PyInteraph2 and PyInKnife2 to analyze networks in protein structural ensembles

Abstract

MotivationProtein dynamic is essential for cellular functions. Due to the complex nature of non-covalent interactions and their long-range effects, the analysis of protein conformations using network theory can be enlightening. Protein Structure Networks (PSNs) rely on different philosophies, and the currently available tools suffer from limitations in terms of input formats, supported network models, and version control. Another issue is the precise definition of cutoffs for the network calculations and the assessment of the stability of the parameters, which ultimately affect the outcome of the analyses.ResultsWe provide two open-source software packages, i.e., PyInteraph2 and PyInKnife2, to implement and analyze PSNs in a harmonized, reproducible, and documented manner. PyInteraph2 interfaces with multiple formats for protein ensembles and calculates a diverse range of network models with the possibility to integrate them into a macro-network and perform further downstream graph analyses. PyInKnife2 is a standalone package that supports the network models implemented in PyInteraph2. It employs a jackknife resampling approach to estimate the convergence of network properties and streamline the selection of distance cutoffs. Several functionalities are based on MDAnalysis and NetworkX, including parallelization, and are available for Python 3.7. PyInteraph2 underwent a massive restructuring in terms of setup, installation, and test support compared to the original PyInteraph software.ConclusionsWe foresee that the modular structure of the code and the version control system of GitHub will promote the transition to a community-driven effort, boost reproducibility, and establish harmonized protocols in the PSN field. As developers, we will guarantee the introduction of new functionalities, assistance, training of new contributors, and maintenance of the package.AvailabilityThe packages are available at https://github.com/ELELAB/pyinteraph2 and https://github.com/ELELAB/PyInKnife2 with guides provided within the packages.

Unraveling membrane properties at the organelle-level with LipidDyn

“…In terms of protein-lipid interaction, we will implement analyses of occurrence, maximal occupancy and time life of contacts along the simulation time [84] . We will provide LipidDyn outputs compatible with Pyinteraph2 [85] , [86] so that protein-membrane simulations can be analyzed using methods from graph theory.…”

psntools - a Python package for protein structure network analysis

“…Protein structure networks representing salt-bridged, hydrogen-bonded, and atomic-contacts-based interactions were calculated using PyInteraph2 40 . Only atoms belonging to charged moieties of two oppositely charged residues were considered for salt bridges calculation.…”

“…Furthermore, the software would benefit from being used and supported by a lively community, where a larger pool of users could report bugs and request new features. In this context, psntools could also benefit from being incorporated into the PyInteraph2 software 40 , bringing the at-a-glance visualization utilities and the capability of grouping PSNs to an actively developed suite that already integrates several methodologies for PSN construction and would gain further appeal in the community from an extension of its analysis toolkit.…”

Unraveling membrane properties at the organelle-level with LipidDyn

“…The copyright holder for this preprint this version posted January 5, 2022. ; https://doi.org/10.1101/2022.01.04.474788 doi: bioRxiv preprint [77,78] so that protein-membrane simulations can be analyzed using methods from graph theory. Furthermore, we plan to include in LipidDyn automated support to convert the information in the processed lipidomics data to design models of membranes for MD simulations that resemble experimentally observed lipid compositions.…”

“…In terms of protein-lipid interaction, we will implement analyses of occurrence, maximal occupancy and time life of contacts along the simulation time. We will provide LipidDyn outputs compatible with Pyinteraph2 [77,78] so that protein-membrane simulations can be analyzed using methods from graph theory.…”