Identification of novel catalytic features of endo-β-1,4-glucanase produced by mulberry longicorn beetle Apriona germari

Mulberry longicorn beetle, Apriona germari, has been reported to produce two endo-β-l,4-glucanases or AgEGases (accession Nos. Q6SS52 and Q5XQD1). AgEGase sequence contains catalytic motif (amino acid residues 37～48), which is the characteristic of family Glycohydrolase 45 and is identified as the substrate binding site. The application of bioinformatics approaches includes sequence analysis, structural modeling and inhibitor docking to relate the structure and function of AgEGases.We have dissected the sequence and structure of AgEGase catalytic motif and compared it with crystal structure of Humicola insolens endoglucanases Ⅴ. The results show an involvement of sulfur containing amino acid residues in the active site of the enzyme. Cys residues and position of disulfide bonds are highly conserved between the two structures of endoglucanases of A.germari. Surface calculation of AgEGase structure in the absence of Cys residues reveals greater accessibility of the catalytic site to the substrate involving Asp42, a highly conserved residue. For the inhibition study, tannin-based structure was docked into the catalytic site of AgEGase using ArgusLab 4.0 and it resulted in a stable complex formation. It is suggested that the inhibition could occur through formation of a stable transition state analog-enzyme complex with the tannin-based inhibitor, as observed with other insect cellulases in our laboratory.     

Textual keyword extraction and summarization: State-of-the-art

With the advent of Web 2.0, there exist many online platforms that results in massive textual data production such as social networks, online blogs, magazines etc. This textual data carries information that can be used for betterment of humanity. Hence, there is a dire need to extract potential information out of it. This study aims to present an overview of approaches that can be applied to extract and later present these valuable information nuggets residing within text in brief, clear and concise way. In this regard, two major tasks of automatic keyword extraction and text summarization are being reviewed. To compile the literature, scientific articles were collected using major digital computing research repositories. In the light of acquired literature, survey study covers early approaches up to all the way till recent advancements using machine learning solutions. Survey findings conclude that annotated benchmark datasets for various textual data-generators such as twitter and social forms are not available. This scarcity of dataset has resulted into relatively less progress in many domains. Also, applications of deep learning techniques for the task of automatic keyword extraction are relatively unaddressed. Hence, impact of various deep architectures stands as an open research direction. For text summarization task, deep learning techniques are applied after advent of word vectors, and are currently governing state-of-the-art for abstractive summarization. Currently, one of the major challenges in these tasks is semantic aware evaluation of generated results.     

Identification of novel catalytic features of endo-β-1,4-glucanase produced by mulberry longicorn beetle Apriona germari

Mulberry longicorn beetle, Apriona germari, has been reported to produce two endo-β-1,4-glucanases or AgEGases (accession Nos. Q6SS52 and Q5XQD1). AgEGase sequence contains catalytic motif (amino acid residues 37~48), which is the characteristic of family Glycohydrolase 45 and is identified as the substrate binding site. The application of bioinformatics ap-proaches includes sequence analysis, structural modeling and inhibitor docking to relate the structure and function of AgEGases. We have dissected the sequence and structure of AgEGase catalytic motif and compared it with crystal structure of Humicola insolens endoglucanases V. The results show an involvement of sulfur containing amino acid residues in the active site of the enzyme. Cys residues and position of disulfide bonds are highly conserved between the two structures of endoglucanases of A. germari. Surface calculation of AgEGase structure in the absence of Cys residues reveals greater accessibility of the catalytic site to the substrate involving Asp42, a highly conserved residue. For the inhibition study, tannin-based structure was docked into the catalytic site of AgEGase using ArgusLab 4.0 and it resulted in a stable complex formation. It is suggested that the inhibition could occur through formation of a stable transition state analog-enzyme complex with the tannin-based inhibitor, as observed with other insect cellulases in our laboratory.     

3D printed microfluidic devices with integrated valves

We report the successful fabrication and testing of 3D printed microfluidic devices with integrated membrane-based valves. Fabrication is performed with a low-cost commercially available stereolithographic 3D printer. Horizontal microfluidic channels with designed rectangular cross sectional dimensions as small as 350 μm wide and 250 μm tall are printed with 100% yield, as are cylindrical vertical microfluidic channels with 350 μm designed (210 μm actual) diameters. Based on our previous work [Rogers et al., Anal. Chem. 83, 6418 (2011)], we use a custom resin formulation tailored for low non-specific protein adsorption. Valves are fabricated with a membrane consisting of a single build layer. The fluid pressure required to open a closed valve is the same as the control pressure holding the valve closed. 3D printed valves are successfully demonstrated for up to 800 actuations.