TMHC-MSAT: Accurate Prediction of Inter-Helical Residue Contacts in Transmembrane Proteins Using MSA Transformer

Residue-residue contact prediction in a protein is one of the most used and informative middle steps to ultimately predict the complete 3D structure of a protein. While most previous studies use methods relying on statistical analysis of sequential properties to infer these contacts, some recent methods based on natural language processing models have gained success in accomplishing the task. However, most of these methods and models are built for globular proteins and not intended for specific types of proteins such as Transmembrane Proteins, which actually comprise about 30% of the proteome in most organisms and play important roles in cellular processes. In this study, we propose a Transmembrane Protein Helices Contacts predictor (TMHC-MSA) that utilizes features extracted by a protein language model called MSA Transformer and incorporates neighborhood information to enhance the quality of the produced contact map. Our proposed model shows that it can successfully outperform the state-of- the-art method by an average of 7% in terms of L precision and even surpass the MSA Transformer by an average of 2.5% on the same metric. Furthermore, we demonstrate that the more accurate contact map produced by our model can be used to generate a more accurate 3D structure.