Protein Design
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Benchmarks
Most implemented
X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular Design
ProGen2: Exploring the Boundaries of Protein Language Models
RITA: a Study on Scaling Up Generative Protein Sequence Models
TaxDiff: Taxonomic-Guided Diffusion Model for Protein Sequence Generation
A Text-guided Protein Design Framework
Geometry-Complete Diffusion for 3D Molecule Generation and Optimization
Papers
Protein Structure Prediction: From Evolutionary Constraints to Generative Modeling
Accurate protein structure prediction is fundamental to structural biology because protein structure underlies molecular function and provides a basis for mechanistic interpretation. Recent advances in deep learning have…
Protein Structure PredictionMultiple Sequence AlignmentProtein DesignChamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling
The rapid evolution of generative models has unlocked new potentials in protein binder design, a pivotal task in structural biology, by facilitating end-to-end generation via joint sequence-structure modeling or hallucin…
Protein DesignSciForge: An AI-Native, Multimodal Workbench for Scientific Discovery
Scientific work increasingly spans heterogeneous artifacts -- papers, code, datasets, scientific file formats, model outputs, figures, manuscripts, and team decisions -- yet general-purpose AI assistants rarely preserve …
Protein DesignVariable-Length Generative Protein Design via Generalized Poisson Flow
The ability to generate variable-length proteins is crucial in protein design, where the optimal length is often unknown and tightly coupled to designability. Current diffusion- and flow-based generative models typically…
Protein DesignDesign-CP: Context Parallelism for Design of Protein Nanoparticles
Many all-atom generative protein models can in principle design large multimeric complexes by jointly modelling all chains, but their quadratic token- and atom-pair representations quickly exceed single-GPU memory as the…
Protein DesignDiffeomorphic Optimization
Generative models learn data distributions that reside on a low-dimensional manifold within a higher-dimensional ambient space. Optimizing differentiable objectives on this manifold is challenging: the ambient loss lands…
Protein Design