Identification of anticancer therapeutic small organic compounds targeting LDHA enzyme and VEGF receptors through the use of a computer-aided structure-based drug design approach

Abstract

It has been reported that LDHA and VEGFRs are being overexpressed in cancer cells to promote cancer progression. Cancer is one of the deadliest diseases worldwide with millions of incidences diagnosed annually (Ferlay, et al., 2021) (Yang, Tian, Wu, Guo, & Lu, 2019). Currently Researchers are exploring accessible and cost-effective ways to combat cancer. One of the promising strategies is to understand the impact of lactate dehydrogenase (LDHA) and Vascular Endothelial Growth Factor Receptors (VEGFRs) in cancer progression (Augoff, Hryniewicz-Jankowska, & Tabola, 2015) (Eichler, Kuhrt, Hoffmann, Wiedemann, & Reichenbach, 2000). It has been reported that LDHA and VEGFRs are being overexpressed in cancer cells to promote cancer progression by providing ATP energy and vascular vessels, respectively (Feng, et al., 2018). In this project we discovered some potential anticancer inhibitors with interesting unique properties that can potentially improve anticancer drugs efficiency. This research is based on in silico identification of small organic molecules that inhibit LDHA enzyme and/or VEGFRs to suppress cancer development. The 3D crystal structures of LDHA enzyme (with PDB code 5W8K and 5W8I) and VEGFRs (with PDB code 3HNG (VEGFR1), 2XIR (VEGFR2) and 4BSJ (VEGFR3)) were downloaded in the Maestro software from RSCB. The entire project was carried out using Maestro 12.7 software except for MD simulations which were carried out in the CHPC platform (Schrödinger, 2021) (CHPC, 2023). Maestro software was validated for its docking efficiency. The protein structures were optimized and minimized using the protein preparation wizard module in Maestro. The binding sites of the protein structures were identified using Site Map tool and their coordination codes were identified using Glide-grid Generation. Ligand libraries (named A – G) with 4 819 ligands in total were generated using reaction-based enumeration, core hopping and some were extracted from PubChem database. The ligands were optimized and minimized using LigPrep. Furthermore, the molecular docking between the ligands and the protein structures were carried out using the Ligand Docking module in Maestro (Schrödinger, 2021). Later, the ligands underwent high throughput screening based on their interaction with the protein and computational ADMET literature test. Only 28 ligands were filtered out from 4816 ligands based on their molecular docking and molecular dynamic characteristics. Among these discovered 28 potential anticancer organic molecules, we have found some thiazole derivatives, imidazole derivatives and silicon-containing organic compounds. Thiazole derivatives, imidazole derivatives and silicon-containing organic compounds have gained interest in cancer research due to their ability to inhibit different types of cancer cells (Gately & West, 2007) (Ali, Lonea, & Aboul-Enein, 2017). Interestingly, some of these organic molecules discovered in this research have novel dual inhibitory characteristics of inhibiting LDHA enzyme and VEGFRs based on their molecular docking and molecular dynamics simulation characteristics. Furthermore, some of these molecules’ binding affinity for LDHA were found to be enhanced by docking them with LDHA crystallized with zinc (PDB code 5W8I). We anticipate that our findings will shade more light towards contributing to the advancement of novel anticancer therapies.