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Bera I, Payghan PV. Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery. Curr Pharm Des 2020; 25:3339-3349. [PMID: 31480998 DOI: 10.2174/1381612825666190903153043] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Accepted: 09/01/2019] [Indexed: 12/31/2022]
Abstract
BACKGROUND Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process. OBJECTIVE The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design. METHOD This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained. RESULTS This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations. CONCLUSION The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.
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Affiliation(s)
- Indrani Bera
- Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD, United States
| | - Pavan V Payghan
- Structural Biology and Bioinformatics Department, CSIR-IICB, Kolkata, India.,Department of Pharmaceutical Sciences, Washington State University College of Pharmacy and Pharmaceutical Sciences, Spokane, WA, United States
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Molecular dynamics of fentanyl bound to μ-opioid receptor. J Mol Model 2019; 25:144. [DOI: 10.1007/s00894-019-3999-2] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Accepted: 03/21/2019] [Indexed: 12/17/2022]
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Bresso E, Togawa R, Hammond-Kosack K, Urban M, Maigret B, Martins NF. GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease. BMC Bioinformatics 2016; 17:463. [PMID: 28105916 PMCID: PMC5249037 DOI: 10.1186/s12859-016-1342-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
BACKGOUND Fusarium graminearum (FG) is one of the major cereal infecting pathogens causing high economic losses worldwide and resulting in adverse effects on human and animal health. Therefore, the development of new fungicides against FG is an important issue to reduce cereal infection and economic impact. In the strategy for developing new fungicides, a critical step is the identification of new targets against which innovative chemicals weapons can be designed. As several G-protein coupled receptors (GPCRs) are implicated in signaling pathways critical for the fungi development and survival, such proteins could be valuable efficient targets to reduce Fusarium growth and therefore to prevent food contamination. RESULTS In this study, GPCRs were predicted in the FG proteome using a manually curated pipeline dedicated to the identification of GPCRs. Based on several successive filters, the most appropriate GPCR candidate target for developing new fungicides was selected. Searching for new compounds blocking this particular target requires the knowledge of its 3D-structure. As no experimental X-Ray structure of the selected protein was available, a 3D model was built by homology modeling. The model quality and stability was checked by 100 ns of molecular dynamics simulations. Two stable conformations representative of the conformational families of the protein were extracted from the 100 ns simulation and were used for an ensemble docking campaign. The model quality and stability was checked by 100 ns of molecular dynamics simulations previously to the virtual screening step. The virtual screening step comprised the exploration of a chemical library with 11,000 compounds that were docked to the GPCR model. Among these compounds, we selected the ten top-ranked nontoxic molecules proposed to be experimentally tested to validate the in silico simulation. CONCLUSIONS This study provides an integrated process merging genomics, structural bioinformatics and drug design for proposing innovative solutions to a world wide threat to grain producers and consumers.
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Affiliation(s)
- Emmanuel Bresso
- EMBRAPA Genetic Resources and Biotechnology, Brasília, DF 70770-917 Brazil
| | - Roberto Togawa
- EMBRAPA Genetic Resources and Biotechnology, Brasília, DF 70770-917 Brazil
| | - Kim Hammond-Kosack
- Department of Plant Biology and Crop Science, Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ UK
| | - Martin Urban
- Department of Plant Biology and Crop Science, Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ UK
| | - Bernard Maigret
- EMBRAPA Genetic Resources and Biotechnology, Brasília, DF 70770-917 Brazil
- CAPSID Team, LORIA, UMR 7503, CNRS, Lorraine University, Vandœuvre-lès-Nancy, 54506 France
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Tikhonova IG, Poerio E. Free fatty acid receptors: structural models and elucidation of ligand binding interactions. BMC STRUCTURAL BIOLOGY 2015; 15:16. [PMID: 26346819 PMCID: PMC4561419 DOI: 10.1186/s12900-015-0044-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2015] [Accepted: 08/26/2015] [Indexed: 12/14/2022]
Abstract
Background The free fatty acid receptors (FFAs), including FFA1 (orphan name: GPR40), FFA2 (GPR43) and FFA3 (GPR41) are G protein-coupled receptors (GPCRs) involved in energy and metabolic homeostasis. Understanding the structural basis of ligand binding at FFAs is an essential step toward designing potent and selective small molecule modulators. Results We analyse earlier homology models of FFAs in light of the newly published FFA1 crystal structure co-crystallized with TAK-875, an ago-allosteric ligand, focusing on the architecture of the extracellular binding cavity and agonist-receptor interactions. The previous low-resolution homology models of FFAs were helpful in highlighting the location of the ligand binding site and the key residues for ligand anchoring. However, homology models were not accurate in establishing the nature of all ligand-receptor contacts and the precise ligand-binding mode. From analysis of structural models and mutagenesis, it appears that the position of helices 3, 4 and 5 is crucial in ligand docking. The FFA1-based homology models of FFA2 and FFA3 were constructed and used to compare the FFA subtypes. From docking studies we propose an alternative binding mode for orthosteric agonists at FFA1 and FFA2, involving the interhelical space between helices 4 and 5. This binding mode can explain mutagenesis results for residues at positions 4.56 and 5.42. The novel FFAs structural models highlight higher aromaticity of the FFA2 binding cavity and higher hydrophilicity of the FFA3 binding cavity. The role of the residues at the second extracellular loop used in mutagenesis is reanalysed. The third positively-charged residue in the binding cavity of FFAs, located in helix 2, is identified and predicted to coordinate allosteric modulators. Conclusions The novel structural models of FFAs provide information on specific modes of ligand binding at FFA subtypes and new suggestions for mutagenesis and ligand modification, guiding the development of novel orthosteric and allosteric chemical probes to validate the importance of FFAs in metabolic and inflammatory conditions. Using our FFA homology modelling experience, a strategy to model a GPCR, which is phylogenetically distant from GPCRs with the available crystal structures, is discussed. Electronic supplementary material The online version of this article (doi:10.1186/s12900-015-0044-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Irina G Tikhonova
- Molecular Therapeutics, School of Pharmacy, Medical Biology Centre, Queen's University Belfast, Belfast, BT9 7BL, Northern Ireland, UK.
| | - Elena Poerio
- Molecular Therapeutics, School of Pharmacy, Medical Biology Centre, Queen's University Belfast, Belfast, BT9 7BL, Northern Ireland, UK.
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Yuan Y, Zaidi SA, Elbegdorj O, Aschenbach LCK, Li G, Stevens DL, Scoggins KL, Dewey WL, Selley DE, Zhang Y. Design, synthesis, and biological evaluation of 14-heteroaromatic-substituted naltrexone derivatives: pharmacological profile switch from mu opioid receptor selectivity to mu/kappa opioid receptor dual selectivity. J Med Chem 2013; 56:9156-69. [PMID: 24144240 PMCID: PMC4373589 DOI: 10.1021/jm4012214] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
On the basis of a mu opioid receptor (MOR) homology model and the isosterism concept, three generations of 14-heteroaromatically substituted naltrexone derivatives were designed, synthesized, and evaluated as potential MOR-selective ligands. The first-generation ligands appeared to be MOR-selective, whereas the second and the third generation ones showed MOR/kappa opioid receptor (KOR) dual selectivity. Docking of ligands 2 (MOR selective) and 10 (MOR/KOR dual selective) to the three opioid receptor crystal structures revealed a nonconserved-residue-facilitated hydrogen-bonding network that could be responsible for their distinctive selectivity profiles. The MOR/KOR dual-selective ligand 10 showed no agonism and acted as a potent antagonist in the tail-flick assay. It also produced less severe opioid withdrawal symptoms than naloxone in morphine-dependent mice. In conclusion, ligand 10 may serve as a novel lead compound to develop MOR/KOR dual-selective ligands, which might possess unique therapeutic value for opioid addiction treatment.
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MESH Headings
- Animals
- Behavior, Animal/drug effects
- CHO Cells
- Chemistry Techniques, Synthetic
- Cricetinae
- Cricetulus
- Drug Design
- Male
- Mice
- Models, Molecular
- Naltrexone/chemical synthesis
- Naltrexone/chemistry
- Naltrexone/metabolism
- Naltrexone/pharmacology
- Protein Conformation
- Receptors, Opioid, kappa/chemistry
- Receptors, Opioid, kappa/metabolism
- Receptors, Opioid, mu/chemistry
- Receptors, Opioid, mu/metabolism
- Substrate Specificity
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Affiliation(s)
- Yunyun Yuan
- Department of Medicinal Chemistry, Virginia Commonwealth University, 800 East Leigh Street, Richmond, VA 23298, USA
| | - Saheem A. Zaidi
- Department of Medicinal Chemistry, Virginia Commonwealth University, 800 East Leigh Street, Richmond, VA 23298, USA
| | - Orgil Elbegdorj
- Department of Medicinal Chemistry, Virginia Commonwealth University, 800 East Leigh Street, Richmond, VA 23298, USA
| | - Lindsey C. K. Aschenbach
- Department of Medicinal Chemistry, Virginia Commonwealth University, 800 East Leigh Street, Richmond, VA 23298, USA
| | - Guo Li
- Department of Medicinal Chemistry, Virginia Commonwealth University, 800 East Leigh Street, Richmond, VA 23298, USA
| | - David L. Stevens
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, 410 North 12th Street, Richmond, VA 23298, USA
| | - Krista L. Scoggins
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, 410 North 12th Street, Richmond, VA 23298, USA
| | - William L. Dewey
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, 410 North 12th Street, Richmond, VA 23298, USA
| | - Dana E. Selley
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, 410 North 12th Street, Richmond, VA 23298, USA
| | - Yan Zhang
- Department of Medicinal Chemistry, Virginia Commonwealth University, 800 East Leigh Street, Richmond, VA 23298, USA
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Latek D, Pasznik P, Carlomagno T, Filipek S. Towards improved quality of GPCR models by usage of multiple templates and profile-profile comparison. PLoS One 2013; 8:e56742. [PMID: 23468878 PMCID: PMC3585245 DOI: 10.1371/journal.pone.0056742] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2012] [Accepted: 01/14/2013] [Indexed: 11/19/2022] Open
Abstract
UNLABELLED G-protein coupled receptors (GPCRs) are targets of nearly one third of the drugs at the current pharmaceutical market. Despite their importance in many cellular processes the crystal structures are available for less than 20 unique GPCRs of the Rhodopsin-like class. Fortunately, even though involved in different signaling cascades, this large group of membrane proteins has preserved a uniform structure comprising seven transmembrane helices that allows quite reliable comparative modeling. Nevertheless, low sequence similarity between the GPCR family members is still a serious obstacle not only in template selection but also in providing theoretical models of acceptable quality. An additional level of difficulty is the prediction of kinks and bulges in transmembrane helices. Usage of multiple templates and generation of alignments based on sequence profiles may increase the rate of success in difficult cases of comparative modeling in which the sequence similarity between GPCRs is exceptionally low. Here, we present GPCRM, a novel method for fast and accurate generation of GPCR models using averaging of multiple template structures and profile-profile comparison. In particular, GPCRM is the first GPCR structure predictor incorporating two distinct loop modeling techniques: Modeller and Rosetta together with the filtering of models based on the Z-coordinate. We tested our approach on all unique GPCR structures determined to date and report its performance in comparison with other computational methods targeting the Rhodopsin-like class. We also provide a database of precomputed GPCR models of the human receptors from that class. AVAILABILITY GPCRM SERVER AND DATABASE: http://gpcrm.biomodellab.eu.
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Affiliation(s)
- Dorota Latek
- International Institute of Molecular and Cell Biology, Warsaw, Poland
- * E-mail: (DL); (SF)
| | - Pawel Pasznik
- International Institute of Molecular and Cell Biology, Warsaw, Poland
| | - Teresa Carlomagno
- EMBL, Structural and Computational Biology Unit, Heidelberg, Germany
| | - Slawomir Filipek
- Faculty of Chemistry, University of Warsaw, Warsaw, Poland
- * E-mail: (DL); (SF)
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Perez-Aguilar JM, Saven JG, Liu R. Human μ Opioid Receptor Models with Evaluation of the Accuracy Using the Crystal Structure of the Murine μ Opioid Receptor. ACTA ACUST UNITED AC 2012; 3:218. [PMID: 24527268 PMCID: PMC3920553 DOI: 10.4172/2155-6148.1000218] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Models of the human μ opioid receptor were constructed using available G-protein-coupled receptor (GPCR) structures using homology (comparative) modeling techniques. The recent publication of a high-resolution crystal structure of a construct based on the murine μ opioid receptor offers a unique opportunity to evaluate the reliability of the homology models and test the relevance of introducing more templates (known structures) to increase the accuracy of the comparative models. In the first model two templates were used: the β2 adrenergic and bovine rhodopsin receptors. For the second model, four templates were utilized: the β2 adrenergic, bovine rhodopsin, β1 adrenergic, and A2A adenosine receptors. Including additional templates improved the accuracy of structural motifs and other features of the model when the same sequence alignment was used. The predicted structures were especially relevant in the case of important receptor regions such as the DRY motif, which has been associated with receptor activation. Additionally, this study showed that receptor sequence similarity is crucial in homology modeling, as indicated in the case of the highly diverse EC2 loop. This study demonstrates the reliability of the homology modeling technique in the case of the μ opioid receptor, a member of the rhodopsin-like family class of GPCRs. The addition of more templates improved the accuracy of the model. The findings regarding the modeling has significant implication to other GPCRs where the crystal structure is still unknown and suggest that homology modeling techniques can provide high quality structural models for interpreting experimental findings and formulating structurally based hypotheses regarding the activity of these important receptors.
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Affiliation(s)
| | - Jeffery G Saven
- Department of Chemistry, University of Pennsylvania, Philadelphia, 19104, USA
| | - Renyu Liu
- Department of Anesthesiology and Critical Care, Hospital of University of Pennsylvania, Philadelphia, 19104, USA
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Fanelli F, De Benedetti PG. Update 1 of: computational modeling approaches to structure-function analysis of G protein-coupled receptors. Chem Rev 2011; 111:PR438-535. [PMID: 22165845 DOI: 10.1021/cr100437t] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Francesca Fanelli
- Dulbecco Telethon Institute, University of Modena and Reggio Emilia, via Campi 183, 41125 Modena, Italy.
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Worth CL, Kreuchwig A, Kleinau G, Krause G. GPCR-SSFE: a comprehensive database of G-protein-coupled receptor template predictions and homology models. BMC Bioinformatics 2011; 12:185. [PMID: 21605354 PMCID: PMC3113946 DOI: 10.1186/1471-2105-12-185] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2010] [Accepted: 05/23/2011] [Indexed: 11/15/2022] Open
Abstract
Background G protein-coupled receptors (GPCRs) transduce a wide variety of extracellular signals to within the cell and therefore have a key role in regulating cell activity and physiological function. GPCR malfunction is responsible for a wide range of diseases including cancer, diabetes and hyperthyroidism and a large proportion of drugs on the market target these receptors. The three dimensional structure of GPCRs is important for elucidating the molecular mechanisms underlying these diseases and for performing structure-based drug design. Although structural data are restricted to only a handful of GPCRs, homology models can be used as a proxy for those receptors not having crystal structures. However, many researchers working on GPCRs are not experienced homology modellers and are therefore unable to benefit from the information that can be gleaned from such three-dimensional models. Here, we present a comprehensive database called the GPCR-SSFE, which provides initial homology models of the transmembrane helices for a large variety of family A GPCRs. Description Extending on our previous theoretical work, we have developed an automated pipeline for GPCR homology modelling and applied it to a large set of family A GPCR sequences. Our pipeline is a fragment-based approach that exploits available family A crystal structures. The GPCR-SSFE database stores the template predictions, sequence alignments, identified sequence and structure motifs and homology models for 5025 family A GPCRs. Users are able to browse the GPCR dataset according to their pharmacological classification or search for results using a UniProt entry name. It is also possible for a user to submit a GPCR sequence that is not contained in the database for analysis and homology model building. The models can be viewed using a Jmol applet and are also available for download along with the alignments. Conclusions The data provided by GPCR-SSFE are useful for investigating general and detailed sequence-structure-function relationships of GPCRs, performing structure-based drug design and for better understanding the molecular mechanisms underlying disease-associated mutations in GPCRs. The effectiveness of our multiple template and fragment approach is demonstrated by the accuracy of our predicted homology models compared to recently published crystal structures.
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Affiliation(s)
- Catherine L Worth
- Leibniz-Institut für Molekulare Pharmakologie, 13125 Berlin, Germany
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Levoin N, Calmels T, Krief S, Danvy D, Berrebi-Bertrand I, Lecomte JM, Schwartz JC, Capet M. Homology Model Versus X-ray Structure in Receptor-based Drug Design: A Retrospective Analysis with the Dopamine D3 Receptor. ACS Med Chem Lett 2011; 2:293-7. [PMID: 24900310 DOI: 10.1021/ml100288q] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2010] [Accepted: 01/28/2011] [Indexed: 12/19/2022] Open
Abstract
Structure-based design methods commonly used in medicinal chemistry rely on a three-dimensional representation of the receptor. However, few crystal structures are solved in comparison with the huge number of pharmaceutical targets. This often renders homology models the only information available. It is particularly true for G protein-coupled receptors (GPCRs), one of the most important targets for approved medicines and current drug discovery projects. However, very few studies have tested their validity in comparison with corresponding crystal structures, especially in a lead optimization perspective. The recent solving of dopamine D3 receptor crystal structure allowed us to assess our historical homology model. We performed a statistical analysis, by docking our in-house lead optimization library of 1500 molecules. We demonstrate here that the refined homology model suits at least as well as the X-ray structure. It is concluded that when the crystal structure of a given GPCR is not available, homology modeling can be an excellent surrogate to support drug discovery efforts.
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Affiliation(s)
- Nicolas Levoin
- Bioprojet-Biotech, 4 rue du Chesnay-Beauregard, 35762 Saint-Grégoire, France
| | - Thierry Calmels
- Bioprojet-Biotech, 4 rue du Chesnay-Beauregard, 35762 Saint-Grégoire, France
| | - Stéphane Krief
- Bioprojet-Biotech, 4 rue du Chesnay-Beauregard, 35762 Saint-Grégoire, France
| | - Denis Danvy
- Bioprojet-Biotech, 4 rue du Chesnay-Beauregard, 35762 Saint-Grégoire, France
| | | | | | | | - Marc Capet
- Bioprojet-Biotech, 4 rue du Chesnay-Beauregard, 35762 Saint-Grégoire, France
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