Designing of sorafenib analogues to target c-RAF for the management of hepatocellular carcinoma; Molecular dynamics and mmPBSA analysis

Introduction Sorafenib remains the only approved treatment for advanced hepatocellular carcinoma (HCC), yet its clinical use is hindered by toxicity and the emergence of drug resistance. Sorafenib's anticancer effects are largely attributed to its inhibition of multiple kinases, including c-Raf, a key player in the Ras-Raf-MEK-ERK signalling cascade that promotes cell growth and survival. Given the critical role of c-Raf in tumor progression, targeting this kinase offers a promising strategy for improving therapeutic outcomes. Developing new analogues with stronger c-Raf inhibition, better pharmacokinetics, and reduced side effects could help address the current limitations of sorafenib. Objectives This study aimed to design novel sorafenib analogues with enhanced binding affinity and favourable pharmacokinetic profiles, specifically targeting the c-Raf kinase to increase therapeutic efficacy against HCC. By using a fragment replacement approach combined with computational methods, the goal was to identify candidates capable of forming stronger, more stable interactions with c-Raf, potentially overcoming resistance linked to sorafenib treatment. Methods A total of 84 sorafenib analogues (A1-A84) were generated by modifying key functional groups, including the 2-picolinamide and substituted phenyl moieties known to influence kinase binding and anticancer activity. These analogues were evaluated through chemoinformatics and pharmacokinetic screening to assess their drug-likeness and safety. Molecular docking was performed to estimate their binding affinity toward c-Raf. Six top-performing analogues (A2, A6, A9, A20, A22, A63) were selected for further analysis. To evaluate their dynamic behaviour, 100 ns all-atom molecular dynamics simulations were conducted, followed by MM-PBSA (Molecular Mechanics Poisson-Boltzmann Surface Area) calculations to determine binding free energies. Principal component analysis (PCA) was carried out to explore key motion patterns within the protein-ligand complexes. Results Molecular docking showed that the selected analogues exhibited stronger binding affinities (-11.6 to -10.9 kcal/mol) compared to sorafenib (-9.3 kcal/mol) and regorafenib (-9.5 kcal/mol). Molecular dynamics simulations substantiated the docking results. MM-PBSA results revealed that at 100 ns, the binding free energy for the c-Raf-sorafenib complex was 86.751 kJ/mol, while the c-Raf complexes with A2, A6, A9, A20, A22, and A63 demonstrated significantly lower free energies of -129.114, -135.637, -136.242, -127.178, -94.25, and -123.176 kJ/mol, respectively, indicating stronger and more stable binding. PCA further confirmed the stability and favourable dynamic profiles of these analogues trajectory with c-Raf. Discussion The improved binding affinities and lower free energies of the top analogues indicate that specific structural changes to sorafenib can enhance its effectiveness against c-Raf. Molecular dynamics and MM-PBSA results suggest the stability and strength of these interactions, particularly for A2, A6, and A9. Conclusion This study identified six promising sorafenib analogues with improved binding affinity, favourable pharmacokinetic characteristics, and stable interactions with c-Raf. By focusing on c-Raf inhibition, the combined use of computational modelling, molecular simulations and mmPBSA analysis provided valuable insights for drug design. Among the candidates, A2, A6, and A9 emerged as promising drug candidates for further development, supporting the potential of targeting c-Raf to enhance therapeutic strategies against hepatocellular carcinoma