Cited by 13Computational Drug Discovery Methodsvaccines and immunoinformatics approachesSynthesis and Characterization of Heterocyclic Compounds

ILP-assisted de novo drug design

Open access
Kaalia, Rama, Srinivasan, Ashwin, Kumar, Amit, Ghosh, Indira·2016·Machine Learning

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Registry

Crossref · 10.1007/s10994-016-5556-x

Cites

43 of 43 references verified0 citation errors · 0 not checkable

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  • ILP has been applied to identifying and predicting ligands.

    “The types of task ILP has been applied to include identifying and predicting ligands (substructures responsible for medical activity) (Finn et al., 1998; Srinivasan et al., 2006; Kaalia et al., 2016)”

    From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Kaalia et al., 2016

    The Conclusions say ILP-derived pharmacophores can identify potential ligands, and the Introduction reports that screening identified known inhibitors. But the Introduction defines ligands as small molecules, not the activity-related structural features described in the parenthesis; those features are pharmacophores. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

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Cites

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1 of the 44 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Martin, Y. C. (2000). DISCO: What we did right and what we missed. In O. F. Guner (Ed.), Pharmacophore perception, development, and use in drug design (Vol. 2, pp. 49-68). San Diego: International University Line.

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Authors
Kaalia, R., Srinivasan, A., Kumar, A., & Ghosh, I.
Affiliations
  • Jawaharlal Nehru University (IN)
  • Birla Institute of Technology and Science, Pilani (IN)
Corresponding author
Srinivasan, Ashwin
Venue
Machine Learning
Published
2016-03-16
Volume
103
Issue
3
Pages
309-341
ISSN
  • 0885-6125 (ISSN-L)
  • 1573-0565
OpenAlex
W2334846969
Cited by
13
References
44
Citations by year
2025: 1 · 2023: 2 · 2022: 2 · 2021: 4 · 2019: 1 · 2017: 1 · 2016: 1
FWCI
0.92
Type
journal article
Language
en
Open access
Locations
Machine Learning (publishedVersion)
Funders
  • Department of Science and Technology, Government of India (Ramanujan Fellowship)
  • Department of Biotechnology, Government of India (BINC Fellowship)
  • DEITY, Government of India
  • DBT, Government of India (Centre of Excellence, SCIS)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
  • Physical Sciences › Chemistry › Organic Chemistry › Synthesis and Characterization of Heterocyclic Compounds
Keywords
de novo drug design, inductive logic programming, molecular interaction fields, aspartic protease, plasmepsin II, Plasmodium falciparum, antimalarial drug discovery, domain-specific constraints

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