title: EASE-MM: Sequence-Based Prediction of Mutation-Induced Stability Changes with Feature-Based Multiple Models.
abstract: Protein engineering and characterisation of non-synonymous single nucleotide variants (SNVs) require accurate prediction of protein stability changes (ΔΔGu) induced by single amino acid substitutions. Here, we have developed a new prediction method called Evolutionary, Amino acid, and Structural Encodings with Multiple Models (EASE-MM), which comprises five specialised support vector machine (SVM) models and makes the final prediction from a consensus of two models selected based on the predicted secondary structure and accessible surface area of the mutated residue. The new method is applicable to single-domain monomeric proteins and can predict ΔΔGu with a protein sequence and mutation as the only inputs. EASE-MM yielded a Pearson correlation coefficient of 0.53-0.59 in 10-fold cross-validation and independent testing and was able to outperform other sequence-based methods. When compared to structure-based energy functions, EASE-MM achieved a comparable or better performance. The application to a large dataset of human germline non-synonymous SNVs showed that the disease-causing variants tend to be associated with larger magnitudes of ΔΔGu predicted with EASE-MM. The EASE-MM web-server is available at http://sparks-lab.org/server/ease.
authors.affiliation: Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia; Queensland Research Laboratory, NICTA, National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia. Electronic address: lukas.folkman@griffithuni.edu.au.
authors.forename: Lukas
authors.initials: L
authors.lastname: Folkman
authors.affiliation: Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia. Electronic address: b.stantic@griffith.edu.au.
authors.forename: Bela
authors.initials: B
authors.lastname: Stantic
authors.affiliation: Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia; Queensland Research Laboratory, NICTA, National ICT Australia, 70-72 Bowen Street, Spring Hill, Queensland 4000, Australia. Electronic address: a.sattar@griffith.edu.au.
authors.forename: Abdul
authors.initials: A
authors.lastname: Sattar
authors.affiliation: Institute for Integrated and Intelligent Systems, Griffith University, 170 Kessels Road, Brisbane, Queensland 4111, Australia; Institute for Glycomics, Griffith University, Parklands Drive, Southport, Queensland 4222, Australia. Electronic address: yaoqi.zhou@griffith.edu.au.
authors.forename: Yaoqi
authors.initials: Y
authors.lastname: Zhou
mesh_terms: D019943:Amino Acid Substitution; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D008958:Models, Molecular; D020125:Mutation, Missense; D015202:Protein Engineering / Q000379:methods*; D055550:Protein Stability; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*
chemical_list: D011506:Proteins
keywords: amino acid substitution; free energy change; machine learning; missense mutation; non-synonymous SNV