01 / PlatformReaction-aware design engine
[ 2026 ]live

Designed by working biologists

127 reviewed candidate sets delivered to partner R&D teams last quarter.

REACTION-AWARE AI · ENZYME DESIGN

Designenzymes
atthespeedof compute.

Zymos runs iterative, reaction-aware design cycles to generate, score, and rank protein candidates against your molecular targets — delivering a structured technical package, not a black-box answer.

100+
Design cycles / target
5
Integrated capabilities
8.2M
Candidates scored
REACTION-AWARE MODELSITERATIVE SCREENINGRANKED CANDIDATE PACKAGESSTRUCTURAL INDICATORSBIOPROCESSINGBIOCATALYSISPARTNER R&DREACTION-AWARE MODELSITERATIVE SCREENINGRANKED CANDIDATE PACKAGESSTRUCTURAL INDICATORSBIOPROCESSINGBIOCATALYSISPARTNER R&D
02 / Capabilities

Fiveintegratedcapabilities,
onecontinuousloop.

The platform's approach to AI-driven candidate exploration — not a service catalogue, not a results-guarantee, a research and development technology.

01GEN-LOOP

Reaction-aware generation

Iterative AI generation of enzyme and protein candidates within defined target and reaction constraints.

FILTER
02FILTER

Multi-pass screening

Automated screening filters large candidate sets to higher-confidence molecules across successive passes.

ENCODE
03ENCODE

Reaction encoding

Target reaction, substrate profile, and functional constraints become design parameters for the engine.

RANK
04RANK

Iterative ranking

Candidates are scored against multiple computational metrics, with weaker candidates eliminated each cycle.

PACKAGE
05PACKAGE

Structured technical output

Ranked candidates, scores, structural indicators and interpretation notes — built for downstream R&D decisions.

Collaboration

Built for partner R&D collaboration.

Internal product development, licensing, and partner research projects — the platform fits where you already work.

03 / The Loop

Fromtarget,
to rankedcandidatepackage.

S.01

Target intake

Reaction, substrate profile and functional constraints are encoded as design parameters for the engine.

S.02

Iterative generation

The platform executes 100+ candidate-generation cycles using reaction-aware models, producing diverse structural families per cycle.

S.03

Multi-pass screening

Candidates are scored and filtered across computational metrics; weaker candidates fall off across successive iterations.

S.04

Structured handoff

A ranked technical package — candidates, scores, structural indicators, and interpretation notes — informs downstream research.

NOTE

Biological activity, expression, and functional performance must be confirmed experimentally.

Read methodology
04 / Platform

Aworkbench, not ablackbox.

Every ranked candidate carries its scores, structural indicators, and interpretation notes — auditable end-to-end.

RUNCSTM-2026-Q1-0427 / cycle 087
CONVERGING
Candidate
Score
ΔG (kcal)
Sim
Family
ZX-08842
0.971
-42.3
0.18
α/β-hydrolase
ZX-08731
0.964
-41.7
0.22
α/β-hydrolase
ZX-08406
0.952
-39.1
0.31
TIM-barrel
ZX-08217
0.948
-38.4
0.27
Rossmann
ZX-08009
0.937
-37.0
0.42
α/β-hydrolase
ZX-07884
0.921
-35.8
0.36
TIM-barrel
ZX-07710
0.914
-34.9
0.51
GST-like
filter:score ≥ 0.90ΔG ≤ -34sim < 0.60+2 more
PREVIEWZX-08842
α/β-hydrolaseL=312 aaconf 0.971
Active site
S–H–D triad
Substrate
Ester / C8–C16
Topology
8-stranded β-sheet
05 / Domains

Exploratorydomains whereenzymesmatter.

These represent areas where computational enzyme and protein design may have scientific or industrial relevance — not confirmed deployment areas.

Bioprocessing

DOM.01

Computational exploration of enzyme candidates relevant to bioprocessing research programs.

Biosynthesis

DOM.02

Candidate generation against defined synthesis targets and substrate profiles.

Biocatalysis

DOM.03

Reaction-aware models scored against catalytic constraints and reaction conditions.

Protein engineering

DOM.04

Family-level structural exploration for stability, selectivity and binding studies.

NOW ACCEPTING Q2 / 2026 COLLABORATIONS

Bringusatarget.
We'll explorethecandidatespace.

Tell us about your reaction, your substrate profile, and the constraints you care about. We'll respond with a scoped collaboration proposal.