Interactions of heparin derivatives with recombinant human keratinocyte growth factor: Structural stability and bioactivity effect study

Abstract

Heparin and heparan sulfate are important glycosaminoglycans that can regulate the activities of many vital proteins, especially the fibroblast growth factor (FGF) family.Because FGF7 (KGF) has an important role in tissue repair and maintaining the integrity of the mucosal barrier, recombinant human keratinocyte growth factor (rhKGF, palifermin) has been approved for the treatment of wound healing and oral cavity.Due to heparin plays an important role in the KGF signaling pathway, a more detailed study of the drug-drug interactions (DDIs) between rhKGF and heparin at the atomic level and investigating their synergistic effect on each other in terms of biology, especially in silico, is necessary for a better understanding of DDIs. In this study, DDIs between rhKGF and low-molecular weight heparin types (LMWH) were investigated.In this regard, scrutiny of the influence of the synergistic heparin types on the structure and biostability of rhKGF is accomplished using computational methods such as molecular docking and molecular dynamic simulations (MDs). Subsequently, the motion behavior of rhKGF in interaction with LMWHs was evaluated based on eigenvectors by using principal component analysis (PCA). Also, the binding free energies of rhKGF-LMWH complexes were calculated by the molecular mechanics/Poisson-Boltzmann surface area (MM-BPSA) method. The result showed that rhKGFidraparinux (À6.9 kcal/mol) and rhKGF-heparin (À6.0 kcal/mol) complexes had significant binding affinity as well as they had a more stable binding to rhKGF than to other LMWH during 100 ns simulation. However, in order to confirm the curative effect of these drugs, clinical trials must be done.Abbreviations: 2-D structure, two-dimensional structure; AUC, area under the curve; CL, average total body clearance; FGF, fibroblast growth factor; HS, heparin sulfate; KGF, keratinocyte growth factor; LINCS, linear constraint solver; LMWH, low-molecular weight heparin; MD, molecular dynamics; MM-PBSA, molecular mechanics-PoissonBoltzmann surface area; MW, molecular weight; NPT, constant number of particles, pressure, and temperature; NVT, constant number of particles, volume, and temperature; OM, oral mucositis; PCA, principal component analysis; PDB, Protein Data Bank; R g , radius of gyration; rhKGF, recombinant human keratinocyte growth factor; RMSD, root mean square deviation; RMSF, root mean square fluctuations; UH, unfractionated heparin; ULMWH, ultra-low molecular weight heparin; Vss, volume of distribution at steady state; ΔE ele , electrostatic contribution; ΔE MM , energy of the molecular mechanics; ΔE vdw , Van der Waals contributions; ΔGnonpol, nonpolar contribution; ΔGpol, polar solvation contribution.

In Silico Identification of Natural Food Compounds as Potential Quorum-Sensing Inhibitors Targeting the LasR Receptor of Pseudomonas aeruginosa

“…By analyzing the first three principal components (PC1, PC2, and PC3) that account for the most variance in the original data (i.e. the largest uncorrelated motion in the trajectory) 44 of tp1 and the four other systems, we observed that ZINC000014708292 accounted for higher variances of 56.2% for the total of the first three PCs, indicating that this ligand increased the motion of the protein’s Cα-atoms, 45 followed by ZINC000014819517, which showed a variance of 48.7%. ZINC000001580795 and ZINC000004098719 exhibited a variance of 36.1% and 36.7%, respectively, meaning that these two ligands induced more stable movement of the protein’s Cα atoms than TP1, which showed a variance of 33.9% for the total of the first three PCs.…”