SilicoXplore: An integrated cloud platform coupling machine learning with physics-based modelling for end-to-end drug discovery, applied to the computational prioritisation of putative New Delhi metallo-β-lactamase-1 binders.
- DOI
- 10.1016/j.jmgm.2026.109566
- Published
- 2026 Sep 4
- Container
- Journal of molecular graphics & modelling
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jmgm.2026.109566,
title = {SilicoXplore: An integrated cloud platform coupling machine learning with physics-based modelling for end-to-end drug discovery, applied to the computational prioritisation of putative New Delhi metallo-β-lactamase-1 binders.},
author = {Mangal P and Shinde O and Chikhale S and Bhowmick S and Islam MA},
year = {2026},
journal = {Journal of molecular graphics \& modelling},
doi = {10.1016/j.jmgm.2026.109566},
url = {https://doi.org/10.1016/j.jmgm.2026.109566}
}RIS
TY - JOUR TI - SilicoXplore: An integrated cloud platform coupling machine learning with physics-based modelling for end-to-end drug discovery, applied to the computational prioritisation of putative New Delhi metallo-β-lactamase-1 binders. AU - Mangal P AU - Shinde O AU - Chikhale S AU - Bhowmick S AU - Islam MA PY - 2026 JO - Journal of molecular graphics & modelling DO - 10.1016/j.jmgm.2026.109566 UR - https://doi.org/10.1016/j.jmgm.2026.109566 ER -
APA
P, M., O, S., S, C., S, B., & MA, I. (2026). SilicoXplore: An integrated cloud platform coupling machine learning with physics-based modelling for end-to-end drug discovery, applied to the computational prioritisation of putative New Delhi metallo-β-lactamase-1 binders.. Journal of molecular graphics & modelling. https://doi.org/10.1016/j.jmgm.2026.109566
Source records
- pubmed · retrieved 2026-09-26T01:22:13.505Z