2003
DOI: 10.1021/ci020345w
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The Signature Molecular Descriptor. 1. Using Extended Valence Sequences in QSAR and QSPR Studies

Abstract: We present a new descriptor named signature based on extended valence sequence. The signature of an atom is a canonical representation of the atom's environment up to a predefined height h. The signature of a molecule is a vector of occurrence numbers of atomic signatures. Two QSAR and QSPR models based on signature are compared with models obtained using popular molecular 2D descriptors taken from a commercially available software (Molconn-Z). One set contains the inhibition concentration at 50% for 121 HIV-1… Show more

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Cited by 220 publications
(245 citation statements)
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“…[117][118][119][120][121] The descriptor introduced by us [123] is based solely on coordinates and nuclear charges, and dubbed ' 'Coulomb-matrix,' ' M, a symmetric square matrix of N I Â N I dimensions,…”
Section: Coulomb Matrix Descriptormentioning
confidence: 99%
“…[117][118][119][120][121] The descriptor introduced by us [123] is based solely on coordinates and nuclear charges, and dubbed ' 'Coulomb-matrix,' ' M, a symmetric square matrix of N I Â N I dimensions,…”
Section: Coulomb Matrix Descriptormentioning
confidence: 99%
“…The data is modelled as log K (= log[(fraction unbound)/(fraction bound)]). The modelling procedure utilizes support vector machines [27] with a linear kernel, signature descriptors [28] and the conformal prediction framework [29] as implemented in cpsign from GenettaSoft [30]. The latest temporal test set comprising 750 compounds shows an R 2 of 0.7 and an RMSEP of 0.4, with about 80 % of the compounds being within 3-fold of the experimental value of fu.…”
Section: Human Plasma Protein Binding As Fraction Unbound (Fu)mentioning
confidence: 99%
“…There are several approaches to do this. The approach that was followed in this study is to compute signature descriptors 2 [8]. Each signature corresponds a specially constructed directed acyclic labelled subgraph in the molecule graph.…”
Section: Application To Compound Activity Predictionmentioning
confidence: 99%