Application of intelligent algorithm in the optimization of novel protein regulatory pathway: Mechanism of action of gastric carcinoma protein p42.3

• Published in: Journal of cancer research and therapeutics Vol. 12; no. 2; pp. 650 - 656
• Main Authors: Liu, Xing'an, Hao, Yibin, Fan, Tianli, Nan, Kejun
• Format: Journal Article
• Language: English
• Published: India Wolters Kluwer - Medknow Publications 01.04.2016; Medknow Publications and Media Pvt. Ltd; Medknow Publications & Media Pvt. Ltd
• Subjects: Algorithms; Amino acids; Bayes Theorem; Cell cycle; Cell Cycle Proteins - chemistry; Cell Cycle Proteins - physiology; Cell growth; Chemotactic Factors - analysis; Computational biology; Deoxyribonucleic acid; Development and progression; DNA; Gastric cancer; Genes; Genetic aspects; Genetic regulation; Health aspects; Humans; Innovations; Kinases; Laboratories; Methods; Optimization; Properties; Protein Domains; Proteins; S100 Proteins - analysis; Stomach cancer; Stomach Neoplasms - etiology; Studies; Tumor proteins; mechanism of action; p42.3; spherical polar coordinates; Bayesian probability optimization; intelligent algorithms; novel protein
• ISSN: 0973-1482; 1998-4138; 1998-4138
• DOI: 10.4103/0973-1482.151856

Aims: This purpose of the study was to optimize the regulatory mechanism of p42.3 novel protein molecule in gastric cancer and also verified it by the use of intelligent algorithms. Subjects and Methods: Threading method was employed to analyze structural domain characteristics of p42.3 protein. Referential proteins were gathered and formed by domain homology and function similarity. Afterwards, the possible regulatory network of p42.3 was established by analyzing the acting pathways of the referential proteins. Spherical polar coordinates stratification and stratified multi-parameter weight were used for calculation of the similarity between the referential proteins and p42.3 protein, the result of which was taken as the prior probability of the initial node in Bayes network, thus the probability of occurrence of each pathway was figured out by using conditional probability formula, and the one with the biggest probability was considered as the possible pathway of p42.3. At last, molecular biological experiments were conducted to verify it. Results: The acting pathway with the maximum probability predicted by Bayesian probability optimizing calculation was "S100A11" - RAGE - P38 - MAPK - Microtubule-associated protein - Spindle protein-Centromere protein - Cell proliferation" which was the most likely acting pathway participated by p42.3, and has been validated by biological experiments. Conclusions: By the theoretical analysis and experimental verification, this study confirmed that assumptions that p42.3 protein was related to the occurrence and development of gastric carcinoma, predicted and verified the acting pathways of p42.3, which will provide a new research direction of the relationship between p42.3 and gastric cancer, as well as the target therapy of gastric cancer. The algorithm in predicting the acting pathway of the protein also offers a new thought in studying new functional proteins.