Biology subjects

Ghose, D. A.

Publications and source records attributed to Ghose, D. A..

2 recordsLinked to original sources

bioRxiv2026

Seed-Guided De Novo Design Expands the Structural Diversity of Antitoxin Protein Binders

De novo design of protein binders targeting extended, multi-site interaction surfaces remains difficult for current generative methods, which often produce limited structural diversity and predominantly helical topologies. Here, we advance diffusion-based binder design by guiding protein backbone generation through "seeds," which are PDB-derived fragments selected for geometric complementarity to the target surface. To test this approach, we computationally generated seed-guided binders of the bacterial toxin RelE. RelB, the native antitoxin of RelE, engages two distinct interfaces with high surface complementarity, making it an appropriate test case. Seed-guided RFdiffusion produced backbones with substantially higher structural diversity and more target contacts than RFdiffusion alone. Experimental screening of 1,402 designs in a high-throughput bacterial survival assay identified multiple functional binders, including variants with nanomolar to low-micromolar affinity and one design with RelE neutralization comparable to RelBpep. Computational structure prediction and mutational analyses support that the designed interfaces rely on seed-derived contacts and adopt binding modes distinct from RelB. Molecular dynamics simulations and hydrogen-deuterium exchange experiments further suggest that one high-affinity design undergoes a conformational change upon binding. Notably, successful designs exhibited reduced cross-reactivity to RelE orthologs compared with RelBpep, suggesting that the extensive interfaces generated through seed-guided design can enable enhanced selectivity. These results establish motif scaffolding of surface-complementing seeds as an effective strategy for overcoming current limitations of de novo generative models, enabling the design of proteins that can engage challenging interface sites.

bioengineering↗

bioRxiv2023

Marginal specificity in protein interactions constrains evolution

The evolution of novel functions in biology relies heavily on gene duplication and divergence, creating large paralogous protein families. Selective pressure to avoid detrimental cross-talk often results in paralogs that exhibit exquisite specificity for their interaction partners. But how robust or sensitive is this specificity to mutation? Here, using deep mutational scanning, we demonstrate that a paralogous family of bacterial signaling proteins exhibits marginal specificity, such that many individual substitutions give rise to substantial cross-talk between normally insulated pathways. Our results indicate that sequence space is locally crowded despite overall sparseness, and we provide evidence that this crowding has constrained the evolution of bacterial signaling proteins. These findings underscore how evolution selects for good enough rather than optimized phenotypes, leading to restrictions on the subsequent evolvability of paralogs. Significance StatementLarge paralogous protein families are found throughout biology, the product of extensive gene duplication. To execute different functions inside cells, paralogs typically acquire different specificities, interacting with only desired, cognate partners and avoiding cross-talk with non-cognate proteins. But how robust is this interaction specificity to mutation? Can individual mutations lead to cross-talk or do paralogs diverge enough such that multiple mutations would be required, providing a mutational buffer against cross-talk? To address these questions, we built mutant libraries that produce all possible single substitutions of a bacterial kinase and then screened for cross-talk to non-cognate proteins. Strikingly, we find that many single substitutions can produce cross-talk, meaning that these pathways typically exhibit only marginal specificity, and demonstrate that this restricts their evolvability.

evolutionary biology↗