Peptide research has boomed recently due to its applications as biomarkers, therapeutic alternatives, or antigenic sub-units in vaccines. Computational tools have assisted with the identification of novel sequences, the prediction of properties, and the modelling of structures. Yet the lack of open-source tools hinders the analysis of this data.
Rodrigo Ochoa, Senior Scientist at Novo Nordisk, an expert and pioneer in open-source peptide technology presented two specific tools that facilitate peptide analysis and design: pyPept and BILN.
BILN is a promising alternative to other biologics line notations like HELM. Medicinal chemists reported that BILN was more human-readable, more user-friendly, and more appropriate for annotating complex peptide sequences than its competitors. Ochoa presented multiple examples of non-natural and natural amino acids to illustrate BILN’s impressive capabilities and unambiguous nature.
“BILN provides an unequivocal translation between the string format and the atomistic description.”
pyPept is a tool that analyses the peptide notation and creates a 2D or 3D representation of them. Scientists can use the 3D format to run an MD simulation to relax the molecule or perform any other modification. By connecting sequence-level notations with molecular objects, pyPept allows researchers to streamline peptide design processes and supports library generation for experimental workflows.
PepFun is another methodology that Ochoa advocates for. He outlined PepFun’s main purpose: “In this package there are different functionalities for analysing the sequences of the peptides, for example, to run basic alignments including natural and non-natural amino acids.” It includes functionalities such as scoring matrices for non-natural amino acids, SAR (structure-activity relationship) analysis, and prediction of peptide properties using machine learning.
Furthermore, Ochoa reiterated the importance of collaboration between academia and industry and democratizing these technologies to promote their wider use the field of peptide analysis and design. He stated: “I think having a community working together on these kinds of methodologies will accelerate the research around these tools.” He continued: “The protocols are fully open-source so they can be embedded in any commercial or non-commercial protocol.”
In summary, these tools promote standardization in peptide research while addressing the complexity of peptide chemical space and enhancing the design of therapeutics. While they are a good starting point, there are ongoing improvements to expand their functionalities and applications.
