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.

Fungicide resistance is a serious problem for agriculture. This is particularly apparent in the case of powdery mildew fungi. Therefore, there is an urgent need to develop new agrochemicals. Chitin is a well-known elicitor of plant immunity, and fungal pathogens have evolved strategies to overcome its detection. Among these strategies, chitin deacetylase (CDA) is responsible for modifying immunogenic chitooligomers and hydrolysing the acetamido group in the N-acetylglucosamine units to avoid recognition. In this work, we tested the hypothesis that CDA can be an appropriate target for antifungals using the cucurbit powdery mildew pathogen Podosphaera xanthii. According to our hypothesis, RNAi silencing of PxCDA resulted in a dramatic reduction in fungal growth that was linked to a rapid elicitation of chitin-triggered immunity. Similar results were obtained with treatments with carboxylic acids such as EDTA, a well-known CDA inhibitor. The disease-suppression activity of EDTA was not associated with its chelating activity since other chelating agents did not suppress disease. The binding of EDTA to CDA was confirmed by molecular docking studies. Furthermore, EDTA also suppressed green and grey mould-causing pathogens applied to oranges and strawberries, respectively. Our results conclusively show that CDA is a promising target for control of phytopathogenic fungi and that EDTA could be a starting point for fungicide design.

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.