Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties.

By Peter Ertl, B. Rohde, P. Selzer. 2000

2,881 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology, Spectroscopy

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Noel M. O'Boyle
2. Antony J. Williams
3. Igor V. Tetko
4. Marwin H. S. Segler
5. David B. Ascher
6. Douglas E. V. Pires
7. Jürgen Bajorath
8. Artem Cherkasov

In Molecular Biology

1. Noel M. O'Boyle
2. David B. Ascher
3. Douglas E. V. Pires
4. Geoffrey R. Hutchison
5. Artem Cherkasov
6. Tom L. Blundell
7. Michael K. Gilson
8. Marwin H. S. Segler

In Spectroscopy

1. Igor V. Tetko
2. Jürgen Bajorath
3. Marwin H. S. Segler
4. Antony J. Williams
5. Eric M. Gifford
6. Kiril Lanevskij
7. Remigijus Didziapetris
8. H. van de Waterbeemd

Citations in the corpus

• ChEMBL: a large-scale bioactivity database for drug discovery (2011, methodology): “Having retrieved a list of compounds of interest, a variety of calculated properties such as molecular weight, calculated lipophilicity (AlogP, 27) and polar surface area (28) can be viewed and filtered via a graphical display.”
• Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions (2009, background): “Lead candidates are normally prioritized according to criteria such as drug-likeness [1,2], natural-product likeness [3], predicted activity or Published: 10 June 2009”
• GuacaMol: Benchmarking Models for De Novo Molecular Design (2018, methodology): “Examples: TPSA, logP; • Similarity or dissimilarity to other molecules; • Presence and absence of substructures, functional groups or atom types.”
• In silico generation of novel, drug-like chemical matter using the LSTM neural network (2017, result): “Calculated common molecular descriptors (molecular weight, logP and TPSA [20]) shown in Figure 3 are very similar to those of the ChEMBL set.”
• Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit (2008, methodology): “In relation to cheminfor-matics, OpenBabel supports SMARTS searching [3], molecular fingerprints [4] (both Daylight-type, and struc-tural-key based), and includes group contribution descriptors for LogP [5], polar surface area (PSA) [6] and molar refractivity (MR) [5].”
• ADMET in silico modelling: towards prediction paradise? (2003, methodology): “A fast fragment-based algorithm for PSA has been reporte”