Pietro Hiram Guzzi1, Luisa di Paola2, Alessandro Giuliani3, Pierangelo Veltri1. 1. Department of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Catanzaro, 88100, Italy. 2. Unit of Chemical-Physics Fundamentals in Chemical Engineering, Department of Engineering, Università Campus Bio-Medico di Roma, via Álvaro del Portillo 21, Rome, 00128, Italy. 3. Environment and Health Department, Istituto Superiore di Sanità.
Abstract
MOTIVATION: Protein Contact Network (PCN) is a powerful method for analysing the structure and function of proteins, with a specific focus on disclosing the molecular features of allosteric regulation through the discovery of modular substructures. The importance of PCN analysis has been shown in many contexts, such as the analysis of SARS-CoV-2 Spike protein and its complexes with the ACE human receptors. Even if there exist many software tools implementing such methods, there is a growing need tools integrating existing approaches. RESULTS: We present PCN-Miner a software tool, implemented in the Python programming language, able to (i) import protein structures from the Protein Data Bank; (ii) generate the corresponding Protein Contact Network; (iii) model, analyse and graphically represent PCNs and related protein structures by using a set of known algorithms and metrics. The PCN-Miner can cover a large set of applications: from clustering to embedding and subsequent analysis. AVAILABILITY: The PCN-Miner tool is freely available at the following GitHub repository: https://github.com/hguzzi/ProteinContactNetworks. Tool is also available as package in the Python Package Index (PyPI) repository. SUPPLEMENTARY INFORMATION: Use cases and support files are available in the GitHub repository.
MOTIVATION: Protein Contact Network (PCN) is a powerful method for analysing the structure and function of proteins, with a specific focus on disclosing the molecular features of allosteric regulation through the discovery of modular substructures. The importance of PCN analysis has been shown in many contexts, such as the analysis of SARS-CoV-2 Spike protein and its complexes with the ACE human receptors. Even if there exist many software tools implementing such methods, there is a growing need tools integrating existing approaches. RESULTS: We present PCN-Miner a software tool, implemented in the Python programming language, able to (i) import protein structures from the Protein Data Bank; (ii) generate the corresponding Protein Contact Network; (iii) model, analyse and graphically represent PCNs and related protein structures by using a set of known algorithms and metrics. The PCN-Miner can cover a large set of applications: from clustering to embedding and subsequent analysis. AVAILABILITY: The PCN-Miner tool is freely available at the following GitHub repository: https://github.com/hguzzi/ProteinContactNetworks. Tool is also available as package in the Python Package Index (PyPI) repository. SUPPLEMENTARY INFORMATION: Use cases and support files are available in the GitHub repository.