Enzyme design
Build protein scaffolds around catalytic geometry, redesign ligand-aware sequences, and connect computation to biochemical testing.
More protein design workflows
Tools for enzyme design
Use these methods to prepare inputs, run the core analysis, inspect outputs, and validate the evidence described in this workflow.
RFdiffusion 2
Generate active-site scaffolds with atomic context
RFdiffusion3
Generate enzyme-oriented all-atom backbones
LigandMPNN
Assign ligand-aware protein sequences
ProteinMPNN
Assign alternative scaffold sequences
EvoPro
Optimize sequence and structure objectives
ESMFold
Refold designed sequences for structural comparison
fpocket
Inspect designed pocket geometry
PROPKA 3
Estimate structure-dependent ionization context
MolProbity
Review clashes and stereochemical geometry
Protein stability prediction
Estimate sequence-level stability signals
NetSolP-1.0
Estimate sequence-level solubility
SASA calculator
Measure solvent-accessible surface area
What is enzyme design?
Enzyme design is the process of creating or modifying proteins to catalyze a specified chemical transformation. Computational workflows represent catalytic residues, transition-state or substrate geometry, cofactors, and surrounding structural constraints, then generate scaffolds and sequences intended to support that arrangement. Success requires more than a folded model: catalytic rate, selectivity, stability, and the proposed reaction mechanism must be measured experimentally.
De novo enzyme design starts from reaction geometry rather than from an existing enzyme sequence. Other projects redesign a natural scaffold while preserving catalytic residues. In either case, ligand and cofactor coordinates must remain chemically meaningful throughout motif scaffolding and ligand-aware sequence design.
The computational funnel should reject candidates that distort catalytic geometry, bury unsatisfied polar atoms, clash with substrates, or fail to refold. Laboratory assays then distinguish true catalysis from background reaction, nonspecific binding, contamination, or an unintended mechanism.
When to use enzyme design
Enzyme design needs an explicit reaction and active-site geometry:
- A catalytic motif must be placed in a new protein scaffold.
- A ligand or cofactor should influence sequence choice around a pocket.
- You can assay reaction rate and relevant background controls.
Strengths and limitations
Atomic motif constraints let scaffold generation preserve proposed catalytic geometry instead of optimizing overall fold alone. Ligand-aware sequence design can use the positioned substrate, metal or cofactor context, and refolding checks whether candidate sequences still support the intended scaffold.
Correct motif placement is only one requirement for catalysis. Protonation, solvent access, dynamics and transition-state stabilization may remain wrong even in a well folded design. A model score cannot establish rate enhancement or substrate selectivity; those claims need quantitative assays and controls.
Enzyme design methods
Motif-scaffolding methods place catalytic atoms within generated protein geometry. The motif is only as meaningful as its chemical model, so protonation, cofactors, substrate pose, and geometric tolerances should be documented.
Ligand-aware sequence design assigns residues around both the backbone and non-protein atoms. It can preserve a pocket context but cannot prove that the designed electrostatics, dynamics, or reaction pathway will produce catalysis.
Applications of enzyme design
Active-site scaffolding can place catalytic residues around a substrate or cofactor when no natural enzyme presents the desired geometry. That structural proposal can guide a focused set of variants for biochemical testing.
Ligand-aware sequence redesign may tune the surrounding pocket while keeping key motif atoms fixed. Compare designed structures against the intended reaction geometry, but judge catalysis by measured product formation and kinetic controls rather than by pocket appearance.
How to run enzyme design online
The featured workflow uses an atomic motif PDB as the design constraint. Check non-protein atoms before generation because the next model uses their positions directly.
- Define the chemistry. Specify the proposed reaction, catalytic atoms, substrate or cofactor and the assay that will distinguish catalysis from background.
- Prepare the motif. Supply a PDB whose catalytic residues and positioned non-protein atoms have correct names, bonds and coordinates.
- Generate scaffolds. Run RFdiffusion 2 around the atomic motif and reject candidates that distort the required geometry.
- Assign sequences. Pass accepted scaffold PDBs with positioned ligand or cofactor context to LigandMPNN; it designs sequence, not ligand placement.
- Refold and inspect. Use ESMFold on designed sequences and compare the predicted pocket with the motif and generated scaffold.
- Test catalysis. Keep unsuccessful designs and measure rate, background and selectivity under controlled reaction conditions.
How to interpret enzyme design results
Inspect motif RMSD, catalytic distances and angles, pocket accessibility, clashes, sequence confidence, refold agreement, and alternate ligand poses. Keep native enzyme and no-enzyme controls when available.
Experimental evaluation should report expression, folding, turnover, catalytic efficiency, substrate scope, and selectivity. Controls must rule out spontaneous reaction and adventitious catalysis.
Experimental validation and handoff
Preserve motif atoms, ligand/cofactor coordinates, geometric constraints, sequence-design settings, and rejected candidates. Validate activity with quantitative assays and controls.
Preserve the input motif, scaffold coordinates and ligand context for each candidate. Report reaction rates with negative controls so background chemistry is not attributed to a designed active site.
How enzyme design works
Generate scaffolds around an active-site motif with RFdiffusion 2, assign ligand-aware sequences with LigandMPNN, and refold with ESMFold.
- Define reaction. Specify the chemical transformation, catalytic residues, ligand or transition-state model, and assay controls.
- Encode active site. Prepare a motif PDB whose atom names, bonds, cofactors, and HETATM context are correct.
- Generate scaffolds. Generate scaffolds that preserve the required active-site geometry and reject distorted motifs.
- Design sequences. Assign ligand-aware sequences, refold candidates, and inspect pockets, clashes, and stability.
- Test catalysis. Express selected designs and measure rate, background, selectivity, and mechanism-relevant controls.
Inputs and outputs
Check formats before running, then inspect and download the result from every workflow step.
Inputs
Design input
PDBFASTAJSONTXTAn active-site motif PDB with catalytic residues and ligand or cofactor HETATM records.
Outputs
Design and review outputs
PDBFASTACSVJSONScaffold PDB files, ligand-aware FASTA sequences, refolded models, design scores, and validation files.
Frequently asked questions
Use chemically consistent coordinates, atom names, residue identities, bonds, and protonation assumptions supported by the selected method. Preserve these records in the motif PDB and document any restraints or surrogate atoms.
You can use it as a hypothesis, but pose uncertainty becomes active-site uncertainty. Compare plausible poses and protonation states, and avoid optimizing an entire campaign around one unvalidated orientation.
Include no-enzyme, inactive-design, denatured-protein, and buffer controls where appropriate, plus a concentration series and time course. Controls should also address contaminating enzymes or cofactors relevant to the expression and purification system.
Not automatically. Reproducible activity above controls can provide a useful starting point for focused redesign or directed evolution, especially when the structure and proposed mechanism remain plausible.
End-to-end enzyme-engineering programs are quote-based rather than sold as a published fixed package. Johnson Matthey’s service covers computational optimization, enzyme-library design, library creation, screening of thousands of variants under process-like conditions, and iterative engineering, but requires the reaction and performance scope before quoting.
Cost is driven by assay development, substrate and cofactor handling, library size, screening throughput, number of engineering rounds, expression and purification, analytical chemistry, and whether process-scale performance is part of the deliverable.
ProteinIQ self-service starts at $29 per month for academic Plus and $99 per month for commercial Pro, with the configured run quoted in credits before submission. A done-for-you enzyme design project is scoped separately; synthesis, expression, and experimental assays are included only when the project quote explicitly says so.
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