Applications of Flow Chemistry Methods and Computer-Aided Approaches to Expedite the Development of HBV Inhibitors

Identifier:  TDX:3205

Handle: https://hdl.handle.net/20.500.11797/TDX3205

Authors:  Raymond, Justine

Abstract:
Hepatitis B is a serious liver infection and the primary cause of liver cancer caused by Hepatitis B Virus (HBV). Even though a prophylactic vaccine is available, Hepatitis B remains as a serious health issue. Currently, FDA-approved antiviral therapies are limited to type 1 interferons and nucleos(t)ide analogues which reduce HBV antigen levels. In recent years, a new class of compounds named capsid assembly modulators (CAMs) have been identified as antiviral agent, showing the potential to efficiently eliminate HBV DNA from infected liver cells. This doctoral thesis objective are the development of novel methodologies, in continuous flow and computationally driven, that will support and accelerate the discovery of new HBV inhibitors within the VIRO-FLOW project. These new processes facilitated the obtention of several building blocks of interest in the development of a new HBV CAMs chemotype. Furthermore, an efficient route for the synthesis of 1,2,4-triazolo-[1,5-a]-pyridine-2-carboxylate in continuous flow has been also developed. The limitations of the reaction were assessed, and an acute mechanistic understanding of the reaction process was afforded by DFT calculations. Moreover diversity-oriented synthetic routes combining batch and flow processes were designed and optimized to obtain a focused library of a new compound series. A structure-activity relationship study was conducted, and two compounds were identified as potential lead. On another hand, a virtual screening workflow combining pharmacophore modelling and molecular docking was created to prioritize the synthesis of new analogues in compound series under development, resulting in new analogues with higher activity than the initial lead. Finally, a combination of molecular dynamics and pharmacophore modelling was used to conduct a large virtual screening (ca. 65 million compounds). The method led to the selection of thirty molecules with excellent antiviral drug-likeness to be further evaluated.