Characterization of binding profiles of heparanase with existing small-molecule inhibitors using computational methods

26 October 2023, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Heparanase (HPSE) is an emerging therapeutic target involved in various diseases. The primary function of the glycosyl hydrolase is to cleave heparan sulfate (HS) side chains from heparan sulfate proteoglycans (HSPGs). This process regulates the homeostasis and the integrity of the extracellular matrix (ECM) and the bioavailability of growth factors and cytokines. Overexpression of heparanase has been observed under various pathological conditions, such as cancer, angiogenesis, and inflammation, suggesting HPSE a promising therapeutic target. However, despite decades of research on HPSE inhibitors, no small-molecule HSPE inhibitor has been approved by regulatory agencies. In this study, we used computational tools to provide insights into small-molecule HPSE inhibitors design. We performed a series of molecular dynamics (MD) simulations and binding profile analyses of 48 diverse small-molecule HPSE inhibitors reported by various research labs. Our results identified the key binding residues on HPSE that should be targeted in inhibitor design, considering both their importance in facilitating interactions with the inhibitor and their functional roles. We also performed energy analyses to create a binding energy map showing the energy breakdown on HPSE residues. To guide future HPSE small-molecule inhibitor discovery, we built a pharmacophore model based on key binding features identified in this study. We also selected and discussed good binding modes discovered through MD. Our findings provide insight into the design and development of small-molecule-based HPSE inhibitors.

Keywords

Heparanase
Small-molecule inhibitor
Molecular dynamics
Molecular modeling

Supplementary materials

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Table S1. The Simplified Molecular Input Line Entry System (SMILES) notation of compounds in the library. Figure S1. The interaction frequency histogram of the inhibitors studied during 200 ns molecular dynamics (MD) simulations.
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