Papers about MolAICal
(#: Co-first; *: Co-corresponding)
[4]. Bai, Q.*, Liu, S., Tian, Y., Xu, T.*, Banegas-Luna, A. J., Pérez-Sánchez, H.*, et al. Application advances of deep learning methods for de novo drug design and molecular dynamics simulation. WIREs Comput Mol Sci. 2021;e1581. https://doi.org/10.1002/wcms.1581
[3]. 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
[2]. Bai, Q.*, et al. MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm. Briefings in bioinformatics 2021, 22, bbaa161. https://doi.org/10.1093/bib/bbaa161
[1]. 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