Papers Protein Folding
“Protein Folding” 태그가 달린 논문 185편 · 필터 해제
MegaFold: System-Level Optimizations for Accelerating Protein Structure Prediction Models
Protein structure prediction models such as AlphaFold3 (AF3) push the frontier of biomolecular modeling by incorporating science-informed architectural changes to the transformer architecture. However, these advances com…
GPUProtein FoldingProtein Structure PredictionRetrievalCentral Dogma Cycle and Network: A Model for Cell Memory
This paper proposes an extension of the traditional Central Dogma of molecular biology to a more dynamic model termed the Central Dogma Cycle (CDC) and a broader network called the Central Dogma Cyclic Network (CDCN). Wh…
Protein FoldingProbably Approximately Correct Labels
Obtaining high-quality labeled datasets is often costly, requiring either extensive human annotation or expensive experiments. We propose a method that supplements such "expert" labels with AI predictions from pre-traine…
Protein Foldingtext annotationProtein Inverse Folding From Structure Feedback
The inverse folding problem, aiming to design amino acid sequences that fold into desired three-dimensional structures, is pivotal for various biotechnological applications. Here, we introduce a novel approach leveraging…
Protein FoldingProtein folding classes -- High-dimensional geometry of amino acid composition space revisited
In this study, the distributions of protein structure classes (or folding types) of experimentally determined structures from a legacy dataset and a comprehensive database SCOP are modeled precisely with geometric constr…
DescriptiveProtein FoldingP: A Universal Measure of Predictive Intelligence
Over the last thirty years, considerable progress has been made with the development of systems that can drive cars, play games, predict protein folding and generate natural language. These systems are described as intel…
Protein FoldingSimultaneous Modeling of Protein Conformation and Dynamics via Autoregression
Understanding protein dynamics is critical for elucidating their biological functions. The increasing availability of molecular dynamics (MD) data enables the training of deep generative models to efficiently explore the…
Protein FoldingPredicting protein folding dynamics using sequence information
Natural protein sequences somehow encode the structural forms that these molecules adopt. Recent developments in structure-prediction are agnostic to the mechanisms by which proteins fold and represent them as static obj…
Protein FoldingDS-ProGen: A Dual-Structure Deep Language Model for Functional Protein Design
Inverse Protein Folding (IPF) is a critical subtask in the field of protein design, aiming to engineer amino acid sequences capable of folding correctly into a specified three-dimensional (3D) conformation. Although subs…
Language ModelingLanguage ModellingProtein DesignProtein FoldingLightNobel: Improving Sequence Length Limitation in Protein Structure Prediction Model via Adaptive Activation Quantization
Recent advances in Protein Structure Prediction Models (PPMs), such as AlphaFold2 and ESMFold, have revolutionized computational biology by achieving unprecedented accuracy in predicting three-dimensional protein folding…
Protein FoldingProtein Structure PredictionQuantizationHallucination, reliability, and the role of generative AI in science
Generative AI is increasingly used in scientific domains, from protein folding to climate modeling. But these models produce distinctive errors known as hallucinations - outputs that are incorrect yet superficially plaus…
HallucinationProtein FoldingLattice Protein Folding with Variational Annealing
Understanding the principles of protein folding is a cornerstone of computational biology, with implications for drug design, bioengineering, and the understanding of fundamental biological processes. Lattice protein fol…
Combinatorial OptimizationDrug DesignProtein FoldingA Novel P-bit-based Probabilistic Computing Approach for Solving the 3-D Protein Folding Problem
In the post-Moore era, the need for efficient solutions to non-deterministic polynomial-time (NP) problems is becoming more pressing. In this context, the Ising model implemented by the probabilistic computing systems wi…
Protein FoldingReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone Generation
Protein backbone generation plays a central role in de novo protein design and is significant for many biological and medical applications. Although diffusion and flow-based generative models provide potential solutions …
3D Molecule GenerationProtein DesignProtein FoldingFluorescence Phasor Analysis: Basic Principles and Biophysical Applications
Fluorescence is one of the most widely used techniques in biological sciences. Its exceptional sensitivity and versatility make it a tool of first choice for quantitative studies in biophysics. The concept of phasors, or…
Protein FoldingPyMOLfold: Interactive Protein and Ligand Structure Prediction in PyMOL
PyMOLfold is a flexible and open-source plugin designed to seamlessly integrate AI-based protein structure prediction and visualization within the widely used PyMOL molecular graphics system. By leveraging state-of-the-a…
PredictionProtein FoldingProtein Structure PredictionInferring protein folding mechanisms from natural sequence diversity
Protein sequences serve as a natural record of the evolutionary constraints that shape their functional structures. We show that it is possible to use only sequence information to go beyond predicting native structures a…
DiversityProtein FoldingMask prior-guided denoising diffusion improves inverse protein folding
Inverse protein folding generates valid amino acid sequences that can fold into a desired protein structure, with recent deep-learning advances showing significant potential and competitive performance. However, challeng…
DenoisingProtein FoldingvalidValidation of an LLM-based Multi-Agent Framework for Protein Engineering in Dry Lab and Wet Lab
Recent advancements in Large Language Models (LLMs) have enhanced efficiency across various domains, including protein engineering, where they offer promising opportunities for dry lab and wet lab experiment workflow aut…
Protein DesignProtein Foldingscientific discoveryLearning dynamical systems from data: Gradient-based dictionary optimization
The Koopman operator plays a crucial role in analyzing the global behavior of dynamical systems. Existing data-driven methods for approximating the Koopman operator or discovering the governing equations of the underlyin…
Protein Folding