A comparative study of computational modeling approaches for evaluating structural dynamics and algorithmic suitability of short length peptides

The existing protein or peptide modeling algorithms are insufficient for accurately modeling short peptides, which are highly unstable in nature. Thus, there is a need to identify their strengths and weaknesses. Hence, we have performed modeling of a random set of peptides using four different algorithms, namely, AlphaFold, PEP-FOLD, Threading and Homology Modeling. The structures were analyzed using Ramachandran plot, VADAR, and molecular dynamics (MD) simulation. The results were correlated with their physicochemical properties and sequence characteristics. Our study reveals novel insights about strengths of each of the modeling algorithms. We found that AlphaFold and Threading complement each other in case of more hydrophobic peptides. Similarly, PEP-FOLD and Homology Modeling complement each other when modeling more hydrophilic peptides. We also found that PEP-FOLD gives both compact structure and stable dynamics for most of the peptides, whereas AlphaFold gives a compact structure for most of these. Finally, our study points towards the usage of integrated approaches in future, thereby, combining the strengths of different modeling algorithms.