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Ligand Based Virtual Screening Using Self-organizing Maps

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Abstract

Conventional drug discovery methods rely primarily on in-vitro experiments with a target molecule and an extensive set of small molecules to choose the suitable ligand. The exploration space for the selected ligand being huge; this approach is highly time-consuming and requires high capital for facilitation. Virtual screening, a computational technique used to reduce this search space and identify lead molecules, can speed up the drug discovery process. This paper proposes a ligand-based virtual screening method using an artificial neural network called self-organizing map (SOM). The proposed work uses two SOMs to predict the active and inactive molecules separately. This SOM based technique can uniquely label a small molecule as active, inactive, and undefined as well. This can reduce the number of false positives in the screening process and improve recall; compared to support vector machine and random forest based models. Additionally, by exploiting the parallelism present in the learning and classification phases of a SOM, a graphics processing unit (GPU) based model yields much better execution time. The proposed GPU-based SOM tool can successfully evaluate a large number of molecules in training and screening phases. The source code of the implementation and related files are available at https://github.com/jayarajpbalakrishnan/2_SOM_SCREEN

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https://github.com/jayarajpbalakrishnan/2_SOM_SCREEN

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Acknowledgements

The authors acknowledge the Department of Computer Science and Engineering, NIT Calicut, for their constant support in completing this work. We would also like to thank the Central Computer Centre for providing the GPU server for running the programs. Special thanks to Ms. Juby Johnson, Ms. Sharon Sunny, and Sonaal Pradheep, NIT Calicut, for their valuable suggestions.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, National Institute of Technology Calicut, Kerala, India

    P. B. Jayaraj, S. Sanjay, Koustub Raja & G. Gopakumar

  2. Open Source Pharma Foundations, National Institute of Advanced Studies, Bangalore, India

    U. C. Jaleel

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  1. P. B. Jayaraj
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  2. S. Sanjay
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  3. Koustub Raja
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  4. G. Gopakumar
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  5. U. C. Jaleel
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Correspondence to P. B. Jayaraj.

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Jayaraj, P.B., Sanjay, S., Raja, K. et al. Ligand Based Virtual Screening Using Self-organizing Maps. Protein J 41, 44–54 (2022). https://doi.org/10.1007/s10930-021-10030-9

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