Sarel Jacob Fleishman

This paper introduces MLEE, a machine learning-assisted enzyme engineering workflow that improves hit rates for high-fitness enzyme variants compared to traditional methods.

The paper designs structurally diverse antibody repertoires with drug-like properties using a computational method called CADAbRe, demonstrating their utility in binding to challenging targets.

This study identifies nanobodies that target Plasmodium adhesins, blocking receptor engagement and inhibiting parasite invasion of red blood cells.

This study compares protein language models (pLMs) with simple baselines in combinatorial protein design, finding no consistent advantage for pLMs in predicting or generating superior variants.

This study identifies structural features of HCV E2 glycoprotein recognized by germline B cell receptors and evaluates strategies to enhance germline antibody interactions.

This study designs stabilized variants of dynamic periplasmic binding proteins by considering mutations compatible with both conformations, improving thermal stability without compromising ligand binding.

This paper introduces LAffAb, a method to co-optimize antibody affinity and stability through combinatorial mutation design, achieving significant affinity gains while maintaining developability.

The paper designs a panel of selective peroxygenases for terpene oxyfunctionalization using computational methods, resulting in improved enzymatic functions and new products.

This paper presents a computational design of high-efficiency Kemp eliminases with unprecedented catalytic efficiency and stability through de novo enzyme design.

GGAssembler designs and synthesizes cost-effective combinatorial mutation libraries for protein engineering using a graph-theoretical approach.

This paper develops a stabilized RH5 VLP vaccine that induces improved anti-malarial antibodies compared to a soluble protein vaccine in preclinical studies.

The paper designs transmembrane domains to control receptor function, showing that oligomeric state affects CAR T cell activity and cytokine release.

The paper studies how two antibodies recognize the glycan antigen CA19-9 using crystallography and computational methods to improve antibody affinity.