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Herman W T van Vlijmen

Showing results (1-10 of 36) with videos related to

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Journal of Molecular Biology|June 1, 2005
Normal mode calculations of icosahedral viruses with full dihedral flexibility by use of molecular symmetryHerman W T van Vlijmen, Martin Karplus
Proteins|October 3, 2007
A knowledge-based forcefield for protein-protein interface designLouis A Clark, Herman W T van Vlijmen
Protein Science : a Publication of the Protein Society|July 27, 2004
A classification of disulfide patterns and its relationship to protein structure and functionAbhas Gupta, Herman W T Van Vlijmen, Juswinder Singh
Journal of Molecular Biology|December 31, 2003
A novel database of disulfide patterns and its application to the discovery of distantly related homologsHerman W T van Vlijmen, Abhas Gupta, Lakshmi S Narasimhan, et al.
Journal of Immunology (Baltimore, Md. : 1950)|June 21, 2006
Trends in antibody sequence changes during the somatic hypermutation processLouis A Clark, Skanth Ganesan, Sarah Papp, et al.
Journal of Cheminformatics|January 12, 2021
Quantitative prediction of selectivity between the A<sub>1</sub> and A<sub>2A</sub> adenosine receptorsLindsey Burggraaff, Herman W T van Vlijmen, Adriaan P IJzerman, et al.
Journal of Chemical Information and Modeling|May 20, 2014
Selecting an optimal number of binding site waters to improve virtual screening enrichments against the adenosine A2A receptorEelke B Lenselink, Thijs Beuming, Woody Sherman, et al.
Journal of Chemical Information and Modeling|January 18, 2022
Divide and Conquer. Pocket-Opening Mixed-Solvent Simulations in the Perspective of Docking Virtual Screening Applications for Drug DiscoveryFrancesc Sabanés Zariquiey, Edgar Jacoby, Ann Vos, et al.
Journal of Cheminformatics|February 21, 2023
DrugEx v3: scaffold-constrained drug design with graph transformer-based reinforcement learningXuhan Liu, Kai Ye, Herman W T van Vlijmen, et al.
Journal of Cheminformatics|May 26, 2019
An exploration strategy improves the diversity of de novo ligands using deep reinforcement learning: a case for the adenosine A<sub>2A</sub> receptorXuhan Liu, Kai Ye, Herman W T van Vlijmen, et al.
Pageof 4

Showing results (1-10 of 36) with videos related to

Sort By:
Pageof 4
Journal of Molecular Biology|June 1, 2005
Normal mode calculations of icosahedral viruses with full dihedral flexibility by use of molecular symmetryHerman W T van Vlijmen, Martin Karplus
Proteins|October 3, 2007
A knowledge-based forcefield for protein-protein interface designLouis A Clark, Herman W T van Vlijmen
Protein Science : a Publication of the Protein Society|July 27, 2004
A classification of disulfide patterns and its relationship to protein structure and functionAbhas Gupta, Herman W T Van Vlijmen, Juswinder Singh
Journal of Molecular Biology|December 31, 2003
A novel database of disulfide patterns and its application to the discovery of distantly related homologsHerman W T van Vlijmen, Abhas Gupta, Lakshmi S Narasimhan, et al.
Journal of Immunology (Baltimore, Md. : 1950)|June 21, 2006
Trends in antibody sequence changes during the somatic hypermutation processLouis A Clark, Skanth Ganesan, Sarah Papp, et al.
Journal of Cheminformatics|January 12, 2021
Quantitative prediction of selectivity between the A<sub>1</sub> and A<sub>2A</sub> adenosine receptorsLindsey Burggraaff, Herman W T van Vlijmen, Adriaan P IJzerman, et al.
Journal of Chemical Information and Modeling|May 20, 2014
Selecting an optimal number of binding site waters to improve virtual screening enrichments against the adenosine A2A receptorEelke B Lenselink, Thijs Beuming, Woody Sherman, et al.
Journal of Chemical Information and Modeling|January 18, 2022
Divide and Conquer. Pocket-Opening Mixed-Solvent Simulations in the Perspective of Docking Virtual Screening Applications for Drug DiscoveryFrancesc Sabanés Zariquiey, Edgar Jacoby, Ann Vos, et al.
Journal of Cheminformatics|February 21, 2023
DrugEx v3: scaffold-constrained drug design with graph transformer-based reinforcement learningXuhan Liu, Kai Ye, Herman W T van Vlijmen, et al.
Journal of Cheminformatics|May 26, 2019
An exploration strategy improves the diversity of de novo ligands using deep reinforcement learning: a case for the adenosine A<sub>2A</sub> receptorXuhan Liu, Kai Ye, Herman W T van Vlijmen, et al.
Pageof 4