Persistent HIV infection requires lifelong treatment and among the 2.1 million new HIV infections that occur every year there is an increased rate of transmitted drug-resistant mutations. This fact requires a constant and timely effort in order to identify and develop new HIV inhibitors with innovative mechanisms. The HIV-1 reverse transcriptase (RT) associated ribonuclease H (RNase H) is the only viral encoded enzyme that still lacks an efficient inhibitor despite the fact that it is a well-validated target whose functional abrogation compromises viral infectivity. Identification of new drugs is a long and expensive process that can be speeded up by in silico methods. In the present study, a structure-guided screening is coupled with a similarity-based search on the Specs database to identify a new class of HIV-1 RNase H inhibitors. Out of the 45 compounds selected for experimental testing, 15 inhibited the RNase H function below 100 μM with three hits exhibiting IC50 values <10 μM. The most active compound, AA, inhibits HIV-1 RNase H with an IC50 of 5.1 μM and exhibits a Mg-independent mode of inhibition. Site-directed mutagenesis studies provide valuable insight into the binding mode of newly identified compounds; for instance, compound AA involves extensive interactions with a lipophilic pocket formed by Ala502, Lys503, and Trp (406, 426 and 535) and polar interactions with Arg557 and the highly conserved RNase H primer-grip residue Asn474. The structural insights obtained from this work provide the bases for further lead optimization.

Structure-guided approach identifies a novel class of HIV-1 Ribonuclease H inhibitors: Binding mode insights through magnesium complexation and site-directed mutagenesis studies

Angela Corona
Co-primo
;
Nicole Grandi;Francesca Esposito;Enzo Tramontano
Penultimo
;
2018-01-01

Abstract

Persistent HIV infection requires lifelong treatment and among the 2.1 million new HIV infections that occur every year there is an increased rate of transmitted drug-resistant mutations. This fact requires a constant and timely effort in order to identify and develop new HIV inhibitors with innovative mechanisms. The HIV-1 reverse transcriptase (RT) associated ribonuclease H (RNase H) is the only viral encoded enzyme that still lacks an efficient inhibitor despite the fact that it is a well-validated target whose functional abrogation compromises viral infectivity. Identification of new drugs is a long and expensive process that can be speeded up by in silico methods. In the present study, a structure-guided screening is coupled with a similarity-based search on the Specs database to identify a new class of HIV-1 RNase H inhibitors. Out of the 45 compounds selected for experimental testing, 15 inhibited the RNase H function below 100 μM with three hits exhibiting IC50 values <10 μM. The most active compound, AA, inhibits HIV-1 RNase H with an IC50 of 5.1 μM and exhibits a Mg-independent mode of inhibition. Site-directed mutagenesis studies provide valuable insight into the binding mode of newly identified compounds; for instance, compound AA involves extensive interactions with a lipophilic pocket formed by Ala502, Lys503, and Trp (406, 426 and 535) and polar interactions with Arg557 and the highly conserved RNase H primer-grip residue Asn474. The structural insights obtained from this work provide the bases for further lead optimization.
2018
HIV-1; RNase H; In silico screening; Magnesium complexation; Mutagenesis; Allosteric inhibition
File in questo prodotto:
File Dimensione Formato  
2018 Poongavanam:Corona.pdf

Solo gestori archivio

Descrizione: Post-print
Tipologia: versione pre-print
Dimensione 2.85 MB
Formato Adobe PDF
2.85 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

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/11584/240624
Citazioni
  • ???jsp.display-item.citation.pmc??? 10
  • Scopus 17
  • ???jsp.display-item.citation.isi??? 17
social impact