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Computational saturation mutagenesis to explore the effect of pathogenic mutations on extra-cellular domains of TREM2 associated with Alzheimer’s and Nasu-Hakola disease

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Abstract

Context

The specialised family of triggering receptors expressed on myeloid cells (TREMs) plays a pivotal role in causing neurodegenerative disorders and activating microglial anti-inflammatory responses. Nasu-Hakola disease (NHD), a rare autosomal recessive disorder, has been associated with mutations in TREM2, which is also responsible for raising the risk of Alzheimer’s disease (AD). Herein, we have made an endeavour to differentiate the confirmed pathogenic variants in TREM2 extra-cellular domain (ECD) linked with NHD and AD using mutation-induced fold stability change (∆∆G), with the computation of 12distinct structure-based methods through saturation mutagenesis. Correlation analysis between relative solvent accessibility (RSA) and ∆∆G expresses the discrete distributive behaviour of mutants associated with TREM2 in AD (R2 = 0.061) and NHD (R2 = 0.601). Our findings put an emphasis on W50 and V126 as major players in maintaining V-like domain in TREM2. Interestingly, we discern that both of them interact with a common residue Y108, which is dissolved upon mutation. This Y108 could have structural or functional role for TREM2 which can be an ideal candidate for further study. Furthermore, the residual interaction network highlights the importance of R47 and R62 in maintaining the CDR loops that are crucial for ligand binding. Future studies using biophysical characterisation of ligand interactions in TREM2-ECD would be helpful for the development of novel therapeutics for AD and NHD.

Methods

ConSurf algorithm and ENDscript were used to determine the position and conservation of each residue in the wild-type ECD of TREM2. The mutation-induced fold stability change (∆∆G) of confirmed pathogenic mutants associated with NHD and AD was estimated using 12 state-of-the-art structure-based protein stability tools. Furthermore, we also computed the effect of random mutation on these sites using computational saturation mutagenesis. Linear regression analysis was performed using mutants ∆∆G and RSA through GraphPad software. In addition, a comprehensive non-bonded residual interaction network (RIN) of wild type and its mutants of TREM2-ECD was enumerated using RING3.0.

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Abbreviations

AD:

Alzheimer’s disease

Aβ:

Amyloid beta

CDR:

Complementarity-determining regions

ECD:

Extra-cellular domain

NHD:

Nasu-Hakola disease

RIN:

Residue interaction network

RSA:

Relative solvent accessibility

TREM:

Triggering receptors expressed on myeloid

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Acknowledgements

The authors acknowledge the support from ICMR-RMRC, Bhubaneswar, for computational facility. The authors also acknowledge DHR for providing Young Scientist grant to BD. The authors also acknowledge ICMR for providing ICMR-Centenary Postdoctoral Fellowship to SP.

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  1. Preety Sthutika Swain and Sunita Panda contributed equally to this work.

Authors and Affiliations

  1. Bioinformatics Division, ICMR-Regional Medical Research Centre, Nalco Square, Chandrasekharpur, Bhubaneswar, 751023, Odisha, India

    Preety Sthutika Swain, Sanghamitra Pati & Budheswar Dehury

  2. Mycology Laboratory, ICMR-Regional Medical Research Centre, Nalco Square, Chandrasekharpur, Bhubaneswar, 751023, Odisha, India

    Sunita Panda

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Contributions

Preety Sthutika Swain: methodology, software investigation, data curation, visualisation, writing — original draft.

Sunita Panda: data curation, methodology, review and editing.

Sanghamitra Pati: writing — review and editing.

Budheswar Dehury: conceptualisation, methodology, review and editing, and supervision.

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Correspondence to Sanghamitra Pati or Budheswar Dehury.

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Swain, P.S., Panda, S., Pati, S. et al. Computational saturation mutagenesis to explore the effect of pathogenic mutations on extra-cellular domains of TREM2 associated with Alzheimer’s and Nasu-Hakola disease. J Mol Model 29, 360 (2023). https://doi.org/10.1007/s00894-023-05770-7

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