This application discloses a method and apparatus for detecting a molecule binding site, an electronic device, and a storage medium, relating to the field of computer technologies. According to one embodiment, the method includes: obtaining 3D coordinates of at least one site in a target molecule; for each site, obtaining a prediction probability indicating a possibility of the each site being a binding site via a site detection model; and determining a binding site from the at least one site in the target molecule based on the prediction probability of the each of the at least one site.

This application discloses a method and apparatus for detecting a molecule binding site, an electronic device, and a storage medium, relating to the field of computer technologies. According to one embodiment, the method includes: obtaining 3D coordinates of at least one site in a target molecule; for each site, obtaining a prediction probability indicating a possibility of the each site being a binding site via a site detection model; and determining a binding site from the at least one site in the target molecule based on the prediction probability of the each of the at least one site.

Methods of identifying RNA-protein interaction sites are provided. Systems for identifying RNA-protein interaction sites are provided. Systems for identifying secondary structures are provided. Methods of identifying secondary structures are provided. Methods of identifying RNA-binding proteins are provided.

Method, device and medium are directed to providing a method for generating three-dimension molecules. The method comprises obtaining a molecular shape of a three-dimension molecule for a drug, wherein the molecular shape is represented by a three-dimension image and generating a plurality of fragments of the three-dimension molecule based on the molecular shape. The method further comprises generating the three-dimension molecule by connecting the plurality of fragments. The method may be used to design high quality drugs for specific protein pockets efficiently and speed up the process of drug development and reduce the cycle of drug development. Furthermore, since the method utilizes large-scale non-experimental data, the method may not rely on expensive experimental data and docking simulation which is time consuming. Additionally, the method utilizes the three-dimension interaction information between molecules and pockets to generate drug molecules, and thus the quality of generated drug molecules can be improved.

The operation efficiency and accuracy of the simultaneous analysis of phospholipids, including fatty acid compositions are increased. After a first-time LC/MS/MS analysis for determining the phospholipid classes of the phospholipid contained in a sample is performed (S2-S3), a second-time LC/MS/MS analysis for determining fatty acid compositions is performed only for the detected phospholipids (S4-S8). By associating a method list in which an MRM transition for phospholipid class determination is recorded for each compound of phospholipid classes with a method list in which an MRM transition for fatty acid composition determination is recorded for each phospholipid compound, it is possible to promptly select MRM transitions for fatty acid composition determination that correspond to compounds of the detected phospholipid classes, and to easily create an analysis method for the second-time analysis.

The present disclosure provides a protein complex, including a three-dimensional structure of the protein complex, that plays a role in regulation of body weight. In addition, the protein complex and components thereof, including three-dimensional structures thereof, find use in identifying agents that can be used to control body weight.

A method for making a modified release composition, comprising: selecting a desired active agent and polymer matrix for formulating into a modified release composition; assessing degradation effect on release of the active agent from the composition including plotting polymer molecular weight (M.sub.wr) at onset of active agent release vs. active agent molecular weight (M.sub.wA); predicting performance of multiple potential formulations for the composition based on the degradation assessment and average polymer matrix initial molecular weight (M.sub.wo) to define a library of building blocks; determining the optimal ratio of the building blocks to satisfy a specified release profile; and making a modified release composition based on the optimal ratio determination.

The present invention relates to polypeptide fragments comprising an amino-terminal fragment of the PA subunit of a viral RNA-dependent RNA polymerase possessing endonuclease activity, wherein the PA subunit is from Influenza A 2009 pandemic H1N1 virus or is a variant thereof. This invention also relates to (i) crystals of the polypeptide fragments which are suitable for structure determination of the polypeptide fragments using X-ray crystallography and (ii) computational methods using the structural coordinates of the polypeptide to screen for and design compounds that modulate, preferably inhibit the endonucleolytically active site within the polypeptide fragment. In addition, this invention relates to methods of identifying compounds that bind to the PA polypeptide fragments possessing endonuclease activity and preferably inhibit the endonucleolytic activity, as well as the compounds themselves. Preferably, the compounds are identifiable by the methods disclosed herein or the pharmaceutical compositions are producible by the methods disclosed herein.

A system and method that predicts whether a given protein-ligand pair is active or inactive and outputs a pose score classifying the propriety of the pose. A 3D bioactivity platform comprising a 3D bioactivity module and data platform scrapes empirical lab-based data that a docking simulator uses to generate a dataset from which a 3D-CNN model is trained. The model then may receive new protein-ligand pairs and determine a classification for the bioactivity and pose propriety of that protein-ligand pair. Furthermore, gradients relating to the binding affinity in the 3D model of the molecule may be used to generate profiles from which new protein targets may be determined.

A system and method that predicts whether a given protein-ligand pair is active or inactive and outputs a pose score classifying the propriety of the pose. A 3D bioactivity platform comprising a 3D bioactivity module and data platform scrapes empirical lab-based data that a docking simulator uses to generate a dataset from which a 3D-CNN model is trained. The model then may receive new protein-ligand pairs and determine a classification for the bioactivity and pose propriety of that protein-ligand pair. Furthermore, gradients relating to the binding affinity in the 3D model of the molecule may be used to generate profiles from which new protein targets may be determined.