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XGen: Real-Space Fitting of Complex Ligand Conformational Ensembles to X-ray Electron Density Maps.
Jain, Ajay N; Cleves, Ann E; Brueckner, Alexander C; Lesburg, Charles A; Deng, Qiaolin; Sherer, Edward C; Reibarkh, Mikhail Y.
Affiliation
  • Jain AN; Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94143 United States.
  • Cleves AE; BioPharmics LLC, Santa Rosa, California 95404 United States.
  • Brueckner AC; Merck and Co., Inc., Kenilworth, New Jersey 07033 United States.
  • Lesburg CA; Merck and Co., Inc., Kenilworth, New Jersey 07033 United States.
  • Deng Q; Merck and Co., Inc., Kenilworth, New Jersey 07033 United States.
  • Sherer EC; Merck and Co., Inc., Kenilworth, New Jersey 07033 United States.
  • Reibarkh MY; Merck and Co., Inc., Kenilworth, New Jersey 07033 United States.
J Med Chem ; 63(18): 10509-10528, 2020 09 24.
Article in En | MEDLINE | ID: mdl-32877178
ABSTRACT
We report a new method for X-ray density ligand fitting and refinement that is suitable for a wide variety of small-molecule ligands, including macrocycles. The approach (called "xGen") augments a force field energy calculation with an electron density fitting restraint that yields an energy reward during the restrained conformational search. The resulting conformer pools balance goodness-of-fit with ligand strain. Real-space refinement from pre-existing ligand coordinates of 150 macrocycles resulted in occupancy-weighted conformational ensembles that exhibited low strain energy. The xGen ensembles improved upon electron density fit compared with the PDB reference coordinates without making use of atom-specific B-factors. Similarly, on nonmacrocycles, de novo fitting produced occupancy-weighted ensembles of many conformers that were generally better-quality density fits than the deposited primary/alternate conformational pairs. The results suggest ubiquitous low-energy ligand conformational ensembles in X-ray diffraction data and provide an alternative to using B-factors as model parameters.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Peptides, Cyclic Type of study: Prognostic_studies Language: En Journal: J Med Chem Journal subject: QUIMICA Year: 2020 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Peptides, Cyclic Type of study: Prognostic_studies Language: En Journal: J Med Chem Journal subject: QUIMICA Year: 2020 Document type: Article