Design and optimization of K-Ras protein inhibitors as anticancer agents using deltarasin as a case study

Abstract

K-Ras serves as an important component of signalling pathways involved in cell cycle control. Proper functioning K-Ras is regulated by phosphodiesterase δ (PDEδ). Deltarasin binds to this prenyl-binding protein thus inhibiting its interaction with K-Ras and hence disrupting Ras signalling. The objective of this study is to use Deltarasin as a template for further iteration of the design of novel drugs with potential clinical use in the management of malignancies. Deltarasin was constructed using SYBYL-X ® V1.2, followed by analysis of the critical interactions with the amino acids lining the Ligand Binding Pocket (LBP). Seeds were modelled based on the Deltarasin scaffold and Virtual Screening (VS) was used to identify ‘hits’, using the same molecule as a template. SYBYL-X ®, X-SCORE® , LigBuilder® , Visual Molecular Dynamics (VMD), Accelrys® Draw, Accelrys® Discovery Studio v3.5, Protein Data Bank and ZINCPharmer® were all used to generate results. The main outcome measures of this research project are to discover and optimise in silico high binding affinity of PDEδ inhibitory drug molecules, as well as molecule display, Ligand Binding Affinity (LBA) and Ligand Binding Energy (LBE) calculations, seed generation and ultimately de novo design. Based on reviewed SAR studies, nine seeds were generated using SYBYL-X ® V1.2. The POCKET and GROW algorithm of LigBuilder® V1.2 were used to generate in silico molecules for each seed. Surflexdocking in SYBYL-X ® V1.2 resulted in five molecules with a total docking score of six or greater. De novo molecules created and optimized, present viable leads for high-throughput screening, leading to identification of novel PDEδ inhibitors for use as anti-cancer agents.