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 91–100 of 175 papers

TitleStatusHype
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
ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learningCode1
Improved motif-scaffolding with SE(3) flow matchingCode3
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design—0
Progressive Multi-Modality Learning for Inverse Protein FoldingCode1
Fast non-autoregressive inverse folding with discrete diffusionCode1
PDB-Struct: A Comprehensive Benchmark for Structure-based Protein DesignCode0
AI-predicted protein deformation encodes energy landscape—0
De novo protein design using geometric vector field networksCode1
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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