Our Technology

Three technologies.
One platform.
Enzymes no one else can make.

We combine directed evolution, AI-guided computational design and ancestral sequence reconstruction in EVOSHUFFLER® — covering a search space no single-method platform can reach. From molecular design to industrial-scale production.

20+

peer-reviewed publications

4

IP-field patents

21

funded R&D projects

3

journal covers
EVOshuffler® Directed Evolution AI-guided Design Ancestral Resurrection
Directed
Evolution
AI-guided
Design
Ancestral
Resurrection
EVOshuffler®
Enzymes no one else can make

“The convergence of directed evolution with computational design and ancestral resurrection gives us access to enzyme properties that evolution alone — even with millions of years — would not necessarily produce.

Miguel Alcalde

Co-founder & Scientific Advisor · Professor of Research, CSIC

One of the world’s leading researchers in directed evolution of enzymes — over 20 years pioneering the engineering of fungal oxidoreductases. Author of landmark publications in Nature Chemical Biology, JACS, ACS Catalysis and Applied & Environmental Microbiology.

Professor of Research — CSIC Spain | Nature Chemical Biology 2025 | JACS · ACS Catalysis | 3 Journal Covers | SLAS EU 2023 keynote

01

EVOSHUFFLER®

Directed Evolution Platform

02

AI-guided Design

Computational Intelligence

03

Ancestral Resurrection

Mesozoic enzyme scaffolds

TECHNOLOGY 01

01

EVOSHUFFLER® — Directed Evolution Platform

Our proprietary platform harnesses Saccharomyces cerevisiae as an evolution machine — combining random mutagenesis, in vivo SDR recombination and high-throughput colorimetric screening under precisely controlled selective pressure.

Step 1

Generate genetic diversity

Random mutagenesis + in vivo SDR recombination — creating combinatorial libraries exploring vast sequence spaces simultaneously.

Step 2

Express in S. cerevisiae

Our proprietary yeast system enables secretion, glycosylation and proper folding of complex fungal oxidoreductases that other hosts cannot produce.

Step 3

Screen in high-throughput

Colorimetric HTP assays identify hits under selective pressure matching your exact process — pH, temperature, solvent, substrate specificity.

Step 4

Iterate to target

Selected variants become parents of the next round — iterative cycles converge on the optimal variant with each generation.

S. cerevisiae host

The only host that correctly expresses complex fungal oxidoreductases — UPOs, laccases, VPs, AAOs.

SDR in vivo

In vivo site-directed recombination creates chimeric variants inaccessible to random mutagenesis alone.

HTP colorimetric assays

Thousands of variants assessed per round under real process conditions.

Controlled selective pressure

Thermostability, pH, solvents, substrate specificity — exactly as in your target process.

Published method documentation
Viña-Gonzalez & Alcalde. Methods in Enzymology 643: 1–12 (2020) · Beltran-Nogal et al., Methods in Enzymology 714 (2025)

Iterative evolution cycle

Mutant
Library
HTP
Screen
Select
Winners
Next
Round
→ target
Technology 02

02

AI-guided Computational Design
Smarter libraries. Fewer rounds.

Structure-based AI reduces the experimental search space before a single variant is screened — predicting beneficial mutations and designing focused libraries with a higher hit rate per evolution round.

Structure-guided library design

AlphaFold-informed structural analysis identifies key residues for targeted mutagenesis — smaller libraries, same coverage, higher hit rate.

Distal site prediction

Computational prediction of allosteric mutations at distal sites — positions entirely missed by random mutagenesis that can dramatically improve performance.

Enantiodivergent C-H design

Computational access to both enantiomers from a single enzyme scaffold — enabling stereoselective synthesis at scale without chiral auxiliaries.

Published outcomes

Repertoire of computationally designed peroxygenases for enantiodivergent C–H oxyfunctionalization reactions — combining AI design with directed evolution.

Gomez de Santos et al. · JACS 145(6), 3443–3453 · 2023

Tobacco Etch Virus protease engineered toward a platform for traceless cleavage using distal site prediction and smart library design.

Bemelmans, Mateljak, Alcalde et al. · ACS Synth. Biol. 14(9) · 2025

Stable and promiscuous galactose oxidases engineered by directed evolution, atomistic design and ancestral reconstruction. ACS Synthetic Biology Journal Cover 2025 — Darwin Day Collection.

Keser, Mateljak, Alcalde et al. · ACS Synth. Biol. 14, 239–246 · 2025

Technology 03

03

Ancestral Sequence Reconstruction
A better starting point.

We reconstruct enzyme sequences from the Mesozoic era — resurrecting proteins with superior thermostability, broader substrate scope and higher evolvability as starting scaffolds for directed evolution campaigns.

150M
Mesozoic era

Ancient fungal enzymes

Ancestral fungal oxidoreductases evolved under very different environmental pressures — inherently more thermostable, broadly promiscuous, highly evolvable.

Computational reconstruction

Phylogenetic resurrection

Maximum likelihood inference reconstructs the most probable ancestral sequences from phylogenetic analysis — expressed and characterised in our yeast system.

Today — evolution starting scaffold

Superior baseline for directed evolution

Ancestral scaffolds accumulate beneficial mutations more readily — campaigns starting there reach performance targets faster with broader catalytic access.

Higher thermostability

More thermostable baseline — giving directed evolution more room to further improve stability under harsh process conditions.

Broader substrate promiscuity

Less specialised than modern enzymes — broader scope gives directed evolution more room to reach novel activities and selectivities.

Higher evolvability

Ancestral scaffolds accumulate beneficial mutations more readily — reaching targets in fewer rounds at lower cost.

Journal Cover — Applied & Environmental Microbiology (2020)

Ancestral Resurrection and Directed Evolution of Fungal Mesozoic Laccases

Gómez-Fernández, Risso, Rueda, Sánchez-Ruiz & Alcalde · 86(14), e00078-20

The convergent platform

Why convergence
changes everything.

Each technology solves a different problem. Together they produce enzymes that wouldn’t be possible otherwise — and succeed on projects others have already tried and failed.

EVOSHUFFLER®

Explores where rational design cannot go

Finds unexpected variants through evolutionary pressure — beneficial mutations in unpredictable positions that no computational model would predict.

AI-guided Design

Accelerates convergence, reduces cost

Smarter libraries mean fewer iterations — faster delivery, lower experimental cost, higher hit rate per evolution round.

Ancestral Resurrection

Gives evolution a head start

Ancestral scaffolds are more evolvable — campaigns reach targets faster with properties modern sequences simply cannot match.

A hit rate and catalytic range that single-method platforms cannot match.
This is why 6 of the world’s top 8 pharma companies trust our enzymes — and why we take on projects others have already attempted and abandoned.

Full value chain

From molecular design
to industrial-scale production.

We cover every step — from the first computational design decisions to kg-scale production supervised by our team. No handoffs. The same team throughout.

Phase 1

Molecular design

Ancestral scaffolds + AI library design.

Ancestral + AI
Phase 2

Directed evolution

EVOshuffler® iterative cycles.

EVOshuffler®
Phase 3

Characterisation

Full biochemical characterisation.

In-house
Phase 4

Pilot production

5L & 30L in-house bioreactors.

In-house
Phase 5

Industrial scale

m³ – kg — partner network.

Supervised

Full value chain coverage — from the first sequence design decisions to industrial kg-scale production. No handoffs. No loss of control. The same team from molecule to manufacturing.

Scientific output

20+ publications.
3 journal covers.

Our technology is documented in the field’s most respected journals — not just internal validation.

Protein purification protocols for recombinant enzymes produced in Pichia pastoris

Keser, M. et al. (2025).

Methods in Molecular Biology. 2697: 657-667.

https://doi.org/10.1007/978-1-0716-4779-0_43.

Engineering the Tobacco Etch Virus protease towards a platform for traceless cleavage using distal site prediction and smart library design

Bemelmans, M. P. et al. (2025).

ACS Synthetic Biology. 14(9), 3721–3733.
https://doi.org/10.1021/acssynbio.5c00423.

Characterization of recombinant unspecific peroxygenase from Candolleomyces aberdarensis through crystallographic and substrate selectivity studies

Menes-Rubio, A. et al. (2025).

ChemCatChem. 17, e202402015.
https://doi.org/10.1002/cctc.202402015.

Engineering unspecific peroxygenases by structure-guided in vivo recombination of homologous protein blocks

Beltran-Nogal, A. et al. (2025).

Methods in Enzymology: Biocatalysis. 714.
https://doi.org/10.1016/bs.mie.2025.01.008.

Journal Cover
Stable and promiscuous galactose oxidases engineered by directed evolution, atomistic design, and ancestral sequence reconstruction

Keser, M. et al. (2025).

ACS Synthetic Biology. 14, 1, 239–246. JOURNAL COVER.
https://doi.org/10.1021/acssynbio.4c00653.

Selected by ACS for a Collection celebrating Darwin Day 2025.
https://pubs.acs.org/page/vi/darwin-day-2025.

Enzyme benchmarking with polyethylene furanoate soluble scaffolds for directed evolution of PEFases

Dolz, M. et al. (2024).

ACS Omega. 9, 45, 45633-45640.
https://doi.org/10.1021/acsomega.4c09053.

Journal Cover
Structural Insights and Reaction Profile of a New Unspecific Peroxygenase from Marasmius wettsteinii Produced in a Tandem-Yeast Expression System

Sánchez-Moreno, I. et al. (2024).

ACS Chemical biology, 19(10), 2240–2253. JOURNAL COVER.
https://doi.org/10.1021/acschembio.4c00504.

The colors of peroxygenase activity: Colorimetric high-throughput screening assays for directed evolution

Dolz, M. et al. (2023).

Methods in Enzymology: P450 enzymes. Elsevier. Vol 693: 73-109.
https://doi.org/10.1016/bs.mie.2023.09.006.

Engineering a highly regioselective fungal peroxygenase for the synthesis of hydroxy fatty acids.

Gomez de Santos, P. et al. (2022).

Angewandte Chemie International Edition. e202217372.
https://doi.org/10.1002/anie.202217372.

Surfing the wave of oxyfunctionalization chemistry by engineering fungal unspecific peroxygenases.

Beltran-Nogal, A. et al. (2022).

Current Opinion in Structural Biology 73: 102342.
https://doi.org/10.1016/j.sbi.2022.102342.

Directing the evolution of the fungal ligninolytic secretome.

Viña-Gonzalez, J. et al. (2021).

In: Protein Engineering: Tools and Applications. Wiley-VCH. 295-311.
https://doi.org/10.1002/9783527815128.ch12.

Directed evolution of the unspecific peroxygenase from Agrocybe aegerita in organic solvents.

Martin-Diaz, J. et al. (2021).

Biotechnology & Bioengineering 118: 3002-3014.
https://doi.org/10.1002/bit.27810

Recent developments in the use of peroxygenases – exploring their high potential in selective oxyfunctionalisations.

Hobisch, M. et al. (2021).

Biotechnology Advances 51: 107615. https://doi.org/10.1016/j.biotechadv.2020.107615

Engineering a Highly Thermostable High-Redox Potential Laccase.

Mateljak, I. et al. (2021).

ACS Sustainable Chem. Eng. 9, 29, 9632–9637. https://pubs.acs.org/doi/10.1021/acssuschemeng.1c00622.

Evolved peroxygenase-aryl alcohol oxidase fusions for self-sufficient oxyfunctionalization reactions.

Gómez-Fernández, B.J. et al. (2020).

ACS Catalysis 10: 13524-13534. https://pubs.acs.org/doi/10.1021/acscatal.0c03029

Journal Cover
Ancestral Resurrection and Directed Evolution of Fungal Mesozoic Laccases.

Gómez-Fernández, B.J. et al. (2020).

Applied and Environmental Microbiology 86 (14): e00778-20. JOURNAL COVER. https://aem.asm.org/content/86/14/e00778-20.abstract.

In vivo site-directed recombination (SDR): An efficient tool to reveal beneficial epistasis.

Viña-Gonzalez, J. et al. (2020).

In: Methods in Enzymology 643. Academic Press Elsevier Inc. Pages 1-12. https://doi.org/10.1016/bs.mie.2020.04.021.

Laccase engineering by directed and computational evolution.

Mateljak, I. et al. (2020).

In: Bioremediation and Waste valorization. Springer Nature Switzerland. 191-206. https://link.springer.com/chapter/10.1007/978-3-030-47906-0_8.

Benchmarking of laboratory evolved unspecific peroxygenases for the synthesis of human drug metabolites.

Gomez de Santos, P. et al. (2019).

Tetrahedron 75: 1827-1831. https://doi.org/10.1016/j.tet.2019.02.013.

Want to apply this platform
to your enzyme challenge?

Our technology is available through directed evolution projects, screening kits and catalogue enzymes. Every engagement starts with a conversation.