Repository logo

Computer-Aided Design of Ligands at Multiple Protein Targets for Multifactorial Diseases



Change log


Kalash, Leen 


Today, drug discovery predominately focuses on the design of ligands with high selectivity towards a specific biological target. A significant limitation in the case of multi-factorial diseases (e.g. neurodegenerative disorders) is that effective therapy may require multi-target drugs addressing the complexity of multi-factorial pathologies. Here, single- and multi-target ligand design was investigated to discover novel compounds active at multiple proteins/multiple binding sites including allosteric ligands. Calpain-1, a challenging target, was selected to develop and evaluate computational approaches to the discovery of novel ligands. Current selective calpain-1 inhibitors are reported to bind to an allosteric site and their mode of action has remained elusive. To elucidate this, a structure-based virtual screening protocol was implemented to find chemically novel compounds with improved selectivity and a reduced side-effects profile. To develop methods for the discovery of multi-target ligands, a multi-target design approach, which could be beneficial in the treatment of Lung Carcinoma and Neurodegenerative diseases, was investigated. A novel ensemble of proteins was targeted to elevate intracellular cAMP, deemed to be beneficial in these diseases resulting in the discovery of ligands with high binding affinity at three targets, PDE10A, A1 and A2A receptors. In tandem, functional activity at the A2A receptor and PDE10A was investigated, resulting in the discovery of novel compounds, which exhibited anti-proliferative effects in lung carcinoma cell-lines correlating with the co-expression of the two targets and increased cAMP levels. Critically, the dynamics of one amino acid residue, Val84, was identified as a novel conformational descriptor of A2A receptor activation. Overall, novel single- and multi-target ligand design approaches are presented in this work, which could be applicable to a wide range of ligand design problems, across (multi-factorial) disease areas and target families. The findings may facilitate improved design of allosteric calpain-1 inhibitors using the PEF(S) domain, and encourage investigating the therapeutic benefits of dual ligands at the A2A receptor and PDE10A against lung cancer in vivo.





Bender, Andreas


Structure-based design, Ligand-based design, MD simulations, docking, multi-target ligands, allosteric inhibitors, multifactorial diseases, lung cancer


Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge
IDB Cambridge International Scholarship and ERC Starting Grant (No. 336159)