GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach.

Protein-peptide interactions (PPepIs) are vital to understanding cellular functions, which can facilitate the design of novel drugs. As an essential component in forming a PPepI, protein-peptide binding sites are the basis for understanding the mechanisms involved in PPepIs. Therefore, accurately identifying protein-peptide binding sites becomes a critical task.

APEX-pHLA: A novel method for accurate prediction of the binding between exogenous short peptides and HLA class I molecules.

Human leukocyte antigen (HLA) molecules play critically significant role within the realm of immunotherapy due to their capacities to recognize and bind exogenous antigens such as peptides, subsequently delivering them to immune cells. Predicting the binding between peptides and HLA molecules (pHLA) can expedite the screening of immunogenic peptides and facilitate vaccine design. However, traditional experimental methods are time-consuming and inefficient.

Multi_CycGT: A Deep Learning-Based Multimodal Model for Predicting the Membrane Permeability of Cyclic Peptides.

Cyclic peptides are gaining attention for their strong binding affinity, low toxicity, and ability to target "undruggable" proteins; however, their therapeutic potential against intracellular targets is constrained by their limited membrane permeability, and researchers need much time and money to test this property in the laboratory. Herein, we propose an innovative multimodal model called Multi_CycGT, which combines a graph convolutional network (GCN) and a transformer to extract one- and two-dimensional features for predicting cyclic peptide permeability. The extensive benchmarking experiments show that our Multi_CycGT model can attain state-of-the-art performance, with an average accuracy of 0.

[Research advance in multi-component pharmacokinetics of Chinese herbal extracts in recent five years].

The multi-component pharmacokinetic study of Chinese herbal extracts elaborates the in vivo processes,including absorption,distribution,metabolism,and excretion,of multiple bioactive components,which is of significance in revealing pharmacodynamic material basis of Chinese herbal medicine. In recent years,with the innovation in ideas,and development of techniques and methods on traditional Chinese medicine( TCM) research,the pharmacokinetic studies of Chinese herbal extracts were extensively performed,and notable progress has been made. This paper reviewed the advancement of multi-component pharmacokinetics of Chinese herbal extracts in recent five years from analysis technology of biological sample,the pharmacokinetic characteristics of Chinese herbal medicine with complex system,and the impacts of processing and pathological state on pharmacokinetics of Chinese herbal extracts,aiming to provide a reference for quality control,product development and rational medication of Chinese herbal extracts.

A pharmacokinetics-pharmacodynamics study of single-dose total glucosides of paeony capsule on reducing serum total bile acid in hepatic injury rats.

Context: Total Glucosides of Paeony (TGP) capsule possesses various hepatoprotective activities. No study is available concerning TGP's concentration-effect relationship on hepatoprotection.

Objective: To establish a pharmacokinetics-pharmacodynamics (PK-PD) modelling on TGP capsule's hepatoprotection after a single oral administration in hepatic injury rats.

[Quantitative determination and optimun extraction technique of nine compounds of ].

Objective: To establish the optimum extraction technique and high performance liquid chromatographic (HPLC) method to simultaneously quantify nine compounds of gallic acid, hydroxy-paeoniflorin, catechin, albiflorin, paeoniflorin, pentagalloylglucose, benzoic acid, benzoylpaeoniflorin and paeonol in .

Methods: Linear gradient elution was applied using water containing 0.1%phosphoric acid and acetonitrile as the mobile phase with a flow rate of 0.