SAMPL7 physical property prediction from EC-RISM theory.
- Published in:
- Journal of Computer-Aided Molecular Design, 2021, v. 35, n. 8, p. 933, doi. 10.1007/s10822-021-00410-9
- By:
- Publication type:
- Article
Works matching IS 0920654X AND DT 2021 AND VI 35 AND IP 8
Results: 6
1
2
Multiple linear regression models for predicting the n‑octanol/water partition coefficients in the SAMPL7 blind challenge.
- Published in:
- Journal of Computer-Aided Molecular Design, 2021, v. 35, n. 8, p. 923, doi. 10.1007/s10822-021-00409-2
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- Publication type:
- Article
3
Energy–entropy method using multiscale cell correlation to calculate binding free energies in the SAMPL8 host–guest challenge.
- Published in:
- Journal of Computer-Aided Molecular Design, 2021, v. 35, n. 8, p. 911, doi. 10.1007/s10822-021-00406-5
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- Publication type:
- Article
4
Multitask machine learning models for predicting lipophilicity (logP) in the SAMPL7 challenge.
- Published in:
- Journal of Computer-Aided Molecular Design, 2021, v. 35, n. 8, p. 901, doi. 10.1007/s10822-021-00405-6
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- Publication type:
- Article
5
Binding affinity prediction for binary drug–target interactions using semi-supervised transfer learning.
- Published in:
- Journal of Computer-Aided Molecular Design, 2021, v. 35, n. 8, p. 883, doi. 10.1007/s10822-021-00404-7
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- Publication type:
- Article
6
Druggable hot spots in trypanothione reductase: novel insights and opportunities for drug discovery revealed by DRUGpy.
- Published in:
- Journal of Computer-Aided Molecular Design, 2021, v. 35, n. 8, p. 871, doi. 10.1007/s10822-021-00403-8
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- Publication type:
- Article