In Silico Drug Development
Computational chemistry has an important role to fill in the development of new pharmaceuticals. With today’s high performance computer clusters coupled to the latest developments in algorithms and software, we are able to screen vast libraries of compounds searching for new potential drug candidates, create in silico models of target proteins, and explore protein-protein interactions crucial for e.g. signalling pathways or toxin mechanisms of action. In the current project, we will utilize such tools (virtual high-throughput screening, compound refinement, homology modelling, modelling of protein-protein interactions, and extensive molecular dynamics simulations to explore ligand-protein interactions and effects of blocked protein-protein interactions), to develop new drug candidates in cancer and to identify novel antibiotics. We will study several possible targets for cancer therapy, with the aim to identify or develop small molecule inhibitors: the RET kinase playing a key role in development of thyroid cancers and certain forms of breast cancer; the Kinesin motor proteins Eg5 (KIF11) and KIF18B, where the latter Is believed to play a major role in e.g. glioblastoma; the small peptide AGR2 secreted from the endoplasmic reticulum upon ER stress and where recent results show that this is an inducer of tumorogenesis; the pro-apoptotic complex APAF-1; and proteins IRE1 and HSPC117 (RtcB) that are crucial for cancer cell survival upon ER stress. In antibiotics research, we focus on extracellular (excreted) targets with the aim to thereby reduce the propensity for resistance development of the pathogen, and on blocking one of the main proteins responsible for resistance towards the common beta-lactam ring based antibiotics. The targets include the secreted Leukotoxin LukED of S. aureus which forms octameric complexes that in turn forms pores in host cell walls; the P. aeruginosa virulence factor exotoxin A that binds to and covalently modifies human elongation factor EF2 required for protein synthesis; and the beta-lactam hydrolyzing family of carbapenemase enzymes. We follow a well-established protocol for these studies, involving protein preparation (homology modelling if needed), systematic docking of ZINC clean drug-like library and similar, refined docking of top ranked ligands, and detailed MD simulations of resulting complexes. In addition we have developed an inverse docking protocol to explore selectivity and possible side effects (safety) of obtained compounds. The clean drug-like compound library to be used contains over 13 million compounds, and we are able to conduct a detail screening campaign plus ensuing MD simulations and compound refinements using approximately 1 000 000 coreh for each target; adding up to the total 1 000 000 core/month currently applied for. The research group has previously been highly successful in using in silico methods for drug development, with several patented drugs already developed. From recent years SNIC allocations, new compounds targeting histone methyl transferase Tip60, the extracellular domain of RET kinase and an allosteric pocket of KIF18B have been obtained and proven positive in assays.