Publications by authors named "A Cleves"
Structure-based pose prediction: Non-cognate docking extended to macrocyclic ligands.
J Comput Aided Mol Des
October 2024
Article Synopsis
- Cross-docking involves predicting how new small-molecule ligands will bind to a protein when these ligands are different from the known binding partners, which is a more complex task than re-docking the original ligands.
- The updated PINC benchmark uses temporal segregation to evaluate cross-docking accuracy, including predictions for 846 future ligands across ten protein targets and an extension for 128 macrocyclic ligands based on data from previously known non-macrocyclic ligands.
- Overall, using methods like Surflex-Dock and ForceGen, the study achieved impressive success rates, with 68% accuracy for the best poses and 92% for any correct poses, outperforming alternative methods like AutoDock Vina and
Objectives: Research indicates that people with lower socioeconomic status (SES) receive inferior healthcare and experience poorer health outcomes compared with those with higher SES, in part due to health professional (HP) bias. We conducted a scoping review of the impact of HP bias about SES on clinical decision-making and its effect on the care of adults with lower SES.
Design: JBI scoping review methods were used to perform a systematic comprehensive search for literature.
Article Synopsis
- * It employs the QuanSA 3D-QSAR method, which utilizes an active learning strategy to select compounds based on their predicted activity and similarity to effective neighboring molecules.
- * Through iterative model refinement, the research successfully identifies key compounds, enhances predictive accuracy, and shows that even minimal data can help generate synthetic candidates.
Systematic optimization of large macrocyclic peptide ligands is a serious challenge. Here, we describe an approach for lead-optimization using the PD-1/PD-L1 system as a retrospective example of moving from initial lead compound to clinical candidate. We show how conformational restraints can be derived by exploiting NMR data to identify low-energy solution ensembles of a lead compound.
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