1
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Zavarzina II, Kuzmenkov AI, Dobrokhotov NA, Maleeva EE, Korolkova YV, Peigneur S, Tytgat J, Krylov NA, Vassilevski AA, Chugunov AO. The scorpion toxin BeKm-1 blocks hERG cardiac potassium channels using an indispensable arginine residue. FEBS Lett 2024; 598:889-901. [PMID: 38563123 DOI: 10.1002/1873-3468.14850] [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: 12/28/2023] [Revised: 02/07/2024] [Accepted: 02/20/2024] [Indexed: 04/04/2024]
Abstract
BeKm-1 is a peptide toxin from scorpion venom that blocks the pore of the potassium channel hERG (Kv11.1) in the human heart. Although individual protein structures have been resolved, the structure of the complex between hERG and BeKm-1 is unknown. Here, we used molecular dynamics and ensemble docking, guided by previous double-mutant cycle analysis data, to obtain an in silico model of the hERG-BeKm-1 complex. Adding to the previous mutagenesis study of BeKm-1, our model uncovers the key role of residue Arg20, which forms three interactions (a salt bridge and hydrogen bonds) with the channel vestibule simultaneously. Replacement of this residue even by lysine weakens the interactions significantly. In accordance, the recombinantly produced BeKm-1R20K mutant exhibited dramatically decreased activity on hERG. Our model may be useful for future drug design attempts.
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Affiliation(s)
- Iana I Zavarzina
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Russia
| | | | - Nikita A Dobrokhotov
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Russia
| | | | | | | | - Jan Tytgat
- Toxicology and Pharmacology, KU Leuven, Belgium
| | - Nikolay A Krylov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Alexander A Vassilevski
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Anton O Chugunov
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
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2
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Ku T, Cao J, Won SJ, Guo J, Camacho-Hernandez GA, Okorom AV, Salomon KW, Lee KH, Loland CJ, Duff HJ, Shi L, Newman AH. Series of (([1,1'-Biphenyl]-2-yl)methyl)sulfinylalkyl Alicyclic Amines as Novel and High Affinity Atypical Dopamine Transporter Inhibitors with Reduced hERG Activity. ACS Pharmacol Transl Sci 2024; 7:515-532. [PMID: 38357284 PMCID: PMC10863442 DOI: 10.1021/acsptsci.3c00322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 12/15/2023] [Accepted: 12/22/2023] [Indexed: 02/16/2024]
Abstract
Currently, there are no FDA-approved medications for the treatment of psychostimulant use disorders (PSUD). We have previously discovered "atypical" dopamine transporter (DAT) inhibitors that do not display psychostimulant-like behaviors and may be useful as medications to treat PSUD. Lead candidates (e.g., JJC8-091, 1) have shown promising in vivo profiles in rodents; however, reducing hERG (human ether-à-go-go-related gene) activity, a predictor of cardiotoxicity, has remained a challenge. Herein, a series of 30 (([1,1'-biphenyl]-2-yl)methyl)sulfinylalkyl alicyclic amines was synthesized and evaluated for DAT and serotonin transporter (SERT) binding affinities. A subset of analogues was tested for hERG activity, and the IC50 values were compared to those predicted by our hERG QSAR models, which showed robust predictive power. Multiparameter optimization scores (MPO > 3) indicated central nervous system (CNS) penetrability. Finally, comparison of affinities in human DAT and its Y156F and Y335A mutants suggested that several compounds prefer an inward facing conformation indicating an atypical DAT inhibitor profile.
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Affiliation(s)
- Therese
C. Ku
- Molecular
Targets and Medications Discovery Branch, National Institute on Drug
Abuse–Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Jianjing Cao
- Molecular
Targets and Medications Discovery Branch, National Institute on Drug
Abuse–Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Sung Joon Won
- Molecular
Targets and Medications Discovery Branch, National Institute on Drug
Abuse–Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Jiqing Guo
- Faculty
of Medicine, Libin Institute, Calgary T2N 4N1, Canada
| | - Gisela A. Camacho-Hernandez
- Molecular
Targets and Medications Discovery Branch, National Institute on Drug
Abuse–Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Amarachi V. Okorom
- Molecular
Targets and Medications Discovery Branch, National Institute on Drug
Abuse–Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Kristine Walloe Salomon
- Laboratory
for Membrane Protein Dynamics, Department of Neuroscience, Faculty
of Health and Medical Sciences, University
of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen, Denmark
| | - Kuo Hao Lee
- Molecular
Targets and Medications Discovery Branch, National Institute on Drug
Abuse–Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Claus J. Loland
- Laboratory
for Membrane Protein Dynamics, Department of Neuroscience, Faculty
of Health and Medical Sciences, University
of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen, Denmark
| | - Henry J. Duff
- Laboratory
for Membrane Protein Dynamics, Department of Neuroscience, Faculty
of Health and Medical Sciences, University
of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen, Denmark
| | - Lei Shi
- Molecular
Targets and Medications Discovery Branch, National Institute on Drug
Abuse–Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Amy Hauck Newman
- Molecular
Targets and Medications Discovery Branch, National Institute on Drug
Abuse–Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
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3
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AlRawashdeh S, Chandrasekaran S, Barakat KH. Structural analysis of hERG channel blockers and the implications for drug design. J Mol Graph Model 2023; 120:108405. [PMID: 36680816 DOI: 10.1016/j.jmgm.2023.108405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/26/2022] [Accepted: 01/09/2023] [Indexed: 01/13/2023]
Abstract
The repolarizing current (Ikr) produced by the hERG potassium channel forms a major component of the cardiac action potential and blocking this current by small molecule drugs can lead to life-threatening cardiotoxicity. Understanding the mechanisms of drug-mediated hERG inhibition is essential to develop a second generation of safe drugs, with minimal cardiotoxic effects. Although various computational tools and drug design guidelines have been developed to avoid binding of drugs to the hERG pore domain, there are many other aspects that are still open for investigation. This includes the use computational modelling to study the implications of hERG mutations on hERG structure and trafficking, the interactions of hERG with hERG chaperone proteins and with membrane-soluble molecules, the mechanisms of drugs that inhibit hERG trafficking and drugs that rescue hERG mutations. The plethora of available experimental data regarding all these aspects can guide the construction of much needed robust computational structural models to study these mechanisms for the rational design of safe drugs.
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Affiliation(s)
- Sara AlRawashdeh
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada
| | | | - Khaled H Barakat
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada.
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4
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Feng H, Wei GW. Virtual screening of DrugBank database for hERG blockers using topological Laplacian-assisted AI models. Comput Biol Med 2023; 153:106491. [PMID: 36599209 PMCID: PMC10120853 DOI: 10.1016/j.compbiomed.2022.106491] [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: 11/17/2022] [Revised: 11/29/2022] [Accepted: 12/27/2022] [Indexed: 12/29/2022]
Abstract
The human ether-a-go-go (hERG) potassium channel (Kv11.1) plays a critical role in mediating cardiac action potential. The blockade of this ion channel can potentially lead fatal disorder and/or long QT syndrome. Many drugs have been withdrawn because of their serious hERG-cardiotoxicity. It is crucial to assess the hERG blockade activity in the early stage of drug discovery. We are particularly interested in the hERG-cardiotoxicity of compounds collected in the DrugBank database considering that many DrugBank compounds have been approved for therapeutic treatments or have high potential to become drugs. Machine learning-based in silico tools offer a rapid and economical platform to virtually screen DrugBank compounds. We design accurate and robust classifiers for blockers/non-blockers and then build regressors to quantitatively analyze the binding potency of the DrugBank compounds on the hERG channel. Molecular sequences are embedded with two natural language processing (NLP) methods, namely, autoencoder and transformer. Complementary three-dimensional (3D) molecular structures are embedded with two advanced mathematical approaches, i.e., topological Laplacians and algebraic graphs. With our state-of-the-art tools, we reveal that 227 out of the 8641 DrugBank compounds are potential hERG blockers, suggesting serious drug safety problems. Our predictions provide guidance for the further experimental interrogation of DrugBank compounds' hERG-cardiotoxicity.
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Affiliation(s)
- Hongsong Feng
- Department of Mathematics, Michigan State University, MI 48824, USA
| | - Guo-Wei Wei
- Department of Mathematics, Michigan State University, MI 48824, USA; Department of Electrical and Computer Engineering, Michigan State University, MI 48824, USA; Department of Biochemistry and Molecular Biology, Michigan State University, MI 48824, USA.
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5
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Goel H, Yu W, MacKerell AD. hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties. CHEMISTRY (BASEL, SWITZERLAND) 2022; 4:630-646. [PMID: 36712295 PMCID: PMC9881610 DOI: 10.3390/chemistry4030045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson's R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.
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Affiliation(s)
- Himanshu Goel
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St. Baltimore, MD 21201, United States
| | - Wenbo Yu
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St. Baltimore, MD 21201, United States
| | - Alexander D. MacKerell
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St. Baltimore, MD 21201, United States
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6
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Creanza TM, Delre P, Ancona N, Lentini G, Saviano M, Mangiatordi GF. Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study. J Chem Inf Model 2021; 61:4758-4770. [PMID: 34506150 PMCID: PMC9282647 DOI: 10.1021/acs.jcim.1c00744] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
![]()
Drug-induced blockade of the human
ether-à-go-go-related
gene (hERG) channel is today considered the main
cause of cardiotoxicity in postmarketing surveillance. Hence, several
ligand-based approaches were developed in the last years and are currently
employed in the early stages of a drug discovery process for in silico cardiac safety assessment of drug candidates.
Herein, we present the first structure-based classifiers able to discern hERG binders from nonbinders. LASSO regularized support
vector machines were applied to integrate docking scores and protein–ligand
interaction fingerprints. A total of 396 models were trained and validated
based on: (i) high-quality experimental bioactivity information returned
by 8337 curated compounds extracted from ChEMBL (version 25) and (ii)
structural predictor data. Molecular docking simulations were performed
using GLIDE and GOLD software programs and four different hERG structural models, namely, the recently published structures
obtained by cryoelectron microscopy (PDB codes: 5VA1 and 7CN1) and
two published homology models selected for comparison. Interestingly,
some classifiers return performances comparable to ligand-based models
in terms of area under the ROC curve (AUCMAX = 0.86 ±
0.01) and negative predictive values (NPVMAX = 0.81 ±
0.01), thus putting forward the herein proposed computational workflow
as a valuable tool for predicting hERG-related cardiotoxicity
without the limitations of ligand-based models, typically affected
by low interpretability and a limited applicability domain. From a
methodological point of view, our study represents the first example
of a successful integration of docking scores and protein–ligand
interaction fingerprints (IFs) through a support vector machine (SVM)
LASSO regularized strategy. Finally, the study highlights the importance
of using hERG structural models accounting for ligand-induced
fit effects and allowed us to select the best-performing protein conformation
(made available in the Supporting Information, SI) to be employed
for a reliable structure-based prediction of hERG-related cardiotoxicity.
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Affiliation(s)
- Teresa Maria Creanza
- CNR-Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, Via Amendola 122/o, 70126 Bari, Italy
| | - Pietro Delre
- Chemistry Department, University of Bari "Aldo Moro", via E. Orabona, 4, I-70125 Bari, Italy.,CNR-Institute of Crystallography, Via Amendola 122/o, 70126 Bari, Italy
| | - Nicola Ancona
- CNR-Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, Via Amendola 122/o, 70126 Bari, Italy
| | - Giovanni Lentini
- Department of Pharmacy-Pharmaceutical Sciences, University of Bari "Aldo Moro", via E. Orabona, 4, I-70125 Bari, Italy
| | - Michele Saviano
- CNR-Institute of Crystallography, Via Amendola 122/o, 70126 Bari, Italy
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7
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Lee KH, Fant AD, Guo J, Guan A, Jung J, Kudaibergenova M, Miranda WE, Ku T, Cao J, Wacker S, Duff HJ, Newman AH, Noskov SY, Shi L. Toward Reducing hERG Affinities for DAT Inhibitors with a Combined Machine Learning and Molecular Modeling Approach. J Chem Inf Model 2021; 61:4266-4279. [PMID: 34420294 DOI: 10.1021/acs.jcim.1c00856] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Psychostimulant drugs, such as cocaine, inhibit dopamine reuptake via blockading the dopamine transporter (DAT), which is the primary mechanism underpinning their abuse. Atypical DAT inhibitors are dissimilar to cocaine and can block cocaine- or methamphetamine-induced behaviors, supporting their development as part of a treatment regimen for psychostimulant use disorders. When developing these atypical DAT inhibitors as medications, it is necessary to avoid off-target binding that can produce unwanted side effects or toxicities. In particular, the blockade of a potassium channel, human ether-a-go-go (hERG), can lead to potentially lethal ventricular tachycardia. In this study, we established a counter screening platform for DAT and against hERG binding by combining machine learning-based quantitative structure-activity relationship (QSAR) modeling, experimental validation, and molecular modeling and simulations. Our results show that the available data are adequate to establish robust QSAR models, as validated by chemical synthesis and pharmacological evaluation of a validation set of DAT inhibitors. Furthermore, the QSAR models based on subsets of the data according to experimental approaches used have predictive power as well, which opens the door to target specific functional states of a protein. Complementarily, our molecular modeling and simulations identified the structural elements responsible for a pair of DAT inhibitors having opposite binding affinity trends at DAT and hERG, which can be leveraged for rational optimization of lead atypical DAT inhibitors with desired pharmacological properties.
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Affiliation(s)
- Kuo Hao Lee
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, United States
| | - Andrew D Fant
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, United States
| | - Jiqing Guo
- Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, Alberta T2N 4N1, Canada
| | - Andy Guan
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, United States
| | - Joslyn Jung
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, United States
| | - Mary Kudaibergenova
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Williams E Miranda
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Therese Ku
- Medicinal Chemistry Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, United States
| | - Jianjing Cao
- Medicinal Chemistry Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, United States
| | - Soren Wacker
- Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, Alberta T2N 4N1, Canada.,Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada.,Achlys Inc., 7-126 Li Ka Shing Center for Health and Innovation, Edmonton, Alberta T6G 2E1, Canada
| | - Henry J Duff
- Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, Alberta T2N 4N1, Canada
| | - Amy Hauck Newman
- Medicinal Chemistry Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, United States
| | - Sergei Y Noskov
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Lei Shi
- Computational Chemistry and Molecular Biophysics Section, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, United States
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8
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Şterbuleac D. Molecular dynamics: a powerful tool for studying the medicinal chemistry of ion channel modulators. RSC Med Chem 2021; 12:1503-1518. [PMID: 34671734 PMCID: PMC8459385 DOI: 10.1039/d1md00140j] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 07/21/2021] [Indexed: 01/10/2023] Open
Abstract
Molecular dynamics (MD) simulations allow researchers to investigate the behavior of desired biological targets at ever-decreasing costs with ever-increasing precision. Among the biological macromolecules, ion channels are remarkable transmembrane proteins, capable of performing special biological processes and revealing a complex regulatory matrix, including modulation by small molecules, either endogenous or exogenous. Recently, given the developments in ion channel structure determination and accessibility of bio-computational techniques, MD and related tools are becoming increasingly popular in the intense research area regarding ligand-channel interactions. This review synthesizes and presents the most important fields of MD involvement in investigating channel-molecule interactions, including, but not limited to, deciphering the binding modes of ligands to their ion channel targets and the mechanisms through which chemical compounds exert their effect on channel function. Special attention is devoted to the importance of more elaborate methods, such as free energy calculations, while principles regarding drug design and discovery are highlighted. Several technical aspects involving the creation and simulation of channel-molecule MD systems (ligand parameterization, proper membrane setup, system building, etc.) are also presented.
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Affiliation(s)
- Daniel Şterbuleac
- Department of Health and Human Development, "Ştefan cel Mare" University of Suceava Str. Universităţii 13, 720229, E Building Suceava Romania
- Department of Forestry and Environmental Protection, "Ştefan cel Mare" University of Suceava Str. Universităţii 13, 720229, E Building Suceava Romania
- Integrated Center for Research, Development and Innovation in Advanced Materials, Nanotechnologies and Distributed Systems for Fabrication and Control (MANSiD), "Ştefan cel Mare" University of Suceava Str. Universităţii 13 720229 Suceava Romania
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9
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Williams JC, Kalyaanamoorthy S. PoseFilter: A PyMOL Plugin for filtering and analyzing small molecule docking in symmetric binding sites. Bioinformatics 2021; 37:3367-3368. [PMID: 33742661 DOI: 10.1093/bioinformatics/btab188] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 02/18/2021] [Accepted: 03/17/2021] [Indexed: 11/13/2022] Open
Abstract
SUMMARY 'PoseFilter' is a PyMOL plugin that assists in analyses and filtering of docked poses. PoseFilter enables automatic detection of symmetric poses from docking outputs and can be accessed using both graphical user interface and command-line options within the PyMOL program. Two methods of analyses, root mean square deviations (RMSD) and interaction fingerprints, are available from this plugin. The capabilities of the plugin are demonstrated using docking outputs from different oligomeric protein-ligand complexes. AVAILABILITY AND IMPLEMENTATION The plugin can be downloaded from the GitHub page, https://github.com/skalyaanamoorthy/PoseFilter. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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10
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Saponara S, Fusi F, Iovinelli D, Ahmed A, Trezza A, Spiga O, Sgaragli G, Valoti M. Flavonoids and hERG channels: Friends or foes? Eur J Pharmacol 2021; 899:174030. [PMID: 33727059 DOI: 10.1016/j.ejphar.2021.174030] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 02/28/2021] [Accepted: 03/11/2021] [Indexed: 01/24/2023]
Abstract
The cardiac action potential is regulated by several ion channels. Drugs capable to block these channels, in particular the human ether-à-go-go-related gene (hERG) channel, also known as KV11.1 channel, may lead to a potentially lethal ventricular tachyarrhythmia called "Torsades de Pointes". Thus, evaluation of the hERG channel off-target activity of novel chemical entities is nowadays required to safeguard patients as well as to avoid attrition in drug development. Flavonoids, a large class of natural compounds abundantly present in food, beverages, herbal medicines, and dietary food supplements, generally escape this assessment, though consumed in consistent amounts. Continuously growing evidence indicates that these compounds may interact with the hERG channel and block it. The present review, by examining numerous studies, summarizes the state-of-the-art in this field, describing the most significant examples of direct and indirect inhibition of the hERG channel current operated by flavonoids. A description of the molecular interactions between a few of these natural molecules and the Rattus norvegicus channel protein, achieved by an in silico approach, is also presented.
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Affiliation(s)
- Simona Saponara
- Dipartimento di Scienze della Vita, Università degli Studi di Siena, via A. Moro 2, 53100, Siena, Italy
| | - Fabio Fusi
- Dipartimento di Biotecnologie, Chimica e Farmacia, Università degli Studi di Siena, via A. Moro 2, 53100, Siena, Italy.
| | - Daniele Iovinelli
- Dipartimento di Biotecnologie, Chimica e Farmacia, Università degli Studi di Siena, via A. Moro 2, 53100, Siena, Italy
| | - Amer Ahmed
- Dipartimento di Scienze della Vita, Università degli Studi di Siena, via A. Moro 2, 53100, Siena, Italy
| | - Alfonso Trezza
- Dipartimento di Biotecnologie, Chimica e Farmacia, Università degli Studi di Siena, via A. Moro 2, 53100, Siena, Italy
| | - Ottavia Spiga
- Dipartimento di Biotecnologie, Chimica e Farmacia, Università degli Studi di Siena, via A. Moro 2, 53100, Siena, Italy
| | - Giampietro Sgaragli
- Dipartimento di Scienze della Vita, Università degli Studi di Siena, via A. Moro 2, 53100, Siena, Italy; Accademia Italiana della Vite e del Vino, via Logge degli Uffizi Corti 1, 50122, Florence, Italy
| | - Massimo Valoti
- Dipartimento di Scienze della Vita, Università degli Studi di Siena, via A. Moro 2, 53100, Siena, Italy
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11
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Naik SR, Bharadwaj P, Dingelstad N, Kalyaanamoorthy S, Mandal SC, Ganesan A, Chattopadhyay D, Palit P. Structure-based virtual screening, molecular dynamics and binding affinity calculations of some potential phytocompounds against SARS-CoV-2. J Biomol Struct Dyn 2021; 40:6921-6938. [PMID: 33682632 DOI: 10.1080/07391102.2021.1891969] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
COVID-19 caused by a positive-sense single stranded RNA virus named as severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) triggered the global pandemic. This virus has infected about 10.37 Crores and taken lives of 2.24 Crores people of 213 countries to date. To cope-up this emergency clinical trials are undergoing with some existing drugs like remdesivir, flavipiravir, lopinavir-ritonavir, nafamostat, doxycycline, hydroxy-chloroquine, dexamethasone, etc., despite their severe toxicity and health hazards among diabetics, hypertensive, cardiac patients or normal individuals. The lack of safe and approved treatment for COVID-19 has forced the scientific community to find novel and safe compounds with potential efficacy. This study evaluates a few selective herbal compounds like glucoraphanin, vitexin, niazinin, etc., as a potential inhibitor of the spike protein and 3-chymotrypsin-like protease (3CLpro) or main protease (Mpro) of SARS-COV-2 through in-silico virtual studies such as molecular docking, target analysis, toxicity prediction and ADME prediction and supported by a Molecular-Dynamic simulation. Selective phytocompounds were docked successfully in the binding site of spike glycoprotein and 3CLpro (Mpro) of SARS-CoV-2. In-silico approaches also predict this molecule to have good solubility, pharmacodynamic property and target accuracy through MD simulation and ADME studies. These hit molecules niazinin, vitexin, glucoraphanin also obey Lipinski's rule along with their stable binding towards target protein of the virus, which makes them suitable for further biochemical and cell-based assays followed by clinical investigations to highlight their potential use in COVID-19 treatment.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shiv Rakesh Naik
- ArGan's Lab, School of Pharmacy, Faculty of Science, University of Waterloo, ON, Canada
| | - Prashant Bharadwaj
- Department of Computer science and Engineering, NIT Agartala, Agartala, India
| | - Nadia Dingelstad
- ArGan's Lab, School of Pharmacy, Faculty of Science, University of Waterloo, ON, Canada
| | | | - Subhash C Mandal
- Pharmacognosy & Phytotherapy Research Laboratory, Division of Pharmacognosy, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
| | - Aravindhan Ganesan
- ArGan's Lab, School of Pharmacy, Faculty of Science, University of Waterloo, ON, Canada
| | | | - Partha Palit
- Department of Pharmaceutical Sciences, Drug Discovery Research Laboratory, Assam University, Silchar, India
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12
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Koulgi S, Jani V, Nair V, Saini JS, Phukan S, Sonavane U, Joshi R, Kamboj R, Palle V. Molecular dynamics of hERG channel: insights into understanding the binding of small molecules for detuning cardiotoxicity. J Biomol Struct Dyn 2021; 40:5996-6012. [PMID: 33494645 DOI: 10.1080/07391102.2021.1875883] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Evaluation of cardiotoxicity potential of new chemical entities (NCEs) has lately become one of the stringent filters in the drug discovery and development process. Cardiotoxicity is caused mainly by the inhibition of human ether-a-go-go related gene (hERG) channel protein. Inhibition of the hERG channel leads to a life-threatening condition known as cardiac arrhythmia. Knowledge of the structural behaviour of the hERG would aid greatly in the design of new drug molecules that do not interact with the protein and add to the safety index. In this study, a computational model for the active-state of hERG was developed. This model was equilibrated by performing the molecular dynamics simulations for 100 ns followed by clustering and selection of a representative structure based on the largest populated cluster. To study the changes in the protein structure on inhibition, three inhibitory ligands, namely, dofetilide, cisapride and terfenadine were docked, followed by molecular dynamics simulations of 200 ns for the apo and each ligand-bound structure. It was observed that docking and simulation studies of the hERG model exhibited noticeable conformational changes in the protein upon ligand-binding. A significant change in the kink of the S6-transmembrane helix was observed. Inter-chain distances between the crucial residues Y652 and F656 (present below the ion-selectivity filter), their side-chain orientation and hydrogen bonding indicated a probable collapse of the pore. These changes may infer the initiation in transition of hERG from an open to an inactive state. Hence, these findings would help in designing compounds devoid of hERG inhibition with reduced cardiotoxicity.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Shruti Koulgi
- High Performance Computing - Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Panchawati, Pashan, Pune
| | - Vinod Jani
- High Performance Computing - Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Panchawati, Pashan, Pune
| | | | - Jagmohan S Saini
- Novel Drug Discovery and Development, Lupin Research Park, Pune, India
| | - Samiron Phukan
- Novel Drug Discovery and Development, Lupin Research Park, Pune, India
| | - Uddhavesh Sonavane
- High Performance Computing - Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Panchawati, Pashan, Pune
| | - Rajendra Joshi
- High Performance Computing - Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Panchawati, Pashan, Pune
| | - Raj Kamboj
- Novel Drug Discovery and Development, Lupin Research Park, Pune, India
| | - Venkata Palle
- Novel Drug Discovery and Development, Lupin Research Park, Pune, India
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13
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Newman AH, Ku T, Jordan CJ, Bonifazi A, Xi ZX. New Drugs, Old Targets: Tweaking the Dopamine System to Treat Psychostimulant Use Disorders. Annu Rev Pharmacol Toxicol 2021; 61:609-628. [PMID: 33411583 DOI: 10.1146/annurev-pharmtox-030220-124205] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The abuse of illicit psychostimulants such as cocaine and methamphetamine continues to pose significant health and societal challenges. Despite considerable efforts to develop medications to treat psychostimulant use disorders, none have proven effective, leaving an underserved patient population and unanswered questions about what mechanism(s) of action should be targeted for developing pharmacotherapies. As both cocaine and methamphetamine rapidly increase dopamine (DA) levels in mesolimbic brain regions, leading to euphoria that in some can lead to addiction, targets in which this increased dopaminergic tone may be mitigated have been explored. Further, understanding and targeting mechanisms underlying relapse are fundamental to the success of discovering medications that reduce the reinforcing effects of the drug of abuse, decrease the negative reinforcement or withdrawal/negative affect that occurs during abstinence, or both. Atypical inhibitors of the DA transporter and partial agonists/antagonists at DA D3 receptors are described as two promising targets for future drug development.
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Affiliation(s)
- Amy Hauck Newman
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, USA;
| | - Therese Ku
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, USA;
| | - Chloe J Jordan
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, USA;
| | - Alessandro Bonifazi
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, USA;
| | - Zheng-Xiong Xi
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland 21224, USA;
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14
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A structure-based computational workflow to predict liability and binding modes of small molecules to hERG. Sci Rep 2020; 10:16262. [PMID: 33004839 PMCID: PMC7530726 DOI: 10.1038/s41598-020-72889-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 09/07/2020] [Indexed: 02/06/2023] Open
Abstract
Off-target interactions of drugs with the human ether-à-go-go related gene 1 (hERG1) channel have been associated with severe cardiotoxic conditions leading to the withdrawal of many drugs from the market over the last decades. Consequently, predicting drug-induced hERG-liability is now a prerequisite in any drug discovery campaign. Understanding the atomic level interactions of drug with the channel is essential to guide the efficient development of safe drugs. Here we utilize the recent cryo-EM structure of the hERG channel and describe an integrated computational workflow to characterize different drug-hERG interactions. The workflow employs various structure-based approaches and provides qualitative and quantitative insights into drug binding to hERG. Our protocol accurately differentiated the strong blockers from weak and revealed three potential anchoring sites in hERG. Drugs engaging in all these sites tend to have high affinity towards hERG. Our results were cross-validated using a fluorescence polarization kit binding assay and with electrophysiology measurements on the wild-type (WT-hERG) and on the two hERG mutants (Y652A-hERG and F656A-hERG), using the patch clamp technique on HEK293 cells. Finally, our analyses show that drugs binding to hERG disrupt and hijack certain native—structural networks in the channel, thereby, gaining more affinity towards hERG.
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15
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Vormfelde SV, Pezous N, Lefèvre G, Kolly C, Neumann U, Jordaan P, Ufer M, Legangneux E. A Pooled Analysis of Three Randomized Phase I/IIa Clinical Trials Confirms Absence of a Clinically Relevant Effect on the QTc Interval by Umibecestat. Clin Transl Sci 2020; 13:1316-1326. [PMID: 32583957 PMCID: PMC7719381 DOI: 10.1111/cts.12832] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 05/01/2020] [Indexed: 01/17/2023] Open
Abstract
Umibecestat, an orally active β‐secretase inhibitor, reduces the production of amyloid beta‐peptide that accumulates in the brain of patients with Alzheimer’s disease. The echocardiogram effects of umibecestat, on QTcF (Fridericia‐corrected QT), on PR and QRS and heart rate (HR), were estimated by concentration‐effect modeling. Three phase I/II studies with durations up to 3 months, with 372 healthy subjects over a wide age range, including both sexes and 2 ethnicities, were pooled, providing a large data set with good statistical power. No clinically relevant effect on QTcF, PR interval, QRS duration, or HR were observed up to supratherapeutic doses. The upper bound of 90% confidence intervals of the ∆QTcF was below the 10 ms threshold of regulatory concern for all concentrations measured. Prespecified sensitivity analysis confirmed the results in both sexes, in those over and below 60 years, and in Japanese subjects. All conclusions were endorsed by the US Food and Drug Administration (FDA).
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Affiliation(s)
- Stefan Viktor Vormfelde
- Department of Translational Medicine, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Nicole Pezous
- Department of Translational Medicine, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Gilbert Lefèvre
- Department of Translational Medicine, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Carine Kolly
- Department of Preclinical Safety, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Ulf Neumann
- Department of Neuroscience, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Pierre Jordaan
- Cardiovascular Safety Expert - CMO and Patient Safety - Oncology, Novartis Pharma, Basel, Switzerland
| | - Mike Ufer
- Department of Translational Medicine, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Eric Legangneux
- Department of Translational Medicine, Novartis Institutes for BioMedical Research, Basel, Switzerland
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16
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Wedlake AJ, Folia M, Piechota S, Allen TEH, Goodman JM, Gutsell S, Russell PJ. Structural Alerts and Random Forest Models in a Consensus Approach for Receptor Binding Molecular Initiating Events. Chem Res Toxicol 2020; 33:388-401. [PMID: 31850746 DOI: 10.1021/acs.chemrestox.9b00325] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
A molecular initiating event (MIE) is the gateway to an adverse outcome pathway (AOP), a sequence of events ending in an adverse effect. In silico predictions of MIEs are a vital tool in a modern, mechanism-focused approach to chemical risk assessment. For 90 biological targets representing important human MIEs, structural alert-based models have been constructed with an automated procedure that uses Bayesian statistics to iteratively select substructures. These models give impressive average performance statistics (an average of 92% correct predictions across targets), significantly improving on previous models. Random Forest models have been constructed from physicochemical features for the same targets, giving similarly impressive performance statistics (93% correct predictions). A key difference between the models is interpretation of predictions-the structural alert models are transparent and easy to interpret, while Random Forest models can only identify the most important physicochemical features for making predictions. The two complementary models have been combined in a consensus model, improving performance compared to each individual model (94% correct predictions) and increasing confidence in predictions. Variation in model performance has been explained by calculating a modelability index (MODI), using Tanimoto coefficient between Morgan fingerprints to identify nearest neighbor chemicals. This work is an important step toward building confidence in the use of in silico tools for assessment of toxicity.
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Affiliation(s)
- Andrew J Wedlake
- Centre for Molecular Informatics, Department of Chemistry , University of Cambridge , Lensfield Road , Cambridge , CB2 1EW , United Kingdom
| | - Maria Folia
- Unilever Safety and Environmental Assurance Centre , Colworth Science Park , Sharnbrook , Bedfordshire , MK44 1LQ , United Kingdom
| | - Sam Piechota
- Unilever Safety and Environmental Assurance Centre , Colworth Science Park , Sharnbrook , Bedfordshire , MK44 1LQ , United Kingdom
| | - Timothy E H Allen
- Centre for Molecular Informatics, Department of Chemistry , University of Cambridge , Lensfield Road , Cambridge , CB2 1EW , United Kingdom.,MRC Toxicology Unit , University of Cambridge , Lancaster Road , Leicester LE19HN , United Kingdom
| | - Jonathan M Goodman
- Centre for Molecular Informatics, Department of Chemistry , University of Cambridge , Lensfield Road , Cambridge , CB2 1EW , United Kingdom
| | - Steve Gutsell
- Unilever Safety and Environmental Assurance Centre , Colworth Science Park , Sharnbrook , Bedfordshire , MK44 1LQ , United Kingdom
| | - Paul J Russell
- Unilever Safety and Environmental Assurance Centre , Colworth Science Park , Sharnbrook , Bedfordshire , MK44 1LQ , United Kingdom
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17
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Dickson CJ, Velez-Vega C, Duca JS. Revealing Molecular Determinants of hERG Blocker and Activator Binding. J Chem Inf Model 2020; 60:192-203. [PMID: 31880933 DOI: 10.1021/acs.jcim.9b00773] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The Kv11.1 potassium channel, encoded by the human ether-a-go-go-related gene (hERG), plays an essential role in the cardiac action potential. hERG blockade by small molecules can induce "torsade de pointes" arrhythmias and sudden death; as such, it is an important off-target to avoid during drug discovery. Recently, a cryo-EM structure of the open channel state of hERG was reported, opening the door to in silico docking analyses and interpretation of hERG structure-activity relationships, with a view to avoiding blocking activity. Despite this, docking directly to this cryo-EM structure has been reported to yield binding modes that are unable to explain known mutagenesis data. In this work, we use molecular dynamics simulations to sample a range of channel conformations and run ensemble docking campaigns at the known hERG binding site below the selectivity filter, composed of the central cavity and the four deep hydrophobic pockets. We identify a hERG conformational state allowing discrimination of blockers vs nonblockers from docking; furthermore, the binding pocket agrees with mutagenesis data, and blocker binding modes fit the hERG blocker pharmacophore. We then use the same protocol to identify a binding pocket in the hERG channel pore for hERG activators, again agreeing with the reported mutagenesis. Our approach may be useful in drug discovery campaigns to prioritize candidate compounds based on hERG liability via virtual docking screens.
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Affiliation(s)
- Callum J Dickson
- Computer-Aided Drug Discovery, Global Discovery Chemistry , Novartis Institutes for BioMedical Research , 181 Massachusetts Avenue , Cambridge , Massachusetts 02139 , United States
| | - Camilo Velez-Vega
- Computer-Aided Drug Discovery, Global Discovery Chemistry , Novartis Institutes for BioMedical Research , 181 Massachusetts Avenue , Cambridge , Massachusetts 02139 , United States
| | - Jose S Duca
- Computer-Aided Drug Discovery, Global Discovery Chemistry , Novartis Institutes for BioMedical Research , 181 Massachusetts Avenue , Cambridge , Massachusetts 02139 , United States
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18
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Slack RD, Ku TC, Cao J, Giancola JB, Bonifazi A, Loland CJ, Gadiano A, Lam J, Rais R, Slusher BS, Coggiano M, Tanda G, Newman AH. Structure-Activity Relationships for a Series of (Bis(4-fluorophenyl)methyl)sulfinyl Alkyl Alicyclic Amines at the Dopamine Transporter: Functionalizing the Terminal Nitrogen Affects Affinity, Selectivity, and Metabolic Stability. J Med Chem 2019; 63:2343-2357. [PMID: 31661268 DOI: 10.1021/acs.jmedchem.9b01188] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Atypical dopamine transporter (DAT) inhibitors have shown therapeutic potential in preclinical models of psychostimulant abuse. In rats, 1-(4-(2-((bis(4-fluorophenyl)methyl)sulfinyl)ethyl)-piperazin-1-yl)-propan-2-ol (3b) was effective in reducing the reinforcing effects of both cocaine and methamphetamine but did not exhibit psychostimulant behaviors itself. While further development of 3b is ongoing, diastereomeric separation, as well as improvements in potency and pharmacokinetics were desirable for discovering pipeline drug candidates. Thus, a series of bis(4-fluorophenyl)methyl)sulfinyl)alkyl alicyclic amines, where the piperazine-2-propanol scaffold was modified, were designed, synthesized, and evaluated for binding affinities at DAT, as well as the serotonin transporter and σ1 receptors. Within the series, 14a showed improved DAT affinity (Ki = 23 nM) over 3b (Ki = 230 nM), moderate metabolic stability in human liver microsomes, and a hERG/DAT affinity ratio = 28. While 14a increased locomotor activity relative to vehicle, it was significantly lower than activity produced by cocaine. These results support further investigation of 14a as a potential treatment for psychostimulant use disorders.
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Affiliation(s)
- Rachel D Slack
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Therese C Ku
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Jianjing Cao
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - JoLynn B Giancola
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Alessandro Bonifazi
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Claus J Loland
- Molecular Neuropharmacology and Genetics Laboratory, Department of Neuroscience and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Alexandra Gadiano
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States.,Department of Neurology, Johns Hopkins Drug Discovery, The Johns Hopkins University School of Medicine, 855 North Wolfe Street, Baltimore, Maryland 21205, United States
| | - Jenny Lam
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States.,Department of Neurology, Johns Hopkins Drug Discovery, The Johns Hopkins University School of Medicine, 855 North Wolfe Street, Baltimore, Maryland 21205, United States
| | - Rana Rais
- Department of Neurology, Johns Hopkins Drug Discovery, The Johns Hopkins University School of Medicine, 855 North Wolfe Street, Baltimore, Maryland 21205, United States
| | - Barbara S Slusher
- Department of Neurology, Johns Hopkins Drug Discovery, The Johns Hopkins University School of Medicine, 855 North Wolfe Street, Baltimore, Maryland 21205, United States
| | - Mark Coggiano
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Gianluigi Tanda
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
| | - Amy Hauck Newman
- Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse-Intramural Research Program, National Institutes of Health, 333 Cassell Drive, Baltimore, Maryland 21224, United States
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19
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Neumann U, Ufer M, Jacobson LH, Rouzade-Dominguez ML, Huledal G, Kolly C, Lüönd RM, Machauer R, Veenstra SJ, Hurth K, Rueeger H, Tintelnot-Blomley M, Staufenbiel M, Shimshek DR, Perrot L, Frieauff W, Dubost V, Schiller H, Vogg B, Beltz K, Avrameas A, Kretz S, Pezous N, Rondeau JM, Beckmann N, Hartmann A, Vormfelde S, David OJ, Galli B, Ramos R, Graf A, Lopez Lopez C. The BACE-1 inhibitor CNP520 for prevention trials in Alzheimer's disease. EMBO Mol Med 2019; 10:emmm.201809316. [PMID: 30224383 PMCID: PMC6220303 DOI: 10.15252/emmm.201809316] [Citation(s) in RCA: 99] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
The beta‐site amyloid precursor protein cleaving enzyme‐1 (BACE‐1) initiates the generation of amyloid‐β (Aβ), and the amyloid cascade leading to amyloid plaque deposition, neurodegeneration, and dementia in Alzheimer's disease (AD). Clinical failures of anti‐Aβ therapies in dementia stages suggest that treatment has to start in the early, asymptomatic disease states. The BACE‐1 inhibitor CNP520 has a selectivity, pharmacodynamics, and distribution profile suitable for AD prevention studies. CNP520 reduced brain and cerebrospinal fluid (CSF) Aβ in rats and dogs, and Aβ plaque deposition in APP‐transgenic mice. Animal toxicology studies of CNP520 demonstrated sufficient safety margins, with no signs of hair depigmentation, retina degeneration, liver toxicity, or cardiovascular effects. In healthy adults ≥ 60 years old, treatment with CNP520 was safe and well tolerated and resulted in robust and dose‐dependent Aβ reduction in the cerebrospinal fluid. Thus, long‐term, pivotal studies with CNP520 have been initiated in the Generation Program.
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Affiliation(s)
- Ulf Neumann
- Neuroscience, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Mike Ufer
- Translational Medicine, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Laura H Jacobson
- Neuroscience, Novartis Institute for BioMedical Research, Basel, Switzerland
| | | | - Gunilla Huledal
- PK Sciences, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Carine Kolly
- Preclinical Safety, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Rainer M Lüönd
- Global Discovery Chemistry, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Rainer Machauer
- Global Discovery Chemistry, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Siem J Veenstra
- Global Discovery Chemistry, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Konstanze Hurth
- Global Discovery Chemistry, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Heinrich Rueeger
- Global Discovery Chemistry, Novartis Institute for BioMedical Research, Basel, Switzerland
| | | | | | - Derya R Shimshek
- Neuroscience, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Ludovic Perrot
- Neuroscience, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Wilfried Frieauff
- Preclinical Safety, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Valerie Dubost
- Preclinical Safety, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Hilmar Schiller
- PK Sciences, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Barbara Vogg
- PK Sciences, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Karen Beltz
- PK Sciences, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Alexandre Avrameas
- Biomarker Discovery, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Sandrine Kretz
- Biomarker Discovery, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Nicole Pezous
- Translational Medicine, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Jean-Michel Rondeau
- Chemical Biology and Therapeutics, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Nicolau Beckmann
- Musculoskeletal Diseases, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Andreas Hartmann
- Preclinical Safety, Novartis Institute for BioMedical Research, Basel, Switzerland
| | - Stefan Vormfelde
- Translational Medicine, Novartis Institute for BioMedical Research, Basel, Switzerland
| | | | - Bruno Galli
- Global Drug Development, Novartis, Basel, Switzerland
| | - Rita Ramos
- Global Drug Development, Novartis, Basel, Switzerland
| | - Ana Graf
- Global Drug Development, Novartis, Basel, Switzerland
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20
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Lin HY, Ho Y, Liu HL. Structure-Based Pharmacophore Modeling to Discover Novel CCR5 Inhibitors for HIV-1/Cancers Therapy. ACTA ACUST UNITED AC 2019. [DOI: 10.4236/jbise.2019.121002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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21
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Jalily Hasani H, Ganesan A, Ahmed M, Barakat KH. Effects of protein-protein interactions and ligand binding on the ion permeation in KCNQ1 potassium channel. PLoS One 2018; 13:e0191905. [PMID: 29444113 PMCID: PMC5812580 DOI: 10.1371/journal.pone.0191905] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 01/12/2018] [Indexed: 12/23/2022] Open
Abstract
The voltage-gated KCNQ1 potassium ion channel interacts with the type I transmembrane protein minK (KCNE1) to generate the slow delayed rectifier (IKs) current in the heart. Mutations in these transmembrane proteins have been linked with several heart-related issues, including long QT syndromes (LQTS), congenital atrial fibrillation, and short QT syndrome. Off-target interactions of several drugs with that of KCNQ1/KCNE1 ion channel complex have been known to cause fatal cardiac irregularities. Thus, KCNQ1/KCNE1 remains an important avenue for drug-design and discovery research. In this work, we present the structural and mechanistic details of potassium ion permeation through an open KCNQ1 structural model using the combined molecular dynamics and steered molecular dynamics simulations. We discuss the processes and key residues involved in the permeation of a potassium ion through the KCNQ1 ion channel, and how the ion permeation is affected by (i) the KCNQ1-KCNE1 interactions and (ii) the binding of chromanol 293B ligand and its derivatives into the complex. The results reveal that interactions between KCNQ1 with KCNE1 causes a pore constriction in the former, which in-turn forms small energetic barriers in the ion-permeation pathway. These findings correlate with the previous experimental reports that interactions of KCNE1 dramatically slows the activation of KCNQ1. Upon ligand-binding onto the complex, the energy-barriers along ion permeation path are more pronounced, as expected, therefore, requiring higher force in our steered-MD simulations. Nevertheless, pulling the ion when a weak blocker is bound to the channel does not necessitate high force in SMD. This indicates that our SMD simulations have been able to discern between strong and week blockers and reveal their influence on potassium ion permeation. The findings presented here will have some implications in understanding the potential off-target interactions of the drugs with the KCNQ1/KCNE1 channel that lead to cardiotoxic effects.
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Affiliation(s)
- Horia Jalily Hasani
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Aravindhan Ganesan
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Marawan Ahmed
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Khaled H. Barakat
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada
- Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alberta, Canada
- Li Ka Shing Applied Virology Institute, University of Alberta, Edmonton, Alberta, Canada
- * E-mail:
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