Application of Face Recognition methodologies to the classification of proteins

Recognition of the possibility for an interaction between two proteins can introduce potential biological functions and may discover novel complexes. In this regard, the first protein can be the Spike of a virus like new discovered and wide-spread Covid-19 disease that usefully may interact with another protein result in eliminating the virus ability to enter the human body. Since the interaction between two proteins based on shape complementarity of their 3D structure, geometrical descriptors of 3D surface that represented for 3D face recognition in computer vision field can reveal the ability of the docking between two proteins. In our protein classification experiment which is based on the docking ability between proteins, we applied four comparison methods on the extracted geometrical features from the proteins surface that can connect each protein with the protein that has the most shape complementary feature. The main aim can be detecting the docking possibility between the Spike proteins of Covid-19 and some of the ACE and Hemoglobin and different Anti-body proteins which can produce novel drugs. The result of our experiment represents that our novel docking recognition can detect potential interaction between the described proteins with different size and resolution by low computational time.