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Docking for Molecules That Bind in a Symmetric Stack with SymDOCK.
Smith, Matthew S; Knight, Ian S; Kormos, Rian C; Pepe, Joseph G; Kunach, Peter; Diamond, Marc I; Shahmoradian, Sarah H; Irwin, John J; DeGrado, William F; Shoichet, Brian K.
Afiliação
  • Smith MS; Department of Pharmaceutical Chemistry, University of California, UCSF Genentech Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States.
  • Knight IS; Program in Biophysics, University of California, UCSF Genentech Hall MC2240, 600 16th St Rm N474D,San Francisco, California 94143, United States.
  • Kormos RC; Department of Pharmaceutical Chemistry, University of California, UCSF Genentech Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States.
  • Pepe JG; Department of Pharmaceutical Chemistry, University of California, UCSF Genentech Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States.
  • Kunach P; Program in Biophysics, University of California, UCSF Genentech Hall MC2240, 600 16th St Rm N474D,San Francisco, California 94143, United States.
  • Diamond MI; Department of Pharmaceutical Chemistry, University of California, UCSF Genentech Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States.
  • Shahmoradian SH; Program in Biophysics, University of California, UCSF Genentech Hall MC2240, 600 16th St Rm N474D,San Francisco, California 94143, United States.
  • Irwin JJ; McGill Research Centre for Studies in Aging, McGill University, 6875 Boulevard LaSalle, Montreal, Quebec H4H 1R3, Canada.
  • DeGrado WF; Department of Neurology and Neurosurgery, McGill University, 1033 Pine Avenue West, Room 310, Montreal, Quebec H3A 1A1, Canada.
  • Shoichet BK; Center for Alzheimer's and Neurodegenerative Diseases, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, 6124 Harry Hines Blvd. Suite NS03.200, Dallas, Texas 75390, United States.
J Chem Inf Model ; 64(2): 425-434, 2024 01 22.
Article em En | MEDLINE | ID: mdl-38191997
ABSTRACT
Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of great current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures, the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein's symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligand's docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural-network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study, SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Chem Inf Model Assunto da revista: INFORMATICA MEDICA / QUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Chem Inf Model Assunto da revista: INFORMATICA MEDICA / QUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos