Browsing by Author "Chiang, Ting-Wei"

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Crystal Structure and Mutational Analysis of Aminoacylhistidine Dipeptidase from Vibrio alginolyticus Reveal a New Architecture of M20 Metallopeptidases
(2010-12-01)
Chang, Chin-Yuan
;
Hsieh, Yin-Cheng
;
Wang, Ting-Yi
;
Chen, Yi-Chin
;
Wang, Yu-Kuo
Aminoacylhistidine dipeptidases (PepD, EC 3.4.13.3) belong to the family of M20 metallopeptidases from the metallopeptidase H clan that catalyze a broad range of dipeptide and tripeptide substrates, including L-carnosine and L-homocarnosine. Homocarnosine has been suggested as a precursor for the neurotransmitter gamma-aminobutyric acid (GABA) and may mediate the antiseizure effects of GABAergic therapies. Here, we report the crystal structure of PepD from Vibrio alginolyticus and the results of mutational analysis of substrate-binding residues in the C-terminal as well as substrate specificity of the PepD catalytic domain-alone truncated protein PepD(CAT). The structure of PepD was found to exist as a homodimer, in which each monomer comprises a catalytic domain containing two zinc ions at the active site center for its hydrolytic function and a lid domain utilizing hydrogen bonds between helices to form the dimer interface. Although the PepD is structurally similar to PepV, which exists as a monomer, putative substrate-binding residues reside in different topological regions of the polypeptide chain. In addition, the lid domain of the PepD contains an "extra" domain not observed in related M20 family metallopeptidases with a dimeric structure. Mutational assays confirmed both the putative di-zinc allocations and the architecture of substrate recognition. In addition, the catalytic domain-alone truncated PepD(CAT) exhibited substrate specificity to L-homocarnosine compared with that of the wild-type PepD, indicating a potential value in applications of PepD(CAT) for GABAergic therapies or neuroprotection.
Crystal Structure and Mutational Analysis of Aminoacylhistidine Dipeptidase from Vibrio alginolyticus Reveal a New Architecture of M20 Metallopeptidases
(2010-12-01)
Chang, Chin-Yuan
;
Hsieh, Yin-Cheng
;
Wang, Ting-Yi
;
Chen, Yi-Chin
;
Wang, Yu-Kuo
Aminoacylhistidine dipeptidases (PepD, EC 3.4.13.3) belong to the family of M20 metallopeptidases from the metallopeptidase H clan that catalyze a broad range of dipeptide and tripeptide substrates, including L-carnosine and L-homocarnosine. Homocarnosine has been suggested as a precursor for the neurotransmitter gamma-aminobutyric acid (GABA) and may mediate the antiseizure effects of GABAergic therapies. Here, we report the crystal structure of PepD from Vibrio alginolyticus and the results of mutational analysis of substrate-binding residues in the C-terminal as well as substrate specificity of the PepD catalytic domain-alone truncated protein PepD(CAT). The structure of PepD was found to exist as a homodimer, in which each monomer comprises a catalytic domain containing two zinc ions at the active site center for its hydrolytic function and a lid domain utilizing hydrogen bonds between helices to form the dimer interface. Although the PepD is structurally similar to PepV, which exists as a monomer, putative substrate-binding residues reside in different topological regions of the polypeptide chain. In addition, the lid domain of the PepD contains an "extra" domain not observed in related M20 family metallopeptidases with a dimeric structure. Mutational assays confirmed both the putative di-zinc allocations and the architecture of substrate recognition. In addition, the catalytic domain-alone truncated PepD(CAT) exhibited substrate specificity to L-homocarnosine compared with that of the wild-type PepD, indicating a potential value in applications of PepD(CAT) for GABAergic therapies or neuroprotection.
Graph-Based Optimal Reactant Minimization for Sample Preparation on Digital Microfluidic Biochips
(2013-01-01)
Chiang, Ting-Wei
;
Liu, Chia-Hung
;
Huang, Juinn-Dar
;
電機資訊學士班
;
Undergraduate Honors Program of Electrical Engineering and Computer Science
Sample preparation is an essential step in biochemical reactions. Reactants must be diluted to achieve given target concentrations in sample preparation. Since some reactants like costly reagents and infant's blood are valuable, their usage should be minimized during dilution. In this paper, we propose an optimal reactant minimization algorithm, GORMA, for sample preparation on digital microfluidic biochips. GORMA adopts a systematic method to exhaustively check all possible dilution solutions and then identifies the one with minimal reactant usage and waste through maximal droplet sharing. Experimental results show that GORMA outperforms all the existing methods in reactant usage. Meanwhile, the waste amount is reduced up to 30% as compared with existing waste minimization methods. Moreover, GORMA requires only 0.6% more operations on average when compared with an operation-minimal dilution method.
Graph-Based Optimal Reactant Minimization for Sample Preparation on Digital Microfluidic Biochips
(2013-01-01)
Chiang, Ting-Wei
;
Liu, Chia-Hung
;
Huang, Juinn-Dar
;
電機資訊學士班
;
電子工程學系及電子研究所
Sample preparation is an essential step in biochemical reactions. Reactants must be diluted to achieve given target concentrations in sample preparation. Since some reactants like costly reagents and infant's blood are valuable, their usage should be minimized during dilution. In this paper, we propose an optimal reactant minimization algorithm, GORMA, for sample preparation on digital microfluidic biochips. GORMA adopts a systematic method to exhaustively check all possible dilution solutions and then identifies the one with minimal reactant usage and waste through maximal droplet sharing. Experimental results show that GORMA outperforms all the existing methods in reactant usage. Meanwhile, the waste amount is reduced up to 30% as compared with existing waste minimization methods. Moreover, GORMA requires only 0.6% more operations on average when compared with an operation-minimal dilution method.
Reactant Minimization during Sample Preparation on Digital Microfluidic Biochips using Skewed Mixing Trees
(2012)
Huang, Juinn-Dar
;
Liu, Chia-Hung
;
Chiang, Ting-Wei
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
Sample preparation is an indispensable process to biochemical reactions. Original reactants are usually diluted to the solutions with desirable concentrations. Since the reactants, like infant's blood, DNA evidence collected from a crime scene, or costly reagents, are extremely valuable, the usage of reactant must be minimized in the sample preparation process. In this paper, we propose the first reactant minimization approach, REMIA, during sample preparation on digital microfluidic biochips (DMFBs). Given a target concentration, REMIA constructs a skewed mixing tree to guide the sample preparation process for reactant minimization. Experimental results demonstrate that REMIA can save about 31%similar to 52% of reactant usage on average compared with three existing sample preparation methods. Besides, REMIA can be extended to tackle the sample preparation problem with multiple target concentrations, and the extended version also successfully decreases the reactant usage further.
Reactant Minimization in Sample Preparation on Digital Microfluidic Biochips
(2015-09-01)
Liu, Chia-Hung
;
Chiang, Ting-Wei
;
Huang, Juinn-Dar
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
Sample preparation plays an essential role in most biochemical reactions. Raw reactants are diluted to solutions with desirable concentration values in this process. Since the reactants, like infant\'s blood, DNA evidence collected from crime scenes, or costly reagents, are extremely valuable, their usage should be minimized whenever possible. In this paper, we propose a two-phased reactant minimization algorithm (REMIA), for sample preparation on digital microfluidic biochips. In the former phase, REMIA builds a reactant-minimized interpolated dilution tree with specific leaf nodes for a target concentration. Two approaches are developed for tree construction; one is based on integer linear programming (ILP) and the other is heuristic. The ILP one guarantees to produce an optimal dilution tree with minimal reactant consumption, whereas the heuristic one ensures runtime efficiency. Then, REMIA constructs a forest consisting of exponential dilution trees to produce those aforementioned specific leaf nodes with minimal reactant consumption in the latter phase. Experimental results show that REMIA achieves a reduction of reactant usage by 32%-52% as compared with three existing state-of-the-art sample preparation approaches. Besides, REMIA can be easily extended to solve the sample preparation problem with multiple target concentrations, and the extended version also effectively lowers the reactant consumption further.
Single femtosecond laser pulse-single crystal formation of glycine at the solution surface
(2013-03-01)
Liu, Tsung-Han
;
Uwada, Takayuki
;
Sugiyama, Teruki
;
Usman, Anwar
;
Hosokawa, Yoichiroh
We demonstrate femtosecond laser-induced crystallization of glycine from its supersaturated solution depending on laser tunable parameters (pulse energy and repetition rate) and focal position, and examine the crystallization probability, crystal morphology, and crystal polymorph. The generation of cavitation bubble through multiphoton absorption of water depends on input laser pulse energy and repetition rate, which strongly determine morphology and number of the obtained crystals. Significant increase in the crystallization probability is observed by irradiating the femtosecond laser pulses to the air/solution interface, and single pulse-induced single crystal formation is successfully achieved. The crystallization mechanism is discussed in view of inhomogeneous mechanical stress induced by cavitation bubble generation and molecular assembly characteristics of the surface. (C) 2012 Elsevier B.V. All rights reserved.