AIMC Topic: Point Mutation

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

Journal of chemical information and modeling Feb 25, 2019
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...
Proteins Protein Stability Transition Temperature Point Mutation Neural Networks, Computer Computational Biology
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Identifying mouse developmental essential genes using machine learning.

Disease models & mechanisms Dec 13, 2018
The genes that are required for organismal survival are annotated as 'essential genes'. Identifying all the essential genes of an animal species can reveal critical functions that are needed during the development of the organism. To inform studies o...
Animals Protein Interaction Maps Mice Databases, Genetic Algorithms Phenotype Reproducibility of Results Gene Ontology Conserved Sequence Point Mutation Chromosomes, Mammalian Genes, Essential Mutagenesis Molecular Sequence Annotation Humans Machine Learning Software Genes, Developmental
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A Machine Learning Approach for Predicting HIV Reverse Transcriptase Mutation Susceptibility of Biologically Active Compounds.

Journal of chemical information and modeling Jul 17, 2018
HIV resistance emerging against antiretroviral drugs represents a great threat to the continued prolongation of the lifespans of HIV-infected patients. Therefore, methods capable of predicting resistance susceptibility in the development of compounds...
Reverse Transcriptase Inhibitors Drug Resistance, Viral HIV Reverse Transcriptase Point Mutation HIV Infections Bayes Theorem Models, Biological HIV-1 Humans Machine Learning Drug Discovery
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Computational design of thermostabilizing point mutations for G protein-coupled receptors.

eLife Jun 21, 2018
Engineering of GPCR constructs with improved thermostability is a key for successful structural and biochemical studies of this transmembrane protein family, targeted by 40% of all therapeutic drugs. Here we introduce a comprehensive computational ap...
Machine Learning Sequence Homology, Amino Acid Animals Humans Binding Sites Protein Interaction Domains and Motifs Protein Conformation, beta-Strand Models, Molecular Protein Binding Protein Engineering Gene Expression Protein Conformation, alpha-Helical Point Mutation Protein Stability Thermodynamics Kinetics Serotonin 5-HT2 Receptor Agonists Sequence Alignment Amino Acid Sequence Receptor, Serotonin, 5-HT2C Serotonin 5-HT2 Receptor Antagonists Crystallography, X-Ray
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modeling of the cryptic E2∼ubiquitin-binding site of E6-associated protein (E6AP)/UBE3A reveals the mechanism of polyubiquitin chain assembly.

The Journal of biological chemistry Sep 18, 2017
To understand the mechanism for assembly of Lys-linked polyubiquitin degradation signals, we previously demonstrated that the E6AP/UBE3A ligase harbors two functionally distinct E2∼ubiquitin-binding sites: a high-affinity Site 1 required for E6AP Cys...
Models, Molecular Humans Iodine Radioisotopes Isoenzymes Animals Point Mutation Expert Systems Amino Acid Substitution Molecular Docking Simulation Ubiquitin-Conjugating Enzymes Biocatalysis Cattle Recombinant Fusion Proteins Ubiquitin Computational Biology Binding Sites Protein Conformation Ubiquitination Mutagenesis, Site-Directed Cysteine Protein Multimerization Ubiquitin-Protein Ligases
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Systematic Prediction of the Impacts of Mutations in MicroRNA Seed Sequences.

Journal of integrative bioinformatics May 18, 2017
MicroRNAs are a class of small non-coding RNAs that are involved in many important biological processes and the dysfunction of microRNA has been associated with many diseases. The seed region of a microRNA is of crucial importance to its target recog...
Humans Substrate Specificity Point Mutation MicroRNAs Gene Ontology
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DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations.

BMC bioinformatics Dec 23, 2016
BACKGROUND: With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer...
Computational Biology Humans Neural Networks, Computer Sequence Analysis, DNA Neoplasms Genes, Neoplasm Point Mutation
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ActiMut-XGB: Predicting thermodynamic stability of point mutations for CALB with protein language model.

International journal of biological macromolecules Jun 1, 2025
Predicting the functional impact of single-point mutations on protein residual activity, especially after high-temperature incubation, is critical in protein engineering. We present an innovative machine learning model based on eXtreme Gradient Boost...
Machine Learning Lipase Protein Engineering Thermodynamics Point Mutation Models, Molecular Fungal Proteins Enzyme Stability
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DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning.

Nucleic acids research Jul 5, 2024
Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting t...
Mutation Humans Protein Interaction Mapping Software Point Mutation Protein Interaction Maps Deep Learning Protein Binding Proteins
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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...
Neural Networks, Computer Machine Learning Protein Stability Point Mutation
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