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Exploring the RNA-Recognition Mechanism Using Supervised Molecular Dynamics (SuMD) Simulations: Toward a Rational Design for Ribonucleic-Targeting Molecules?
Bissaro, Maicol; Sturlese, Mattia; Moro, Stefano.
Afiliación
  • Bissaro M; Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padua, Italy.
  • Sturlese M; Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padua, Italy.
  • Moro S; Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padua, Italy.
Front Chem ; 8: 107, 2020.
Article en En | MEDLINE | ID: mdl-32175307
ABSTRACT
Although proteins have represented the molecular target of choice in the development of new drug candidates, the pharmaceutical importance of ribonucleic acids has gradually been growing. The increasing availability of structural information has brought to light the existence of peculiar three-dimensional RNA arrangements, which can, contrary to initial expectations, be recognized and selectively modulated through small chemical entities or peptides. The application of classical computational methodologies, such as molecular docking, for the rational development of RNA-binding candidates is, however, complicated by the peculiarities characterizing these macromolecules, such as the marked conformational flexibility, the singular charges distribution, and the relevant role of solvent molecules. In this work, we have thus validated and extended the applicability domain of SuMD, an all-atoms molecular dynamics protocol that allows to accelerate the sampling of molecular recognition events on a nanosecond timescale, to ribonucleotide targets of pharmaceutical interest. In particular, we have proven the methodological ability by reproducing the binding mode of viral or prokaryotic ribonucleic complexes, as well as that of artificially engineered aptamers, with an impressive degree of accuracy.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Front Chem Año: 2020 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Front Chem Año: 2020 Tipo del documento: Article País de afiliación: Italia