Diversity‐oriented biosynthesis of a library of antimycin‐like compounds (380 altogether) was accomplished by using multiplex combinatorial biosynthesis. The core strategy depends on the use of combinatorial chemistry at different biosynthetic stages. This approach is applicable for the diversification of polyketides, nonribosomal peptides, and the hybrids that share a similar biosynthetic logic.
Inactivation of Thiolase by 2-Alkynoyl-CoA via Its Intrinsic Isomerase Activity
作者:Long Wu、Jia Zeng、Guisheng Deng、Fei Guo、Nan Li、Xiaojun Liu、Xiusheng Chu、Ding Li
DOI:10.1021/ol0712677
日期:2007.9.1
Selective inactivation of cytosolic thiolase by 2-alkynoyi-CoA via its intrinsic isomerase activity was studied, which provides an example for rationally developing mechanism-based inhibitors based on a side activity of the enzyme, and may become a supplemental method for better treatment of cardiovascular disease and cancer.
Identification of Compounds with Potential Antibacterial Activity against <i>Mycobacterium</i> through Structure-Based Drug Screening
To identify novel antibiotics against Mycobacterium tuberculosis, we performed a hierarchical structure-based drug screening (SBDS) targeting the enoyl-acyl carrier protein reductase (InhA) with a compound library of 154,118 chemicals. We then evaluated whether the candidate hit compounds exhibited inhibitory effects on the growth of two model mycobacterial strains: Mycobacterium smegmatis and Mycobacterium vanbaalenii. Two compounds (KE3 and KE4) showed potent inhibitory effects against both model mycobacterial strains. In addition, we rescreened KE4 analogs, which were identified from a compound library of 461,383 chemicals through fingerprint analysis and genetic algorithm-based docking simulations. All of the KE4 analogs (KES1 - KES5) exhibited inhibitory effects on the growth of M. smegmatis and/or M. vanbaalenii. Based on the predicted binding modes, we probed the structure-activity relationships of KE4 and its analogs and found a correlative relationship between the IC50 values and the interaction residues/LogP values. The most potent inhibitor, compound KES4, strongly and stably inhibited the long-term growth of the model bacteria and showed higher inhibitory effects (IC50 = 4.8 mu M) than isoniazid (IC50 = 5.4 mu M), which is a first-line drug for tuberculosis therapy. Moreover, compound KES4 did not exhibit any toxic effects that impede cell growth in several mammalian cell lines and enterobacteria. The structural and experimental information of these novel chemical compounds will likely be useful for the development of new anti-TB drugs. Furthermore, the methodology that was used for the identification of the effective chemical compound is also likely to be effective in the SBDS of other candidate medicinal drugs.
Metabolomics-Based Identification of Disease-Causing Agents
申请人:Skolnick Jeffrey
公开号:US20110246081A1
公开(公告)日:2011-10-06
A method, computer-readable medium, and system for identifying one or more metabolites associated with a disease, comprising: comparing gene expression data from diseased cells to gene expression data from control cells in order to deduce genes that are differentially-regulated in the diseased cells relative to the control cells; based on enzyme function and pathway data for all human metabolites that utilize the genes that are differentially-regulated in the disease cells, identifying one or more metabolites whose intracellular levels are higher or lower in diseased cells than in control cells, and thereby associating the one or more metabolites with the disease.
[EN] METABOLOMICS-BASED IDENTIFICATION OF DISEASE-CAUSING AGENTS<br/>[FR] IDENTIFICATION D'AGENTS PROVOQUANT UNE MALADIE BASÉE SUR LA MÉTABOLOMIQUE
申请人:GEORGIA TECH RES INST
公开号:WO2009052186A1
公开(公告)日:2009-04-23
A method, computer-readable medium, and system for identifying one or more metabolites associated with a disease, comprising: comparing gene expression data from diseased cells to gene expression data from control cells in order to deduce genes that are differentially-regulated in the diseased cells relative to the control cells; based on enzyme function and pathway data for all human metabolites that utilize the genes that are differentially-regulated in the disease cells, identifying one or more metabolites whose intracellular levels are higher or lower in diseased cells than in control cells, and thereby associating the one or more metabolites with the disease.