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Computational methods applied to the discovery of stem cell factor ligands

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Abstract

A computational study of the stem cell factor (SCF) and potential ligands was carried out starting with a crystallographic model deposited in the protein data bank. The inhibition of the SCF dimerization equilibrium was considered as the rationale for the lead identification of specific ligands. A preliminary molecular dynamics characterization of the SCF dimer allowed to verify the most flexible loop involved in the dimeric area. Then a virtual screening, coupled with energy minimization in GB/SA water, scored the compounds implemented in the NCI diversity molecular database. Ten top ranked ligands were analyzed considering both the SCF loop perturbation in the dimerization area and the network of intermolecular hydrogen bonds. Among these ten compounds two natural agents were identified. The computational work revealed useful new insights for rational design of novel SCF dimerization inhibitors.

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Authors and Affiliations

  1. Laboratorio di Chimica Farmaceutica Computazionale, Dipartimento di Scienze Farmacobiologiche, Università degli Studi “Magna Græcia” di Catanzaro, Edificio delle Bioscienze, Viale Europa, 88100, Catanzaro, Italy

    Stefano Alcaro & Francesco Ortuso

  2. Consorzio per le Applicazioni di Supercalcolo Per Università e Ricerca (CASPUR), Via dei Tizii, 6, 00185, Rome, Italy

    Lorenzo Gontrani

  3. OpenShell s.a.s. Via Papa Giovanni XXIII, 60, 67039, Sulmona (AQ), Italy

    Ottaviano Incani

Authors
  1. Stefano Alcaro
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  2. Lorenzo Gontrani
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  3. Ottaviano Incani
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  4. Francesco Ortuso
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Correspondence to Stefano Alcaro.

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Contribution to the Nino Russo Special Issue.

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Alcaro, S., Gontrani, L., Incani, O. et al. Computational methods applied to the discovery of stem cell factor ligands. Theor Chem Account 120, 523–531 (2008). https://doi.org/10.1007/s00214-008-0431-x

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  • DOI: https://doi.org/10.1007/s00214-008-0431-x

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