Skip to main content

Advertisement

SpringerLink
Log in

Dynamics of TUBB protein with five majorly occurring natural variants: a risk of cortical dysplasia

  • Original Paper
  • Published:
Journal of Molecular Modeling Aims and scope Submit manuscript

Abstract

Beta-tubulin (TUBB) protein is one of the components of the microtubule cytoskeleton that plays a critical role in the central nervous system. Genetic variants of TUBB cause cortical dysplasia, a developmental brain defect implicated in axonal guidance and the neuron migration. In this study, we assess pathogenic variants (Q15K, Y222F, M299V, V353I, and E401K) of TUBB protein and compared with non-pathogenic variant G235S to determine their impact on protein dynamic to cause cortical dysplasia. Among the analyzed variants, Q15K, Y222F, M299V, and E401K were noticed to have deleterious effect. Then, variant structures were modeled and their affinity with their known cofactor Guanosine-5'-triphosphate (GTP) was assessed which showed diverse binding energies ranged between (-7.436 to -6.950 kcal/mol) for the variants compared to wild-type (-7.428 kcal/mol). Finally, the molecular dynamics simulation of each variant was investigated which showed difference in trajectory between the pathogenic and non-pathogenic variant. Our analysis suggests change in amino acid residue of TUBB structure has notably affects the protein flexibility and their interactions with known cofactor. Overall, our findings provide insight on the relationship between TUBB variants and their structural dynamics that may cause diverse effects leading to cortical dysplasia.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Data availability

All the information is accessible on UniProt, RCSB, and the simulation data would be provided on reasonable request to corresponding author. The accession numbers to access this data are given in the manuscript.

References

  1. Jiang X, Nardelli J (2016) Cellular and molecular introduction to brain development. Neurobiol Dis 92:3–17. https://doi.org/10.1016/j.nbd.2015.07.007

    Article  CAS  PubMed  Google Scholar 

  2. Desikan RS, Barkovich AJ (2016) Malformations of cortical development. Ann Neurol 80(6):797–810. https://doi.org/10.1002/ana.24793

    Article  PubMed  PubMed Central  Google Scholar 

  3. Bahi-Buisson N, Poirier K, Fourniol F, Saillour Y, Valence S, Lebrun N, Hully M, Bianco CF, Boddaert N, Elie C, Lascelles K, Souville I LIS-Tubulinopathies Consortium, Beldjord C, Chelly J (2014) The wide spectrum of tubulinopathies: what are the key features for the diagnosis? Brain J Neurol 137:1676–1700. https://doi.org/10.1093/brain/awu082

    Article  Google Scholar 

  4. Oegema R, Cushion TD, Phelps IG, Chung SK, Dempsey JC, Collins S, Mullins JG, Dudding T, Gill H, Green AJ, Dobyns WB (2015) Recognizable cerebellar dysplasia associated with mutations in multiple tubulin genes. Hum Mol Genet 24(18):5313–5325. https://doi.org/10.1093/hmg/ddv250

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Lu I, Chen C, Tung CY, Chen HH, Pan JP, Chang CH, Cheng JS, Chen YA, Wang CH, Huang CW, Kang YN (2018) Identification of genes associated with cortical malformation using a transposon-mediated somatic mutagenesis screen in mice. Nat Commun 9(1):1–5. https://doi.org/10.1038/s41467-018-04880-8

    Article  CAS  Google Scholar 

  6. Hebebrand M, Hüffmeier U, Trollmann R, Hehr U, Uebe S, Ekici AB, Kraus C, Krumbiegel M, Reis A, Thiel CT, Popp B (2019) The mutational and phenotypic spectrum of TUBA1A-associated tubulinopathy. Orphanet J Rare Dis 14(1):1–3. https://doi.org/10.1186/s13023-019-1020-x

    Article  Google Scholar 

  7. Romaniello R, Arrigoni F, Fry AE, Bassi MT, Rees MI, Borgatti R, Pilz DT, Cushion TD (2018) Tubulin genes and malformations of cortical development. Eur J Med Genet 61(12):744–754. https://doi.org/10.1016/j.ejmg.2018.07.012

    Article  PubMed  Google Scholar 

  8. Tian G, Bhamidipati A, Cowan NJ, Lewis SA (1999) Tubulin folding cofactors as GTPase-activating proteins: GTP hydrolysis and the assembly of the α/β-tubulin heterodimer. J Biol Chem 274(34):24054–24058. https://doi.org/10.1074/jbc.274.34.24054

    Article  CAS  PubMed  Google Scholar 

  9. Breuss M, Heng JI, Poirier K, Tian G, Jaglin XH, Qu Z, Braun A, Gstrein T, Ngo L, Haas M, Bahi-Buisson N (2012) Mutations in the β-tubulin gene TUBB5 cause microcephaly with structural brain abnormalities. Cell Rep 2(6):1554–1562. https://doi.org/10.1016/jcelrep201211017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Wattanathamsan O, Pongrakhananon V (2021) Post-translational modifications of tubulin: their role in cancers and the regulation of signaling molecules. Cancer Gene Ther: 1–8. https://doi.org/10.1038/s41417-021-00396-4

  11. Song J, Gao QL, Wu BW, Zhu T, Cui XX, Jin CJ, Wang SY, Wang SH, Fu DJ, Liu HM, Zhang SY (2020) Discovery of tertiary amide derivatives incorporating benzothiazole moiety as anti-gastric cancer agents in vitro via inhibiting tubulin polymerization and activating the Hippo signaling pathway. Eur J Med Chem 203:112618. https://doi.org/10.1016/j.ejmech.2020.112618

    Article  CAS  PubMed  Google Scholar 

  12. Baldassari S, Ribierre T, Marsan E, Adle-Biassette H, Ferrand-Sorbets S, Bulteau C, Dorison N, Fohlen M, Polivka M, Weckhuysen S, Dorfmüller G, Chipaux M, Baulac S (2019) Dissecting the genetic basis of focal cortical dysplasia: a large cohort study. Actaneuropathologica 138(6):885–900. https://doi.org/10.1007/s00401-019-02061-5

    Article  CAS  Google Scholar 

  13. Sferra A, Petrini S, Bellacchio E, Nicita F, Scibelli F, Dentici ML, Alfieri P, Cestra G, Bertini ES, Zanni G (2020) TUBB variants underlying different phenotypes result in altered vesicle trafficking and microtubule dynamics. Int J Mol Sci 21(4):1385. https://doi.org/10.3390/ijms21041385

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Umair M, Khan S, Mohammad T, Shafie A, Anjum F, Islam A, Hassan MI (2021) Impact of single amino acid substitution on the structure and function of TANK-binding kinase-1. J Cell Biochem 122(10):1475–1490. https://doi.org/10.1002/jcb.30070

    Article  CAS  PubMed  Google Scholar 

  15. Saxena S, Murthy TK, Chandramohan V, Yadav AK, Singh TR (2021) Structural and functional analysis of disease-associated mutations in GOT1 gene: An in silico study. Comput Biol Med 136:104695. https://doi.org/10.1016/j.compbiomed.2021.104695

    Article  CAS  PubMed  Google Scholar 

  16. Ghafoor S, Silveira KD, Qamar R, Azam M, Kannu P (2022) Exome Sequencing Identifies a Biallelic GALNS Variant (p. Asp233Asn) Causing Mucopolysaccharidosis Type IVA in a Pakistani Consanguineous Family. Genes 13(10):1743. https://doi.org/10.3390/genes13101743

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Clementel D, Del Conte A, Monzon AM, Camagni GF, Minervini G, Piovesan D, Tosatto SC (2022) RING 3.0: fast generation of probabilistic residue interaction networks from structural ensembles. Nucleic Acids Research 50(W1):W651–W656. https://doi.org/10.1093/nar/gkac365

    Article  PubMed  PubMed Central  Google Scholar 

  18. Peele KA, Durthi CP, Srihansa T, Krupanidhi S, Ayyagari VS, Babu DJ, Indira M, Reddy AR, Venkateswarulu TC (2020) Molecular docking and dynamic simulations for antiviral compounds against SARS-CoV-2: A computational study. Inform Med Unlocked 19:100345. https://doi.org/10.1016/j.imu.2020.100345

    Article  PubMed  PubMed Central  Google Scholar 

  19. Chen Z, Ruan P, Wang L, Nie X, Ma X, Tan Y (2021) T and B cell Epitope analysis of SARS-CoV-2 S protein based on immunoinformatics and experimental research. J Cell Mol Med 25(2):1274–1289. https://doi.org/10.1111/jcmm.16200

    Article  CAS  PubMed  Google Scholar 

  20. Price DJ, Brooks CL (2004) A modified TIP3P water potential for simulation with Ewald summation. J Chem Phys 121(20):10096–10103. https://doi.org/10.1063/11808117

    Article  CAS  PubMed  Google Scholar 

  21. Hess B, Bekker H, Berendsen HJ, Fraaije JG (1997) LINCS: a linear constraint solver for molecular simulations. J Comput Chem 18(12):1463–1472. https://doi.org/10.1021/ct700200b

    Article  CAS  Google Scholar 

  22. Nemati R, Molakarimi M, Mohseni A, Taghdir M, Khalifeh K, Sajedi RH (2021) Thermostability of Ctenophore and coelenterate Ca2+-Regulated Apo-photoproteins: A comparative study. ACS Chem Biol 16(8):1538–45. https://doi.org/10.1021/acschembio.1c00401

    Article  CAS  PubMed  Google Scholar 

  23. Gonçalves FG, Tomás de Andrade LF, Taranath A, Lakshmanan R, Goetti R, Feltrin FS, Mankad K, Teixeira SR, Hanagandi PB, Tubulinopathies AF (2018) Topics in magnetic resonance imaging 27(6):395–408. https://doi.org/10.1097/RMR.0000000000000188

  24. Chen S, Alhassen W, VakilMonfared R, Vachirakorntong B, Nauli SM, Baldi P, Alachkar A (2021) Dynamic changes of brain cilia transcriptomes across the human lifespan. Int J Mol Sci 22(19):10387. https://doi.org/10.3390/ijms221910387

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Salinas RE, Ogohara C, Thomas MI, Shukla KP, Miller SI, Ko DC (2014) A cellular genome-wide association study reveals human variation in microtubule stability and a role in inflammatory cell death. Mol Biol Cell 25(1):76–86. https://doi.org/10.1091/mbc.E13-06-0294

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Isrie M, Breuss M, Tian G, Hansen AH, Cristofoli F, Morandell J, Kupchinsky ZA, Sifrim A, Rodriguez-Rodriguez CM, Dapena EP (2015) Doonanco K (2015) Mutations in either TUBB or MAPRE2 cause circumferential skin creases Kunze type. The American Journal of Human Genetics 97(6):790–800. https://doi.org/10.1016/j.ajhg.2015.10.014

    Article  CAS  PubMed  Google Scholar 

  27. Lizarraga SB, Margossian SP, Harris MH, Campagna DR, Han AP, Blevins S, Mudbhary R, Barker JE, Walsh CA, Fleming MD (2010) Cdk5rap2 regulates centrosome function and chromosome segregation in neuronal progenitors. Development (Cambridge, England) 137(11):1907–1917. https://doi.org/10.1242/dev040410

    Article  CAS  PubMed  Google Scholar 

  28. Walsh CA, Engle EC (2010) Allelic diversity in human developmental neurogenetics: insights into biology and disease. Neuron 68(2):245–253. https://doi.org/10.1016/jneuron201009042

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Shaik NA, Al-Qahtani F, Nasser K, Jamil K, Alrayes NM, Elango R, Awan ZA, Banaganapalli B (2020) Molecular insights into the coding region mutations of low-density lipoprotein receptor adaptor protein 1 (LDLRAP1) linked to familial hypercholesterolemia. J Gene Med 22(6):e3176. https://doi.org/10.1002/jgm3176

    Article  CAS  PubMed  Google Scholar 

  30. Amant RS, Jiménez DA, Burger D (2008) Low-power, high-performance analog neural branch prediction. In 2008 41st IEEE/ACM International Symposium on Microarchitecture (pp 447–458)

  31. Choudhury A, Mohammad T, Anjum F, Shafie A, Singh IK, Abdullaev B, Pasupulet VR, Adnan M, Yadav DK, Hassan MI (2022) Comparative analysis of web-based programs for single amino acid substitutions in proteins. PloS one 17(5):e0267084. https://doi.org/10.1371/journalpone0267084

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Islam MJ, Parves MR, Mahmud S, Tithi FA, Reza MA (2019) Assessment of structurally and functionally high-risk nsSNPs impacts on human bone morphogenetic protein receptor type IA (BMPR1A) by computational approach. Comput Biol Chem 80:31–45. https://doi.org/10.1016/jcompbiolchem201903004

    Article  CAS  PubMed  Google Scholar 

  33. Galehdari H, Saki N, Mohammadi-Asl J, Rahim F (2013) Meta-analysis diagnostic accuracy of SNP-based pathogenicity detection tools: a case of UTG1A1 gene mutations. Int J Mol Epidemiol Genet 4(2):77–85

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Attard TJ, Welburn JP, Marsh JA (2022) Understanding molecular mechanisms and predicting phenotypic effects of pathogenic tubulin mutations. PLoS Comput Biol 18(10):e1010611. https://doi.org/10.1371/journal.pcbi.1010611

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Daison FA, Kumar N, Balakrishnan S, Venugopal K, Elango S, Sokkar P (2022) Molecular dynamics studies on the bacterial membrane pore formation by small molecule antimicrobial agents. J Chem Inform Model 62(1):40–48. https://doi.org/10.1021/acsjcim1c01049

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We owe our gratitude to Chettinad Academy of Research and Education, Chettinad Hospital and Research Institute, Kelambakkam, Tamil Nadu, India for providing computing resources and support.

Author information

Author notes

  1. V. Janakiraman and M. Sudhan equally contributed.

Authors and Affiliations

  1. Drug Discovery and Multi-Omics Laboratory, Faculty of Allied Health Sciences, Chettinad Hospital and Research Institute, Chettinad Academy of Research and Education, Kelambakkam, 603103, Tamil Nadu, India

    V. Janakiraman, M. Sudhan & Shiek S. S. J. Ahmed

  2. Department of Clinical Laboratories Sciences, College of Applied Medical Sciences, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia

    Khalid J. Alzahrani

  3. Department of Optometry, College of Applied Medical Sciences, Qassim University, Buraydah, Saudi Arabia

    Saleh Alshammeri

  4. College of Dental Medicine, Roseman University of Health Sciences, South Jordan, UT, USA

    Shankargouda Patil

Authors
  1. V. Janakiraman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Sudhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Khalid J. Alzahrani
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Saleh Alshammeri
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shiek S. S. J. Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shankargouda Patil
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Shiek SSJ Ahmed contributed to the study conception and design. Material preparation, data collection and analysis were performed by Janakiraman and Sudhan M. The Interpretation and first draft of the manuscript was written by Khalid J. Alzahrani and Saleh Alshammeri. Shankargouda Patil involved in molecular docking investigation and interpretation. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Shiek S. S. J. Ahmed.

Ethics declarations

Ethical approval

Not applicable.

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Janakiraman, V., Sudhan, M., Alzahrani, K.J. et al. Dynamics of TUBB protein with five majorly occurring natural variants: a risk of cortical dysplasia. J Mol Model 29, 100 (2023). https://doi.org/10.1007/s00894-023-05506-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00894-023-05506-7

Keywords

Search

Navigation