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Sinatti VVC, Gonçalves CAX, Romão-Dumaresq AS. Identification of metabolites identical and similar to drugs as candidates for metabolic engineering. J Biotechnol 2019; 302:67-76. [PMID: 31254549 DOI: 10.1016/j.jbiotec.2019.06.303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 04/20/2019] [Accepted: 06/25/2019] [Indexed: 11/18/2022]
Abstract
Natural compounds and derivatives play an essential role in the pharmaceutical industry, however, the difficulty in resynthesizing natural products or isolate them from the native host, often limit their availability, elevate costs and slow down the pharmaceutical manufacturing process. In this context, application of synthetic biology could enable the efficient production of large amounts of drugs or drug precursors in heterologous microorganisms aiming to accelerate the entire manufacturing process. Considering this perspective, here we developed a pipeline to automatically search for metabolites available in the metabolic space that are structurally similar to worldwide approved drugs. This pipeline involved the in silico screening of metabolites from a metabolic pathway meta-database using both Tanimoto coefficients based on Daylight like fingerprints and Maximum Common Substructure algorithm. The method was successfully applied to identify metabolites sharing essential scaffolds with one or more drugs as potential candidates for metabolic engineering. Three of these metabolites (Festuclavine, Scopolamine, and Baccatin III) were identified as similar to many drugs like Cabergoline, Oxitropium, Paclitaxel and had their metabolic pathways computationally mapped for their production in Saccharomyces cerevisiae with our proprietary pathway design software. These compounds are examples of new opportunities for the application of synthetic biology in pharmaceutical production.
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Affiliation(s)
- Vanessa V C Sinatti
- SENAI Innovation Institute for Biosynthetics, Technology Center for Chemical and Textile Industry, Rio de Janeiro, Brazil.
| | - Carlos Alberto X Gonçalves
- SENAI Innovation Institute for Biosynthetics, Technology Center for Chemical and Textile Industry, Rio de Janeiro, Brazil
| | - Aline S Romão-Dumaresq
- SENAI Innovation Institute for Biosynthetics, Technology Center for Chemical and Textile Industry, Rio de Janeiro, Brazil
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Tiwari R, Ahire D, Kumar H, Sinha S, Chauthe SK, Subramanian M, Iyer R, Sarabu R, Bajpai L. Use of Hybrid Capillary Tube Apparatus on 400 MHz NMR for Quantitation of Crucial Low-Quantity Metabolites Using aSICCO Signal. Drug Metab Dispos 2017; 45:1215-1224. [PMID: 28935657 DOI: 10.1124/dmd.117.077073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 09/13/2017] [Indexed: 11/22/2022] Open
Abstract
Metabolites of new chemical entities can influence safety and efficacy of a molecule and often times need to be quantified in preclinical studies. However, synthetic standards of metabolites are very rarely available in early discovery. Alternate approaches such as biosynthesis need to be explored to generate these metabolites. Assessing the quantity and purity of these small amounts of metabolites with a nondestructive analytical procedure becomes crucial. Quantitative NMR becomes the method of choice for these samples. Recent advances in high-field NMR (>500 MHz) with the use of cryoprobe technology have helped to improve sensitivity for analysis of small microgram quantity of such samples. However, this type of NMR instrumentation is not routinely available in all laboratories. To analyze microgram quantities of metabolites on a routine basis with lower-resolution 400 MHz NMR instrument fitted with a broad band fluorine observe room temperature probe, a novel hybrid capillary tube setup was developed. To quantitate the metabolite in the sample, an artificial signal insertion for calculation of concentration observed (aSICCO) method that introduces an internally calibrated mathematical signal was used after acquiring the NMR spectrum. The linearity of aSICCO signal was established using ibuprofen as a model analyte. The limit of quantification of this procedure was 0.8 mM with 10 K scans that could be improved further with the increase in the number of scans. This procedure was used to quantify three metabolites-phenytoin from fosphenytoin, dextrophan from dextromethorphan, and 4-OH-diclofenac from diclofenac-and is suitable for minibiosynthesis of metabolites from in vitro systems.
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Affiliation(s)
- Ranjeet Tiwari
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Deepak Ahire
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Hemantha Kumar
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Sarmistha Sinha
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Siddheshwar Kisan Chauthe
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Murali Subramanian
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Ramaswamy Iyer
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Ramakanth Sarabu
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
| | - Lakshmikant Bajpai
- Discovery Analytical Sciences (R.T., H.K., S.K.C., R.S., L.B.) and Pharmaceutical Candidate Optimization (D.A., S.S., M.S.), Bristol-Myers Squibb-Biocon Research Center, Bangalore, India; and Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Princeton, New Jersey (R.I.)
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Guo W, Sheng J, Feng X. Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2017; 162:265-299. [PMID: 28424826 DOI: 10.1007/10_2017_2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Metabolic engineering of industrial microorganisms to produce chemicals, fuels, and drugs has attracted increasing interest as it provides an environment-friendly and renewable route that does not depend on depleting petroleum sources. However, the microbial metabolism is so complex that metabolic engineering efforts often have difficulty in achieving a satisfactory yield, titer, or productivity of the target chemical. To overcome this challenge, 13C Metabolic Flux Analysis (13C-MFA) has been developed to investigate rigorously the cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, 13C-MFA has been widely used in academic labs and the biotechnology industry to pinpoint the key issues related to microbial-based chemical production and to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this chapter we introduce the basics of 13C-MFA and illustrate how 13C-MFA has been applied to synergize with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production.
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Affiliation(s)
- Weihua Guo
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA
| | - Jiayuan Sheng
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA
| | - Xueyang Feng
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA.
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