• Medha Dave Department of Bioinformatics, Maharaja Krishnakumarsinhji Bhavnagar University, Bhavnagar, Gujarat, India
  • Aditi Daga Department of Microbiology, MVM Science Collage, Saurashtra University, Rajkot, Gujarat, India
  • Rakesh Rawal Department of Cancer Biology, The Gujarat Cancer and Research institute, Ahmedabad, Gujarat, India.


MLL, Fusion Protein, Molecular modeling, Simulation, Structure Prediction


Objective: AF9-MLL has been implicated in the pathogenesis of AML, New Therapeutic regimens are prerequisite for this category of hematological malignancy due to the poor prognosis. The experimental 3D structure of AF9-MLL is not available. Therefore, present study aims in developing the homology model and evaluating the best model through Energy Minimization and MD simulation. The structure further analyzed for functional Annotation.

Methods: To the best of our knowledge, our study is novel in terms of predicting homology based 3D model of AF9-MLL leukemogenic fusion protein, facilitated by I-TASSER. The 3D modeled structure was subsequently optimized with MD simulation for 2 ns. Further stereo-chemical analysis and verification of the best structure so obtained were undertaken by different computational programs including PROCHECK, PROVE, Verify3D and ERRAT.

Results: Homology model predicted from I-TASSER and refined by YASARA showed results with 86.5% residues in the most favorable region, 14.7% in the allowed region, 0.8% in the generously allowed region and 0.3% in the disallowed region. The RMSD between the modeled and the refined structure was found to be 2.37 Ã…. The results of ERRAT, Verify_3D, Prove and ProSA confirmed that the simulated model and energy minimized model is very good then the predicted raw model. The final structure was successfully submitted in Protein Model Database (PMDB) under ID: PM0080061.

Conclusion: In this study, homology model was developed and Validated for MLL-AF9 using bio-informatics tools. These analyses validated that the simulated model is best, robust as well as reliable enough to be used for future study and the functional analysis shows the presence of CXXC domain. Eventually, these molecular and structural studies result in advancement of newer therapies.



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How to Cite

Dave, M., A. Daga, and R. Rawal. “STRUCTURAL AND FUNCTIONAL ANALYSIS OF AF9-MLL ONCOGENIC FUSION PROTEIN USING HOMOLOGY MODELING AND SIMULATION BASED APPROACH”. International Journal of Pharmacy and Pharmaceutical Sciences, vol. 7, no. 12, Dec. 2015, pp. 155-61,



Original Article(s)