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 121–130 of 175 papers

TitleStatusHype
Generative AI for Controllable Protein Sequence Design: A Survey—0
Generative Adversarial Model-Based Optimization via Source Critic RegularizationCode0
Learning immune receptor representations with protein language models—0
Enhancing the efficiency of protein language models with minimal wet-lab data through few-shot learning—0
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design—0
PDB-Struct: A Comprehensive Benchmark for Structure-based Protein DesignCode0
AI-predicted protein deformation encodes energy landscape—0
Generative artificial intelligence for de novo protein design—0
DockGame: Cooperative Games for Multimeric Rigid Protein Docking—0
Expected flow networks in stochastic environments and two-player zero-sum gamesCode0
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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