Project #15485
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#15485 : Providing correlationPlus software to the scientific community for analysis of dynamical correlations in biological macromolecules
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Name of Applicant : Mustafa Tekpinar
Date of application : 10-07-2020
Unit : Structural Dynamics of Macromolecules
Location : Metchnikof Building - 3. Floor - 3040
Phone : +33 07 58 88 62 42
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Project context and summary :

Molecular dynamics simulations and elastic network models are two widely used computational methods for investigation of dynamics of biological macromolecules. These methods can reveal dynamical correlations between residues, nucleotides, domains and chains of biological macromolecules. Even though analyses of these correlations are employed frequently, there is not an application and API that can facilitate the analysis and the visualization of them. A coherent API/app can accelerate the analysis process and reveal details of allosteric interactions. We developed a Python package called correlationPlus that can facilitate and accelerate the dynamical correlation analyses. The package contains both an API and a command line interface. It analyzes raw dynamical correlation maps and plots 2D heatmaps. It can extract the correlation map of individual chains automatically. The correlations can be projected onto PDB structures with correlationPlus and they can be visualized by the popular molecular visualization software VMD. Several studies showed that graph theoretical analysis of dynamical correlations can reveal active sites and domains within proteins. correlationPlus provides a purely Python framework to calculate several graph theoretical centrality measures such as degree, betweenness, closeness, current flow closeness, and current flow betweenness etc. In addition to 2D figures of the centralities, the centrality measure in question can also be projected onto the protein structure with correlationPlus for 3D inspection by VMD. To make correlationPlus app and API available to the scientific community, we need to package and make it distributable. As in many scientific software, correlationPlus also depend on many excellent libraries such as numpy, matplotlib, prody etc. Installation of correlationPlus with pip and/or conda can help the users to install correlationPlus by satisfying the requirements automatically. In this way, the end-users can analyze dynamical correlations rapidly. Unfortunately, we do not have any expertise in the packaging and distribution of Python packages. As a result, we need technical expertise of C3BI for packaging and making correlationPlus distributable to the scientific community.

Related team publications :
Only a Subset of Normal Modes is Sufficient to Identify Linear Correlations in Proteins. Tekpinar, M. , Yildirim, A. 
Journal of Chemical Information and Modeling.  2018 58 (9), 1947-1961
. DOI: 10.1021/acs.jcim.8b00486
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Project Type : Medium
Status : In Progress

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