Cited by 17Genomics and Rare DiseasesProtein Structure and DynamicsGenetics and Neurodevelopmental Disorders

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Structural Protein Effects Underpinning Cognitive Developmental Delay of the PURA p.Phe233del Mutation Modelled by Artificial Intelligence and the Hybrid Quantum Mechanics–Molecular Mechanics Framework

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López-Rivera, Juan Javier, Rodríguez-Salazar, Luna, Soto-Ospina, Alejandro, Estrada-Serrato, Carlos, Serrano, David, Chaparro-Solano, Henry Mauricio, Londoño, Olga, Rueda, Paula A., Ardila, Geraldine, Villegas-Lanau, Andrés, Godoy-Corredor, Marcela, Cuartas, Mauricio, Vélez, Jorge I., Vidal, Oscar M., Isaza-Ruget, Mario A., Arcos-Burgos, Mauricio·2022·Brain Sciences

Published version of a preprint

Abstract

A whole-exome capture and next-generation sequencing was applied to an 11 y/o patient with a clinical history of congenital hypotonia, generalized motor and cognitive neurodevelopmental delay, and severe cognitive deficit, and without any identifiable Syndromic pattern, and to her parents, we disclosed a de novo heterozygous pathogenic mutation, c.697_699del p.Phe233del (rs786204835)(ACMG classification PS2, PM1, PM2, PP5), harbored in the PURA gene (MIM*600473) (5q31.3), associated with Autosomal Dominant Mental Retardation 31 (MIM # 616158). We used the significant improvement in the accuracy of protein structure prediction recently implemented in AlphaFold that incorporates novel neural network architectures and training procedures based on the evolutionary, physical, and geometric constraints of protein structures. The wild-type (WT) sequence and the mutated sequence, missing the Phe233, were reconstructed. The predicted local Distance Difference Test (lDDT) for the PURAwt and the PURA–Phe233del showed that the occurrence of the Phe233del affects between 220–320 amino acids. The distortion in the PURA structural conformation in the ~5 Å surrounding area after the p.Phe233del produces a conspicuous disruption of the repeat III, where the DNA and RNA helix unwinding capability occurs. PURA Protein–DNA docking corroborated these results in an in silico analysis that showed a loss of the contact of the PURA–Phe233del III repeat domain model with the DNA. Together, (i) the energetic and stereochemical, (ii) the hydropathic indexes and polarity surfaces, and (iii) the hybrid Quantum Mechanics–Molecular Mechanics (QM–MM) analyses of the PURA molecular models demarcate, at the atomic resolution, the specific surrounding region affected by these mutations and pave the way for future cell-based functional analysis. To the best of our knowledge, this is the first report of a de novo mutation underpinning a PURA syndrome in a Latin American patient and highlights the importance of predicting the molecular effects in protein structure using artificial intelligence algorithms and molecular and atomic resolution stereochemical analyses.

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Figures

Figure 1 (a) De novo heterozygous mutation found in the proband, c.697_699del (p.Phe233del), NM_005859.5, PURA (MIM*600473), located at Chr5:139,494,453-139,494,455 (rs786204835). This deletion causes the loss of Phenylalanine at residue 233 of the protein (in-frame), codon located from position 697 to 699 of the cDNA. (b) β-sheet composition with three Phenylalanine expansions: Phe231 (red), Phe232 (green), and Phe 233 (magenta). (c) Phe233 shows its hydrogens in a #D conformation (magenta arrow). (d) Phe233 polar contact measurements are less than 4 Å (magenta arrow).
Figure 1 (a) De novo heterozygous mutation found in the proband, c.697_699del (p.Phe233del), NM_005859.5, PURA (MIM*600473), located at Chr5:139,494,453-139,494,455 (rs786204835). This deletion causes the loss of Phenylalanine at residue 233 of the protein (in-frame), codon located from position 697 to 699 of the cDNA. (b) β-sheet composition with three Phenylalanine expansions: Phe231 (red), Phe232 (green), and Phe 233 (magenta). (c) Phe233 shows its hydrogens in a #D conformation (magenta arrow). (d) Phe233 polar contact measurements are less than 4 Å (magenta arrow).CC BY · PubMed Central
Figure 2 (a) PURAwt AlphaFold modeling showing the three principal purine-rich (PUR) elements (in white). Magenta arrows show the DNA docking site regions forming a spanner head that will interact with the DNA. (b) Zoom of the protein–DNA docking site with three principal residues in contact with the DNA molecule (c-MYC promoter region), THR 252, TYR 253, and ARG 254. (c) Zoom and 180-degree rotation to visualize the opposite protein–DNA docking site with its three principal residues in contact with the DNA molecule (c-MYC promoter region), VAL 149, GLU 151, and LYS 154.
Figure 2 (a) PURAwt AlphaFold modeling showing the three principal purine-rich (PUR) elements (in white). Magenta arrows show the DNA docking site regions forming a spanner head that will interact with the DNA. (b) Zoom of the protein–DNA docking site with three principal residues in contact with the DNA molecule (c-MYC promoter region), THR 252, TYR 253, and ARG 254. (c) Zoom and 180-degree rotation to visualize the opposite protein–DNA docking site with its three principal residues in contact with the DNA molecule (c-MYC promoter region), VAL 149, GLU 151, and LYS 154.CC BY · PubMed Central
Figure 3 The PURA–DNA comparative analyses show that DNA docking damages PURA Protein–DNA docking. (a) In silico analysis by HDOCK shows 10 top models between PURA-WT AlphaFold and previously reported DNA promoter regions of the c-Myc. (b) HDOCK docking analysis between AlpahFold predicted PURA–Phe233del protein and the c-Myc DNA promoter regions.
Figure 3 The PURA–DNA comparative analyses show that DNA docking damages PURA Protein–DNA docking. (a) In silico analysis by HDOCK shows 10 top models between PURA-WT AlphaFold and previously reported DNA promoter regions of the c-Myc. (b) HDOCK docking analysis between AlpahFold predicted PURA–Phe233del protein and the c-Myc DNA promoter regions.CC BY · PubMed Central
Figure 4 Hydrophobicity analysis (Molecular Lipophilicity Potential, MLP maps) of the (a) PURAwt, and (b) PURAPhe233del system. The analysis shows that in the wild type variant, the Phe 233 is harbored in a golden region (hydrophobic), implicating that it plays a significant role in the 3D arrangement, while the hydrophobicity changes once the deletion occurs. This is also appreciated in (c), which depicts the hydrophobicity index plot zooming in on the 233-amino-acid region (see text).
Figure 4 Hydrophobicity analysis (Molecular Lipophilicity Potential, MLP maps) of the (a) PURAwt, and (b) PURAPhe233del system. The analysis shows that in the wild type variant, the Phe 233 is harbored in a golden region (hydrophobic), implicating that it plays a significant role in the 3D arrangement, while the hydrophobicity changes once the deletion occurs. This is also appreciated in (c), which depicts the hydrophobicity index plot zooming in on the 233-amino-acid region (see text).CC BY · PubMed Central
Figure 5 Functional comparison of the connective and electronic structures for the QM/MM simulation of PURAwt and PURA–Phe233del. (a) For PURAwt, the angle between amino acids F232-F233 was 37.57°, while for F233-D234, the bond angle distancing the CH2 carbons constituting the side chain by 7.215 Å was 113.84° (reference distance of the amino acids in the β-sheets). (b) For PURA–Phe233del, the bond angle between F231-F232 is 35.51°, and the bond angle between F232-D233 changes to 112.47°, indicating that the binding distance for the reference structure decreases to 6.103 Å, which affects the accessible area of the structure. (c) Electrostatic potential maps of the PURAwt β-sheets involved. The area and volume values for the electronic region in the region undergoing variation were 3032.37 Å2 and 2930.94 Å3, respectively. (d) Electrostatic potential maps of the PURA–Phe233del β-sheets. The area and volume values for the electronic region in the region undergoing variation change to 2852.30 Å2 and 2773.77 Å3, respectively, which is in agreement with the loss of enough electronic topology contributed by the Phe233 amino acid and its aromaticity.
Figure 5 Functional comparison of the connective and electronic structures for the QM/MM simulation of PURAwt and PURA–Phe233del. (a) For PURAwt, the angle between amino acids F232-F233 was 37.57°, while for F233-D234, the bond angle distancing the CH2 carbons constituting the side chain by 7.215 Å was 113.84° (reference distance of the amino acids in the β-sheets). (b) For PURA–Phe233del, the bond angle between F231-F232 is 35.51°, and the bond angle between F232-D233 changes to 112.47°, indicating that the binding distance for the reference structure decreases to 6.103 Å, which affects the accessible area of the structure. (c) Electrostatic potential maps of the PURAwt β-sheets involved. The area and volume values for the electronic region in the region undergoing variation were 3032.37 Å2 and 2930.94 Å3, respectively. (d) Electrostatic potential maps of the PURA–Phe233del β-sheets. The area and volume values for the electronic region in the region undergoing variation change to 2852.30 Å2 and 2773.77 Å3, respectively, which is in agreement with the loss of enough electronic topology contributed by the Phe233 amino acid and its aromaticity.CC BY · PubMed Central
Figure 6 (a) Predicted local Distance Difference Test (lDDT) for the PURA WT and (b) PURA–Phe233del-predicted structure deletion per amino acid using five different models via AlpahFold2. Models show that the occurrence of the Phe233del affects between 220–320 amino acids (red arrow). (c) A 3D reconstruction of the transcriptional activator protein Pur-alpha (PURA; Uniprot: Q00577) from the WT sequence using AlphaFold, focusing on the surrounding area of the Phe233 amino acid (in magenta; magenta arrow). (d) A 3D reconstruction of the PURA–Phe233del. Note the distortion (61.3 Å vs. 64.3 Å) in PURA structural conformation after the p.Phe233del occurs.
Figure 6 (a) Predicted local Distance Difference Test (lDDT) for the PURA WT and (b) PURA–Phe233del-predicted structure deletion per amino acid using five different models via AlpahFold2. Models show that the occurrence of the Phe233del affects between 220–320 amino acids (red arrow). (c) A 3D reconstruction of the transcriptional activator protein Pur-alpha (PURA; Uniprot: Q00577) from the WT sequence using AlphaFold, focusing on the surrounding area of the Phe233 amino acid (in magenta; magenta arrow). (d) A 3D reconstruction of the PURA–Phe233del. Note the distortion (61.3 Å vs. 64.3 Å) in PURA structural conformation after the p.Phe233del occurs.CC BY · PubMed Central
Figure 7 PURA–Phe233del disrupts DNA biding. (a) A molecular view of PURA Protein–DNA docking analysis showing three different HDOCK models between PURAwt AlphaFold and the c-Myc DNA promoter region. Magenta arrows indicate disruption of specific docking sites (in white; magenta arrows). (b) HDOCK docking analysis shows the c-Myc DNA binding disruption caused by the AlpahFold2 predicted PURA–Phe233del protein.
Figure 7 PURA–Phe233del disrupts DNA biding. (a) A molecular view of PURA Protein–DNA docking analysis showing three different HDOCK models between PURAwt AlphaFold and the c-Myc DNA promoter region. Magenta arrows indicate disruption of specific docking sites (in white; magenta arrows). (b) HDOCK docking analysis shows the c-Myc DNA binding disruption caused by the AlpahFold2 predicted PURA–Phe233del protein.CC BY · PubMed Central

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Cites

Research works printed but not linked: 51

  1. Tanaka, 2015, De novo mutations in PURA are associated with hypotonia and developmental delay, Mol. Case Stud., 1, a000356, 10.1101/mcs.a000356 · DOI
  2. Lalani, 2014, Mutations in PURA cause profound neonatal hypotonia, seizures, and encephalopathy in 5q31.3 microdeletion syndrome, Am. J. Hum. Genet., 95, 579, 10.1016/j.ajhg.2014.09.014 · DOI
  3. Hunt, 2014, Whole exome sequencing in family trios reveals de novo mutations in PURA as a cause of severe neurodevelopmental delay and learning disability, J. Med. Genet., 51, 806, 10.1136/jmedgenet-2014-102798 · DOI · Paper page
  4. Khalili, 2003, Pur Is Essential for Postnatal Brain Development and Developmentally Coupled Cellular Proliferation As Revealed by Genetic Inactivation in the Mouse, Mol. Cell. Biol., 23, 6857, 10.1128/MCB.23.19.6857-6875.2003 · DOI
  5. Wortman, 2010, Regulation of PURA gene transcription by three promoters generating distinctly spliced 5-prime leaders: A novel means of fine control over tissue specificity and viral signals, BMC Mol. Biol., 11, 1, 10.1186/1471-2199-11-81 · DOI
  6. White, 2009, Multiple roles for Purα in cellular and viral regulation, Cell Cycle, 8, 1, 10.4161/cc.8.3.7585 · DOI
  7. Hokkanen, 2012, Lack of Pur-alpha alters postnatal brain development and causes megalencephaly, Hum. Mol. Genet., 21, 473, 10.1093/hmg/ddr476 · DOI
  8. Reijnders, 2018, PURA syndrome: Clinical delineation and genotype-phenotype study in 32 individuals with review of published literature, J. Med. Genet., 55, 104, 10.1136/jmedgenet-2017-104946 · DOI
  9. Okamoto, 2017, Patient with a novel purine-rich element binding protein A mutation, Congenit. Anom., 57, 201, 10.1111/cga.12214 · DOI
  10. Shimojima, 2018, Infantile spasms related to a 5q31.2-q31.3 microdeletion including PURA, Hum. Genome Var., 5, 18007, 10.1038/hgv.2018.7 · DOI
  11. Bonaglia, 2015, Long-term follow-up of a patient with 5q31.3 microdeletion syndrome and the smallest de novo 5q31.2q31.3 deletion involving PURA, Mol. Cytogenet., 8, 89, 10.1186/s13039-015-0193-9 · DOI
  12. Qiao, 2019, Exome sequencing identified a de novo mutation of PURA gene in a patient with familial Xp22.31 microduplication, Eur. J. Med. Genet., 62, 103, 10.1016/j.ejmg.2018.06.010 · DOI
  13. Okorie, 2020, 1233 Mitochondrial Myopathy Making It Hard To Sleep! OSA management in Mitochondrial Myopathy with a variant in SNAPC4 and PURA genes, Sleep, 43, A470, 10.1093/sleep/zsaa056.1227 · DOI
  14. Spangenberg, 2021, Novel frameshift mutation in PURA gene causes severe encephalopathy of unclear cause, Mol. Genet. Genom. Med., 9, e1622, 10.1002/mgg3.1622 · DOI
  15. Mayorga, 2018, A frame-shift deletion in the PURA gene associates with a new clinical finding: Hypoglycorrhachia. Is GLUT1 a new PURA target?, Mol. Genet. Metab., 123, 331, 10.1016/j.ymgme.2017.12.436 · DOI
  16. 2020, A novel de novo mutation in the PURA gene associated with a new clinical finding: Large brainstem, J. Genet., 99, 7, 10.1007/s12041-019-1165-3 · DOI
  17. Senior, A.W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., and Green, T. (2020). AlphaFold. Nature, 577. · DOI · Paper page
  18. Al-Numan, H.H., Jan, R.M., Al-Saud, N.B.S., Rashidi, O.M., Alrayes, N.M., Alsufyani, H.A., Mujalli, A., Shaik, N.A., Mosli, M.H., and Elango, R. (2022). Exome Sequencing Identifies the Extremely Rare ITGAV and FN1 Variants in Early Onset Inflammatory Bowel Disease Patients. Front. Pediatr., 10. · DOI
  19. Buel, 2022, Can AlphaFold2 predict the impact of missense mutations on structure?, Nat. Struct. Mol. Biol., 29, 1, 10.1038/s41594-021-00714-2 · DOI · Paper page
  20. McKenna, 2010, The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data, Genome Res., 20, 1297, 10.1101/gr.107524.110 · DOI · Paper page
  21. Johar, 2015, Candidate gene discovery in autoimmunity by using extreme phenotypes, next generation sequencing and whole exome capture, Autoimmun. Rev., 14, 204, 10.1016/j.autrev.2014.10.021 · DOI
  22. Mastronardi, 2017, Genetics of non-syndromic childhood obesity and the use of high-throughput DNA sequencing technologies, J. Diabetes Complicat., 31, 1549, 10.1016/j.jdiacomp.2017.04.026 · DOI
  23. Landires, I., Núñez-Samudio, V., Fernandez, J., Sarria, C., Villareal, V., Córdoba, F., Apráez-Ippolito, G., Martínez, S., Vidal, O.M., and Vélez, J.I. (2020). Calpainopathy: Description of a Novel Mutation and Clinical Presentation with Early Severe Contractures. Genes, 11. · DOI
  24. Boguszewski, 2014, Whole Exome Sequencing of Extreme Morbid Obesity Patients: Translational Implications for Obesity and Related Disorders, Genes, 5, 709, 10.3390/genes5030709 · DOI
  25. Tayeh, 2022, Clinical pharmacogenomic testing and reporting: A technical standard of the American College of Medical Genetics and Genomics (ACMG), Genet. Med., 24, 759, 10.1016/j.gim.2021.12.009 · DOI
  26. Kearney, 2011, American College of Medical Genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants, Genet. Med., 13, 680, 10.1097/GIM.0b013e3182217a3a · DOI · Paper page
  27. Kalia, 2017, Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): A policy statement of the American College of Medical Genetics and Genomics, Genet. Med., 19, 249, 10.1038/gim.2016.190 · DOI
  28. Yan, 2020, The HDOCK server for integrated protein–protein docking, Nat. Protoc., 15, 1829, 10.1038/s41596-020-0312-x · DOI
  29. Bergemann, 1992, The HeLa Pur factor binds single-stranded DNA at a specific element conserved in gene flanking regions and origins of DNA replication, Mol. Cell. Biol., 12, 1257
  30. Bergemann, 1992, Sequence of cDNA comprising the human pur gene and sequence-specific single-stranded-DNA-binding properties of the encoded protein, Mol. Cell. Biol., 12, 5673
  31. Wortman, 2005, Mechanism of DNA binding and localized strand separation by Purα and comparison with Pur family member, Purβ, Biochim. Biophys. Acta Mol. Cell Res., 1743, 64, 10.1016/j.bbamcr.2004.08.010 · DOI
  32. Ma, 1994, Conservation in human and mouse Purα of a motif common to several proteins involved in initiation of DNA replication, Gene, 149, 311, 10.1016/0378-1119(94)90167-8 · DOI
  33. Haas, 1993, A developmentally regulated DNA-binding protein from mouse brain stimulates myelin basic protein gene expression, Mol. Cell. Biol., 13, 3103
  34. Studer, 2014, Assessing the local structural quality of transmembrane protein models using statistical potentials (QMEANBrane), Bioinformatics, 30, i505, 10.1093/bioinformatics/btu457 · DOI
  35. Benkert, 2008, QMEAN: A comprehensive scoring function for model quality assessment, Proteins: Struct. Funct. Bioinform., 71, 261, 10.1002/prot.21715 · DOI
  36. Laskowski, 1993, PROCHECK: A program to check the stereochemical quality of protein structures, J. Appl. Crystallogr., 26, 283, 10.1107/S0021889892009944 · DOI · Paper page
  37. Gasteiger, E., Hoogland, C., Gattiker, A., Wilkins, M.R., Appel, R.D., and Bairoch, A. (2005). The Proteomics Protocols Handbook-Chapter 52: Protein Identification and Analysis Tools on the ExPASy Server. Proteom. Protoc. Handb., 571–607. · DOI
  38. Pettersen, 2004, UCSF Chimera?A visualization system for exploratory research and analysis, J. Comput. Chem., 25, 1605, 10.1002/jcc.20084 · DOI
  39. Guex, 1997, SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modeling, Electrophoresis, 18, 2714, 10.1002/elps.1150181505 · DOI
  40. Humphrey, 1996, VMD: Visual molecular dynamics, J. Mol. Graph., 14, 33, 10.1016/0263-7855(96)00018-5 · DOI · Paper page
  41. Phillips, 2005, Scalable molecular dynamics with NAMD, J. Comput. Chem., 26, 1781, 10.1002/jcc.20289 · DOI · Paper page
  42. 2020, Redox mechanism of Trypanosoma cruzi Resistance to Nitro Prodrugs Benznidazole and Nifurtimox, Int. J. Bioinform. Comput. Biol., 5, 1
  43. Bedoya, 2021, Structural Predictive Model of Presenilin-2 Protein and Analysis of Structural Effects of Familial Alzheimer’s Disease Mutations, Biochem. Res. Int., 2021, 9542038
  44. Bedoya, 2021, Protein Predictive Modeling and Simulation of Mutations of Presenilin-1 Familial Alzheimer’s Disease on the Orthosteric Site, Front. Mol. Biosci., 8, 387
  45. Cano, 2021, Diffusion Mechanism Modeling of Metformin in Human Organic Cationic Amino Acid Transporter one and Functional Impact of S189L, R206C, and G401S Mutation, Front. Pharmacol., 11, 587590, 10.3389/fphar.2020.587590 · DOI
  46. Ahmadi, 2018, Multiscale modeling of enzymes: QM-cluster, QM/MM, and QM/MM/MD: A tutorial review, Int. J. Quantum Chem., 118, e25558, 10.1002/qua.25558 · DOI
  47. Dewar, 1985, Development and use of quantum mechanical molecular models. 76. AM1: A new general purpose quantum mechanical molecular model, J. Am. Chem. Soc., 107, 3902, 10.1021/ja00299a024 · DOI
  48. Dewar, M.J.S., Zoebisch, E.G., Healy, E.F., and Stewart, J.J.P. (1985). AM1: A New General Purpose Quantum Mechanical Molecular Model1. J. Am. Chem. Soc., 107. · DOI
  49. Baker, 2007, Role of aromatic amino acids in protein-nucleic acid recognition, Biopolymers, 85, 456, 10.1002/bip.20682 · DOI
  50. Molitor, 2021, The Molecular Function of PURA and Its Implications in Neurological Diseases, Front. Genet., 12, 638217, 10.3389/fgene.2021.638217 · DOI
  51. Grzybowska, 2012, Human intronless genes: Functional groups, associated diseases, evolution, and mRNA processing in absence of splicing, Biochem. Biophys. Res. Commun., 424, 1, 10.1016/j.bbrc.2012.06.092 · DOI

Metadata

Authors
López-Rivera, J. J., Rodríguez-Salazar, L., Soto-Ospina, A., Estrada-Serrato, C., Serrano, D., Chaparro-Solano, H. M., Londoño, O., Rueda, P. A., Ardila, G., Villegas-Lanau, A., Godoy-Corredor, M., Cuartas, M., Vélez, J. I., Vidal, O. M., Isaza-Ruget, M. A., & Arcos-Burgos, M.
Affiliations
  • INPAC Research Group, Fundación Universitaria Sanitas, Bogotá 111321, Colombia
  • Grupo de Bioinformática, Laboratorio de Clínica Colsanitas, Bogotá 110221, Colombia
  • Universidad de Antioquia (CO)
  • Grupo de Genética Médica, Clínica Universitaria Colombia y Clínica Pediátrica Colsanitas, Bogotá 111321, Colombia
  • Genética Molecular (GenMol), Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia, Medellín 050012, Colombia
  • Laboratorio Clínico y de Patología, Clínica Colsanitas, Bogotá 110221, Colombia
  • Grupo de Investigación Estudios en Psicología, Departamento de Psicología, Escuela de Humanidades, Universidad EAFIT, Medellín 050022, Colombia
  • Universidad del Norte, Barranquilla 080001, Colombia
  • Universidad del Norte (CO)
  • Fundación Universitaria Sanitas (CO)
  • Grupo de Investigación en Psiquiatría (GIPSI), Departamento de Psiquiatría, Instituto de Investigaciones Médicas, Facultad de Medicina, Universidad de Antioquia, Medellín 050012, Colombia
Venue
Brain Sciences
Publisher
MDPI AG
Published
2022-06-30
Volume
12
Issue
7
Pages
871
ISSN
2076-3425 (ISSN-L)
OpenAlex
W4283757303
Cited by
17
References
3
Citations by year
2026: 2 · 2025: 1 · 2024: 9 · 2023: 4
FWCI
2.10
Type
journal article
Language
en
Open access
Locations
  • Brain Sciences (publishedVersion, cc-by)
  • Preprints.org (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Institutional Repository University of Antioquia (University of Antioquia) (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Keralty
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
Keywords
PURA gene, de novo mutations, congenital hypotonia, neurodevelopmental delay, protein structure prediction, AlphaFold, protein-DNA docking

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