NADbinder: Identification of NAD interacting residues in proteins

NADbinder: Identification of NAD Interacting Residues in Proteins Overview NADbinder is a computational platform developed for predicting NAD interacting residues (NIRs) in proteins using amino acid sequence information and machine learning techniques. The method predicts: NAD binding proteins (NADBP) NAD interacting residues (NIRs) without requiring structural information. Research Paper Title: Identification of NAD interacting residues in proteins Authors: Hifzur R Ansari and Gajendra P. S. Raghava Journal: BMC Bioinformatics (2010) DOI: https://doi.org/10.1186/1471-2105-11-160 https://github.com/Piyushh1104/NADbinder.git Background Nicotinamide adenine dinucleotide (NAD⁺) is an important cofactor involved in: Cellular metabolism Energy transfer Signal transduction Regulatory pathways NAD binding proteins play critical roles in many biological functions and diseases. Traditional similarity-based approaches were limited in identifying all NAD binding proteins, especially non-classical proteins lacking Rossmann fold motifs. NADbinder was developed to overcome these limitations using sequence-based computational prediction. Dataset Information The dataset was obtained from: Protein Data Bank (PDB) SuperSite database Ligand Protein Contact (LPC) server Dataset Statistics 555 NAD binding proteins analyzed 1556 protein chains extracted 195 non-redundant protein chains selected 4772 NAD interacting residues identified Redundancy reduction was performed using CD-HIT at 40% sequence identity.