In this work, we present and discuss a comprehensive set of both newly and previously synthesized compounds belonging to 5 distinct molecular classes of linear aromatic N-polycyclic systems that efficiently inhibits bovine viral diarrhea virus (BVDV) infection. A coupled in silico/in vitro investigation was employed to formulate a molecular rationale explaining the notable affinity of all molecules to BVDV RNA dependent RNA polymerase (RdRp) NS5B. We initially developed a three-dimensional common-feature pharmacophore model according to which two hydrogen bond acceptors and one hydrophobic aromatic feature are shared by all molecular series in binding the viral polymerase. The pharmacophoric information was used to retrieve a putative binding site on the surface of the BVDV RdRp and to guide compound docking within the protein binding site. The affinity of all compounds towards the enzyme was scored via molecular dynamics-based simulations, showing high correlation with in vitro EC50 data. The determination of the interaction spectra of the protein residues involved in inhibitor binding highlighted amino acids R295 and Y674 as the two fundamental H-bond donors, while two hydrophobic cavities HC1 (residues A221, I261, I287, and Y289) and HC2 (residues V216, Y303, V306, K307, P408, and A412) fulfill the third pharmacophoric requirement. Three RdRp (K263, R295 and Y674) residues critical for drug binding were selected and mutagenized, both in silico and in vitro, into alanine, and the affinity of a set of selected compounds towards the mutant RdRp isoforms was determined accordingly. The agreement between predicted and experimental data confirmed the proposed common molecular rationale shared by molecules characterized by different chemical scaffolds in binding to the BVDV RdRp, ultimately yielding compound 6b (EC50 = 0.3 μM; IC50 = 0.48 μM) as a new, potent inhibitor of this Pestivirus.
A combined in silico/in vitro approach unveils common molecular requirements for efficient BVDV RdRp binding of linear aromatic N-polycyclic systems
La Colla, P;Collu, G;Delogu, I;Loddo, RUltimo
2016-01-01
Abstract
In this work, we present and discuss a comprehensive set of both newly and previously synthesized compounds belonging to 5 distinct molecular classes of linear aromatic N-polycyclic systems that efficiently inhibits bovine viral diarrhea virus (BVDV) infection. A coupled in silico/in vitro investigation was employed to formulate a molecular rationale explaining the notable affinity of all molecules to BVDV RNA dependent RNA polymerase (RdRp) NS5B. We initially developed a three-dimensional common-feature pharmacophore model according to which two hydrogen bond acceptors and one hydrophobic aromatic feature are shared by all molecular series in binding the viral polymerase. The pharmacophoric information was used to retrieve a putative binding site on the surface of the BVDV RdRp and to guide compound docking within the protein binding site. The affinity of all compounds towards the enzyme was scored via molecular dynamics-based simulations, showing high correlation with in vitro EC50 data. The determination of the interaction spectra of the protein residues involved in inhibitor binding highlighted amino acids R295 and Y674 as the two fundamental H-bond donors, while two hydrophobic cavities HC1 (residues A221, I261, I287, and Y289) and HC2 (residues V216, Y303, V306, K307, P408, and A412) fulfill the third pharmacophoric requirement. Three RdRp (K263, R295 and Y674) residues critical for drug binding were selected and mutagenized, both in silico and in vitro, into alanine, and the affinity of a set of selected compounds towards the mutant RdRp isoforms was determined accordingly. The agreement between predicted and experimental data confirmed the proposed common molecular rationale shared by molecules characterized by different chemical scaffolds in binding to the BVDV RdRp, ultimately yielding compound 6b (EC50 = 0.3 μM; IC50 = 0.48 μM) as a new, potent inhibitor of this Pestivirus.File | Dimensione | Formato | |
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Carta 321-334 (2016).pdf
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