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In silico prediction of deleterious non-synonymous SNPs in STAT3 Cover

In silico prediction of deleterious non-synonymous SNPs in STAT3

Asian Biomedicine
Volume 17 (2023): Issue 4 (August 2023)
By: Athira Ajith and  Usha Subbiah  
Open Access
|Oct 2023

Figures & Tables

Figure 1.

Evolutionary conservancy of STAT3 by ConSurf server. The high-risk nsSNPs are denoted by black boxes. nsSNPs, non-synonymous single nucleotide polymorphisms; STAT, signal transducer and activator of transcription factors.
Evolutionary conservancy of STAT3 by ConSurf server. The high-risk nsSNPs are denoted by black boxes. nsSNPs, non-synonymous single nucleotide polymorphisms; STAT, signal transducer and activator of transcription factors.

Figure 2.

Structural variation of the wild-type and mutant residues by Project HOPE. The wild-type residue is presented as green and the mutant residue is shown in red.
Structural variation of the wild-type and mutant residues by Project HOPE. The wild-type residue is presented as green and the mutant residue is shown in red.

Figure 3.

Secondary structure prediction and calculations using SOPMA. The SOPMA program predicts the secondary structure of the STAT3 protein. The black boxes represent wild amino acids that might be altered by STAT3 pathogenic nsSNPs. Alpha helix, extended strand, beta turn, and random coil are all represented by the letters “h,” “e,” “t,” and “c,” respectively. nsSNPs, non-synonymous single nucleotide polymorphisms; STAT, signal transducer and activator of transcription factors.
Secondary structure prediction and calculations using SOPMA. The SOPMA program predicts the secondary structure of the STAT3 protein. The black boxes represent wild amino acids that might be altered by STAT3 pathogenic nsSNPs. Alpha helix, extended strand, beta turn, and random coil are all represented by the letters “h,” “e,” “t,” and “c,” respectively. nsSNPs, non-synonymous single nucleotide polymorphisms; STAT, signal transducer and activator of transcription factors.

Figure 4.

Protein–protein interaction network of STAT3 using STRING server showing strong functional association with EP300, PIAS3, IL10RA, JAK1, JAK2, EGFR, HSP90AA1, SRC, and homeobox protein NANOG. A weak interaction has been observed for HIF1A. EGFR, epidermal growth factor receptor; EP300, histone acetyltransferase p300; HIF1A, hypoxia-inducible factor 1-alpha; HSP90AA1, heat shock protein HSP 90-alpha; IL10RA, interleukin-10 receptor; JAK, Janus kinases; PIAS3, E3 SUMO-protein ligase; SRC, proto-oncogene tyrosine-protein kinase; STAT, signal transducer and activator of transcription factors; STRING, Search Tool for the Retrieval of Interacting Genes/Proteins.
Protein–protein interaction network of STAT3 using STRING server showing strong functional association with EP300, PIAS3, IL10RA, JAK1, JAK2, EGFR, HSP90AA1, SRC, and homeobox protein NANOG. A weak interaction has been observed for HIF1A. EGFR, epidermal growth factor receptor; EP300, histone acetyltransferase p300; HIF1A, hypoxia-inducible factor 1-alpha; HSP90AA1, heat shock protein HSP 90-alpha; IL10RA, interleukin-10 receptor; JAK, Janus kinases; PIAS3, E3 SUMO-protein ligase; SRC, proto-oncogene tyrosine-protein kinase; STAT, signal transducer and activator of transcription factors; STRING, Search Tool for the Retrieval of Interacting Genes/Proteins.

Figure 5.

3D model and binding site residues for domain 1 predicted by RaptorX.
3D model and binding site residues for domain 1 predicted by RaptorX.

Figure 6.

Gene–gene interaction network of STAT3 gene shows physical and genetic interaction with nuclear factor kappa B subunit 1 (NFKB1Z) and mitogen-activated protein kinase kinase 5 (MAP2K5), EGFR, and signal transducer and activator of transcription 1 (STAT1). EGFR, epidermal growth factor receptor; STAT, signal transducer and activator of transcription factors.
Gene–gene interaction network of STAT3 gene shows physical and genetic interaction with nuclear factor kappa B subunit 1 (NFKB1Z) and mitogen-activated protein kinase kinase 5 (MAP2K5), EGFR, and signal transducer and activator of transcription 1 (STAT1). EGFR, epidermal growth factor receptor; STAT, signal transducer and activator of transcription factors.

Figure 7.

3D structure prediction of STAT3 by AlphaFold. STAT, signal transducer and activator of transcription factors.
3D structure prediction of STAT3 by AlphaFold. STAT, signal transducer and activator of transcription factors.

Figure 8.

Visual representation of protein flexible conformation based on the vibrational entropy difference (ΔΔS) and the interatomic interaction between wild-type and mutant structures on STAT3 structure. Amino acids colored according to the vibrational entropy change upon mutation. BLUE represents a rigidification of the structure and RED a gain in flexibility. WT and MT residues are depicted as light-green sticks alongside the surrounding residues that are involved in any form of interaction.
Visual representation of protein flexible conformation based on the vibrational entropy difference (ΔΔS) and the interatomic interaction between wild-type and mutant structures on STAT3 structure. Amino acids colored according to the vibrational entropy change upon mutation. BLUE represents a rigidification of the structure and RED a gain in flexibility. WT and MT residues are depicted as light-green sticks alongside the surrounding residues that are involved in any form of interaction.

List of nsSNPs of STAT3 gene predicted as deleterious by different bioinformatics tools

S. No.rs IDAllelesAmino acid changeSIFT (score)Polyphen (Humvar) (score)PANTHERSNP & GO (RI)PROVEAN (score)PHD -SNP (RI)MUTANT I DDG value (<0)
1rs145786768C/AV507FDeleterious (0.004)Probably damaging (0.990)Probably damagingDisease (9)Deleterious (−3.744)Disease (6)Decrease (−2.49)
2rs193922716G/AR335WDeleterious (0)Probably damaging (0.996)Probably damagingDisease (3)Deleterious (−5.816)Neutral (1)Decrease (−0.36)
3rs193922717C/TE415KDeleterious (0.003)Probably damaging (0.955)Probably damagingDisease (5)Deleterious (−3.097)Neutral (0)Decrease (−1.00)
4rs193922719T/AK591MDeleterious (0.002)Possibly damaging (0.751)Probably damagingDisease (8)Deleterious (−4.949)Disease (6)Decrease (−0.13)
5rs1803125G/TQ32KDeleterious (0.025)Possibly damaging (0.868)Probably damagingDisease (0)Neutral (−1.975)Disease (3)Decrease (−0.41)
6rs11547455G/AS629FDeleterious (0.001)Possibly damaging (0.481)Probably damagingDisease (5)Deleterious (−3.097)Disease (1)Increase (0.64)
7rs11547455G/AS727FDeleterious (0.002)Probably damaging (0.974)Probably damagingNeutral (0)Deleterious (−3.858)Neutral (1)Decrease (−0.20)
8rs374063766C/GQ198HDeleterious (0.035)Probably damaging (0.965)Probably damagingNeutral (3)Neutral (−1.942)Neutral (3)Decrease (−0.82)
9rs11547455G/AS727FDeleterious (0.002)Probably damaging (0.974)Probably damagingNeutral (0)Deleterious (−3.858)Neutral (1)Decrease (−0.20)

Analysis of evolutionary conservation profile of high-risk nsSNPs of STAT3 by ConSurf

Amino acid changeConservation scoreBuried/exposedFunctional/structural
V507F8Buried-
R335W9ExposedFunctional
E415K8Exposed-
K591M9ExposedFunctional
F561Y8ExposedFunctional
Q32K7Exposed-

Prediction of protein stability using DynaMut server

Amino acid changeStability-based predictionΔ Vibrational entropy energy
ΔΔG kcal/molNMA-based predictions ΔΔG ENCoMOther structure-based predictionsΔΔSVib ENCoM (kcal/mol/K)Flexibility
ΔΔG mCSM (kcal/mol)DDG SDM (kcal/mol)ΔΔG DUET (kcal/mol)
Q32K0.087 (Stabilizing)−0.009 kcal/mol (Destabilizing)−0.453 (Destabilizing)0.030 (Stabilizing)−0.019 (Destabilizing)0.012Increase of molecule flexibility
F561Y−0.705 (Destabilizing)−0.089 (Destabilizing)−0.673 (Destabilizing)−1.030 (Destabilizing)−0.560 (Destabilizing)0.111Increase of molecule flexibility
K591M0.057 (Stabilizing)0.016 (Destabilizing)0.335 (Stabilizing)0.130 (Stabilizing)0.485 (Stabilizing)−0.019Decrease of molecule flexibility
E415K0.107 (Stabilizing)0.023 (Destabilizing)−0.461 (Destabilizing)−0.150 (Destabilizing)−0.062 (Destabilizing)−0.029Decrease of molecule flexibility
V507F0.627 (Stabilizing)0.195 (Destabilizing)−1.244 (Destabilizing)−1.190 (Destabilizing)1.458 (Destabilizing)−0.244Decrease of molecule flexibility
R335W0.050 (Stabilizing)−0.172 (Destabilizing)−0.198 (Destabilizing)−0.010 (Destabilizing)−0.447 (Destabilizing)0.215Increase of molecule flexibility

NetsurfP-2_0 prediction based on relative solvent accessibility, stability, and secondary structure prediction

Amino acid changeNetsurfP-2.0
Class assignmentRSAASASecondary structurePhiPsi
V507FBuried13%20 Åα helix−64°−44°
R335WExposed44%101 ÅCoil−110°137°
E415KExposed52%90 ÅStrand/β sheet−108°137°
K591MExposed37%77 Åα helix−57°−41°
E594KBuried6%10 Åα helix−66°−41°
F561YBuried4%8 Åα helix−60°−38°
R609SBuried9%22 ÅStrand/β sheet−112°132°
DOI: https://doi.org/10.2478/abm-2023-0059 | Journal eISSN: 1875-855X | Journal ISSN: 1905-7415
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Language: English
Page range: 185 - 199
Published on: Oct 18, 2023
Published by: Chulalongkorn University
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year
Keywords:
deleterious,
In silico,
prediction,
single nucleotide polymorphism
Related subjects:
Medicine,
Assistive professions, nursing,
Basic medical science,
Basic medical science, other,
Clinical medicine,
Clinical medicine, other

© 2023 Athira Ajith, Usha Subbiah, published by Chulalongkorn University
This work is licensed under the Creative Commons Attribution 4.0 License.

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