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
Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic SupervisionCode1
Diffusion Sequence Models for Enhanced Protein Representation and GenerationCode1
Generative Adversarial Model-Based Optimization via Source Critic RegularizationCode0
Beyond Human-Like Processing: Large Language Models Perform Equivalently on Forward and Backward Scientific TextCode0
Building Confidence in Deep Generative Protein DesignCode0
CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language ModelsCode0
Conditioning by adaptive sampling for robust designCode0
Expanding functional protein sequence space using generative adversarial networksCode0
Expected flow networks in stochastic environments and two-player zero-sum gamesCode0
Fast and Flexible Protein Design Using Deep Graph Neural NetworksCode0
Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure PredictionCode0
Gate-based Quantum Computing for Protein DesignCode0
Generative Models for Graph-Based Protein DesignCode0
mGPfusion: Predicting protein stability changes with Gaussian process kernel learning and data fusionCode0
Multi-Objective Quality-Diversity in Unstructured and Unbounded SpacesCode0
PDB-Struct: A Comprehensive Benchmark for Structure-based Protein DesignCode0
Persistent Sheaf Laplacian Analysis of Protein FlexibilityCode0
ProDCoNN-server: a web server for protein sequence prediction and design from a three-dimensional structureCode0
Robust Model-Based Optimization for Challenging Fitness LandscapesCode0
Protein Sequence Design with Batch Bayesian OptimisationCode0
PSBench: a large-scale benchmark for estimating the accuracy of protein complex structural modelsCode0
Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and ReviewCode0
Scalable Coupling of Deep Learning with Logical ReasoningCode0
Scoring-Assisted Generative Exploration for Proteins (SAGE-Prot): A Framework for Multi-Objective Protein Optimization via Iterative Sequence Generation and EvaluationCode0
Variational auto-encoding of protein sequencesCode0
Efficient generative modeling of protein sequences using simple autoregressive models—0
DS-ProGen: A Dual-Structure Deep Language Model for Functional Protein Design—0
Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces—0
DockGame: Cooperative Games for Multimeric Rigid Protein Docking—0
Ideal gas behavior of rotamerically defined conformers in native globular proteins—0
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient—0
Diffusion on language model encodings for protein sequence generation—0
Diffusion Models in Bioinformatics: A New Wave of Deep Learning Revolution in Action—0
Design in the Dark: Learning Deep Generative Models for De Novo Protein Design—0
Improving Protein Sequence Design through Designability Preference Optimization—0
Iterative Importance Fine-tuning of Diffusion Models—0
Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning—0
De novo design of high-affinity protein binders with AlphaProteo—0
Lattice protein design using Bayesian learning—0
Deep Generative Modeling for Protein Design—0
Learning immune receptor representations with protein language models—0
Conditional Generative Modeling for De Novo Hierarchical Multi-Label Functional Protein Design—0
Leveraging Deep Generative Model For Computational Protein Design And Optimization—0
CCPL: Cross-modal Contrastive Protein Learning—0
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
Computational Protein Science in the Era of Large Language Models (LLMs)—0
Metropolis Sampling for Constrained Diffusion Models—0
The Dance of Atoms-De Novo Protein Design with Diffusion Model—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