A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking

@article{Ballester2010AML,
  title={A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking},
  author={Pedro J. Ballester and John B. O. Mitchell},
  journal={Bioinformatics},
  year={2010},
  volume={26 9},
  pages={1169-75}
}
MOTIVATION Accurately predicting the binding affinities of large sets of diverse protein-ligand complexes is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for analysing the outputs of molecular docking, which in turn is an important technique for drug discovery, chemical biology and structural biology. Each scoring function assumes a predetermined theory-inspired functional form for the relationship between the variables that… CONTINUE READING
Highly Influential
This paper has highly influenced 16 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Recent Discussions
This paper has been referenced on Twitter 1 time over the past 90 days. VIEW TWEETS
77 Extracted Citations
49 Extracted References
Similar Papers

Citing Papers

Publications influenced by this paper.
Showing 1-10 of 77 extracted citations

Referenced Papers

Publications referenced by this paper.
Showing 1-10 of 49 references

Comparative Assessment of Scoring Functions on a Diverse Test Set

  • T Cheng
  • J. Chem. Inf. Model.,
  • 2009

Similar Papers

Loading similar papers…