ReviewInternational journal of molecular sciences2019
Structural Perspective on Revealing and Altering Molecular Functions of Genetic Variants Linked with Diseases.
Review in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 33 citations in OpenAlex.
- Integrated Computational Analysis Reveals Structurally Destabilizing Missense Variants in theGenes · 2026Article
- In Silico Functional and Structural Analysis ofGenes · 2026Article
- Functional classification of platelet gene variants using CRISPR HDR in CD34American journal of human genetics · 2025Article
- Systematic evaluation of predictors for binding free energy changes upon mutations in protein complexes.Briefings in bioinformatics · 2025Article
- Decoding the effects of mutation on protein interactions using machine learning.Biophysics reviews · 2025Review
- Remote laboratory training for high school students: grocery store based hands-on project in protein crystallography.Journal of applied crystallography · 2023Article
- PKAD-2: New entries and expansion of functionalities of the database of experimentally measured pKa's of proteins.Journal of computational biophysics and chemistry · 2023Article
- Computer simulations on oxidative stress-induced reactions in SARS-CoV-2 spike glycoprotein: a multi-scale approach.Molecular diversity · 2022Article
- Mechanism of activation and the rewired network: New drug design concepts.Medicinal research reviews · 2022Review
- Pathogenic variation types in human genes relate to diseases through Pfam and InterPro mapping.Frontiers in molecular biosciences · 2022Article
- The deleterious impact of a non-synonymous SNP on protein structure and function is apparent in hypertension.Journal of molecular modeling · 2021Article
- Identification of discriminative gene-level and protein-level features associated with pathogenic gain-of-function and loss-of-function variants.American journal of human genetics · 2021Article
- Article
- Alteration of Exon Definition Causes Amelogenesis Imperfecta.Journal of dental research · 2020Article
- Characterization of human frataxin missense variants in cancer tissues.Human mutation · 2019Article
- Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Structural information of biological macromolecules is crucial and necessary to deliver predictions about the effects of mutations-whether polymorphic or deleterious (i.e., disease causing), wherein, thermodynamic parameters, namely, folding and binding free energies potentially serve as effective biomarkers. It may be emphasized that the effect of a mutation depends on various factors, including the type of protein (globular, membrane or intrinsically disordered protein) and the structural context in which it occurs. Such information may positively aid drug-design. Furthermore, due to the intrinsic plasticity of proteins, even mutations involving radical change of the structural and physico⁻chemical properties of the amino acids (native vs. mutant) can still have minimal effects on protein thermodynamics. However, if a mutation causes significant perturbation by either folding or binding free energies, it is quite likely to be deleterious. Mitigating such effects is a promising alternative to the traditional approaches of designing inhibitors. This can be done by structure-based in silico screening of small molecules for which binding to the dysfunctional protein restores its wild type thermodynamics. In this review we emphasize the effects of mutations on two important biophysical properties, stability and binding affinity, and how structures can be used for structure-based drug design to mitigate the effects of disease-causing variants on the above biophysical properties.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.