Institute of Visual Computing (IVC)

Karl Kirschner Portrait

Dr Karl Kirschner

Research Scientist/Mentor and Teacher/International Chair (2017-'19)

karl.kirschner@h-brs.de

Unit

Institute of Technology, Resource and Energy-efficient Engineering (TREE), Institute of Visual Computing (IVC)

Research fields

  • Computational Chemistry

Location

Sankt Augustin

Room

C 228

Address

Grantham-Allee 20

53754, Sankt Augustin

Telephone

+49 2241 865 267

Profile

Fields of activity
  • Institute for Visual Computing
  • Visual Computing in Theoretical Chemistry
  • Project FLOW: Newtonian molecular modelling. In order to generate reliable and accurate force fields, a large number of molecules must be analysed. These large amounts of data are visualised and analysed using the high-resolution HORNET display.

Curriculum vitae

Short CV

  • 1999 PhD in physical chemistry at the University of Georgia (USA)
  • Publications (peer-reviewed publications): 48 in total in approx. 23 different journals, 2 book chapters
  • 2 U.S. patents for a pharmacologically active agent that inhibits breast cancer in animal models (mice)
  • Research interests in the field of theoretical chemistry (see also detailed CV-Research Highlights):
    1. Force-field development for molecular modelling (e.g. Glycam06, Wolf2Pack)
    2. Biological modelling and drug design (e.g carbohydrates, lipids, breast cancer, ribosome)
    3. Modelling molecular nonbonded clusters (e.g. water clusters)
  • Supervision of students in research projects: A total of 44 undergraduate students, 2 Master students, 2 doctoral students
  • Previous courses include Physical Chemistry, Introduction to computational chemistry methods and The history of America's Adirondack Park

Detailed curriculum vitae as PDF

Research Projects

Utilization of Molecular Modelling for Bio-Chemical Application Scenarios (UMMBAS)

Bio-chemical research is increasingly dependent on accurate computer modelling and analysis. This field of research is by its very nature highly interdisciplinary, as basic physical laws must be implemented algorithmically in order to make relevant contributions in life science applications. The project and the associated initiative UMMBAS bundles the strong cross-disciplinary expertise at the H-BRS in method development, visualisation and the application of computer-based procedures for deciphering material science and biochemical issues.

Project management at the H-BRS

Prof. Dr Matthias Preller
Teaser Placeholder

Publications

Publications since 2015 (67 total since 1993)

  1. A Hagg and KN Kirschner. “Open-Source Machine Learning in Computational Chemistry”. Journal of Chemical Information and Modeling 63.15 (2023), 4505–4532 https://doi.org/10.1021/acs.jcim.3c00643
  2. M Müller, A Hagg, R Strickstrock, M Hülsmann, A Asteroth, KN Kirschner, & D Reith. “Determining Lennard-Jones Parameters Using Multiscale Target Data through Presampling-Enhanced, Surrogate-Assisted Global Optimization”. Journal of Chemical Information and Modeling 63.7 (2023), 1872–1881 https://doi.org/10.1021/acs.jcim.2c01231

  3.  W Fiedler, F Freisleben, J Wellbrock, & Kirschner, Karl N. “Mebendazole’s Conformational
    Space and Its Predicted Binding to Human Heat-Shock Protein 90”. Journal of Chemical
    Information and Modeling 62.15 (2022), 3604–3617 https://doi.org/10.3390/ijms221910670

  4. R Strickstrock, M Hülsmann, D Reith, and KN Kirschner. “Optimizing Lennard-Jones
    parameters by coupling single molecule and ensemble target data”. Computer Physics
    Communications 274 (2022), 108285 https://doi.org/10.1016/j.cpc.2022.108285

  5. F. Freisleben, F. Modemann, J. Muschhammer, H. Stamm, F. Brauneck, A. Krispien, C. Bokemeyer, K.N. Kirschner, J. Wellbrock, & W. Fiedler. "Mebendazole Mediates Proteasomal Degradation of GLI Transcription Factors in Acute Myeloid Leukemia," International Journal of Molecular Sciences, 2021, 22, 10670 https://doi.org/10.3390/ijms221910670
  6. Cesari, A.; Uccello Barretta, G.; Kirschner, K.N.; Pappalardo, M.; Basile, L.; Guccione, S.; Russotto, C.; Lauro, M. R.; Cavaliere, F. & Balzano, F. “Interaction of natural flavonoid eriocitrin with β-cyclodextrin and hydroxypropyl-β-cyclodextrin: an NMR and molecular dynamics investigation,” New J. Chem., The Royal Society of Chemistry, 2020, 44, 16431-16441 https://pubs.rsc.org/en/content/articlelanding/2020/nj/d0nj02022b#!divAbstract
  7. K.N. Kirschner, S. Keil, K. Seuser, and C. Siefer, “Teaching Technical Journalism with an Engineering Foundation,” in 2020 IEEE Global Engineering Education Conference (EDUCON), Porto, Portugal, 2020, pp. 808-813, doi: 10.1109/EDUCON45650.2020.9125242. (Won Best Paper.)
  8. K.N. Kirschner, D. Reith, and W. Heiden, “The performance of Dunning, Jensen, and Karlsruhe basis sets on computing relative energies and geometries,” Soft Materials, 2020, 18, 200-214 https://www.tandfonline.com/doi/full/10.1080/1539445X.2020.1714656
  9. Schenk, M.R.; Köddermann, T.; Kirschner, K.N.; Knauer, S. & Reith, D. “Molecular Dynamics in the Energy Sector: Experiment and Modeling of the CO2/CH4 Mixture,” Journal of Chemical & Engineering Data, 2020, 65, 1117-1123 https://pubs.acs.org/doi/10.1021/acs.jced.9b00503
  10. Krämer, A.; Pickard, F.; Huang, J.; Venable, R.; Reith, D.; Kirschner, K.; Pastor, R. & Brooks, B. “Interactions of Water and Alkanes: Modifying Additive Force Fields to Account for Polarization Effects,” J. Chem. Theory Comput., 2019, 15 (6), 3854-3867  https://pubs.acs.org/doi/10.1021/acs.jctc.9b00016
  11. Mitchell, S. R.; Larkin, K.; Grieselhuber, N. R.; Lai, T.-H.; Cannon, M.; Orwick, S.; Sharma, P.; Asemelash, Y.; Zhang, P.; Goettl, V. M.; Beaver, L.; Mims, A.; Puduvalli, V. K.; Blachly, J. S.; Lehman, A.; Harrington, B.; Henderson, S.; Breitbach, J. T.; Williams, K. E.; Dong, S.; Baloglu, E.; Senapedis, W.; Kirschner, K.; Sampath, D.; Lapalombella, R. & Byrd, J. C. “Selective targeting of NAMPT by KPT-9274 in acute myeloid leukemia, Blood Advances, American Society of Hematology, 2019, 3, 242-255  https://www.bloodadvances.org/content/3/3/242
  12. A. Bernardi, R. Faller, D. Reith, and K.N. Kirschner, “ACPYPE update for nonuniform 1-4 scale factors: Conversion of the GLYCAM06 force field from AMBER to GROMACS,” SoftwareX, 2019, 10, 100241 https://www.sciencedirect.com/science/article/pii/S2352711018300736
  13. K. Kirschner, J. Bode, and D. Reith, “The International Chair - Concept and Benefits of a New Interdisciplinary Faculty Position,” in 2019 IEEE Global Engineering Education Conference (EDUCON), 2019, 775-780 https://ieeexplore.ieee.org/document/8725255
  14. K. N. Kirschner, W. Heiden, and D. Reith. “Small alcohols revisited: CCSD(T) relative potential energies for the minima, first- and second-order saddle points, and torsion-coupled surfaces,” ACS Omega, 3(1):419–432, 2018 https://pubs.acs.org/doi/abs/10.1021/acsomega.7b01367
  15. A. Bernardi, K.N. Kirschner, and R. Faller. “Structural analysis of human glycoprotein butyrylcholinesterase using atomistic molecular dynamics: The importance of glycosylation site ASN241,” PLOS ONE, 12(11):1–17, 11 2017 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0187994
  16. T. Köddermann, M.R. Schenk, M. Hülsmann, A. Krämer, K.N. Kirschner, and D. Reith. “Molecular dynamics simulation of membrane free energy profiles using accurate force field for ionic liquids.” In Scientific Computing and Algorithms in Industrial Simulations. Springer, Cham, 2017 https://link.springer.com/chapter/10.1007/978-3-319-62458-7_14
  17. K. N. Kirschner, W. Heiden, and D. Reith. “Relative electronic and free energies of octane’s unique conformations. Molecular Physics, 115(9-12):1155–1165, 2017 https://www.tandfonline.com/doi/abs/10.1080/00268976.2016.1262076
  18. R. Elfgen, M. Hülsmann A. Krämer, T. Köddermann, K.N. Kirschner, and D. Reith. “Optimized atomistic force fields for aqueous solutions of magnesium and calcium chloride: Analysis, achievements and limitations,” The European Physical Journal Special Topics, 225(8):1391–1409, 2016 https://link.springer.com/article/10.1140/epjst/e2016-60112-7
  19. M. Hülsmann, K.N. Kirschner, A. Krämer, D.D. Heinrich, O. Krämer-Fuhrmann, and D. Reith. “Optimizing molecular models through force-field parameterization via the efficient combination of modular program packages. In Q. R. Snurr, S. C. Adjiman, and A. D. Kofke, editors, Foundations of Molecular Modeling and Simulation: Select Papers from FOMMS 2015, pages 53–77. Springer Singapore, Singapore, 2016 https://link.springer.com/chapter/10.1007/978-981-10-1128-3_4
  20. K.N. Kirschner, D. Reith, O. Jato, and A. Hinkenjann. “Visualizing potential energy curves and conformations on ultra high-resolution display walls,” Journal of Molecular Graphics and Modelling, 62:174–180, 2015 https://www.sciencedirect.com/science/article/pii/S1093326315300577

Further Information

Further information