Combined multi-parameter filtering and prioritization of a chemical library for cancer disease target

Cancer is a multifactorial disease and remains a significant problem owing to its complex nature. There is an urgent need to identify and design hybrid anticancer drugs that achieve a desired biological effect by combining two or more pharmacophores into a single molecule. Herein, we utilized MOLHYBRID program to generate a chemical library of 46740 unique molecules based on known anticancer pharmacophores and targeting the cancer protein, using the crystal structure of the B-Raf V600E oncogenic mutant in complex PLX4033 (vemurafenib) (PDB ID: 3OG7). The B-Raf V600E mutant is prevalent cancer-associated kinase mutation, particularly in melanoma, where it promotes the activation of the RAF/MEK/ERK. A comprehensive analysis of the chemical library and virtual screening was conducted using several computational methods such as molecular docking, molecular dynamics (MD) simulations, and density functional theory (DFT). To further elucidate the distinctiveness and three-dimensionality (3D) of the molecules, several other techniques such as principal moment of inertia (PMI), Murcko scaffold analysis, molecular frameworks (MFs), and multi-fusion similarity maps (MFSM) were used. The filtering cut-off was performed using the synthetic accessibility score (SAS) and quantitative estimation of drug-likeness (QED) using the criteria SAS values < 6 and QED values > 0.4. After intensive filtering of the molecules also based on drug-likeness rules, molecule 40254 had the strongest binding energy of -8.70 kcal/mol. The pharmacological evaluation suggested that the selected molecules showed adherence to Lipinski's rule with minimal violations (0 - 1). The four molecules (40254, 39155, 11090, and 7879), which were selected as potential hits, exhibited stability in the binding pocket of the protein during the MD simulations. Overall, the root mean square deviation (RMSD) remained stable at around 4.0 Å. The analyses of evaluating stability also include the root mean square fluctuation (RMSF), protein-ligand contacts, and radius of gyration (Rg). DFT was used to investigate the chemical reactivity, and it suggested that the most reactive molecule was molecule 14186 with a small energy gap of 3.09 eV, a high softness of 0.64 eV, and a greater electrophilicity index of 4.46 eV. Collectively, these findings justify further experimental work on the four promising candidates for anti-cancer agents.