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Article ; Online: Patient-specific analysis of co-expression to measure biological network rewiring in individuals.

Wei, Lanying / Xin, Yucui / Pu, Mengchen / Zhang, Yingsheng

Life science alliance

2023 Volume 7, Issue 2

Abstract: To effectively understand the underlying mechanisms of disease and inform the development of personalized therapies, it is critical to harness the power of differential co-expression (DCE) network analysis. Despite the promise of DCE network analysis in ... ...

Abstract	To effectively understand the underlying mechanisms of disease and inform the development of personalized therapies, it is critical to harness the power of differential co-expression (DCE) network analysis. Despite the promise of DCE network analysis in precision medicine, current approaches have a major limitation: they measure an average differential network across multiple samples, which means the specific etiology of individual patients is often overlooked. To address this, we present Cosinet, a DCE-based single-sample network rewiring degree quantification tool. By analyzing two breast cancer datasets, we demonstrate that Cosinet can identify important differences in gene co-expression patterns between individual patients and generate scores for each individual that are significantly associated with overall survival, recurrence-free interval, and other clinical outcomes, even after adjusting for risk factors such as age, tumor size, HER2 status, and PAM50 subtypes. Cosinet represents a remarkable development toward unlocking the potential of DCE analysis in the context of precision medicine.
MeSH term(s)	Humans ; Female ; Breast Neoplasms/genetics ; Breast Neoplasms/pathology ; Risk Factors
Language	English
Publishing date	2023-11-17
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2575-1077
ISSN (online)	2575-1077
DOI	10.26508/lsa.202302253
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Modified Electrostatic Complementary Score Function and Its Application Boundary Exploration in Drug Design.

Zhao, Liming / Pu, Mengchen / Wang, Huting / Ma, Xiangyu / Zhang, Yingsheng J

Journal of chemical information and modeling

2022 Volume 62, Issue 18, Page(s) 4420–4426

Abstract: In recent years, machine learning (ML) models have been found to quickly predict various molecular properties with accuracy comparable to high-level quantum chemistry methods. One such example is the calculation of electrostatic potential (ESP). ... ...

Abstract	In recent years, machine learning (ML) models have been found to quickly predict various molecular properties with accuracy comparable to high-level quantum chemistry methods. One such example is the calculation of electrostatic potential (ESP). Different ESP prediction ML models were proposed to generate surface molecular charge distribution. Electrostatic complementarity (EC) can apply ESP data to quantify the complementarity between a ligand and its binding pocket, leading to the potential to increase the efficiency of drug design. However, there is not much research discussing EC score functions and their applicability domain. We propose a new EC score function modified from the one originally developed by Bauer and Mackey, and confirm its effectiveness against the available Pearson's
MeSH term(s)	Drug Design ; Ligands ; Machine Learning ; Static Electricity
Chemical Substances	Ligands
Language	English
Publishing date	2022-09-07
Publishing country	United States
Document type	Journal Article
ZDB-ID	190019-5
ISSN	1549-960X ; 0095-2338
ISSN (online)	1549-960X
ISSN	0095-2338
DOI	10.1021/acs.jcim.2c00616
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Article ; Online: Deep learning model accurately classifies metastatic tumors from primary tumors based on mutational signatures.

Zheng, Weisheng / Pu, Mengchen / Li, Xiaorong / Du, Zhaolan / Jin, Sutong / Li, Xingshuai / Zhou, Jielong / Zhang, Yingsheng

Scientific reports

2023 Volume 13, Issue 1, Page(s) 8752

Abstract: Metastatic propagation is the leading cause of death for most cancers. Prediction and elucidation of metastatic process is crucial for the treatment of cancer. Even though somatic mutations have been linked to tumorigenesis and metastasis, it is less ... ...

Abstract	Metastatic propagation is the leading cause of death for most cancers. Prediction and elucidation of metastatic process is crucial for the treatment of cancer. Even though somatic mutations have been linked to tumorigenesis and metastasis, it is less explored whether metastatic events can be identified through genomic mutational signatures, which are concise descriptions of the mutational processes. Here, we developed MetaWise, a Deep Neural Network (DNN) model, by applying mutational signatures as input features calculated from Whole-Exome Sequencing (WES) data of TCGA and other metastatic cohorts. This model can accurately classify metastatic tumors from primary tumors and outperform traditional machine learning (ML) models and a deep learning (DL) model, DiaDeL. Signatures of non-coding mutations also have a major impact on the model's performance. SHapley Additive exPlanations (SHAP) and Local Surrogate (LIME) analyses identify several mutational signatures which are directly correlated to metastatic spread in cancers, including APOBEC-mutagenesis, UV-induced signatures, and DNA damage response deficiency signatures.
MeSH term(s)	Humans ; Deep Learning ; Mutation ; Neoplasms/genetics ; Mutagenesis ; Carcinogenesis/genetics
Language	English
Publishing date	2023-05-30
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-35842-w
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Article ; Online: Identifying New Ligands for JNK3 by Fluorescence Thermal Shift Assays and Native Mass Spectrometry.

Cheng, Chongyun / Liu, Miaomiao / Gao, Xiaoqin / Wu, Dong / Pu, Mengchen / Ma, Jun / Quinn, Ronald J / Xiao, Zhicheng / Liu, Zhijie

ACS omega

2022 Volume 7, Issue 16, Page(s) 13925–13931

Abstract: The c-Jun N-terminal kinases (JNKs) are evolutionary highly conserved serine/threonine kinases. Numerous findings suggest that JNK3 is involved in the pathogenesis of neurodegenerative diseases, so the inhibition of JNK3 may be a potential therapeutic ... ...

Abstract	The c-Jun N-terminal kinases (JNKs) are evolutionary highly conserved serine/threonine kinases. Numerous findings suggest that JNK3 is involved in the pathogenesis of neurodegenerative diseases, so the inhibition of JNK3 may be a potential therapeutic intervention. The identification of novel compounds with promising pharmacological properties still represents a challenge. Fluorescence thermal shift screening of a chemically diversified lead-like scaffold library of 2024 pure compounds led to the initial identification of seven JNK3 binding hits, which were classified into four scaffold groups according to their chemical structures. Native mass spectrometry validated the interaction of 4 out of the 7 hits with JNK3. Binding geometries and interactions of the top 2 hits were evaluated by docking into a JNK3 crystal structure. Hit
Language	English
Publishing date	2022-04-14
Publishing country	United States
Document type	Journal Article
ISSN	2470-1343
ISSN (online)	2470-1343
DOI	10.1021/acsomega.2c00340
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Article: Using graph-based model to identify cell specific synthetic lethal effects.

Pu, Mengchen / Cheng, Kaiyang / Li, Xiaorong / Xin, Yucui / Wei, Lanying / Jin, Sutong / Zheng, Weisheng / Peng, Gongxin / Tang, Qihong / Zhou, Jielong / Zhang, Yingsheng

Computational and structural biotechnology journal

2023 Volume 21, Page(s) 5099–5110

Abstract: Synthetic lethal (SL) pairs are pairs of genes whose simultaneous loss-of-function results in cell death, while a damaging mutation of either gene alone does not affect the cell's survival. This makes SL pairs attractive targets for precision cancer ... ...

Abstract	Synthetic lethal (SL) pairs are pairs of genes whose simultaneous loss-of-function results in cell death, while a damaging mutation of either gene alone does not affect the cell's survival. This makes SL pairs attractive targets for precision cancer therapies, as targeting the unimpaired gene of the SL pair can selectively kill cancer cells that already harbor the impaired gene. Limited by the difficulty of finding true SL pairs, especially on specific cell types, current computational approaches provide only limited insights because of overlooking the crucial aspects of cellular context dependency and mechanistic understanding of SL pairs. As a result, the identification of SL targets still relies on expensive, time-consuming experimental approaches. In this work, we applied cell-line specific multi-omics data to a specially designed deep learning model to predict cell-line specific SL pairs. Through incorporating multiple types of cell-specific omics data with a self-attention module, we represent gene relationships as graphs. Our approach achieves the prediction of SL pairs in a cell-specific manner and demonstrates the potential to facilitate the discovery of cell-specific SL targets for cancer therapeutics, providing a tool to unearth mechanisms underlying the origin of SL in cancer biology. The code and data of our approach can be found at https://github.com/promethiume/SLwise.
Language	English
Publishing date	2023-10-09
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2694435-2
ISSN	2001-0370
ISSN	2001-0370
DOI	10.1016/j.csbj.2023.10.011
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Article ; Online: Protein crystal quality oriented disulfide bond engineering.

Pu, Mengchen / Xu, Zhijie / Peng, Yao / Hou, Yaguang / Liu, Dongsheng / Wang, Yang / Liu, Haiguang / Song, Gaojie / Liu, Zhi-Jie

Protein & cell

2017 Volume 9, Issue 7, Page(s) 659–663

MeSH term(s)	Algorithms ; Crystallography, X-Ray ; Disulfides/chemistry ; Models, Molecular ; Protein Conformation ; Proteins/chemistry
Chemical Substances	Disulfides ; Proteins
Language	English
Publishing date	2017-10-17
Publishing country	Germany
Document type	Letter ; Research Support, Non-U.S. Gov't
ZDB-ID	2543451-2
ISSN	1674-8018 ; 1674-800X
ISSN (online)	1674-8018
ISSN	1674-800X
DOI	10.1007/s13238-017-0482-7
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Article ; Online: All Ca(2+)-binding loops of light-sensitive ctenophore photoprotein berovin bind magnesium ions: The spatial structure of Mg(2+)-loaded apo-berovin.

Burakova, Ludmila P / Natashin, Pavel V / Malikova, Natalia P / Niu, Fengfeng / Pu, Mengchen / Vysotski, Eugene S / Liu, Zhi-Jie

Journal of photochemistry and photobiology. B, Biology

2016 Volume 154, Page(s) 57–66

Abstract: Light-sensitive photoprotein berovin accounts for a bright bioluminescence of ctenophore Beroe abyssicola. Berovin is functionally identical to the well-studied Ca(2+)-regulated photoproteins of jellyfish, however in contrast to those it is extremely ... ...

Abstract	Light-sensitive photoprotein berovin accounts for a bright bioluminescence of ctenophore Beroe abyssicola. Berovin is functionally identical to the well-studied Ca(2+)-regulated photoproteins of jellyfish, however in contrast to those it is extremely sensitive to the visible light. Berovin contains three EF-hand Ca(2+)-binding sites and consequently belongs to a large family of the EF-hand Ca(2+)-binding proteins. Here we report the spatial structure of apo-berovin with bound Mg(2+) determined at 1.75Å. The magnesium ion is found in each functional EF-hand loop of a photoprotein and coordinated by oxygen atoms donated by the side-chain groups of aspartate, carbonyl groups of the peptide backbone, or hydroxyl group of serine with characteristic oxygen-Mg(2+) distances. As oxygen supplied by the side-chain of the twelfth residue of all Ca(2+)-binding loops participates in the magnesium ion coordination, it was suggested that Ca(2+)-binding loops of berovin belong to the mixed Ca(2+)/Mg(2+) rather than Ca(2+)-specific type. In addition, we report an effect of physiological concentration of Mg(2+) on bioluminescence of berovin (sensitivity to Ca(2+), rapid-mixed kinetics, light-sensitivity, thermostability, and apo-berovin conversion into active protein). The different impact of physiological concentration of Mg(2+) on berovin bioluminescence as compared to hydromedusan photoproteins was attributed to different affinities of the Ca(2+)-binding sites of these photoproteins to Mg(2+).
MeSH term(s)	Aequorin/chemistry ; Aequorin/metabolism ; Amino Acid Sequence ; Animals ; Binding Sites ; Calcium/chemistry ; Calcium/metabolism ; Crystallography, X-Ray ; Ctenophora ; Ions/chemistry ; Kinetics ; Light ; Luminescent Measurements ; Luminescent Proteins/chemistry ; Luminescent Proteins/metabolism ; Magnesium/chemistry ; Magnesium/metabolism ; Molecular Dynamics Simulation ; Protein Precursors/chemistry ; Protein Precursors/metabolism ; Protein Structure, Tertiary
Chemical Substances	Ions ; Luminescent Proteins ; Protein Precursors ; Aequorin (50934-79-7) ; Magnesium (I38ZP9992A) ; Calcium (SY7Q814VUP)
Language	English
Publishing date	2016-01
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	623022-2
ISSN	1873-2682 ; 1011-1344
ISSN (online)	1873-2682
ISSN	1011-1344
DOI	10.1016/j.jphotobiol.2015.11.012
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Zs.A 2347: Show issues

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Article ; Online: Structural basis for DNA recognition by STAT6.

Li, Jing / Rodriguez, Jose Pindado / Niu, Fengfeng / Pu, Mengchen / Wang, Jinan / Hung, Li-Wei / Shao, Qiang / Zhu, Yanping / Ding, Wei / Liu, Yanqing / Da, Yurong / Yao, Zhi / Yang, Jie / Zhao, Yongfang / Wei, Gong-Hong / Cheng, Genhong / Liu, Zhi-Jie / Ouyang, Songying

Proceedings of the National Academy of Sciences of the United States of America

2016 Volume 113, Issue 46, Page(s) 13015–13020

Abstract: STAT6 participates in classical IL-4/IL-13 signaling and stimulator of interferon genes-mediated antiviral innate immune responses. Aberrations in STAT6-mediated signaling are linked to development of asthma and diseases of the immune system. In addition, ...

Abstract	STAT6 participates in classical IL-4/IL-13 signaling and stimulator of interferon genes-mediated antiviral innate immune responses. Aberrations in STAT6-mediated signaling are linked to development of asthma and diseases of the immune system. In addition, STAT6 remains constitutively active in multiple types of cancer. Therefore, targeting STAT6 is an attractive proposition for treating related diseases. Although a lot is known about the role of STAT6 in transcriptional regulation, molecular details on how STAT6 recognizes and binds specific segments of DNA to exert its function are not clearly understood. Here, we report the crystal structures of a homodimer of phosphorylated STAT6 core fragment (STAT6
Language	English
Publishing date	2016-11-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.1611228113
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Zs.A 1148: Show issues

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Article: 5-HT2C Receptor Structures Reveal the Structural Basis of GPCR Polypharmacology

Peng, Yao / McCorvy, John D / Harpsøe, Kasper / Lansu, Katherine / Yuan, Shuguang / Popov, Petr / Qu, Lu / Pu, Mengchen / Che, Tao / Nikolajsen, Louise F / Huang, Xi-Ping / Wu, Yiran / Shen, Ling / Bjørn-Yoshimoto, Walden E / Ding, Kang / Wacker, Daniel / Han, Gye Won / Cheng, Jianjun / Katritch, Vsevolod /

Jensen, Anders A / Hanson, Michael A / Zhao, Suwen / Gloriam, David E / Roth, Bryan L / Stevens, Raymond C / Liu, Zhi-Jie

Cell. 2018 Feb. 08, v. 172, no. 4

2018

Abstract: Drugs frequently require interactions with multiple targets—via a process known as polypharmacology—to achieve their therapeutic actions. Currently, drugs targeting several serotonin receptors, including the 5-HT₂C receptor, are useful for treating ... ...

Abstract	Drugs frequently require interactions with multiple targets—via a process known as polypharmacology—to achieve their therapeutic actions. Currently, drugs targeting several serotonin receptors, including the 5-HT₂C receptor, are useful for treating obesity, drug abuse, and schizophrenia. The competing challenges of developing selective 5-HT₂C receptor ligands or creating drugs with a defined polypharmacological profile, especially aimed at G protein-coupled receptors (GPCRs), remain extremely difficult. Here, we solved two structures of the 5-HT₂C receptor in complex with the highly promiscuous agonist ergotamine and the 5-HT₂A₋C receptor-selective inverse agonist ritanserin at resolutions of 3.0 Å and 2.7 Å, respectively. We analyzed their respective binding poses to provide mechanistic insights into their receptor recognition and opposing pharmacological actions. This study investigates the structural basis of polypharmacology at canonical GPCRs and illustrates how understanding characteristic patterns of ligand-receptor interaction and activation may ultimately facilitate drug design at multiple GPCRs.
Keywords	agonists ; drug design ; drugs ; ergotamine ; ligands ; serotonin receptors ; therapeutics
Language	English
Dates of publication	2018-0208
Size	p. 719-730.e14.
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	187009-9
ISSN	1097-4172 ; 0092-8674
ISSN (online)	1097-4172
ISSN	0092-8674
DOI	10.1016/j.cell.2018.01.001
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Crystal structures of agonist-bound human cannabinoid receptor CB

Nature

2017 Volume 547, Issue 7664, Page(s) 468–471

Abstract: The cannabinoid receptor 1 ( ... ...

Abstract	The cannabinoid receptor 1 (CB
MeSH term(s)	Binding Sites ; Cannabinoid Receptor Agonists/chemical synthesis ; Cannabinoid Receptor Agonists/chemistry ; Cannabinoid Receptor Agonists/pharmacology ; Crystallography, X-Ray ; Dronabinol/analogs & derivatives ; Dronabinol/chemical synthesis ; Dronabinol/chemistry ; Dronabinol/pharmacology ; Droperidol/analogs & derivatives ; Droperidol/chemical synthesis ; Droperidol/chemistry ; Droperidol/pharmacology ; Heterotrimeric GTP-Binding Proteins/metabolism ; Humans ; Ligands ; Molecular Docking Simulation ; Protein Binding ; Protein Conformation ; Receptor, Cannabinoid, CB1/agonists ; Receptor, Cannabinoid, CB1/antagonists & inhibitors ; Receptor, Cannabinoid, CB1/chemistry ; Receptor, Cannabinoid, CB1/metabolism
Chemical Substances	7'-Isothiocyanato-11-hydroxy-1',1'-dimethylheptylhexahydrocannabinol ; AM11542 ; Cannabinoid Receptor Agonists ; Ligands ; Receptor, Cannabinoid, CB1 ; Dronabinol (7J8897W37S) ; Heterotrimeric GTP-Binding Proteins (EC 3.6.5.1) ; Droperidol (O9U0F09D5X)
Language	English
Publishing date	2017-07-05
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/nature23272
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