Review
Biochemical Research Methods
Anna Marabotti, Bernardina Scafuri, Angelo Facchiano
Summary: This review summarizes the computational methods developed over the past 30 years for predicting the change in thermodynamic stability of proteins due to mutations, as well as their current applications. It discusses the limitations of existing methods and provides guidance on selecting the most suitable tools for different needs.
BRIEFINGS IN BIOINFORMATICS
(2021)
Review
Biochemistry & Molecular Biology
Maria Petrosino, Leonore Novak, Alessandra Pasquo, Roberta Chiaraluce, Paola Turina, Emidio Capriotti, Valerio Consalvi
Summary: The study integrated experimental data and computational methods to effectively evaluate the impact of missense variants on cancer-related genes and provided new insights for assessing the risk of complex disorders and developing treatment strategies.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Biochemical Research Methods
Ibrahim Berber, Cesim Erten, Hilal Kazan
Summary: This study focuses on predicting mutations in protein-protein interactions and shows that the Predator model outperforms existing methods. The predictions shed light on potential cancer driver genes and reveal patterns of mutual exclusivity between the identified genes and their disrupted partners across cancer cohorts under study.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Joicymara S. Xavier, Thanh-Binh Nguyen, Malancha Karmarkar, Stephanie Portelli, Pamela M. Rezende, Joao P. L. Velloso, David B. Ascher, Douglas E. Pires
Summary: ThermoMutDB is a manually curated database containing experimental data of thermodynamic parameters for proteins, allowing users to contribute new data points and programmatically access the database via a RESTful API. It also includes corrections for annotation errors in previously curated entries, making it a valuable research tool.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Haicang Zhang, Michelle S. Xu, Xiao Fan, Wendy K. Chung, Yufeng Shen
Summary: Computational method gMVP based on graph attention neural networks is developed to accurately predict pathogenic missense variants, and it shows superior performance compared to other methods. The pooling of information and transfer learning capability of gMVP contribute to its improved interpretation of missense variants.
NATURE MACHINE INTELLIGENCE
(2022)
Article
Biology
Tingting Sun, Yuting Chen, Yuhao Wen, Zefeng Zhu, Minghui Li
Summary: Resistance to small-molecule drugs is a major cause of therapeutic drug failure in clinical practice, with missense mutations altering protein-ligand binding being a critical mechanism for genetic disease and drug resistance. PremPLI, a structure-based machine learning method, has shown robust predictive performance with higher accuracy in quantitatively estimating the effects of single mutations on ligand binding affinity changes.
COMMUNICATIONS BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Fabrizio Pucci, Martin Schwersensky, Marianne Rooman
Summary: This study discusses the application of new methods based on artificial intelligence in predicting the impact of mutations on protein stability, as well as their limitations and challenges.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2022)
Article
Cell Biology
Matteo Tiberti, Luca Di Leo, Mette Vixo Vistesen, Rikke Sofie Kuhre, Francesco Cecconi, Daniela De Zio, Elena Papaleo
Summary: Cancer genomics and cancer mutation databases provide information on missense mutations in cancer patient samples. Predicting the impact of these mutations and validating them experimentally can help identify pathogenic mutations. In this study, the bioinformatic tool Cancermuts was proposed to gather and annotate cancer mutations, and it was applied to investigate AMBRA1 mutations in melanoma. The tool successfully identified two mutations with enhanced tumorigenic potential, highlighting its usefulness.
CELL DEATH & DISEASE
(2022)
Article
Multidisciplinary Sciences
Hongjian Qi, Haicang Zhang, Yige Zhao, Chen Chen, John J. Long, Wendy K. Chung, Yongtao Guan, Yufeng Shen
Summary: MVP, a new prediction method using deep residual networks, outperforms previous methods in prioritizing pathogenic missense variants, especially in genes tolerant of loss of function variants. The model is trained separately in genes with different genetic effect size and mode of action, demonstrating its utility in prioritizing de novo variants contributing to developmental disorders.
NATURE COMMUNICATIONS
(2021)
Article
Biochemistry & Molecular Biology
Catarina A. Madeira, Carolina Anselmo, Joao M. Costa, Catia A. Bonito, Ricardo J. Ferreira, Daniel J. . V. A. Santos, Ronald J. Wanders, Joao B. Vicente, Fatima V. Ventura, Paula Leandro
Summary: Medium chain acyl-CoA dehydrogenase (MCAD) deficiency is caused by mutations in the ACADM gene, leading to impaired function and/or structure of MCAD. This study investigates the effects of amino acid substitutions on FAD incorporation and finds that most variants result in reduced FAD content, but some can be rescued by cofactor supplementation, indicating the importance of cofactor availability for MCAD function.
BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE
(2023)
Review
Biochemistry & Molecular Biology
David A. Korasick, John J. Tanner
Summary: Certain mutations in the ALDH7A1 gene cause pyridoxine-dependent epilepsy (PDE), characterized by seizures and sometimes intellectual disability. These mutations, including over 70 missense mutations, have complex effects on the structure and catalytic activity of ALDH7A1. Mutations targeting active site residues and those remote from the site show varied impact, indicating the challenge in predicting the effects of missense mutations on enzyme function. Additional biophysical analyses of disease-causing mutations are necessary to develop predictive rules for enzyme structure and function.
Article
Oncology
Prashant Chittiboina, Debjani Mandal, Alejandro Bugarini, David T. Asuzu, Dustin Mullaney, Panagiotis Mastorakos, Stefan Stoica, Reinier Alvarez, Gretchen Scott, Dragan Maric, Abdel Elkahloun, Zhengping Zhuang, Emily Y. Chew, Chunzhang Yang, Marston Linehan, Russell R. Lonser
Summary: This study examined the therapeutic effect of short-term oral vorinostat in patients with germline missense VHL mutations and central nervous system hemangioblastomas. The results showed that vorinostat increased the expression of missense mutated VHL protein in tumor cells and suppressed downstream hypoxia-inducible factor effectors. Additionally, vorinostat prevented the interaction between Hsp90 and mutated VHL protein, leading to protein rescue and tumor growth arrest.
CLINICAL CANCER RESEARCH
(2023)
Article
Biochemical Research Methods
Anna Marabotti, Eugenio Del Prete, Bernardina Scafuri, Angelo Facchiano
Summary: Despite advancements in predicting the thermodynamic stability of proteins using Web tools, issues such as bias towards destabilizing mutations and unreliable results persist. To enhance predictive reliability, utilizing multiple predictors and combining their outcomes into a consensus is recommended.
BMC BIOINFORMATICS
(2021)
Article
Multidisciplinary Sciences
Hania Shah, Khushbukhat Khan, Naila Khan, Yasmin Badshah, Naeem Mahmood Ashraf, Maria Shabbir
Summary: This study predicted the structure and post-translational modifications of protein kinase C iota (PKCl) for the first time, and investigated deleterious missense variants in PKCl. Computational approaches were used to determine the pathogenicity of the variants, their impact on protein structure and function, and their association with cancer. The results reveal that these variants may contribute to protein malfunctioning.
SCIENTIFIC REPORTS
(2022)
Article
Genetics & Heredity
Adebiyi Sobitan, William Edwards, Md Shah Jalal, Ayanfeoluwa Kolawole, Hemayet Ullah, Atanu Duttaroy, Jiang Li, Shaolei Teng
Summary: Research has found that most potential missense mutations destabilize MPO, while a small percentage stabilize the MPO protein. Certain specific missense mutations have the highest impact on MPO stability and are potentially associated with human diseases. Additionally, analysis revealed a connection between certain post-translational modification (PTM) sites and disease-associated missense mutations.
Article
Biochemistry & Molecular Biology
Ning Zhang, Haoyu Lu, Yuting Chen, Zefeng Zhu, Qing Yang, Shuqin Wang, Minghui Li
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2020)
Article
Biology
Tingting Sun, Yuting Chen, Yuhao Wen, Zefeng Zhu, Minghui Li
Summary: Resistance to small-molecule drugs is a major cause of therapeutic drug failure in clinical practice, with missense mutations altering protein-ligand binding being a critical mechanism for genetic disease and drug resistance. PremPLI, a structure-based machine learning method, has shown robust predictive performance with higher accuracy in quantitatively estimating the effects of single mutations on ligand binding affinity changes.
COMMUNICATIONS BIOLOGY
(2021)