LWPQ: an in silico designed multi-core super-agonist motif-like regulatory peptide for the activation of human stem cell transcripts using an integrated computational approach

The role of KIT ligand CXC chemokine receptor CXCR4, fibroblast growth factors and their receptors (FGFRs), Notch or its ligand Jagged1 and retinoic acid (RA) signaling in determining the fate of these cells in the regulation of normal hematopoietic stem cells is well-known An increasing amount of evidence from experimental and computational bioinformatic analysis suggests that there are many domains in DNA sequences that remain evolutionarily conserved. In some cases, these conserved patterns in a collection of unaligned DNA and protein sequences present the same functional and regulatory properties and are significant for the molecular role of these sequences. Discriminative motif finding algorithms aim to increase the sensitivity and selectivity of conserved motif discovery by utilizing a specific set of DNA and protein sequences, and searching for binding sites and homolog repeats among the sets of the selected sequences. In the present study we introduce a combined bioinformatic software-based discriminative methodology to detect short, highly and most conserved motifs between the DNA sequences within the FLT3, CXCR4, CKIT, HOXB4, JAGGED1, FGF1 proteins and then, on finding out a multi-target motif conserved featured superagonist peptide about them including their physical regulatory properties, as well as their function as an ex-vivo positive modulator for the enhancement of human stem cell expansion rates.