Innovative Computational Approaches in Drug Discovery: Design and Development of Brand New Chemotherapeutic Agents

Abstract

This PhD thesis is mainly focused on the applications of classical and advanced computational techniques to the medicinal chemistry field. Particularly, the wide armoury of known computational methods was here exploited to facilitate the identification and the development of new potential drug candidates. The manuscript is divided into four chapters. The first one describes the classical drug discovery pipeline and the advantages offered by computer-aided approaches. In the second one, a theoretical overview of the methodologies applied in this work is provided. The final chapters (3 and 4) focus on four research projects, divided into two distinct sections, based on the kind of employed methodologies. In detail, in Chapter 3, two studies centred on the ligand binding problem are presented: i) a successful virtual screening campaign targeting the DNA G-Quadruplex structure of the KRAS proto-oncogene promoter, and ii) a mechanistic insight into the binding mechanism of small molecules to FPR2, a GPCR involved in the resolution of the inflammatory process. In Chapter 4, instead, the importance of an accurate conformational sampling for rationalizing the activity/selectivity profile of peptide ligands is highlighted. In the first case study, due to the availability of NMR-derived data, a mixed computational-experimental approach was adopted to investigate the folding and binding properties of a small cyclopeptide, endowed with remarkable antiviral activity against Herpes Simplex Virus 1 (HSV1) infections. On the other hand, in the last project of this thesis, a purely computational approach was employed for studying the binding mechanism of the well-characterized antitumoral nonapeptide iRGD to integrin receptors