SOTAVerified

Protein Design

Formally, given the design requirements of users, models are required to generate protein amino acid sequences that align with those requirements.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–110 of 175 papers

TitleStatusHype
Mimetic Neural Networks: A unified framework for Protein Design and Folding—0
Computational Protein Design with Deep Learning Neural Networks—0
Model-based reinforcement learning for protein backbone design—0
Modular decomposition of protein structure using community detection—0
Computational Protein Design Using AND/OR Branch-and-Bound Search—0
Computational design of target-specific linear peptide binders with TransformerBeta—0
Multi-Attribute Constraint Satisfaction via Language Model Rewriting—0
Controllable Protein Design with Language Models—0
Natural Language Guided Ligand-Binding Protein Design—0
Clusters and Coarse Partitions in LP Relaxations—0
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All datasetsCATH 4.2CATH 4.3

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GraphTransPerplexity6.63—Unverified
2StructGNNPerplexity6.4—Unverified
3AlphaDesignPerplexity6.3—Unverified
4GCAPerplexity6.05—Unverified
5GVPPerplexity5.36—Unverified
6ProteinMPNNPerplexity4.61—Unverified
7PiFoldPerplexity4.55—Unverified
8Knowledge-DesignPerplexity3.46—Unverified
#ModelMetricClaimedVerifiedStatus
1ESM-IFPerplexity6.44—Unverified
2GVP-largePerplexity6.17—Unverified