Mutant anaplastic lymphoma kinase inhibitor identification by integrated in silico approaches

Nadeem Ahmad, Salman Ali Khan, Madiha Sardar, Mamona Mushtaq, Ali Raza Siddiqui, Sajida Munsif, Mohammad Nur-e-Alam, Dmitry Nerukh, Zaheer Ul-Haq*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Non-small-cell lung cancer (NSCLC) is the primary form of lung cancer globally and remains a leading cause of mortality. Anaplastic lymphoma kinase (ALK) mutations, such as I1171N + L1198H, have been discovered to confer resistance to current ALK inhibitors, reducing their therapeutic effectiveness. Addressing drug resistance necessitates exploring selective inhibitors for innovative therapeutic approaches. In this study, a structure-based pharmacophore model, using ALK-approved inhibitors, was developed to screen an In-house database for potential mutant ALK inhibitors. Compounds with requisite pharmacophoric features were evaluated for binding potential against the I1171N + L1198H ALK mutant phenotype. Selected hits underwent assessment for chemical reactivity, and dynamics stability. The study identified five chemical scaffolds (NS1-5) with favorable binding modes and pharmacokinetic properties. The conformational ensembles featured the average RMSD values, ranging from 0.4 to 0.6 nm. RMSF analysis revealed consistent side chain fluctuations with reduced flexibility, while Rog analysis indicated convergence of most complexes. NS1 and NS5, in particular emerged as promising candidates, exhibiting remarkable performance than others, with binding free energies of −210.12 ± 9.94 and −163.68 ± 11.14 kcal/mol, respectively. These findings thus suggest further exploration and optimisation of NS1 and NS5 for mutant ALK inhibitors for the treatment of NSCLC.
Original languageEnglish
Pages (from-to)404-419
Number of pages16
JournalMolecular Simulation
Issue number5
Early online date17 Feb 2024
Publication statusPublished - 29 Feb 2024

Bibliographical note

Copyright © 2024 Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis Group in Molecular Simulation on 17th February 2024, available online at: This version is made available under the terms of the Creative Commons Attribution-NonCommercial License (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.


  • Condensed Matter Physics
  • General Materials Science
  • General Chemical Engineering
  • Modeling and Simulation
  • Information Systems
  • General Chemistry


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