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 31–40 of 175 papers

TitleStatusHype
Persistent Sheaf Laplacian Analysis of Protein FlexibilityCode0
Fast and Accurate Antibody Sequence Design via Structure Retrieval—0
Steering Protein Family Design through Profile Bayesian Flow—0
Iterative Importance Fine-tuning of Diffusion Models—0
A Variational Perspective on Generative Protein Fitness Optimization—0
Controllable Protein Sequence Generation with LLM Preference OptimizationCode1
Computational Protein Science in the Era of Large Language Models (LLMs)—0
Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and ReviewCode0
A General Framework for Inference-time Scaling and Steering of Diffusion ModelsCode3
From thermodynamics to protein design: Diffusion models for biomolecule generation towards autonomous protein engineering—0
Show:102550
← PrevPage 4 of 18Next →
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