Improved protein–ligand docking using GOLD

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Molecular Docking and Structure-Based Drug Design Strategies (2015, background): “Gold, for instance, attempts to mimic the covalent bond formation by defining an atom in both the ligand and the receptor to play the role of “link atoms” [94].”
Structure-Based Virtual Screening: From Classical to Artificial Intelligence (2020, methodology): “Some published force-ﬁeld scoring functions include the ones described in Li et al. (2015), Goldscore (Verdonk et al., 2003), and Sybyl/D-Score (Ash et al., 1997).”
The VSGB 2.0 model: A next generation energy model for high resolution protein structure modeling (2011, background): “50 The hydrophobic term rewards contacts between nonpolar heavy atoms and stabilizes hydrophobic contacts.”
Leveraging molecular structure and bioactivity with chemical language models for de novo drug design (2023, methodology): “Aiming to rationalize the difference in activity between compound 1 and the 4-amino-pyrazolopyrimidine derivatives 17 – 22 , automated ligand docking was performed using GOLD software 60 .”
Protein-ligand docking in the new millennium--a retrospective of 10 years in the field. (2013, methodology): “They found that GOLD's ChemPLP was the most effective scoring function for pose prediction in cognate protein–ligand complexes among those available in GOLD, achieving a success rate of 87% over the ASTEX 85 sites below a 2.0 Å RMSD and 68 % below 1.0 Å RMSD. ChemScore, ASP and GoldScore gave sucess”