In the drug discovery process, accurate methods of computing the affinity of small molecules with a desired biological target are strongly needed. Even if, in the last years, the accuracy and efficiency of the available virtual screening algorithms have been improved, many drawbacks and limitations still exist. For example, docking methods lack a reliable simulation of both ligand and receptor flexibilities, as well as good scoring functions able to estimate ligand binding energies in reasonable agreement with experimental data. These limitations often lead to a high level of false positives or false negatives in the hit list. For that reason, it is generally agreed that docking results need to be post-processed with more accurate tools.To this end, we developed Binding Estimation After Refinement (BEAR), a new and automated post-docking procedure for the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate prediction of binding free energies using MM-PBSA and MM-GBSA1 (Figure1). The BEAR performance in virtual screening was evaluated on several macromolecular targets and related sets of known ligands, determining the enrichment factors and assessing the correlation between predicted and experimental binding affinities. These analyses suggested critical improvements with respect to standard docking softwares2,3. Moreover, when applied in virtual screening campaigns, BEAR was able to discover novel and potent inhibitors of Plasmodium falciparum plasmepsin II with an impressive hit rate 4, and has been successful in identifying promising scaffolds for the design of irreversible protein kinase inhibitors5. Therefore, taken as a whole, the results obtained so far prospect that BEAR may become a prominent tool in the drug discovery pipeline.The BEAR virtual screening procedure is reliable and strongly automated, and can be tailored to the needs of the end-user in terms of computational time and the desired accuracy of the results. BEAR is under constant development and validation on additional biological targets in order to further improve accuracy, automation and calculation speed.

Improving enrichment and hit rate in virtual screening / Rastelli, Giulio; Degliesposti, Gianluca; Parenti, Marco Daniele; C., Portioli. - In: DRUGS OF THE FUTURE. - ISSN 0377-8282. - STAMPA. - 35:(2010), pp. 108-108. (Intervento presentato al convegno XXIst International Symposium on Medicinal Chemistry tenutosi a Brissels nel September 5-9, 2010).

Improving enrichment and hit rate in virtual screening

RASTELLI, Giulio;DEGLIESPOSTI, Gianluca;PARENTI, Marco Daniele;
2010

Abstract

In the drug discovery process, accurate methods of computing the affinity of small molecules with a desired biological target are strongly needed. Even if, in the last years, the accuracy and efficiency of the available virtual screening algorithms have been improved, many drawbacks and limitations still exist. For example, docking methods lack a reliable simulation of both ligand and receptor flexibilities, as well as good scoring functions able to estimate ligand binding energies in reasonable agreement with experimental data. These limitations often lead to a high level of false positives or false negatives in the hit list. For that reason, it is generally agreed that docking results need to be post-processed with more accurate tools.To this end, we developed Binding Estimation After Refinement (BEAR), a new and automated post-docking procedure for the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate prediction of binding free energies using MM-PBSA and MM-GBSA1 (Figure1). The BEAR performance in virtual screening was evaluated on several macromolecular targets and related sets of known ligands, determining the enrichment factors and assessing the correlation between predicted and experimental binding affinities. These analyses suggested critical improvements with respect to standard docking softwares2,3. Moreover, when applied in virtual screening campaigns, BEAR was able to discover novel and potent inhibitors of Plasmodium falciparum plasmepsin II with an impressive hit rate 4, and has been successful in identifying promising scaffolds for the design of irreversible protein kinase inhibitors5. Therefore, taken as a whole, the results obtained so far prospect that BEAR may become a prominent tool in the drug discovery pipeline.The BEAR virtual screening procedure is reliable and strongly automated, and can be tailored to the needs of the end-user in terms of computational time and the desired accuracy of the results. BEAR is under constant development and validation on additional biological targets in order to further improve accuracy, automation and calculation speed.
2010
35
108
108
Rastelli, Giulio; Degliesposti, Gianluca; Parenti, Marco Daniele; C., Portioli
Improving enrichment and hit rate in virtual screening / Rastelli, Giulio; Degliesposti, Gianluca; Parenti, Marco Daniele; C., Portioli. - In: DRUGS OF THE FUTURE. - ISSN 0377-8282. - STAMPA. - 35:(2010), pp. 108-108. (Intervento presentato al convegno XXIst International Symposium on Medicinal Chemistry tenutosi a Brissels nel September 5-9, 2010).
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/645016
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact