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Mutation, Missense

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Linking Protein Stability to Pathogenicity: Predicting Clinical Significance of Single-Missense Mutations in Ocular Proteins Using Machine Learning.

International journal of molecular sciences 39519200
Understanding the effect of single-missense mutations on protein stability is crucial for clinical decision-making and therapeutic development. The impact of these mutations on protein stability and 3D structure remains underexplored. Here, we develo...
cis-trans-Isomerases Clinical Relevance Eye Diseases Eye Proteins Humans Machine Learning Mutation, Missense Protein Stability
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Toward trustable use of machine learning models of variant effects in the clinic.

American journal of human genetics 39561772
There has been considerable progress in building models to predict the effect of missense substitutions in protein-coding genes, fueled in large part by progress in applying deep learning methods to sequence data. These models have the potential to e...
Computer Simulation Deep Learning Genetic Variation Humans Machine Learning Models, Genetic Mutation, Missense
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Deep learning-based assessment of missense variants in the gene presented with bilateral congenital cataract.

BMJ open ophthalmology 39809522
OBJECTIVE: We compared the protein structure and pathogenicity of clinically relevant variants of the gene with AlphaFold2 (AF2), Alpha Missense (AM), and ThermoMPNN for the first time.
Cataract Deep Learning Female Humans Male Mutation, Missense Phenotype
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AFFIPred: AlphaFold2 structure-based Functional Impact Prediction of missense variations.

Protein science : a publication of the Protein Society 39840793
Protein structure holds immense potential for pathogenicity prediction, albeit structure-based predictors are limited compared to the sequence-based counterparts due to the "structure knowledge gap" between large number of available protein sequences...
Computational Biology Databases, Protein Humans Machine Learning Models, Molecular Mutation, Missense Protein Conformation Proteins Software
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Interpretable Dynamic Directed Graph Convolutional Network for Multi-Relational Prediction of Missense Mutation and Drug Response.

IEEE journal of biomedical and health informatics 39423073
Tumor heterogeneity presents a significant challenge in predicting drug responses, especially as missense mutations within the same gene can lead to varied outcomes such as drug resistance, enhanced sensitivity, or therapeutic ineffectiveness. These ...
Antineoplastic Agents Computational Biology Deep Learning Humans Mutation, Missense Neoplasms Neural Networks, Computer
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Integrating Artificial Intelligence and Bioinformatics Methods to Identify Disruptive STAT1 Variants Impacting Protein Stability and Function.

Genes 40149454
The Signal Transducer and Activator of Transcription 1 () gene is an essential component of the JAK-STAT signaling pathway. This pathway plays a pivotal role in the regulation of different cellular processes, including immune responses, cell growth,...
Artificial Intelligence Computational Biology Humans Mutation, Missense Polymorphism, Single Nucleotide Protein Stability STAT1 Transcription Factor
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A novel seven-tier framework for the classification of MEFV missense variants using adaptive and rigid classifiers.

Scientific reports 40090944
There is a great discrepancy between the clinical categorization of MEFV gene variants and in silico tool predictions. In this study, we developed a seven-tier classification system for MEFV missense variants of unknown significance and recommended a...
Algorithms Computational Biology Computer Simulation Databases, Genetic Familial Mediterranean Fever Humans Machine Learning Mutation, Missense Pyrin
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Accelerated Missense Mutation Identification in Intrinsically Disordered Proteins Using Deep Learning.

Biomacromolecules 40072940
We use a combination of Brownian dynamics (BD) simulation results and deep learning (DL) strategies for the rapid identification of large structural changes caused by missense mutations in intrinsically disordered proteins (IDPs). We used ∼6500 IDP s...
Algorithms Deep Learning Humans Intrinsically Disordered Proteins Molecular Dynamics Simulation Mutation, Missense Neural Networks, Computer
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Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

Journal of chemical information and modeling 40228162
Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosphatase and tensin homologue (PTEN) serves as a paradigmatic model for mapping its mutational landsca...
Autism Spectrum Disorder Humans Machine Learning Molecular Dynamics Simulation Mutation, Missense Neoplasms Protein Conformation PTEN Phosphohydrolase
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Accurate identification and mechanistic evaluation of pathogenic missense variants with .

Proceedings of the National Academy of Sciences of the United States of America 40314982
Understanding the effects of missense mutations or single amino acid variants (SAVs) on protein function is crucial for elucidating the molecular basis of diseases/disorders and designing rational therapies. We introduce here , a machine learning too...
Algorithms Computational Biology Databases, Protein Humans Machine Learning Mutation, Missense Proteins
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