Our Publications

PharmAI's technology is based on over 100 man years of academic research. Our scientists continuously improve our algorithm to better and faster optimize our drug discovery engine. Below is a selected list of publications that is the base of the PharmAIs algorithm.


In Silico Driven Prediction of MAPK14 Off-Targets Reveals Unrelated Proteins with High Accuracy Florian Kaiser, Maximilian G. Plach, Christoph Leberecht, Thomas Schubert, V. Joachim Haupt bioRxiv 2020.07.24.219071; doi: https://doi.org/10.1101/2020.07.24.219071.



The structural basis of the genetic code: amino acid recognition by aminoacyl-tRNA synthetases. Kaiser et al (2020)



Application of our Focused Library Service. Kaiser F, et al. (2020) Focus Your Screening Library: Rapid Identification of Novel PDE2 Inhibitors with in silico Driven Library Prioritization and MicroScale Thermophoresis. bioRxiv 2020.04.22.021360; doi: https://doi.org/10.1101/2020.04.22.021360



Drug Repositioning from Infectious Disease (Malaria) to Cancer Chemoresistance. Salentin S, et al. (2017) From malaria to cancer: Computational drug repositioning of amodiaquine using PLIP interaction patterns. Sci Rep. 7:11401



New Drug Candidates for Cancer Chemoresistance. Heinrich JC, et al. (2016) New HSP27 inhibitors efficiently suppress drug resistance development in cancer cells. Oncotarget. 7:68156



New Drug Candidates for Tuberculosis. Štular T, et al. (2016) Discovery of M. tuberculosis InhA inhibitors by binding sites comparison and ligands prediction. J Med Chem. 59:11069-11078



Drug Repositioning from Antiviral to Chagas Disease. Haupt VJ, et al. (2016) Computational Drug Repositioning by Target Hopping: A Use Case in Chagas Disease. Curr Pharm Des. 22:3124



Interaction Patterns for Characterization of Ligand Binding. Salentin S, et al. (2015) PLIP: fully automated protein-ligand interaction profiler. Nucl Acids Res. 43:443



Binding Site Similarity Largely Explains Drug Promiscuity. Haupt VJ, et al. (2013) Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key. PLOS ONE 8:10.1371 (Top 10% most cited in PLOS ONE)