Molecular property prediction, crucial for early drug candidate screening and optimization,
has seen advancements with deep learning-based methods. While deep learning-based …

Machine-learning-based scoring functions (MLSFs) have gained attention for their potential
to improve accuracy in binding affinity prediction and structure-based virtual screening …

Lead optimization is one of the crucial steps in the drug discovery pipeline. After identifying
the lead molecule and obtaining its 2D geometry, understanding the best conformation it …

Fast and accurate assessment of small-molecule dihedral energetics is crucial for molecular
design and optimization in medicinal chemistry. Yet, accurate prediction of torsion energy …

Background The performance of 3D-based virtual screening similarity functions is affected
by the applied conformations of compounds. Therefore, the results of 3D approaches are …

Ligand-based virtual screening (LBVS) is a promising approach for rapid and low-cost
screening of potentially bioactive molecules in the early stage of drug discovery. Compared …

A pervasive challenge in drug design is determining how to expand a ligand─ a small
molecule that binds to a target biomolecule─ in order to improve various properties of the …

Ensemble docking can be a successful virtual screening technique that addresses the
innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method …

The goal of structure-based drug discovery is to find small molecules that bind to a given
target protein. Deep learning has been used to generate drug-like molecules with certain …

The worldwide increase and proliferation of drug resistant microbes, coupled with the lag in
new drug development, represents a major threat to human health. In order to reduce the …