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 71–80 of 175 papers

TitleStatusHype
Prot42: a Novel Family of Protein Language Models for Target-aware Protein Binder Generation—0
Multi-Objective Quality-Diversity in Unstructured and Unbounded SpacesCode0
Advanced Deep Learning Methods for Protein Structure Prediction and Design—0
ProtTeX: Structure-In-Context Reasoning and Editing of Proteins with Large Language Models—0
Applying computational protein design to therapeutic antibody discovery -- current state and perspectives—0
A Model-Centric Review of Deep Learning for Protein Design—0
Agentic End-to-End De Novo Protein Design for Tailored Dynamics Using a Language Diffusion Model—0
Persistent Sheaf Laplacian Analysis of Protein FlexibilityCode0
Steering Protein Family Design through Profile Bayesian Flow—0
Fast and Accurate Antibody Sequence Design via Structure Retrieval—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