The investigation of horse myostatin with human follistatin by molecular docking method

Myostatin is a transforming growth factor-beta (TGF-beta) family member that plays roles as a negativeregulator of muscle mass development. Follistatin is a myostatin-binding protein that can inhibit myostatinactivity to promote muscle growth. This is an important way for increasing growth especially in demo horses.Here, we aimed to prediction inhibition activity of equine myostatin protein with human follistatin, throughbioinformatics tools. The Swiss-model server was applied to predict the third (three-dimensional) structureof horse myostatin protein and studies with SAVES ۶.۰ online server. After that, the interactions of myostatinwith human follistatin were evaluated using variety of tools such as Verify۳D, ERRAT and ClusPro۲.۰ onlinesoftware [۲, ۳]. The results showed that the Verify۳D for this protein was at least ۸۸% of the amino acidresidues have an average score of ۳D-۱D> = ۰.۲, which is acceptable for our protein. strategy evaluatesproteins using a three-dimensional structure. This score varies from -۱ (poor score) to +۱ (good score).ERRAT is an online server that confirms the structure of a protein on the assumption of nuclear fusionbetween different types of atoms, with total quality index in this study was ۸۳.۵۲ which is acceptable.According to the Ramachandarn plot, for horse myostatin ۸۸.۷% of the amino acids in this structure were inthe desired region, which is acceptable for predicting the third structure. The docking result showed that theN-terminal of follistatin was in contact with TGF-beta region in myostation that related to myostatin activityaccording to crystallography structure, derived from the docking of human follistatin with mouse myostatin.Finally, our research indicated that the binding energy in our predicted model was -۹۰۳ which is close to theresult of binding energy of the docking human follistatin with mouse myostatin which is reported –۱۳۲۳.۳.

Keywords:

Follistatin , Equus caballus , Myostatin , Bioinformatics , Molecular Docking