ComputOrgChem Unisa

Target Identification

Introduction

Inverse Virtual Screening

One of the main challenges in pharmaceutical research is to identify the target(s) of a specific molecule with the purpose of elucidating the mechanism of action or understand side effects that may not be connected to the primary action of the compound. This is particularly important when studying natural products that, sometimes, are available in an amount not sufficient for extended biological tests. To facilitate this procedure, our group developed an innovative approach called Inverse Virtual Screening (more info here and here) that, using an automatic protocol, predicts the binding affinity of a single compound against a panel of selected targets.

2D Target Identification

Our group developed an innovative integrated approach for the identification of specific interactome and main macromolecular targets of a small pool of molecule (either natural or synthetic) to disclose their potential biological effect. The results obtained by Inverse Virtual Screening and chemical proteomics (i.e., DARTS) will be processed using a mathematical model to establish a quantitative affinity parameter, weighted on both methods, to detect the most promising interaction targets in the proteome of a specific cell (e.g., solid tumors) and/or organism (e.g., human, bacteria).

Latest papers:

  • Cassiano, C.; Morretta, E.; Costantini, M.; Fassi, E.M.A.; Colombo, G.; Sattin, S.; Casapullo, A., Analysis of Hsp90 allosteric modulators interactome reveals a potential dual action mode involving mitochondrial MDH2. Bioorg. Chem. 2021, 115, 105258. https://doi.org/10.1016/j.bioorg.2021.105258
  • Chini, M. G.; Lauro, G.; Bifulco, G., Addressing the target identification and accelerating the repositioning of anti-Inflammatory/anti-cancer organic compounds by computational approaches. Eur. J. Org. Chem. 2021, 2021, 2966-2981. https://doi.org/10.1002/ejoc.202100245
  • Potenza, M.; Cavalluzzi, M. M.; Milani, G.; Lauro, G.; Carino, A.; Roselli, R.; Fiorucci, S.; Zampella, A.; Pierri, C. L.; Lentini, G.; Bifulco, G., Inverse Virtual Screening for the rapid re-evaluation of the presumed biological safe profile of natural products. The case of steviol from Stevia rebaudiana glycosides on farnesoid X receptor (FXR). Bioorg. Chem. 2021, 111, 104897. https://doi.org/10.1016/j.bioorg.2021.104897
  • De Vita, S.; Chini, M. G.; Lauro, G.; Bifulco, G., Accelerating the repurposing of FDA-approved drugs against coronavirus disease-19 (COVID-19). RSC Adv. 2020, 10, 40867-40875. https://doi.org/10.1039/d0ra09010g
  • Morretta, E.; Tosco, A.; Monti, M. C.; Casapullo, A., Crellastatin A, a PARP-1 Inhibitor Discovered by Complementary Proteomic Approaches. ChemMedChem, 2020, 15, 317-323. https://doi.org/10.1002/cmdc.201900634
  • De Vita, S.; Lauro, G.; Ruggiero, D.; Terracciano, S.; Riccio, R.; Bifulco, G., Protein Preparation Automatic Protocol for High-Throughput Inverse Virtual Screening: Accelerating the Target Identification by Computational Methods. J. Chem. Inf. Model. 2019, 59, 4678-4690. https://doi.org/10.1021/acs.jcim.9b00428
  • Di Micco, S.; Pulvirenti, L.; Bruno, I.; Terracciano, S.; Russo, A.; Vaccaro, M. C.; Ruggiero, D.; Muccilli, V.; Cardullo, N.; Tringali, C.; Riccio, R.; Bifulco, G., Identification by Inverse Virtual Screening of magnolol-based scaffold as new tankyrase-2 inhibitors. Med. Chem. 2018, 26, 3953-3957. https://doi.org/10.1016/j.bmc.2018.06.019