Papers Protein Stability Prediction
“Protein Stability Prediction” 태그가 달린 논문 8편 · 필터 해제
Zero-shot protein stability prediction by inverse folding models: a free energy interpretation
Inverse folding models have proven to be highly effective zero-shot predictors of protein stability. Despite this success, the link between the amino acid preferences of an inverse folding model and the free-energy consi…
Protein Stability PredictionAlgoRxplorers | Precision in Mutation: Enhancing Drug Design with Advanced Protein Stability Prediction Tools
Predicting the impact of single-point amino acid mutations on protein stability is essential for understanding disease mechanisms and advancing drug development. Protein stability, quantified by changes in Gibbs free ene…
Drug DesignDrug DiscoveryProtein Stability PredictionTransfer LearningImproving the prediction of protein stability changes upon mutations by geometric learning and a pre-training strategy
Accurate prediction of protein mutation effects is of great importance in protein engineering and design. Here we propose GeoStab-suite, a suite of three geometric learning-based models—GeoFitness, GeoDDG and GeoDTm—for …
PredictionProtein Stability PredictionA Pipeline for Data-Driven Learning of Topological Features with Applications to Protein Stability Prediction
In this paper, we propose a data-driven method to learn interpretable topological features of biomolecular data and demonstrate the efficacy of parsimonious models trained on topological features in predicting the stabil…
Feature ImportanceProtein Stability PredictionPredicting a Protein's Stability under a Million Mutations
Stabilizing proteins is a foundational step in protein engineering. However, the evolutionary pressure of all extant proteins makes identifying the scarce number of mutations that will improve thermodynamic stability cha…
Protein Stability PredictionMega-scale experimental analysis of protein folding stability in biology and design
Advances in DNA sequencing and machine learning are providing insights into protein sequences and structures on an enormous scale1. However, the energetics driving folding are invisible in these structures and remain lar…
Protein FoldingProtein Stability PredictionPredicting protein stability changes under multiple amino acid substitutions using equivariant graph neural networks
The accurate prediction of changes in protein stability under multiple amino acid substitutions is essential for realising true in-silico protein re-design. To this purpose, we propose improvements to state-of-the-art De…
Protein Stability PredictionmGPfusion: Predicting protein stability changes with Gaussian process kernel learning and data fusion
Proteins are commonly used by biochemical industry for numerous processes. Refining these proteins' properties via mutations causes stability effects as well. Accurate computational method to predict how mutations affect…
Protein DesignProtein Stability Prediction