title: Dihedral Angle-Based Sampling of Natural Product Polyketide Conformations: Application to Permeability Prediction.
abstract: Macrocycles pose challenges for computer-aided drug design due to their conformational complexity. One fundamental challenge is identifying all low-energy conformations of the macrocyclic ring, which is important for modeling target binding, passive membrane permeation, and other conformation-dependent properties. Macrocyclic polyketides are medically and biologically important natural products characterized by structural and functional diversity. Advances in synthetic biology and semisynthetic methods may enable creation of an even more diverse set of non-natural product polyketides for drug discovery and other applications. However, the conformational sampling of these flexible compounds remains demanding. We developed and optimized a dihedral angle-based macrocycle conformational sampling method for macrocycles of arbitrary structure, and here we apply it to diverse polyketide natural products. First, we evaluated its performance using a data set of 37 polyketides with available crystal structures, with 9-22 rotatable bonds in the macrocyclic ring. Our optimized protocol was able to reproduce the crystal structure of polyketides' aglycone backbone within 0.50 Å RMSD for 31 out of 37 polyketides. Consistent with prior structural studies, our analysis suggests that polyketides tend to have multiple distinct low-energy structures, including the bioactive (target-bound) conformation as well as others of unknown significance. For this reason, we also introduce a strategy to improve both efficiency and accuracy of the conformational search by utilizing torsional restraints derived from NMR vicinal proton couplings to restrict the conformational search. Finally, as a first application of the method, we made blinded predictions of the passive membrane permeability of a diverse set of polyketides, based on their predicted structures in low- and high-dielectric media.
authors.affiliation: Department of Pharmaceutical Chemistry, University of California , San Francisco, California 94158, United States.
authors.forename: Qin
authors.initials: Q
authors.lastname: Wang
authors.affiliation: Neuroscience and Pain Medicinal Chemistry, Pfizer Worldwide Research and Development , Cambridge, Massachusetts 02139, United States.
authors.forename: Simone
authors.initials: S
authors.lastname: Sciabola
authors.affiliation: Neuroscience and Pain Medicinal Chemistry, Pfizer Worldwide Research and Development , Cambridge, Massachusetts 02139, United States.
authors.forename: Gabriela
authors.initials: G
authors.lastname: Barreiro
authors.affiliation: Neuroscience and Pain Medicinal Chemistry, Pfizer Worldwide Research and Development , Cambridge, Massachusetts 02139, United States.
authors.forename: Xinjun
authors.initials: X
authors.lastname: Hou
authors.forename: Guoyun
authors.initials: G
authors.lastname: Bai
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Shapiro
authors.forename: Frank
authors.initials: F
authors.lastname: Koehn
authors.affiliation: Neuroscience and Pain Medicinal Chemistry, Pfizer Worldwide Research and Development , Cambridge, Massachusetts 02139, United States.
authors.forename: Anabella
authors.initials: A
authors.lastname: Villalobos
authors.affiliation: Department of Pharmaceutical Chemistry, University of California , San Francisco, California 94158, United States.
authors.forename: Matthew P
authors.initials: MP
authors.lastname: Jacobson
mesh_terms: D001688:Biological Products / Q000737:chemistry* / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D008958:Models, Molecular; D008968:Molecular Conformation; D010539:Permeability; D061065:Polyketides / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D001688:Biological Products; D061065:Polyketides