Literature DB >> 29569365

Structural effects of point mutations in proteins.

Suvethigaa Shanthirabalan1, Jacques Chomilier2, Mathilde Carpentier1,2.   

Abstract

A structural database of 11 families of chains differing by a single amino acid substitution has been built. Another structural dataset of 5 families with identical sequences has been used for comparison. The RMSD computed after a global superimposition of the mutated protein on each native one is smaller than the RMSD calculated among proteins of identical sequences. The effect of the perturbation is very local, and not necessarily the highest at the position of the mutation. A RMSD between mutated and native proteins is computed over a 3-residue or a 7-residue window at each position. To separate the effects of structural fluctuations due to point mutations from other sources, pair RMSD have been translated into P values which themselves are included in a score called P-RANK. This score allows highlighting small backbone distortions by comparing these RMSD between mutated and native positions to the RMSD at the same positions in the absence of a mutation. It results from the P-RANK that 38% of all mutations produce a significant effect on the displacement. When compared with a random distribution of RMSD at un-mutated positions, we show that, even if the RMSD is greater when the mutation is in loops than in regular secondary structure, the relative effect is more important for regular secondary structures and for buried positions. We confirm the absence of correlation between RMSD and the predicted variation of free energy of folding but we found a small correlation between high RMSD and the error in the prediction of ΔΔG.
© 2018 Wiley Periodicals, Inc.

Keywords:  conformation; free energy; mutations; proteins; root mean square deviation

Mesh:

Substances:

Year:  2018        PMID: 29569365     DOI: 10.1002/prot.25499

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  6 in total

1.  Development and Validation of a Gene-Targeted dCAPS Marker for Marker-Assisted Selection of Low-Alkaloid Content in Seeds of Narrow-Leafed Lupin (Lupinus angustifolius L.).

Authors:  Magdalena Kroc; Katarzyna Czepiel; Paulina Wilczura; Monika Mokrzycka; Wojciech Święcicki
Journal:  Genes (Basel)       Date:  2019-06-04       Impact factor: 4.096

Review 2.  Protein ensembles link genotype to phenotype.

Authors:  Ruth Nussinov; Chung-Jung Tsai; Hyunbum Jang
Journal:  PLoS Comput Biol       Date:  2019-06-20       Impact factor: 4.475

3.  Impaired SorLA maturation and trafficking as a new mechanism for SORL1 missense variants in Alzheimer disease.

Authors:  Sebastien Feuillette; Laetitia Miguel; Anne Rovelet-Lecrux; Catherine Schramm; Ségolène Pernet; Olivier Quenez; Isabelle Ségalas-Milazzo; Laure Guilhaudis; Stéphane Rousseau; Gaëtan Riou; Thierry Frébourg; Dominique Campion; Gaël Nicolas; Magalie Lecourtois
Journal:  Acta Neuropathol Commun       Date:  2021-12-18       Impact factor: 7.801

4.  Computer-Based Immunoinformatic Analysis to Predict Candidate T-Cell Epitopes for SARS-CoV-2 Vaccine Design.

Authors:  Xueyin Mei; Pan Gu; Chuanlai Shen; Xue Lin; Jian Li
Journal:  Front Immunol       Date:  2022-03-30       Impact factor: 7.561

5.  Functional and Structural Impact of Deleterious Missense Single Nucleotide Polymorphisms in the NR3C1, CYP3A5, and TNF-α Genes: An In Silico Analysis.

Authors:  Navakanth Raju Ramayanam; Ranjani Manickam; Vijayakumar Thangavel Mahalingam; Khang Wen Goh; Chrismawan Ardianto; Poovi Ganesan; Long Chiau Ming; Rajanandh Muhasaparur Ganesan
Journal:  Biomolecules       Date:  2022-09-16

6.  Signatures of TRI5, TRI8 and TRI11 Protein Sequences of Fusarium incarnatum-equiseti Species Complex (FIESC) Indicate Differential Trichothecene Analogue Production.

Authors:  Ria T Villafana; Sephra N Rampersad
Journal:  Toxins (Basel)       Date:  2020-06-11       Impact factor: 4.546

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.