An In Silico Strategy against Adam’s Oliver Syndrome by Predicting RNAi...

[Full title: An In Silico Strategy against Adam’s Oliver Syndrome by Predicting RNAi Molecules against Dominant Genes by Suppressing Rho GTPases]

[Find the meaning and references behind the names: Oliver, Dhanya, Cds, Class, India, Aim, Rna, Sirna, Gene, Rho, Ramachandran, Janga, Block, Krishna, Show, Adam, Central, Dock, Aos, Narasimha, Six, Original, Mirna, Data, Major, Far, Genes, Reddy, Rac, Server, Sep, Cell, Adams, Jul, Switch, Due, Dll, Guntur, Study, Heat, Strong, Target, Early, Neeraj]

Asian Journal of Pharmaceutic s • Jul-Sep 2022 • 16 (3) | 314 An In Silico Strategy against Adam’s Oliver Syndrome by Predicting RNAi Molecules against Dominant Genes by Suppressing Rho GTPases S. F. Choragudi*, M. S. Ekklesia Sesham, Narasimha Vakkalagadda, Neeraj Krishna Vedantam, Devendranadh Reddy Janga, Dhanya Koneru, Angirekula Harisairam, Krishna Keerthika Oruganti Department of Biotechnology, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India Abstract Aim: To analyse the In Silico Strategy against Adam’s Oliver Syndrome by Predicting RNAi Molecules against Dominant Genes by Suppressing Rho GTPases. Methods: There are six genes known (ARHGAP 31, DLL 4, NOTCH 1, RBPJ, DOCK 6, and EOGT) reported so far, which can cause this syndrome. We retrieved CCDS and CDS sequences of each gene from the NCBI database and multiple sequence alignment was performed using ClustalΩ. After target identification, we chose ARHGAP 31 as the target gene, as it is a major cause of cutis aplasia, also the regulator of Rho GTPase activity. siRNA and miRNA were designed using Invitrogen Block-iT. Results: The Proteins related to ARHGAP 31 were obtained using Blastx. GC content analysis of ARHGAP 31 using ENDMEMO was found to be 54.55%, and RNA-RNA interaction was interpreted using IntaRNA. Heat capacity, c = 17.88025 J/kg ºk, was analyzed using OligoCalc server and prediction of secondary structure was done using Modeller 9.22 and SAVES. The dope score, analyzed from the RC plot, for qseq 4.B 99990004 is –48,617.11328. The Z-score value was calculated using ProSA. The Z-score value for the modeled protein is 9.12. Conclusion: Study indicates that by suppressing Rho GTPase activity of ARHGAP 31 gene, we can reduce the occurrence of AOS during early embryonic stages Keywords: Aplasia cutis congenita, clustal Ω , inherited congenital disorder, ramachandran plot, RNA-RNA interactions, terminal transverse limb defects Address for correspondence: S. F. Choragudi, Department of Biotechnology, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur - 522 502, Andhra Pradesh, India E-mail: felicebt@kluniversity.in Received: 30-04-2022 Revised: 08-08-2022 Accepted: 21:08:2022 INTRODUCTION T he Adams-Oliver syndrome (AOS) is a rare heterogeneous congenital incongruity interpreted by the presence of aplasia cutis congenita and with transverse terminal limb defects. Apart from these two, cutis marmorata and other anomalies include cardiovascular, respiratory, central nervous system, and orofacial defects were observed. These anomalies are caused due to mutations in six genes [1] The genes identified were ARHGAP 31, NOTCH 1, EOGT, DOCK 6, DLL 4, and RBPJ ARHGAP 31, located on chromosome 3, encodes a Rho GTPase-Activating Protein 31. Signaling by Rho GTPases and signaling by GPCR are among the associated pathways of this gene. This gene functions as an activating protein for RAC 1 and CDC 42. ARHGAP 31 acts as a molecular switch that controls many aspects of cell activity through the mechanism of cycling between two conformational forms ORIGINAL AR TICLE

[Find the meaning and references behind the names: Find, Four, Less, Key, Edema, Active, Single, Body, Gov, Loss, Mash, Liver, Fate, Development, Turn, Fisher, Heart, Blood, High, Few, Mass, Manner, Play, Chemical, Role, Bone, Factor, Tree, Bones, Skull, Nih, Pass, Common, Stretch]

Choragudi, et al. : Bioinformatics approach towards Adam’s Oliver syndrome Asian Journal of Pharmaceutic s • Jul-Sep 2022 • 16 (3) | 315 Between the active and inactive cycles of gene are controlled by Cdc 42/Rac 1 and guanine nucleotide exchange factors pathways are crucial for development processes of limbs and scalp, and their signaling directly impacts on cell migration and proliferation in a cell-specific manner. Although CdGAPs function in vascular development is unknown, its mutation causes superficial vessel defects and subcutaneous edema [2] The single-pass transmembrane receptor protein is known as notch receptor. Signaling pathways stimulated by notch proteins play crucial role in the developmental events of many tissues all over the body, as well as the heart, bones, muscles, liver, and blood cells, amidst other anomalies. Mutations in Notch signaling have mainly depicted with bone and vascular disorders and cardiac malformations. Notch genes play a key role in determining cell fate. Notch pathway has four receptors, namely, NOTCH 1, NOTCH 2, NOTCH 3, and NOTCH 4. Mutations in NOTCH 1 are the most common cause of AOS The EOGT gene translates to an enzyme, which acts in the lumen of the endoplasmic reticulum, by transferring a molecule called N-acetyl glucosamine to modify eukaryotic growth factor (EGF)-like domains, including the Notch receptors, in turn, regulating development signaling. Very few proteins are altered by EOGT protein which is known, but it is known that NOTCH proteins can be modified by EOGT [3] DOCK 6 delivers instructions for a protein called guanine nucleotide exchange factor, which is known as activating proteins called GTPases. They play a significant role in cells by their chemical signaling. GTPases such as Cdc 42 and Rac 1 are activated through the presence of DOCK 6 protein by the attached GDP which is exchanged from GTP. Once Cdc 42 and Rac 1 became active, the signals are transmitted which are crucial for various events of embryonic developments. This type of regulation of GTPases is due to DOCK 6 protein in the developmental events of the skull, limbs, and heart. DOCK 6 conjointly performs a task within the development of fibers (axons) that stretch of nerve cells [4] MATERIALS AND METHODS Retrieval of CCDS and CDS sequences The fastA formats of CCDS and CDS sequences were retrieved from NCBI [https://www.ncbi.nlm.nih.gov/] with accession numbers – ARHGAP 31 (NG_007665), DLL 4 (NG_046974), NOTCH 1 (NG_007458), RBPJ (NG_030343), DOCK 6 (NG_031953), and EOGT (NG_042829) Phylogenetic analysis The fastA format CCDS and CDS sequences were retrieved and, with the help of ClustalΩ, [5] multiple sequence alignment was performed to find the evolutionary relationship Target identification From the analysis of the phylogenetic tree obtained from ClustalΩ, ARHGPA 31 gene was considered as the target gene due to its high functionality siRNA and miRNA designing siRNA and miRNA were designed by taking CCDS sequences of the genes as input which is responsible for AOS with the help of Invitrogen BLOCK-iT by Thermo Fisher [https:// rnaidesigner.thermofisher.com/rnaiexpress/] Evaluation of result Sequence retrieval Protein BLAST was performed using BLASTx [https:// blast.ncbi.nlm.nih.gov/Blast.cgi] and based on E values and percent identity hits were retrieved GC content GC content of the nucleotide sequence of ARHGAP 31 gene was calculated using the ENDMEMO [http://www ENDMEMO.com/] RNA-RNA interaction RNA-RNA interaction was done with the help of IntaRNA [6] by taking miRNA sequences having less than 50% GC content against the target protein sequence Heat capacity Using OligoCalc, [7] the heat capacity was determined for the sequence of interest. The formula used to calculate heat capacity c=Q/m Δ T Where, Q= heat loss, Δ T= temperature, and m= mass Prediction of secondary structure 3 D structures of proteins were predicted using MODELLER 9.22 software [8] in which totally five structures were predicted based on dope scope; the structures in PDB [9] format were considered for further analysis.

[Find the meaning and references behind the names: Files, Mbi, Edu, Ata, Energy, Table, Atat]

Choragudi, et al. : Bioinformatics approach towards Adam’s Oliver syndrome Asian Journal of Pharmaceutic s • Jul-Sep 2022 • 16 (3) | 316 Evaluation of PDB using RC plot Energy was computed for the PDB files obtained from the Modeller 9.22 software. The energy values for the PDB files computed before and after energy minimization Based on energy value, the stable protein structure is finalized and analysis of the protein is done using SAVES server [HTTPS://SERVICESN.MBI.UCLA.EDU/SAVES/] and Ramachandran plot was obtained from the PROCHECK [10] RESULTS AND DISCUSSION Retrieval of CCDS and CDS sequences The FastA formats of CCDS and CDS of all the six genes involved in the Adams-Oliver syndrome are retrieved from NCBI and provided in Table 1 CCDS of all genes ARHGAP 31 AT G A A G A A C A A G G G T G C TA A G C A G A A G C T G A A A C G A A A G G G A G C C G C C A G C G C G T T T G G C T G T G A C C T G A C G G A G T AT C T G G A A A G C T C G G G A C A G G AT G T T C C ATA C G . G A G A C C T C A A C C A G C T G T T T T T A C CAGCCTCAGCGGAGATCAGTAATTCTGGATG GAAGAAGTGGGAG GCAAATAGAATGA DDL 4 AT G G C G G C A G C G T C C C G G A G C G C C T C T G G C T G G G C G C T A C T G C T G C T G G T G G C A C T T T G G C A G C A G C G C G C G G C C G G C T C C G G C G T C T T C C A G C T G C C C A G T C T G T G T G T T T G ATAT C A G A G G A G A G G A AT G A A TGTGTCATTGCCACGGAGGTAT AA DOCK 6 AT G G C T G C C T C C G A G C G C C G C G C C T T C G C G C A C A A G AT C A A C A G G A C G G T G G C C G C A G A G G T G C G G A A G C A G G T G T C C C G G G A A C G C A G T G G C T C C C C C C A C T C C A G C A C C C C A G C T G A T G G C A C C C A C C C C A C C C G G C C T C A G G A A C T C C T T G A A C A G A G C A A G T T T C C G A A AGGCAGACCTCTGA EOGT A T G T T A A T G T T G T T T G T C T T T G G A G T C T T A C T T C A T G A A G T C T C A C T G A G T G G T C A G A A T G A A G C T C C T C C T A A T A C T C A C A G C A T T C C A G G C G A A C C T C T G T A T A A C T A T G C G A C C A C G T A T T G C A A C A C C C A A A G T G G C C A TTTAAGAAGAAACATGATGAGC TATAA NOTCH 1 A T G C C G C C G C T C C T G G C G C C C C T G C T C T G C C T G G C G C T G C T G C C C G C G C T C G C C G C A C G A G G C C C G C G A T C C G A G G G C G T C T C C A G C C C T C C C A C C A G C A T G C A G T C C C A G A T C G C C C G C A T T C C G G A G G C C T T C AAGTAA RBPJ A T G C G A A A T T A T T T A A A A G A G C G A G G G G A T C A A A C A G T A C T T A T T C T T C A T G C A A A A G T T G C A C A G A A G T C A T A T G G A A A T G A A A A A A G G T T T T T T T G C C C A C C T C C T A C A G C G A G G G A A G T T A C A C A A A C G C C A G C A C A A A T T C A A C C A GTGTCACATCATCTACAGCCA CAGTGGTATCCTAA Table 1: Genes and retrieved CDS accession no. with version Gene name ARHGAP 31 DLL 4 DOCK 6 EOGT NOTCH 1 RBPJ Accession and version AB 033030.1 AB 036931.1 AB 037816.2 AJ 868234.1 AB 209873.1 AK 302230.1 AK 293726.1 AB 043894.1 AK 295664.1 AK 091089.1 AF 308602.1 AK 303244.1 BC 112163.1 AF 253468.1 AK 316063.1 AK 126187.1 AK 000012.1 BC 064976.1 BC 112165.1 AK 313831.1 BC 008335.1 AK 290356.1 CR 457221.1 BC 020780.1 AY 358894.1 BC 051330.1 AK 294101.1 M 73980.1 D 14041.1 BC 106950.2 BC 146786.1 AK 304102.1 L 07872.1 BC 028935.1 L 07874.1 BC 060887.1 L 07876.1 BX 640821.1 KC 347596.1

[Find the meaning and references behind the names: Stage, Start, Cases, Main, Match, Shown]

Choragudi, et al. : Bioinformatics approach towards Adam’s Oliver syndrome Asian Journal of Pharmaceutic s • Jul-Sep 2022 • 16 (3) | 317 Phylogenetic tree analysis Multiple sequence alignment was done to know the sequence homology between the genes, first, individual multiple sequence alignment was performed for the CDS sequence of each gene separately, and later, total multiple sequence alignment was done for all the genes, as shown in Figure 1 Target identification On phylogenetic analysis observation, ARHGPA 31 is considered as the main target as mutations in ARHGAP 31 which is the major cause of cutis aplasia (this condition was observed in almost all AOS cases) and this gene is also the regulator of Rho GTPase activity, especially during the forming of the heart skull and limbs in embryonic development stage siRNA and miRNA designing Invitrogen BLOCK-iT by Thermo Fisher used for designing siRNA and miRNA as both regulate the gene expression, the sequences are tabulated in Tables 2 and 3 Evaluation of result Blastx The sequence homology of the gene was detected by performing protein blast using Blastx. Protein homology had recognized that percent identity alone was an inferior method of differentiating homology among proteins compared, based on E values and percentage identity, maximum hits were retrieved Proteins obtained from blastx based on % identity Gene: ARHGAP 31 Protein accession no 3 IUG_A, 5 C 5 S_A Percent identity 68.00%, 36.31 E value 3 e-90, 1 e-20 GC content Using ENDMEMO, the GC content of ARHGAP 31 gene was calculated P 31 and the GC content of the ARHGAP 31 gene is 54.55% Figure 1: Complete phylogenetic tree analysis of all the six genes Table 2: siRNA designed for ARHGAP 31 S. No. Start Sequence GC% Tuschl’s pattern match 1 534 CCTCAGGTCTAAAGAAATT 36.85 2 882 GCGAAAGCTCTCCAGTAAA 47.37 B 3 1015 GCTACTATCCGACCAGCTA 52.64 1015 4 1778 CCTTGAGCTCTCAACATTT 42.11 1778 5 2036 CCAGCCCAATTCAGCCTAT 52.64 BD 6 2601 GGTTGAGATCGTCTCACAA 47.37 B 7 2652 GCCTTCAGACTGTGACGAA 52.64 B 8 2855 GCCATTCTCTAGATAGCAA 42.11 B 9 2971 GCACCCAGGAGAGAGATTA 52.64 10 4030 CCTCAGAGCCTAATCTTAT 42.11 BD

[Find the meaning and references behind the names: Wise, Mol, Seed, Fly, Swiss, Cal]

Choragudi, et al. : Bioinformatics approach towards Adam’s Oliver syndrome Asian Journal of Pharmaceutic s • Jul-Sep 2022 • 16 (3) | 318 RNA-RNA interaction RNA-RNA interactions analysis was done with the help of IntaRNA by taking miRNA against the target gene [Figure 2 ] sequence and the following results were obtained and tabulated in Table 4 Values related to the selected interaction RNA 1 Energy: –17.19620 kcal/mol [Figure 3] Hybridization energy: 22.7 kcal/mol Unfolding energy – Target: 5.53496 Unfolding energy – Query: 0.01086 Position – Target RNA: 1421–1434 Position – Query RNA: 3–15 Position seed – Target RNA: 1424–1430 Position seed – Query RNA: 7–13 Heat capacity Using OligoCalc, the heat capacity was determined for the sequence of interest using the following formula, c=Q/m Δ T Q=37.526 cal; m=24123454.14 g; Δ T=87 ºk c=17.88025 J/kg ºk Prediction of secondary structure of protein The secondary three-dimensional structure of proteins was speculated using MODELLER 9.22 software in which totally five structures were predicted. Based on dope scope, these structures in PDB format were considered for further analysis Evaluation of protein using RC plot PDB flies of proteins were obtained using Swiss PDB software (five PDB files for each gene) that is previously obtained from the MODELLER 9.22 software; the total energy was computed before and after energy minimization Figure 2: Selected interaction between target and query sequences of RNA 1 Figure 3: Position-wise minimal energy profile Table 4: Identified interactions between the target and query sequences Target Position Query Position Energy (kcal/mol) ARHGAP 31 1421–1434 RNA 1 3–15 –17.19620 ARHGAP 31 1597–1610 RNA 8 7–20 –12.71700 ARHGAP 31 1442–1457 RNA 5 2–18 –11.45040 ARHGAP 31 1253–1265 RNA 9 2–15 –10.49060 ARHGAP 31 520–535 RNA 6 3–18 –9.20387 ARHGAP 31 1468–1478 RNA 2 9–19 –8.90014 ARHGAP 31 1428–1441 RNA 7 8–20 –7.88810 ARHGAP 31 413–425 RNA 4 4–15 –7.65874 ARHGAP 31 178–194 RNA 3 1–16 –7.33259 Table 3: miRNA designed for ARHGAP 31 S. No. Start Sequence GC% 1 410 AGCTTCCTCCATCCCACTATA 47.62 2 880 AAGCGAAAGCTCTCCAGTAAA 42.86 3 938 CTGGATCAGACTCCAAATCAA 42.86 4 1079 CCAAGGGAAATTTCAATCGAA 38.1 5 2448 TCTCTACATAGACCAGCTGAA 42.86 6 2599 GAGGTTGAGATCGTCTCACAA 47.62 7 2845 CTTCGCCAGAGCCATTCTCTA 52.39 8 2943 GAGGAATTCTGACCCTCTTCA 47.62 9 2985 GATTACTGGATGGGATGAGAA 42.86 10 3727 ACTCAGAAACCTGCCAAAGAT 42.86

[Find the meaning and references behind the names: File, Lower]

Choragudi, et al. : Bioinformatics approach towards Adam’s Oliver syndrome Asian Journal of Pharmaceutic s • Jul-Sep 2022 • 16 (3) | 319 Table 5: The energy values for the PDB files computed before and after energy minimization S. No. PDB id Total energy before energy minimization (k cal/mol) Total energy after energy minimization (k cal/mol) Difference in energy (k cal/mol) 1 qseq 1.B 99990001 7,382,181 82,501 7,299,680 2 qseq 1.B 99990002 11,336,477 102,977 11,233,500 3 qseq 1.B 99990003 25,373,424 83,640.930 25,289,784 4 qseq 1.B 99990004 43,927,516 89,997 43,837,519 5 qseq 1.B 99990005 20,664,946 77,391 20,587,555 Figure 4: Ramachandran plot of ARHGAP 31 Figure 5: Number of residues targeted against Z-score with value 9.12 Before and after energy minimization, the values were recorded for each protein using the same method, and finally, the PDB file which recorded greater energy difference value, before and after energy minimization, was selected. Ramachandran plot was obtained using SAVES-PROCHECK server as [Figure 4]and analysis was done using ProSA [11] and the data are tabulated in Table 5 qseq 4.B 99990004 was considered as dope score was lower for this specific id than the other. The dope score for qseq 4 B 99990004 is –48,617.11328 Ramachandran plot The Z-score value was calculated using ProSA. The Z-score value for the modeled protein is 9.12, Figure 5 CONCLUSION Adams-Oliver syndrome is an inherited congenital disorder, following either a dominant or recessive pattern. There are six genes known (ARHGAP 31, DLL 4, NOTCH 1, RBPJ, DOCK 6, and EOGT) reported so far, which can cause this syndrome. We retrieved CCDS and CDS sequences of each gene from the NCBI database and multiple sequence alignment was performed using Clustal Ω . After target identification, we chose ARHGAP 31 as the target gene, as it is a major cause of cutis aplasia, also the regulator of Rho GTPase activity. siRNA and miRNA were designed using Invitrogen Block-iT. Proteins related to ARHGAP 31 were obtained using Blastx. GC content analysis of ARHGAP 31 using ENDMEMO was found to be 54.55%, and RNA-RNA interaction was interpreted using IntaRNA. Heat capacity, c = 17.88025 J/kg ºk, was analyzed using OligoCalc server and prediction of secondary structure was done using Modeller 9.22 and SAVES. The dope score, analyzed from the RC plot, for qseq 4.B 99990004 is –48,617.11328. The Z-score value was calculated using ProSA. The Z-score value for the modeled protein is 9.12. By suppressing Rho GTPase activity of ARHGAP 31 gene, we can reduce the occurrence of AOS during early embryonic stages.

[Find the meaning and references behind the names: Sri, Garg, Thornton, Vidya, Work, Fournier, Berman, Shali, Macarthur, Int, Mann, Stanley, Westbrook, Sci, Final, Read, Lakshmi, Pushpa, Sree, Brown, Chenna, Duquette, Part, Mcwilliam, Wright, Rep, Bhat, Gilliland, Web, Moss, Madan, Acid, Caron, Webb, Sai, Feng, Nil, Sali, Lalitha, Laskowski, Crystal, Thank, Ishii, Larkin, App, Bank, Jenny, Quality, None]

Choragudi, et al. : Bioinformatics approach towards Adam’s Oliver syndrome Asian Journal of Pharmaceutic s • Jul-Sep 2022 • 16 (3) | 320 ACKNOWLEDGMENT Authors thank the management of KL Educational Foundation, Vaddeswaram, for providing laboratory facilities for this work CONFLICTS OF INTEREST The authors report no financial or any other conflicts of interest in this work AUTHORS’ CONTRIBUTION Dr. Choragudi S.F and Ekklesia Sesham M S have designed and directed through the project; Narasimha Vakkalagadda, Neeraj Krishna Vedantam, Devendranadh Reddy Janga, Dhanya Koneru, and Angirekula Harisairam and Krishna Keerthika Oruganti performed the experiment part and all together has analyzed the results obtained. Dr. Chorgudi S.F. and Ekklesia Sesham M S reverified the results and rectified the mistakes if any. Both authors read and approve the final version of the manuscript REFERENCES 1. Madan A, Sardana K, Garg VK. Adams oliver syndrome. Indian Pediatr 2015;52:633-4 2. Caron C, DeGeer J, Fournier P, Duquette PM, Luangrath V, Ishii H, et al . CdGAP/ARHGAP 31, a Cdc 42/Rac 1 GTPase regulator, is critical for vascular development and VEGF-mediated angiogenesis. Sci Rep 2016;6:27485 3. Müller R, Jenny A, Stanley P. The EGF repeat-specific O-GlcNAc-transferase Eogt interacts with notch signaling and pyrimidine metabolism pathways in Drosophila. PloS one 2013;8:e 62835 4. Ekklesia Shesham MS, Sai Pushpa Sree V, Lakshmi V, Vidya Sree T, Sri Lalitha M. Adam’s oliver syndrome. Int J Sci Tech Res 2019;8:2970-3 5. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al . Clustal W and clustal X version 2.0. Bioinformatics 2007;23:2947-8 6. Mann M, Wright PR, Backofen R. IntaRNA 2.0: Enhanced and customizable prediction of RNA-RNA interactions. Nucleic Acid Res 2017;45:W 435-9 7. Kibbe WA. OligoCalc: An online oligonucleotide properties calculator. Nucleic Acid Res 2007;35:W 43-6 8. Webb B, Sali A. Comparative protein structure modeling using MODELLER. Curr Protoc Bioinformatics 2016;54:5.6.1-37 9. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al . The protein data bank. Nucleic Acid Res 2000;28:235-42 10. Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK-a program to check the stereochemical quality of protein structures. J App Crystal 1993;26:283-91 11. Wiederstein M, Sippl MJ. ProSA-web: Interactive web service for the recognition of errors in threedimensional structures of proteins. Nucleic Acid Res 2007;35:W 407-10 Source of Support: Nil. Conflicts of Interest: None declared.

Other Health Sciences Concepts:

[back to top]

Discover the significance of concepts within the article: ‘An In Silico Strategy against Adam’s Oliver Syndrome by Predicting RNAi...’. Further sources in the context of Health Sciences might help you critically compare this page with similair documents:

Shirna, Save, Prosha, Embryonic development, Gene expression, Cell proliferation, Protein structure, Cell migration, Phylogenetic tree, Ramachandran plot, Phylogenetic analysis, SAVES server, Energy minimization, Cell fate, Secondary structure, Phylogenetic tree analysis, Multiple sequence alignment, Heat capacity, Target identification, NCBI database, Sequence retrieval, Notch signaling, Procheck, DOPE score, Chemical signaling, Target gene, GC content, MiRNA, Vascular development, Sequence homology, Rho GTPase, Thermo Fisher, GPCR, Dominant Genes, NOTCH 1, Protein BLAST, Z-score value, RBPJ, Guanine nucleotide exchange factor, Notch receptor.