Understanding the interactions between a ligand and its molecular target is crucial in guiding the optimization of molecules for any drug design workflow. Multiple experimental and computational methods have been developed to better understand these...
Accurately predicting protein-ligand interactions is crucial for understanding cellular processes. We introduce SurfDock, a deep-learning method that addresses this challenge by integrating protein sequence, three-dimensional structural graphs and su...
BACKGROUND: Molecular interactions between proteins and their ligands are important for drug design. A pharmacophore consists of favorable molecular interactions in a protein binding site and can be utilized for virtual screening. Pharmacophores are ...
Journal of chemical information and modeling
39724561
In recent years, the deep learning (DL) technique has rapidly developed and shown great success in scoring the protein-ligand binding affinities. The protein-ligand conformation optimization based on DL-derived scoring functions holds broad applicati...
Traditional testing methods in pharmaceutical development can be time-consuming and costly, but in silico evaluation tools can offer a solution. Our in-house Active-IT system, a Ligand-Based Virtual Screening (LBVS) tool, was developed to predict the...
Journal of chemical theory and computation
39705058
Enzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities...
MOTIVATION: Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule li...
Journal of chemical information and modeling
39690486
Accurate identification of adenosine triphosphate (ATP) binding sites is crucial for understanding cellular functions and advancing drug discovery, particularly in targeting kinases for cancer treatment. Existing methods face significant challenges d...
Drug design has always been pursuing techniques with time- and cost-benefits. Virtual screening, generally classified as ligand-based (LBVS) and structure-based (SBVS) approaches, could identify active compounds in the large chemical library to reduc...
Protein science : a publication of the Protein Society
39660955
Computational methods to predict binding affinity of protein-ligand complex have been used extensively to design inhibitors for proteins selected as drug targets. In recent years machine learning (ML) is being increasingly used for design of drugs/in...