摘要
Innovation in drug discovery for human diseases stands to benefit from systems science and next-generation phenomics approaches. An example is idiopathic pulmonary fibrosis (IPF) that is a chronic pulmonary disorder leading to respiratory failure and for which preventive and therapeutic medicines are sorely needed. Matrix metalloproteinases (MMPs), particularly MMP1 and MMP7, have been associated with IPF pathogenesis and are thus relevant to IPF drug discovery. This study evaluates the comparative therapeutic potentials of doxycycline, pirfenidone, and nintedanib in relation to MMP1 and MMP7 using molecular docking, molecular dynamics simulations, and a next-generation phenomics approach. Adsorption, distribution, metabolism, excretion, and toxicity analysis revealed that doxycycline and nintedanib adhered to Lipinski's rule of five, while pirfenidone exhibited no violations. The toxicity analysis revealed favorable safety profiles, with lethal dose 50 values of doxycycline, pirfenidone, and nintedanib being 2240kg, 580, and 500 mg/kg, respectively. Homology modeling validated the accuracy of the structures of the target proteins, that is, MMP1 and MMP7. The Protein Contacts Atlas tool, a next-generation phenomics platform that broadens the scope of phenomics research, was employed to visualize protein contacts at atomic levels, revealing interaction surfaces in MMP1 and MMP7. Docking studies revealed that nintedanib exhibited superior binding affinities with the candidate proteins (-6.9 kcal/mol for MMP1 and -7.9 kcal/mol for MMP7) compared with doxycycline and pirfenidone. Molecular dynamics simulations further demonstrated the stability of protein-ligand complexes. These findings highlight the notable potential of nintedanib in relation to future IPF therapeutics innovation. By integrating in silico and a next-generation phenomics approach, this study opens up new avenues for drug discovery and development for IPF and possibly, for precision/personalized medicines that consider the molecular signatures of therapeutic candidates for each patient.