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CavFind: A Novel Algorithm to Detect Cavities on Protein Structure

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Proceedings of Fifth International Conference on Computer and Communication Technologies (IC3T 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 897))

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Abstract

Various essential functions in living organisms are performed by binding of proteins with other molecules (ligands). Proper detection and analysis of ligand binding locations (cavities) leads towards the success of the overall drug designing system. The main challenge towards that goal is that the problem is computationally hard. In the present study, a soft computing-based algorithm has been proposed that is capable of detecting cavities on protein’s structure. The proposed algorithm is based on Voronoi decomposition and implemented by applying the self-organizing map (SOM) clustering algorithm. The proposed algorithm is evaluated with 48 protein–ligand complexes and compared with two existing algorithms like Fpocket and ConCavity and compared with the results stored in two existing databases like BioLiP and CaviDB. The proposed algorithm is also capable of computing some descriptors of the detected cavities.

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Acknowledgements

Authors are thankful to The University of Burdwan for their support and infrastructure. Authors are also thankful to the RCSB PDB for their online dataset.

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Authors and Affiliations

  1. Department of Computer Science, The University of Burdwan, Golapbag, Purba Bardhaman, West Bengal, 713104, India

    Swati Adhikari & Parthajit Roy

Authors
  1. Swati Adhikari
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  2. Parthajit Roy
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Corresponding author

Correspondence to Parthajit Roy .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Kakatiya Institute of Technology and Science, Hanumakonda, Telangana, India

    B. Rama Devi

  2. Department of Electronics and Communication Engineering, National Institute of Technology, Warangal, Warangal, Telangana, India

    Kishore Kumar

  3. Department of Electronics and Communication Engineering, Kakatiya Institute of Technology and Science, Hanamkonda, Telangana, India

    M. Raju

  4. Department of CSE and IT, CMR Technical Campus, Hyderabad, Telangana, India

    K. Srujan Raju

  5. Department of Science and Engineering, Heriot-Watt University, Edinburgh, UK

    Mathini Sellathurai

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Adhikari, S., Roy, P. (2024). CavFind: A Novel Algorithm to Detect Cavities on Protein Structure. In: Devi, B.R., Kumar, K., Raju, M., Raju, K.S., Sellathurai, M. (eds) Proceedings of Fifth International Conference on Computer and Communication Technologies. IC3T 2023. Lecture Notes in Networks and Systems, vol 897. Springer, Singapore. https://doi.org/10.1007/978-981-99-9704-6_6

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