N ANOTECHNOLOGY has been revolutionized penetrating all sectors in our life through the nanoscien... more N ANOTECHNOLOGY has been revolutionized penetrating all sectors in our life through the nanoscience as an essential science for a wide range of technologies. Amazing achievements resulted from this nanotechnology including all agricultural fields such as plant nutrition and crop productivity, energy sector, food sector, and plant biotechnology. A conjugation between plant biotechnology and nanotechnology has been produced an important science called plant bio-nanotechnology. Several fields have been invaded through different nanobiotechnology applications in agriculture including (1) the nanotechnology of encapsulated agro-chemicals, (2) the monitoring of different environmental stresses and crop conditions using nanobiosensors, (3) the improvement of crop production and ameliorating plants against diseases and (4) solution several environmental problems. The crop productivity also could be improved using some new agro-chemicals (e.g., nanofertilizers and nanopesticides). These agro-chemicals are very effective in delivering encapsulating nanomaterials and then enhancement the productivity of crops as well as the suppress plant pests and diseases and protecting the environment from pollution. On the other hand, nanoparticles could enter the food chain via different nano-agrochemicals or nano-processed foods. Therefore, many approaches including uptake of nanoparticles by plants, entry and bio-distribution of nanoparticles into the food chain are needed before using of different bionanotechnological tools in agro-production sector. Further new regulations should be created or rebuilt for new approaches in plant bionanotechnology. Therefore, this review will focus on our needs and risks in the plant nanobiotechnology.
New antibiotics are needed to battle growing antibiotic resistance, but the development process f... more New antibiotics are needed to battle growing antibiotic resistance, but the development process from hit, to lead, and ultimately to a useful drug, takes decades. Although progress in molecular property prediction using machine-learning methods has opened up new pathways for aiding the antibiotics development process, many existing solutions rely on large datasets and finding structural similarities to existing antibiotics. Challenges remain in modelling of unconventional antibiotics classes that are drawing increasing research attention. In response, we developed an antimicrobial activity prediction model for conjugated oligoelectrolyte molecules, a new class of antibiotics that lacks extensive prior structure-activity relationship studies. Our approach enables us to predict minimum inhibitory concentration for E. coli K12, with 21 molecular descriptors selected by recursive elimination from a set of 5,305 descriptors. This predictive model achieves an R 2 of 0.65 with no prior knowledge of the underlying mechanism. We find the molecular representation optimum for the domain is the key to good predictions of antimicrobial activity. In the case of conjugated oligoelectrolytes, a representation reflecting the 3-dimensional shape of the molecules is most critical. Although it is demonstrated with a specific example of conjugated oligoelectrolytes, our proposed approach for creating the predictive model can be readily adapted to other novel antibiotic candidate domains.
N ANOTECHNOLOGY has been revolutionized penetrating all sectors in our life through the nanoscien... more N ANOTECHNOLOGY has been revolutionized penetrating all sectors in our life through the nanoscience as an essential science for a wide range of technologies. Amazing achievements resulted from this nanotechnology including all agricultural fields such as plant nutrition and crop productivity, energy sector, food sector, and plant biotechnology. A conjugation between plant biotechnology and nanotechnology has been produced an important science called plant bio-nanotechnology. Several fields have been invaded through different nanobiotechnology applications in agriculture including (1) the nanotechnology of encapsulated agro-chemicals, (2) the monitoring of different environmental stresses and crop conditions using nanobiosensors, (3) the improvement of crop production and ameliorating plants against diseases and (4) solution several environmental problems. The crop productivity also could be improved using some new agro-chemicals (e.g., nanofertilizers and nanopesticides). These agro-chemicals are very effective in delivering encapsulating nanomaterials and then enhancement the productivity of crops as well as the suppress plant pests and diseases and protecting the environment from pollution. On the other hand, nanoparticles could enter the food chain via different nano-agrochemicals or nano-processed foods. Therefore, many approaches including uptake of nanoparticles by plants, entry and bio-distribution of nanoparticles into the food chain are needed before using of different bionanotechnological tools in agro-production sector. Further new regulations should be created or rebuilt for new approaches in plant bionanotechnology. Therefore, this review will focus on our needs and risks in the plant nanobiotechnology.
New antibiotics are needed to battle growing antibiotic resistance, but the development process f... more New antibiotics are needed to battle growing antibiotic resistance, but the development process from hit, to lead, and ultimately to a useful drug, takes decades. Although progress in molecular property prediction using machine-learning methods has opened up new pathways for aiding the antibiotics development process, many existing solutions rely on large datasets and finding structural similarities to existing antibiotics. Challenges remain in modelling of unconventional antibiotics classes that are drawing increasing research attention. In response, we developed an antimicrobial activity prediction model for conjugated oligoelectrolyte molecules, a new class of antibiotics that lacks extensive prior structure-activity relationship studies. Our approach enables us to predict minimum inhibitory concentration for E. coli K12, with 21 molecular descriptors selected by recursive elimination from a set of 5,305 descriptors. This predictive model achieves an R 2 of 0.65 with no prior knowledge of the underlying mechanism. We find the molecular representation optimum for the domain is the key to good predictions of antimicrobial activity. In the case of conjugated oligoelectrolytes, a representation reflecting the 3-dimensional shape of the molecules is most critical. Although it is demonstrated with a specific example of conjugated oligoelectrolytes, our proposed approach for creating the predictive model can be readily adapted to other novel antibiotic candidate domains.
Uploads
Papers by Mohamed Ragab