1
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Szél V, Zsidó BZ, Hetényi C. Enthalpic Classification of Water Molecules in Target-Ligand Binding. J Chem Inf Model 2024; 64:6583-6595. [PMID: 39135312 DOI: 10.1021/acs.jcim.4c00794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Water molecules play various roles in target-ligand binding. For example, they can be replaced by the ligand and leave the surface of the binding pocket or stay conserved in the interface and form bridges with the target. While experimental techniques supply target-ligand complex structures at an increasing rate, they often have limitations in the measurement of a detailed water structure. Moreover, measurements of binding thermodynamics cannot distinguish between the different roles of individual water molecules. However, such a distinction and classification of the role of individual water molecules would be key to their application in drug design at atomic resolution. In this study, we investigate a quantitative approach for the description of the role of water molecules during ligand binding. Starting from complete hydration structures of the free and ligand-bound target molecules, binding enthalpy scores are calculated for each water molecule using quantum mechanical calculations. A statistical evaluation showed that the scores can distinguish between conserved and displaced classes of water molecules. The classification system was calibrated and tested on more than 1000 individual water positions. The practical tests of the enthalpic classification included important cases of antiviral drug research on HIV-1 protease inhibitors and the Influenza A ion channel. The methodology of classification is based on open source program packages, Gromacs, Mopac, and MobyWat, freely available to the scientific community.
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Affiliation(s)
- Viktor Szél
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, Pécs 7624, Hungary
| | - Balázs Zoltán Zsidó
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, Pécs 7624, Hungary
| | - Csaba Hetényi
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, Pécs 7624, Hungary
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2
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Bayarsaikhan B, Zsidó BZ, Börzsei R, Hetényi C. Efficient Refinement of Complex Structures of Flexible Histone Peptides Using Post-Docking Molecular Dynamics Protocols. Int J Mol Sci 2024; 25:5945. [PMID: 38892133 PMCID: PMC11172440 DOI: 10.3390/ijms25115945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 05/26/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024] Open
Abstract
Histones are keys to many epigenetic events and their complexes have therapeutic and diagnostic importance. The determination of the structures of histone complexes is fundamental in the design of new drugs. Computational molecular docking is widely used for the prediction of target-ligand complexes. Large, linear peptides like the tail regions of histones are challenging ligands for docking due to their large conformational flexibility, extensive hydration, and weak interactions with the shallow binding pockets of their reader proteins. Thus, fast docking methods often fail to produce complex structures of such peptide ligands at a level appropriate for drug design. To address this challenge, and improve the structural quality of the docked complexes, post-docking refinement has been applied using various molecular dynamics (MD) approaches. However, a final consensus has not been reached on the desired MD refinement protocol. In this present study, MD refinement strategies were systematically explored on a set of problematic complexes of histone peptide ligands with relatively large errors in their docked geometries. Six protocols were compared that differ in their MD simulation parameters. In all cases, pre-MD hydration of the complex interface regions was applied to avoid the unwanted presence of empty cavities. The best-performing protocol achieved a median of 32% improvement over the docked structures in terms of the change in root mean squared deviations from the experimental references. The influence of structural factors and explicit hydration on the performance of post-docking MD refinements are also discussed to help with their implementation in future methods and applications.
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Affiliation(s)
- Bayartsetseg Bayarsaikhan
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary; (B.B.); (B.Z.Z.); (R.B.)
| | - Balázs Zoltán Zsidó
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary; (B.B.); (B.Z.Z.); (R.B.)
| | - Rita Börzsei
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary; (B.B.); (B.Z.Z.); (R.B.)
| | - Csaba Hetényi
- Pharmacoinformatics Unit, Department of Pharmacology and Pharmacotherapy, Medical School, University of Pécs, Szigeti út 12, H-7624 Pécs, Hungary; (B.B.); (B.Z.Z.); (R.B.)
- National Laboratory for Drug Research and Development, Magyar tudósok krt. 2, H-1117 Budapest, Hungary
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3
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Ceccarelli G, Goracci L, Carotti A, Paccoia F, Passeri D, Cipolloni M, Di Bona S, Cruciani G, Pellicciari R, Gioiello A. Discovery and Structure-Activity Relationships of Novel ssDAF-12 Receptor Modulators. J Med Chem 2024; 67:4150-4169. [PMID: 38417155 DOI: 10.1021/acs.jmedchem.3c02421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2024]
Abstract
The nuclear receptor ssDAF-12 has been recognized as the key molecular player regulating the life cycle of the nematode parasite Strongyloides stercoralis. ssDAF-12 ligands permit the receptor to function as an on/off switch modulating infection, making it vulnerable to therapeutic intervention. In this study, we report the design and synthesis of a set of novel dafachronic acid derivatives, which were used to outline the first structure-activity relationship targeting the ssDAF-12 receptor and to unveil hidden properties shared by the molecular shape of steroidal ligands that are relevant to the receptor binding and modulation. Moreover, biological results led to the discovery of sulfonamide 3 as a submicromolar ssDAF-12 agonist endowed with a high receptor selectivity, no toxicity, and improved properties, as well as to the identification of unprecedented ssDAF-12 antagonists that can be exploited in the search for novel chemical tools and alternative therapeutic approaches for treating parasitism such as Strongyloidiasis.
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Affiliation(s)
- Giada Ceccarelli
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123 Perugia, Italy
| | - Laura Goracci
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Via dell' Elce di Sotto 8, 06123 Perugia, Italy
| | - Andrea Carotti
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123 Perugia, Italy
| | - Federico Paccoia
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123 Perugia, Italy
| | | | | | - Stefano Di Bona
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Via dell' Elce di Sotto 8, 06123 Perugia, Italy
| | - Gabriele Cruciani
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Via dell' Elce di Sotto 8, 06123 Perugia, Italy
| | | | - Antimo Gioiello
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123 Perugia, Italy
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4
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Papadourakis M, Sinenka H, Matricon P, Hénin J, Brannigan G, Pérez-Benito L, Pande V, van Vlijmen H, de Graaf C, Deflorian F, Tresadern G, Cecchini M, Cournia Z. Alchemical Free Energy Calculations on Membrane-Associated Proteins. J Chem Theory Comput 2023; 19:7437-7458. [PMID: 37902715 PMCID: PMC11017255 DOI: 10.1021/acs.jctc.3c00365] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Indexed: 10/31/2023]
Abstract
Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.
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Affiliation(s)
- Michail Papadourakis
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Hryhory Sinenka
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Pierre Matricon
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Jérôme Hénin
- Laboratoire
de Biochimie Théorique UPR 9080, CNRS and Université Paris Cité, 75005 Paris, France
| | - Grace Brannigan
- Center
for Computational and Integrative Biology, Rutgers University−Camden, Camden, New Jersey 08103, United States of America
- Department
of Physics, Rutgers University−Camden, Camden, New Jersey 08102, United States
of America
| | - Laura Pérez-Benito
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Vineet Pande
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Herman van Vlijmen
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Chris de Graaf
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Francesca Deflorian
- Sosei
Heptares, Steinmetz Building,
Granta Park, Great Abington, Cambridge CB21 6DG, United
Kingdom
| | - Gary Tresadern
- CADD,
In Silico Discovery, Janssen Research &
Development, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Marco Cecchini
- Institut
de Chimie de Strasbourg, UMR7177, CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France
| | - Zoe Cournia
- Biomedical
Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece
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5
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de Oliveira C, Leswing K, Feng S, Kanters R, Abel R, Bhat S. FEP Protocol Builder: Optimization of Free Energy Perturbation Protocols Using Active Learning. J Chem Inf Model 2023; 63:5592-5603. [PMID: 37594480 DOI: 10.1021/acs.jcim.3c00681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
Significant improvements have been made in the past decade to methods that rapidly and accurately predict binding affinity through free energy perturbation (FEP) calculations. This has been driven by recent advances in small-molecule force fields and sampling algorithms combined with the availability of low-cost parallel computing. Predictive accuracies of ∼1 kcal mol-1 have been regularly achieved, which are sufficient to drive potency optimization in modern drug discovery campaigns. Despite the robustness of these FEP approaches across multiple target classes, there are invariably target systems that do not display expected performance with default FEP settings. Traditionally, these systems required labor-intensive manual protocol development to arrive at parameter settings that produce a predictive FEP model. Due to the (a) relatively large parameter space to be explored, (b) significant compute requirements, and (c) limited understanding of how combinations of parameters can affect FEP performance, manual FEP protocol optimization can take weeks to months to complete, and often does not involve rigorous train-test set splits, resulting in potential overfitting. These manual FEP protocol development timelines do not coincide with tight drug discovery project timelines, essentially preventing the use of FEP calculations for these target systems. Here, we describe an automated workflow termed FEP Protocol Builder (FEP-PB) to rapidly generate accurate FEP protocols for systems that do not perform well with default settings. FEP-PB uses an active-learning workflow to iteratively search the protocol parameter space to develop accurate FEP protocols. To validate this approach, we applied it to pharmaceutically relevant systems where default FEP settings could not produce predictive models. We demonstrate that FEP-PB can rapidly generate accurate FEP protocols for the previously challenging MCL1 system with limited human intervention. We also apply FEP-PB in a real-world drug discovery setting to generate an accurate FEP protocol for the p97 system. FEP-PB is able to generate a more accurate protocol than the expert user, rapidly validating p97 as amenable to free energy calculations. Additionally, through the active-learning workflow, we are able to gain insight into which parameters are most important for a given system. These results suggest that FEP-PB is a robust tool that can aid in rapidly developing accurate FEP protocols and increasing the number of targets that are amenable to the technology.
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Affiliation(s)
- César de Oliveira
- Schrodinger, Inc., 9868 Scranton Road, Suite 3200, San Diego, California 92121, United States
| | - Karl Leswing
- Schrodinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Shulu Feng
- Schrodinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - René Kanters
- Schrodinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Robert Abel
- Schrodinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
| | - Sathesh Bhat
- Schrodinger, Inc., 1540 Broadway, 24th Floor, New York, New York 10036, United States
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6
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Shi J, Cho JH, Hwang W. Heterogeneous and Allosteric Role of Surface Hydration for Protein-Ligand Binding. J Chem Theory Comput 2023; 19:1875-1887. [PMID: 36820489 PMCID: PMC10848206 DOI: 10.1021/acs.jctc.2c00776] [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: 07/27/2022] [Indexed: 02/24/2023]
Abstract
Atomistic-level understanding of surface hydration mediating protein-protein interactions and ligand binding has been a challenge due to the dynamic nature of water molecules near the surface. We develop a computational method to evaluate the solvation free energy based on the density map of the first hydration shell constructed from all-atom molecular dynamics simulation and use it to examine the binding of two intrinsically disordered ligands to their target protein domain. One ligand is from the human protein, and the other is from the 1918 Spanish flu virus. We find that the viral ligand incurs a 6.9 kcal/mol lower desolvation penalty upon binding to the target, which is consistent with its stronger binding affinity. The difference arises from the spatially fragmented and nonuniform water density profiles of the first hydration shell. In particular, residues that are distal from the ligand-binding site contribute to a varying extent to the desolvation penalty, among which the "entropy hotspot" residues contribute significantly. Thus, ligand binding alters hydration on remote sites in addition to affecting the binding interface. The nonlocal effect disappears when the conformational motion of the protein is suppressed. The present results elucidate the interplay between protein conformational dynamics and surface hydration. Our approach of measuring the solvation free energy based on the water density of the first hydration shell is tolerant of the conformational fluctuation of protein, and we expect it to be applicable to investigating a broad range of biomolecular interfaces.
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Affiliation(s)
- Jie Shi
- Department
of Biomedical Engineering, Texas A&M
University, College
Station, Texas 777843, United States
| | - Jae-Hyun Cho
- Department
of Biochemistry and Biophysics, Texas A&M
University, College Station, Texas 77843, United States
| | - Wonmuk Hwang
- Department
of Biomedical Engineering, Texas A&M
University, College Station, Texas 77843, United States
- Department
of Materials Science and Engineering, Texas
A&M University, College Station, Texas 77843, United States
- Department
of Physics and Astronomy, Texas A&M
University, College Station, Texas 77843, United States
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7
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Dutta P, Roy P, Sengupta N. Effects of External Perturbations on Protein Systems: A Microscopic View. ACS OMEGA 2022; 7:44556-44572. [PMID: 36530249 PMCID: PMC9753117 DOI: 10.1021/acsomega.2c06199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
Protein folding can be viewed as the origami engineering of biology resulting from the long process of evolution. Even decades after its recognition, research efforts worldwide focus on demystifying molecular factors that underlie protein structure-function relationships; this is particularly relevant in the era of proteopathic disease. A complex co-occurrence of different physicochemical factors such as temperature, pressure, solvent, cosolvent, macromolecular crowding, confinement, and mutations that represent realistic biological environments are known to modulate the folding process and protein stability in unique ways. In the current review, we have contextually summarized the substantial efforts in unveiling individual effects of these perturbative factors, with major attention toward bottom-up approaches. Moreover, we briefly present some of the biotechnological applications of the insights derived from these studies over various applications including pharmaceuticals, biofuels, cryopreservation, and novel materials. Finally, we conclude by summarizing the challenges in studying the combined effects of multifactorial perturbations in protein folding and refer to complementary advances in experiment and computational techniques that lend insights to the emergent challenges.
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Affiliation(s)
- Pallab Dutta
- Department
of Biological Sciences, Indian Institute
of Science Education and Research (IISER) Kolkata, Mohanpur741246, India
| | - Priti Roy
- Department
of Biological Sciences, Indian Institute
of Science Education and Research (IISER) Kolkata, Mohanpur741246, India
- Department
of Chemistry, Oklahoma State University, Stillwater, Oklahoma74078, United States
| | - Neelanjana Sengupta
- Department
of Biological Sciences, Indian Institute
of Science Education and Research (IISER) Kolkata, Mohanpur741246, India
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8
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Tošović J, Fijan D, Jukič M, Bren U. Conserved Water Networks Identification for Drug Design Using Density Clustering Approaches on Positional and Orientational Data. J Chem Inf Model 2022; 62:6105-6117. [PMID: 36351288 DOI: 10.1021/acs.jcim.2c00801] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
This work describes the development and testing of a method for the identification and classification of conserved water molecules and their networks from molecular dynamics (MD) simulations. The conserved waters in the active sites of proteins influence protein-ligand binding. Recently, several groups have argued that a water network formed from conserved waters can be used to interpret the thermodynamic signature of the binding site. We implemented a novel methodology in which we apply the complex approach to categorize water molecules extracted from the MD simulation trajectories using clustering approaches. The main advantage of our methodology as compared to current state of the art approaches is the inclusion of the information on the orientation of hydrogen atoms to further inform the clustering algorithm and to classify the conserved waters into different subtypes depending on how strongly certain orientations are preferred. This information is vital for assessing the stability of water networks. The newly developed approach is described in detail as well as validated against known results from the scientific literature including comparisons with the experimental data on thermolysin, thrombin, and Haemophilus influenzae virulence protein SiaP as well as with the previous computational results on thermolysin. We observed excellent agreement with the literature and were also able to provide additional insights into the orientations of the conserved water molecules, highlighting the key interactions which stabilize them. The source code of our approach, as well as the utility tools used for visualization, are freely available on GitHub.
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Affiliation(s)
- Jelena Tošović
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000Maribor, Slovenia
| | | | - Marko Jukič
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000Maribor, Slovenia.,Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000Koper, Slovenia
| | - Urban Bren
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, SI-2000Maribor, Slovenia.,Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000Koper, Slovenia.,Institute of Environmental Protection and Sensors, Beloruska ulica 7, SI-2000Maribor, Slovenia
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9
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Saleem U, Khalid S, Zaib S, Anwar F, Akhtar MF, Hussain L, Saleem A, Ahmad B. Wound Healing Potential and In Silico Appraisal of Convolvulus arvensis L. Methanolic Extract. BIOMED RESEARCH INTERNATIONAL 2022; 2022:1373160. [PMID: 36467883 PMCID: PMC9715325 DOI: 10.1155/2022/1373160] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 10/21/2022] [Accepted: 10/28/2022] [Indexed: 10/29/2023]
Abstract
Convolvulus arvensis L. is rich in phenolic compounds and traditionally used to treat wounds, skin ulcer, and inflammation. The current study is aimed at scientifically potentiating its traditional wound healing use. The methanolic extract of C. arvensis stem (CaME) was analyzed for HPLC and GC-MS analyses. The binding modes of active compounds were investigated against protein targets glycogen synthase kinase-3β (GSK-3β), transforming growth factor-beta (TGF-β), c-myc, and β-catenin by molecular docking followed by molecular dynamic simulations which revealed some conserved mode of binding as reported in crystal structures. The antioxidant potential of CaME was evaluated by in vitro methods such as 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, hydrogen peroxide scavenging, and ferric reducing power assays. Ointment formulations of 10 and 20% CaME were applied topically and evaluated for wound healing potency against the excisional wound on the skin of Wistar rats. Gentamycin (0.1%) served as standard therapy. The healing process was observed for 20 days in the form of wound size and epithelialization followed by histopathological evaluation of the wound area. Chemical characterization showed the presence of 7-hexadecenoic acid, 2-hexadecylicosan-1-ol, quercetin, gallic acid, ferulic acid, and other compounds. The plant extract exhibited significant in vitro antioxidant activity. The animals treated with 10% ointment showed moderate healing, whereas the treatment with 20% CaME revealed healing potential comparable to the standard 0.1% gentamycin as coevidenced from histopathological evaluation of skin. The study corroborates promising potential of C. arvensis on the healing of wounds, which possibly will be attributed to its antioxidant activity, fatty acids, quercetin, and gallic and caffeic acids, and binding potential of its phytoconstituents (phenolic acids) with wound healing targets.
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Affiliation(s)
- Uzma Saleem
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad 38000, Pakistan
| | - Sana Khalid
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad 38000, Pakistan
| | - Shingraf Zaib
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad 38000, Pakistan
| | - Fareeha Anwar
- Riphah Institute of Pharmaceutical Sciences, Riphah International University, Lahore, Pakistan
| | - Muhammad Furqan Akhtar
- Riphah Institute of Pharmaceutical Sciences, Riphah International University, Lahore, Pakistan
| | - Liaqat Hussain
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad 38000, Pakistan
| | - Ammara Saleem
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad 38000, Pakistan
| | - Bashir Ahmad
- Hamza College of Pharmaceutical and Allied Health Sciences, Lahore, Pakistan
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10
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Ge Y, Baumann HM, Mobley DL. Absolute Binding Free Energy Calculations for Buried Water Molecules. J Chem Theory Comput 2022; 18:6482-6499. [PMID: 36197451 PMCID: PMC9873352 DOI: 10.1021/acs.jctc.2c00658] [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] [Indexed: 01/27/2023]
Abstract
Water often plays a key role in mediating protein-ligand interactions. Understanding contributions from active-site water molecules to binding thermodynamics of a ligand is important in predicting binding free energies for ligand optimization. In this work, we tested a non-equilibrium switching method for absolute binding free energy calculations on water molecules in binding sites of 13 systems. We discuss the lessons we learned about identified issues that affected our calculations and ways to address them. This work fits with our larger focus on how to do accurate ligand binding free energy calculations when water rearrangements are very slow, such as rearrangements due to ligand modification (as in relative free energy calculations) or ligand binding (as in absolute free energy calculations). The method studied in this work can potentially be used to account for limited water sampling via providing endpoint corrections to free energy calculations using our calculated binding free energy of water.
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Affiliation(s)
- Yunhui Ge
- Department of Pharmaceutical Sciences, University of California, Irvine, California92697, United States
| | - Hannah M Baumann
- Department of Pharmaceutical Sciences, University of California, Irvine, California92697, United States
| | - David L Mobley
- Department of Pharmaceutical Sciences, University of California, Irvine, California92697, United States
- Department of Chemistry, University of California, Irvine, California92697, United States
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11
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Jacobson KA, Gao ZG, Matricon P, Eddy MT, Carlsson J. Adenosine A 2A receptor antagonists: from caffeine to selective non-xanthines. Br J Pharmacol 2022; 179:3496-3511. [PMID: 32424811 PMCID: PMC9251831 DOI: 10.1111/bph.15103] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 04/30/2020] [Accepted: 05/03/2020] [Indexed: 12/12/2022] Open
Abstract
A long evolution of knowledge of the psychostimulant caffeine led in the 1960s to another purine natural product, adenosine and its A2A receptor. Adenosine is a short-lived autocrine/paracrine mediator that acts pharmacologically at four different adenosine receptors in a manner opposite to the pan-antagonist caffeine and serves as an endogenous allostatic regulator. Although detrimental in the developing brain, caffeine appears to be cerebroprotective in aging. Moderate caffeine consumption in adults, except in pregnancy, may also provide benefit in pain, diabetes, and kidney and liver disorders. Inhibition of A2A receptors is one of caffeine's principal effects and we now understand this interaction at the atomic level. The A2A receptor has become a prototypical example of utilizing high-resolution structures of GPCRs for the rational design of chemically diverse drug molecules. The previous focus on discovery of selective A2A receptor antagonists for neurodegenerative diseases has expanded to include immunotherapy for cancer, and clinical trials have ensued. LINKED ARTICLES: This article is part of a themed issue on Structure Guided Pharmacology of Membrane Proteins (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.14/issuetoc.
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Affiliation(s)
- Kenneth A. Jacobson
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Zhan-Guo Gao
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Pierre Matricon
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Matthew T. Eddy
- Department of Chemistry, University of Florida, Gainesville, FL, USA
| | - Jens Carlsson
- Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
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12
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Ge Y, Wych DC, Samways ML, Wall ME, Essex JW, Mobley DL. Enhancing Sampling of Water Rehydration on Ligand Binding: A Comparison of Techniques. J Chem Theory Comput 2022; 18:1359-1381. [PMID: 35148093 PMCID: PMC9241631 DOI: 10.1021/acs.jctc.1c00590] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Water often plays a key role in protein structure, molecular recognition, and mediating protein-ligand interactions. Thus, free energy calculations must adequately sample water motions, which often proves challenging in typical MD simulation time scales. Thus, the accuracy of methods relying on MD simulations ends up limited by slow water sampling. Particularly, as a ligand is removed or modified, bulk water may not have time to fill or rearrange in the binding site. In this work, we focus on several molecular dynamics (MD) simulation-based methods attempting to help rehydrate buried water sites: BLUES, using nonequilibrium candidate Monte Carlo (NCMC); grand, using grand canonical Monte Carlo (GCMC); and normal MD. We assess the accuracy and efficiency of these methods in rehydrating target water sites. We selected a range of systems with varying numbers of waters in the binding site, as well as those where water occupancy is coupled to the identity or binding mode of the ligand. We analyzed the rehydration of buried water sites in binding pockets using both clustering of trajectories and direct analysis of electron density maps. Our results suggest both BLUES and grand enhance water sampling relative to normal MD and grand is more robust than BLUES, but also that water sampling remains a major challenge for all of the methods tested. The lessons we learned for these methods and systems are discussed.
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Affiliation(s)
- Yunhui Ge
- Department of Pharmaceutical Sciences, University of California, Irvine, California 92697, United States
| | - David C Wych
- Department of Pharmaceutical Sciences, University of California, Irvine, California 92697, United States
- Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Marley L Samways
- School of Chemistry, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Michael E Wall
- Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States
| | - Jonathan W Essex
- School of Chemistry, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - David L Mobley
- Department of Pharmaceutical Sciences, University of California, Irvine, California 92697, United States
- Department of Chemistry, University of California, Irvine, California 92697, United States
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13
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Potterton A, Heifetz A, Townsend-Nicholson A. Predicting Residence Time of GPCR Ligands with Machine Learning. Methods Mol Biol 2022; 2390:191-205. [PMID: 34731470 DOI: 10.1007/978-1-0716-1787-8_8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Drug-target residence time, the duration of binding at a given protein target, has been shown in some protein families to be more significant for conferring efficacy than binding affinity. To carry out efficient optimization of residence time in drug discovery, machine learning models that can predict that value need to be developed. One of the main challenges with predicting residence time is the paucity of data. This chapter outlines all of the currently available ligand kinetic data, providing a repository that contains the largest publicly available source of GPCR-ligand kinetic data to date. To help decipher the features of kinetic data that might be beneficial to include in computational models for the prediction of residence time, the experimental evidence for properties that influence residence time are summarized. Finally, two different workflows for predicting residence time with machine learning are outlined. The first is a single-target model trained on ligand features; the second is a multi-target model trained on features generated from molecular dynamics simulations.
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Affiliation(s)
- Andrew Potterton
- Structural and Molecular Biology, University College London, London, UK
- Evotec (U.K.) Ltd., Abingdon, Oxfordshire, UK
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14
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Wang P, Gao X, Zhang K, Pei Q, Xu X, Yan F, Dong J, Jing C. Exploring the binding mechanism of positive allosteric modulators in human metabotropic glutamate receptor 2 using molecular dynamics simulations. Phys Chem Chem Phys 2021; 23:24125-24139. [PMID: 34596645 DOI: 10.1039/d1cp02157e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Positive allosteric modulators (PAMs) of human metabotropic glutamate receptor 2 (hmGlu2) are well-known in the treatment of psychiatric disorders for their higher selectivity and lower tolerance risk. A variety of PAMs have been reported over the last decade and two compounds were in Phase II clinical trials for schizophrenia and anxiety. These trials were discontinued on account of the unsatisfactory therapeutic efficacy, but PAMs were explored as novel treatments for addiction and epilepsy. Thus, it is still important to explore novel hmGlu2 PAMs in the near future. Nowadays, the challenges in optimizing drug potency and improving scaffold diversity for PAMs are the noncomprehensive character analyses of multiple scaffolds; the exploration of the binding modes of PAMs in the allosteric binding site have been proposed to reduce this difficulty. However, there has been no comprehensive research about the binding profiles of PAMs in the hmGlu2 receptor. To address this issue, this work explores the binding characters of eight PAMs representing five chemical series by multiple computational methods. As a result, the shared binding modes of the eight studied PAMs interacting with 15 residues in the allosteric binding site were defined. In addition, the reduced hydrophobicity with low electronegativity of R1, increased hydrophobicity with low negative electron density of R2 and the electronegativity of the linker were identified as indicators that regulate the affinity of PAMs. This finding agrees well with the physicochemical properties of reported multiple series PAMs. This comprehensive work sheds additional light on the binding mechanism and physicochemical regularity underlining PAMs affinity and could be further utilized as a structural and energetic blueprint for discovering and assessing novel PAMs for hmGlu2.
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Affiliation(s)
- Panpan Wang
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Xiaonan Gao
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Ke Zhang
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Qinglan Pei
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Xiaobo Xu
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Fengmei Yan
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Jianghong Dong
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
| | - Chenxi Jing
- College of Chemistry and Pharmaceutical Engineering, Huanghuai University, Zhumadian 463000, China.
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15
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Abstract
Molecular docking is one of the most widely used computational tools in structure-based drug design and is critically dependent on accuracy and robustness of the scoring function. In this work, we introduce a new scoring function Lin_F9, which is a linear combination of nine empirical terms, including a unified metal bond term to specifically describe metal-ligand interactions. Parameters in Lin_F9 are obtained with a multistage fitting protocol using explicit water-included structures. For the CASF-2016 benchmark test set, Lin_F9 achieves the top scoring power among all 34 classical scoring functions for both original crystal poses and locally optimized poses with Pearson correlation coefficients (R) of 0.680 and 0.687, respectively. Meanwhile, in comparison with Vina, Lin_F9 achieves consistently better scoring power and ranking power with various types of protein-ligand complex structures that mimic real docking applications, including end-to-end flexible docking for the CASF-2016 benchmark test set using a single or an ensemble of protein receptor structures, as well as for D3R Grand Challenge (GC4) test sets. Lin_F9 has been implemented in a fork of Smina as an optional built-in scoring function that can be used for docking applications as well as for further improvement of scoring functions and docking protocols. Lin_F9 is accessible through https://yzhang.hpc.nyu.edu/Lin_F9/.
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Affiliation(s)
- Chao Yang
- Department of Chemistry, New York University, New York, New York 10003, United States
| | - Yingkai Zhang
- Department of Chemistry, New York University, New York, New York 10003, United States
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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16
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Deganutti G, Atanasio S, Rujan RM, Sexton PM, Wootten D, Reynolds CA. Exploring Ligand Binding to Calcitonin Gene-Related Peptide Receptors. Front Mol Biosci 2021; 8:720561. [PMID: 34513925 PMCID: PMC8427520 DOI: 10.3389/fmolb.2021.720561] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 08/13/2021] [Indexed: 01/31/2023] Open
Abstract
Class B1 G protein-coupled receptors (GPCRs) are important targets for many diseases, including cancer, diabetes, and heart disease. All the approved drugs for this receptor family are peptides that mimic the endogenous activating hormones. An understanding of how agonists bind and activate class B1 GPCRs is fundamental for the development of therapeutic small molecules. We combined supervised molecular dynamics (SuMD) and classic molecular dynamics (cMD) simulations to study the binding of the calcitonin gene-related peptide (CGRP) to the CGRP receptor (CGRPR). We also evaluated the association and dissociation of the antagonist telcagepant from the extracellular domain (ECD) of CGRPR and the water network perturbation upon binding. This study, which represents the first example of dynamic docking of a class B1 GPCR peptide, delivers insights on several aspects of ligand binding to CGRPR, expanding understanding of the role of the ECD and the receptor-activity modifying protein 1 (RAMP1) on agonist selectivity.
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Affiliation(s)
- Giuseppe Deganutti
- Centre for Sport, Exercise and Life Sciences, Coventry University, Coventry, United Kingdom
| | - Silvia Atanasio
- School of Life Sciences, University of Essex, Colchester, United Kingdom
| | - Roxana-Maria Rujan
- Centre for Sport, Exercise and Life Sciences, Coventry University, Coventry, United Kingdom
| | - Patrick M. Sexton
- Drug Discovery Biology Theme, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia
- ARC Centre for Cryo-Electron Microscopy of Membrane Proteins, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia
| | - Denise Wootten
- Drug Discovery Biology Theme, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia
- ARC Centre for Cryo-Electron Microscopy of Membrane Proteins, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia
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17
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Samways ML, Taylor RD, Bruce Macdonald HE, Essex JW. Water molecules at protein-drug interfaces: computational prediction and analysis methods. Chem Soc Rev 2021; 50:9104-9120. [PMID: 34184009 DOI: 10.1039/d0cs00151a] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The fundamental importance of water molecules at drug-protein interfaces is now widely recognised and a significant feature in structure-based drug design. Experimental methods for analysing the role of water in drug binding have many challenges, including the accurate location of bound water molecules in crystal structures, and problems in resolving specific water contributions to binding thermodynamics. Computational analyses of binding site water molecules provide an alternative, and in principle complete, structural and thermodynamic picture, and their use is now commonplace in the pharmaceutical industry. In this review, we describe the computational methodologies that are available and discuss their strengths and weaknesses. Additionally, we provide a critical analysis of the experimental data used to validate the methods, regarding the type and quality of experimental structural data. We also discuss some of the fundamental difficulties of each method and suggest directions for future study.
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Affiliation(s)
- Marley L Samways
- School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, UK.
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18
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Mancino V, Ceccarelli G, Carotti A, Goracci L, Sardella R, Passeri D, Pellicciari R, Gioiello A. Synthesis and biological activity of cyclopropyl Δ7-dafachronic acids as DAF-12 receptor ligands. Org Biomol Chem 2021; 19:5403-5412. [PMID: 34056641 DOI: 10.1039/d1ob00912e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The four cyclopropyl stereoisomers of Δ7-dafachronic acids were prepared from the bile acid hyodeoxycholic acid and employed as chemical tools to exploit the importance of the orientation and spatial disposition of the carboxyl tail and the C25-methyl group for the binding at the DAF-12 receptor. The synthesis route was based on (a) Walden inversion and stereoselective PtO2-hydrogenation to convert the L-shaped 5β-cholanoid scaffold into the planar 5α-sterol intermediate; (b) two-carbon homologation of the side chain by Wittig and cyclopropanation reaction; and (c) formation of the 3-keto group and Δ7 double bond. The synthesized isomers were isolated and tested for their activity as DAF-12 ligands by AlphaScreen assays. Results showed a significant loss of potency and efficacy for all the four stereoisomers when compared to the parent endogenous ligand. Computational analysis has evidenced the configurational and conformational arrangement of both the carboxylic and the C25-methyl group of dafachronic acids as key structural determinants for DAF-12 binding and activation.
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Affiliation(s)
- Valentina Mancino
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123, Perugia, Italy. and TES Pharma S.r.l., Corso Vannucci 47, 06121, Perugia, Italy
| | - Giada Ceccarelli
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123, Perugia, Italy.
| | - Andrea Carotti
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123, Perugia, Italy.
| | - Laura Goracci
- Department of Chemistry, Biology and Biotechnology, University of Perugia, Via dell'Elce di Sotto 8, 06123, Perugia, Italy
| | - Roccaldo Sardella
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123, Perugia, Italy.
| | | | | | - Antimo Gioiello
- Department of Pharmaceutical Sciences, University of Perugia, Via del Liceo 1, 06123, Perugia, Italy.
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19
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Majellaro M, Jespers W, Crespo A, Núñez MJ, Novio S, Azuaje J, Prieto-Díaz R, Gioé C, Alispahic B, Brea J, Loza MI, Freire-Garabal M, Garcia-Santiago C, Rodríguez-García C, García-Mera X, Caamaño O, Fernandez-Masaguer C, Sardina JF, Stefanachi A, El Maatougui A, Mallo-Abreu A, Åqvist J, Gutiérrez-de-Terán H, Sotelo E. 3,4-Dihydropyrimidin-2(1 H)-ones as Antagonists of the Human A 2B Adenosine Receptor: Optimization, Structure-Activity Relationship Studies, and Enantiospecific Recognition. J Med Chem 2020; 64:458-480. [PMID: 33372800 DOI: 10.1021/acs.jmedchem.0c01431] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
We present and thoroughly characterize a large collection of 3,4-dihydropyrimidin-2(1H)-ones as A2BAR antagonists, an emerging strategy in cancer (immuno) therapy. Most compounds selectively bind A2BAR, with a number of potent and selective antagonists further confirmed by functional cyclic adenosine monophosphate experiments. The series was analyzed with one of the most exhaustive free energy perturbation studies on a GPCR, obtaining an accurate model of the structure-activity relationship of this chemotype. The stereospecific binding modeled for this scaffold was confirmed by resolving the two most potent ligands [(±)-47, and (±)-38 Ki = 10.20 and 23.6 nM, respectively] into their two enantiomers, isolating the affinity on the corresponding (S)-eutomers (Ki = 6.30 and 11.10 nM, respectively). The assessment of the effect in representative cytochromes (CYP3A4 and CYP2D6) demonstrated insignificant inhibitory activity, while in vitro experiments in three prostate cancer cells demonstrated that this pair of compounds exhibits a pronounced antimetastatic effect.
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Affiliation(s)
- María Majellaro
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Willem Jespers
- Department of Cell and Molecular Biology, Uppsala University, SE-75124 Uppsala, Sweden
| | - Abel Crespo
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - María J Núñez
- SNL, Departamento de Farmacología, Facultade de Medicina, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Silvia Novio
- SNL, Departamento de Farmacología, Facultade de Medicina, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Jhonny Azuaje
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Rubén Prieto-Díaz
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Claudia Gioé
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Belma Alispahic
- Department of Cell and Molecular Biology, Uppsala University, SE-75124 Uppsala, Sweden
| | - José Brea
- Centro Singular de Investigación en Medicina Molecular y Enfermedades Crónicas (CIMUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - María I Loza
- Centro Singular de Investigación en Medicina Molecular y Enfermedades Crónicas (CIMUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Manuel Freire-Garabal
- SNL, Departamento de Farmacología, Facultade de Medicina, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Carlota Garcia-Santiago
- SNL, Departamento de Farmacología, Facultade de Medicina, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Carlos Rodríguez-García
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Xerardo García-Mera
- Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Olga Caamaño
- Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Christian Fernandez-Masaguer
- Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Javier F Sardina
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Angela Stefanachi
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari ALDO MORO, via Orabona 4, 70125 Bari, Italy
| | - Abdelaziz El Maatougui
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Ana Mallo-Abreu
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Johan Åqvist
- Department of Cell and Molecular Biology, Uppsala University, SE-75124 Uppsala, Sweden
| | | | - Eddy Sotelo
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain.,Departamento de Química Orgánica, Facultade de Farmacia, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
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20
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Jespers W, Verdon G, Azuaje J, Majellaro M, Keränen H, García‐Mera X, Congreve M, Deflorian F, de Graaf C, Zhukov A, Doré AS, Mason JS, Åqvist J, Cooke RM, Sotelo E, Gutiérrez‐de‐Terán H. X-Ray Crystallography and Free Energy Calculations Reveal the Binding Mechanism of A 2A Adenosine Receptor Antagonists. Angew Chem Int Ed Engl 2020; 59:16536-16543. [PMID: 32542862 PMCID: PMC7540567 DOI: 10.1002/anie.202003788] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 05/18/2020] [Indexed: 01/04/2023]
Abstract
We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X-ray crystallography to reveal the binding mode of an antagonist series to the A2A adenosine receptor (AR). Eight A2A AR binding site mutations from biophysical mapping experiments were initially analyzed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A2A AR were experimentally determined and investigated through a cycle of ligand-FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X-ray crystallography of the A2A AR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A2A AR, an emerging target in immuno-oncology.
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Affiliation(s)
- Willem Jespers
- Department of Cell and Molecular BiologyUppsala University, BMC, Biomedical CenterBox 596UppsalaSweden
| | - Grégory Verdon
- Sosei HeptaresSteinmetz Granta Park, Great AbingtonCambridgeCB21 6DGUK
| | - Jhonny Azuaje
- Departament of Organic ChemistryFaculty of FarmacyUniversidade de Santiago de CompostelaSpain
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS)Universidade de Santiago de CompostelaSpain
| | - Maria Majellaro
- Departament of Organic ChemistryFaculty of FarmacyUniversidade de Santiago de CompostelaSpain
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS)Universidade de Santiago de CompostelaSpain
| | - Henrik Keränen
- Department of Cell and Molecular BiologyUppsala University, BMC, Biomedical CenterBox 596UppsalaSweden
- Present address: H. Lundbeck A/SOttiliavej 92500ValbyDenmark
| | - Xerardo García‐Mera
- Departament of Organic ChemistryFaculty of FarmacyUniversidade de Santiago de CompostelaSpain
| | - Miles Congreve
- Sosei HeptaresSteinmetz Granta Park, Great AbingtonCambridgeCB21 6DGUK
| | | | - Chris de Graaf
- Sosei HeptaresSteinmetz Granta Park, Great AbingtonCambridgeCB21 6DGUK
| | - Andrei Zhukov
- Sosei HeptaresSteinmetz Granta Park, Great AbingtonCambridgeCB21 6DGUK
| | - Andrew S. Doré
- Sosei HeptaresSteinmetz Granta Park, Great AbingtonCambridgeCB21 6DGUK
| | - Jonathan S. Mason
- Sosei HeptaresSteinmetz Granta Park, Great AbingtonCambridgeCB21 6DGUK
| | - Johan Åqvist
- Department of Cell and Molecular BiologyUppsala University, BMC, Biomedical CenterBox 596UppsalaSweden
| | - Robert M. Cooke
- Sosei HeptaresSteinmetz Granta Park, Great AbingtonCambridgeCB21 6DGUK
| | - Eddy Sotelo
- Departament of Organic ChemistryFaculty of FarmacyUniversidade de Santiago de CompostelaSpain
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS)Universidade de Santiago de CompostelaSpain
| | - Hugo Gutiérrez‐de‐Terán
- Department of Cell and Molecular BiologyUppsala University, BMC, Biomedical CenterBox 596UppsalaSweden
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21
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Jespers W, Verdon G, Azuaje J, Majellaro M, Keränen H, García‐Mera X, Congreve M, Deflorian F, Graaf C, Zhukov A, Doré AS, Mason JS, Åqvist J, Cooke RM, Sotelo E, Gutiérrez‐de‐Terán H. X‐Ray Crystallography and Free Energy Calculations Reveal the Binding Mechanism of A
2A
Adenosine Receptor Antagonists. Angew Chem Int Ed Engl 2020. [DOI: 10.1002/ange.202003788] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Willem Jespers
- Department of Cell and Molecular BiologyUppsala University, BMC, Biomedical Center Box 596 Uppsala Sweden
| | - Grégory Verdon
- Sosei Heptares Steinmetz Granta Park, Great Abington Cambridge CB21 6DG UK
| | - Jhonny Azuaje
- Departament of Organic ChemistryFaculty of FarmacyUniversidade de Santiago de Compostela Spain
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS)Universidade de Santiago de Compostela Spain
| | - Maria Majellaro
- Departament of Organic ChemistryFaculty of FarmacyUniversidade de Santiago de Compostela Spain
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS)Universidade de Santiago de Compostela Spain
| | - Henrik Keränen
- Department of Cell and Molecular BiologyUppsala University, BMC, Biomedical Center Box 596 Uppsala Sweden
- Present address: H. Lundbeck A/S Ottiliavej 9 2500 Valby Denmark
| | - Xerardo García‐Mera
- Departament of Organic ChemistryFaculty of FarmacyUniversidade de Santiago de Compostela Spain
| | - Miles Congreve
- Sosei Heptares Steinmetz Granta Park, Great Abington Cambridge CB21 6DG UK
| | | | - Chris Graaf
- Sosei Heptares Steinmetz Granta Park, Great Abington Cambridge CB21 6DG UK
| | - Andrei Zhukov
- Sosei Heptares Steinmetz Granta Park, Great Abington Cambridge CB21 6DG UK
| | - Andrew S. Doré
- Sosei Heptares Steinmetz Granta Park, Great Abington Cambridge CB21 6DG UK
| | - Jonathan S. Mason
- Sosei Heptares Steinmetz Granta Park, Great Abington Cambridge CB21 6DG UK
| | - Johan Åqvist
- Department of Cell and Molecular BiologyUppsala University, BMC, Biomedical Center Box 596 Uppsala Sweden
| | - Robert M. Cooke
- Sosei Heptares Steinmetz Granta Park, Great Abington Cambridge CB21 6DG UK
| | - Eddy Sotelo
- Departament of Organic ChemistryFaculty of FarmacyUniversidade de Santiago de Compostela Spain
- Centro Singular de Investigación en Química Biolóxica y Materiais Moleculares (CIQUS)Universidade de Santiago de Compostela Spain
| | - Hugo Gutiérrez‐de‐Terán
- Department of Cell and Molecular BiologyUppsala University, BMC, Biomedical Center Box 596 Uppsala Sweden
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22
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Deflorian F, Perez-Benito L, Lenselink EB, Congreve M, van Vlijmen HWT, Mason JS, Graaf CD, Tresadern G. Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation. J Chem Inf Model 2020; 60:5563-5579. [PMID: 32539374 DOI: 10.1021/acs.jcim.0c00449] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
The computational prediction of relative binding free energies is a crucial goal for drug discovery, and G protein-coupled receptors (GPCRs) are arguably the most important drug target class. However, they present increased complexity to model compared to soluble globular proteins. Despite breakthroughs, experimental X-ray crystal and cryo-EM structures are challenging to attain, meaning computational models of the receptor and ligand binding mode are sometimes necessary. This leads to uncertainty in understanding ligand-protein binding induced changes such as, water positioning and displacement, side chain positioning, hydrogen bond networks, and the overall structure of the hydration shell around the ligand and protein. In other words, the very elements that define structure activity relationships (SARs) and are crucial for accurate binding free energy calculations are typically more uncertain for GPCRs. In this work we use free energy perturbation (FEP) to predict the relative binding free energies for ligands of two different GPCRs. We pinpoint the key aspects for success such as the important role of key water molecules, amino acid ionization states, and the benefit of equilibration with specific ligands. Initial calculations following typical FEP setup and execution protocols delivered no correlation with experiment, but we show how results are improved in a logical and systematic way. This approach gave, in the best cases, a coefficient of determination (R2) compared with experiment in the range of 0.6-0.9 and mean unsigned errors compared to experiment of 0.6-0.7 kcal/mol. We anticipate that our findings will be applicable to other difficult-to-model protein ligand data sets and be of wide interest for the community to continue improving FE binding energy predictions.
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Affiliation(s)
- Francesca Deflorian
- Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge CB21 6DG United Kingdom
| | - Laura Perez-Benito
- Computational Chemistry, Janssen Research & Development, Janssen Pharmaceutica N. V., Turnhoutseweg 30, B-2340 Beerse, Belgium
| | - Eelke B Lenselink
- Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2300, RA, The Netherlands
| | - Miles Congreve
- Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge CB21 6DG United Kingdom
| | - Herman W T van Vlijmen
- Computational Chemistry, Janssen Research & Development, Janssen Pharmaceutica N. V., Turnhoutseweg 30, B-2340 Beerse, Belgium
| | - Jonathan S Mason
- Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge CB21 6DG United Kingdom
| | - Chris de Graaf
- Sosei Heptares, Steinmetz Building, Granta Park, Great Abington, Cambridge CB21 6DG United Kingdom
| | - Gary Tresadern
- Computational Chemistry, Janssen Research & Development, Janssen Pharmaceutica N. V., Turnhoutseweg 30, B-2340 Beerse, Belgium
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23
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Salmaso V, Jacobson KA. In Silico Drug Design for Purinergic GPCRs: Overview on Molecular Dynamics Applied to Adenosine and P2Y Receptors. Biomolecules 2020; 10:E812. [PMID: 32466404 PMCID: PMC7356333 DOI: 10.3390/biom10060812] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 05/21/2020] [Accepted: 05/22/2020] [Indexed: 12/14/2022] Open
Abstract
Molecular modeling has contributed to drug discovery for purinergic GPCRs, including adenosine receptors (ARs) and P2Y receptors (P2YRs). Experimental structures and homology modeling have proven to be useful in understanding and predicting structure activity relationships (SAR) of agonists and antagonists. This review provides an excursus on molecular dynamics (MD) simulations applied to ARs and P2YRs. The binding modes of newly synthesized A1AR- and A3AR-selective nucleoside derivatives, potentially of use against depression and inflammation, respectively, have been predicted to recapitulate their SAR and the species dependence of A3AR affinity. P2Y12R and P2Y1R crystallographic structures, respectively, have provided a detailed understanding of the recognition of anti-inflammatory P2Y14R antagonists and a large group of allosteric and orthosteric antagonists of P2Y1R, an antithrombotic and neuroprotective target. MD of A2AAR (an anticancer and neuroprotective target), A3AR, and P2Y1R has identified microswitches that are putatively involved in receptor activation. The approach pathways of different ligands toward A2AAR and P2Y1R binding sites have also been explored. A1AR, A2AAR, and A3AR were utilizes to study allosteric phenomena, but locating the binding site of structurally diverse allosteric modulators, such as an A3AR enhancer LUF6000, is challenging. Ligand residence time, a predictor of in vivo efficacy, and the structural role of water were investigated through A2AAR MD simulations. Thus, new MD and other modeling algorithms have contributed to purinergic GPCR drug discovery.
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Affiliation(s)
| | - Kenneth A. Jacobson
- Molecular Recognition Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA;
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24
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New Insights into Key Determinants for Adenosine 1 Receptor Antagonists Selectivity Using Supervised Molecular Dynamics Simulations. Biomolecules 2020; 10:biom10050732. [PMID: 32392873 PMCID: PMC7278174 DOI: 10.3390/biom10050732] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 04/27/2020] [Accepted: 04/28/2020] [Indexed: 12/13/2022] Open
Abstract
Adenosine receptors (ARs), like many otherGprotein-coupledreceptors (GPCRs), are targets of primary interest indrug design. However, one of the main limits for the development of drugs for this class of GPCRs is the complex selectivity profile usually displayed by ligands. Numerous efforts have been madefor clarifying the selectivity of ARs, leading to the development of many ligand-based models. The structure of the AR subtype A1 (A1AR) has been recently solved, providing important structural insights. In the present work, we rationalized the selectivity profile of two selective A1AR and A2AAR antagonists, investigating their recognition trajectories obtained by Supervised Molecular Dynamics from an unbound state and monitoring the role of the water molecules in the binding site.
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25
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Sivakumar KC, Haixiao J, Naman CB, Sajeevan TP. Prospects of multitarget drug designing strategies by linking molecular docking and molecular dynamics to explore the protein-ligand recognition process. Drug Dev Res 2020; 81:685-699. [PMID: 32329098 DOI: 10.1002/ddr.21673] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 03/24/2020] [Accepted: 04/06/2020] [Indexed: 12/14/2022]
Abstract
The designing of drugs that can simultaneously affect different protein targets is one novel and promising way to treat complex diseases. Multitarget drugs act on multiple protein receptors each implicated in the same disease state, and may be considered to be more beneficial than conventional drug therapies. For example, these drugs can have improved therapeutic potency due to synergistic effects on multiple targets, as well as improved safety and resistance profiles due to the combined regulation of potential primary therapeutic targets and compensatory elements and lower dosage typically required. This review analyzes in-silico methods that facilitate multitarget drug design that facilitate the discovery and development of novel therapeutic agents. Here presented is a summary of the progress in structure-based drug discovery techniques that study the process of molecular recognition of targets and ligands, moving from static molecular docking to improved molecular dynamics approaches in multitarget drug design, and the advantages and limitations of each.
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Affiliation(s)
- Krishnankutty Chandrika Sivakumar
- National Centre for Aquatic Animal Health, Cochin University of Science and Technology, Kochi, India.,Bioinformatics Facility, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, India
| | - Jin Haixiao
- Li Dak Sum Marine Biopharmaceutical Research Center, Department of Marine Pharmacy, College of Food and Pharmaceutical Sciences, Ningbo University, Ningbo, China
| | - C Benjamin Naman
- Li Dak Sum Marine Biopharmaceutical Research Center, Department of Marine Pharmacy, College of Food and Pharmaceutical Sciences, Ningbo University, Ningbo, China.,Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA
| | - T P Sajeevan
- National Centre for Aquatic Animal Health, Cochin University of Science and Technology, Kochi, India
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26
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Bodnarchuk MS, Packer MJ, Haywood A. Utilizing Grand Canonical Monte Carlo Methods in Drug Discovery. ACS Med Chem Lett 2020; 11:77-82. [PMID: 31938467 DOI: 10.1021/acsmedchemlett.9b00499] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 12/11/2019] [Indexed: 12/17/2022] Open
Abstract
The concepts behind targeting waters for potency and selectivity gains have been well documented and explored, although maximizing such potential gains can prove to be challenging. This problem is exacerbated in cases where there are multiple interacting waters, wherein perturbation of one water can affect the free energy landscape of the remaining waters. Knowing the right modification a priori is challenging, and computational approaches are ideally suited to help answer the key question of which substitution is best to try. Here, we use Grand Canonical Monte Carlo and the recent Grand Canonical Alchemical Perturbation methods to both understand and predict the effect of ligand-mediated water displacement when more than one water molecule is involved, as well as to understand how exploiting water networks can help govern selectivity.
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Affiliation(s)
- Michael S. Bodnarchuk
- Computational Chemistry, R&D Oncology, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Martin J. Packer
- Computational Chemistry, R&D Oncology, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Alexe Haywood
- Computational Chemistry, R&D Oncology, AstraZeneca, Cambridge CB4 0WG, United Kingdom
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27
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Hu X, Maffucci I, Contini A. Advances in the Treatment of Explicit Water Molecules in Docking and Binding Free Energy Calculations. Curr Med Chem 2020; 26:7598-7622. [DOI: 10.2174/0929867325666180514110824] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Revised: 02/26/2018] [Accepted: 04/18/2018] [Indexed: 12/30/2022]
Abstract
Background:
The inclusion of direct effects mediated by water during the ligandreceptor
recognition is a hot-topic of modern computational chemistry applied to drug discovery
and development. Docking or virtual screening with explicit hydration is still debatable,
despite the successful cases that have been presented in the last years. Indeed, how to select
the water molecules that will be included in the docking process or how the included waters
should be treated remain open questions.
Objective:
In this review, we will discuss some of the most recent methods that can be used in
computational drug discovery and drug development when the effect of a single water, or of a
small network of interacting waters, needs to be explicitly considered.
Results:
Here, we analyse the software to aid the selection, or to predict the position, of water
molecules that are going to be explicitly considered in later docking studies. We also present
software and protocols able to efficiently treat flexible water molecules during docking, including
examples of applications. Finally, we discuss methods based on molecular dynamics
simulations that can be used to integrate docking studies or to reliably and efficiently compute
binding energies of ligands in presence of interfacial or bridging water molecules.
Conclusions:
Software applications aiding the design of new drugs that exploit water molecules,
either as displaceable residues or as bridges to the receptor, are constantly being developed.
Although further validation is needed, workflows that explicitly consider water will
probably become a standard for computational drug discovery soon.
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Affiliation(s)
- Xiao Hu
- Università degli Studi di Milano, Dipartimento di Scienze Farmaceutiche, Sezione di Chimica Generale e Organica “A. Marchesini”, Via Venezian, 21 20133 Milano, Italy
| | - Irene Maffucci
- Pasteur, Département de Chimie, École Normale Supérieure, PSL Research University, Sorbonne Universités, UPMC Univ. Paris 06, CNRS, 75005 Paris, France
| | - Alessandro Contini
- Università degli Studi di Milano, Dipartimento di Scienze Farmaceutiche, Sezione di Chimica Generale e Organica “A. Marchesini”, Via Venezian, 21 20133 Milano, Italy
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28
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Lu J, Hou X, Wang C, Zhang Y. Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions. J Chem Inf Model 2019; 59:4540-4549. [PMID: 31638801 PMCID: PMC6878146 DOI: 10.1021/acs.jcim.9b00645] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Structure-based drug design is critically dependent on accuracy of molecular docking scoring functions, and there is of significant interest to advance scoring functions with machine learning approaches. In this work, by judiciously expanding the training set, exploring new features related to explicit mediating water molecules as well as ligand conformation stability, and applying extreme gradient boosting (XGBoost) with Δ-Vina parametrization, we have improved robustness and applicability of machine-learning scoring functions. The new scoring function ΔvinaXGB can not only perform consistently among the top compared to classical scoring functions for the CASF-2016 benchmark but also achieves significantly better prediction accuracy in different types of structures that mimic real docking applications.
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Affiliation(s)
- Jianing Lu
- Department of Chemistry, New York University, New York, New York 10003, United States
| | - Xuben Hou
- Department of Chemistry, New York University, New York, New York 10003, United States
- Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Science, Shandong University, Jinan, Shandong 250012, China
| | - Cheng Wang
- Department of Chemistry, New York University, New York, New York 10003, United States
| | - Yingkai Zhang
- Department of Chemistry, New York University, New York, New York 10003, United States
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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29
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Bruno A, Costantino G, Sartori L, Radi M. The In Silico Drug Discovery Toolbox: Applications in Lead Discovery and Optimization. Curr Med Chem 2019; 26:3838-3873. [PMID: 29110597 DOI: 10.2174/0929867324666171107101035] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Revised: 09/27/2017] [Accepted: 09/28/2017] [Indexed: 01/04/2023]
Abstract
BACKGROUND Discovery and development of a new drug is a long lasting and expensive journey that takes around 20 years from starting idea to approval and marketing of new medication. Despite R&D expenditures have been constantly increasing in the last few years, the number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. To cope with this issue, a number of in silico techniques are currently being used for an early stage evaluation/prediction of potential safety issues, allowing to increase the drug-discovery success rate and reduce costs associated with the development of a new drug. METHODS In the present review, we will analyse the early steps of the drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan. RESULTS A comprehensive list of widely used in silico tools, databases, and public initiatives that can be effectively implemented and used in the drug discovery pipeline has been provided. A few examples of how these tools can be problem-solving and how they may increase the success rate of a drug discovery and development program have been also provided. Finally, selected examples where the application of in silico tools had effectively contributed to the development of marketed drugs or clinical candidates will be given. CONCLUSION The in silico toolbox finds great application in every step of early drug discovery: (i) target identification and validation; (ii) hit identification; (iii) hit-to-lead; and (iv) lead optimization. Each of these steps has been described in details, providing a useful overview on the role played by in silico tools in the decision-making process to speed-up the discovery of new drugs.
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Affiliation(s)
- Agostino Bruno
- Experimental Therapeutics Unit, IFOM - The FIRC Institute for Molecular Oncology Foundation, Via Adamello 16 - 20139 Milano, Italy
| | - Gabriele Costantino
- Dipartimento di Scienze degli Alimenti e del Farmaco, Universita degli Studi di Parma, Viale delle Scienze, 27/A, 43124 Parma, Italy
| | - Luca Sartori
- Experimental Therapeutics Unit, IFOM - The FIRC Institute for Molecular Oncology Foundation, Via Adamello 16 - 20139 Milano, Italy
| | - Marco Radi
- Dipartimento di Scienze degli Alimenti e del Farmaco, Universita degli Studi di Parma, Viale delle Scienze, 27/A, 43124 Parma, Italy
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30
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Lu Q, Qi LW, Liu J. Improving protein–ligand binding prediction by considering the bridging water molecules in Autodock. JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY 2019. [DOI: 10.1142/s0219633619500275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Water plays a significant role in determining the protein–ligand binding modes, especially when water molecules are involved in mediating protein–ligand interactions, and these important water molecules are receiving more and more attention in recent years. Considering the effects of water molecules has gradually become a routine process for accurate description of the protein–ligand interactions. As a free docking program, Autodock has been most widely used in predicting the protein–ligand binding modes. However, whether the inclusion of water molecules in Autodock would improve its docking performance has not been systematically investigated. Here, we incorporate important bridging water molecules into Autodock program, and systematically investigate the effectiveness of these water molecules in protein–ligand docking. This approach was evaluated using 18 structurally diverse protein–ligand complexes, in which several water molecules bridge the protein–ligand interactions. Different treatment of water molecules were tested by using the fixed and rotatable water molecules, and a considerable improvement in successful docking simulations was found when including these water molecules. This study illustrates the necessity of inclusion of water molecules in Autodock docking, and emphasizes the importance of a proper treatment of water molecules in protein–ligand binding predictions.
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Affiliation(s)
- Qiangna Lu
- State Key Laboratory of Natural Medicines, Department of Chinese Medicine, Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 210009, P. R. China
| | - Lian-Wen Qi
- State Key Laboratory of Natural Medicines, Department of Chinese Medicine, Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 210009, P. R. China
| | - Jinfeng Liu
- State Key Laboratory of Natural Medicines, Department of Chinese Medicine, Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 210009, P. R. China
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31
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Free-Energy Calculations for Bioisosteric Modifications of A 3 Adenosine Receptor Antagonists. Int J Mol Sci 2019; 20:ijms20143499. [PMID: 31315296 PMCID: PMC6679372 DOI: 10.3390/ijms20143499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 07/12/2019] [Accepted: 07/14/2019] [Indexed: 11/16/2022] Open
Abstract
Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A3 adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.
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32
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Arimont M, Hoffmann C, de Graaf C, Leurs R. Chemokine Receptor Crystal Structures: What Can Be Learned from Them? Mol Pharmacol 2019; 96:765-777. [PMID: 31266800 DOI: 10.1124/mol.119.117168] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 06/21/2019] [Indexed: 12/18/2022] Open
Abstract
Chemokine receptors belong to the class A of G protein-coupled receptors (GPCRs) and are implicated in a wide variety of physiologic functions, mostly related to the homeostasis of the immune system. Chemokine receptors are also involved in multiple pathologic processes, including immune and autoimmune diseases, as well as cancer. Hence, several members of this GPCR subfamily are considered to be very relevant therapeutic targets. Since drug discovery efforts can be significantly reinforced by the availability of crystal structures, substantial efforts in the area of chemokine receptor structural biology could dramatically increase the outcome of drug discovery campaigns. This short review summarizes the available data on chemokine receptor crystal structures, discusses the numerous applications from chemokine receptor structures that can enhance the daily work of molecular pharmacologists, and describes the challenges and pitfalls to consider when relying on crystal structures for further research applications. SIGNIFICANCE STATEMENT: This short review summarizes the available data on chemokine receptor crystal structures, discusses the numerous applications from chemokine receptor structures that can enhance the daily work of molecular pharmacologists, and describes the challenges and pitfalls to consider when relying on crystal structures for further research applications.
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Affiliation(s)
- Marta Arimont
- Division of Medicinal Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (M.A., R.L.); Institute for Molecular Cell Biology, Centre for Molecular Biomedicine, University Hospital Jena, Friedrich Schiller University, Jena, Germany (C.H.); and Sosei Heptares, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Carsten Hoffmann
- Division of Medicinal Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (M.A., R.L.); Institute for Molecular Cell Biology, Centre for Molecular Biomedicine, University Hospital Jena, Friedrich Schiller University, Jena, Germany (C.H.); and Sosei Heptares, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Chris de Graaf
- Division of Medicinal Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (M.A., R.L.); Institute for Molecular Cell Biology, Centre for Molecular Biomedicine, University Hospital Jena, Friedrich Schiller University, Jena, Germany (C.H.); and Sosei Heptares, Great Abington, Cambridge, United Kingdom (C.d.G.)
| | - Rob Leurs
- Division of Medicinal Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (M.A., R.L.); Institute for Molecular Cell Biology, Centre for Molecular Biomedicine, University Hospital Jena, Friedrich Schiller University, Jena, Germany (C.H.); and Sosei Heptares, Great Abington, Cambridge, United Kingdom (C.d.G.)
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33
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Lesca E, Panneels V, Schertler GFX. The role of water molecules in phototransduction of retinal proteins and G protein-coupled receptors. Faraday Discuss 2019; 207:27-37. [PMID: 29410984 DOI: 10.1039/c7fd00207f] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
G protein coupled receptors (GPCRs) are a key family of membrane proteins in all eukaryotes and also very important drug targets for medical intervention. The extensively studied visual pigment rhodopsin is a prime example of a family A GPCR. Its chromophore ligand retinal is covalently linked to a lysine in helix seven forming a protonated Schiff base. Interestingly, this is the same situation in other-non-GPCR-retinal proteins, like the prototype light-driven microbial proton pump bacteriorhodopsin, albeit there is no (or only a very remote) phylogenetical link. Close to the retinal ligand, several water molecules help to organise a functionally important hydrogen bond network that undergoes significant changes during photo-activation. Such water-mediated networks are also critical for ligand binding of other GPCRs and they are becoming increasingly important in drug discovery. GPCRs also contain a partially conserved water mediated hydrogen bond network that stabilises the ground state of the receptor, and rearrangement of this network leads to the stabilization of the active state. Some water molecules have a specific role in this process to appropriately orient specific residues relative to the Schiff base, and to modulate the fine structure of the transmembrane bundle, particularly near the intracellular G protein binding site. While the atomic details of these mechanisms are still missing, the recent developments in free electron lasers (FELs) are enabling us to begin to observe the changes in waters and relevant side chains shortly after photo activation at an unprecedented level of spatial and temporal resolution.
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Affiliation(s)
- Elena Lesca
- Division of Biology and Chemistry, Laboratory of Biomolecular Research, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland.
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34
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Acúrcio RC, Scomparin A, Satchi‐Fainaro R, Florindo HF, Guedes RC. Computer‐aided drug design in new druggable targets for the next generation of immune‐oncology therapies. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2019. [DOI: 10.1002/wcms.1397] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Rita C. Acúrcio
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy Universidade de Lisboa Lisbon Portugal
| | - Anna Scomparin
- Department of Physiology and Pharmacology, Sackler Faculty of Medicine Tel Aviv University Tel Aviv Israel
| | - Ronit Satchi‐Fainaro
- Department of Physiology and Pharmacology, Sackler Faculty of Medicine Tel Aviv University Tel Aviv Israel
| | - Helena F. Florindo
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy Universidade de Lisboa Lisbon Portugal
| | - Rita C. Guedes
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy Universidade de Lisboa Lisbon Portugal
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35
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Magarkar A, Schnapp G, Apel AK, Seeliger D, Tautermann CS. Enhancing Drug Residence Time by Shielding of Intra-Protein Hydrogen Bonds: A Case Study on CCR2 Antagonists. ACS Med Chem Lett 2019; 10:324-328. [PMID: 30891134 DOI: 10.1021/acsmedchemlett.8b00590] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 02/07/2019] [Indexed: 12/15/2022] Open
Abstract
The target residence time (RT) for a given ligand is one of the important parameters that have to be optimized during drug design. It is well established that shielding the receptor-ligand hydrogen bond (H-bond) interactions from water has been one of the factors in increasing ligand RT. Building on this foundation, here we report that shielding an intra-protein H-bond, which confers rigidity to the binding pocket and which is not directly involved in drug-receptor interactions, can strongly influence RT for CCR2 antagonists. Based on our recently solved CCR2 structure with MK-0812 and molecular dynamics (MD) simulations, we show that the RT for this and structurally related ligands is directly dependent on the shielding of the Tyr120-Glu291 H-bond from the water. If solvated this H-bond is often broken, making the binding pocket flexible and leading to shorter RT.
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Affiliation(s)
- Aniket Magarkar
- Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Strasse 65, D-88397 Biberach a.d. Riss, Germany
| | - Gisela Schnapp
- Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Strasse 65, D-88397 Biberach a.d. Riss, Germany
| | - Anna-Katharina Apel
- Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Strasse 65, D-88397 Biberach a.d. Riss, Germany
| | - Daniel Seeliger
- Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Strasse 65, D-88397 Biberach a.d. Riss, Germany
| | - Christofer S. Tautermann
- Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorfer Strasse 65, D-88397 Biberach a.d. Riss, Germany
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36
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Peeking at G-protein-coupled receptors through the molecular dynamics keyhole. Future Med Chem 2019; 11:599-615. [DOI: 10.4155/fmc-2018-0393] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Molecular dynamics is a state of the art computational tool for the investigation of biophysics phenomenon at a molecular scale, as it enables the modeling of dynamic processes, such as conformational motions, molecular solvation and ligand binding. The recent advances in structural biology have led to a bloom in published G-protein-coupled receptor structures, representing a solid and valuable resource for molecular dynamics studies. During the last decade, indeed, a plethora of physiological and pharmacological facets of this membrane protein superfamily have been addressed by means of molecular dynamics simulations, including the activation mechanism, allosterism and, very recently, biased signaling. Here, we try to recapitulate some of the main contributions that molecular dynamics has recently produced in the field.
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37
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Nittinger E, Gibbons P, Eigenbrot C, Davies DR, Maurer B, Yu CL, Kiefer JR, Kuglstatter A, Murray J, Ortwine DF, Tang Y, Tsui V. Water molecules in protein–ligand interfaces. Evaluation of software tools and SAR comparison. J Comput Aided Mol Des 2019; 33:307-330. [DOI: 10.1007/s10822-019-00187-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 01/24/2019] [Indexed: 01/08/2023]
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38
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Abstract
G protein-coupled receptors (GPCRs) represent both the largest class of drug targets and the largest family of human membrane proteins. Recent three-dimensional structures have revealed the presence of many water molecules buried inside GPCRs, but the functional role of these water molecules has been unclear. Using extensive atomic-level computer simulations, we find that, although most of these waters are highly mobile, a few are stable. These stable water molecules mediate state-dependent and state-independent polar networks that are conserved across diverse GPCRs. These findings promise to help guide the rational design of GPCR-targeted drugs. G protein-coupled receptors (GPCRs) have evolved to recognize incredibly diverse extracellular ligands while sharing a common architecture and structurally conserved intracellular signaling partners. It remains unclear how binding of diverse ligands brings about GPCR activation, the common structural change that enables intracellular signaling. Here, we identify highly conserved networks of water-mediated interactions that play a central role in activation. Using atomic-level simulations of diverse GPCRs, we show that most of the water molecules in GPCR crystal structures are highly mobile. Several water molecules near the G protein-coupling interface, however, are stable. These water molecules form two kinds of polar networks that are conserved across diverse GPCRs: (i) a network that is maintained across the inactive and the active states and (ii) a network that rearranges upon activation. Comparative analysis of GPCR crystal structures independently confirms the striking conservation of water-mediated interaction networks. These conserved water-mediated interactions near the G protein-coupling region, along with diverse water-mediated interactions with extracellular ligands, have direct implications for structure-based drug design and GPCR engineering.
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39
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Bruce Macdonald HE, Cave-Ayland C, Ross GA, Essex JW. Ligand Binding Free Energies with Adaptive Water Networks: Two-Dimensional Grand Canonical Alchemical Perturbations. J Chem Theory Comput 2018; 14:6586-6597. [PMID: 30451501 PMCID: PMC6293443 DOI: 10.1021/acs.jctc.8b00614] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
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Computational methods
to calculate ligand binding affinities are
increasing in popularity, due to improvements in simulation algorithms,
computational resources, and easy-to-use software. However, issues
can arise in relative ligand binding free energy simulations if the
ligands considered have different active site water networks, as simulations
are typically performed with a predetermined number of water molecules
(fixed N ensembles) in preassigned locations. If an alchemical perturbation
is attempted where the change should result in a different active
site water network, the water molecules may not be able to adapt appropriately
within the time scales of the simulations—particularly if the
active site is occluded. By combining the grand canonical ensemble
(μVT) to sample active site water molecules, with conventional
alchemical free energy methods, the water network is able to dynamically
adapt to the changing ligand. We refer to this approach as grand canonical
alchemical perturbation (GCAP). In this work we demonstrate GCAP for
two systems; Scytalone Dehydratase (SD) and Adenosine A2A receptor. For both systems, GCAP is shown to perform
well at reproducing experimental binding affinities. Calculating the
relative binding affinities with a naïve, conventional
attempt to solvate the active site illustrates how poor results can
be if proper consideration of water molecules in occluded pockets
is neglected. GCAP results are shown to be consistent with time-consuming
double decoupling simulations. In addition, by obtaining the free
energy surface for ligand perturbations, as a function of both the
free energy coupling parameter and water chemical potential, it is
possible to directly deconvolute the binding energetics in terms of
protein–ligand direct interactions and protein binding site
hydration.
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Affiliation(s)
| | | | - Gregory A Ross
- Computational and Systems Biology Program, Sloan Kettering Institute , Memorial Sloan Kettering Cancer Center , New York, New York 10065 , United States
| | - Jonathan W Essex
- School of Chemistry , University of Southampton , Southampton , SO17 1BJ , U.K
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40
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Congreve M, Brown GA, Borodovsky A, Lamb ML. Targeting adenosine A2A receptor antagonism for treatment of cancer. Expert Opin Drug Discov 2018; 13:997-1003. [DOI: 10.1080/17460441.2018.1534825] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Miles Congreve
- Heptares Therapeutics Limited, Steinmetz Building, Cambridge, Granta Park, UK
| | - Giles A. Brown
- Heptares Therapeutics Limited, Steinmetz Building, Cambridge, Granta Park, UK
| | | | - Michelle L. Lamb
- Medicinal Chemistry, Oncology, IMED Biotech Unit, AstraZeneca, Boston, MA, USA
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41
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Salmaso V, Moro S. Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview. Front Pharmacol 2018; 9:923. [PMID: 30186166 PMCID: PMC6113859 DOI: 10.3389/fphar.2018.00923] [Citation(s) in RCA: 325] [Impact Index Per Article: 54.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 07/26/2018] [Indexed: 12/22/2022] Open
Abstract
Computational techniques have been applied in the drug discovery pipeline since the 1980s. Given the low computational resources of the time, the first molecular modeling strategies relied on a rigid view of the ligand-target binding process. During the years, the evolution of hardware technologies has gradually allowed simulating the dynamic nature of the binding event. In this work, we present an overview of the evolution of structure-based drug discovery techniques in the study of ligand-target recognition phenomenon, going from the static molecular docking toward enhanced molecular dynamics strategies.
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Affiliation(s)
- Veronica Salmaso
- Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy
| | - Stefano Moro
- Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy
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42
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Matter H, Güssregen S. Characterizing hydration sites in protein-ligand complexes towards the design of novel ligands. Bioorg Med Chem Lett 2018; 28:2343-2352. [PMID: 29880400 DOI: 10.1016/j.bmcl.2018.05.061] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 05/28/2018] [Accepted: 05/30/2018] [Indexed: 11/18/2022]
Abstract
Water is an essential part of protein binding sites and mediates interactions to ligands. Its displacement by ligand parts affects the free binding energy of resulting protein-ligand complexes. Therefore the characterization of solvation properties is important for design. Of particular interest is the propensity of localized water to be favorably displaced by a ligand. This review discusses two popular computational approaches addressing these questions, namely WaterMap based on statistical mechanics analysis of MD simulations and 3D RISM based on integral equation theory of liquids. The theoretical background and recent applications in structure-based design will be presented.
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Affiliation(s)
- Hans Matter
- Sanofi-Aventis Deutschland GmbH, Integrated Drug Discovery (IDD), Synthetic Molecular Design, Building G838, Industriepark Höchst, 65926 Frankfurt am Main, Germany.
| | - Stefan Güssregen
- Sanofi-Aventis Deutschland GmbH, Integrated Drug Discovery (IDD), Synthetic Molecular Design, Building G838, Industriepark Höchst, 65926 Frankfurt am Main, Germany
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43
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Miszta P, Jakowiecki J, Rutkowska E, Turant M, Latek D, Filipek S. Approaches for Differentiation and Interconverting GPCR Agonists and Antagonists. Methods Mol Biol 2018; 1705:265-296. [PMID: 29188567 DOI: 10.1007/978-1-4939-7465-8_12] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
Predicting the functional preferences of the ligands was always a highly demanding task, much harder that predicting whether a ligand can bind to the receptor. This is because of significant similarities of agonists, antagonists and inverse agonists which are binding usually in the same binding site of the receptor and only small structural changes can push receptor toward a particular activation state. For G protein-coupled receptors, due to a large progress in crystallization techniques and also in receptor thermal stabilization, it was possible to obtain a large number of high-quality structures of complexes of these receptors with agonists and non-agonists. Additionally, the long-time-scale molecular dynamics simulations revealed how the activation processes of GPCRs can take place. Using both theoretical and experimental knowledge it was possible to employ many clever and sophisticated methods which can help to differentiate agonists and non-agonists, so one can interconvert them in search of the optimal drug.
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Affiliation(s)
- Przemysław Miszta
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Jakub Jakowiecki
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Ewelina Rutkowska
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Maria Turant
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Dorota Latek
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland
| | - Sławomir Filipek
- Biological and Chemical Research Centre, Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093, Warsaw, Poland.
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44
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Fu T, Zheng G, Tu G, Yang F, Chen Y, Yao X, Li X, Xue W, Zhu F. Exploring the Binding Mechanism of Metabotropic Glutamate Receptor 5 Negative Allosteric Modulators in Clinical Trials by Molecular Dynamics Simulations. ACS Chem Neurosci 2018. [PMID: 29522307 DOI: 10.1021/acschemneuro.8b00059] [Citation(s) in RCA: 100] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Metabotropic glutamate receptor 5 (mGlu5) plays a key role in synaptic information storage and memory, which is a well-known target for a variety of psychiatric and neurodegenerative disorders. In recent years, the increasing efforts have been focused on the design of allosteric modulators, and the negative allosteric modulators (NAMs) are the front-runners. Recently, the architecture of the transmembrane (TM) domain of mGlu5 receptor has been determined by crystallographic experiment. However, it has been not well understood how the pharmacophores of NAMs accommodated into the allosteric binding site. In this study, molecular dynamics (MD) simulations were performed on mGlu5 receptor bound with NAMs in preclinical or clinical development to shed light on this issue. In order to identify the key residues, the binding free energies as well as per-residue contributions for NAMs binding to mGlu5 receptor were calculated. Subsequently, the in silico site-directed mutagenesis of the key residues was performed to verify the accuracy of simulation models. As a result, the shared common features of the studied 5 clinically important NAMs (mavoglurant, dipraglurant, basimglurant, STX107, and fenobam) interacting with 11 residues in allosteric site were obtained. This comprehensive study presented a better understanding of mGlu5 receptor NAMs binding mechanism, which would be further used as a useful framework to assess and discover novel lead scaffolds for NAMs.
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Affiliation(s)
- Tingting Fu
- Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences, and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing 401331, China
- Innovative Drug Research and Bioinformatics Group, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Guoxun Zheng
- Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences, and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing 401331, China
- Innovative Drug Research and Bioinformatics Group, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Gao Tu
- Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences, and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing 401331, China
- Innovative Drug Research and Bioinformatics Group, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Fengyuan Yang
- Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences, and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing 401331, China
- Innovative Drug Research and Bioinformatics Group, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Yuzong Chen
- Bioinformatics and Drug Design Group, Department of Pharmacy, National University of Singapore, Singapore 117543, Singapore
| | - Xiaojun Yao
- State Key Laboratory of Applied Organic Chemistry and Department of Chemistry, Lanzhou University, Lanzhou 730000, China
| | - Xiaofeng Li
- Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences, and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing 401331, China
- Innovative Drug Research and Bioinformatics Group, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Weiwei Xue
- Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences, and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing 401331, China
| | - Feng Zhu
- Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences, and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing 401331, China
- Innovative Drug Research and Bioinformatics Group, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
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45
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Abstract
The following chapter examines some of the current "state-of-the-art" tools for predicting, scoring, and examining explicit water molecules in proteins and protein/ligand complexes, highlighting some of the ways information can be readily examined in a manner that is useful in a drug discovery process.
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Affiliation(s)
- Andrea Bortolato
- Heptares Therapeutics Ltd., BioPark, Broadwater Road, Welwyn Garden City, Hertfordshire, AL7 3AX, UK
| | - Benjamin G Tehan
- Heptares Therapeutics Ltd., BioPark, Broadwater Road, Welwyn Garden City, Hertfordshire, AL7 3AX, UK.
| | - Robert T Smith
- Heptares Therapeutics Ltd., BioPark, Broadwater Road, Welwyn Garden City, Hertfordshire, AL7 3AX, UK
| | - Jonathan S Mason
- Heptares Therapeutics Ltd., BioPark, Broadwater Road, Welwyn Garden City, Hertfordshire, AL7 3AX, UK
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46
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Yang Y, Abdallah AHA, Lill MA. Calculation of Thermodynamic Properties of Bound Water Molecules. Methods Mol Biol 2018; 1762:389-402. [PMID: 29594782 DOI: 10.1007/978-1-4939-7756-7_19] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Water molecules in the binding site of a protein significantly influence protein structure and function, for example, by mediating protein-ligand interactions or in form of desolvation as driving force for ligand binding. The knowledge about location and thermodynamic properties of water molecules in the binding site is crucial to the understanding of protein function. This chapter describes the method of calculating the location and thermodynamic properties of bound water molecules from molecular dynamics (MD) simulation trajectories. Thermodynamic profiles of water molecules can be calculated either with or without the presence of a bound ligand based on the scientific problem. The location and thermodynamic profile of hydration sites mediating the protein-ligand interactions is important for understanding protein-ligand binding. The protein desolvation free energy can be estimated for any ligand by summation of the hydration site free energies of the displaced hydration sites. The WATsite program with an easy-to-use graphical user interface (GUI) based on PyMOL was developed for those calculations and is discussed in this chapter. The WATsite program and its PyMOL plugin are available free of charge from http://people.pharmacy.purdue.edu/~mlill/software/watsite/version3.shtml .
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Affiliation(s)
- Ying Yang
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, West Lafayette, IN, USA
| | - Amr H A Abdallah
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, West Lafayette, IN, USA
| | - Markus A Lill
- Department of Medicinal Chemistry and Molecular Pharmacology, College of Pharmacy, Purdue University, West Lafayette, IN, USA.
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47
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Abstract
The vast increase of recently solved GPCR X-ray structures forms the basis for GPCR homology modeling to atomistic accuracy. Nowadays, homology models can be employed for GPCR-ligand optimization and have been reported as invaluable tools for drug design in the last few years. Elucidation of the complex GPCR pharmacology and the associated GPCR conformations made clear that different homology models have to be constructed for different activation states of the GPCRs. Therefore, templates have to be chosen accordingly to their sequence homology as well as to their activation state. The subsequent ligand placement is nontrivial, as some recent X-ray structures show very unusual ligand binding sites and solvent involvement, expanding the space of the putative ligand binding site from the generic retinal binding pocket to the whole receptor. In the present study, a workflow is presented starting from the selection of the target sequence, guiding through the GPCR modeling process, and finishing with ligand placement and pose validation.
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Affiliation(s)
- Christofer S Tautermann
- Department for Medicinal Chemistry, Boehringer Ingelheim Pharma, GmbH & Co KG, Birkendorfer Straße 65, 88397, Biberach an der Riss, Germany.
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48
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Cournia Z, Allen B, Sherman W. Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations. J Chem Inf Model 2017; 57:2911-2937. [PMID: 29243483 DOI: 10.1021/acs.jcim.7b00564] [Citation(s) in RCA: 404] [Impact Index Per Article: 57.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Accurate in silico prediction of protein-ligand binding affinities has been a primary objective of structure-based drug design for decades due to the putative value it would bring to the drug discovery process. However, computational methods have historically failed to deliver value in real-world drug discovery applications due to a variety of scientific, technical, and practical challenges. Recently, a family of approaches commonly referred to as relative binding free energy (RBFE) calculations, which rely on physics-based molecular simulations and statistical mechanics, have shown promise in reliably generating accurate predictions in the context of drug discovery projects. This advance arises from accumulating developments in the underlying scientific methods (decades of research on force fields and sampling algorithms) coupled with vast increases in computational resources (graphics processing units and cloud infrastructures). Mounting evidence from retrospective validation studies, blind challenge predictions, and prospective applications suggests that RBFE simulations can now predict the affinity differences for congeneric ligands with sufficient accuracy and throughput to deliver considerable value in hit-to-lead and lead optimization efforts. Here, we present an overview of current RBFE implementations, highlighting recent advances and remaining challenges, along with examples that emphasize practical considerations for obtaining reliable RBFE results. We focus specifically on relative binding free energies because the calculations are less computationally intensive than absolute binding free energy (ABFE) calculations and map directly onto the hit-to-lead and lead optimization processes, where the prediction of relative binding energies between a reference molecule and new ideas (virtual molecules) can be used to prioritize molecules for synthesis. We describe the critical aspects of running RBFE calculations, from both theoretical and applied perspectives, using a combination of retrospective literature examples and prospective studies from drug discovery projects. This work is intended to provide a contemporary overview of the scientific, technical, and practical issues associated with running relative binding free energy simulations, with a focus on real-world drug discovery applications. We offer guidelines for improving the accuracy of RBFE simulations, especially for challenging cases, and emphasize unresolved issues that could be improved by further research in the field.
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Affiliation(s)
- Zoe Cournia
- Biomedical Research Foundation, Academy of Athens , 4 Soranou Ephessiou, 11527 Athens, Greece
| | - Bryce Allen
- Silicon Therapeutics , 300 A Street, Boston, Massachusetts 02210, United States
| | - Woody Sherman
- Silicon Therapeutics , 300 A Street, Boston, Massachusetts 02210, United States
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49
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Structure-Based Design of Potent and Selective Ligands at the Four Adenosine Receptors. Molecules 2017; 22:molecules22111945. [PMID: 29125553 PMCID: PMC6150288 DOI: 10.3390/molecules22111945] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 11/07/2017] [Accepted: 11/08/2017] [Indexed: 12/19/2022] Open
Abstract
The four receptors that signal for adenosine, A1, A2A, A2B and A3 ARs, belong to the superfamily of G protein-coupled receptors (GPCRs). They mediate a number of (patho)physiological functions and have attracted the interest of the biopharmaceutical sector for decades as potential drug targets. The many crystal structures of the A2A, and lately the A1 ARs, allow for the use of advanced computational, structure-based ligand design methodologies. Over the last decade, we have assessed the efficient synthesis of novel ligands specifically addressed to each of the four ARs. We herein review and update the results of this program with particular focus on molecular dynamics (MD) and free energy perturbation (FEP) protocols. The first in silico mutagenesis on the A1AR here reported allows understanding the specificity and high affinity of the xanthine-antagonist 8-Cyclopentyl-1,3-dipropylxanthine (DPCPX). On the A2AAR, we demonstrate how FEP simulations can distinguish the conformational selectivity of a recent series of partial agonists. These novel results are complemented with the revision of the first series of enantiospecific antagonists on the A2BAR, and the use of FEP as a tool for bioisosteric design on the A3AR.
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50
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Azuaje J, Jespers W, Yaziji V, Mallo A, Majellaro M, Caamaño O, Loza MI, Cadavid MI, Brea J, Åqvist J, Sotelo E, Gutiérrez-de-Terán H. Effect of Nitrogen Atom Substitution in A3 Adenosine Receptor Binding: N-(4,6-Diarylpyridin-2-yl)acetamides as Potent and Selective Antagonists. J Med Chem 2017; 60:7502-7511. [DOI: 10.1021/acs.jmedchem.7b00860] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
| | - Willem Jespers
- Department
of Cell and Molecular Biology, Uppsala University, Uppsala SE-75124, Sweden
| | | | | | | | | | | | | | | | - Johan Åqvist
- Department
of Cell and Molecular Biology, Uppsala University, Uppsala SE-75124, Sweden
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