Cetamolol Hydrochloride

From the deductive point of view, neurotransmitter receptors can be divided into categories such as cholinergic (muscarinic, nicotinic), adrenergic (alpha- and beta-), dopaminergic, serotoninergic (5-HT1 approximately 5-HT5), and histaminergic (H1 and H2). Selective agonists and antagonists of each receptor subtype can have specific useful therapeutic applications. For understanding the molecular mechanisms of action, an inductive method of analysis is useful.

The aim of the present study is to examine the structure-activity relationships of agents acting on G-protein coupled receptors.

Representative sets of G-PCR agonists and antagonists were identified from the literature and Medline [P.M. Walsh (2003) Physicians' Desk Reference; M.J. O'Neil (2001) The Merck Index]. The molecular weight (MW), calculated logarithm of octanol/water partition coefficient (C log P) and molar refraction (CMR), dipole moment (DM), E(lumo) (the energy of the lowest unoccupied molecular orbital, a measure of the electron affinity of a molecule and its reactivity as an electrophile), E(homo) (the energy of the highest occupied molecular orbital, related to the ionization potential of a molecule, and its reactivity as a nucleophile), and the total number of hydrogen bonds (H(b)) (donors and receptors), were chosen as molecular descriptors for SAR analyses.

The data suggest that not only do neurotransmitters share common structural features but their receptors belong to the same ensemble of G-protein coupled receptor with seven to eight transmembrane domains with their resultant dipoles in an antiparallel configuration. Moreover, the analysis indicates that the receptor exists in a dynamic equilibrium between the closed state and the open state. The energy needed to open the closed state is provided by the hydrolysis of GTP. A composite 3-D parameter frame setting of all the neurotransmitter agonists and antagonists are presented using MW, Hb and mu as independent variables.

It appears that all neurotransmitters examined in this study operate by a similar mechanism with the G-protein coupled receptors.

A new application of TOPological Sub-structural MOlecular DEsign (TOPS-MODE) was carried out in herbicides using computer-aided molecular design. Two series of compounds, one containing herbicide and the other containing nonherbicide compounds, were processed by a k-Means Cluster Analysis in order to design the training and prediction sets. A linear classification function to discriminate the herbicides from the nonherbicide compounds was developed. The model correctly and clearly classified 88% of active and 94% of inactive compounds in the training set. More specifically, the model showed a good global classification of 91%, i.e., (168 cases out of 185). While in the prediction set, they showed an overall predictability of 91% and 92% for active and inactive compounds, being the global percentage of good classification of 92%. To assess the range of model applicability, a virtual screening of structurally heterogeneous series of herbicidal compounds was carried out. Two hundred eighty-four out of 332 were correctly classified (86%). Furthermore this paper describes a fragment analysis in order to determine the contribution of several fragments toward herbicidal property; also the present of halogens in the selected fragments were analyzed. It seems that the present TOPS-MODE based QSAR is the first alternate general "in silico" technique to experimentation in herbicides discovery.