If WADDAICA is used in your work, please cite the below two papers:
1. Bai, Q.*, Ma, J., Liu, S., Xu, T., Banegas-Luna, A. J., Pérez-Sánchez, H.*, et al. WADDAICA: A webserver for aiding protein drug design by artificial intelligence and classical algorithm. Computational and Structural Biotechnology Journal 19, 3573-3579, (2021).
https://doi.org/10.1016/j.csbj.2021.06.017
Download:
[EndNote style]
2. Bai, Q., Research and development of MolAICal for drug design via deep learning and classical
programming. arXiv 2020. doi: https://arxiv.org/abs/2006.09747 Download:
[EndNote style]
We are grateful to "Tencent AI Lab Rhino-Bird Focused Research Program (No. JR202004)" who supports the grant for this project. This work was partially supported by grants from the Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia (Spain) under Project 20988/PI/18, Spanish Ministry of Science and Innovation under Project CTQ2017-87974-R, and by European Project Horizon 2020 SC1-BHC-02-2019 [REVERT, ID:848098]. We thank the authors and projects of AutoDock Vina [1], and MolAICal [2], pafnucy [3], onionnet [4], ligdream [5], Chemistry Development Kit [6], Open Babel [7], JSME [8] and Jmol (http://www.jmol.org) for sharing their licenses.
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