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A computationally affordable approach for accurate prediction of the binding affinity of JAK2 inhibitors

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Abstract

Janus kinase 2 (JAK2) inhibitors are potential anticancer drugs in the treatment of lymphoma, leukemia, thrombocytosis and particularly myeloproliferative diseases. However, the resemblance among JAK family members has challenged the identification of highly selective inhibitors for JAK2 to reduce undesired side effects. As a result, a robust search for promising JAK2 inhibitors using a computational approach that can effectively nominate new potential candidates to be further analyzed through laborious experimental operations has become necessary. In this study, the binding affinities of JAK2 inhibitors were rapidly and precisely estimated using the fast pulling of ligand (FPL) simulations combined with a modified linear interaction energy (LIE) method. The approach correlates with the experimental binding affinities of JAK2 inhibitors with a correlation coefficient of R = 0.82 and a root-mean-square error of 0.67 kcal•mol−1. The data reveal that the FPL/LIE method is highly approximate in anticipating the relative binding free energies of known JAK2 inhibitors with an affordable consumption of computational resources, and thus, it is very promising to be applied in in silico screening for new potential JAK2 inhibitors from a large number of molecules available.

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Data availability

The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.

Code availability

The code generated during the current study is available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Institute of Materials Science, Vietnam Academy of Science and Technology, Hanoi, Vietnam

    Nguyen Thi Mai & Nguyen Thanh Tung

  2. Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam

    Nguyen Thi Mai, Ngo Thi Lan & Nguyen Thanh Tung

  3. Institute of Science and Technology, TNU-University of Sciences, Thai Nguyen, Tan Thinh, Vietnam

    Ngo Thi Lan

  4. Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Thien Y. Vu

  5. NTT Hi-Tech Institute, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

    Huong Thi Thu Phung

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  1. Nguyen Thi Mai
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  2. Ngo Thi Lan
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  3. Thien Y. Vu
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  4. Nguyen Thanh Tung
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Contributions

All authors had contributed to the study’s conception and design. Material preparation, data collection and analysis were performed by Nguyen Thi Mai, Ngo Thi Lan and Thien Y Vu. The first draft of the manuscript was written by Huong Thi Thu Phung and Nguyen Thanh Tung, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Nguyen Thanh Tung or Huong Thi Thu Phung.

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Mai, N.T., Lan, N.T., Vu, T.Y. et al. A computationally affordable approach for accurate prediction of the binding affinity of JAK2 inhibitors. J Mol Model 28, 163 (2022). https://doi.org/10.1007/s00894-022-05149-0

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