Unified QSAR approach to antimicrobials. Part 3: first multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds.

Several pathogen parasite species show different susceptibilities to different antiparasite drugs. Unfortunately, almost all structure-based methods are one-task or one-target Quantitative Structure-Activity Relationships (ot-QSAR) that predict the biological activity of drugs against only one parasite species. Consequently, multi-tasking learning to predict drugs activity against different species by a single model (mt-QSAR) is vitally important. In the two previous works of the present series we reported two single mt-QSAR models in order to predict the antimicrobial activity against different fungal (Bioorg. Med. Chem.2006, 14, 5973-5980) or bacterial species (Bioorg. Med. Chem.2007, 15, 897-902). These mt-QSARs offer a good opportunity (unpractical with ot-QSAR) to construct drug-drug similarity Complex Networks and to map the contribution of sub-structures to function for multiple species. These possibilities were unattended in our previous works. In the present work, we continue this series toward other important direction of chemotherapy (antiparasite drugs) with the development of an mt-QSAR for more than 500 drugs tested in the literature against different parasites. The data were processed by Linear Discriminant Analysis (LDA) classifying drugs as active or non-active against the different tested parasite species. The model correctly classifies 212 out of 244 (87.0%) cases in training series and 207 out of 243 compounds (85.4%) in external validation series. In order to illustrate the performance of the QSAR for the selection of active drugs we carried out an additional virtual screening of antiparasite compounds not used in training or predicting series; the model recognized 97 out of 114 (85.1%) of them. We also give the procedures to construct back-projection maps and to calculate sub-structures contribution to the biological activity. Finally, we used the outputs of the QSAR to construct, by the first time, a multi-species Complex Networks of antiparasite drugs. The network predicted has 380 nodes (compounds), 634 edges (pairs of compounds with similar activity). This network allows us to cluster different compounds and identify on average three known compounds similar to a new query compound according to their profile of biological activity. This is the first attempt to calculate probabilities of antiparasitic action of drugs against different parasites.

Analysis of Pathotypes of Colletotrichum lindemuthianum Found in the Central Region of Mexico and Resistance in Elite Germ Plasm of Phaseolus vulgaris.

The pathotypes of 17 isolates of Colletotrichum lindemuthianum from the central region of Mexico were characterized to determine the genetic relationship among isolates from this region and other regions of Mexico, and to evaluate the resistance present in the elite germ plasm collection of Phaseolus vulgaris at INIFAP. Eight pathotypes were identified, including pathotype 292, which is reported for the first time in Mexico. The lack of isolates infecting cultivar TU carrying the Co-5 resistance gene suggests that this cultivar is a useful source of resistance. Six pathotypes produced susceptible reactions on only differential cultivars of Middle American origin, one pathotype on a single cultivar of Andean origin, and one pathotype on cultivars of both Middle American and Andean origin. Comparison of amplified fragment length polymorphism (AFLP) genotypes of 21 isolates confirmed suggestions that populations of C. lindemuthianum are comprised of asexually reproducing clonal lineages. Analysis of five different pathotypes of C. lindemuthianum on 21 elite genotypes of P. vulgaris identified four genotypes from different races of P. vulgaris resistant to all five pathotypes. This information will allow breeders and farmers to select the resistant genotypes most suited to their needs.

Identification of Co-1 Anthracnose Resistance and Linked Molecular Markers in Common Bean Line A193.

Phaseolus vulgaris line A193 has been shown to be widely resistant to Colletotrichum lindemuthianum, including race 1472, one of the most virulent races of C. lindemuthianum characterized. Resistance to C. lindemuthianum race 1472 in P. vulgaris line A193 was investigated in segregating F2 and F2.3 populations from a cross between A193 and Flor de Mayo Bajio (a commercial cultivar highly susceptible to C. lindemuthianum). Resistance to 1472 in A193 was determined to be conditioned by a single dominant gene. Inoculation of crosses between A193 and cultivars Michigan Dark Red Kidney and Perry Marrow with race 1472 suggest that resistance in A193 is conditioned by the Co-1 gene. Inoculation of the cross A193 × Perry Marrow with C. lindemuthianum race 2, demonstrated that resistance to race 2 in Perry Marrow is also conditioned by a single dominant gene and is distinct to resistance in A193 or Michigan Dark Red Kidney. Three AFLP markers (ECAG/MACC-1, EACA/MAGA-2, EAGG/MAAC-8) linked in repulsion to the Co-1 locus were identified by screening the A193 × Flor de Mayo F2 population with 314 random amplified polymorphic DNA, amplified fragment length polymorphism, and restriction fragment length polymorphism markers. The two most closely linked markers should be useful in marker-assisted selection for Co-1.