Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.
Superresolution imaging of solids is essential to explore local symmetry breaking and derived material properties. Electron ptychography is one of the most promising schemes to realize superresolution imaging beyond aberration correction. However, to reach both deep sub-angstrom resolution imaging and accurate measurement of atomic structures, it is still required for the electron beam to be nearly parallel to the zone axis of crystals. Here, we report an efficient and robust method to correct the specimen misorientation in electron ptychography, giving deep sub-angstrom resolution for specimens with large misorientations. The method largely reduces the experimental difficulties of electron ptychography and paves the way for widespread applications of ptychographic deep sub-angstrom resolution imaging.
Sub-angstrom resolution imaging of porous materials like zeolites is important to reveal their structure-property relationships involved in ion exchange, molecule adsorption and separation, and catalysis. Using multislice electron ptychography, we successfully measured the atomic structure of zeolite at sub-angstrom lateral resolution for 100-nanometer-thick samples. Both lateral and depth deformations of the straight channels are mapped, showing the three-dimensional structural inhomogeneity and flexibility. Since most zeolites in industrial applications are usually tens to hundreds of nanometers thick, the sub-angstrom resolution imaging and accurate measurements of depth-dependent local structures with electron ptychography at low-dose condition will find wide applications in porous materials close to their industrially relevant conditions.
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