Zobrazeno 1 - 10
of 85
pro vyhledávání: '"Friedrich Rippmann"'
Publikováno v:
Journal of Cheminformatics, Vol 11, Iss 1, Pp 1-13 (2019)
Abstract In this paper, we explore the impact of combining different in silico prediction approaches and data sources on the predictive performance of the resulting system. We use inhibition of the hERG ion channel target as the endpoint for this stu
Externí odkaz:
https://doaj.org/article/4898d22f8b0b40dab92106c115aeb952
Autor:
Boris Grinshpun, Nels Thorsteinson, Joao NS Pereira, Friedrich Rippmann, David Nannemann, Vanita D. Sood, Yves Fomekong Nanfack
Publikováno v:
mAbs, Vol 13, Iss 1 (2021)
Understanding the pharmacokinetic (PK) properties of a drug, such as clearance, is a crucial step for evaluating efficacy. The PK of therapeutic antibodies can be complex and is influenced by interactions with the target, Fc-receptors, anti-drug anti
Externí odkaz:
https://doaj.org/article/832aaa3c9e4849959c6b25c7511f548b
Autor:
Andreas Evers, Shipra Malhotra, Wolf-Guido Bolick, Ahmad Najafian, Maria Borisovska, Shira Warszawski, Yves Fomekong Nanfack, Daniel Kuhn, Friedrich Rippmann, Alejandro Crespo, Vanita Sood
To select the most promising screening hits from antibody and VHH display campaigns for subsequent in-depth profiling and optimization, it is highly desirable to assess and select sequences on properties beyond only their binding signals from the sor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2f6751b606d86b2bb7387402410e11a
https://doi.org/10.1101/2022.11.19.517175
https://doi.org/10.1101/2022.11.19.517175
Autor:
Sophia Hönig, Wolf-Guido Bolick, Daniel Kuhn, Lukas Friedrich, Emanuel Ehmki, Thomas Fuchß, Birgitta Leuthner, Friedrich Rippmann, Matthias Rarey
Explainable and accurate predictions of bioactivity values are indispensable to accelerate drug design and reduce attrition during drug development. To enhance the accuracy of predictions, a new algorithmic approach was designed, which unites the adv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be83cf17223fbc60e04fdd776cd4a511
https://doi.org/10.21203/rs.3.rs-1836491/v1
https://doi.org/10.21203/rs.3.rs-1836491/v1
Autor:
Wouter Heyndrickx, Lewis Mervin, Tobias Morawietz, Noé Sturm, Lukas Friedrich, Adam Zalewski, Anastasia Pentina, Lina Humbeck, Martijn Oldenhof, Ritsuya Niwayama, Peter Schmidtke, Nikolas Fechner, Jaak Simm, Adam Arany, Nicolas Drizard, Rama Jabal, Arina Afanasyeva, Regis Loeb, Shlok Verma, Simon Harnqvist, Matthew Holmes, Balasz Pejo, Maria Telenczuk, Nicholas Holway, Arne Dieckmann, Nicola Rieke, Friederike Zumsande, Djork-Arné Clevert, Michael Krug, Christopher Luscombe, Darren Green, Peter Ertl, Peter Antal, David Marcus, Nicolas Do Huu, Hideyoshi Fuji, Stephen Pickett, Gergely Acs, Eric Boniface, Bernd Beck, Yax Sun, Arnaud Gohier, Friedrich Rippmann, Ola Engkvist, Andreas H. Göller, Yves Moreau, Mathieu N. Galtier, Ansgar Schuffenhauer, Hugo Ceulemans
Federated multi-partner machine learning can be an appealing and efficient method to increase the effective training data volume and thereby the predictivity of models, particularly when the generation of training data is resource intensive. In the l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8072552725a14731d649af1b8aedc958
https://doi.org/10.26434/chemrxiv-2022-ntd3r
https://doi.org/10.26434/chemrxiv-2022-ntd3r
Autor:
Sang-Kyu Park, Lukas Friedrich, Nawal A. Yahya, Claudia M. Rohr, Evgeny G. Chulkov, David Maillard, Friedrich Rippmann, Thomas Spangenberg, Jonathan S. Marchant
Publikováno v:
Sci Transl Med
Praziquantel (PZQ) is an essential medicine for treating parasitic flatworm infections such as schistosomiasis, which afflicts over 250 million people. However, PZQ is not universally effective, lacking activity against liver flukes of the Fasciola g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97301d735650c2764af7ee561314cc9f
https://pubmed.ncbi.nlm.nih.gov/34936384
https://pubmed.ncbi.nlm.nih.gov/34936384
Protein kinases are among the most important drug targets because their dysregulation can cause cancer, inflammatory, and degenerative diseases. Developing selective inhibitors is challenging due to the highly conserved binding sites across the rough
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a6d8fa65776d6d76f389e588000feb5
https://doi.org/10.26434/chemrxiv-2021-n3288
https://doi.org/10.26434/chemrxiv-2021-n3288
Autor:
Vanita D. Sood, Yves Fomekong Nanfack, Boris Grinshpun, D.P. Nannemann, Nels Thorsteinson, Friedrich Rippmann, Joao Ns Pereira
Publikováno v:
mAbs
article-version (VoR) Version of Record
article-version (VoR) Version of Record
Understanding the pharmacokinetic (PK) properties of a drug, such as clearance, is a crucial step for evaluating efficacy. The PK of therapeutic antibodies can be complex and is influenced by interactions with the target, Fc-receptors, anti-drug anti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0380c685276acd53872af522654530c9
http://europepmc.org/articles/PMC8204999
http://europepmc.org/articles/PMC8204999
Publikováno v:
Journal of Cheminformatics, Vol 11, Iss 1, Pp 1-13 (2019)
Journal of Cheminformatics
Journal of Cheminformatics
In this paper, we explore the impact of combining different in silico prediction approaches and data sources on the predictive performance of the resulting system. We use inhibition of the hERG ion channel target as the endpoint for this study as it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5133950b1a593067e9b70cb1ff111b86
http://link.springer.com/article/10.1186/s13321-019-0334-y
http://link.springer.com/article/10.1186/s13321-019-0334-y
Autor:
Jesús Alvarado-Valverde, Manjeet Kumar, Friedrich Rippmann, Renato J. Alves, Elizabeth Martínez-Pérez, Toby J. Gibson, Hugo Sámano-Sánchez, Jelena Čalyševa, Denis C. Shields, Bálint Mészáros, Lucía B. Chemes
Publikováno v:
Science Signaling
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
Cytosolic tail motifs in host cell surface receptors predict modes of SARS-CoV-2 entry and propagation.
SARS-CoV-2: From entry to autophagy? SARS-CoV-2, the virus that causes COVID-19, enters cells through endocytosis upon binding to the cell su
SARS-CoV-2: From entry to autophagy? SARS-CoV-2, the virus that causes COVID-19, enters cells through endocytosis upon binding to the cell su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19da050326160040809b5eacbbcad544
http://europepmc.org/articles/PMC7928535
http://europepmc.org/articles/PMC7928535