Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Evan N, Feinberg"'
Autor:
Evan N. Feinberg, Debnil Sur, Zhenqin Wu, Brooke E. Husic, Huanghao Mai, Yang Li, Saisai Sun, Jianyi Yang, Bharath Ramsundar, Vijay S. Pande
Publikováno v:
ACS Central Science, Vol 4, Iss 11, Pp 1520-1530 (2018)
Externí odkaz:
https://doaj.org/article/d9ff7e5b3ecd43a4b7301d611325923a
Autor:
Bitna Yi, Alam Jahangir, Andrew K Evans, Denise Briggs, Kristine Ravina, Jacqueline Ernest, Amir B Farimani, Wenchao Sun, Jayakumar Rajadas, Michael Green, Evan N Feinberg, Vijay S Pande, Mehrdad Shamloo
Publikováno v:
PLoS ONE, Vol 12, Iss 7, p e0180319 (2017)
The beta-1 adrenergic receptor (ADRB1) is a promising therapeutic target intrinsically involved in the cognitive deficits and pathological features associated with Alzheimer's disease (AD). Evidence indicates that ADRB1 plays an important role in reg
Externí odkaz:
https://doaj.org/article/8f7924083cf944cba60e9ea23b9edaaf
Publikováno v:
Crystals, Vol 4, Iss 4, Pp 450-465 (2014)
Separating functionalized single-wall carbon nanotubes (SWCNTs) from functionalized amorphous carbon is challenging, due to their polydispersity and similar physicochemical properties. We describe a single-step, dialytic separation method that takes
Externí odkaz:
https://doaj.org/article/ef61bb78df4644ed9565e5bbe0d053f2
Autor:
Alex C. Ferris, Rajendra Uprety, Susruta Majumdar, Gavril W. Pasternak, Vijay S. Pande, Evan N. Feinberg, Gabriel N. Redel-Traub, Abdullah Allaoa, Travis C. Palmer, András Váradi
Publikováno v:
European Journal of Medicinal Chemistry. 164:241-251
A library-friendly approach to generate new scaffolds is decisive for the development of molecular probes, drug like molecules and preclinical entities. Here, we present the design and synthesis of novel heterocycles with spiro-2,6-dioxopiperazine an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1acd9fd55ee980d26b89c2cd8e1b3d75
https://doi.org/10.1016/j.ejmech.2018.12.048
https://doi.org/10.1016/j.ejmech.2018.12.048
Publikováno v:
Crystals
Crystals, Vol 4, Iss 4, Pp 450-465 (2014)
Volume 4
Issue 4
Pages 450-465
Crystals, Vol 4, Iss 4, Pp 450-465 (2014)
Volume 4
Issue 4
Pages 450-465
Separating functionalized single-wall carbon nanotubes (SWCNTs) from functionalized amorphous carbon is challenging, due to their polydispersity and similar physicochemical properties. We describe a single-step, dialytic separation method that takes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c160b413af4ae282e425db7457241a1
https://pubmed.ncbi.nlm.nih.gov/33981452
https://pubmed.ncbi.nlm.nih.gov/33981452
Publikováno v:
Journal of medicinal chemistry. 63(16)
The absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties of drug candidates are important for their efficacy and safety as therapeutics. Predicting ADMET properties has therefore been of great interest to the computation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5853683c51e01201b2ac1429ecacbcb8
https://pubmed.ncbi.nlm.nih.gov/32286824
https://pubmed.ncbi.nlm.nih.gov/32286824
Autor:
Brooke E. Husic, Debnil Sur, Zhenqin Wu, Vijay S. Pande, Huanghao Mai, Saisai Sun, Yang Li, Jianyi Yang, Evan N. Feinberg, Bharath Ramsundar
Publikováno v:
ACS Central Science, Vol 4, Iss 11, Pp 1520-1530 (2018)
ACS Central Science
ACS Central Science
The arc of drug discovery entails a multiparameter optimization problem spanning vast length scales. They key parameters range from solubility (angstroms) to protein-ligand binding (nanometers) to in vivo toxicity (meters). Through feature learning--
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85ca3d58cbaa8dc20174123462d685c2
https://doi.org/10.1021/acscentsci.8b00507
https://doi.org/10.1021/acscentsci.8b00507
Autor:
Evan N. Feinberg, Joseph Gomes, Vijay S. Pande, Caleb Geniesse, Aneesh S. Pappu, Zhenqin Wu, Bharath Ramsundar, Karl Leswing
Publikováno v:
Chemical Science. 9:513-530
Molecular machine learning has been maturing rapidly over the last few years. Improved methods and the presence of larger datasets have enabled machine learning algorithms to make increasingly accurate predictions about molecular properties. However,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a80afbd584722d6dc08c13cd237582bb
https://doi.org/10.1039/c7sc02664a
https://doi.org/10.1039/c7sc02664a
Autor:
Ralf C. Kling, Toon Laeremans, Adrian L. Sanborn, Kathryn E. Livingston, William I. Weis, Evan N. Feinberg, Sébastien Granier, Aashish Manglik, Thor S. Thorsen, Brian K. Kobilka, AJ Venkatakrishnan, Ron O. Dror, Weijiao Huang, Jan Steyaert, John R. Traynor, Peter Gmeiner, Hideaki E. Kato, Stephen M. Husbands
Publikováno v:
Nature. 584:E16-E16
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54241b075c2efb22a67089c338a313ba
https://doi.org/10.1038/s41586-020-2542-z
https://doi.org/10.1038/s41586-020-2542-z
Autor:
Rajendra, Uprety, András, Váradi, Abdullah, Allaoa, Gabriel N, Redel-Traub, Travis C, Palmer, Evan N, Feinberg, Alex C, Ferris, Vijay S, Pande, Gavril W, Pasternak, Susruta, Majumdar
Publikováno v:
European journal of medicinal chemistry. 164
A library-friendly approach to generate new scaffolds is decisive for the development of molecular probes, drug like molecules and preclinical entities. Here, we present the design and synthesis of novel heterocycles with spiro-2,6-dioxopiperazine an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::62597cdd7795708592c1719db35f4552
https://pubmed.ncbi.nlm.nih.gov/30597325
https://pubmed.ncbi.nlm.nih.gov/30597325