Computational design of novel diphtheria toxin inhibitors using natural products-based drug discovery

Abstract

Diphtheria, caused by Corynebacterium diphtheriae, is still a major global health concern, especially in resource-limited settings. Current antimicrobial agents target the bacterium specifically, but they do not neutralize the main virulence factor, the diphtheria toxin. Additionally, the emergence of antimicrobial resistance further reduces the effectiveness of current antimicrobial agents, highlighting the need for antimicrobial agents with minimal resistance. This study aims to discover novel small-molecule inhibitors that can directly bind and inhibit the diphtheria toxin, offering a strategic therapeutic approach beyond conventional antimicrobial regimens. A structure-based drug design approach was employed using a curated compound library containing 30,472 natural products. We then employed a series of rigorous computational approaches such as drug-likeness filtration, pharmacophore modeling, molecular docking, MM-GBSA analysis, and ADMET prediction to screen this extensive library of natural products. Furthermore, we used Molecular Dynamics (MD) simulations over 100 nano-seconds to validate the stability of the ligand-protein complex, ensuring the robustness of our findings. Out of the screened compounds, five novel drug candidates exhibited strong binding affinities with binding energies of −10.031 kcal/mol, −9.383 kcal/mol, −8.807 kcal/mol, −8.414 kcal/mol, and −7.870 kcal/mol respectively, surpassing the reference ligand, Ampicillin. Among these, ZINC000013396848 stands out with the highest docking score of − 10.031 kcal/mol and a high energy binding energy of − 75.557 kcal/mol, which supported their potential inhibitory efficacy against the diphtheria toxin. The pharmacokinetic profile of ZINC000013396848 and ZINC000085569420 exhibited low toxicity, including reduced risks of carcinogenicity, and hepatoxicity, positioning them as promising candidates for further investigation. This study identifies ZINC000013396848 as a potent diphtheria toxin inhibitor with the highest docking profile and has been proven to be energetically stable when complex with the target protein. The exceptional performance of ZINC000013396848 in our study warrants further investigation for its potential use in both vitro and vivo studies. • Targeted diphtheria toxin inhibition was explored as a novel therapy, beyond traditional antimicrobial agents. • A library of 30,472 natural compounds from the ZINC database was computationally screened using multi-step in silico methods. • ZINC000013396848 had the highest docking score and strongest binding affinity among all screened compounds. • ADMET and toxicity predictions show ZINC000013396848 & ZINC000085569420 have good pharmacokinetics and low toxicity. • Molecular dynamics showed ZINC000013396848 is highly stable, supporting its promise for further experimental validation.