Interactions of 5-deazapteridine derivatives with Mycobacterium tuberculosis and with human dihydrofolate reductases.

There are major differences between the structures of human dihydrofolate reductase (hDHFR) and Mycobacterium tuberculosis dihydrofolate reductase (mtDHFR). These differences may allow us to design more selective mtDHFR inhibitors. In this paper we study the reactions of six different compounds derived from 5-deazapteridine with human and bacterial enzymes. Results suggest that the addition of hydrophobic groups to the aminophenyl ring would increase mtDHFR-inhibitor affinity and selectivity.

LIV-3D-QSAR models for PGI2 receptor ligands using multiple conformations.

A new 3D descriptor, the local intersection volume (LIV), was developed by our group and applied to the construction of 3D-QSAR models for ligands of the PGI(2) receptor (IP). The target compounds are a set of 42 aromatic heterocyclic derivatives [Meanwell et al., J. Med. Chem. 36 (1993), 3884], which show agonist activities in the IP receptor and are inhibitors of platelet aggregation. The LIV-3D-QSAR models were obtained through the analysis of 30% of the generated conformations for each compound, using a combined Genetic Algorithm (GA) and Partial Least Square (PLS) approach [Rogers and Hopfinger, J. Inf. Comput. Sci. 34 (1994) 854]. Statistically, Model 3 is the best as well as the most comprehensive in a mechanistic sense. Furthermore, it can be applied to design new IP ligands.

Synthetic and theoretical studies on the reduction of electron withdrawing group conjugated olefins using the Hantzsch 1,4-dihydropyridine ester.

The Hantzsch 1,4-dihydropyridine ester (1) has been observed to be a useful selective reducing agent for the reduction of electron-withdrawing conjugated double bonds. The rate of this reaction was observed to be dependent upon the nature of the conjugated substituents and, consequently, the electronic nature of the unsaturated double bond. Theoretical calculations confirmed the importance of the HOMO-LUMO gap for this reaction and implicated a hydride transfer, agreeing with the experimentally observed reaction rate order. The calculations also revealed the importance of a boatlike structure of the 1,4-dihydropyridine nucleus as well as a trans arrangement of the ester groups to facilitate the hydride transfer.

Thrombin inhibition by novel benzamidine derivatives: a free-energy perturbation study.

Thrombin is a serine protease responsible for blood coagulation. Since thrombin inhibitors appear to be effective in the treatment and prevention of thrombotic and embolic disorders, considerable attention has been focused on the structure and interactions of this enzyme. In this work, to evaluate the relative free energies of hydration and binding to thrombin for some benzamidine derivatives, we used the finite difference thermodynamic integration (FDTI) algorithm within the Discover program of MSI. By this method, two possible orders of hydration for the candidates were obtained: p-amidinophenylpyruvate > p-(2-oxo-1-propyl)benzamidine > p-methylbenzamidine > p-ethylbenzamidine > p-(1-propyl)benzamidine > benzamidine and p-amidinophenylpyruvate > p-(2-oxo-1-propyl)benzamidine > p-methylbenzamidine > p-ethylbenzamidine > benzamidine > p-(1-propyl)benzamidine. We also obtained the following order for thrombin binding: p-(2-oxo-1-propyl)benzamidine > p-ethylbenzamidine > p-(1-propyl)benzamidine > p-methylbenzamidine > benzamidine > p-amidinophenylpyruvate.

Local intersection volume: a new 3D descriptor applied to develop a 3D-QSAR pharmacophore model for benzodiazepine receptor ligands.

In this work, we have developed a new descriptor, named local intersection volume (LIV), in order to compose a 3D-QSAR pharmacophore model for benzodiazepine receptor ligands. The LIV can be classified as a 3D local shape descriptor in contraposition to the global shape descriptors. We have selected from the literature 49 non-benzodiazepine compounds as a training data set and the model was obtained and evaluated by genetic algorithms (GA) and partial least-squares (PLS) methods using LIVs as descriptors. The LIV 3D-QSAR model has a good predictive capacity according the cross-validation test by "leave-one-out" procedure (Q(2)=0.72). The developed model was compared to a comprehensive and extensive SAR pharmacophore model, recently proposed by Cook and co-workers, for benzodiazepine receptor ligands [J. Med. Chem. 43 (2000) 71]. It showed a relevant correlation with the pharmacophore groups pointed out in that work. Our LIV 3D-QSAR model was also able to predict affinity values for a series of nine compounds (test data set) that was not included into the training data set.