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 111–120 of 175 papers

TitleStatusHype
Open-Source Protein Language Models for Function Prediction and Protein Design—0
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design—0
Breaking the Performance Ceiling in Complex Reinforcement Learning requires Inference Strategies—0
Pan-protein Design Learning Enables Task-adaptive Generalization for Low-resource Enzyme Design—0
What Do LLMs Need to Understand Graphs: A Survey of Parametric Representation of Graphs—0
PDBench: Evaluating Computational Methods for Protein Sequence Design—0
Towards deep learning sequence-structure co-generation for protein design—0
PDFBench: A Benchmark for De novo Protein Design from Function—0
Boosting AND/OR-Based Computational Protein Design: Dynamic Heuristics and Generalizable UFO—0
Toward the Explainability of Protein Language Models for Sequence Design—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