Jürgen Bajorath

Research interests

Publications

• Evolution of Support Vector Machine and Regression Modeling in Chemoinformatics and Drug Discovery

  Journal of Computer-Aided Molecular Design · 2022 · 10.1007/s10822-022-00442-9

• Interpretation of machine learning models using shapley values: application to compound potency and multi-target activity predictions

  Journal of Computer-Aided Molecular Design · 2020 · 10.1007/s10822-020-00314-0

• QSAR without borders

  Chemical Society Reviews · 2020 · https://doi.org/10.1039/d0cs00098a

• Interpretation of Compound Activity Predictions from Complex Machine Learning Models Using Local Approximations and Shapley Values

  Journal of Medicinal Chemistry · 2019 · 10.1021/acs.jmedchem.9b01101

• Application of Generative Autoencoder in De Novo Molecular Design

  Molecular Informatics · 2017 · 10.1002/minf.201700123

• Recent Advances in Scaffold Hopping

  Journal of Medicinal Chemistry · 2016 · 10.1021/acs.jmedchem.6b01437

• Polypharmacology: Challenges and Opportunities in Drug Discovery

  Journal of Medicinal Chemistry · 2014 · https://doi.org/10.1021/jm5006463

• Molecular Similarity in Medicinal Chemistry

  Journal of Medicinal Chemistry · 2013 · 10.1021/jm401411z

• Exploring Activity Cliffs in Medicinal Chemistry

  Journal of Medicinal Chemistry · 2012 · 10.1021/jm201706b

• State-of-the-art in ligand-based virtual screening

  Drug Discovery Today · 2011 · 10.1016/j.drudis.2011.02.011

• Current Trends in Ligand-Based Virtual Screening: Molecular Representations, Data Mining Methods, New Application Areas, and Performance Evaluation

  Journal of Chemical Information and Modeling · 2010 · 10.1021/ci900419k

• Quo Vadis, Virtual Screening? A Comprehensive Survey of Prospective Applications

  Journal of Medicinal Chemistry · 2010 · 10.1021/jm101020z

• Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches

  Drug Discovery Today · 2007 · 10.1016/j.drudis.2007.01.011

• Rational Development of LEA29Y (belatacept), a High-Affinity Variant of CTLA4-Ig with Potent Immunosuppressive Properties

  American Journal of Transplantation · 2005 · 10.1111/j.1600-6143.2005.00749.x

• Docking and scoring in virtual screening for drug discovery: methods and applications

  Nature Reviews Drug Discovery · 2004 · https://doi.org/10.1038/nrd1549

• Molecular Modeling and Functional Mapping of B7-H1 and B7-DC Uncouple Costimulatory Function from PD-1 Interaction

  The Journal of Experimental Medicine · 2003 · 10.1084/jem.20021752

• B7-H4, a Molecule of the B7 Family, Negatively Regulates T Cell Immunity

  Immunity · 2003 · 10.1016/s1074-7613(03)00152-3

• Integration of virtual and high-throughput screening

  Nature Reviews Drug Discovery · 2002 · https://doi.org/10.1038/nrd941

• Molecular Descriptors in Chemoinformatics, Computational Combinatorial Chemistry, and Virtual Screening

  Combinatorial Chemistry & High Throughput Screening · 2000 · https://doi.org/10.2174/1386207003331454

• Covalent Dimerization of CD28/CTLA-4 and Oligomerization of CD80/CD86 Regulate T Cell Costimulatory Interactions

  Journal of Biological Chemistry · 1996 · 10.1074/jbc.271.43.26762

• IMMUNE REGULATION BY CD40 AND ITS LIGAND GP39

  Annual Review of Immunology · 1996 · 10.1146/annurev.immunol.14.1.591

• The membrane-bound and soluble forms of HLA-G bind identical sets of endogenous peptides but differ with respect to TAP association

  Immunity · 1995 · 10.1016/1074-7613(95)90130-2

• Human B7-1 (CD80) and B7-2 (CD86) bind with similar avidities but distinct kinetics to CD28 and CTLA-4 receptors

  Immunity · 1994 · https://doi.org/10.1016/s1074-7613(94)80021-9

• Complementarity determining region 1 (CDR1)- and CDR3-analogous regions in CTLA-4 and CD28 determine the binding to B7-1.

  The Journal of Experimental Medicine · 1994 · 10.1084/jem.180.6.2049

• The CD40 ligand, gp39, is defective in activated T cells from patients with X-linked hyper-IgM syndrome

  Cell · 1993 · 10.1016/0092-8674(93)90668-g

Current projects

No projects listed.