Craig L. Dobbins

Endocytosis and lysosomal trafficking of cell surface receptors can be triggered by endogenous ligands. Therapeutic approaches such as lysosome-targeting chimaeras1,2 (LYTACs) and cytokine receptor-targeting chimeras3 (KineTACs) have used this to target specific proteins for degradation by fusing modified native ligands to target binding proteins. Although powerful, these approaches can be limited by competition with native ligands and requirements for chemical modification that limit genetic encodability and can complicate manufacturing, and, more generally, there may be no native ligands that stimulate endocytosis through a given receptor. Here we describe computational design approaches for endocytosis-triggering binding proteins (EndoTags) that overcome these challenges. We present EndoTags for insulin-like growth factor 2 receptor (IGF2R) and asialoglycoprotein receptor (ASGPR), sortilin and transferrin receptors, and show that fusing these tags to soluble or transmembrane target protein binders leads to lysosomal trafficking and target degradation. As these receptors have different tissue distributions, the different EndoTags could enable targeting of degradation to different tissues. EndoTag fusion to a PD-L1 antibody considerably increases efficacy in a mouse tumour model compared to antibody alone. The modularity and genetic encodability of EndoTags enables AND gate control for higher-specificity targeted degradation, and the localized secretion of degraders from engineered cells. By promoting endocytosis, EndoTag fusion increases signalling through an engineered ligand–receptor system by nearly 100-fold. EndoTags have considerable therapeutic potential as targeted degradation inducers, signalling activators for endocytosis-dependent pathways, and cellular uptake inducers for targeted antibody–drug and antibody–RNA conjugates. Computationally designed genetically encoded proteins can be used to target surface proteins, thereby triggering endocytosis and subsequent intracellular degradation, activating signalling or increasing cellular uptake in specific tissues.

Risk is present in all decisions, though often its assessment is skewed to the negative effects. This paper presents material on the sources of risk in agriculture, procedures for managing two types of risks (operational and strategic) and the interaction of time and risk.

Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.

Successful farm business managers must understand the determinants of profitability and have an overall long‐term or strategic management focus. The objective of this research was to explore the use of an e‐learning tool to help producers understand the impacts of different production, pricing, cost control, and investment decisions on their farm’s financial performance. This objective was accomplished by developing and testing a computer‐based training and application tool to facilitate determination of the financial health of farm businesses using the DuPont profitability analysis model. The results of the two experiments indicate that the computer software was effective for teaching techniques of profitability analysis contained within the DuPont model.