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

Showing 131140 of 175 papers

TitleStatusHype
Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure PredictionCode0
ProGen2: Exploring the Boundaries of Protein Language ModelsCode2
Robust deep learning based protein sequence design using ProteinMPNNCode3
RITA: a Study on Scaling Up Generative Protein Sequence ModelsCode2
TERMinator: A Neural Framework for Structure-Based Protein Design using Tertiary Repeating Motifs0
Generative De Novo Protein Design with Global ContextCode1
Generative power of a protein language model trained on multiple sequence alignmentsCode1
AlphaDesign: A graph protein design method and benchmark on AlphaFoldDBCode1
Gate-based Quantum Computing for Protein DesignCode0
Controllable Protein Design with Language Models0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GraphTransPerplexity6.63Unverified
2StructGNNPerplexity6.4Unverified
3AlphaDesignPerplexity6.3Unverified
4GCAPerplexity6.05Unverified
5GVPPerplexity5.36Unverified
6ProteinMPNNPerplexity4.61Unverified
7PiFoldPerplexity4.55Unverified
8Knowledge-DesignPerplexity3.46Unverified
#ModelMetricClaimedVerifiedStatus
1ESM-IFPerplexity6.44Unverified
2GVP-largePerplexity6.17Unverified