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 51–100 of 175 papers

TitleStatusHype
ProtAgents: Protein discovery via large language model multi-agent collaborations combining physics and machine learningCode1
RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA DesignCode1
MADE: Graph Backdoor Defense with Masked Unlearning—0
MAP Estimation for Graphical Models by Likelihood Maximization—0
MeMDLM: De Novo Membrane Protein Design with Masked Discrete Diffusion Protein Language Models—0
Metropolis Sampling for Constrained Diffusion Models—0
Mimetic Neural Networks: A unified framework for Protein Design and Folding—0
Model-based reinforcement learning for protein backbone design—0
Modular decomposition of protein structure using community detection—0
Multi-Attribute Constraint Satisfaction via Language Model Rewriting—0
Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design—0
Open-Source Protein Language Models for Function Prediction and Protein Design—0
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design—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
PDFBench: A Benchmark for De novo Protein Design from Function—0
Natural Language Guided Ligand-Binding Protein Design—0
AlphaFold Database Debiasing for Robust Inverse Folding—0
Protriever: End-to-End Differentiable Protein Homology Search for Fitness Prediction—0
Advanced Deep Learning Methods for Protein Structure Prediction and Design—0
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design—0
Agentic End-to-End De Novo Protein Design for Tailored Dynamics Using a Language Diffusion Model—0
AI-predicted protein deformation encodes energy landscape—0
A Model-Centric Review of Deep Learning for Protein Design—0
A natural upper bound to the accuracy of predicting protein stability changes upon mutations—0
Applying computational protein design to therapeutic antibody discovery -- current state and perspectives—0
A Survey of Deep Learning Methods in Protein Bioinformatics and its Impact on Protein Design—0
A Variational Perspective on Generative Protein Fitness Optimization—0
Backdiff: a diffusion model for generalized transferable protein backmapping—0
Benchmarking deep generative models for diverse antibody sequence design—0
BERT and LLMs-Based avGFP Brightness Prediction and Mutation Design—0
Boosting AND/OR-Based Computational Protein Design: Dynamic Heuristics and Generalizable UFO—0
Breaking the Performance Ceiling in Complex Reinforcement Learning requires Inference Strategies—0
Clusters and Coarse Partitions in LP Relaxations—0
Computational design of target-specific linear peptide binders with TransformerBeta—0
Computational Protein Design Using AND/OR Branch-and-Bound Search—0
Computational Protein Design with Deep Learning Neural Networks—0
Computational Protein Science in the Era of Large Language Models (LLMs)—0
Conditional Generative Modeling for De Novo Hierarchical Multi-Label Functional Protein Design—0
Deep Generative Modeling for Protein Design—0
De novo design of high-affinity protein binders with AlphaProteo—0
Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning—0
Design in the Dark: Learning Deep Generative Models for De Novo Protein Design—0
Diffusion Models in Bioinformatics: A New Wave of Deep Learning Revolution in Action—0
Diffusion on language model encodings for protein sequence generation—0
DockGame: Cooperative Games for Multimeric Rigid Protein Docking—0
DS-ProGen: A Dual-Structure Deep Language Model for Functional Protein Design—0
Efficient generative modeling of protein sequences using simple autoregressive models—0
EMOCPD: Efficient Attention-based Models for Computational Protein Design Using Amino Acid Microenvironment—0
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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