DE NOVO DESIGN THROUGH OPTMAVEN AND CURRENT ADVANCEMENTS IN ITS DESIGN, BENCHMARKED BY THE ZIKA VIRUS

Open Access
Author:
Paulus, Jordan George
Area of Honors:
Chemical Engineering
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
  • Costas Maranas, Thesis Supervisor
  • Themis Matsoukas, Honors Advisor
Keywords:
  • OptMAVEn
  • antibody
  • computational
  • de novo design
  • IPRO
  • MILP
  • OptCDR
  • MAPs
Abstract:
De novo design of antibodies targeting a specific antigen epitope has been a constant challenge as in vivo strategies fail to alleviate this problem, with alternative solutions proving to be either ineffective, controversial, or time consuming. To this end, the Costas Maranas lab has defined a single workflow for not only the de novo design of an antibody but also the subsequent affinity maturation of working antibodies using the Optimal Method for Antibody Variable region Engineering (OptMAVEn), which employs Iterative Protein Redesign and Optimization (IPRO), a core computational module, and a Mixed-Integer Linear Programming (MILP) formulation. Herein, we effectively sift through OptMAVEn generated designs and glean vital stability information about the antigen-antibody complex and rank these designs based on their interaction energies, ultimately streamlining the discovery of potential antibodies by producing potential, affinity-matured antibody designs that can be tested in vitro. Despite OptMAVEn’s current ability to identify potential antibody designs at a high efficiency, multiple aspects of this procedure remain undeveloped and unrefined in their design. Therefore, we have upgraded OptMAVEn to OptMAVEn 2.0 by reducing CPU time and disk storage, improving the selection of germline designs via clustering, installing a user-customizable search space for antigen positioning, integrating OptMAVEn with IPRO for seamless workflow and only relying on open-source softwares. To test the increased functionality of these new additions, OptMAVEn 2.0 was benchmarked with the Zika virus, an infectious disease that had a recent outbreak in North and South America. From this benchmarking, OptMAVEn 2.0 proves to decrease the computational time, provide a more effective and streamlined workflow, and initiate the start of a publicly accessible design process without hindering the quality of the design output.