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| 100 | 1 | _ | |a Guaitoli, Valentina |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a A computational strategy to understand structure-activity relationship of 1,3-disubstituted imidazole [1,5-α] pyrazine derivatives described as ATP competitive inhibitors of the IGF-1 receptor related to Ewing sarcoma |
| 260 | _ | _ | |a Heidelberg |c 2020 |b Springer |
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| 500 | _ | _ | |a Unfortunately, the authors do not have a copy of the submitted version anymore |
| 520 | _ | _ | |a We followed a comprehensive computational strategy to understand and eventually predict the structure-activity relationship ofthirty-three 1,3-disubstituted imidazole [1,5-α] pyrazine derivatives described as ATP competitive inhibitors of the IGF-1receptor related to Ewing sarcoma. The quantitative structure-activity relationship model showed that the inhibitory potency iscorrelated with the molar volume, a steric descriptor and the net charge calculated value on atom C1 (q1) and N4 (q4) of thepharmacophore, all of them appearing to give a positive contribution to the inhibitory activity. According to experimental andcalculated values, the most potent compoundwould be 3-[4-(azetidin-2-ylmethyl) cyclohexyl]-1-[3-(benzyloxy) phenyl] imidazo[1,5-α]pyrazin-8-amine (compound 23). Docking was used to guess important residues involved in the ATP-competitive inhibitoryactivity. It was validated by 200 ns of molecular dynamics (MD) simulation using improved linear interaction energy (LIE)method. MD of previously preferred structures by docking shows that the most potent ligand could establish hydrogen bondswith the ATP-binding site of the receptor, and the Ser979 and Ser1059 residues contribute favourably to the binding stability ofcompound 23.MDsimulation also gave arguments about the chemical structure of the compound 23 being able to fit in the ATPbindingpocket, expecting to remain stable into it during the entire simulation and allowing us to hint the significant contributionexpected to be given by electrostatic and hydrophobic interactions to the ligand-receptor complex stability. This computationalcombined strategy here described could represent a useful and effective prime approach to guide the identification of tyrosinekinase inhibitors as new lead compounds. |
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| 700 | 1 | _ | |a Alvarez-Ginarte, Yoanna María |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Montero-Cabrera, Luis Alberto |0 P:(DE-HGF)0 |b 2 |e Corresponding author |
| 700 | 1 | _ | |a Bencomo-Martínez, Alberto |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Badel, Yoana Pérez |0 P:(DE-HGF)0 |b 4 |
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| 773 | _ | _ | |a 10.1007/s00894-020-04470-w |g Vol. 26, no. 8, p. 222 |0 PERI:(DE-600)1284729-x |n 8 |p 222 |t Journal of molecular modeling |v 26 |y 2020 |x 0948-5023 |
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