Maximilian Gantz

Protein ubiquitylation regulates numerous cellular processes, but difficulties in generating site-specifically ubiquitylated proteins limit our understanding of individual modification events. In cells, ubiquitylation is mediated by an E1-E2-E3 enzyme cascade, with substrate recognition largely determined by more than 600 human E3 ligases, making it challenging to redirect ubiquitin transfer to a chosen lysine. Here we use RFdiffusion3 to design ubiquitin ligases from scratch that use a cysteine-based catalytic triad to conjugate an activated ubiquitin donor to a selected lysine in a chosen target substrate. Of 48 tested designs, 35 ubiquitylated a model peptide, with the most active ligases achieving near-quantitative ubiquitin transfer. We next challenged the approach with the homotrimeric sliding clamp proliferating cell nuclear antigen (PCNA), whose ubiquitylation at lysine (K) 164 governs DNA damage tolerance while displaying 45 off-target lysines for ubiquitination. Screening of 48 designs delivered a site-selective ligase. Incorporation of a single activity-increasing substitution and coupling to E1-dependent donor activation resulted in 90% conversion from unactivated ubiquitin, delivering higher rates and superior selectivity compared to a natural promiscuous E2. Using this cascade, we transferred di-, tri- and tetraubiquitin chains of defined length to PCNA K164 through a native isopeptide bond. These results establish de novo enzyme design as a route towards programmable, site-specific protein ubiquitylation. That a single de novo designed protein can bind both an activated ubiquitin donor and a globular target, and use a proficient catalytic machinery to selectively transfer ubiquitin to one lysine among 45, illustrates the level of functional complexity now within reach of de novo enzyme design.

Amide bond formation is of central importance in the chemical industry, underpinning the synthesis of small bioactive molecules, macrocycles, peptides and their conjugates. Conventional methods of amide synthesis rely on stoichiometric coupling agents and costly protecting group manipulations. While biocatalysis can alleviate some of these challenges, enzymes typically operate across a narrow range of substrates and their adaptation to new coupling partners requires extensive engineering. Here we show that de novo amide ligases featuring a cysteine catalytic triad can be programmed computationally to operate across diverse substrate classes with high selectivity. We first designed complementary peptide ligases to selectively functionalise either the N-terminus or a single lysine residue of a polypeptide sequence containing 36 competing lysines. Crystal structures of both ligases show excellent agreement with the designs, with structural modelling suggesting that amidation outcompetes hydrolysis because the catalytically competent geometry forms only upon acceptor binding. We then extended our approach to the synthesis of small bioactive molecules by designing stereoselective ligases that mediate a key amide bonding forming step in the synthesis of the preventative HIV therapeutic lenacapavir. These results establish de novo enzyme design as a programmable platform for achieving selective amide bond formations across a wide range of molecular targets.

RAVE MS utilizes low cost mass spectrometer and autosampler hardware to continuously inject samples for analysis at a sampling rate of approximately 12 s per sample with comparable results to commercial direct inject systems.

The ability of unevolved amino acid sequences to become biological catalysts was key to the emergence of life on Earth. However, billions of years of evolution separate complex modern enzymes from their simpler early ancestors. To probe how unevolved sequences can develop new functions, we use ultrahigh-throughput droplet microfluidics to screen for phosphoesterase activity amidst a library of more than one million sequences based on a de novo designed 4-helix bundle. Characterization of hits revealed that acquisition of function involved a large jump in sequence space enriching for truncations that removed >40% of the protein chain. Biophysical characterization of a catalytically active truncated protein revealed that it dimerizes into an α-helical structure, with the gain of function accompanied by increased structural dynamics. The identified phosphodiesterase is a manganese-dependent metalloenzyme that hydrolyses a range of phosphodiesters. It is most active towards cyclic AMP, with a rate acceleration of ~10⁹ and a catalytic proficiency of >10¹⁴ M⁻¹, comparable to larger enzymes shaped by billions of years of evolution.

Protein design and directed evolution have separately contributed enormously to protein engineering. Without being mutually exclusive, the former relies on computation from first principles, while the latter is a combinatorial approach based on chance. Advances in ultrahigh throughput (uHT) screening, next generation sequencing and machine learning may create alternative routes to engineered proteins, where functional information linked to specific sequences is interpreted and extrapolated in silico. In particular, the miniaturisation of functional tests in water-in-oil emulsion droplets with picoliter volumes and their rapid generation and analysis (>1 kHz) allows screening of >10⁷-membered libraries in a day. Subsequently, decoding the selected clones by short or long-read sequencing methods leads to large sequence-function datasets that may allow extrapolation from experimental directed evolution to further improved mutants beyond the observed hits. In this work, we explore experimental strategies for how to draw up ‘fitness landscapes’ in sequence space with uHT droplet microfluidics, review the current state of AI/ML in enzyme engineering and discuss how uHT datasets may be combined with AI/ML to make meaningful predictions and accelerate biocatalyst engineering.

The ability of unevolved amino acid sequences to become biological catalysts was key to the emergence of life on Earth. However, billions of years of evolution separate complex modern enzymes from their simpler early ancestors. To study how unevolved sequences can develop new functions, we screened for enzymatic activity in a collection of > 1 million novel sequences based on a de novo 4-helix bundle library of semi-random sequences. To mirror evolutionary selection for biological function, we screened the collection using ultrahigh-throughput droplet microfluidics to identify features that yield phosphoesterase activity. Characterization of active hits demonstrated that acquiring new function required a large jump in sequence space: screening enriched for truncations that removed > 40% of the protein chain and introduced a catalytically important cysteine. The truncated protein dimerized into a dynamic α-helical structure, consistent with the idea that gain of function was accompanied by an increase in structural dynamics relative to the parental 4-helix bundle. The purified protein catalyzes the hydrolysis of a range of phosphodiesters, with the greatest activity toward the biological second messenger cyclic AMP (cAMP). The novel cAMPase is a manganese-dependent metalloenzyme and catalyzes cAMP hydrolysis with a rate acceleration on the order of 10 ⁹ and catalytic proficiency on the order of 10 ¹⁴ M ⁻¹ , comparable to large enzymes shaped by billions of years of evolution. These findings suggest that fragmentation to modular primordial peptides can be a fertile avenue for introducing structural and functional diversity into proteins. GRAPHICAL