Coupling effects of distal loops on structural stability and enzymatic activity of Escherichia coli dihydrofolate reductase revealed by deletion mutants

Horiuchi, Yuji; Ohmae, Eiji; Tate, Shin‐ichi; Gekko, Kunihiko

doi:10.1016/j.bbapap.2009.12.011

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…DHFR was chosen for our study because conformational changes and long-range concerted motions are associated with catalysis [10], [11]. For example, based on an ensemble of X-ray structures, DHFR is proposed to transition between an open, occluded and closed conformation during catalysis [12].…”

Section: Introductionmentioning

confidence: 99%

Histidine Hydrogen-Deuterium Exchange Mass Spectrometry for Probing the Microenvironment of Histidine Residues in Dihydrofolate Reductase

et al. 2011

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BackgroundHistidine Hydrogen-Deuterium Exchange Mass Spectrometry (His-HDX-MS) determines the HDX rates at the imidazole C2-hydrogen of histidine residues. This method provides not only the HDX rates but also the pK a values of histidine imidazole rings. His-HDX-MS was used to probe the microenvironment of histidine residues of E. coli dihydrofolate reductase (DHFR), an enzyme proposed to undergo multiple conformational changes during catalysis.Methodology/Principal FindingsUsing His-HDX-MS, the pK a values and the half-lives (t 1/2) of HDX reactions of five histidine residues of apo-DHFR, DHFR in complex with methotrexate (DHFR-MTX), DHFR in complex with MTX and NADPH (DHFR-MTX-NADPH), and DHFR in complex with folate and NADP+ (DHFR-folate-NADP+) were determined. The results showed that the two parameters (pK a and t 1/2) are sensitive to the changes of the microenvironment around the histidine residues. Although four of the five histidine residues are located far from the active site, ligand binding affected their pK a, t 1/2 or both. This is consistent with previous observations of ligand binding-induced distal conformational changes on DHFR. Most of the observed pK a and t 1/2 changes could be rationalized using the X-ray structures of apo-DHFR, DHFR-MTX-NADPH, and DHFR-folate-NADP+. The availability of the neutron diffraction structure of DHFR-MTX enabled us to compare the protonation states of histidine imidazole rings.Conclusions/SignificanceOur results demonstrate the usefulness of His-HDX-MS in probing the microenvironments of histidine residues within proteins.

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Section: Introductionmentioning

confidence: 99%

Histidine Hydrogen-Deuterium Exchange Mass Spectrometry for Probing the Microenvironment of Histidine Residues in Dihydrofolate Reductase

et al. 2011

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“…sensitive loop regions of the protein (35), alone and in combination. The resulting variants were analyzed by their ability to complement an E. coli DHFR knock-out strain that requires an extra-chromosomal DHFR for growth (26).…”

Section: Journal Of Biological Chemistrymentioning

confidence: 99%

Comparative Laboratory Evolution of Ordered and Disordered Enzymes

Schulenburg¹,

Stark

Künzle

et al. 2015

Journal of Biological Chemistry

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Background: Intrinsic protein disorder has been hypothesized to be advantageous for protein evolution. Results: Parallel evolution of structured and disordered dihydrofolate reductases afforded comparable increases in activity without substantially changing the dynamic properties of the starting scaffolds. Conclusion: Ordered and disordered enzymes can be similarly evolvable. Significance: Understanding how structural (dis)order influences evolutionary pathways may aid efforts to engineer existing proteins for new tasks.

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Drug target discovery via network modeling: a mathematical model of theE. colifolate network response to trimethoprim

Jalli

Lunt

et al. 2019

Preprint

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2The antibiotic trimethoprim targets the bacterial dihydrofolate reductase enzyme and 3 subsequently affects the entire folate network. We present an expanded mathematical model of 4 trimethoprim's action on the Escherichia coli folate network that greatly improves upon Kwon et 5 al. (2008). The improvement upon the Kwon Model lends greater insight into the effects of 6 trimethoprim at higher resolution and accuracy. More importantly, the presented mathematical 7 model enables drug target discovery in a way the earlier model could not. Using the improved 8 mathematical model as a scaffold, we use parameter optimization to search for new drug targets 9 that replicate the effect of trimethoprim. We present the model and model-scaffold strategy as 10 an efficient route for drug target discovery. 1112 Introduction 13 Antibiotic resistance 14 Antibiotic resistance is a major health policy concern. New and resistant forms of 15 common infections such as tuberculosis necessitate urgent drug development efforts [1][2][3].16 Strategies such as discovering new bacterial communication networks and inhibiting these 17 networks are a popular avenue for drug discovery yet are very expensive in both time and 18 resources. Utilizing math models to gain a greater level of insight into the mechanisms of known 19 drugs may offer opportunities for drug development, using well-studied and richly described 20 pathways that already show weakness to chemical intervention to search for new potential 21 targets [4]. The presented work models the mechanism of a common antibiotic, trimethoprim, at 2 22 the biological information layer at which it functions, the metabolic network level. This is done 23 not only to study the mechanism of trimethoprim but to find alternatives to it by attempting to 24 replicate its effect on the folate network, which is known to be critical to cell function. The 25 presented mathematical model improves on previous work by providing a higher resolution 26 model of Trimethoprim's effect on E. coli. Without a highly detailed model of the bacterial folate 27 network and trimethoprim's effect on it, the presented strategy of drug target discovery would 28 not be possible. 29 The folate network and trimethoprim 30 The folate network is a traditional therapeutic target for both cancerous and bacterial 31 cells due to the integral role folates play in cell division [5, 6]. The folate network provides and 32 accepts one-carbon units for the biosynthesis of amino acids and metabolites such as S-adenosyl 33 methionine (SAM), the universal methyl group donor [7-9]. The antibiotic trimethoprim (TM) 34 inhibits the activity of bacterial dihydrofolate reductase (DHFR), an enzyme that converts 35 dihydrofolate (DHF) to tetrahydrofolate (THF, Fig 1). DHFR inhibition causes a spike in DHF. DHF 36 in turn inhibits folypolyglutamate gamma synthetase (FPGS), the enzyme tasked with adding 37 glutamates to THF and its derivatives [10, 11]. Because folate-catalyzed conversions of one-38 carbon units are sensitive to glutamation lev...

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Coupling effects of distal loops on structural stability and enzymatic activity of Escherichia coli dihydrofolate reductase revealed by deletion mutants

Cited by 3 publications

References 33 publications

Histidine Hydrogen-Deuterium Exchange Mass Spectrometry for Probing the Microenvironment of Histidine Residues in Dihydrofolate Reductase

Histidine Hydrogen-Deuterium Exchange Mass Spectrometry for Probing the Microenvironment of Histidine Residues in Dihydrofolate Reductase

Comparative Laboratory Evolution of Ordered and Disordered Enzymes

Drug target discovery via network modeling: a mathematical model of theE. colifolate network response to trimethoprim

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