Interactive 3D Visualization Engine for Molecular Docking and Structural Complex Analysis
DOI:
https://doi.org/10.61467/2007.1558.2026.v17i3.1274Keywords:
Molecular Docking, Webserver molecular visualizers, 3D molecular structure viewer, Acoplamiento molecular, visualizadores moleculares en línea, visor de estructuras moleculares en 3DAbstract
This paper presents the initial development of a new docking analysis tool leveraging WebGL for real-time molecular visualization directly in the browser eliminating the installation burden and offering a fresh level of interactivity and modularity in docking result interpretation. The methodology consists of developing a web API in the Python programming language, implementing the interaction between the React Framework and the underlaying Python script to process data, cluster the docked conformation, calculate the secondary structure of the protein PDB file and retrieve the results to the React Framework to visual representation. The tool renders visual components of the 3D molecular structure viewer in react-three/fiber, react-three/drei, and WebGL, providing a user-friendly and modern interface; and leveraging the computational pipeline capabilities to reduce CPU load to the WebGL engine.
Spanish-language metadata / Metadatos en español
Título en español:
Motor de visualización 3D interactivo para el acoplamiento molecular y el análisis de complejos estructurales
Resumen:
Este artículo presenta el desarrollo inicial de una nueva herramienta de análisis de acoplamiento que aprovecha WebGL para la visualización molecular en tiempo real directamente en el navegador, lo que elimina la necesidad de instalación y ofrece un nuevo nivel de interactividad y modularidad en la interpretación de los resultados del acoplamiento. La metodología consiste en desarrollar una API web en el lenguaje de programación Python, implementando la interacción entre el marco React y el script de Python subyacente para procesar datos, agrupar la conformación acoplada, calcular la estructura secundaria del archivo PDB de la proteína y enviar los resultados al marco React para su representación visual. La herramienta representa los componentes visuales del visor de estructuras moleculares en 3D en React-Three/Fiber, React-Three/Drei y WebGL, lo que ofrece una interfaz moderna y fácil de usar; además, aprovecha las capacidades del proceso computacional para reducir la carga de la CPU en el motor WebGL.
Palabras Claves:
Acoplamiento molecular, visualizadores moleculares en línea, visor de estructuras moleculares en 3D
Smart citations:
https://scite.ai/reports/10.61467/2007.1558.2026.v17i3.1274
Dimensions.
Open Alex.
References
Ahmad, S. (2023, August 19). Exploring PyMOL colors for molecular visualization. LinkedIn. https://www.linkedin.com/pulse/exploring-pymol-colors-molecular-visualization-sunail-ahmad-/
Dey, R., Chaube, U., Bhatt, H., & Patel, B. (2025). Small molecule drug design. In Encyclopedia of Bioinformatics and Computational Biology (2nd ed., Vol. 6, pp. 622–633). Elsevier. https://doi.org/10.1016/B978-0-323-95502-7.00262-1
García-Pérez, C., Therón, R., & López-Pérez, J. L. (2017). JADOPPT: Java based AutoDock preparing and processing tool. Bioinformatics, 33(4), 583–585. https://doi.org/10.1093/bioinformatics/btw677
Goddard, T. D., Huang, C. C., Meng, E. C., Pettersen, E. F., Couch, G. S., Morris, J. H., & Ferrin, T. E. (2018). UCSF ChimeraX: Meeting modern challenges in visualization and analysis. Protein Science, 27(1), 14–25. https://doi.org/10.1002/pro.3235
Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics, 14(1), 33–38. https://doi.org/10.1016/0263-7855(96)00018-5
Khronos Group. (n.d.). WebGL: Low-level 3D graphics API based on OpenGL ES. Retrieved June 4, 2026, from https://www.khronos.org/webgl/
Molsoft. (n.d.). IcmJS: JavaScript 3D molecular viewer. Retrieved June 4, 2026, from https://www.molsoft.com/activeicmjs.html
Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., & Olson, A. J. (2009). AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30(16), 2785–2791. https://doi.org/10.1002/jcc.21256
Nguyen, H., Case, D. A., & Rose, A. S. (2018). NGLview: Interactive molecular graphics for Jupyter notebooks. Bioinformatics, 34(7), 1241–1242. https://doi.org/10.1093/bioinformatics/btx789
NIH Resource for Macromolecular Modeling and Bioinformatics, & Theoretical and Computational Biophysics Group. (2012, January 29). VMD user’s guide (Version 1.9.1). University of Illinois at Urbana-Champaign. https://www.ks.uiuc.edu/Research/vmd/vmd-1.9.1/ug/ug.html
Nipype. (2025). pydra: 1.0a2 [Computer software]. Zenodo. https://zenodo.org/records/16671149
PyMOL. (n.d.). Welcome to PyMOL. Retrieved June 4, 2026, from https://pymol.org/dokuwiki/doku.php?id=welcome
Rego, N., & Koes, D. (2015). 3Dmol.js: Molecular visualization with WebGL. Bioinformatics, 31(8), 1322–1324. https://doi.org/10.1093/bioinformatics/btu829
Rose, A. S., & Hildebrand, P. W. (2015). NGL Viewer: A web application for molecular visualization. Nucleic Acids Research, 43(W1), W576–W579. https://doi.org/10.1093/nar/gkv402
Rose, A. S., Bradley, A. R., Valasatava, Y., Duarte, J. M., Prlić, A., & Rose, P. W. (2018). NGL viewer: Web-based molecular graphics for large complexes. Bioinformatics, 34(21), 3755–3758. https://doi.org/10.1093/bioinformatics/bty419
Schrödinger, LLC. (2015). The PyMOL molecular graphics system (Version 1.8) [Computer software].
Seeliger, D., & de Groot, B. L. (2010). Ligand docking and binding site analysis with PyMOL and Autodock/Vina. Journal of Computer-Aided Molecular Design, 24, 417–422. https://doi.org/10.1007/s10822-010-9352-6
Sehnal, D., Bittrich, S., Deshpande, M., Svobodová, R., Berka, K., Bazgier, V., Velankar, S., Burley, S. K., Koča, J., & Rose, A. S. (2021). Mol* Viewer: Modern web app for 3D visualization and analysis of large biomolecular structures. Nucleic Acids Research, 49(W1), W431–W437. https://doi.org/10.1093/nar/gkab314
Seshadri, K., Liu, P., & Koes, D. R. (2020). The 3Dmol.js Learning Environment: A Classroom Response System for 3D Chemical Structures. Journal of Chemical Education, 97(10), 3872–3876. https://doi.org/10.1021/acs.jchemed.0c00579
Spivak, M., Stone, J. E., Ribeiro, J., Saam, J., Freddolino, L., Bernardi, R. C., & Tajkhorshid, E. (2023). VMD as a platform for interactive small molecule preparation and visualization in quantum and classical simulations. Journal of Chemical Information and Modeling, 63(15), 4664–4678. https://doi.org/10.1021/acs.jcim.3c00658
Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimisation, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
University of Pittsburgh. (n.d.). Using 3Dmol.js. Retrieved August 1, 2025, from https://3dmol.csb.pitt.edu/doc/
Varela-Salinas, G., García-Pérez, C. A., Peláez, R., & Rodríguez, A. J. (2017). Visual clustering approach for docking results from Vina and AutoDock. In F. Martínez de Pisón, R. Urraca, H. Quintián, & E. Corchado (Eds.), Hybrid Artificial Intelligent Systems. HAIS 2017 (Lecture Notes in Computer Science, Vol. 10334, pp. 342–353). Springer. https://doi.org/10.1007/978-3-319-59650-1_29
Yuan, S., Chan, H. C. S., & Hu, Z. (2017). Using PyMOL as a platform for computational drug design. WIREs Computational Molecular Science, 7(2), Article e1298. https://doi.org/10.1002/wcms.1298
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
