AIMC Topic: Protein Stability

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Machine learning and statistical analyses for extracting and characterizing "fingerprints" of antibody aggregation at container interfaces from flow microscopy images.

Biotechnology and bioengineering
Therapeutic proteins are exposed to numerous stresses during their manufacture, shipping, storage and administration to patients, causing them to aggregate and form particles through a variety of different mechanisms. These varied mechanisms generate...

Application of machine learning to predict monomer retention of therapeutic proteins after long term storage.

International journal of pharmaceutics
An important aspect of initial developability assessments as well formulation development and selection of therapeutic proteins is the evaluation of data obtained under accelerated stress condition, i.e. at elevated temperatures. We propose the appli...

Robust Prediction of Single and Multiple Point Protein Mutations Stability Changes.

Biomolecules
Accurate prediction of protein stability changes resulting from amino acid substitutions is of utmost importance in medicine to better understand which mutations are deleterious, leading to diseases, and which are neutral. Since conducting wet lab ex...

Unified rational protein engineering with sequence-based deep representation learning.

Nature methods
Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically...

Seq2seq Fingerprint with Byte-Pair Encoding for Predicting Changes in Protein Stability upon Single Point Mutation.

IEEE/ACM transactions on computational biology and bioinformatics
The engineering of stable proteins is crucial for various industrial purposes. Several machine learning methods have been developed to predict changes in the stability of proteins corresponding to single point mutations. To improve the prediction acc...

DeepDDG: Predicting the Stability Change of Protein Point Mutations Using Neural Networks.

Journal of chemical information and modeling
Accurately predicting changes in protein stability due to mutations is important for protein engineering and for understanding the functional consequences of missense mutations in proteins. We have developed DeepDDG, a neural network-based method, fo...

PON-tstab: Protein Variant Stability Predictor. Importance of Training Data Quality.

International journal of molecular sciences
Several methods have been developed to predict effects of amino acid substitutions on protein stability. Benchmark datasets are essential for method training and testing and have numerous requirements including that the data is representative for the...

Predicting the Effect of Single and Multiple Mutations on Protein Structural Stability.

Molecules (Basel, Switzerland)
Predicting how a point mutation alters a protein's stability can guide pharmaceutical drug design initiatives which aim to counter the effects of serious diseases. Conducting mutagenesis studies in physical proteins can give insights about the effect...

Stability of infliximab solutions in different temperature and dilution conditions.

Journal of pharmaceutical and biomedical analysis
Infliximab is a monoclonal antibody widely used for the treatment of inflammatory diseases. Over the past few years, many studies have assessed that monoclonal antibodies are prone to aggregation under stress conditions. The aim of this study was to ...