Research graph
References from Squidly harnesses enzyme functional hierarchy and contrastive learning to efficiently predict catalytic residues from sequence. Local targets link to admitted publications; unresolved targets remain external evidence.
Atom-level enzyme active site scaffolding using RFdiffusion2
10.1038/s41592-025-02975-x · 2026 · External reference
Basic local alignment search tool
10.1016/s0022-2836(05)80360-2 · 1990 · External reference
Analysis of catalytic residues in enzyme active sites
10.1016/s0022-2836(02)01036-7 · 2002 · External reference
Chai-1: decoding the molecular interactions of life
10.1101/2024.10.10.615955 · 2024 · External reference
Fast and sensitive protein alignment using DIAMOND
10.1038/nmeth.3176 · 2015 · External reference
How accurate and statistically robust are catalytic site predictions based on closeness centrality?
10.1186/1471-2105-8-153 · 2007 · External reference
Learning a Similarity Metric Discriminatively, with Application to Face Verification
10.1109/cvpr.2005.202 · 2005 · External reference
UniProt: the universal protein knowledgebase in 2023
10.1093/nar/gkac1052 · 2022 · External reference
Automatic methods for predicting functionally important residues
10.1016/s0022-2836(02)01451-1 · 2003 · External reference
ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information
10.1093/bioinformatics/19.1.163 · 2003 · External reference
Neural network ensembles
10.1109/34.58871 · 1990 · External reference
Bilingual Language Model for Protein Sequence and Structure
10.1101/2023.07.23.550085 · 2024 · External reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · 2021 · External reference
Hard negative mixing for contrastive learning
2020 · External reference
Supervised contrastive learning
2020 · External reference
Semantic search using protein large language models detects class II microcins in bacterial genomes
10.1101/2023.11.15.567263 · 2023 · External reference
Simple and scalable predictive uncertainty estimation using deep ensembles
2017 · External reference
Contrastive representation learning: a framework and review
10.1109/access.2020.3031549 · 2020 · External reference
An effective deployment of contrastive learning in multi-label text classification
10.48550/arxiv.2212.00552 · 2022 · External reference
Evolutionary-scale prediction of atomic-level protein structure with a language model
10.1126/science.ade2574 · 2023 · External reference
Determinants and prediction of esterase substrate promiscuity patterns
10.1021/acschembio.7b00996 · 2018 · External reference
Comparison of site-specific rate-inference methods for protein sequences: empirical Bayesian methods are superior
10.1093/molbev/msh194 · 2004 · External reference
Enzyme nomenclature and classification: the state of the art
10.1111/febs.16274 · 2023 · External reference
Leveraging protein language models for accurate multiple sequence alignments
10.1101/gr.277675.123 · 2023 · External reference
CLIPZyme: reaction-conditioned virtual screening of enzymes
10.48550/arxiv.2402.06748 · 2024 · External reference
Squidly
2026 · External reference
SCREEN: a graph-based contrastive learning tool to infer catalytic residues and assess enzyme mutations
10.1093/gpbjnl/qzae094 · 2024 · External reference
Prediction of catalytic residues using support vector machine with selected protein sequence and structural properties
10.1186/1471-2105-7-312 · 2006 · External reference
Catalytic site proximity profiling for functional unification of sequence-diverse radical S -adenosylmethionine enzymes
10.1021/acsbiomedchemau.2c00085 · 2023 · External reference
Transformer protein language models are unsupervised structure learners
10.1101/2020.12.15.422761 · 2020 · External reference
Catalyzing the future: recent advances in chemical synthesis using enzymes
10.1016/j.cbpa.2024.102536 · 2024 · External reference
Mechanism and catalytic site atlas (M-CSA): a database of enzyme reaction mechanisms and active sites
10.1093/nar/gkx1012 · 2018 · External reference
A global analysis of function and conservation of catalytic residues in enzymes
10.1074/jbc.rev119.006289 · 2020 · External reference
A highly sensitive model based on graph neural networks for enzyme key catalytic residue prediction
10.1021/acs.jcim.3c00273 · 2023 · External reference
Fast, scalable generation of high-quality protein multiple sequence alignments using clustal omega
10.1038/msb.2011.75 · 2011 · External reference
PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework
10.1016/j.jtbi.2018.01.023 · 2018 · External reference
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
10.1038/nbt.3988 · 2017 · External reference
Do protein language models learn phylogeny?
10.1093/bib/bbaf047 · 2024 · External reference
Fast and accurate protein structure search with Foldseek
10.1038/s41587-023-01773-0 · 2024 · External reference
BERTology Meets Biology: Interpreting Attention in Protein Language Models
10.1101/2020.06.26.174417 · 2021 · External reference
Protein function annotation with structurally aligned local sites of activity (SALSAs)
10.1186/1471-2105-14-s3-s13 · 2013 · External reference
Protein-small molecule binding site prediction based on a pre-trained protein language model with contrastive learning
10.1186/s13321-024-00920-2 · 2024 · External reference
Multi-modal deep learning enables efficient and accurate annotation of enzymatic active sites
10.1038/s41467-024-51511-6 · 2024 · External reference
CARE: a benchmark suite for the classification and retrieval of enzymes
10.48550/arxiv.2406.15669 · 2025 · External reference
Evaluation of features for catalytic residue prediction in novel folds
10.1110/ps.062523907 · 2007 · External reference
Hot spots-making directed evolution easier
10.1016/j.biotechadv.2022.107926 · 2022 · External reference
Enzyme function prediction using contrastive learning
10.1126/science.adf2465 · 2023 · External reference
Accurate sequence-based prediction of catalytic residues
10.1093/bioinformatics/btn433 · 2008 · External reference
Models and datasets for Squidly
10.5281/zenodo.15541320 · 2025 · External reference
