic acid B (13), apo-latrunculin T (14), 20-methoxy-fijianolide A (15), and aignopsane ketal (16). Compounds 13 and 16 represent important derivatives of the aignopsane class, 14 exhibited inhibition of T. brucei without disrupting microfilament assembly, and 15 demonstrated modest microtubule-stabilizing effects. The use of removable well plate libraries to avoid false positives from extracts enriched with only one or two major metabolites is also discussed. Overall, these results highlight the advantages of applying modern methods in natural products-based research to accelerate the HT discovery of therapeutic leads and/or new molecular structures using LC-MS-UV-ELSD-based libraries.
Databáze: MEDLINE