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Van, M.

Publications and source records attributed to Van, M..

2 recordsLinked to original sources

Computational design of pH-sensitive binders

pH gradients are central to physiology, from vesicle acidification to the acidic tumor microenvironment. While therapeutics have been developed to exploit these pH changes to modulate activity across different physiological environments, current approaches for generating pH-dependent binders, such as combinatorial histidine scanning and display-based selections, are largely empirical and often labor-intensive. Here we describe two complementary principles and associated computational methods for designing pH-dependent binders: (i) introducing histidine residues adjacent to positively charged residues at binder-target interfaces to induce electrostatic repulsion and weaken binding at low pH, and (ii) introducing buried histidine-containing charged hydrogen-bonding networks in the binder core such that the protein is destabilized under acidic conditions. Using these methods, we designed binders that dissociate at acidic pH against ephrin type-A receptor 2, tumor necrosis factor receptor 2, interleukin-6, proprotein convertase subtilisin/kexin type 9, and the interleukin-2 mimic Neo2. Fusions of the designs to pH-independent binders of lysosomal trafficking receptors function as catalytic degraders, inducing target degradation at substoichiometric levels. Our methods should be broadly useful for designing pH-sensitive protein therapeutics.

biochemistry↗

Development of compact transcriptional effectors using high-throughput measurements in diverse contexts

Human nuclear proteins contain >1000 transcriptional effector domains that can activate or repress transcription of target genes. We lack a systematic understanding of which effector domains regulate transcription robustly across genomic, cell-type, and DNA-binding domain (DBD) contexts. Here, we developed dCas9-mediated high-throughput recruitment (HT-recruit), a pooled screening method for quantifying effector function at endogenous targets, and tested effector function for a library containing 5092 nuclear protein Pfam domains across varied contexts. We find many effectors depend on target and DBD contexts, such as HLH domains that can act as either activators or repressors. We then confirm these findings and further map context dependencies of effectors drawn from unannotated protein regions using a larger library containing 114,288 sequences tiling chromatin regulators and transcription factors. To enable efficient perturbations, we select effectors that are potent in diverse contexts, and engineer (1) improved ZNF705 KRAB CRISPRi tools to silence promoters and enhancers, and (2) a compact human activator combination NFZ for better CRISPRa and inducible circuit delivery. Together, this effector-by-context functional map reveals context-dependence across human effectors and guides effector selection for robustly manipulating transcription.

systems biology↗