ComputOrgChem Unisa

Target Identification


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:

De Vita S.; Chini M.G.; Bifulco G.; Lauro G.; “Target identification by structure-based computational approaches: Recent advances and perspectives”, Bioorg. Med. Chem. Lett.2023, 83, 129171.

De Vita S.; Finamore C.; Chini M.G.; Saviano G.; De Felice V.; De Marino S.; Lauro G.; Casapullo A.; Fantasma F.; Trombetta F.; Bifulco G.; Iorizzi M.; “Phytochemical analysis of the methanolic extract and essential oil from leaves of industrial hemp Futura 75 Cultivar: Isolation of a new cannabinoid derivative and biological profile using computational approaches.”, Plants2022, 11, 1671.

Gazzillo E.; Terracciano S.; Ruggiero D.; Potenza M.; Chini M.G.; Lauro G., Fischer K.; Hofstetter R.K.; Giordano A.; Werz O.; Bruno I.; Bifulco G.; “Repositioning of quinazolinedione-based compounds on soluble epoxide hydrolase (sEH) through 3D structure-based pharmacophore model-driven Iinvestigation.”, Molecules2022, 27, 3866.

Molecules 27 03866 g001 550
Biomolecules 12 00099 g004 550

Saviano A.; De Vita S.; Chini M.G.; Marigliano N.; Lauro G.; Casillo G.M.; Raucci F.; Iorizzi M.; Hofstetter R.K.; Fischer K.; Koeberle A.; Werz O.; Maione F.; Bifulco G.; “In silicoin vitro, and in vivo analysis of tanshinone IIA and cryptotanshinone from Salvia miltiorrhiza as modulators of cyclooxygenase-2/mPGES-1/endothelial prostaglandin EP3 pathway.”, Biomolecules2022, 12, 99.

De Vita S.; Chini M.G.; Saviano G.; Finamore C., Festa C.; Lauro G.; De Marino S.; Russo R.; Avagliano C.; Casapullo A.; Calignano A.; Bifulco G.; Iorizzi M.; “Biological profile of two Gentiana lutea l. metabolites using computational approaches and in vitro tests.”, Biomolecules2021, 11, 1490.

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. 2021115, 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.

Description unavailable

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.

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.