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 131–140 of 175 papers

TitleStatusHype
SurfPro: Functional Protein Design Based on Continuous Surface—0
TERMinator: A Neural Framework for Structure-Based Protein Design using Tertiary Repeating Motifs—0
The Dance of Atoms-De Novo Protein Design with Diffusion Model—0
Controllable Protein Design with Language Models—0
Towards deep learning sequence-structure co-generation for protein design—0
Toward the Explainability of Protein Language Models for Sequence Design—0
Training Free Guided Flow Matching with Optimal Control—0
Fast uncovering of protein sequence diversity from structure—0
UniIF: Unified Molecule Inverse Folding—0
Using GANs for De Novo Protein Design Targeting Microglial IL-3Rα to Inhibit Alzheimer's Progression—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