4.6 Article

Effect of naturally-occurring mutations on the stability and function of cancer-associated NQO1: Comparison of experiments and computation

Journal

FRONTIERS IN MOLECULAR BIOSCIENCES
Volume 9, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fmolb.2022.1063620

Keywords

protein function; protein stability; genotype-phenotype correlations; computational prediction; sequence conservation

Funding

  1. ERDF/Spanish Ministry of Science, Innovation and Universities-State Research Agency
  2. Consejeria de Economia, Conocimiento, Empresas y Universidad, Junta de Andalucia [RTI 2018-096246-B-I00]
  3. ERDF/Counseling of Economic transformation, Industry, Knowledge and Universities [P18-RT-2413]
  4. Comunidad Valenciana [B-BIO-84-UGR20]
  5. Novo Nordisk Foundation [CIAICO/2021/135]
  6. [NNF18OC0033950]

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Recent advances in DNA sequencing technologies have revealed individual variability in the human genome. This study focuses on the analysis of naturally-occurring variants of NQO1 and found a correlation between experimental analysis and computational predictions, although outliers still exist.
Recent advances in DNA sequencing technologies are revealing a large individual variability of the human genome. Our capacity to establish genotype-phenotype correlations in such large-scale is, however, limited. This task is particularly challenging due to the multifunctional nature of many proteins. Here we describe an extensive analysis of the stability and function of naturally-occurring variants (found in the COSMIC and gnomAD databases) of the cancer-associated human NAD(P)H:quinone oxidoreductase 1 (NQO1). First, we performed in silico saturation mutagenesis studies (> 5,000 substitutions) aimed to identify regions in NQO1 important for stability and function. We then experimentally characterized twenty-two naturally-occurring variants in terms of protein levels during bacterial expression, solubility, thermal stability, and coenzyme binding. These studies showed a good overall correlation between experimental analysis and computational predictions; also the magnitude of the effects of the substitutions are similarly distributed in variants from the COSMIC and gnomAD databases. Outliers in these experimental-computational genotype-phenotype correlations remain, and we discuss these on the grounds and limitations of our approaches. Our work represents a further step to characterize the mutational landscape of NQO1 in the human genome and may help to improve high-throughput in silico tools for genotype-phenotype correlations in this multifunctional protein associated with disease.

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