Dataset Information

HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy.

ABSTRACT:

Purpose

HLA protein receptors play a key role in cellular immunity. They bind intracellular peptides and display them for recognition by T-cell lymphocytes. Because T-cell activation is partially driven by structural features of these peptide-HLA complexes, their structural modeling and analysis are becoming central components of cancer immunotherapy projects. Unfortunately, this kind of analysis is limited by the small number of experimentally determined structures of peptide-HLA complexes. Overcoming this limitation requires developing novel computational methods to model and analyze peptide-HLA structures.

Methods

Here we describe a new platform for the structural modeling and analysis of peptide-HLA complexes, called HLA-Arena, which we have implemented using Jupyter Notebook and Docker. It is a customizable environment that facilitates the use of computational tools, such as APE-Gen and DINC, which we have previously applied to peptide-HLA complexes. By integrating other commonly used tools, such as MODELLER and MHCflurry, this environment includes support for diverse tasks in structural modeling, analysis, and visualization.

Results

To illustrate the capabilities of HLA-Arena, we describe 3 example workflows applied to peptide-HLA complexes. Leveraging the strengths of our tools, DINC and APE-Gen, the first 2 workflows show how to perform geometry prediction for peptide-HLA complexes and structure-based binding prediction, respectively. The third workflow presents an example of large-scale virtual screening of peptides for multiple HLA alleles.

Conclusion

These workflows illustrate the potential benefits of HLA-Arena for the structural modeling and analysis of peptide-HLA complexes. Because HLA-Arena can easily be integrated within larger computational pipelines, we expect its potential impact to vastly increase. For instance, it could be used to conduct structural analyses for personalized cancer immunotherapy, neoantigen discovery, or vaccine development.

SUBMITTER: Antunes DA

PROVIDER: S-EPMC7397777 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo meet increasing demands to train neuroendovascular techniques, we developed a dedicated simulator applying individualized three-dimensional intracranial aneurysm models ('HANNES'; Hamburg Anatomic Neurointerventional Endovascular Simulator). We hypothesized that HANNES provides a realistic and reproducible training environment to practice coil embolization and to exemplify disparities between neurointerventionalists, thus objectively benchmarking operators at different levels of experience.MethodsSix physicians with different degrees of neurointerventional procedural experience were recruited into a standardized training protocol comprising catheterization of two internal carotid artery (ICA) aneurysms and one basilar tip aneurysm, followed by introduction of one framing coil into each aneurysm and finally complete coil embolization of one determined ICA aneurysm. The level of difficulty increased with every aneurysm. Fluoroscopy was recorded and assessed for procedural characteristics and adverse events.ResultsPhysicians were divided into inexperienced and experienced operators, depending on their experience with microcatheter handling. Mean overall catheterization times increased with difficulty of the aneurysm model. Inexperienced operators showed longer catheterization times (median; IQR: 47; 30-84s) than experienced operators (21; 13-58s, p = 0.011) and became significantly faster during the course of the attempts (rho = -0.493, p = 0.009) than the experienced physicians (rho = -0.318, p = 0.106). Number of dangerous maneuvers throughout all attempts was significantly higher for inexperienced operators (median; IQR: 1.0; 0.0-1.5) as compared to experienced operators (0.0; 0.0-1.0, p = 0.014).ConclusionHANNES represents a modular neurointerventional training environment for practicing aneurysm coil embolization in vitro. Objective procedural metrics correlate with operator experience, suggesting that the system could be useful for assessing operator proficiency.