Quantum computational simulation of immuno-oncological drugs
Abstract
Much of the recent excitement in the cancer immunotherapy approach has been generated by the recognition that immune checkpoint proteins, like the receptors PD-1 (Programmed cell Death-Ligand 1) and CTLA-4 (Cytotoxic T-Lymphocyte-Associated Protein 4), can be blocked by antibody-based drugs, with deeper effects. Promising clinical data have already been released, pointing out to the efficiency of the monoclonal antibody immune-oncological drugs pembrolizumab (PEM), nivolumab (NIV), and ipilimumab (IPI) to block these immune checkpoint proteins pathway, triggering the T-lymphocytes against a wide range of cancers, as well as being an important issue for clinical research. Their use was already approved by the US-FDA (United States-Food and Drug Administration) office since the last decade. To date, although many structural properties of these drugs have been unveiled, binding energy features of both checkpoint proteins, PD-1 and CTLA-4, based on crystallographic X-Ray data, need a deeper understanding. In this context, by employing quantum chemistry methods based on the Density Functional Theory (DFT) and the molecular fractionation with conjugate caps (MFCC) scheme, we investigate in silico the binding energy features of the receptors PD-1 and CTLA-4 in complex with their drugs inhibitor (PEM, NIV, and IPI), highlighting the most relevant residue-residue interactions, looking for new insights into the mechanisms of the pathway blockade to further engineer their affinity and…
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