Estimation of Aqueous Solubility of Chemical Compounds Using E-State Indices

By Igor V. Tetko, V. Tanchuk, T. Kasheva, A. Villa. Journal of chemical information and computer sciences, 2001

334 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computational Theory and Mathematics, Electrochemistry

View Paper: https://www.semanticscholar.org/paper/6b22b574aed6b71975e8e094c71e58a54a860a0b

How researchers see this paper

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

In Biomedical Engineering

1. John C. Dearden
2. Igor V. Tetko
3. Antony J. Williams
4. Igor I. Baskin
5. Gennadiy Poda
6. Valery Tkachenko

In Computational Theory and Mathematics

1. Igor V. Tetko
2. Antony J. Williams
3. John C. Dearden
4. Gennadiy Poda
5. Igor I. Baskin
6. Matthias Rupp 
7. Valery Tkachenko
8. Raimund Mannhold

In Electrochemistry

1. John C. Dearden

Citations in the corpus

• Contribution of solid-state properties to the aqueous solubility of drugs. (2006, methodology): “…derived models based on 2D or 3D chemical descriptors (Abraham and Le, 1999; Catana et al., 2005; Delaney, 2004; Huuskonen et al., 2000; Katritzky et al., 1998; Lind and Maltseva, 2003; Meylan and Howard, 2000; Raevsky et al., 2004; Tetko et al., 2001; Votano et al., 2004; Yan and Gasteiger, 2003).”
• Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information (2011, background): “ALOGPS descriptors (2D) predict logP [54] and the aqueous solubility [55] of chemicals.”
• Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules (2007, neutral): “[23], and later revised by several authors[24, 25, 26].”
• Extended Functional Groups (EFG): An Efficient Set for Chemical Characterization and Structure-Activity Relationship Studies of Chemical Compounds (2015, neutral): “Solubility in water [11] Estate 1311 ASNN 0.”
• In silico prediction of aqueous solubility (2006, methodology): “They took six of the methods listed in Table 2 [3,30,91-96], all of which are based on two dimensional descriptors and do not require the melting point of a compound to be used.”
• Calculation of molecular lipophilicity: state of the art and comparison of methods on more than 96000 compounds (2009, result): “A similar behavior was observed with predictions of the aqueous solubility of chemicals.(166) We confirm these claims in Figure 2: for the public and the Pfizer datasets all methods produced larger RMSE for molecules with larger numbers of NHA.”