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 61–70 of 175 papers

TitleStatusHype
Fast and Accurate Antibody Sequence Design via Structure Retrieval—0
From thermodynamics to protein design: Diffusion models for biomolecule generation towards autonomous protein engineering—0
Applying computational protein design to therapeutic antibody discovery -- current state and perspectives—0
Clusters and Coarse Partitions in LP Relaxations—0
Geometric deep learning assists protein engineering. Opportunities and Challenges—0
Enhancing the efficiency of protein language models with minimal wet-lab data through few-shot learning—0
A natural upper bound to the accuracy of predicting protein stability changes upon mutations—0
EMOCPD: Efficient Attention-based Models for Computational Protein Design Using Amino Acid Microenvironment—0
Efficient generative modeling of protein sequences using simple autoregressive models—0
Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction—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