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 101–150 of 175 papers

TitleStatusHype
Mimetic Neural Networks: A unified framework for Protein Design and Folding—0
Computational Protein Design with Deep Learning Neural Networks—0
Model-based reinforcement learning for protein backbone design—0
Modular decomposition of protein structure using community detection—0
Computational Protein Design Using AND/OR Branch-and-Bound Search—0
Computational design of target-specific linear peptide binders with TransformerBeta—0
Multi-Attribute Constraint Satisfaction via Language Model Rewriting—0
Controllable Protein Design with Language Models—0
Natural Language Guided Ligand-Binding Protein Design—0
Clusters and Coarse Partitions in LP Relaxations—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
Breaking the Performance Ceiling in Complex Reinforcement Learning requires Inference Strategies—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
Towards deep learning sequence-structure co-generation for protein design—0
PDFBench: A Benchmark for De novo Protein Design from Function—0
Boosting AND/OR-Based Computational Protein Design: Dynamic Heuristics and Generalizable UFO—0
Toward the Explainability of Protein Language Models for Sequence Design—0
Plug-and-Play Controllable Generation for Discrete Masked Models—0
BERT and LLMs-Based avGFP Brightness Prediction and Mutation Design—0
Prediction of amino acid side chain conformation using a deep neural network—0
Pre-training of Graph Neural Network for Modeling Effects of Mutations on Protein-Protein Binding Affinity—0
Training Free Guided Flow Matching with Optimal Control—0
Benchmarking deep generative models for diverse antibody sequence design—0
Backdiff: a diffusion model for generalized transferable protein backmapping—0
Fast uncovering of protein sequence diversity from structure—0
Prot42: a Novel Family of Protein Language Models for Target-aware Protein Binder Generation—0
A Variational Perspective on Generative Protein Fitness Optimization—0
ProtDAT: A Unified Framework for Protein Sequence Design from Any Protein Text Description—0
A Survey of Deep Learning Methods in Protein Bioinformatics and its Impact on Protein Design—0
ProteinBench: A Holistic Evaluation of Protein Foundation Models—0
Protein design by multiobjective optimization: evolutionary and non-evolutionary approaches—0
Protein Design with Dynamic Protein Vocabulary—0
Applying computational protein design to therapeutic antibody discovery -- current state and perspectives—0
ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering—0
UniIF: Unified Molecule Inverse Folding—0
Protein Structure Prediction until CASP15—0
ProteinWeaver: A Divide-and-Assembly Approach for Protein Backbone Design—0
ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning—0
ProtFlow: Fast Protein Sequence Design via Flow Matching on Compressed Protein Language Model Embeddings—0
ProT-GFDM: A Generative Fractional Diffusion Model for Protein Generation—0
ProtTeX: Structure-In-Context Reasoning and Editing of Proteins with Large Language Models—0
Using GANs for De Novo Protein Design Targeting Microglial IL-3Rα to Inhibit Alzheimer's Progression—0
Recent advances in interpretable machine learning using structure-based protein representations—0
Reinforcement Learning for Sequence Design Leveraging Protein Language Models—0
A natural upper bound to the accuracy of predicting protein stability changes upon mutations—0
A Model-Centric Review of Deep Learning for Protein Design—0
Validation of an LLM-based Multi-Agent Framework for Protein Engineering in Dry Lab and Wet Lab—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