Benjamin G Tehan
Monash University, Parkville campus
6 Papers
17 Citations
Benjamin G Tehan is an academic researcher from Monash University, Parkville campus. The author has contributed to research in topics: Binding site & Dopaminergic. The author has an hindex of 5, co-authored 6 publications.
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Papers
A Consensus Neural Network-Based Technique for Discriminating Soluble and Poorly Soluble Compounds
David T. Manallack,Benjamin G Tehan,Emanuela Gancia,Brian D Hudson,Martyn G Ford,David J. Livingstone,David C. Whitley,William R. Pitt +7 more
TL;DR: This paper presents studies of consensus neural networks trained on BCUTs to discriminate compounds with poor aqueous solubility from those with reasonablesolubility, intended to be used as a filter in the selection of screening candidates, compound purchases, and the application of synthetic priorities to combinatorial libraries.
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Molecular field analysis of clozapine analogs in the development of a pharmacophore model of antipsychotic drug action.
TL;DR: This modeled series of 30 clozapine analogs using a pharmacophore based on the ligands octoclothepin and tefludazine provides an excellent framework to aid in the design of novel antipsychotics with diminished propensity to produce clinically limiting side effects.
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Molecular Mapping in the CNS
TL;DR: An overview of the latest strategies used in 3D-QSAR based drug design and survey the most recent applications of these strategies to the CNS are given.
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Analysis of agonism by dopamine at the dopaminergic D2 G-protein coupled receptor based on comparative modelling of rhodopsin
TL;DR: A number of theoretical dopaminergic D 2 models were constructed using comparative modelling techniques and revealed the importance of the chi angle of serine 197 and the effect this has on the bending of helix 5 when an agonist is present in the binding site.
1
Estimation of pKa Using Semiempirical Molecular Orbital Methods. Part 1: Application to Phenols and Carboxylic Acids.
Benjamin G Tehan,Edward John Lloyd,Margaret G. Wong,William R. Pitt,John Gary Montana,David T. Manallack,Emanuela Gancia +6 more
TL;DR: In this article, a set of QM properties derived from frontier electron theory have been used to produce a predictive model of the dissociation constants of phenols, benzoic acids and aliphatic carboxylic acids.