LIVIVO - Search results -

Search results

Result 1 - 10 of total 73

Search options

Article ; Online: Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence.

Duran-Frigola, Miquel / Cigler, Marko / Winter, Georg E

Journal of the American Chemical Society

2023 Volume 145, Issue 5, Page(s) 2711–2732

Abstract: Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) ... ...

Abstract	Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) promises to overcome some of these limitations. In brief, TPD is dependent on small molecules that induce the proximity between a protein of interest (POI) and an E3 ubiquitin ligase, causing ubiquitination and degradation of the POI. In this perspective, we want to reflect on current challenges in the field, and discuss how advances in multiomics profiling, artificial intelligence, and machine learning (AI/ML) will be vital in overcoming them. The presented roadmap is discussed in the context of small-molecule degraders but is equally applicable for other emerging proximity-inducing modalities.
MeSH term(s)	Humans ; Artificial Intelligence ; Multiomics ; Proteolysis ; Ubiquitin-Protein Ligases/metabolism ; Ubiquitination
Chemical Substances	Ubiquitin-Protein Ligases (EC 2.3.2.27)
Language	English
Publishing date	2023-01-27
Publishing country	United States
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't
ZDB-ID	3155-0
ISSN	1520-5126 ; 0002-7863
ISSN (online)	1520-5126
ISSN	0002-7863
DOI	10.1021/jacs.2c11098
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Bonn / Germany

Z 4' 55/32: Show issues
Z 7.3: Show issues

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: AI can help to tailor drugs for Africa - but Africans should lead the way.

Turon, Gemma / Njoroge, Mathew / Mulubwa, Mwila / Duran-Frigola, Miquel / Chibale, Kelly

Nature

2024 Volume 628, Issue 8007, Page(s) 265–267

MeSH term(s)	Africa ; Artificial Intelligence/trends ; Drug Development/methods ; Drug Development/trends ; Biomedical Research/methods ; Biomedical Research/trends ; Databases as Topic ; Research Personnel/trends ; African People
Language	English
Publishing date	2024-04-08
Publishing country	England
Document type	News
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/d41586-024-01001-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 26: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MG 9: Show issues
Zs.MO 244: Show issues

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Machine Learning Approaches Identify Chemical Features for Stage-Specific Antimalarial Compounds.

van Heerden, Ashleigh / Turon, Gemma / Duran-Frigola, Miquel / Pillay, Nelishia / Birkholtz, Lyn-Marié

ACS omega

2023 Volume 8, Issue 46, Page(s) 43813–43826

Abstract: Efficacy data from diverse chemical libraries, screened against the various stages of the malaria ... ...

Abstract	Efficacy data from diverse chemical libraries, screened against the various stages of the malaria parasite
Language	English
Publishing date	2023-11-07
Publishing country	United States
Document type	Journal Article
ISSN	2470-1343
ISSN (online)	2470-1343
DOI	10.1021/acsomega.3c05664
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: First fully-automated AI/ML virtual screening cascade implemented at a drug discovery centre in Africa.

Turon, Gemma / Hlozek, Jason / Woodland, John G / Kumar, Ankur / Chibale, Kelly / Duran-Frigola, Miquel

Nature communications

2023 Volume 14, Issue 1, Page(s) 5736

Abstract: Streamlined data-driven drug discovery remains challenging, especially in resource-limited settings. We present ZairaChem, an artificial intelligence (AI)- and machine learning (ML)-based tool for quantitative structure-activity/property relationship ( ... ...

Abstract	Streamlined data-driven drug discovery remains challenging, especially in resource-limited settings. We present ZairaChem, an artificial intelligence (AI)- and machine learning (ML)-based tool for quantitative structure-activity/property relationship (QSAR/QSPR) modelling. ZairaChem is fully automated, requires low computational resources and works across a broad spectrum of datasets. We describe an end-to-end implementation at the H3D Centre, the leading integrated drug discovery unit in Africa, at which no prior AI/ML capabilities were available. By leveraging in-house data collected over a decade, we have developed a virtual screening cascade for malaria and tuberculosis drug discovery comprising 15 models for key decision-making assays ranging from whole-cell phenotypic screening and cytotoxicity to aqueous solubility, permeability, microsomal metabolic stability, cytochrome inhibition, and cardiotoxicity. We show how computational profiling of compounds, prior to synthesis and testing, can inform progression of frontrunner compounds at H3D. This project is a first-of-its-kind deployment at scale of AI/ML tools in a research centre operating in a low-resource setting.
MeSH term(s)	Artificial Intelligence ; Machine Learning ; Africa ; Biological Assay ; Drug Discovery
Language	English
Publishing date	2023-09-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-41512-2
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque.

Fernández-Torras, Adrià / Duran-Frigola, Miquel / Bertoni, Martino / Locatelli, Martina / Aloy, Patrick

Nature communications

2022 Volume 13, Issue 1, Page(s) 5304

Abstract: Biomedical data is accumulating at a fast pace and integrating it into a unified framework is a major challenge, so that multiple views of a given biological event can be considered simultaneously. Here we present the Bioteque, a resource of ... ...

Abstract	Biomedical data is accumulating at a fast pace and integrating it into a unified framework is a major challenge, so that multiple views of a given biological event can be considered simultaneously. Here we present the Bioteque, a resource of unprecedented size and scope that contains pre-calculated biomedical descriptors derived from a gigantic knowledge graph, displaying more than 450 thousand biological entities and 30 million relationships between them. The Bioteque integrates, harmonizes, and formats data collected from over 150 data sources, including 12 biological entities (e.g., genes, diseases, drugs) linked by 67 types of associations (e.g., 'drug treats disease', 'gene interacts with gene'). We show how Bioteque descriptors facilitate the assessment of high-throughput protein-protein interactome data, the prediction of drug response and new repurposing opportunities, and demonstrate that they can be used off-the-shelf in downstream machine learning tasks without loss of performance with respect to using original data. The Bioteque thus offers a thoroughly processed, tractable, and highly optimized assembly of the biomedical knowledge available in the public domain.
MeSH term(s)	Knowledge ; Knowledge Bases ; Machine Learning ; Pattern Recognition, Automated ; Proteins
Chemical Substances	Proteins
Language	English
Publishing date	2022-09-09
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-33026-0
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Endothelial transcriptomic analysis identifies biomarkers of severe and cerebral malaria.

Gomes, Cláudia / Varo, Rosauro / Duran-Frigola, Miquel / Sitoe, Antonio / Bila, Rubão / Machevo, Sonia / Mayor, Alfredo / Bassat, Quique / Rodriguez, Ana

JCI insight

2023 Volume 8, Issue 22

Abstract: Malaria can quickly progress from an uncomplicated infection into a life-threatening severe disease. However, the unspecificity of early symptoms often makes it difficult to identify patients at high risk of developing severe disease. Additionally, one ... ...

Abstract	Malaria can quickly progress from an uncomplicated infection into a life-threatening severe disease. However, the unspecificity of early symptoms often makes it difficult to identify patients at high risk of developing severe disease. Additionally, one of the most feared malaria complications - cerebral malaria - is challenging to diagnose, often resulting in treatment delays that can lead to adverse outcomes. To identify candidate biomarkers for the prognosis and/or diagnosis of severe and cerebral malaria, we have analyzed the transcriptomic response of human brain microvascular endothelial cells to erythrocytes infected with Plasmodium falciparum. Candidates were validated in plasma samples from a cohort of pediatric patients with malaria from Mozambique, resulting in the identification of several markers with capacity to distinguish uncomplicated from severe malaria, the most potent being the metallopeptidase ADAMTS18. Two other biomarkers, Angiopoietin-like-4 and Inhibin-βE were able to differentiate children with cerebral malaria within the severe malaria group, showing increased sensitivity after combination in a biomarker signature. The validation of the predicted candidate biomarkers in plasma of children with severe and cerebral malaria underscores the power of this transcriptomic approach and indicates that a specific endothelial response to P. falciparum-infected erythrocytes is linked to the pathophysiology of severe malaria.
MeSH term(s)	Humans ; Child ; Malaria, Cerebral/diagnosis ; Endothelial Cells ; Transcriptome ; Malaria, Falciparum/diagnosis ; Biomarkers ; ADAMTS Proteins
Chemical Substances	Biomarkers ; ADAMTS18 protein, human (EC 3.4.24.-) ; ADAMTS Proteins (EC 3.4.24.-)
Language	English
Publishing date	2023-11-22
Publishing country	United States
Document type	Journal Article
ISSN	2379-3708
ISSN (online)	2379-3708
DOI	10.1172/jci.insight.172845
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Encircling the regions of the pharmacogenomic landscape that determine drug response.

Fernández-Torras, Adrià / Duran-Frigola, Miquel / Aloy, Patrick

Genome medicine

2019 Volume 11, Issue 1, Page(s) 17

Abstract: Background: The integration of large-scale drug sensitivity screens and genome-wide experiments is changing the field of pharmacogenomics, revealing molecular determinants of drug response without the need for previous knowledge about drug action. In ... ...

Abstract	Background: The integration of large-scale drug sensitivity screens and genome-wide experiments is changing the field of pharmacogenomics, revealing molecular determinants of drug response without the need for previous knowledge about drug action. In particular, transcriptional signatures of drug sensitivity may guide drug repositioning, prioritize drug combinations, and point to new therapeutic biomarkers. However, the inherent complexity of transcriptional signatures, with thousands of differentially expressed genes, makes them hard to interpret, thus giving poor mechanistic insights and hampering translation to clinics. Methods: To simplify drug signatures, we have developed a network-based methodology to identify functionally coherent gene modules. Our strategy starts with the calculation of drug-gene correlations and is followed by a pathway-oriented filtering and a network-diffusion analysis across the interactome. Results: We apply our approach to 189 drugs tested in 671 cancer cell lines and observe a connection between gene expression levels of the modules and mechanisms of action of the drugs. Further, we characterize multiple aspects of the modules, including their functional categories, tissue-specificity, and prevalence in clinics. Finally, we prove the predictive capability of the modules and demonstrate how they can be used as gene sets in conventional enrichment analyses. Conclusions: Network biology strategies like module detection are able to digest the outcome of large-scale pharmacogenomic initiatives, thereby contributing to their interpretability and improving the characterization of the drugs screened.
MeSH term(s)	Algorithms ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics ; Gene Regulatory Networks ; Genome-Wide Association Study/methods ; Humans ; Pharmacogenomic Variants
Language	English
Publishing date	2019-03-26
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2484394-5
ISSN	1756-994X ; 1756-994X
ISSN (online)	1756-994X
ISSN	1756-994X
DOI	10.1186/s13073-019-0626-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Connecting chemistry and biology through molecular descriptors.

Fernández-Torras, Adrià / Comajuncosa-Creus, Arnau / Duran-Frigola, Miquel / Aloy, Patrick

Current opinion in chemical biology

2021 Volume 66, Page(s) 102090

Abstract: Through the representation of small molecule structures as numerical descriptors and the exploitation of the similarity principle, chemoinformatics has made paramount contributions to drug discovery, from unveiling mechanisms of action and repurposing ... ...

Abstract	Through the representation of small molecule structures as numerical descriptors and the exploitation of the similarity principle, chemoinformatics has made paramount contributions to drug discovery, from unveiling mechanisms of action and repurposing approved drugs to de novo crafting of molecules with desired properties and tailored targets. Yet, the inherent complexity of biological systems has fostered the implementation of large-scale experimental screenings seeking a deeper understanding of the targeted proteins, the disrupted biological processes and the systemic responses of cells to chemical perturbations. After this wealth of data, a new generation of data-driven descriptors has arisen providing a rich portrait of small molecule characteristics that goes beyond chemical properties. Here, we give an overview of biologically relevant descriptors, covering chemical compounds, proteins and other biological entities, such as diseases and cell lines, while aligning them to the major contributions in the field from disciplines, such as natural language processing or computer vision. We now envision a new scenario for chemical and biological entities where they both are translated into a common numerical format. In this computational framework, complex connections between entities can be unveiled by means of simple arithmetic operations, such as distance measures, additions, and subtractions.
MeSH term(s)	Biology ; Computational Biology ; Drug Discovery ; Proteins
Chemical Substances	Proteins
Language	English
Publishing date	2021-10-06
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1439176-4
ISSN	1879-0402 ; 1367-5931
ISSN (online)	1879-0402
ISSN	1367-5931
DOI	10.1016/j.cbpa.2021.09.001
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 4986: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Rationalizing Drug Response in Cancer Cell Lines.

Juan-Blanco, Teresa / Duran-Frigola, Miquel / Aloy, Patrick

Journal of molecular biology

2018 Volume 430, Issue 18 Pt A, Page(s) 3016–3027

Abstract: Cancer cell lines (CCLs) play an important role in the initial stages of drug discovery allowing, among others, for the screening of drug candidates. As CCL panels continue to grow in size and diversity, many polymorphisms in genes encoding drug- ... ...

Abstract	Cancer cell lines (CCLs) play an important role in the initial stages of drug discovery allowing, among others, for the screening of drug candidates. As CCL panels continue to grow in size and diversity, many polymorphisms in genes encoding drug-metabolizing enzymes, transporters and drug targets, as well as disease-related genes have been linked to altered drug sensitivity. However, identifying the correlation between this variability and pharmacological responses remains challenging due to the heterogeneity of cancer biology and the intricate interplay between cell lines and drug molecules. Here, we propose a network-based strategy that exploits information on gene expression and somatic mutations of CCLs to group cells according to their molecular similarity. We then identify genes that are characteristic of each cluster and correlate their status with drug response. We find that CCLs with similar characteristic active network regions present specific responses to certain drugs, and identify a limited set of genes that might be directly involved in drug sensitivity or resistance.
MeSH term(s)	Antineoplastic Agents/pharmacology ; Bayes Theorem ; Cell Line, Tumor ; Drug Discovery ; Drug Screening Assays, Antitumor/methods ; Gene Expression Profiling ; Humans ; Mutation ; Protein Interaction Mapping ; ROC Curve ; Therapeutic Index, Drug
Chemical Substances	Antineoplastic Agents
Language	English
Publishing date	2018-04-04
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	80229-3
ISSN	1089-8638 ; 0022-2836
ISSN (online)	1089-8638
ISSN	0022-2836
DOI	10.1016/j.jmb.2018.03.021
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 867: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Endothelial transcriptomic analysis identifies biomarkers of severe and cerebral malaria

Cláudia Gomes / Rosauro Varo / Miquel Duran-Frigola / Antonio Sitoe / Rubão Bila / Sonia Machevo / Alfredo Mayor / Quique Bassat / Ana Rodriguez

JCI Insight, Vol 8, Iss

2023 Volume 22

Abstract	Malaria can quickly progress from an uncomplicated infection into a life-threatening severe disease. However, the unspecificity of early symptoms often makes it difficult to identify patients at high risk of developing severe disease. Additionally, one of the most feared malaria complications — cerebral malaria — is challenging to diagnose, often resulting in treatment delays that can lead to adverse outcomes. To identify candidate biomarkers for the prognosis and/or diagnosis of severe and cerebral malaria, we have analyzed the transcriptomic response of human brain microvascular endothelial cells to erythrocytes infected with Plasmodium falciparum. Candidates were validated in plasma samples from a cohort of pediatric patients with malaria from Mozambique, resulting in the identification of several markers with capacity to distinguish uncomplicated from severe malaria, the most potent being the metallopeptidase ADAMTS18. Two other biomarkers, Angiopoietin-like-4 and Inhibin-βE were able to differentiate children with cerebral malaria within the severe malaria group, showing increased sensitivity after combination in a biomarker signature. The validation of the predicted candidate biomarkers in plasma of children with severe and cerebral malaria underscores the power of this transcriptomic approach and indicates that a specific endothelial response to P. falciparum–infected erythrocytes is linked to the pathophysiology of severe malaria.
Keywords	Infectious disease ; Medicine ; R
Subject code	616
Language	English
Publishing date	2023-11-01T00:00:00Z
Publisher	American Society for Clinical investigation
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED