NAD
Description
Background: -------------- Nicotinamide adenine dinucleotide (NADH) is a ubiquitous redox cofactor that participates in a wide range of enzymatic and regulatory processes. These include metabolism, signalling, and diseases such as cancer and neurodegeneration. Our work presents a comprehensive computational structural analysis of NADH recognition across protein families using 345 NADH-bound crystal structures from the Protein Data Bank. Our study establishes a unified biophysical framework that links NADH shape, interaction signatures, and protein context, providing rational insights for cofactor engineering and the design of NADH-targeted inhibitors. Content Description: ------------------------ This dataset contains: (1) code repository (2) Input datasets The code repository provides: (a) Configuration file (/generator/NAIConfig.py) (b) Code (/generator/NAICofactor.py) for generating statistics around NAI (a three-letter identifier for Nicotinamide adenine dinucleotide in the Protein Data Bank) and its interactions with proteins corresponding to six groups of protein-NAI interaction complexes having six distinct shapes. Input datasets: (/groups/): RCSB PDB ids of six different groups of NADH interaction complexes, corresponding to six distinct shapes of the 3-dimensional structures of these complexes Other Data Used in the Computation: ----------------------------------------------------- (1) RCSB PDB Coordinate files: Retrieved from RCSB PDB (https://www.rcsb.org/) (2) Protein-Ligand Interaction Profile (PLIP) reports (retrieved programmatically using PLIP utility (https://github.com/pharmai/plip)) Tools and Databases/Resources Used: ----------------------------------------- (1) PLIP: PLIP: fully automated protein–ligand interaction profiler - PMC, (n.d.). https://pmc.ncbi.nlm.nih.gov/articles/PMC4489249/#_ad93_ (2) Open Babel: N. M O'Boyle, M. Banck, C. A. James, C. Morley, T. Vandermeersch and G. R. Hutchison, Open Babel: An open chemical toolbox. J Cheminform. 2011 Oct 7;3:33. https://doi.org/10.1186/1758-2946-3-33. (3) Biopython: P. J. A. Cock, T. Antao, J. T. Chang, B. A. Chapman, C. J. Cox, A. Dalke, I. Friedberg, T. Hamelryck, F. Kauff, B. Wilczynski and M. J. L. de Hoon, Biopython: freely available Python tools for computational molecular biology and bioinformatics, Bioinformatics, Volume 25, Issue 11, June 2009, Pages 1422–1423. https://doi.org/10.1093/bioinformatics/btp163. (4) Standard Python packages
Files
Steps to reproduce
Shape Identification of NADH Structures and Classification: -------------------------------------------------------------------- In this work, we have studied and analysed 345 PDB entries containing NADH as the co-crystallized complex with enzymes. To get better insights, all the NADH structures extracted from 345 complexes from RCSB PDB were superimposed using the “Quick Align” feature in the Maestro workspace (Schrödinger Suite, Release 2022–1, Academic license). Upon close observation of the various natural shapes of NADH, it was seen that out of 345, 259 of the 3D NADH conformations broadly fell into 6 shapes. The list of PDB ids of these six groups have been provided in the /groups/ folder. Running the Programs to Generate Statistics: --------------------------------------------------- (1) Install Python and all dependencies and packages imported in both: /generator/NAIConfig.py and /generator/NAICofactor.py. (2) Change the high level path: path_higher (/generator/NAIConfig.py ) to point to the right directory. (3) Place the list of RCSB PDB ids corresponding to a group in a directory and override the variable: pdblistfilepath (NAD/tree/main/generator/NAIConfig.py) with the right location for this file. (4) Change group_ (/generator/NAIConfig.py) variable to appropriately point to the right group of complexes. (5) Run NAICofactor.py (e.g., (in a Linux environment) nohup python -u NAICofactor.py> outputfile.out 2>&1 &).
Institutions
- Indian Institute of Technology Hyderabad