Computational Tools to Expedite the Identification of Potential PXR Modulators in Complex Natural Product Mixtures – A Case Study with Five Closely Related Licorice Species

Authors

Pankaj Pandey, University of MississippiFollow
Manal Alhusban, University of Mississippi
Jongmin Ahn, University of Mississippi
Bharathi Avula, University of Mississippi
Saqlain Haider, University of Mississippi
Cristina Avonto, University of Mississippi
Zulfiqar Ali, University of Mississippi
Shabana I. Khan, University of Mississippi
Daneel Ferreira, University of Mississippi
Ikhlas A. Khan, University of Mississippi
Amar G. Chittiboyina, University of Mississippi

Department

NCNPR

Files

Description

Corresponding author (NCNPR): Pankaj Pandey, ppandey@olemiss.edu

Publication Date

10-11-2022

Relational Format

poster

Recommended Citation

Pandey, Pankaj; Alhusban, Manal; Ahn, Jongmin; Avula, Bharathi; Haider, Saqlain; Avonto, Cristina; Ali, Zulfiqar; Khan, Shabana I.; Ferreira, Daneel; Khan, Ikhlas A.; and Chittiboyina, Amar G., "Computational Tools to Expedite the Identification of Potential PXR Modulators in Complex Natural Product Mixtures – A Case Study with Five Closely Related Licorice Species" (2022). Annual Poster Session 2022. 15.
https://egrove.olemiss.edu/pharm_annual_posters_2022/15