IN SILICO TARGET FISHING APPROACHES FOR ANTILEISHMANIAL QUINOLINE DERIVATIVES

IN SILICO TARGET FISHING APPROACHES FOR ANTILEISHMANIAL QUINOLINE DERIVATIVES

• Author
• Marília C. da Silva
• Co-authors
• Jéssika O. Viana , Jayne M. S. Santos , Euzébio G. Barbosa , Claudio G. Lima-Junior , Karen C. Weber
• Abstract

• INTRODUCTION
  Quinolines are compounds that have demonstrated activity against parasitic targets,  with  high selectivity and low toxicity, being so extensively studied as potential antimalarial, antibacterial, antifungal, antitumor and antituberculosis potential (1-3).
  In addition, several works have pointed out quinolines as promising antileishmanial agents (4). Our research group synthesized 7 new quinoline derivatives (5), of which two were identified to have activity against L. donovani (4). This parasite species causes one of the most severe forms of leishmaniasis, known as visceral leishmaniasis, responsible for high mortality rates around the world (6).
  However, the knowledge about leishmania biological targets for these ligands is still quite incipient (7). Computational methods have been applied to the identification of potential targets based on ligand structure, through similarity analysis with known inhibitor ligands, and based on receptor structure, through target-ligand interaction studies (8). These methods have demonstrated good predictive power, as confirmed by in vitro enzymatic assays (9).
  
  AIMS
  The present study aims to identify biological targets with high affinities for a set of seven 2-aryl-quinoline-4-carboxylic acids with potential activity against Leishmania donovani strains.
  
  METHODS
  Two target identification approaches were used: (i) ligand-based, searching in target fishing servers based on similarity principles (SwissTargetPrediction), molecular fingerprints (SEA), molecular 3D similarity (ChemMapper), and deep learning-based algorithm (TargetNet), and (ii) receptor-based, using molecular docking studies in 23,000 proteins extracted from the PDB, following the method described by Viana et al. (9). Docking simulations were conducted using the AutoDock Vina program.
  
  RESULTS AND DISCUSSION
  The results of both approaches indicated different enzymes as the target with the highest affinity for the ligands under study. The ligand similarity-based servers identified Dihydroorotate dehydrogenase as the main target of the quinoline derivatives in Homo sapiens. Conversely, the receptor-based study identified the N-myristoyltransferase protein of Leishmania major (LmNMT) as the mechanism of action for the quinoline derivatives in Leishmania species. Based on these results, redocking studies were performed with the same parameters for L. major enzymes, which are the only ones with crystallographic complexes available in PDB, sharing more than 90% of sequence identity to the N-myristoyltransferase of Leishmania donovani (LdNMT) enzymes under study. Additionally, we observed that all compounds exhibited a higher energy value than the PDB inhibitor (-9.9 kcal/mol), with -12.4 kcal/mol in LmNMT and -12.1 kcal/mol in LdNMT for the best-interacting compound in the series. We observed a docking similarity between the PDB inhibitor and the most active compound, highlighting the residues Phe90 and Tyr217 as key interactions for inhibition. Furthermore, ?-? interaction regions added greater ligand stability in the binding site. These findings will guide our undergoing structure-based development of derivatives with improved chemical properties to further optimize the therapeutic potential of quinolines as antileishmanial agents.
  
  CONCLUSION
  In this study, we employed two target fishing approaches, identifying the enzyme N-myristoyltransferase (NMT) from Leishmania as the best putative target for quinoline derivatives in Leishmania spp. Additionally, the active sites of LmNMT and LdNMT showed a high sequence identity, with conservation of the catalytic region. Furthermore, all 7 quinoline derivatives exhibited higher interaction energy compared to the PDB inhibitor, with a high docking score energy. Thus, the target fishing method allowed for the screening and selection of potential targets for the quinolines under study.
  
  ACKNOWLEDGMENT

  The authors would like to thank the National Institute of Science and Technology on Molecular Sciences (INCT-CiMol), Grant CNPq 406804/2022-2, the Laboratory of Quantum Computational Chemistry and UFPB.

   

  REFERENCES
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  [9] de Oliveira Viana, J., Silva e Souza, E., Sbaraini, N., Vainstein, M. H., Gomes, J. N.S.,de Moura, R. O., & Barbosa, E. G. (2023). Scaffold repositioning of spiro-acridine derivatives as fungi chitinase inhibitor by target fishing and in vitro studies. Scientific Reports, 13(1), 7320.
   

   

   

   

• Keywords
• Target prediction, Antileishmanial activity, Molecular Docking
• Modality
• Pôster
• Subject Area
• Quimioinformatics, Bioinformatics and TheoreticalChemistry