A Statistical Approach to Detect Intrinsically Disordered Proteins Associated with Uterine Leiomyoma

Uterine Leiomyoma is mainly widespread non-malignant tumor. Around more than 80% woman have these particular tumor among them only 30% of them are detected. Integrin-ᵦ1 is one of the up regulated biomarkers during tumorigenesis which is also associated with structural disordered. Intrinsically disordered proteins are one of the types which are dealing with un-structuredness especially in tertiary structural orchestration. Around 30% of the human proteins consist of intrinsically disordered regions. It is obvious that IDPs should have a significant change of functional activities under structure-function paradigm. Mostly IDPs are associated with malignancies, neurodegenerative diseases and heart diseases. DNA methylation is one Post Transcriptional Modification (PTM) techniques where methyl groups are added to nucleotide bases. It is responsible to control the functionality of Transcription Factors (TFs). Along with that, the structural orchestration is also affected due to PTM. Very few diseases related studies are focused on structural disordered along with methylation.

In this article, our motivation is to establish a relation between uterine leiomyoma at differential methylation rate and tissue specific disordered proteins.

In this article, we propose a framework for achieving our aforementioned object. We start with two set of data i.e., set of gene specifically related with uterine leiomyoma (GUL) and set of tissue specific proteins from uniprot (Puterine). Subsequently, 'two sample T-Test' is applied on GUL to find differentially methylated sample for uterine leiomyoma (DGUL). Comparing the gene transcripts of DGUL with the Puterine , the common biomarkers are selected (DPuterine). Thereafter the selected list of proteins is analyzed under D2P2 to find percentage disorder rate, number SCOP, number protein families and rate PTM. Proteins, with more than 10% of structural disorder rate, consider as structurally disordered (PUL disordered). Finally, to validate the listed up proteins we perform KEGG pathway and Gene Ontology analysis.

Following the proposed framework, we start with 2246 proteins from uniprot which are kept in Puterine. Under DGUL there are 6555 genes which are differentially methylated (p-value <0.05). Only 434 proteins selected from the intersection of DGUL and Puterine. Among them only 210 proteins are fallen PUL disordered with more than 10% structural disorder. Top ten proteins under the range of 100% to 74.2% are selected shown in the article. After performing KEGG pathway analysis and Gene Ontology analysis, it is found that Q969W3 has no connection with KEGG or GO terms.

After the applying the framework, we get some verified group of proteins at different stages of the proposed method. The group of 210 disordered proteins is verified from the KEGG and GO analysis. As the result is verified at satisfactory level then it can be said that the framework is successfully analyzed intrinsically disordered proteins, having a connection with differential methylation levels for a specific disease.