Joshua E. Goldford

This paper reconstructs the historical emergence of enzymatic folds using metabolic reaction networks, finding that enzyme evolution is embedded in metabolic interdependencies and that β-proteins dominated early metabolism.

This paper introduces Horizyn-1, a deep learning framework for enzyme discovery that improves performance with larger datasets and validates its effectiveness through experimental testing.

The paper models ancient metabolic networks to show purine synthesis was a bottleneck in metabolic evolution, requiring non-autocatalytic phosphoryl agents and leading to coenzyme emergence.

The paper uses metabolic modeling and sequence analysis to show that coenzyme redundancy reduces protein costs and promotes coenzyme specificity in E. coli.

The paper compares the thermodynamic properties of biological and non-biological compounds in redox chemical space, finding metabolites have lower Gibbs energies and specific functional group enrichments.

The paper shows that under certain boundary conditions, early life could have relied on an organo-sulfur metabolism driven by a modified reductive TCA cycle.