Depth dependent amino acid substitution matrices and their use in predicting deleterious mutations

Farheen, Nida; Sen, Neeladri; Nair, Sanjana; Tan, Kuan Pern; Madhusudhan, M.S.

doi:10.1016/j.pbiomolbio.2017.02.004

Cited by 13 publications

(12 citation statements)

References 51 publications

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“…Residue frequencies also vary according to depth within a protein’s core (i.e. distance from a protein’s surface), suggesting benefit from using an array of depth-specific directional substitution matrices ( Farheen et al , 2017 ; Yampolsky and Stoltzfus, 2005 ). Such specialized implementations will become more feasible as DMS datasets are generated for more proteins.…”

Section: Discussionmentioning

confidence: 99%

DeMaSk: a deep mutational scanning substitution matrix and its use for variant impact prediction

Munro

Singh

2020

Bioinformatics

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Motivation Accurately predicting the quantitative impact of a substitution on a protein’s molecular function would be a great aid in understanding the effects of observed genetic variants across populations. While this remains a challenging task, new approaches can leverage data from the increasing numbers of comprehensive deep mutational scanning (DMS) studies that systematically mutate proteins and measure fitness. Results We introduce DeMaSk, an intuitive and interpretable method based only upon DMS datasets and sequence homologs that predicts the impact of missense mutations within any protein. DeMaSk first infers a directional amino acid substitution matrix from DMS datasets and then fits a linear model that combines these substitution scores with measures of per-position evolutionary conservation and variant frequency across homologs. Despite its simplicity, DeMaSk has state-of-the-art performance in predicting the impact of amino acid substitutions, and can easily and rapidly be applied to any protein sequence. Availability and implementation https://demask.princeton.edu generates fitness impact predictions and visualizations for any user-submitted protein sequence. Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Discussionmentioning

confidence: 99%

DeMaSk: a deep mutational scanning substitution matrix and its use for variant impact prediction

Munro

Singh

2020

Bioinformatics

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“…The protein-coding transcript used was NM_015937.6. We predicted the functional alteration of novel variants using polymorphism phenotyping-2 (PolyPhen-2) ( Adzhubei et al, 2010 ) and SIFT (Sorting intolerant from tolerant) ( Farheen et al, 2017 ), CADD 1 , and mutationTaster 2 .…”

Section: Methodsmentioning

confidence: 99%

Deep-Phenotyping the Less Severe Spectrum of PIGT Deficiency and Linking the Gene to Myoclonic Atonic Seizures

Bayat

Pendziwiat

Obersztyn³

et al. 2021

Front. Genet.

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The two aims of this study were (i) to describe and expand the phenotypic spectrum of PIGT deficiency in affected individuals harboring the c.1582G>A; p.Val528Met or the c.1580A > G; p.Asn527Ser variant in either homozygous or compound heterozygous state, and (ii) to identify potential genotype-phenotype correlations and any differences in disease severity among individuals with and without the PIGT variants. The existing literature was searched to identify individuals with and without the two variants. A detailed phenotypic assessment was performed of 25 individuals (both novel and previously published) with the two PIGT variants. We compared severity of disease between individuals with and without these PIGT variants. Twenty-four individuals carried the PIGT variant Val528Met in either homozygous or compound heterozygous state, and one individual displayed the Asn527Ser variant in a compound heterozygous state. Disease severity in the individual with the Asn527Ser variant was compatible with that in the individuals harboring the Val528Met variant. While individuals without the Asn527Ser or Val528Met variant had focal epilepsy, profound developmental delay (DD), and risk of premature death, those with either of the two variants had moderate to severe DD and later onset of epilepsy with both focal and generalized seizures. Individuals homozygous for the Val528Met variant generally became seizure-free on monotherapy with antiepileptic drugs, compared to other PIGT individuals who were pharmaco-resistant. Two patients were diagnosed with myoclonic-atonic seizures, and a single patient was diagnosed with eyelid myoclonia. Our comprehensive analysis of this large cohort of previously published and novel individuals with PIGT variants broadens the phenotypical spectrum and shows that both Asn527Ser and Val528Met are associated with a milder phenotype and less severe outcome. Our data show that PIGT is a new candidate gene for myoclonic atonic epilepsy. Our genotype-phenotype correlation will be useful for future genetic counseling. Natural history studies of this mild spectrum of PIGT-related disorder may shed light on hitherto unknown aspects of this rare disorder.

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“…The quantity measures the degree of burial of the atom. Depth has been shown capable of concisely describing protein environment, as substantiated by its utilities in protein design and function predictions (Tan et al, 2011, 2013, Farheen et al, 2017. Atom depth values were computed using default parameters.…”

Section: Residue Depthmentioning

confidence: 99%

Packpred: Predicting the functional effect of missense mutations

Tan

Kanitkar

Keong

et al. 2021

Preprint

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1.AbstractPredicting the functional consequences of single point mutations has relevance to protein function annotation and to clinical analysis/diagnosis. We developed and tested Packpred that makes use of a multi-body clique statistical potential in combination with a depth dependent amino acid substitution matrix (FADHM) and positional Shannon Entropy to predict the functional consequences of point mutations in proteins. Parameters were trained over a saturation mutagenesis data set of T4-lysozyme (1966 mutations). The method was tested over another saturation mutagenesis data set (CcdB; 1534 mutations) and the Missense3D data set (4099 mutations). The performance of Packpred was compared against those of six other contemporary methods. With MCC values of 0.42, 0.47 and 0.36 on the training and testing data sets respectively, Packpred outperforms all method in all data sets, with the exception of marginally underperforming to FADHM in the CcdB data set. On analyzing the results, we could build meta servers that chose best performing methods of wild type amino acids and for wild type-mutant amino acid pairs. This lead to an increase of MCC value of 0.40 and 0.51 for the two meta predictors respectively on the Missense3D data set. We conjecture that it is possible to improve accuracy with better meta predictors as among the 7 methods compared, at the least one method or another is able to correctly predict ∼99% of the data.

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Depth dependent amino acid substitution matrices and their use in predicting deleterious mutations

Cited by 13 publications

References 51 publications

DeMaSk: a deep mutational scanning substitution matrix and its use for variant impact prediction

DeMaSk: a deep mutational scanning substitution matrix and its use for variant impact prediction

Deep-Phenotyping the Less Severe Spectrum of PIGT Deficiency and Linking the Gene to Myoclonic Atonic Seizures

Packpred: Predicting the functional effect of missense mutations

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