(585f) Optmaven-2.0: A Fast Protocol for de novo Design of Antibody Variable Region Against Aspecific Antigen Epitope

Monoclonal antibodies are the therapeutic agents in a rapidly growing number of medicines for cancers, infectious diseases, and autoimmune disorders. However, laboratory-based methods of developing therapeutic monoclonal antibodies (e.g. immunized mice, hybridomas, and phage display) are time-consuming and cannot target a specific antigen epitope or minimize immunogenicity. To this end, we developed OptMAVEn, the first software for de novo design of fully human monoclonal antibodies targeting a specific antigen epitope. In this work, we introduce OptMAVEn-2.0, which improves upon OptMAVEn by 1) reducing computational resource requirements without compromising design quality, 2) identifying nearly 30% more de novo antibody designs than OptMAVEn, 3) clustering the designs to better identify high-affinity antibodies, 4) eliminating intra-antibody steric clashes using an updated set of clashing parts. Benchmarking on a set of ten antigens revealed that OptMAVEn-2.0 uses an average of 74% less CPU time and 84% less disk storage relative to OptMAVEn. We further tested OptMAVEn-2.0 on 54 additional antigen epitopes which were used to benchmark OptMAVEn to identify that the current protocol allows us to de novo design antibody variable fragments under 24 hours independent of the antigen size. We subsequently used OptMAVEn-2.0 to design 77 antibodies targeting a Zika envelope protein (5gzn) as a test case where nine out of top ten designs were predicted to bind with greater affinity than a native human antibody and has similar immunogenicity scores as the native antibody. 30 ns (with 2fs time step) molecular dynamics simulations on two of these nine designs along with the native antibody corroborate the stability of these designs. OptMAVEn-2.0 can be downloaded at http://www.maranasgroup.com/software.htm.