Gaining insight into the pharmacology of ligand engagement with G-protein coupled receptors (GPCRs) under biologically relevant conditions is vital to both drug discovery and basic research. NanoLuc-based bioluminescence resonance energy transfer (Na...
Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes in molecular structure in response to the environmental condition, interactions with other proteins,...
Cilia are microtubule based cellular appendages that function as signaling centers for a diversity of signaling pathways in many mammalian cell types. Cilia length is highly conserved, tightly regulated, and varies between different cell types and ti...
DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track ...
Machine learning is one of the most potential ways to realize the function prediction of the incremental large-scale G-protein-coupled receptors (GPCR). Prior research reveals that the key to determining the overall classification accuracy of GPCR is...
Identification of drug-target interactions (DTIs) is vital for drug discovery. However, traditional biological approaches have some unavoidable shortcomings, such as being time consuming and expensive. Therefore, there is an urgent need to develop no...
Methods in molecular biology (Clifton, N.J.)
34731470
Drug-target residence time, the duration of binding at a given protein target, has been shown in some protein families to be more significant for conferring efficacy than binding affinity. To carry out efficient optimization of residence time in drug...
Journal of chemical information and modeling
35257580
Molecular dynamics (MD) simulations have made great contribution to revealing structural and functional mechanisms for many biomolecular systems. However, how to identify functional states and important residues from vast conformation space generated...
MOTIVATION: Drug discovery has witnessed intensive exploration of predictive modeling of drug-target physical interactions over two decades. However, a critical knowledge gap needs to be filled for correlating drug-target interactions with clinical o...
In this study we show that protein language models can encode structural and functional information of GPCR sequences that can be used to predict their signaling and functional repertoire. We used the ESM1b protein embeddings as features and the bind...