In Silico characterization of STK11- a protein involved in PJ Syndrome
M Reddy, B Bhanu, M Prasad, N Ramya, K Madhulika
Keywords
ampk, intestinal cancer, lkb1, peutz-jeghers syndrome, stk11, tumors
Citation
M Reddy, B Bhanu, M Prasad, N Ramya, K Madhulika. In Silico characterization of STK11- a protein involved in PJ Syndrome. The Internet Journal of Genomics and Proteomics. 2008 Volume 4 Number 1.
Abstract
Studies of hereditary cancer syndromes have contributed greatly to our understanding of molecular events involved in tumor genesis. One such syndrome of our interest is Peutz-Jeghers Syndrome, a hereditary disease, in which there is predisposition to benign and malignant tumors of many organ systems. Here, we investigate the genes responsible for the Peutz-Jeghers syndrome (PJS) and the pathway of disease causing mechanism. The STK11, Serine/Threonine Kinase 11, commonly known as LKB1 is the gene responsible for this syndrome. This gene is coding a protein of length 433 amino acids, 48.6 kDa. The protein sequence is retrieved from the protein database of NCBI. The analysis of this protein is performed using various in silico methods.
Introduction
Peutz-Jeghers syndrome is characterized by the development of growths called hamartomatous polyps in the gastrointestinal tract (particularly the stomach and intestines) [1]. Patients with this syndrome have a 15-fold increased risk of developing intestinal cancer compared to that of the general population [2,3]. Almost 50% of patients with Peutz-Jeghers syndrome develop and die from cancer around the age of 57 years. The cumulative risk for developing any cancers associated with Peutz-Jeghers syndrome in patients aged 15–64 years is 93% [4,5]. Peutz-Jeghers syndrome has been described in all races. The occurrence of cases in males and females is about equal. The average age at diagnosis is 23 years in men and 26 years in women. The gastrointestinal polyps found in this syndrome are typical hamartomas. Gastrointestinal polyps can result in chronic bleeding and anemia and cause recurrent obstruction and intussusceptions requiring repeated laparotomies and bowel resections. Mucocutaneous hyper pigmentation appears in childhood as dark blue to dark brown macules around the mouth, eyes, and nostrils, in the perianal area, and on the buccal mucosa [6,7]. The signaling pathway of the
Figure 1
The reference sequence has been curated by NCBI staff. The reference sequence was derived from AC011544.6 and AC004221.2. These sequences are submitted by DOE Joint Genome Institute, Stanford Human Genome Center & DOE Joint Genome Institute, Lawrence Livermore National Laboratory, Livermore, CA respectively.
Methodology
Identification of Mutations from the Uniprot database
The STK11 gene is a tumor suppressor gene, which means that it normally prevents cells from growing and dividing too rapidly or in an uncontrolled way. The mutations are found to occur in the domain region, disrupting its ability to restrain cell division. Thus, the mutations in the STK11 gene are responsible for the Peutz Jeghers Syndrome. These mutations are identified from the protein information given in Uniprot Database [9] listed in Table 1.
Sequence analysis of the STK11 protein
The sequence analysis is performed using blastp [10] from NCBI. Sequences with high similarity are structurally conserved and are functionally related. Hence, the similar protein is identified to analyze if it has any role in the syndrome. Similarity search is performed against the non redundant database taking the expect threshold as 1 and blosum matrix 80. The query protein is compared with various model organisms. The protein having good score, high identities & similarities and fewer gaps is selected from the results of the similarity search in all the model organisms. This resulted in the identification of STK11 proteins in all the organisms selected (Table 2) and also the AMPK (Activated AMP Protein Kinase) as the closest protein to STK11 (Table 3). The AMPK has high sequence similarity and a common domain (kinase) with STK11.
Phylogenetic Studies using Biology Workbench
Evolutionary studies are performed on the sequences taken from the similarity search results. A multiple sequence alignment is built and the dendrogram is constructed (Figure 1) by Clustal W [11] to find the evolutionary relationship between STK11 and AMPK. The conservations in these proteins are analyzed from the Multiple Sequence Alignment built using both the local (Figures 2&3) and the global alignments (Figure 4) by Texshade [12] and Boxshade respectively. The distance matrix (Figure 5) is constructed using ClustalDist [13] to confirm the results of the dendrogram.
Structural Comparison of STK11 & AMPK
The structures of STK11 and the AMPK are analyzed to find the structural similarity. The secondary structure elements, alpha helices, beta sheets and coils are predicted using the tool Hierarchical Neural Network (HNN) [14] from the Expasy proteomics server. The composition of the secondary structure elements are listed in table 5. The 3D structures are retrieved using comparative modeling (CPH Models) [15] and threading methods (3DPSSM [16] server & HHPred [17]). The same structural entry, 2H6D is obtained from both the principles for the two proteins. The cartoon view of the structure is given in Figure 6. Also, the other properties of the protein viz, the molecular weight, atomic composition, iso electric point, half-life, extinction co efficient, Gravy, amino acid composition, instability index and aliphatic index are retrieved using the Protparam [18] tool, the results of which are listed in the table 4.
As the studies reveal good similarity of AMPK with STK11, the KEGG [19] pathway (Figure 7) is obtained to gain more insights into the disease causing mechanism. It is observed that AMPK is involved in the mTOR signaling pathway and that it is activated by its phosphorylation through STK11. Therefore, the phosporylation sites of AMPK are predicted using the tool NetPhos [20]. Also, the Prosite [21] pattern (Table 6), domain (ProDom [22] (Table 7) and family (Pfam [23]) of the proteins (Tables 8 & 9) is retrieved. The protein localization and the solubility are identified from Psort [24] (Table 10) & Sosui [25] (Table 11) respectively.
Results
Figure 2
The sequence of STK11 is retrieved from the protein database of NCBI. The accession number of the protein is
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MEVVDPQQLGMFTEGELMSVGMDTFIHRIDSTEVIYQPRRKRAKLIGKYLMGDLLGEGSYGKVKEVLDSETLCRRAVKILKKKKLRRIPNGEANVKKEIQLLRRLRHKNVIQLVDVLYNEEKQKMYMVMEYCVCGMQEMLDSVPEKRFPVCQAHGYFCQLIDGLEYLHSQGIVHKDIKPGNLLLTTGGTLKISDLGVAEALHPFAADDTCRTSQGSPAFQPPEIANGLDTFSGFKVDIWSAGVTLYNITTGLYPFEGDNIYKLFENIGKGSYAIPGDCGPPLSDLLKGMLEYEPAKRFSIRQIRQHSWFRKKHPPAEAPVPIPPSPDTKDRWRSMTVVPYLEDLHGADEDEDLFDIEDDIIYTQDFTVPGQVPEEEASHNGQRRGLPKAVCMNGTEAAQLSTKSRAEGRAPNPARKACSASSKIRRLSACKQQ
Figure 3
Figure 4
The similarity search result has given significant similarity between the query and the AMPK in all the model organisms listed above in the tables. The studies of the proteins in the results indicate that the STK11 protein and the AMPK are having a kinase domain in common.
Figure 5
Figure 6
Figure 7
Figure 8
Violet and green colors are observed dominantly in the results of TEXSHADE and BOXSHADE respectively. These colors indicate the residues conserved in all the species taken.
Figure 9
Figure 10
# Extinction coefficients are in units of M-1 cm-1, at 280 nm measured in water.
* Abs 0.1% (=1 g/l) 0.812, assuming ALL Cys residues appear as half cystines
** Abs 0.1% (=1 g/l) 0.799, assuming NO Cys residues appear as half cystines
~ The N-terminal of the sequence considered is M (Met). The estimated half-life is: 30 hours (mammalian reticulocytes, in vitro), >20 hours (yeast, in vivo), >10 hours (Escherichia coli, in vivo).
` The instability index provides an estimate of the stability of a protein in a test tube. Statistical analysis of 12 unstable and 32 stable proteins has revealed that there are certain dipeptides, the occurrence of which is significantly different in the unstable proteins compared with those in the stable ones. The authors of this method have assigned a weight value of instability to each of the 400 different dipeptides (DIWV). Using these weight values it is possible to compute an instability index (II) which is defined as:
Figure 11
Where: L is the length of sequence
DIWV(xx [i+1]) is the instability weight value for the dipeptide starting in position i.
A protein whose instability index is smaller than 40 is predicted as stable, a value above 40 predicts that the protein may be unstable.
Both these proteins exhibit similar physico-chemical properties, the properties that are similar are highlighted in the table above.
Figure 12
Figure 13
Figure 14
The cartoon view of the secondary structural elements, alpha helices, beta sheets & coils are colored red, green & yellow respectively. The amino acid Leucine contributing the highest percent in composition is highlighted using the ball& stick rasmol view (orange color).
Figure 15
The PROSITE pattern observed in the results of these proteins is the signature pattern of the Serine – Threonine protein kinase family. The kinase domain is shared in common for both the proteins. This confirms the hypothesis made in the similarity search.
Figure 16
Figure 17
Figure 18
Both these proteins belong to a family of PKinase. However, the protein AMPK is a member of many other families as seen in the result. This is because this protein is involved in many metabolic pathways.
Figure 19
These results confirm that these are mostly cytoplasmic proteins.
Figure 20
Figure 21
Figure 22
Discussion
The Insilico analysis of the STK11 reveals the role of AMPK in the Peutz-Jeghers syndrome. AMP-activated protein kinase (AMPK) is a primary regulator of the cellular response to lowered ATP levels in eukaryotic cells [26,27]. AMPK is a serine/threonine protein kinase [26].
The pathway also suggests involvement of both these proteins in the same pathway of cell growth. However, AMPK is involved in many other metabolic processes. AMPK acts as a metabolic master switch regulating several intracellular systems including the cellular uptake of glucose, the β-oxidation of fatty acids and the biogenesis of glucose transporter 4 (GLUT4). STK11 has been shown to phosphorylate AMPK on Thr-172 and serves as an essential component of physiological AMPK activation. The identified human mutations of STK11 occur in the catalytic domain and cause a loss of its kinase activity. This failure of STK11 phosphorylation impairs its downstream signaling of AMPK [28], thus disturbing the normal cycle of cell growth to abnormal growth leading to the formation of hamartomatous, cancerous polyps, i.e. the Peutz-Jeghers Syndrome. The role of STK11/AMPK in the survival of a subset of genetically defined tumor cells may provide opportunities for cancer therapeutics.
Acknowledgements
We would like to thank Mr. G. Ashok Kumar, Director, Ventura Institute of Biosciences, Hyderabad, for providing necessary facilities during the period of the project work.
