Several commonly used molecular mechanics force fields have been tested for accuracy in conformational energy calculations. Differences in performance between the force fields are discussed for different classes of structures. MMFF93 and force fields based on the MM2 or MM3 functional form are found to perform significantly better than other force fields in the test, with average conformational energy errors around 0.5 kcal/mol. CFF91 also reaches this accuracy for the subset in which fully determined parameters are used, but it doubles the overall error due to use of estimated parameters. Harmonic force fields generally have average errors exceeding 1 kcal/mol. Factors influencing accuracy are identified and discussed. 0 1996 by John Wiley & Sons, Inc. different programs can be run on personal computers or small workstations. The problem today in routine work is not so much how to perform the calculation as what force field to use. A few years ago, two of us participated in a compafison of some of the most popular force fields at that time.' However, the last few years have seen the advent
The serotonin transporter (SERT) is one of the neurotransmitter transporters that plays a critical role in the regulation of endogenous amine concentrations and therefore is an important target for therapeutic agents affecting the central nervous system. The recently published, high resolution X-ray structure of the closely related amino acid transporter, Aquifex aeolicus leucine transporter (LeuT), provides an opportunity to develop a three-dimensional model of the structure of SERT. We present herein a homology model of SERT using LeuT as the template and containing escitalopram as a bound ligand. Our model explains selectivities known from mutational studies and varying ligand data, which are discussed and illustrated in the paper.
A receptor-interaction model for serotonin 5-HT2 receptor antagonists has been developed by conformational analysis with molecular mechanics (MM2(91)) and superimposition studies of serotonin 5-HT2 receptor antagonists. Substituted 3-(4-piperidinyl)-,1-(4- piperidinyl)-,3-(1,2,3,6-tetrahydropyridin-4-yl)-, and 1-(1,2,3,6-tetrahydropyridin-4-yl)-1H-indoles, substituted 3-(4-fluorophenyl)-1-(4-piperazinyl)indans, cyprohepatadine derivatives, ritanserin, and danitracene have been used as bases for the model. Other serotonin 5-HT2 receptor antagonists, such as ketanserin and MDL 11,939, are well accommodated into the model. Comparison of the model with a recently described receptor-interaction model for dopamine D2 receptor antagonists suggests a common pharmacophore for dopamine D2 and serotonin 5-HT2 receptor antagonists. Important steric differences between 5-HT2 receptor antagonists with additional high affinity for dopamine D2 receptors and serotonin 5-HT2 receptor antagonists with high selectivity versus D2 receptors are described. The geometry of the receptor-interaction model described is significantly different from that of a recently reported receptor-interaction model for 5-HT2 receptor agonists and antagonists developed by use of (+)-LSD as a template, suggesting the existence of two binding modes at the 5-HT2 receptor.
The molecular alignments obtained from a previously reported pharmacophore model have been employed in a three-dimensional quantitative structure-activity relationship (3D QSAR) study, to obtain a more detailed insight into the structure-activity relationships for D(2) and D(4) receptor antagonists. The frequently applied CoMFA method and the related CoMSIA method were used. Statistically significant models have been derived with these two methods, based on a set of 32 structurally diverse D(2) and D(4) receptor antagonists. The CoMSIA and the CoMFA methods produced equally good models expressed in terms of q(2) values. The predictive power of the derived models were demonstrated to be high. Graphical interpretation of the results, provided by the CoMSIA method, brings to light important structural features of the compounds related to either low- or high-affinity D(2) or D(4) antagonism. The results of the 3D QSAR studies indicate that bulky N-substituents decrease D(2) binding, whereas D(4) binding is enhanced. Electrostatically favorable and unfavorable regions exclusive to D(2) receptor binding were identified. Likewise, certain hydrogen-bond acceptors can be used to lower D(2) affinity. These observations may be exploited for the design of novel dopamine D(4) selective antagonists.
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