Comparative Structural Analysis of HMPV Proteins Using Swiss Modeler and Alpha Fold

Background and Objectives Human metapneumovirus (HMPV) is a significant pathogen causing respiratory infections, particularly in vulnerable populations such as infants, the elderly, and immunocompromised individuals. It shares clinical symptoms with respiratory syncytial virus (RSV), including coughing, wheezing, and pneumonia. Discovered in 2001, HMPV is genetically related to RSV and avian pneumovirus, and its fusion (F) and attachment (G) proteins play crucial roles in viral entry. The F protein is involved in both attachment and fusion, which is different from other paramyxoviruses where the attachment protein is typically essential for entry. Despite its clinical relevance, the structural biology of HMPV proteins is not well understood. Advances in computational biology, especially using tools like AlphaFold (for ab initio structure prediction) and Swiss-Modeler (for homology modeling), offer new opportunities to predict the three-dimensional structures of HMPV proteins. This research aims to conduct a comparative structural analysis of HMPV using these methods to gain insights into the virus’s molecular mechanisms and potential therapeutic targets. By enhancing our understanding of HMPV’s biology, this study may contribute to developing new antiviral strategies to mitigate the virus’s impact, particularly in high-risk groups. Methods HMPV's conserved RNA sequences were converted into protein sequences using Biopython. The protein sequences were input in FASTA format for structure prediction using AlphaFold2 on Google Colab. The default MSA pipeline was used for multiple sequence alignments (MSA). The selected sequences were analyzed with a BLAST search using the non-redundant protein sequence (nr) database and blastp algorithm. Swiss-Model and AlphaFold were used for 3D structure prediction. For the 5 protein sequences with matches from BLAST, comparisons were made between experimentally determined structures (EM or X-ray) and the predicted models. For the 13 sequences without BLAST matches, comparisons between Swiss-Model and AlphaFold predictions were conducted. ChimeraX was used for structure visualization, and R was employed for data analysis, with all code implemented in RStudio. Results While AlphaFold offers superior coverage and confidence, especially for novel insights and structural regions lacking templates, Swiss-Model remains valuable for validating conserved domains. Together, these approaches provide a comprehensive framework for advancing HMPV research, aiding in pandemic response and vaccine development efforts. Conclusion By combining the strengths of both Swiss-Modeler and AlphaFold, this study presents a robust approach to HMPV structural biology, which could lead to new therapeutic strategies, vaccine candidates, and drug discovery efforts. Future integration of dynamic simulations and experimental validation will enhance the predictive power of these models and deepen the understanding of HMPV’s molecular mechanisms.