Enzyme engineering

Ultra-fast sequence search and clustering. 10,000x faster than BLAST for database searches, with powerful sequence clustering capabilities for proteins and nucleotides.

Sensitive sequence homology search using profile hidden Markov models. More accurate than BLAST for detecting remote homologs, ideal for finding evolutionarily distant protein family members.

Perform multiple sequence alignment using MAFFT (Multiple Alignment using Fast Fourier Transform). Supports multiple algorithms from fast progressive to highly accurate iterative methods.

Statistical Coupling Analysis for protein families. Identifies co-evolving residue groups (sectors) from multiple sequence alignments using the SCA method from the Ranganathan Lab.

Calculate sequence-derived protein properties including molecular weight, theoretical pI, extinction coefficients, aromaticity, secondary structure fractions, composition classes, instability, aliphatic index, and GRAVY.

Boltz-2 is a biomolecular foundation model for structure and binding affinity prediction. Supports proteins, ligands, DNA, and RNA in multi-component complexes. Automatically scales GPU resources for large complexes. Predicts binding affinity with near-FEP accuracy at 1000x faster speed.

PDBFixer is an OpenMM-based tool used for fixing problems in protein/DNA/RNA structure files, including adding missing atoms, adding missing residues, and fixing improper formatting.

Open-source protein pocket detection using Voronoi tessellation and alpha spheres. Identifies ligand binding sites with druggability scores.

Predict pKa values of ionizable groups in proteins and protein-ligand complexes from 3D structure. PROPKA calculates environment-driven pKa shifts for standard ionizable residues, terminal groups, and supported ligand atom types.

Geometric deep learning model for predicting protein binding sites directly from 3D structure. Identifies where proteins interact with other proteins, antibodies, or disordered proteins with high accuracy, including for novel protein folds.

DLKcat predicts enzyme turnover numbers (kcat values) from protein sequences and substrate structures using its published deep-learning model.

Official CleaveNet tool for matrix metalloproteinase cleavage prediction and peptide generation. Predict cleavage z-scores plus uncertainty across 18 MMP variants, evaluate against truth z-scores, or generate candidate peptides unconditionally or from MMP z-score profiles.

Predict protease and chemical cleavage sites across a protein sequence for up to 39 enzymes simultaneously. Identify where each enzyme cuts, the cleavage residue, and context window around each site.

GNINA is a molecular docking tool that combines traditional physics-based docking with deep learning CNN scoring for protein-small-molecule complexes. It provides accurate binding predictions with confidence scores, optimized for high-throughput virtual screening.

RFdiffusion2 is an atom-level enzyme active site scaffolding tool that generates protein scaffolds around your input motif. REQUIRES an input PDB structure containing the active site residues to scaffold. For ligand-aware design, ligands must be embedded in the input PDB as HETATM records.

Design and score protein sequences with ligand, metal, nucleotide, and fixed-side-chain context, with optional native side-chain packing.

Design and score protein sequences for fixed backbone structures with source-native ProteinMPNN checkpoints, constraints, symmetry, and optional side-chain packing.

Predict protein thermostability changes (ΔΔG) for point mutations using a graph neural network. Enables computational saturation mutagenesis screening to identify stabilizing mutations.

Calculate sequence-derived indicators related to protein stability, including the Guruprasad instability index, aliphatic index, GRAVY, aromaticity, estimated net charge, and charged-residue fraction.

Predict protein solubility and usability for E. coli expression using ESM protein language models

Validate protein structure quality with all-atom contact analysis, Ramachandran plots, rotamer assessment, and geometry checks.