PharmAIs 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.
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/10.1101/2020.04.22.021360https://www.biorxiv.org/content/10.1101/2020.04.22.021360v1
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. 7:11401https://www.nature.com/articles/s41598-017-11924-4
New Drug Candidates for Cancer Chemoresistance. Heinrich JC, et al. (2016) New HSP27 inhibitors efficiently suppress drug resistance development in cancer cells. Oncotarget. 7:68156http://www.oncotarget.com/index.php?journal=oncotarget&page=article&op=view&path=11905&pubmed-linkout=1
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. 59:11069-11078https://pubs.acs.org/doi/abs/10.1021/acs.jmedchem.6b01277
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. 22:3124http://www.eurekaselect.com/139787/article
Interaction Patterns for Characterization of Ligand Binding. Salentin S, et al. (2015) PLIP: fully automated protein-ligand interaction profiler. Nucl Acids Res. 43:443https://academic.oup.com/nar/article/43/W1/W443/2467865?searchresult=1
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)https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0065894