On the Frustration to Predict Binding Affinities from Protein-Ligand Structures with Deep Neural Networks.
Accurate prediction of binding affinities from protein-ligand atomic coordinates remains a major challenge in early stages of drug discovery.
Accurate prediction of binding affinities from protein-ligand atomic coordinates remains a major challenge in early stages of drug discovery.
Carbohydrate-protein interactions are key for cell-cell and host-pathogen recognition and thus, emerged as viable therapeutic targets.
Screening of fragment libraries is a valuable approach to the drug discovery process.
Inhibiting receptor tyrosine kinases is commonly achieved by two main strategies targeting either the intracellular kinase domain by low molecular weight compounds or the …
SUMMARY: The 3D structure of transmembrane helices plays a key role in the function of membrane proteins.
Pseudomonas aeruginosa is an opportunistic ESKAPE pathogen that produces two lectins, LecA and LecB, as part of its large arsenal of virulence factors.
Rationalizing the identification of hidden similarities across the repertoire of druggable protein cavities remains a major hurdle to a true proteome-wide structure-based …
The chemokine receptor CCR5 is a key player in HIV-1 infection.
Hundreds of fast scoring functions have been developed over the last 20 years to predict binding free energies from three-dimensional structures of protein-ligand complexes.
Because of the antimicrobial resistance crisis, lectins are considered novel drug targets.