1
|
Carlsson J, Luttens A. Structure-based virtual screening of vast chemical space as a starting point for drug discovery. Curr Opin Struct Biol 2024; 87:102829. [PMID: 38848655 DOI: 10.1016/j.sbi.2024.102829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/16/2024] [Accepted: 04/21/2024] [Indexed: 06/09/2024]
Abstract
Structure-based virtual screening aims to find molecules forming favorable interactions with a biological macromolecule using computational models of complexes. The recent surge of commercially available chemical space provides the opportunity to search for ligands of therapeutic targets among billions of compounds. This review offers a compact overview of structure-based virtual screens of vast chemical spaces, highlighting successful applications in early drug discovery for therapeutically important targets such as G protein-coupled receptors and viral enzymes. Emphasis is placed on strategies to explore ultra-large chemical libraries and synergies with emerging machine learning techniques. The current opportunities and future challenges of virtual screening are discussed, indicating that this approach will play an important role in the next-generation drug discovery pipeline.
Collapse
Affiliation(s)
- Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, BMC, Box 596, SE-751 24 Uppsala, Sweden.
| | - Andreas Luttens
- Institute for Medical Engineering & Science and Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| |
Collapse
|
2
|
Lyu J, Kapolka N, Gumpper R, Alon A, Wang L, Jain MK, Barros-Álvarez X, Sakamoto K, Kim Y, DiBerto J, Kim K, Glenn IS, Tummino TA, Huang S, Irwin JJ, Tarkhanova OO, Moroz Y, Skiniotis G, Kruse AC, Shoichet BK, Roth BL. AlphaFold2 structures guide prospective ligand discovery. Science 2024; 384:eadn6354. [PMID: 38753765 PMCID: PMC11253030 DOI: 10.1126/science.adn6354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 04/24/2024] [Indexed: 05/18/2024]
Abstract
AlphaFold2 (AF2) models have had wide impact but mixed success in retrospective ligand recognition. We prospectively docked large libraries against unrefined AF2 models of the σ2 and serotonin 2A (5-HT2A) receptors, testing hundreds of new molecules and comparing results with those obtained from docking against the experimental structures. Hit rates were high and similar for the experimental and AF2 structures, as were affinities. Success in docking against the AF2 models was achieved despite differences between orthosteric residue conformations in the AF2 models and the experimental structures. Determination of the cryo-electron microscopy structure for one of the more potent 5-HT2A ligands from the AF2 docking revealed residue accommodations that resembled the AF2 prediction. AF2 models may sample conformations that differ from experimental structures but remain low energy and relevant for ligand discovery, extending the domain of structure-based drug design.
Collapse
Affiliation(s)
- Jiankun Lyu
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
- The Evnin Family Laboratory of Computational Molecular Discovery, The Rockefeller University, New York, NY 10065, USA
| | - Nicholas Kapolka
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
| | - Ryan Gumpper
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
| | - Assaf Alon
- Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Liang Wang
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94035, USA
| | - Manish K. Jain
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
| | - Ximena Barros-Álvarez
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94035, USA
| | - Kensuke Sakamoto
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
- National Institute of Mental Health Psychoactive Drug Screening Program (NIMH PDSP), School of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
| | - Yoojoong Kim
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
| | - Jeffrey DiBerto
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
| | - Kuglae Kim
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
| | - Isabella S. Glenn
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Tia A. Tummino
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Sijie Huang
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - John J. Irwin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | | | - Yurii Moroz
- Chemspace LLC, Kyiv 02094, Ukraine
- Taras Shevchenko National University of Kyiv, Kyiv 01601, Ukraine
- Enamine Ltd., Kyiv 02094, Ukraine
| | - Georgios Skiniotis
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94035, USA
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Andrew C. Kruse
- Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Brian K. Shoichet
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94158, USA
| | - Bryan L. Roth
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
- National Institute of Mental Health Psychoactive Drug Screening Program (NIMH PDSP), School of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599, USA
- Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| |
Collapse
|
3
|
Zhao H. The Science and Art of Structure-Based Virtual Screening. ACS Med Chem Lett 2024; 15:436-440. [PMID: 38628791 PMCID: PMC11017385 DOI: 10.1021/acsmedchemlett.4c00093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 03/11/2024] [Indexed: 04/19/2024] Open
Abstract
Structure-based virtual screening has gained momentum again as the high attrition rate at every stage of drug discovery drives the need to explore a greater chemical space. From the Bayesian perspective, its shortcomings as a viable strategy for sustainable hit discovery are discussed, with regard to the prior hit rates of screening libraries and the performance of computational methods. Lessons are shared in selecting virtual hits for experimental validation learned from a series of eight successful campaigns, one of which impacted the discovery of a drug candidate currently in clinical trials.
Collapse
Affiliation(s)
- Hongtao Zhao
- Medicinal Chemistry, Research and Early
Development, Respiratory and Immunology (R&I), BioPharmaceuticals
R&D, AstraZeneca, Gothenburg 43183, Sweden
| |
Collapse
|
4
|
Liu F, Wu CG, Tu CL, Glenn I, Meyerowitz J, Levit Kaplan A, Lyu J, Cheng Z, Tarkhanova OO, Moroz YS, Irwin JJ, Chang W, Shoichet BK, Skiniotis G. Small vs. Large Library Docking for Positive Allosteric Modulators of the Calcium Sensing Receptor. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.27.573448. [PMID: 38234749 PMCID: PMC10793424 DOI: 10.1101/2023.12.27.573448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Drugs acting as positive allosteric modulators (PAMs) to enhance the activation of the calcium sensing receptor (CaSR) and to suppress parathyroid hormone (PTH) secretion can treat hyperparathyroidism but suffer from side effects including hypocalcemia and arrhythmias. Seeking new CaSR modulators, we docked libraries of 2.7 million and 1.2 billion molecules against transforming pockets in the active-state receptor dimer structure. Consistent with simulations suggesting that docking improves with library size, billion-molecule docking found new PAMs with a hit rate that was 2.7-fold higher than the million-molecule library and with hits up to 37-fold more potent. Structure-based optimization of ligands from both campaigns led to nanomolar leads, one of which was advanced to animal testing. This PAM displays 100-fold the potency of the standard of care, cinacalcet, in ex vivo organ assays, and reduces serum PTH levels in mice by up to 80% without the hypocalcemia typical of CaSR drugs. Cryo-EM structures with the new PAMs show that they induce residue rearrangements in the binding pockets and promote CaSR dimer conformations that are closer to the G-protein coupled state compared to established drugs. These findings highlight the promise of large library docking for therapeutic leads, especially when combined with experimental structure determination and mechanism.
Collapse
Affiliation(s)
- Fangyu Liu
- Dept. of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco CA 94143, USA
| | - Cheng-Guo Wu
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Chia-Ling Tu
- San Francisco VA Medical Center, Dept. of Medicine, University of California, San Francisco, San Francisco CA 94158, USA
| | - Isabella Glenn
- Dept. of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco CA 94143, USA
| | - Justin Meyerowitz
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Anat Levit Kaplan
- Dept. of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco CA 94143, USA
| | - Jiankun Lyu
- Dept. of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco CA 94143, USA
- Current address: The Rockefeller University, New York, NY, 10065
| | - Zhiqiang Cheng
- San Francisco VA Medical Center, Dept. of Medicine, University of California, San Francisco, San Francisco CA 94158, USA
| | | | - Yurii S. Moroz
- Chemspace LLC, Kyiv, 02094, Ukraine
- Taras Shevchenko National University of Kyiv, Kyiv, 01601, Ukraine
- Enamine Ltd., Kyiv, 02094, Ukraine
| | - John J. Irwin
- Dept. of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco CA 94143, USA
| | - Wenhan Chang
- San Francisco VA Medical Center, Dept. of Medicine, University of California, San Francisco, San Francisco CA 94158, USA
| | - Brian K. Shoichet
- Dept. of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco CA 94143, USA
| | - Georgios Skiniotis
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
| |
Collapse
|
5
|
Isert C, Atz K, Riniker S, Schneider G. Exploring protein-ligand binding affinity prediction with electron density-based geometric deep learning. RSC Adv 2024; 14:4492-4502. [PMID: 38312732 PMCID: PMC10835705 DOI: 10.1039/d3ra08650j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 01/19/2024] [Indexed: 02/06/2024] Open
Abstract
Rational structure-based drug design relies on accurate predictions of protein-ligand binding affinity from structural molecular information. Although deep learning-based methods for predicting binding affinity have shown promise in computational drug design, certain approaches have faced criticism for their potential to inadequately capture the fundamental physical interactions between ligands and their macromolecular targets or for being susceptible to dataset biases. Herein, we propose to include bond-critical points based on the electron density of a protein-ligand complex as a fundamental physical representation of protein-ligand interactions. Employing a geometric deep learning model, we explore the usefulness of these bond-critical points to predict absolute binding affinities of protein-ligand complexes, benchmark model performance against existing methods, and provide a critical analysis of this new approach. The models achieved root-mean-squared errors of 1.4-1.8 log units on the PDBbind dataset, and 1.0-1.7 log units on the PDE10A dataset, not indicating significant advantages over benchmark methods, and thus rendering the utility of electron density for deep learning models context-dependent. The relationship between intermolecular electron density and corresponding binding affinity was analyzed, and Pearson correlation coefficients r > 0.7 were obtained for several macromolecular targets.
Collapse
Affiliation(s)
- Clemens Isert
- ETH Zurich, Department of Chemistry and Applied Biosciences Vladimir-Prelog-Weg 4 8093 Zurich Switzerland +41 44 633 73 27
| | - Kenneth Atz
- ETH Zurich, Department of Chemistry and Applied Biosciences Vladimir-Prelog-Weg 4 8093 Zurich Switzerland +41 44 633 73 27
| | - Sereina Riniker
- ETH Zurich, Department of Chemistry and Applied Biosciences Vladimir-Prelog-Weg 4 8093 Zurich Switzerland +41 44 633 73 27
| | - Gisbert Schneider
- ETH Zurich, Department of Chemistry and Applied Biosciences Vladimir-Prelog-Weg 4 8093 Zurich Switzerland +41 44 633 73 27
| |
Collapse
|
6
|
Smith M, Knight IS, Kormos RC, Pepe JG, Kunach P, Diamond MI, Shahmoradian SH, Irwin JJ, DeGrado WF, Shoichet BK. Docking for Molecules That Bind in a Symmetric Stack with SymDOCK. J Chem Inf Model 2024; 64:425-434. [PMID: 38191997 PMCID: PMC10806807 DOI: 10.1021/acs.jcim.3c01749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/10/2024]
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.
Collapse
Affiliation(s)
- Matthew
S. Smith
- Department
of Pharmaceutical Chemistry, University
of California, UCSF Genentech
Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States
- Program
in Biophysics, University of California, UCSF Genentech Hall MC2240, 600
16th St Rm N474D,San Francisco, California 94143, United States
| | - Ian S. Knight
- Department
of Pharmaceutical Chemistry, University
of California, UCSF Genentech
Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States
| | - Rian C. Kormos
- Department
of Pharmaceutical Chemistry, University
of California, UCSF Genentech
Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States
- Program
in Biophysics, University of California, UCSF Genentech Hall MC2240, 600
16th St Rm N474D,San Francisco, California 94143, United States
| | - Joseph G. Pepe
- Department
of Pharmaceutical Chemistry, University
of California, UCSF Genentech
Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States
- Program
in Biophysics, University of California, UCSF Genentech Hall MC2240, 600
16th St Rm N474D,San Francisco, California 94143, United States
| | - Peter Kunach
- McGill
Research Centre for Studies in Aging, McGill
University, 6875 Boulevard LaSalle, Montreal, Quebec H4H 1R3, Canada
- Department
of Neurology and Neurosurgery, McGill University, 1033 Pine Avenue West, Room 310, Montreal, Quebec H3A 1A1, Canada
- 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
- Department
of Neurology, University of Texas Southwestern
Medical Center, 5323 Harry Hines Blvd., G2.222, Dallas, Texas 75390-9368, United States
- Department
of Neuroscience, University of Texas Southwestern
Medical Center, 5323 Harry Hines Blvd., Dallas, Texas 75390-9111, United States
| | - Marc I. Diamond
- 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
- Department
of Neurology, University of Texas Southwestern
Medical Center, 5323 Harry Hines Blvd., G2.222, Dallas, Texas 75390-9368, United States
- Department
of Neuroscience, University of Texas Southwestern
Medical Center, 5323 Harry Hines Blvd., Dallas, Texas 75390-9111, United States
| | - Sarah H. Shahmoradian
- 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
- Department
of Biophysics, University of Texas Southwestern
Medical Center, 5323 Harry Hines Blvd., Dallas, Texas 75390-8816, United States
| | - John J. Irwin
- Department
of Pharmaceutical Chemistry, University
of California, UCSF Genentech
Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States
| | - William F. DeGrado
- Department
of Pharmaceutical Chemistry, University
of California, UCSF Genentech
Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States
- Cardiovascular
Research Institute, University of California, 555 Mission Bay Blvd South, PO Box 589001, San Francisco, California 94158-9001, United
States
| | - Brian K. Shoichet
- Department
of Pharmaceutical Chemistry, University
of California, UCSF Genentech
Hall Box 2280, 600 16th St Rm 518,San Francisco, California 94158, United States
| |
Collapse
|
7
|
Sweeney A, Mulvaney T, Maiorca M, Topf M. ChemEM: Flexible Docking of Small Molecules in Cryo-EM Structures. J Med Chem 2024; 67:199-212. [PMID: 38157562 PMCID: PMC10788898 DOI: 10.1021/acs.jmedchem.3c01134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 11/28/2023] [Accepted: 12/08/2023] [Indexed: 01/03/2024]
Abstract
Cryo-electron microscopy (cryo-EM), through resolution advancements, has become pivotal in structure-based drug discovery. However, most cryo-EM structures are solved at 3-4 Å resolution, posing challenges for small-molecule docking and structure-based virtual screening due to issues in the precise positioning of ligands and the surrounding side chains. We present ChemEM, a software package that employs cryo-EM data for the accurate docking of one or multiple ligands in a protein-binding site. Validated against a highly curated benchmark of high- and medium-resolution cryo-EM structures and the corresponding high-resolution controls, ChemEM displayed impressive performance, accurately placing ligands in all but one case, often surpassing cryo-EM PDB-deposited solutions. Even without including the cryo-EM density, the ChemEM scoring function outperformed the well-established AutoDock Vina score. Using ChemEM, we illustrate that valuable information can be extracted from maps at medium resolution and underline the utility of cryo-EM structures for drug discovery.
Collapse
Affiliation(s)
- Aaron Sweeney
- Leibniz Institute of Virology (LIV), Hamburg 20251, Germany
- Centre for Structural Systems Biology, Hamburg 22607, Germany
- Universitätsklinikum Hamburg
Eppendorf (UKE), Hamburg 20246, Germany
| | - Thomas Mulvaney
- Leibniz Institute of Virology (LIV), Hamburg 20251, Germany
- Centre for Structural Systems Biology, Hamburg 22607, Germany
- Universitätsklinikum Hamburg
Eppendorf (UKE), Hamburg 20246, Germany
| | - Mauro Maiorca
- Leibniz Institute of Virology (LIV), Hamburg 20251, Germany
- Centre for Structural Systems Biology, Hamburg 22607, Germany
- Universitätsklinikum Hamburg
Eppendorf (UKE), Hamburg 20246, Germany
| | | |
Collapse
|
8
|
Chakrabarti M, Tan YS, Balius TE. Considerations Around Structure-Based Drug Discovery for KRAS Using DOCK. Methods Mol Biol 2024; 2797:67-90. [PMID: 38570453 DOI: 10.1007/978-1-0716-3822-4_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2024]
Abstract
Molecular docking is a popular computational tool in drug discovery. Leveraging structural information, docking software predicts binding poses of small molecules to cavities on the surfaces of proteins. Virtual screening for ligand discovery is a useful application of docking software. In this chapter, using the enigmatic KRAS protein as an example system, we endeavor to teach the reader about best practices for performing molecular docking with UCSF DOCK. We discuss methods for virtual screening and docking molecules on KRAS. We present the following six points to optimize our docking setup for prosecuting a virtual screen: protein structure choice, pocket selection, optimization of the scoring function, modification of sampling spheres and sampling procedures, choosing an appropriate portion of chemical space to dock, and the choice of which top scoring molecules to pick for purchase.
Collapse
Affiliation(s)
- Mayukh Chakrabarti
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Y Stanley Tan
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Trent E Balius
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.
| |
Collapse
|
9
|
Gahbauer S, DeLeon C, Braz JM, Craik V, Kang HJ, Wan X, Huang XP, Billesbølle CB, Liu Y, Che T, Deshpande I, Jewell M, Fink EA, Kondratov IS, Moroz YS, Irwin JJ, Basbaum AI, Roth BL, Shoichet BK. Docking for EP4R antagonists active against inflammatory pain. Nat Commun 2023; 14:8067. [PMID: 38057319 PMCID: PMC10700596 DOI: 10.1038/s41467-023-43506-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 11/12/2023] [Indexed: 12/08/2023] Open
Abstract
The lipid prostaglandin E2 (PGE2) mediates inflammatory pain by activating G protein-coupled receptors, including the prostaglandin E2 receptor 4 (EP4R). Nonsteroidal anti-inflammatory drugs (NSAIDs) reduce nociception by inhibiting prostaglandin synthesis, however, the disruption of upstream prostanoid biosynthesis can lead to pleiotropic effects including gastrointestinal bleeding and cardiac complications. In contrast, by acting downstream, EP4R antagonists may act specifically as anti-inflammatory agents and, to date, no selective EP4R antagonists have been approved for human use. In this work, seeking to diversify EP4R antagonist scaffolds, we computationally dock over 400 million compounds against an EP4R crystal structure and experimentally validate 71 highly ranked, de novo synthesized molecules. Further, we show how structure-based optimization of initial docking hits identifies a potent and selective antagonist with 16 nanomolar potency. Finally, we demonstrate favorable pharmacokinetics for the discovered compound as well as anti-allodynic and anti-inflammatory activity in several preclinical pain models in mice.
Collapse
Affiliation(s)
- Stefan Gahbauer
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Chelsea DeLeon
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, 27514, USA
| | - Joao M Braz
- Department of Anatomy, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Veronica Craik
- Department of Anatomy, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Hye Jin Kang
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, 27514, USA
- Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, South Korea
| | - Xiaobo Wan
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Xi-Ping Huang
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, 27514, USA
| | - Christian B Billesbølle
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Yongfeng Liu
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, 27514, USA
| | - Tao Che
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, 27514, USA
- Center of Clinical Pharmacology, Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Ishan Deshpande
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Madison Jewell
- Department of Anatomy, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Elissa A Fink
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Ivan S Kondratov
- Enamine Ltd., Kyiv, Ukraine
- V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Sciences of Ukraine, Kyiv, Ukraine
| | - Yurii S Moroz
- Chemspace LLC, Kyiv, Ukraine
- National Taras Shevchenko University of Kyiv, Kyiv, Ukraine
| | - John J Irwin
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Allan I Basbaum
- Department of Anatomy, University of California San Francisco, San Francisco, CA, 94158, USA.
| | - Bryan L Roth
- Department of Pharmacology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, 27514, USA.
- National Institute of Mental Health Psychoactive Drug Screening Program, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, 27514, USA.
- Division of Chemical Biology and Medicinal Chemistry, University of North Carolina at Chapel Hill Eshelman School of Pharmacy, Chapel Hill, NC, 27514, USA.
| | - Brian K Shoichet
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA.
| |
Collapse
|
10
|
Smith MS, Knight IS, Kormos RC, Pepe JG, Kunach P, Diamond MI, Shahmoradian SH, Irwin JJ, DeGrado WF, Shoichet BK. Docking for molecules that bind in a symmetric stack with SymDOCK. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.27.564400. [PMID: 37961414 PMCID: PMC10634874 DOI: 10.1101/2023.10.27.564400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of much 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.
Collapse
Affiliation(s)
- Matthew S. Smith
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Program in Biophysics, University of California, San Francisco, San Francisco, CA, USA
| | - Ian S. Knight
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Rian C. Kormos
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Program in Biophysics, University of California, San Francisco, San Francisco, CA, USA
| | - Joseph G. Pepe
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Program in Biophysics, University of California, San Francisco, San Francisco, CA, USA
| | - Peter Kunach
- McGill Research Centre for Studies in Aging, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Center for Alzheimer’s and Neurodegenerative Diseases, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Marc I. Diamond
- Center for Alzheimer’s and Neurodegenerative Diseases, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sarah H. Shahmoradian
- Center for Alzheimer’s and Neurodegenerative Diseases, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - John J. Irwin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - William F. DeGrado
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Brian K. Shoichet
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| |
Collapse
|
11
|
Fink EA, Bardine C, Gahbauer S, Singh I, Detomasi TC, White K, Gu S, Wan X, Chen J, Ary B, Glenn I, O'Connell J, O'Donnell H, Fajtová P, Lyu J, Vigneron S, Young NJ, Kondratov IS, Alisoltani A, Simons LM, Lorenzo‐Redondo R, Ozer EA, Hultquist JF, O'Donoghue AJ, Moroz YS, Taunton J, Renslo AR, Irwin JJ, García‐Sastre A, Shoichet BK, Craik CS. Large library docking for novel SARS-CoV-2 main protease non-covalent and covalent inhibitors. Protein Sci 2023; 32:e4712. [PMID: 37354015 PMCID: PMC10364469 DOI: 10.1002/pro.4712] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 05/29/2023] [Accepted: 06/21/2023] [Indexed: 06/25/2023]
Abstract
Antiviral therapeutics to treat SARS-CoV-2 are needed to diminish the morbidity of the ongoing COVID-19 pandemic. A well-precedented drug target is the main viral protease (MPro ), which is targeted by an approved drug and by several investigational drugs. Emerging viral resistance has made new inhibitor chemotypes more pressing. Adopting a structure-based approach, we docked 1.2 billion non-covalent lead-like molecules and a new library of 6.5 million electrophiles against the enzyme structure. From these, 29 non-covalent and 11 covalent inhibitors were identified in 37 series, the most potent having an IC50 of 29 and 20 μM, respectively. Several series were optimized, resulting in low micromolar inhibitors. Subsequent crystallography confirmed the docking predicted binding modes and may template further optimization. While the new chemotypes may aid further optimization of MPro inhibitors for SARS-CoV-2, the modest success rate also reveals weaknesses in our approach for challenging targets like MPro versus other targets where it has been more successful, and versus other structure-based techniques against MPro itself.
Collapse
Affiliation(s)
- Elissa A. Fink
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
- Graduate Program in BiophysicsUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Conner Bardine
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
- Graduate Program in Chemistry and Chemical BiologyUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Stefan Gahbauer
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Isha Singh
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Tyler C. Detomasi
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Kris White
- Department of MicrobiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Global Health and Emerging Pathogens InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Shuo Gu
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Xiaobo Wan
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Jun Chen
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Beatrice Ary
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Isabella Glenn
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Joseph O'Connell
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Henry O'Donnell
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Pavla Fajtová
- Skaggs School of Pharmacy and Pharmaceutical SciencesUniversity of California‐San DiegoSan DiegoCaliforniaUSA
| | - Jiankun Lyu
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Seth Vigneron
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Nicholas J. Young
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Ivan S. Kondratov
- Enamine Ltd.KyïvUkraine
- V.P. Kukhar Institute of Bioorganic Chemistry and PetrochemistryNational Academy of Sciences of UkraineKyïvUkraine
| | - Arghavan Alisoltani
- Division of Infectious Diseases, Center for Pathogen Genomics and Microbial Evolution, Feinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Lacy M. Simons
- Division of Infectious Diseases, Center for Pathogen Genomics and Microbial Evolution, Feinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Ramon Lorenzo‐Redondo
- Division of Infectious Diseases, Center for Pathogen Genomics and Microbial Evolution, Feinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Egon A. Ozer
- Division of Infectious Diseases, Center for Pathogen Genomics and Microbial Evolution, Feinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Judd F. Hultquist
- Division of Infectious Diseases, Center for Pathogen Genomics and Microbial Evolution, Feinberg School of MedicineNorthwestern UniversityChicagoIllinoisUSA
| | - Anthony J. O'Donoghue
- Skaggs School of Pharmacy and Pharmaceutical SciencesUniversity of California‐San DiegoSan DiegoCaliforniaUSA
| | - Yurii S. Moroz
- National Taras Shevchenko University of KyïvKyïvUkraine
- Chemspace LLCKyïvUkraine
| | - Jack Taunton
- Department of Cellular and Molecular PharmacologyUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Adam R. Renslo
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - John J. Irwin
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
| | - Adolfo García‐Sastre
- Department of MicrobiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Global Health and Emerging Pathogens InstituteIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Medicine, Division of Infectious DiseasesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Tisch Cancer Institute, Icahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Pathology, Molecular and Cell‐Based MedicineIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- QBI COVID‐19 Research Group (QCRG)San FranciscoCaliforniaUSA
| | - Brian K. Shoichet
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
- QBI COVID‐19 Research Group (QCRG)San FranciscoCaliforniaUSA
| | - Charles S. Craik
- Department of Pharmaceutical ChemistryUniversity of California‐San FranciscoSan FranciscoCaliforniaUSA
- QBI COVID‐19 Research Group (QCRG)San FranciscoCaliforniaUSA
| |
Collapse
|
12
|
Singh I, Li F, Fink EA, Chau I, Li A, Rodriguez-Hernández A, Glenn I, Zapatero-Belinchón FJ, Rodriguez ML, Devkota K, Deng Z, White K, Wan X, Tolmachova NA, Moroz YS, Kaniskan HÜ, Ott M, García-Sastre A, Jin J, Fujimori DG, Irwin JJ, Vedadi M, Shoichet BK. Structure-Based Discovery of Inhibitors of the SARS-CoV-2 Nsp14 N7-Methyltransferase. J Med Chem 2023; 66:7785-7803. [PMID: 37294077 PMCID: PMC10374283 DOI: 10.1021/acs.jmedchem.2c02120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
An under-explored target for SARS-CoV-2 is the S-adenosyl methionine (SAM)-dependent methyltransferase Nsp14, which methylates the N7-guanosine of viral RNA at the 5'-end, allowing the virus to evade host immune response. We sought new Nsp14 inhibitors with three large library docking strategies. First, up to 1.1 billion lead-like molecules were docked against the enzyme's SAM site, leading to three inhibitors with IC50 values from 6 to 50 μM. Second, docking a library of 16 million fragments revealed 9 new inhibitors with IC50 values from 12 to 341 μM. Third, docking a library of 25 million electrophiles to covalently modify Cys387 revealed 7 inhibitors with IC50 values from 3.5 to 39 μM. Overall, 32 inhibitors encompassing 11 chemotypes had IC50 values < 50 μM and 5 inhibitors in 4 chemotypes had IC50 values < 10 μM. These molecules are among the first non-SAM-like inhibitors of Nsp14, providing starting points for future optimization.
Collapse
Affiliation(s)
- Isha Singh
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94143, United States
| | - Fengling Li
- Structural Genomics Consortium, University of Toronto, Toronto, Ontario M5G 1L7, Canada
| | - Elissa A Fink
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94143, United States
- Graduate Program in Biophysics, University of California San Francisco, San Francisco, California 94143, United States
| | - Irene Chau
- Structural Genomics Consortium, University of Toronto, Toronto, Ontario M5G 1L7, Canada
| | - Alice Li
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Drug Discovery Program, Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada
| | - Annía Rodriguez-Hernández
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, California 94158, United States
| | - Isabella Glenn
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94143, United States
| | | | - M Luis Rodriguez
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Kanchan Devkota
- Structural Genomics Consortium, University of Toronto, Toronto, Ontario M5G 1L7, Canada
| | - Zhijie Deng
- Mount Sinai Center for Therapeutics Discovery, Departments of Pharmacological Sciences, Oncological Sciences and Neuroscience, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Kris White
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Xiaobo Wan
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94143, United States
| | - Nataliya A Tolmachova
- Enamine Ltd, Kyïv 02094, Ukraine
- Institute of Bioorganic Chemistry and Petrochemistry, National Ukrainian Academy of Science, Kyïv 02660, Ukraine
| | - Yurii S Moroz
- National Taras Shevchenko University of Kyïv, Kyïv 01601, Ukraine
- Chemspace, Riga LV-1082, Latvia
| | - H Ümit Kaniskan
- Mount Sinai Center for Therapeutics Discovery, Departments of Pharmacological Sciences, Oncological Sciences and Neuroscience, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Melanie Ott
- Gladstone Institutes, San Francisco, California 94158, United States
- QBI COVID-19 Research Group (QCRG), San Francisco, California 94158, United States
- Department of Medicine, University of California, San Francisco, San Francisco, California 94158, United States
- Chan Zuckerberg Biohub, San Francisco, California 94158, United States
| | - Adolfo García-Sastre
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
- QBI COVID-19 Research Group (QCRG), San Francisco, California 94158, United States
- Department of Medicine, Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
- The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Jian Jin
- Mount Sinai Center for Therapeutics Discovery, Departments of Pharmacological Sciences, Oncological Sciences and Neuroscience, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
- QBI COVID-19 Research Group (QCRG), San Francisco, California 94158, United States
| | - Danica Galonić Fujimori
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94143, United States
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, California 94158, United States
- QBI COVID-19 Research Group (QCRG), San Francisco, California 94158, United States
| | - John J Irwin
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94143, United States
- QBI COVID-19 Research Group (QCRG), San Francisco, California 94158, United States
| | - Masoud Vedadi
- Structural Genomics Consortium, University of Toronto, Toronto, Ontario M5G 1L7, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- QBI COVID-19 Research Group (QCRG), San Francisco, California 94158, United States
- Drug Discovery Program, Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada
| | - Brian K Shoichet
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California 94143, United States
- QBI COVID-19 Research Group (QCRG), San Francisco, California 94158, United States
| |
Collapse
|
13
|
Lyu J, Irwin JJ, Shoichet BK. Modeling the expansion of virtual screening libraries. Nat Chem Biol 2023; 19:712-718. [PMID: 36646956 PMCID: PMC10243288 DOI: 10.1038/s41589-022-01234-w] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 11/22/2022] [Indexed: 01/17/2023]
Abstract
Recently, 'tangible' virtual libraries have made billions of molecules readily available. Prioritizing these molecules for synthesis and testing demands computational approaches, such as docking. Their success may depend on library diversity, their similarity to bio-like molecules and how receptor fit and artifacts change with library size. We compared a library of 3 million 'in-stock' molecules with billion-plus tangible libraries. The bias toward bio-like molecules in the tangible library decreases 19,000-fold versus those 'in-stock'. Similarly, thousands of high-ranking molecules, including experimental actives, from five ultra-large-library docking campaigns are also dissimilar to bio-like molecules. Meanwhile, better-fitting molecules are found as the library grows, with the score improving log-linearly with library size. Finally, as library size increases, so too do rare molecules that rank artifactually well. Although the nature of these artifacts changes from target to target, the expectation of their occurrence does not, and simple strategies can minimize their impact.
Collapse
Affiliation(s)
- Jiankun Lyu
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA
| | - John J Irwin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA.
| | - Brian K Shoichet
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA.
| |
Collapse
|
14
|
Singh I, Seth A, Billesbølle CB, Braz J, Rodriguiz RM, Roy K, Bekele B, Craik V, Huang XP, Boytsov D, Pogorelov VM, Lak P, O'Donnell H, Sandtner W, Irwin JJ, Roth BL, Basbaum AI, Wetsel WC, Manglik A, Shoichet BK, Rudnick G. Structure-based discovery of conformationally selective inhibitors of the serotonin transporter. Cell 2023; 186:2160-2175.e17. [PMID: 37137306 PMCID: PMC10306110 DOI: 10.1016/j.cell.2023.04.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 02/05/2023] [Accepted: 04/06/2023] [Indexed: 05/05/2023]
Abstract
The serotonin transporter (SERT) removes synaptic serotonin and is the target of anti-depressant drugs. SERT adopts three conformations: outward-open, occluded, and inward-open. All known inhibitors target the outward-open state except ibogaine, which has unusual anti-depressant and substance-withdrawal effects, and stabilizes the inward-open conformation. Unfortunately, ibogaine's promiscuity and cardiotoxicity limit the understanding of inward-open state ligands. We docked over 200 million small molecules against the inward-open state of the SERT. Thirty-six top-ranking compounds were synthesized, and thirteen inhibited; further structure-based optimization led to the selection of two potent (low nanomolar) inhibitors. These stabilized an outward-closed state of the SERT with little activity against common off-targets. A cryo-EM structure of one of these bound to the SERT confirmed the predicted geometry. In mouse behavioral assays, both compounds had anxiolytic- and anti-depressant-like activity, with potencies up to 200-fold better than fluoxetine (Prozac), and one substantially reversed morphine withdrawal effects.
Collapse
Affiliation(s)
- Isha Singh
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th St., Byers Hall Suite 508D, San Francisco, CA 94143, USA
| | - Anubha Seth
- Department of Pharmacology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8066, USA
| | - Christian B Billesbølle
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th St., Byers Hall Suite 508D, San Francisco, CA 94143, USA
| | - Joao Braz
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Ramona M Rodriguiz
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Mouse Behavioral and Neuroendocrine Analysis Core Facility, Duke University Medical Center, Durham, NC 27710, USA
| | - Kasturi Roy
- Department of Pharmacology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8066, USA
| | - Bethlehem Bekele
- Department of Pharmacology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8066, USA
| | - Veronica Craik
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Xi-Ping Huang
- Department of Pharmacology, NIMH Psychoactive Drug Screening Program, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Danila Boytsov
- Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, 1090 Vienna, Austria
| | - Vladimir M Pogorelov
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
| | - Parnian Lak
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th St., Byers Hall Suite 508D, San Francisco, CA 94143, USA
| | - Henry O'Donnell
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th St., Byers Hall Suite 508D, San Francisco, CA 94143, USA
| | - Walter Sandtner
- Institute of Pharmacology, Center for Physiology and Pharmacology, Medical University of Vienna, 1090 Vienna, Austria
| | - John J Irwin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th St., Byers Hall Suite 508D, San Francisco, CA 94143, USA
| | - Bryan L Roth
- Department of Pharmacology, NIMH Psychoactive Drug Screening Program, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Allan I Basbaum
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94143, USA.
| | - William C Wetsel
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Mouse Behavioral and Neuroendocrine Analysis Core Facility, Duke University Medical Center, Durham, NC 27710, USA; Departments of Cell Biology and Neurobiology, Duke University Medical Center, Durham, NC 27710, USA.
| | - Aashish Manglik
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th St., Byers Hall Suite 508D, San Francisco, CA 94143, USA; Department of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA 94115, USA.
| | - Brian K Shoichet
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 1700 4th St., Byers Hall Suite 508D, San Francisco, CA 94143, USA.
| | - Gary Rudnick
- Department of Pharmacology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8066, USA.
| |
Collapse
|
15
|
Tingle B, Tang KG, Castanon M, Gutierrez JJ, Khurelbaatar M, Dandarchuluun C, Moroz YS, Irwin JJ. ZINC-22─A Free Multi-Billion-Scale Database of Tangible Compounds for Ligand Discovery. J Chem Inf Model 2023; 63:1166-1176. [PMID: 36790087 PMCID: PMC9976280 DOI: 10.1021/acs.jcim.2c01253] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Indexed: 02/16/2023]
Abstract
Purchasable chemical space has grown rapidly into the tens of billions of molecules, providing unprecedented opportunities for ligand discovery but straining the tools that might exploit these molecules at scale. We have therefore developed ZINC-22, a database of commercially accessible small molecules derived from multi-billion-scale make-on-demand libraries. The new database and tools enable analog searching in this vast new space via a facile GUI, CartBlanche, drawing on similarity methods that scale sublinearly in the number of molecules. The new library also uses data organization methods, enabling rapid lookup of molecules and their physical properties, including conformations, partial atomic charges, c Log P values, and solvation energies, all crucial for molecule docking, which had become slow with older database organizations in previous versions of ZINC. As the libraries have continued to grow, we have been interested in finding whether molecular diversity has suffered, for instance, because certain scaffolds have come to dominate via easy analoging. This has not occurred thus far, and chemical diversity continues to grow with database size, with a log increase in Bemis-Murcko scaffolds for every two-log unit increase in database size. Most new scaffolds come from compounds with the highest heavy atom count. Finally, we consider the implications for databases like ZINC as the libraries grow toward and beyond the trillion-molecule range. ZINC is freely available to everyone and may be accessed at cartblanche22.docking.org, via Globus, and in the Amazon AWS and Oracle OCI clouds.
Collapse
Affiliation(s)
- Benjamin
I. Tingle
- Department
of Pharmaceutical Chemistry, University
of California San Francisco, 1700 4th St, Mailcode 2550, San Francisco, California 94158-2330, United States
| | - Khanh G. Tang
- Department
of Pharmaceutical Chemistry, University
of California San Francisco, 1700 4th St, Mailcode 2550, San Francisco, California 94158-2330, United States
| | - Mar Castanon
- Department
of Pharmaceutical Chemistry, University
of California San Francisco, 1700 4th St, Mailcode 2550, San Francisco, California 94158-2330, United States
| | - John J. Gutierrez
- Department
of Pharmaceutical Chemistry, University
of California San Francisco, 1700 4th St, Mailcode 2550, San Francisco, California 94158-2330, United States
| | - Munkhzul Khurelbaatar
- Department
of Pharmaceutical Chemistry, University
of California San Francisco, 1700 4th St, Mailcode 2550, San Francisco, California 94158-2330, United States
| | - Chinzorig Dandarchuluun
- Department
of Pharmaceutical Chemistry, University
of California San Francisco, 1700 4th St, Mailcode 2550, San Francisco, California 94158-2330, United States
| | - Yurii S. Moroz
- Taras
Shevchenko National University of Kyïv, 60 Volodymyrska Street, Kyïv 01601, Ukraine
- Chemspace
LLC, 85 Chervonotkatska
Street, Kyïv 02094, Ukraine
| | - John J. Irwin
- Department
of Pharmaceutical Chemistry, University
of California San Francisco, 1700 4th St, Mailcode 2550, San Francisco, California 94158-2330, United States
| |
Collapse
|
16
|
Xu M, Shen C, Yang J, Wang Q, Huang N. Systematic Investigation of Docking Failures in Large-Scale Structure-Based Virtual Screening. ACS OMEGA 2022; 7:39417-39428. [PMID: 36340123 PMCID: PMC9632257 DOI: 10.1021/acsomega.2c05826] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
In recent years, large-scale structure-based virtual screening has attracted increasing levels of interest for identification of novel compounds corresponding to potential drug targets. It is critical to understand the strengths and weaknesses of docking algorithms to increase the success rate in practical applications. Here, we systematically investigated the docking successes and failures of two representative docking programs: UCSF DOCK 3.7 and AutoDock Vina. DOCK 3.7 performed better in early enrichment on the Directory of Useful Decoys: Enhanced (DUD-E) data set, although both docking methods were roughly comparable in overall enrichment performance. DOCK 3.7 also showed superior computational efficiency. Intriguingly, the Vina scoring function showed a bias toward compounds with higher molecular weights. Both the tested docking approaches yielded incorrectly predicted ligand binding poses caused by the limitations of torsion sampling. Based on a careful analysis of docking results from six representative cases, we propose the reasons underlying docking failures; furthermore, we provide a few solutions, representing practical guidance for large-scale virtual screening campaigns and future docking algorithm development.
Collapse
Affiliation(s)
- Min Xu
- College
of Life Sciences, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- National
Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science
Park, Beijing 102206, China
| | - Cheng Shen
- National
Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science
Park, Beijing 102206, China
- Graduate
School of Peking Union Medical College, Chinese Academy of Medical Sciences, No. 9, Dongdan Santiao, Dongcheng District, Beijing 100730, China
| | - Jincai Yang
- National
Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science
Park, Beijing 102206, China
| | - Qing Wang
- National
Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science
Park, Beijing 102206, China
- School
of Pharmaceutical Science and Technology, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China
| | - Niu Huang
- National
Institute of Biological Sciences, 7 Science Park Road, Zhongguancun Life Science
Park, Beijing 102206, China
- Tsinghua
Institute of Multidisciplinary Biomedical Research, Tsinghua University, 7 Science Park Road, Zhongguancun Life Science Park, Beijing 102206, China
| |
Collapse
|
17
|
Fink EA, Xu J, Hübner H, Braz JM, Seemann P, Avet C, Craik V, Weikert D, Schmidt MF, Webb CM, Tolmachova NA, Moroz YS, Huang XP, Kalyanaraman C, Gahbauer S, Chen G, Liu Z, Jacobson MP, Irwin JJ, Bouvier M, Du Y, Shoichet BK, Basbaum AI, Gmeiner P. Structure-based discovery of nonopioid analgesics acting through the α 2A-adrenergic receptor. Science 2022; 377:eabn7065. [PMID: 36173843 PMCID: PMC10360211 DOI: 10.1126/science.abn7065] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Because nonopioid analgesics are much sought after, we computationally docked more than 301 million virtual molecules against a validated pain target, the α2A-adrenergic receptor (α2AAR), seeking new α2AAR agonists chemotypes that lack the sedation conferred by known α2AAR drugs, such as dexmedetomidine. We identified 17 ligands with potencies as low as 12 nanomolar, many with partial agonism and preferential Gi and Go signaling. Experimental structures of α2AAR complexed with two of these agonists confirmed the docking predictions and templated further optimization. Several compounds, including the initial docking hit '9087 [mean effective concentration (EC50) of 52 nanomolar] and two analogs, '7075 and PS75 (EC50 4.1 and 4.8 nanomolar), exerted on-target analgesic activity in multiple in vivo pain models without sedation. These newly discovered agonists are interesting as therapeutic leads that lack the liabilities of opioids and the sedation of dexmedetomidine.
Collapse
Affiliation(s)
- Elissa A. Fink
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Graduate Program in Biophysics, University of California, San Francisco, San Francisco, CA, USA
| | - Jun Xu
- Kobilka Institute of Innovative Drug Discovery, School of Life and Health Sciences, Chinese University of Hong Kong, Shenzhen, Guangdong 518172, China
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Harald Hübner
- Department of Chemistry and Pharmacy, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
| | - Joao M. Braz
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
| | - Philipp Seemann
- Department of Chemistry and Pharmacy, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
| | - Charlotte Avet
- Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada
| | - Veronica Craik
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
| | - Dorothee Weikert
- Department of Chemistry and Pharmacy, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
| | - Maximilian F. Schmidt
- Department of Chemistry and Pharmacy, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
| | - Chase M. Webb
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Graduate Program in Pharmaceutical Sciences and Pharmacogenomics, University of California, San Francisco, San Francisco, CA, USA
| | - Nataliya A. Tolmachova
- Enamine Ltd., 02094 Kyiv, Ukraine
- Institute of Bioorganic Chemistry and Petrochemistry, National Ukrainian Academy of Science, 02660 Kyiv, Ukraine
| | - Yurii S. Moroz
- National Taras Shevchenko University of Kyiv, 01601 Kyiv, Ukraine
- Chemspace, Riga LV-1082, Latvia
| | - Xi-Ping Huang
- National Institute of Mental Health Psychoactive Drug Screening Program (NIMH PDSP), School of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
| | - Chakrapani Kalyanaraman
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Stefan Gahbauer
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Geng Chen
- Kobilka Institute of Innovative Drug Discovery, School of Life and Health Sciences, Chinese University of Hong Kong, Shenzhen, Guangdong 518172, China
| | - Zheng Liu
- Kobilka Institute of Innovative Drug Discovery, School of Life and Health Sciences, Chinese University of Hong Kong, Shenzhen, Guangdong 518172, China
| | - Matthew P. Jacobson
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - John J. Irwin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Michel Bouvier
- Department of Biochemistry and Molecular Medicine, Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada
| | - Yang Du
- Kobilka Institute of Innovative Drug Discovery, School of Life and Health Sciences, Chinese University of Hong Kong, Shenzhen, Guangdong 518172, China
| | - Brian K. Shoichet
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Allan I. Basbaum
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
| | - Peter Gmeiner
- Department of Chemistry and Pharmacy, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
| |
Collapse
|
18
|
Hernandez CC, Tarfa RA, Miguel I Limcaoco J, Liu R, Mondal P, Hill C, Keith Duncan R, Tzounopoulos T, Stephenson CRJ, O'Meara MJ, Wipf P. Development of an automated screen for Kv7.2 potassium channels and discovery of a new agonist chemotype. Bioorg Med Chem Lett 2022; 71:128841. [PMID: 35671848 PMCID: PMC9469649 DOI: 10.1016/j.bmcl.2022.128841] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 05/11/2022] [Accepted: 06/01/2022] [Indexed: 01/11/2023]
Abstract
To identify pore domain ligands on Kv7.2 potassium ion channels, we compared wild-type (WT) and W236L mutant Kv7.2 channels in a series of assays with previously validated and novel agonist chemotypes. Positive controls were retigabine, flupirtine, and RL-81; i.e. Kv7.2 channel activators that significantly shift voltage-dependent activation to more negative potentials (ΔV50) at 5 µM. We identified 6 new compounds that exhibited differential enhancing activity between WT and W236L mutant channels. Whole cell patch-clamp electrophysiology studies were conducted to identify Kv7.2. Kv7.2/3, Kv7.4, and Kv7.5 selectivity. Our results validate the SyncroPatch platform and establish new structure activity relationships (SAR). Specifically, in addition to selective Kv7.2, Kv7.2/3, Kv7.4. and Kv7.5 agonists, we identified a novel chemotype, ZK-21, a 4-aminotetrahydroquinoline that is distinct from any of the previously described Kv7 channel modifiers. Using flexible receptor docking, ZK-21 was predicted to be stabilized by W236 and bind perpendicular to retigabine, burying the benzyl carbamate group into a tunnel reaching the core of the pore domain.
Collapse
Affiliation(s)
- Ciria C Hernandez
- Life Sciences Institute, University of Michigan, Ann Arbor, MI 48109, United States
| | - Rahilla A Tarfa
- Department of Otolaryngology, Pittsburgh Hearing Research Center, University of Pittsburgh, Pittsburgh, PA 15260, United States
| | - Jose Miguel I Limcaoco
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, United States
| | - Ruiting Liu
- Department of Chemistry, University of Pittsburgh, Pittsburgh, PA 15260, United States
| | - Pravat Mondal
- Department of Chemistry, University of Pittsburgh, Pittsburgh, PA 15260, United States
| | - Clare Hill
- Department of Chemistry, University of Pittsburgh, Pittsburgh, PA 15260, United States; Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, PA 15213, United States
| | - R Keith Duncan
- Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, MI 48109, United States
| | - Thanos Tzounopoulos
- Department of Otolaryngology, Pittsburgh Hearing Research Center, University of Pittsburgh, Pittsburgh, PA 15260, United States
| | - Corey R J Stephenson
- Department of Chemistry, University of Michigan, Ann Arbor, MI 48109, United States
| | - Matthew J O'Meara
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, United States
| | - Peter Wipf
- Department of Chemistry, University of Pittsburgh, Pittsburgh, PA 15260, United States; Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, PA 15213, United States; School of Pharmacy, University of Eastern Finland, 70210 Kuopio, Finland
| |
Collapse
|
19
|
Gahbauer S, Correy GJ, Schuller M, Ferla MP, Doruk YU, Rachman M, Wu T, Diolaiti M, Wang S, Neitz RJ, Fearon D, Radchenko D, Moroz Y, Irwin JJ, Renslo AR, Taylor JC, Gestwicki JE, von Delft F, Ashworth A, Ahel I, Shoichet BK, Fraser JS. Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 Macrodomain of SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.06.27.497816. [PMID: 35794891 PMCID: PMC9258288 DOI: 10.1101/2022.06.27.497816] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 152 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated protein dynamics within the active site, and key inhibitor motifs that will template future drug development against Mac1.
Collapse
Affiliation(s)
- Stefan Gahbauer
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA
| | - Galen J. Correy
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Marion Schuller
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE, UK
| | - Matteo P. Ferla
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
- National Institute for Health Research Oxford Biomedical Research Centre, Oxford, OX4 2PG, UK
| | - Yagmur Umay Doruk
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94158, USA
| | - Moira Rachman
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA
| | - Taiasean Wu
- Institute for Neurodegenerative Disease, University of California San Francisco, San Francisco, CA 94158, USA
- Chemistry and Chemical Biology Graduate Program, University of California San Francisco, San Francisco, CA 94158, USA
| | - Morgan Diolaiti
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94158, USA
| | - Siyi Wang
- Chemistry and Chemical Biology Graduate Program, University of California San Francisco, San Francisco, CA 94158, USA
| | - R. Jeffrey Neitz
- Department of Pharmaceutical Chemistry and Small Molecule Discovery Center, University of California, San Francisco, California 94158, USA
| | - Daren Fearon
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot OX11 0FA, UK
| | - Dmytro Radchenko
- Enamine Ltd., Chervonotkatska Street 78, Kyiv 02094, Ukraine
- Taras Shevchenko National University of Kyiv, Volodymyrska Street 60, Kyiv, 01601, Ukraine
| | - Yurii Moroz
- Taras Shevchenko National University of Kyiv, Volodymyrska Street 60, Kyiv, 01601, Ukraine
- Chemspace, Chervonotkatska Street 78, Kyiv, 02094, Ukraine
| | - John J. Irwin
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA
| | - Adam R. Renslo
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry and Small Molecule Discovery Center, University of California, San Francisco, California 94158, USA
| | - Jenny C. Taylor
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
- National Institute for Health Research Oxford Biomedical Research Centre, Oxford, OX4 2PG, UK
| | - Jason E. Gestwicki
- Institute for Neurodegenerative Disease, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Pharmaceutical Chemistry and Small Molecule Discovery Center, University of California, San Francisco, California 94158, USA
| | - Frank von Delft
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot OX11 0FA, UK
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
- Department of Biochemistry, University of Johannesburg, Auckland Park 2006, South Africa
| | - Alan Ashworth
- Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA 94158, USA
| | - Ivan Ahel
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, OX1 3RE, UK
| | - Brian K. Shoichet
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA
| | - James S. Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
| |
Collapse
|
20
|
Rath P, Ranjan A, Ghosh A, Chauhan A, Gurnani M, Tuli HS, Habeeballah H, Alkhanani MF, Haque S, Dhama K, Verma NK, Jindal T. Potential Therapeutic Target Protein Tyrosine Phosphatase-1B for Modulation of Insulin Resistance with Polyphenols and Its Quantitative Structure–Activity Relationship. Molecules 2022; 27:molecules27072212. [PMID: 35408611 PMCID: PMC9000704 DOI: 10.3390/molecules27072212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/10/2022] [Accepted: 03/17/2022] [Indexed: 11/17/2022] Open
Abstract
The increase in the number of cases of type 2 diabetes mellitus (T2DM) and the complications associated with the side effects of chemical/synthetic drugs have raised concerns about the safety of the drugs. Hence, there is an urgent need to explore and identify natural bioactive compounds as alternative drugs. Protein tyrosine phosphatase 1B (PTP1B) functions as a negative regulator and is therefore considered as one of the key protein targets modulating insulin signaling and insulin resistance. This article deals with the screening of a database of polyphenols against PTP1B activity for the identification of a potential inhibitor. The research plan had two clear objectives. Under first objective, we conducted a quantitative structure–activity relationship analysis of flavonoids with PTP1B that revealed the strongest correlation (R2 = 93.25%) between the number of aromatic bonds (naro) and inhibitory concentrations (IC50) of PTP1B. The second objective emphasized the binding potential of the selected polyphenols against the activity of PTP1B using molecular docking, molecular dynamic (MD) simulation and free energy estimation. Among all the polyphenols, silydianin, a flavonolignan, was identified as a lead compound that possesses drug-likeness properties, has a higher negative binding energy of −7.235 kcal/mol and a pKd value of 5.2. The free energy-based binding affinity (ΔG) was estimated to be −7.02 kcal/mol. MD simulation revealed the stability of interacting residues (Gly183, Arg221, Thr263 and Asp265). The results demonstrated that the identified polyphenol, silydianin, could act as a promising natural PTP1B inhibitor that can modulate the insulin resistance.
Collapse
Affiliation(s)
- Prangya Rath
- Amity Institute of Environmental Sciences, Amity University, Noida 201303, India; (P.R.); (M.G.)
| | - Anuj Ranjan
- Academy of Biology and Biotechnology, Southern Federal University, 344006 Rostov-on-Don, Russia
- Correspondence: (A.R.); (A.G.); Tel.: +91-999-090-7571 (A.R.); +91-967-862-9146 (A.G.)
| | - Arabinda Ghosh
- Microbiology Division, Department of Botany, Gauhati University, Guwahati 781014, India
- Correspondence: (A.R.); (A.G.); Tel.: +91-999-090-7571 (A.R.); +91-967-862-9146 (A.G.)
| | - Abhishek Chauhan
- Amity Institute of Environmental Toxicology Safety and Management, Amity University, Noida 201303, India; (A.C.); (T.J.)
| | - Manisha Gurnani
- Amity Institute of Environmental Sciences, Amity University, Noida 201303, India; (P.R.); (M.G.)
| | - Hardeep Singh Tuli
- Department of Biotechnology, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala 133207, India;
| | - Hamza Habeeballah
- Faculty of Applied Medical Sciences, King Abdulaziz University, Rabigh Branch, Rabigh 25732, Saudi Arabia;
| | - Mustfa F. Alkhanani
- Emergency Service Department, College of Applied Sciences, AlMaarefa University, Riyadh 11597, Saudi Arabia;
| | - Shafiul Haque
- Research and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan 45142, Saudi Arabia;
- Faculty of Medicine, Bursa Uludağ University Görükle Campus, Nilüfer 16059, Turkey
| | - Kuldeep Dhama
- Division of Pathology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, India;
| | - Naval Kumar Verma
- Homeopathy, Ministry of Ayush, Ayush Bhawan, B Block, GPO Complex INA, New Delhi 110023, India;
| | - Tanu Jindal
- Amity Institute of Environmental Toxicology Safety and Management, Amity University, Noida 201303, India; (A.C.); (T.J.)
| |
Collapse
|
21
|
Penner P, Guba W, Schmidt R, Meyder A, Stahl M, Rarey M. The Torsion Library: Semiautomated Improvement of Torsion Rules with SMARTScompare. J Chem Inf Model 2022; 62:1644-1653. [PMID: 35318851 DOI: 10.1021/acs.jcim.2c00043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The Torsion Library is a collection of torsion motifs associated with angle distributions, derived from crystallographic databases. It is used in strain assessment, conformer generation, and geometry optimization. A hierarchical structure of expert curated SMARTS defines the chemical environments of rotatable bonds and associates these with preferred angles. SMARTS can be very complex and full of implications, which make them difficult to maintain manually. Recent developments in automatically comparing SMARTS patterns can be applied to the Torsion Library to ensure its correctness. We specifically discuss the implementation and the limits of such a procedure in the context of torsion motifs and show several examples of how the Torsion Library benefits from this. All automated changes are validated manually and then shown to have an effect on the angle distributions by correcting matching behavior. The corrected Torsion Library itself is available including both PDB as well as CSD histograms in the Supporting Information and can be used to evaluate rotatable bonds at https://torsions.zbh.uni-hamburg.de.
Collapse
Affiliation(s)
- Patrick Penner
- Universität Hamburg,ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Wolfgang Guba
- Roche Pharma Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland
| | - Robert Schmidt
- Universität Hamburg,ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Agnes Meyder
- Universität Hamburg,ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Martin Stahl
- Roche Pharma Research & Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland
| | - Matthias Rarey
- Universität Hamburg,ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| |
Collapse
|
22
|
Andrianov GV, Ong WJG, Serebriiskii I, Karanicolas J. Efficient Hit-to-Lead Searching of Kinase Inhibitor Chemical Space via Computational Fragment Merging. J Chem Inf Model 2021; 61:5967-5987. [PMID: 34762402 PMCID: PMC8865965 DOI: 10.1021/acs.jcim.1c00630] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
In early-stage drug discovery, the hit-to-lead optimization (or "hit expansion") stage entails starting from a newly identified active compound and improving its potency or other properties. Traditionally, this process relies on synthesizing and evaluating a series of analogues to build up structure-activity relationships. Here, we describe a computational strategy focused on kinase inhibitors, intended to expedite the process of identifying analogues with improved potency. Our protocol begins from an inhibitor of the target kinase and generalizes the synthetic route used to access it. By searching for commercially available replacements for the individual building blocks used to make the parent inhibitor, we compile an enumerated library of compounds that can be accessed using the same chemical transformations; these huge libraries can exceed many millions─or billions─of compounds. Because the resulting libraries are much too large for explicit virtual screening, we instead consider alternate approaches to identify the top-scoring compounds. We find that contributions from individual substituents are well described by a pairwise additivity approximation, provided that the corresponding fragments position their shared core in precisely the same way relative to the binding site. This key insight allows us to determine which fragments are suitable for merging into single new compounds and which are not. Further, the use of pairwise approximation allows interaction energies to be assigned to each compound in the library without the need for any further structure-based modeling: interaction energies instead can be reliably estimated from the energies of the component fragments, and the reduced computational requirements allow for flexible energy minimizations that allow the kinase to respond to each substitution. We demonstrate this protocol using libraries built from six representative kinase inhibitors drawn from the literature, which target five different kinases: CDK9, CHK1, CDK2, EGFRT790M, and ACK1. In each example, the enumerated library includes additional analogues reported by the original study to have activity, and these analogues are successfully prioritized within the library. We envision that the insights from this work can facilitate the rapid assembly and screening of increasingly large libraries for focused hit-to-lead optimization. To enable adoption of these methods and to encourage further analyses, we disseminate the computational tools needed to deploy this protocol.
Collapse
Affiliation(s)
- Grigorii V. Andrianov
- Program in Molecular Therapeutics, Fox Chase Cancer Center, Philadelphia, PA 19111-2497,Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia, 420008
| | - Wern Juin Gabriel Ong
- Program in Molecular Therapeutics, Fox Chase Cancer Center, Philadelphia, PA 19111-2497,Bowdoin College, Brunswick, ME 04011
| | - Ilya Serebriiskii
- Program in Molecular Therapeutics, Fox Chase Cancer Center, Philadelphia, PA 19111-2497,Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia, 420008
| | - John Karanicolas
- Program in Molecular Therapeutics, Fox Chase Cancer Center, Philadelphia, PA 19111-2497,To whom correspondence should be addressed. , 215-728-7067
| |
Collapse
|
23
|
Structures of the σ 2 receptor enable docking for bioactive ligand discovery. Nature 2021; 600:759-764. [PMID: 34880501 DOI: 10.1038/s41586-021-04175-x] [Citation(s) in RCA: 98] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 10/19/2021] [Indexed: 11/08/2022]
Abstract
The σ2 receptor has attracted intense interest in cancer imaging1, psychiatric disease2, neuropathic pain3-5 and other areas of biology6,7. Here we determined the crystal structure of this receptor in complex with the clinical candidate roluperidone2 and the tool compound PB288. These structures templated a large-scale docking screen of 490 million virtual molecules, of which 484 compounds were synthesized and tested. We identified 127 new chemotypes with affinities superior to 1 μM, 31 of which had affinities superior to 50 nM. The hit rate fell smoothly and monotonically with docking score. We optimized three hits for potency and selectivity, and achieved affinities that ranged from 3 to 48 nM, with up to 250-fold selectivity versus the σ1 receptor. Crystal structures of two ligands bound to the σ2 receptor confirmed the docked poses. To investigate the contribution of the σ2 receptor in pain, two potent σ2-selective ligands and one potent σ1/σ2 non-selective ligand were tested for efficacy in a mouse model of neuropathic pain. All three ligands showed time-dependent decreases in mechanical hypersensitivity in the spared nerve injury model9, suggesting that the σ2 receptor has a role in nociception. This study illustrates the opportunities for rapid discovery of in vivo probes through structure-based screens of ultra large libraries, enabling study of underexplored areas of biology.
Collapse
|
24
|
Foloppe N, Chen IJ. The reorganization energy of compounds upon binding to proteins, from dynamic and solvated bound and unbound states. Bioorg Med Chem 2021; 51:116464. [PMID: 34798378 DOI: 10.1016/j.bmc.2021.116464] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 09/26/2021] [Accepted: 10/01/2021] [Indexed: 11/30/2022]
Abstract
The intramolecular reorganization energy (ΔEReorg) of compounds upon binding to proteins is a component of the binding free energy, which has long received particular attention, for fundamental and practical reasons. Understanding ΔEReorg would benefit the science of molecular recognition and drug design. For instance, the tolerable strain energy of compounds upon binding has been elusive. Prior studies found some large ΔEReorg values (e.g. > 10 kcal/mol), received with skepticism since they imply excessive opposition to binding. Indeed, estimating ΔEReorg is technically difficult. Typically, ΔEReorg has been approached by taking two energy-minimized conformers representing the bound and unbound states, and subtracting their conformational energy. This is a drastic oversimplification, liable to conformational collapse of the unbound conformer. Instead, the present work applies extensive molecular dynamics (MD) and the modern OPLS3 force-field to simulate compounds bound and unbound states, in explicit solvent under physically relevant conditions. The thermalized unbound compounds populate multiple conformations, not reducible to one or a few energy-minimized conformers. The intramolecular energies in the bound and unbound states were averaged over pertinent conformational ensembles, and the reorganization enthalpy upon binding (ΔHReorg) deduced by subtraction. This was applied to 76 systems, including 43 approved drugs, carefully selected for i) the quality of the bioactive X-ray structures and ii) the diversity of the chemotypes, their properties and protein targets. It yielded comparatively low ΔHReorg values (median = 1.4 kcal/mol, mean = 3.0 kcal/mol). A new finding is the observation of negative ΔHReorg values. Indeed, reorganization energies do not have to oppose binding, e.g. when intramolecular interactions stabilize preferentially the bound state. Conversely, even with competing water molecules, intramolecular interactions can occur predominantly in the unbound compound, and be replaced by intermolecular counterparts upon protein binding. Such disruption of intramolecular interactions upon binding gives rise to occasional larger ΔHReorg values. Such counterintuitive larger ΔHReorg values may be rationalized as a redistribution of interactions upon binding, qualitatively compatible with binding.
Collapse
Affiliation(s)
- Nicolas Foloppe
- Vernalis (R&D) Ltd, Granta Park, Abington, Cambridge CB21 6GB, UK.
| | - I-Jen Chen
- Vernalis (R&D) Ltd, Granta Park, Abington, Cambridge CB21 6GB, UK.
| |
Collapse
|
25
|
Guo J, Janet JP, Bauer MR, Nittinger E, Giblin KA, Papadopoulos K, Voronov A, Patronov A, Engkvist O, Margreitter C. DockStream: a docking wrapper to enhance de novo molecular design. J Cheminform 2021; 13:89. [PMID: 34789335 PMCID: PMC8596819 DOI: 10.1186/s13321-021-00563-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 10/29/2021] [Indexed: 01/09/2023] Open
Abstract
Recently, we have released the de novo design platform REINVENT in version 2.0. This improved and extended iteration supports far more features and scoring function components, which allows bespoke and tailor-made protocols to maximize impact in small molecule drug discovery projects. A major obstacle of generative models is producing active compounds, in which predictive (QSAR) models have been applied to enrich target activity. However, QSAR models are inherently limited by their applicability domains. To overcome these limitations, we introduce a structure-based scoring component for REINVENT. DockStream is a flexible, stand-alone molecular docking wrapper that provides access to a collection of ligand embedders and docking backends. Using the benchmarking and analysis workflow provided in DockStream, execution and subsequent analysis of a variety of docking configurations can be automated. Docking algorithms vary greatly in performance depending on the target and the benchmarking and analysis workflow provides a streamlined solution to identifying productive docking configurations. We show that an informative docking configuration can inform the REINVENT agent to optimize towards improving docking scores using public data. With docking activated, REINVENT is able to retain key interactions in the binding site, discard molecules which do not fit the binding cavity, harness unused (sub-)pockets, and improve overall performance in the scaffold-hopping scenario. The code is freely available at https://github.com/MolecularAI/DockStream .
Collapse
Affiliation(s)
- Jeff Guo
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Jon Paul Janet
- Medicinal Chemistry, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Matthias R Bauer
- Structure & Biophysics, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Eva Nittinger
- Medicinal Chemistry, Research and Early Development, Respiratory and Immunology (R&I), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Kathryn A Giblin
- Medicinal Chemistry, Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, UK
| | | | - Alexey Voronov
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Atanas Patronov
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden
| | - Ola Engkvist
- Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden
- Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | | |
Collapse
|
26
|
Bender BJ, Gahbauer S, Luttens A, Lyu J, Webb CM, Stein RM, Fink EA, Balius TE, Carlsson J, Irwin JJ, Shoichet BK. A practical guide to large-scale docking. Nat Protoc 2021; 16:4799-4832. [PMID: 34561691 PMCID: PMC8522653 DOI: 10.1038/s41596-021-00597-z] [Citation(s) in RCA: 184] [Impact Index Per Article: 61.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 06/22/2021] [Indexed: 02/08/2023]
Abstract
Structure-based docking screens of large compound libraries have become common in early drug and probe discovery. As computer efficiency has improved and compound libraries have grown, the ability to screen hundreds of millions, and even billions, of compounds has become feasible for modest-sized computer clusters. This allows the rapid and cost-effective exploration and categorization of vast chemical space into a subset enriched with potential hits for a given target. To accomplish this goal at speed, approximations are used that result in undersampling of possible configurations and inaccurate predictions of absolute binding energies. Accordingly, it is important to establish controls, as are common in other fields, to enhance the likelihood of success in spite of these challenges. Here we outline best practices and control docking calculations that help evaluate docking parameters for a given target prior to undertaking a large-scale prospective screen, with exemplification in one particular target, the melatonin receptor, where following this procedure led to direct docking hits with activities in the subnanomolar range. Additional controls are suggested to ensure specific activity for experimentally validated hit compounds. These guidelines should be useful regardless of the docking software used. Docking software described in the outlined protocol (DOCK3.7) is made freely available for academic research to explore new hits for a range of targets.
Collapse
Affiliation(s)
- Brian J Bender
- Department of Pharmaceutical Chemistry, University of California-San Francisco, San Francisco, CA, USA
| | - Stefan Gahbauer
- Department of Pharmaceutical Chemistry, University of California-San Francisco, San Francisco, CA, USA
| | - Andreas Luttens
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Jiankun Lyu
- Department of Pharmaceutical Chemistry, University of California-San Francisco, San Francisco, CA, USA
| | - Chase M Webb
- Department of Pharmaceutical Chemistry, University of California-San Francisco, San Francisco, CA, USA
| | - Reed M Stein
- Department of Pharmaceutical Chemistry, University of California-San Francisco, San Francisco, CA, USA
| | - Elissa A Fink
- Department of Pharmaceutical Chemistry, University of California-San Francisco, San Francisco, CA, USA
| | - Trent E Balius
- NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc, Frederick, MD, USA
| | - Jens Carlsson
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - John J Irwin
- Department of Pharmaceutical Chemistry, University of California-San Francisco, San Francisco, CA, USA
| | - Brian K Shoichet
- Department of Pharmaceutical Chemistry, University of California-San Francisco, San Francisco, CA, USA.
| |
Collapse
|