Optimization of Benzoisothiazole dioxide inhibitory activity of the NS5B polymerase of HCV genotype 4 using ligand-steered homological modeling, reaction-driven scaffold-hopping and Enovo workflow
Mahmoud, Amr Hamed; Abouzid, Khaled; El Ella, Dalal Abd El Rahman Abou; Hamid Ismail, Mohamed Abdel;
Abstract
Infection caused by hepatitis C virus (HCV) is a significant world health problem for which novel therapies are in urgent demand. The virus is highly prevalent in the Middle East and Africa particularly Egypt with more than 90% of infections due to genotype 4. Nonstructural (NS5B) viral proteins have emerged as an attractive target for HCV antivirals discovery. A potent class of inhibitors having benzisothiazole dioxide scaffold has been identified on this target, however they were mainly active on genotype 1 while exhibiting much lowered activity on other genotypes due to the high degree of mutation of its binding site. Based on this fact, we employed a novel strategy to optimize this class on genotype 4. This strategy depends on using a refined ligand-steered homological model of this genotype to study the mutation binding energies of the binding site amino acid residues, the essential features for interaction and provide a structure-based pharmacophore model that can aid optimization. This model was applied on a focused library which was generated using a reaction-driven scaffold-hopping strategy. The hits retrieved were subjected to Enovo pipeline pilot optimization workflow that employs R-group enumeration, core-constrained protein docking using modified CDOCKER and finally ranking of poses using an accurate molecular mechanics generalized Born with surface area method.
Other data
Title | Optimization of Benzoisothiazole dioxide inhibitory activity of the NS5B polymerase of HCV genotype 4 using ligand-steered homological modeling, reaction-driven scaffold-hopping and Enovo workflow | Authors | Mahmoud, Amr Hamed; Abouzid, Khaled ; El Ella, Dalal Abd El Rahman Abou; Hamid Ismail, Mohamed Abdel | Issue Date | 2011 | Journal | Bioinformation | Volume | 7 | Issue | 7 | Start page | 328 | End page | 333 | ISSN | 09738894 09732063 |
DOI | 10.6026/97320630007328 | PubMed ID | 22355232 |
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