Discovery of lupus nephritis targeted inhibitors based on De novo molecular design: comprehensive application of vinardo scoring, ADMET analysis, and molecular dynamics simulation

Abstract

Lupus Nephritis (LN) is an autoimmune disease affecting the kidneys, and conventional drug studies have limitations due to its imprecise and complex pathogenesis. Therefore, the aim of this study was to design a novel Lupus Nephritis-targeted drug with good clinical due potential, high potency and selectivity by computer-assisted approach.NIK belongs to the serine/threonine protein kinase, which is gaining attention as a drug target for Lupus Nephritis. we used bioinformatics, homology modelling and sequence comparison analysis, small molecule ab initio design, ADMET analysis, molecular docking, molecular dynamics simulation, and MM/PBSA analysis to design and explore the selectivity and efficiency of a novel Lupus Nephritis-targeting drug, ClImYnib, and a classical NIK inhibitor, NIK SMI1. We used bioinformatics techniques to determine the correlation between lupus nephritis and the NF-κB signaling pathway. De novo drugs design was used to create a NIK-targeted inhibitor, ClImYnib, with lower toxicity, after which we used molecular dynamics to simulate NIK SMI1 against ClImYnib, and the simulation results showed that ClImYnib had better selectivity and efficiency. Our research delves into the molecular mechanism of protein ligands, and we have designed and validated an excellent NIK inhibitor using multiple computational simulation methods. More importantly, it provides an idea of target designing small molecules.

Communicated by Ramaswamy H. Sarma

Keywords:

• Computer-aided drug design
• De novo drugs design
• molecular docking
• NF-kappaB inducible kinase
• molecular
• dynamics
• MM/pbsa
• electrostatic potential

Authors’ contributions

Kaiyuan Z conceived, designed, and coordinated the study, validated the results, and reviewed the manuscript; Kaiyuan Z and Yingkai T designed and con-ducted the experiments, analyzed the data, and wrote initial manuscript; Kaiyuan Z, Yingkai T, Haiyue Y, Jingtao Y, Lu Tao reviewed the manuscript. Ping X oversaw all the work and provided funding. All authors read and approved the final manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All raw data has been uploaded to https://github.com/kyang1027/ClImYnib. Any questions can be emailed to the first author.

Additional information

Funding

This funding comes from the 2022 National Student Innovation and Entrepreneurship Training Programme Project of Bengbu Medical College [2022103670].