S4: Using computations to drive novel enzyme and antibody design

We demonstrate a general computational workflow that can create enzymatic activity for a non-natural substrate. First, quantum mechanical calculations will be employed to converge on the ground and transition states of the rate-limiting step in each system. Next, IPRO will be used to find the optimal rotamer/residue combination in predefined design positions that minimize the interaction energy with the reactant/product ground state structures. These candidate designs are next screened with QM/MM calculations for their efficacy on improving binding energy (better binding), lowering the activation barrier (better catalyst), and allowing for product molecule release (product off-rate). We highlight results and compare with experimental kcat and km values for the dihydrofolate reductase enzyme.

OptCDR is a general computational method to design the binding portions of antibodies to have high specificity and affinity against any targeted epitope of an antigen.  First, combinations of canonical structures for the antibody complementarity determining regions (CDRs) that are most likely to be able to favorably bind the antigen are selected.  This is followed by the simultaneous refinement of the CDR structures’ backbones and optimal amino acid selection for each position.  OptCDR is applied to three computational test cases: a peptide from the capsid of hepatitis C, the hapten fluorescein, and the protein vascular endothelial growth factor.  The results demonstrate that OptCDR can efficiently generate diverse antibody libraries of a pre-specified size with promising antigen affinity potential as exemplified by computationally derived binding metrics.