Membrane proteins are essential vessels for cell communication both with other cells and noncellular structures. They modulate environment responses and mediate a myriad of biological processes. Dimerization and multimerization processes have been shown to further increase the already high specificity of these processes. Due to their central role in various cell and organism functions, these multimers are often associated with health conditions, such as Alzheimer's disease (AD), Parkinson's disease (PD), and diabetes, among others.Understanding the membrane protein dimers' interface takes advantage of the specificity of the structure, for which we must pinpoint the most relevant interfacial residues, since they are extremely likely to be crucial for complex formation. Here, we describe step by step our own in silico protocol to characterize these residues, making use of known experimental structures. We detail the computational pipeline from data acquisition and pre-processing to feature extraction. A molecular dynamics simulation protocol to further study membrane dimer proteins and their interfaces is also illustrated.
Keywords: Feature extraction; Interfacial residues; Machine learning; Membrane protein dimers; Molecular dynamics; Protein-protein interaction.