Protein-protein interactions at membranes play an inevitable role in the function of proteins
there. However, the task of studying the interactions is of many difficulties in case of the membrane
proteins, due to their hydrophobic environment. This is why the use of bioinformatics methods,
especially machine learning approaches is essential to understand the membrane proteins' function.
However, the machine learning methods for prediction of the interaction sites of membrane proteins
are faced with numerous challenges. This paper aims to describe the current state of machine learning
applications in inferring the membrane protein interaction sites, and to assess the methods up to now
proposed. We have introduced the membrane protein interaction site prediction methods, presented the
contribution degrees of parameters at membrane protein interaction interfaces, and compared the performance of methods
through several case predictions.
Keywords: Bioinformatics, example prediction, membrane proteins, machine learning, performance comparison, protein
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