Aptamers represent a challenging field of research, relevant for diagnosis in macular degeneration, cancer, thrombosis and many inflammatory diseases, and promising in drug discovery and development. Their selection is currently performed by a stable in vitro technology, namely, SELEX. Furthermore, computationalstatistical tools have been developed to complement the SELEX selection; they work both in the preliminary stage of selection, by designing high affinity aptamers for the assigned target, and also in the final stage, analyzing the features of the best performers to implement the selection technique further. A massive use of the in silico approach is, at present, only restricted by the limited knowledge of the specific aptamer-target topology. Actually, only about fifty X-ray structures of aptamer-protein complexes have been experimentally resolved, highlighting how this knowledge has to be improved. The structure of biomolecules like aptamer-protein complexes can be represented by networks, from which several parameters can be extracted. This work briefly reviews the literature, discussing if and how general network parameters in the framework of Proteotronics and graph theory (such as electrical features, link number, free energy change, and assortativity), are important in characterizing the complexes, anticipating some features of the biomolecules. To better explain this topic, a case-study is proposed, constituted by a set of anti-angiopoietin (Ang2) aptamers, whose performances are known from the experiments, and for which two different types of conformers were predicted. A topological indicator is proposed, named Möbius (M), which combines local and global information, and seems able to discriminate between the two possible types of conformers, so that it can be considered as a useful complement to the in vitro screening for pharmaceutical aims.

Aptamers Which Target Proteins: What Proteotronics Suggests to Pharmaceutics

Cataldo R.;De Nunzio G.
;
Alfinito E.
2020-01-01

Abstract

Aptamers represent a challenging field of research, relevant for diagnosis in macular degeneration, cancer, thrombosis and many inflammatory diseases, and promising in drug discovery and development. Their selection is currently performed by a stable in vitro technology, namely, SELEX. Furthermore, computationalstatistical tools have been developed to complement the SELEX selection; they work both in the preliminary stage of selection, by designing high affinity aptamers for the assigned target, and also in the final stage, analyzing the features of the best performers to implement the selection technique further. A massive use of the in silico approach is, at present, only restricted by the limited knowledge of the specific aptamer-target topology. Actually, only about fifty X-ray structures of aptamer-protein complexes have been experimentally resolved, highlighting how this knowledge has to be improved. The structure of biomolecules like aptamer-protein complexes can be represented by networks, from which several parameters can be extracted. This work briefly reviews the literature, discussing if and how general network parameters in the framework of Proteotronics and graph theory (such as electrical features, link number, free energy change, and assortativity), are important in characterizing the complexes, anticipating some features of the biomolecules. To better explain this topic, a case-study is proposed, constituted by a set of anti-angiopoietin (Ang2) aptamers, whose performances are known from the experiments, and for which two different types of conformers were predicted. A topological indicator is proposed, named Möbius (M), which combines local and global information, and seems able to discriminate between the two possible types of conformers, so that it can be considered as a useful complement to the in vitro screening for pharmaceutical aims.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/438238
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 5
social impact