Background We previously reported that the tomato glycoalkaloid tomatine inhibited the growth of Trichomonas vaginalis strain G3, Tritrichomonas foetus strain D1, and Tritrichomonas foetus-like strain C1 that cause disease in humans and farm and domesticated animals. The increasing prevalence of antibiotic resistance requires development of new tools to enhance or replace medicinal antibiotics. Methods Wild tomato plants were harvested and divided into leaves, stems, and fruit of different colors: green, yellow, and red. Samples were freeze dried and ground with a handheld mill. The resulting powders were evaluated for their potential anti-microbial effects on protozoan parasites, bacteria, and fungi. A concentration of 0.02% (w/v) was used for the inhibition of protozoan parasites. A high concentration of 10% (w/v) solution was tested for bacteria and fungi as an initial screen to evaluate potential anti-microbial activity and results using this high concentration limits its clinical relevance. Results Natural powders derived from various parts of tomato plants were all effective in inhibiting the growth of the three trichomonads to varying degrees. Test samples from leaves, stems, and immature ‘green’ tomato peels and fruit, all containing tomatine, were more effective as an inhibitor of the D1 strain than those prepared from yellow and red tomato peels which lack tomatine. Chlorogenic acid and quercetin glycosides were present in all parts of the plant and fruit, while caffeic acid was only found in the fruit peels. Any correlation between plant components and inhibition of the G3 and C1 strains was not apparent, although all the powders were variably effective. Tomato leaf was the most effective powder in all strains, and was also the highest in tomatine. S. enterica showed a minor susceptibility while B. cereus and C. albicans fungi both showed a significant growth inhibition with some of the test powders. The powders inhibited growth of the pathogens without affecting beneficial lactobacilli found in the normal flora of the vagina. Conclusions The results suggest that powders prepared from tomato leaves, stems, and green tomato peels and to a lesser extent from peels from yellow and red tomatoes offer potential multiple health benefits against infections caused by pathogenic protozoa, bacteria, and fungi, without affecting beneficial lactobacilli that also reside in the normal flora of the vagina.

Protein-protein interactions often involve a complex system of intermolecular interactions between residues and atoms at the binding site. A comprehensive exploration of these interactions can help reveal key residues involved in protein-protein recognition that are not obvious using other protein analysis techniques. This paper presents and extends DiffBond, a novel method for identifying and classifying intermolecular bonds while applying standard definitions of bonds in chemical literature to explain protein interactions. DiffBond predicted intermolecular bonds from four protein complexes: Barnase-Barstar, Rap1a-raf, SMAD2-SMAD4, and a subset of complexes formed from three-finger toxins and nAChRs. Based on validation through manual literature search and through comparison of two protein complexes from the SKEMPI dataset, DiffBond was able to identify intermolecular ionic bonds and hydrogen bonds with high precision and recall, and identify salt bridges with high precision. DiffBond predictions on bond existence were also strongly correlated with observations of Gibbs free energy change and electrostatic complementarity in mutational experiments. DiffBond can be a powerful tool for predicting and characterizing influential residues in protein-protein interactions, and its predictions can support research in mutational experiments and drug design.

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This paper presents HBcompare, a method that classifies protein structures according to ligand binding preference categories by analyzing hydrogen bond topology. HBcompare excludes other characteristics of protein structure so that, in the event of accurate classification, it can implicate the involvement of hydrogen bonds in selective binding. This approach contrasts from methods that represent many aspects of protein structure because holistic representations cannot associate classification with just one characteristic. To our knowledge, HBcompare is the first technique with this capability. On five datasets of proteins that catalyze similar reactions with different preferred ligands, HBcompare correctly categorized proteins with similar ligand binding preferences 89.5% of the time. Using only hydrogen bond topology, classification accuracy with HBcompare surpassed standard structure-based comparison algorithms that use atomic coordinates. As a tool for implicating the role of hydrogen bonds in protein function categories, HBcompare represents a first step towards the automatic explanation of biochemical mechanisms.