AIMC Topic: Protein Stability

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Prediction and design of thermostable proteins with a desired melting temperature.

Scientific reports May 14, 2025
The stability of proteins at higher temperatures is crucial for their functionality, which is measured by their melting temperature (Tm). The Tm is the temperature at which 50% of the protein loses its native structure and activity. Existing methods ...
Protein Stability Transition Temperature Machine Learning Proteins
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Deep-Learning-Based Approaches for Rational Design of Stapled Peptides With High Antimicrobial Activity and Stability.

Microbial biotechnology Mar 1, 2025
Antimicrobial peptides (AMPs) face stability and toxicity challenges in clinical use. Stapled modification enhances their stability and effectiveness, but its application in peptide design is rarely reported. This study built ten prediction models fo...
Hemolysis Antimicrobial Peptides Bacteria Protein Stability Anti-Bacterial Agents Drug Design Deep Learning Microbial Sensitivity Tests Humans
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DDGemb: predicting protein stability change upon single- and multi-point variations with embeddings and deep learning.

Bioinformatics (Oxford, England) Dec 26, 2024
MOTIVATION: The knowledge of protein stability upon residue variation is an important step for functional protein design and for understanding how protein variants can promote disease onset. Computational methods are important to complement experimen...
Deep Learning Computational Biology Software Protein Stability Proteins Databases, Protein
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PROSTATA: a framework for protein stability assessment using transformers.

Bioinformatics (Oxford, England) Nov 1, 2023
MOTIVATION: Accurate prediction of change in protein stability due to point mutations is an attractive goal that remains unachieved. Despite the high interest in this area, little consideration has been given to the transformer architecture, which is...
Machine Learning Protein Stability Neural Networks, Computer Point Mutation
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DDMut: predicting effects of mutations on protein stability using deep learning.

Nucleic acids research Jul 5, 2023
Understanding the effects of mutations on protein stability is crucial for variant interpretation and prioritisation, protein engineering, and biotechnology. Despite significant efforts, community assessments of predictive tools have highlighted ongo...
Point Mutation Deep Learning Proteins Mutation Protein Stability Software
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BayeStab: Predicting effects of mutations on protein stability with uncertainty quantification.

Protein science : a publication of the Protein Society Nov 1, 2022
Predicting protein thermostability change upon mutation is crucial for understanding diseases and designing therapeutics. However, accurately estimating Gibbs free energy change of the protein remained a challenge. Some methods struggle to generalize...
Uncertainty Neural Networks, Computer Mutation Protein Stability Bayes Theorem
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On the critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation.

Briefings in bioinformatics Jan 18, 2021
A review, recently published in this journal by Fang (2019), showed that methods trained for the prediction of protein stability changes upon mutation have a very critical bias: they neglect that a protein variation (A- > B) and its reverse (B- > A) ...
Mutation Protein Stability Machine Learning Algorithms
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FireProtDB: database of manually curated protein stability data.

Nucleic acids research Jan 8, 2021
The majority of naturally occurring proteins have evolved to function under mild conditions inside the living organisms. One of the critical obstacles for the use of proteins in biotechnological applications is their insufficient stability at elevate...
Models, Molecular Internet Protein Stability Datasets as Topic Proteins Databases, Protein Software Computational Biology Molecular Sequence Annotation Point Mutation Machine Learning
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A critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation.

Briefings in bioinformatics Jul 15, 2020
A number of machine learning (ML)-based algorithms have been proposed for predicting mutation-induced stability changes in proteins. In this critical review, we used hypothetical reverse mutations to evaluate the performance of five representative al...
Machine Learning Algorithms Protein Stability Proteins Mutation
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A systematic exploration of [Formula: see text] cutoff ranges in machine learning models for protein mutation stability prediction.

Journal of bioinformatics and computational biology Oct 1, 2018
Discerning how a mutation affects the stability of a protein is central to the study of a wide range of diseases. Mutagenesis experiments on physical proteins provide precise insights about the effects of amino acid substitutions, but such studies ar...
Random Allocation Amino Acid Substitution Support Vector Machine Proteins Algorithms Mutation Computational Biology Protein Stability Neural Networks, Computer Machine Learning
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