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

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Showing 1–50 of 175 papers

TitleStatusHype
OpenProteinSet: Training data for structural biology at scaleCode4
Proteina: Scaling Flow-based Protein Structure Generative ModelsCode3
A General Framework for Inference-time Scaling and Steering of Diffusion ModelsCode3
TaxDiff: Taxonomic-Guided Diffusion Model for Protein Sequence GenerationCode3
X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular DesignCode3
Improved motif-scaffolding with SE(3) flow matchingCode3
Robust deep learning based protein sequence design using ProteinMPNNCode3
ReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone GenerationCode2
MotifBench: A standardized protein design benchmark for motif-scaffolding problemsCode2
Concept Bottleneck Language Models For protein designCode2
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein DesignCode2
RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow MatchingCode2
Out of Many, One: Designing and Scaffolding Proteins at the Scale of the Structural Universe with Genie 2Code2
Fast protein backbone generation with SE(3) flow matchingCode2
Hypergraph Isomorphism ComputationCode2
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
Knowledge-Design: Pushing the Limit of Protein Design via Knowledge RefinementCode2
DiffDock-PP: Rigid Protein-Protein Docking with Diffusion ModelsCode2
A Text-guided Protein Design FrameworkCode2
Geometry-Complete Diffusion for 3D Molecule Generation and OptimizationCode2
ProGen2: Exploring the Boundaries of Protein Language ModelsCode2
RITA: a Study on Scaling Up Generative Protein Sequence ModelsCode2
Diffusion Sequence Models for Enhanced Protein Representation and GenerationCode1
Improving large language models with concept-aware fine-tuningCode1
Controllable Protein Sequence Generation with LLM Preference OptimizationCode1
Bridge-IF: Learning Inverse Protein Folding with Markov BridgesCode1
Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic SupervisionCode1
Reinforcement learning on structure-conditioned categorical diffusion for protein inverse foldingCode1
Geometric Trajectory Diffusion ModelsCode1
Metalic: Meta-Learning In-Context with Protein Language ModelsCode1
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein DesignCode1
Learning the Language of Protein StructureCode1
ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learningCode1
Progressive Multi-Modality Learning for Inverse Protein FoldingCode1
Fast non-autoregressive inverse folding with discrete diffusionCode1
De novo protein design using geometric vector field networksCode1
Score-Based Generative Models for Designing Binding Peptide BackbonesCode1
Practical and Asymptotically Exact Conditional Sampling in Diffusion ModelsCode1
Protein Design with Guided Discrete DiffusionCode1
Improving few-shot learning-based protein engineering with evolutionary samplingCode1
Diffusion Models for Constrained DomainsCode1
Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue CloudsCode1
RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA DesignCode1
AlphaFold Distillation for Protein DesignCode1
PiFold: Toward effective and efficient protein inverse foldingCode1
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
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-designCode1
Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein DesignCode1
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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