Effect of Different Calcium Levels on Growth,Yield and Fruit Quality of Tomatoes in Substrate Culture

Tomato seedlings were grown in substrate culture with pots. The formulation of Holland Greenhouse Horticulture Research Institute was used(as CK) and the effects of different Ca concentrations(LCa, CK and HCa)on growth, yield, and fruit quality(protein, Vitamin C, nitrates, organic acid and soluble sugar) of tomato were studied keeping concentrations of other nutrients unchanged in the nutrient solution. The results showed that parameters related to the growth of tomato(plant height and Stem diameter), changes of tomato yield per plant and quality of tomato fruits were the highest when the plants were grown at 20% Ca treatments. In the second study, increased EC concentrations of nutrient solution resulted in stronger plants with improved yields and quality. Four different concentration gradients of nutrient solution treatment were designed based on the results of the first research stage(EC=1.5, 2.5, 3.5, 4.5 m S/cm, respectively). The single tomato plant had the highest production which is 2 268.994 g/plant, when the nutrient solution strength was at EC=1.5 m S cm, whereas they have the best fruit quality when the solution strength at EC 4.5 m S/cm. This suggests the need for wide popularization of the nutrient solution formula in large areas to improve the tomato production.

Artificial intelligence and big data facilitated targeted drug discovery

Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data.The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer.DrugBank is a database including detailed information of approved,investigational and withdrawn drugs,as well as other nutraceutical and metabolite structures.PubChem is a chemical compound database including all commercially available compounds as well as other synthesisable compounds.Protein Data Bank is a crystal structure database including X-ray,cryo-EM and nuclear magnetic resonance protein three-dimensional structures as well as their ligands.On the other hand,artificial intelligence(AI)is playing an important role in the drug discovery progress.The integration of such big data and AI is making a great difference in the discovery of novel targeted drug.In this review,we focus on the currently available advanced methods for the discovery of highly effective lead compounds with great absorption,distribution,metabolism,excretion and toxicity properties.

Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets

The discovery of targeted drugs heavily relies on three-dimensional(3D)structures of target proteins.When the 3D structure of a protein target is unknown,it is very difficult to design its corresponding targeted drugs.Although the 3D structures of some proteins(the so-called undruggable targets)are known,their targeted drugs are still absent.As increasing crystal/cryogenicelectron microscopy structures are deposited in Protein Data Bank,it is much more possible to discover the targeted drugs.Moreover,it is also highly probable to turn previous undruggable targets into druggable ones when we identify their hidden allosteric sites.In this review,we focus on the currently available advanced methods for the discovery of novel compounds targeting proteins without 3D structure and how to turn undruggable targets into druggable ones.