PMID- 35844380
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20220719
IS  - 1319-562X (Print)
IS  - 2213-7106 (Electronic)
IS  - 2213-7106 (Linking)
VI  - 29
IP  - 5
DP  - 2022 May
TI  - Integrated computational approaches to screen gene expression data to determine 
      key genes and therapeutic targets for type-2 diabetes mellitus.
PG  - 3276-3286
LID - 10.1016/j.sjbs.2022.02.004 [doi]
AB  - There is a rapid rise in cases of Type-2-diabetes mellitus (T2DM) globally, 
      irrespective of the geography, ethnicity or any other variable factors. The 
      molecular mechanisms that could cause the condition of T2DM need to be more 
      thoroughly analysed to understand the clinical manifestations and to derive 
      better therapeutic regimes. Tools in bioinformatics are used to trace out key 
      gene elements and to identify the key causative gene elements and their possible 
      therapeutic agents. Microarray datasets were retrieved from the Gene expression 
      omnibus database and studied using R to derive different expressed gene (DEG) 
      elements. With the comparison of the expressed genes with disease specific genes 
      in DisGeNET, the final annotated genes were taken for analysis. Gene Ontology 
      studies, Protein-protein interaction (PPI), Co-expression analysis, Gene-drug 
      interactions were performed to scale down the hub genes and to identify the 
      novelty across the genes analysed so far. In vivo and invitro analysis of key 
      genes and the trace of interaction pathway is crucial to better understand the 
      unique outcomes from the novel genes, forming the basis to understand the pathway 
      that ends up causing T2DM. Afterwards, docking was executed enabling recognition 
      of interacting residues involved in inhibition. The complex CCL5-265 and 
      CD8A-40585 thus docked showed best results as is evident from its PCA analysis 
      and MMGBSA calculation. There is now scope for deriving candidate drugs that 
      could possibly detect personalized therapies for T2DM.
CI  - (c) 2022 The Author(s).
FAU - Alhumaydhi, Fahad A
AU  - Alhumaydhi FA
AD  - Department of Medical Laboratories, College of Applied Medical Sciences, Qassim 
      University, Buraydah 52571, Saudi Arabia.
LA  - eng
PT  - Journal Article
DEP - 20220210
PL  - Saudi Arabia
TA  - Saudi J Biol Sci
JT  - Saudi journal of biological sciences
JID - 101543796
PMC - PMC9280245
OTO - NOTNLM
OT  - Differently expressed genes
OT  - Gene expression omnibus
OT  - Molecular dynamics simulation
OT  - Transcription factors
OT  - Type-2 diabetes mellitus
COIS- The authors declare that they have no known competing financial interests or 
      personal relationships that could have appeared to influence the work reported in 
      this paper.
EDAT- 2022/07/19 06:00
MHDA- 2022/07/19 06:01
PMCR- 2022/02/10
CRDT- 2022/07/18 03:36
PHST- 2021/12/30 00:00 [received]
PHST- 2022/02/01 00:00 [revised]
PHST- 2022/02/06 00:00 [accepted]
PHST- 2022/07/18 03:36 [entrez]
PHST- 2022/07/19 06:00 [pubmed]
PHST- 2022/07/19 06:01 [medline]
PHST- 2022/02/10 00:00 [pmc-release]
AID - S1319-562X(22)00080-8 [pii]
AID - 10.1016/j.sjbs.2022.02.004 [doi]
PST - ppublish
SO  - Saudi J Biol Sci. 2022 May;29(5):3276-3286. doi: 10.1016/j.sjbs.2022.02.004. Epub 
      2022 Feb 10.