Browsing by Author "Chen, Yen-Fu"

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Aurintricarboxylic acid inhibits influenza virus neuraminidase
(2009-02-01)
Hung, Hui-Chen
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Tseng, Ching-Ping
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Yang, Jinn-Moon
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Ju, Yi-Wei
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Tseng, Sung-Nain
There is a continuing threat that the highly pathogenic avian influenza virus will cause future influenza pandemics. In this study, we screened a library of compounds that are biologically active and structurally diverse for inhibitory activity against influenza neuraminidase (NA). We found that aurintricarboxylic acid (ATA) is a potent inhibitor of NA activity of both group-1 and group-2 influenza viruses with IC(50)S (effective concentration to inhibit NA activity by 50%) values at low micromolar concentrations. ATA was equally potent in inhibiting the NA activity derived from wild-type NA and its H274Y mutant which renders NA resistance to inhibition by oseltamivir. Although ATA is structurally distinct from sialic acid, molecular modeling experiments suggested that ATA binds to NA at the enzyme's substrate binding site. These results indicate that ATA may be a good starting material for the design of a novel class of NA inhibitors for the treatment influenza viruses. (C) 2008 Elsevier B.V. All rights reserved.
Core Site-Moiety Maps Reveal Inhibitors and Binding Mechanisms of Orthologous Proteins by Screening Compound Libraries
(2012-02-29)
Hsu, Kai-Cheng
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Cheng, Wen-Chi
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Chen, Yen-Fu
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Wang, Hung-Jung
;
Li, Ling-Ting
Members of protein families often share conserved structural subsites for interaction with chemically similar moieties despite low sequence identity. We propose a core site-moiety map of multiple proteins (called CoreSiMMap) to discover inhibitors and mechanisms by profiling subsite-moiety interactions of immense screening compounds. The consensus anchor, the subsite-moiety interactions with statistical significance, of a CoreSiMMap can be regarded as a "hot spot" that represents the conserved binding environments involved in biological functions. Here, we derive the CoreSiMMap with six consensus anchors and identify six inhibitors (IC50 < 8.0 mu M) of shikimate kinases (SKs) of Mycobacterium tuberculosis and Helicobacter pylori from the NCI database (236,962 compounds). Studies of site-directed mutagenesis and analogues reveal that these conserved interacting residues and moieties contribute to pocket-moiety interaction spots and biological functions. These results reveal that our multi-target screening strategy and the CoreSiMMap can increase the accuracy of screening in the identification of novel inhibitors and subsite-moiety environments for elucidating the binding mechanisms of targets.
Direct visualization of triplex DNA molecular dynamics by fluorescence resonance energy transfer and atomic force microscopy measurements
(2007-11-12)
Chang, Chia-Ching
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Lin, Po-Yen
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Chen, Yen-Fu
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Chang, Chia-Seng
;
Kan, Lou-Sing
We have detected the dynamics of 17-mer DNA triplex dissociation mechanism at the molecular level. Fluorescence resonance energy transfer (FRET) was used as an indicator of intermolecular interaction in nanometer range, whereas atomic force microscopy (AFM) was employed to address single molecule with sub-angstrom precision. The maximum rupture force of DNA triplex was found at pH 4.65, consistent with macroscopic observations. These results indicated that the FRET together with an AFM detection system could be used to reveal the DNA triplex interaction in nanometer scale unambiguously. (c) 2007 American Institute of Physics.
GemAffinity: a scoring function for predicting binding affinity and Virtual Screening
(2012)
Hsu, Kai-Cheng
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Chen, Yen-Fu
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Yang, Jinn-Moon
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生物科技學系
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生物資訊及系統生物研究所
Prediction of protein-ligand binding affinities plays an essential role for molecular recognition and virtual screening. We have developed a scoring function, namely GemAffinity, to predict binding affinities by using a stepwise regression method and 88 descriptors from 891 complex structures. GemAffinity consists of five descriptors, including van der Waals contacts; metal-ligand interactions; water effects; ligand deformation penalty; and conserved hydrogen-bonded residues. Experimental results indicate that GemAffinity is the best among 13 methods on a test set and can enrich screening accuracies on four sets. We believe that GemAffinity is useful for virtual screening and drug discovery.
GemAffinity: A Scoring Function for Predicting Binding Affinity and Virtual Screening
(2009)
Hsu, Kai-Cheng
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Chen, Yen-Fu
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Yang, Jinn-Moon
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生物資訊及系統生物研究所
;
Institude of Bioinformatics and Systems Biology
Prediction of protein-ligand binding affinities is an important issue in molecular recognition and virtual screening. We have developed a scoring function, namely GemAffinity, to predict binding affinities by analyzing 88 descriptors derived from 891 protein-ligand structures selected from the Protein Data Bank (PDB). Based on these 88 descriptors, we derived GemAffinity using a stepwise regression method to identify five descriptors, including van der Waals contact; metal-ligand interactions; water effects; ligand deformation penalties; and highly conserved residues interacting to a bound ligand with hydrogen bonds. GemAffinity was evaluated on an independent set, and the correlation between predicted and experimental values is 0.572. GemAffinity is the best among 13 methods on this set. Our GemAffinity was then applied to virtual screening for thymidine kinase (TIC), human carbonic anhydrase II (HCAII), estrogen receptor of antagonists (ER) and agonists (ERA). Experimental results indicate that GemAffinity is able to reduce the disadvantages (i.e. preferring highly polar or high molecular weight compounds) of energy-based scoring functions. In addition, GemAffinity easily combined with other scoring functions to enrich screening accuracies. We believe that GemAffinity is useful to predict binding affinity and virtual screening.
iGEMDOCK: a graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis
(2011-02-15)
Hsu, Kai-Cheng
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Chen, Yen-Fu
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Lin, Shen-Rong
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Yang, Jinn-Moon
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生物科技學系
Background: Pharmacological interactions are useful for understanding ligand binding mechanisms of a therapeutic target. These interactions are often inferred from a set of active compounds that were acquired experimentally. Moreover, most docking programs loosely coupled the stages (binding-site and ligand preparations, virtual screening, and post-screening analysis) of structure-based virtual screening (VS). An integrated VS environment, which provides the friendly interface to seamlessly combine these VS stages and to identify the pharmacological interactions directly from screening compounds, is valuable for drug discovery. Results: We developed an easy-to-use graphic environment, iGEMDOCK, integrating VS stages (from preparations to post-screening analysis). For post-screening analysis, iGEMDOCK provides biological insights by deriving the pharmacological interactions from screening compounds without relying on the experimental data of active compounds. The pharmacological interactions represent conserved interacting residues, which often form binding pockets with specific physico-chemical properties, to play the essential functions of a target protein. Our experimental results show that the pharmacological interactions derived by iGEMDOCK are often hot spots involving in the biological functions. In addition, iGEMDOCK provides the visualizations of the protein-compound interaction profiles and the hierarchical clustering dendrogram of the compounds for post-screening analysis. Conclusions: We have developed iGEMDOCK to facilitate steps from preparations of target proteins and ligand libraries toward post-screening analysis. iGEMDOCK is especially useful for post-screening analysis and inferring pharmacological interactions from screening compounds. We believe that iGEMDOCK is useful for understanding the ligand binding mechanisms and discovering lead compounds. iGEMDOCK is available at http://gemdock.life.nctu.edu.tw/dock/igemdock.php.
MicroRNA-224 down-regulates Glycine N-methyltransferase gene expression in Hepatocellular Carcinoma
(2018-08-16)
Hung, Jung-Hsien
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Li, Chung-Hsien
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Yeh, Ching-Hua
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Huang, Pin-Cheng
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Fang, Cheng-Chieh
Glycine N-methyltransferase (GNMT) is a tumor suppressor for HCC. It is down-regulated in HCC, but the mechanism is not fully understood. MicroRNA-224 (miR-224) acts as an onco-miR in HCC. This study is the first to investigate miR-224 targeting the coding region of GNMT transcript. The GNMT-MT plasmid containing a miR-224 binding site silent mutation of the GNMT coding sequence can escape the suppression of miR-224 in HEK293T cells. Expression of both exogenous and endogenous GNMT was suppressed by miR-224, while miR-224 inhibitor enhanced GNMT expression. miR-224 counteracts the effects of GNMT on the reduction of cell proliferation and tumor growth. The levels of miR-224 and GNMT mRNA showed a significant inverse relationship in tumor specimens from HCC patients. Utilizing CCl4-treated hepatoma cells and mice as a cell damage of inflammatory or liver injury model, we observed that the decreased expression levels of GNMT were accompanied with the elevated expression levels of miR-224 in hepatoma cells and mouse liver. Finally, hepatic AAV-mediated GNMT also reduced CCl4-induced miR-224 expression and liver fibrosis. These results indicated that AAV-mediated GNMT has potential liver protection activity. miR-224 can target the GNMT mRNA coding sequence and plays an important role in GNMT suppression during liver tumorigenesis.
Pathway-based Screening Strategy for Multitarget Inhibitors of Diverse Proteins in Metabolic Pathways
(2013-07-01)
Hsu, Kai-Cheng
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Cheng, Wen-Chi
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Chen, Yen-Fu
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Wang, Wen-Ching
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Yang, Jinn-Moon
Many virtual screening methods have been developed for identifying single-target inhibitors based on the strategy of "one-disease, one-target, one-drug". The hit rates of these methods are often low because they cannot capture the features that play key roles in the biological functions of the target protein. Furthermore, single-target inhibitors are often susceptible to drug resistance and are ineffective for complex diseases such as cancers. Therefore, a new strategy is required for enriching the hit rate and identifying multitarget inhibitors. To address these issues, we propose the pathway-based screening strategy (called PathSiMMap) to derive binding mechanisms for increasing the hit rate and discovering multitarget inhibitors using site-moiety maps. This strategy simultaneously screens multiple target proteins in the same pathway; these proteins bind intermediates with common substructures. These proteins possess similar conserved binding environments (pathway anchors) when the product of one protein is the substrate of the next protein in the pathway despite their low sequence identity and structure similarity. We successfully discovered two multitarget inhibitors with IC50 of <10 mu M for shikimate dehydrogenase and shikimate kinase in the shikimate pathway of Helicobacter pylori. Furthermore, we found two selective inhibitors (IC50 of <10 mu M) for shikimate dehydrogenase using the specific anchors derived by our method. Our experimental results reveal that this strategy can enhance the hit rates and the pathway anchors are highly conserved and important for biological functions. We believe that our strategy provides a great value for elucidating protein binding mechanisms and discovering multitarget inhibitors.
SiMMap: a web server for inferring site-moiety map to recognize interaction preferences between protein pockets and compound moieties
(2010-07-01)
Chen, Yen-Fu
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Hsu, Kai-Cheng
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Lin, Shen-Rong
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Wang, Wen-Ching
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Huang, Yu-Chi
The protein-ligand interacting mechanism is essential to biological processes and drug discovery. The SiMMap server statistically derives site-moiety map with several anchors, which describe the relationship between the moiety preferences and physicochemical properties of the binding site, from the interaction profiles between query target protein and its docked (or co-crystallized) compounds. Each anchor includes three basic elements: a binding pocket with conserved interacting residues, the moiety composition of query compounds and pocket-moiety interaction type (electrostatic, hydrogen bonding or van der Waals). We provide initial validation of the site-moiety map on three targets, thymidine kinase, and estrogen receptors of antagonists and agonists. Experimental results show that an anchor is often a hot spot and the site-moiety map can help to assemble potential leads by optimal steric, hydrogen bonding and electronic moieties. When a compound highly agrees with anchors of site-moiety map, this compound often activates or inhibits the target protein. We believe that the site-moiety map is useful for drug discovery and understanding biological mechanisms. The SiMMap web server is available at http://simfam.life.nctu.edu.tw/.
Structures of Helicobacter pylori Shikimate Kinase Reveal a Selective Inhibitor-Induced-Fit Mechanism
(2012-03-16)
Cheng, Wen-Chi
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Chen, Yen-Fu
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Wang, Hung-Jung
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Hsu, Kai-Cheng
;
Lin, Shuang-Chih
Shikimate kinase (SK), which catalyzes the specific phosphorylation of the 3-hydroxyl group of shikimic acid in the presence of ATP, is the enzyme in the fifth step of the shikimate pathway for biosynthesis of aromatic amino acids. This pathway is present in bacteria, fungi, and plants but absent in mammals and therefore represents an attractive target pathway for the development of new antimicrobial agents, herbicides, and antiparasitic agents. Here we investigated the detailed structure-activity relationship of SK from Helicobacter pylori (HpSK). Site-directed mutagenesis and isothermal titration calorimetry studies revealed critical conserved residues (D33, F48, R57, R116, and R132) that interact with shikimate and are therefore involved in catalysis. Crystal structures of HpSK center dot SO4, R57A, and HpSK center dot shikimate-3-phosphate center dot ADP show a characteristic three-layer architecture and a conformationally elastic region consisting of F48, R57, R116, and R132, occupied by shikimate. The structure of the inhibitor complex, E114A.162535, was also determined, which revealed a dramatic shift in the elastic LID region and resulted in conformational locking into a distinctive form. These results reveal considerable insight into the active-site chemistry of SKs and a selective inhibitor-induced-fit mechanism.
Symmetry of the Optical Phonons in LuVO4: A Raman Study
(2020-05-01)
Rafailov, Peter
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Dimitrov, Dimitre
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Chen, Yen-Fu
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Lee, Chi-Shen
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Juang, Jenh-Yih
A thorough analysis of the first-order vibrational spectrum of LuVO4 is presented by using polarized micro-Raman spectroscopy with special focus on the phonon modes with the weakest intensity and occasional controversial assignment. Group-theory analysis is carried out to demonstrate the determination of numbers and symmetries of the Raman active modes. Crystal- and correlation-field splitting effects in the vibrational spectrum of LuVO4 are discussed. Under conditions adjusted to minimize the birefringence effects we recorded, in each main scattering configuration, a series of Raman spectra in different sample orientations achieved by rotating the sample around the incident laser beam. The dependence of the Raman intensity on the rotational angle allowed us to identify the correct symmetry of the phonons with exceptionally weak scattering cross-section. A complete assignment of all twelve first-order Raman active phonons of LuVO4 is thus obtained.
TSCC: Two-Stage Combinatorial Clustering for virtual screening using protein-ligand interactions and physicochemical features
(2010-12-02)
Clinciu, Daniel L.
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Chen, Yen-Fu
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Ko, Cheng-Neng
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Lo, Chi-Chun
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Yang, Jinn-Moon
Background: The increasing numbers of 3D compounds and protein complexes stored in databases contribute greatly to current advances in biotechnology, being employed in several pharmaceutical and industrial applications. However, screening and retrieving appropriate candidates as well as handling false positives presents a challenge for all post-screening analysis methods employed in retrieving therapeutic and industrial targets. Results: Using the TSCC method, virtually screened compounds were clustered based on their protein-ligand interactions, followed by structure clustering employing physicochemical features, to retrieve the final compounds. Based on the protein-ligand interaction profile (first stage), docked compounds can be clustered into groups with distinct binding interactions. Structure clustering (second stage) grouped similar compounds obtained from the first stage into clusters of similar structures; the lowest energy compound from each cluster being selected as a final candidate. Conclusion: By representing interactions at the atomic-level and including measures of interaction strength, better descriptions of protein-ligand interactions and a more specific analysis of virtual screening was achieved. The two-stage clustering approach enhanced our post-screening analysis resulting in accurate performances in clustering, mining and visualizing compound candidates, thus, improving virtual screening enrichment.