Zeolite micropores become more energetically stable by the occlusion of organic structure directing agents (templates). This energetic stabilisation, if approximated by van der Waals zeo-template interactions, can be calculated in a fast way by using modern computing techniques incorporating big data handling algorithms for massive screening. A software suite is presented which calculates an arbitrarily large 2-D matrix (template×zeolite) giving the zeo-template van der Waals interaction energy corresponding to the minimum energy conformation assuming one template molecule in a pure silica zeolite unit cell. With the goal of simplicity, the software only needs two coordinate input files of template and zeolite unit cell. Though a number of approximations have been considered, the software allows to compare, for a given template, which competing zeolite phases may become more stabilised. Applied to zeolite hypothetical databases, it may be of help to suggest templates for their synthesis.

Recent years have witnessed a remarkable rise in QSAR methods based on MT and its application to drug design. New methodologies have been introduced in the area such as QSAR multi-target, Markov networks or perturbation methods. Moreover, novel topological indices, such as Bourgas' descriptors and other new concepts as the derivative of a graph or cliques capable to distinguish between conformers, have also been introduced. New drugs have also been discovered, including anticonvulsants, anineoplastics, antimalarials or antiallergics, just to name a few. In the authors' opinion, MT and QSAR have moved from an attractive possibility to representing a foundation stone in the process of drug discovery.

No abstract

The results outlined herein can be explained by considering that MT represents a new paradigm in the field of drug design. This means that it is not only an alternative method to the conventional methods, but it is also independent, that is, it represents a pathway to connect directly molecular structure with the experimental properties of the compounds (particularly drugs). Moreover, the process can be realized also in the reverse pathway, that is, designing new molecules from their topological pattern, what opens almost limitless expectations in new drugs development, given that the virtual universe of molecules is much greater than that of the existing ones.

One of the main pharmacological problems today in the treatment of chronic inflammation diseases consists of the fact that anti-inflammatory drugs usually exhibit side effects. The natural products offer a great hope in the identification of bioactive lead compounds and their development into drugs for treating inflammatory diseases. Computer-aided drug design has proved to be a very useful tool for discovering new drugs and, specifically, Molecular Topology has become a good technique for such a goal. A topological-mathematical model, obtained by linear discriminant analysis, has been developed for the search of new anti-inflammatory natural compounds. An external validation obtained with the remaining compounds (those not used in building up the model), has been carried out. Finally, a virtual screening on natural products was performed and 74 compounds showed actual anti-inflammatory activity. From them, 54 had been previously described as anti-inflammatory in the literature. This can be seen as a plus in the model validation and as a reinforcement of the role of Molecular Topology as an efficient tool for the discovery of new anti-inflammatory natural compounds.

A topological-mathematical model obtained by linear discriminant analysis has been used to the search of new nonsteroidal antinflammatory drugs (NSAIDs). After carrying out an in silico screening based on such a model, on the Aldrich database, new structures potentially active were selected. Among these structures stand fourteen compounds, from which only one had been previously recorded as NSAID in the literature. The experimental tests performed on the remaining substances demonstrated that several compounds showed either in vitro or in vivo or both activity. Moreover, four compounds, namely 1,3-bis(benzyloxycarbonyl)-2-methyl-2-thiopseudourea, 4,6-dichloro-2-methylthio-5-phenylpyrimidine, 2-chloro-2',6'-acetoxylidide and trans-1,3-diphenyl-2-propen-1-ol, showed a significant in vivo antinflammatory activity as compared to the reference drug (indomethacin). These results reinforce the role of Molecular Topology as a useful tool for drug discovery.

No abstract

No abstract