How to accurately estimate protein–ligand binding affinity remains a key challenge in
computer-aided drug design (CADD). In many cases, it has been shown that the binding …

Surflex-Dock employs an empirically derived scoring function to rank putative protein−
ligand interactions by flexible docking of small molecules to proteins of known structure. The …

Protein–ligand binding is essential to almost all life processes. The understanding of protein–
ligand interactions is fundamentally important to rational drug and protein design. Based on …

In this review article, we will explore the foundations of different classes of docking and
scoring functions, their possible limitations, and their suitable application domains. We also …

Accurate determination of protein–ligand binding affinity is a fundamental problem in
biochemistry useful for many applications including drug design and protein–ligand docking …

The rapid and accurate in silico prediction of protein-ligand binding free energies or binding
affinities has the potential to transform drug discovery. In recent years, there has been a …

In recent years, protein–ligand interaction scoring functions derived through machine-
learning are repeatedly reported to outperform conventional scoring functions. However …

Automated docking is one of the most important tools for structure‐based drug design that
allows prediction of ligand binding poses and also provides an estimate of how well small …

We introduce the new knowledge-based scoring function DSX that consists of distance-
dependent pair potentials, novel torsion angle potentials, and newly defined solvent …

Accurately predicting the binding affinities of large diverse sets of protein-ligand complexes
efficiently is a key challenge in computational biomolecular science, with applications in …