Jason Donald

WORK HISTORY

EDUCATION

SKILLS

ABOUT JASON DONALD

My focus is computational enzyme engineering and AI-assisted protein design. I have more than a decade of experience developing models, design workflows, and analytics systems that support both industrial biotechnology and therapeutic enzyme programs. My expertise centers on integrating structure-based modeling, AI/machine learning, sequence analysis, and pathway engineering to guide enzyme optimization and accelerate experimental workflows.Across 14 years in industry, I have contributed deep technical work and structured leadership. My background includes computational and wet-lab protein engineering, therapeutic enzyme development (including recombinase optimization), metabolic engineering, data and informatics system development, and cross-functional integration with NGS, mammalian cell culture, bacterial fermentation, analytical chemistry, and molecular biology teams. I have developed modeling platforms, guided enzyme design programs, and mentored computational scientists advancing tools in protein modeling, E. coli selection assays, AI/ML, and biocatalyst and recombinase optimization.Interests and areas of work:• Computational enzyme engineering (structure prediction, stability design, substrate specificity, AI/ML-driven sequence design)• Protein structural bioinformatics• Integration of metabolic modeling with enzyme and pathway design• Development of analytics pipelines and LIS/data systems supporting R&D• Mentoring technical staff and shaping modeling and engineering standardsI enjoy discerning key insights from complex datasets, maintaining deep technical focus, and designing systems that support excellent experimental science. My aim is to build tools and frameworks that enable R&D teams to deliver practical, high-quality outcomes in industrial and therapeutic biotechnology.