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Chan WKB, Carlson HA, Traynor JR. Application of Mixed-Solvent Molecular Dynamics Simulations for Prediction of Allosteric Sites on G Protein-Coupled Receptors. Mol Pharmacol 2023; 103:274-285. [PMID: 36868791 PMCID: PMC10166447 DOI: 10.1124/molpharm.122.000612] [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: 08/16/2022] [Revised: 12/30/2022] [Accepted: 01/23/2023] [Indexed: 03/05/2023] Open
Abstract
The development of small molecule allosteric modulators acting at G protein-coupled receptors (GPCRs) is becoming increasingly attractive. Such compounds have advantages over traditional drugs acting at orthosteric sites on these receptors, in particular target specificity. However, the number and locations of druggable allosteric sites within most clinically relevant GPCRs are unknown. In the present study, we describe the development and application of a mixed-solvent molecular dynamics (MixMD)-based method for the identification of allosteric sites on GPCRs. The method employs small organic probes with druglike qualities to identify druggable hotspots in multiple replicate short-timescale simulations. As proof of principle, we first applied the method retrospectively to a test set of five GPCRs (cannabinoid receptor type 1, C-C chemokine receptor type 2, M2 muscarinic receptor, P2Y purinoceptor 1, and protease-activated receptor 2) with known allosteric sites in diverse locations. This resulted in the identification of the known allosteric sites on these receptors. We then applied the method to the μ-opioid receptor. Several allosteric modulators for this receptor are known, although the binding sites for these modulators are not known. The MixMD-based method revealed several potential allosteric sites on the mu-opioid receptor. Implementation of the MixMD-based method should aid future efforts in the structure-based drug design of drugs targeting allosteric sites on GPCRs. SIGNIFICANCE STATEMENT: Allosteric modulation of G protein-coupled receptors (GPCRs) has the potential to provide more selective drugs. However, there are limited structures of GPCRs bound to allosteric modulators, and obtaining such structures is problematic. Current computational methods utilize static structures and therefore may not identify hidden or cryptic sites. Here we describe the use of small organic probes and molecular dynamics to identify druggable allosteric hotspots on GPCRs. The results reinforce the importance of protein dynamics in allosteric site identification.
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Affiliation(s)
- Wallace K B Chan
- Department of Pharmacology and Edward F. Domino Research Center (W.K.B.C., J.R.T.) and Department of Medicinal Chemistry (H.A.C., J.R.T.), University of Michigan, Ann Arbor, Michigan
| | - Heather A Carlson
- Department of Pharmacology and Edward F. Domino Research Center (W.K.B.C., J.R.T.) and Department of Medicinal Chemistry (H.A.C., J.R.T.), University of Michigan, Ann Arbor, Michigan
| | - John R Traynor
- Department of Pharmacology and Edward F. Domino Research Center (W.K.B.C., J.R.T.) and Department of Medicinal Chemistry (H.A.C., J.R.T.), University of Michigan, Ann Arbor, Michigan
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2
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Tu G, Xu B, Luo D, Liu J, Liu Z, Chen G, Xue W. Multi-state Model-Based Identification of Cryptic Allosteric Sites on Human Serotonin Transporter. ACS Chem Neurosci 2023; 14:1686-1694. [PMID: 37067527 DOI: 10.1021/acschemneuro.3c00155] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/18/2023] Open
Abstract
Serotonin transporter (SERT) plays a fundamental role in taking the synaptic cleft serotonin back to the presynaptic neuron. The discovery of allosteric SERT modulators represents the next-generation medication for psychiatric disorders such as depression. Here, based on the cryo-EM structures of ibogaine in complex with SERT in distinct conformations, the multiple functional structures of the transporter bound to serotonin, including outward-open (OOholo), outward-occluded (OCholo), and inward-open (IOholo and IOholo'), were carefully characterized by induced-fit docking Gaussian-accelerated molecular dynamics (IFD-GaMD) simulation and the free-energy landscape analysis. Further MM/GBSA binding free energy, per-residue contribution, and molecular interaction fingerprint calculations revealed the interaction variations of serotonin with SERT in functional structures, which confirmed the allostery of SERT during serotonin reuptake. Moreover, five unique cryptic allosteric sites, which are druggable and capable of targeting by small molecules, were identified on the characterized multistate structures. These results provide structural and energetic information for the molecular mechanism of serotonin reuptake and will provide opportunities for the development of novel therapeutics based on the identified new allosteric sites on SERT.
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Affiliation(s)
- Gao Tu
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Binbin Xu
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Ding Luo
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Jin Liu
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
| | - Zerong Liu
- Central Nervous System Drug Key Laboratory of Sichuan Province, Sichuan Credit Pharmaceutical CO., Ltd., Luzhou 646000, China
| | - Gang Chen
- Central Nervous System Drug Key Laboratory of Sichuan Province, Sichuan Credit Pharmaceutical CO., Ltd., Luzhou 646000, China
| | - Weiwei Xue
- Chongqing Key Laboratory of Natural Product Synthesis and Drug Research, School of Pharmaceutical Sciences, Chongqing University, Chongqing 401331, China
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3
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Shpakov AO. Allosteric Regulation of G-Protein-Coupled Receptors: From Diversity of Molecular Mechanisms to Multiple Allosteric Sites and Their Ligands. Int J Mol Sci 2023; 24:6187. [PMID: 37047169 PMCID: PMC10094638 DOI: 10.3390/ijms24076187] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/21/2023] [Accepted: 03/23/2023] [Indexed: 03/29/2023] Open
Abstract
Allosteric regulation is critical for the functioning of G protein-coupled receptors (GPCRs) and their signaling pathways. Endogenous allosteric regulators of GPCRs are simple ions, various biomolecules, and protein components of GPCR signaling (G proteins and β-arrestins). The stability and functional activity of GPCR complexes is also due to multicenter allosteric interactions between protomers. The complexity of allosteric effects caused by numerous regulators differing in structure, availability, and mechanisms of action predetermines the multiplicity and different topology of allosteric sites in GPCRs. These sites can be localized in extracellular loops; inside the transmembrane tunnel and in its upper and lower vestibules; in cytoplasmic loops; and on the outer, membrane-contacting surface of the transmembrane domain. They are involved in the regulation of basal and orthosteric agonist-stimulated receptor activity, biased agonism, GPCR-complex formation, and endocytosis. They are targets for a large number of synthetic allosteric regulators and modulators, including those constructed using molecular docking. The review is devoted to the principles and mechanisms of GPCRs allosteric regulation, the multiplicity of allosteric sites and their topology, and the endogenous and synthetic allosteric regulators, including autoantibodies and pepducins. The allosteric regulation of chemokine receptors, proteinase-activated receptors, thyroid-stimulating and luteinizing hormone receptors, and beta-adrenergic receptors are described in more detail.
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Affiliation(s)
- Alexander O Shpakov
- Sechenov Institute of Evolutionary Physiology and Biochemistry, Russian Academy of Sciences, 194223 St. Petersburg, Russia
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4
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Du Q, Tu G, Qian Y, Yang J, Yao X, Xue W. Unbiased molecular dynamics simulation of a first-in-class small molecule inhibitor binds to oncostatin M. Comput Biol Med 2023; 155:106709. [PMID: 36854228 DOI: 10.1016/j.compbiomed.2023.106709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/08/2023] [Accepted: 02/19/2023] [Indexed: 02/25/2023]
Abstract
Small molecule inhibitors (SMIs) targeting oncostatin M (OSM) signaling pathway represent new therapeutics to combat cancer, inflammatory bowel disease (IBD) and CNS disease. Recently, the first-in-class SMI named SMI-10B that target OSM and block its interaction with receptor (OSMR) were reported. However, the binding pocket and interaction mode of the compound on OSM remain poorly understood, which hampering the rational design of SMIs that target OSM. Here, using SMI-10B as a probe, the multiple pockets on OSM for small molecules binding were extensively explored by unbiased molecular dynamics (MD) simulations. Then, the near-native structure of the complex was identified by molecular mechanics generalized Born surface area (MM/GBSA) binding energy funnel. Moreover, the binding stabilities of the protein-ligand complexes in near- and non-native conformations were verified by additional independent MD runs and absolute free energy perturbation (FEP) calculation. In summary, the unique feature of SMI-10B spontaneously binds to OSM characterized here not only provide detailed information for understanding the molecular mechanism of SMI-10B binding to OSM, but also will facilitate the rational design of novel and more potent SMIs to block OSM signaling.
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Affiliation(s)
- Qingqing Du
- Depart of Pharmacy, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Gao Tu
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau, 999078, China
| | - Yan Qian
- Depart of Pharmacy, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
| | - Jingyi Yang
- School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China
| | - Xiaojun Yao
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau, 999078, China
| | - Weiwei Xue
- School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.
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5
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Zhao Y, Zhang J, Zhang H, Gu S, Deng Y, Tu Y, Hou T, Kang Y. Sigmoid Accelerated Molecular Dynamics: An Efficient Enhanced Sampling Method for Biosystems. J Phys Chem Lett 2023; 14:1103-1112. [PMID: 36700836 DOI: 10.1021/acs.jpclett.2c03688] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Gaussian accelerated molecular dynamics (GaMD) is recognized as a popular enhanced sampling method for tackling long-standing challenges in biomolecular simulations. Inspired by GaMD, Sigmoid accelerated molecular dynamics (SaMD) is proposed in this work by adding a Sigmoid boost potential to improve the balance between the highest acceleration and accurate reweighting. Compared with GaMD, SaMD extends the accessible time scale and improves the computational efficiency as tested in three tasks. In the alanine dipeptide task, SaMD can produce the free energy landscape with better accuracy and efficiency. In the chignolin folding task, the estimated Gibbs free energy difference can converge to the experimental value ∼30% faster. In the protein-ligand binding task, the bound conformations are closer to the crystal structure with a minimal ligand root-mean-square deviation of 1.7 Å. The binding of the ligand XK263 to the HIV protease is reproduced by SaMD in ∼60% less simulation time.
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Affiliation(s)
- Yihao Zhao
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
| | - Jintu Zhang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
- CarbonSilicon AI Technology Company, Ltd., Hangzhou310018, Zhejiang, China
| | - Haotian Zhang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
- CarbonSilicon AI Technology Company, Ltd., Hangzhou310018, Zhejiang, China
| | - Shukai Gu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
| | - Yafeng Deng
- CarbonSilicon AI Technology Company, Ltd., Hangzhou310018, Zhejiang, China
| | - Yaoquan Tu
- Division of Theoretical Chemistry and Biology, Department of Chemistry, KTH Royal Institute of Technology, 114 28Stockholm, Sweden
| | - Tingjun Hou
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
| | - Yu Kang
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou310058, Zhejiang, China
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6
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Wakefield AE, Bajusz D, Kozakov D, Keserű GM, Vajda S. Conservation of Allosteric Ligand Binding Sites in G-Protein Coupled Receptors. J Chem Inf Model 2022; 62:4937-4954. [PMID: 36195573 PMCID: PMC9847135 DOI: 10.1021/acs.jcim.2c00209] [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: 01/21/2023]
Abstract
Despite the growing number of G protein-coupled receptor (GPCR) structures, only 39 structures have been cocrystallized with allosteric inhibitors. These structures have been studied by protein mapping using the FTMap server, which determines the clustering of small organic probe molecules distributed on the protein surface. The method has found druggable sites overlapping with the cocrystallized allosteric ligands in 21 GPCR structures. Mapping of Alphafold2 generated models of these proteins confirms that the same sites can be identified without the presence of bound ligands. We then mapped the 394 GPCR X-ray structures available at the time of the analysis (September 2020). Results show that for each of the 21 structures with bound ligands there exist many other GPCRs that have a strong binding hot spot at the same location, suggesting potential allosteric sites in a large variety of GPCRs. These sites cluster at nine distinct locations, and each can be found in many different proteins. However, ligands binding at the same location generally show little or no similarity, and the amino acid residues interacting with these ligands also differ. Results confirm the possibility of specifically targeting these sites across GPCRs for allosteric modulation and help to identify the most likely binding sites among the limited number of potential locations. The FTMap server is available free of charge for academic and governmental use at https://ftmap.bu.edu/.
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Affiliation(s)
- Amanda E. Wakefield
- Department of Chemistry, Boston University, Boston, MA 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Dávid Bajusz
- Medicinal Chemistry Research Group, Research Center for Natural Sciences, H-1117 Budapest, Hungary
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook NY 11794
| | - György M Keserű
- Medicinal Chemistry Research Group, Research Center for Natural Sciences, H-1117 Budapest, Hungary
| | - Sandor Vajda
- Department of Chemistry, Boston University, Boston, MA 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
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7
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Wakefield AE, Kozakov D, Vajda S. Mapping the binding sites of challenging drug targets. Curr Opin Struct Biol 2022; 75:102396. [PMID: 35636004 PMCID: PMC9790766 DOI: 10.1016/j.sbi.2022.102396] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 04/20/2022] [Accepted: 04/25/2022] [Indexed: 02/03/2023]
Abstract
An increasing number of medically important proteins are challenging drug targets because their binding sites are too shallow or too polar, are cryptic and thus not detectable without a bound ligand or located in a protein-protein interface. While such proteins may not bind druglike small molecules with sufficiently high affinity, they are frequently druggable using novel therapeutic modalities. The need for such modalities can be determined by experimental or computational fragment based methods. Computational mapping by mixed solvent molecular dynamics simulations or the FTMap server can be used to determine binding hot spots. The strength and location of the hot spots provide very useful information for selecting potentially successful approaches to drug discovery.
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Affiliation(s)
- Amanda E. Wakefield
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215,Department of Chemistry, Boston University, Boston, Massachusetts 02215
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA NY, USA
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215,Department of Chemistry, Boston University, Boston, Massachusetts 02215
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8
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Casadó-Anguera V, Casadó V. Unmasking allosteric binding sites: Novel targets for GPCR drug discovery. Expert Opin Drug Discov 2022; 17:897-923. [PMID: 35649692 DOI: 10.1080/17460441.2022.2085684] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
INTRODUCTION Unexpected non-apparent and hidden allosteric binding sites are non-classical and non-apparent allosteric centers in 3-D X-ray protein structures until orthosteric or allosteric ligands bind to them. The orthosteric center of one protomer that modulates binding centers of the other protomers within an oligomer is also an unexpected allosteric site. Furthermore, another partner protein can also produce these effects, acting as an unexpected allosteric modulator. AREAS COVERED This review summarizes both classical and non-classical allosterism. The authors focus on G protein-coupled receptor (GPCR) oligomers as a paradigm of allosteric molecules. Moreover, they show several examples of unexpected allosteric sites such as hidden allosteric sites in a protomer that appear after the interaction with other molecules and the allosterism exerted between orthosteric sites within GPCR oligomer, emphasizing on the allosteric modulations that can occur between binding sites. EXPERT OPINION The study of these new non-classical allosteric sites will expand the diversity of allosteric control on the function of orthosteric sites within proteins, whether GPCRs or other receptors, enzymes or transporters. Moreover, the design of new drugs targeting these hidden allosteric sites or already known orthosteric sites acting as allosteric sites in protein homo- or hetero-oligomers will increase the therapeutic potential of allosterism.
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Affiliation(s)
- Verònica Casadó-Anguera
- Laboratory of Molecular Neuropharmacology, Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, and Institute of Biomedicine of the Universitat de Barcelona, Barcelona, Spain.,Laboratory of Neuropharmacology-Neurophar, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Vicent Casadó
- Laboratory of Molecular Neuropharmacology, Department of Biochemistry and Molecular Biomedicine, Faculty of Biology, Universitat de Barcelona, and Institute of Biomedicine of the Universitat de Barcelona, Barcelona, Spain
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9
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Martí D, Alemán C, Ainsley J, Ahumada O, Torras J. IgG1-b12-HIV-gp120 Interface in Solution: A Computational Study. J Chem Inf Model 2022; 62:359-371. [PMID: 34971312 PMCID: PMC8790758 DOI: 10.1021/acs.jcim.1c01143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Indexed: 11/29/2022]
Abstract
The use of broadly neutralizing antibodies against human immunodeficiency virus type 1 (HIV-1) has been shown to be a promising therapeutic modality in the prevention of HIV infection. Understanding the b12-gp120 binding mechanism under physiological conditions may assist the development of more broadly effective antibodies. In this work, the main conformations and interactions between the receptor-binding domain (RBD) of spike glycoprotein gp120 of HIV-1 and the IgG1-b12 mAb are studied. Accelerated molecular dynamics (aMD) and ab initio hybrid molecular dynamics have been combined to determine the most persistent interactions between the most populated conformations of the antibody-antigen complex under physiological conditions. The results show the most persistent receptor-binding mapping in the conformations of the antibody-antigen interface in solution. The binding-free-energy decomposition reveals a small enhancement in the contribution played by the CDR-H3 region to the b12-gp120 interface compared to the crystal structure.
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Affiliation(s)
- Didac Martí
- Department
of Chemical Engineering (EEBE), Universitat
Politècnica de Catalunya, C/Eduard Maristany 10-14, Ed I2, 08019 Barcelona, Spain
- Barcelona
Research Center for Multiscale Science and Engineering, Universitat Politècnica de Catalunya, C/Eduard Maristany 10-14, 08019 Barcelona, Spain
| | - Carlos Alemán
- Department
of Chemical Engineering (EEBE), Universitat
Politècnica de Catalunya, C/Eduard Maristany 10-14, Ed I2, 08019 Barcelona, Spain
- Barcelona
Research Center for Multiscale Science and Engineering, Universitat Politècnica de Catalunya, C/Eduard Maristany 10-14, 08019 Barcelona, Spain
- Institute
for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology, Baldiri Reixac 10-12, 08028 Barcelona, Spain
| | - Jon Ainsley
- Department
of Chemical Engineering (EEBE), Universitat
Politècnica de Catalunya, C/Eduard Maristany 10-14, Ed I2, 08019 Barcelona, Spain
- Evotec
Campus Curie, 195 Rte d’Espagne, 31100 Toulouse, Occitanie, France
| | - Oscar Ahumada
- Mecwins
S.L., Parque Científico de Madrid PTM, C/Santiago Grisolía 2,
Tres Cantos, Madrid 28760, Spain
| | - Juan Torras
- Department
of Chemical Engineering (EEBE), Universitat
Politècnica de Catalunya, C/Eduard Maristany 10-14, Ed I2, 08019 Barcelona, Spain
- Barcelona
Research Center for Multiscale Science and Engineering, Universitat Politècnica de Catalunya, C/Eduard Maristany 10-14, 08019 Barcelona, Spain
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10
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Kaushik AC, Sahi S, Wei DQ. Computational Methods for Structure-Based Drug Design Through System Biology. Methods Mol Biol 2022; 2385:161-174. [PMID: 34888721 DOI: 10.1007/978-1-0716-1767-0_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The advances in computational chemistry and biology, computer science, structural biology, and molecular biology go in parallel with the rapid progress in target-based systems. This technique has become a powerful tool in medicinal chemistry for the identification of hit molecules. The recent developments in target-based systems have played a major role in the creation of libraries of compounds, and it has also been widely applied for the design of molecular docking methods. The main advantage of this method is that it hits the fragment that has the strongest binding, has relatively small size, and leads to better compounds in terms of pharmacokinetic properties when compared with virtual screening (VS) and high-throughput screening (HTS) hits. De novo design is an essential aspect of target-based systems and requires the synthesis of chemical to allow the design of promising compound.
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Affiliation(s)
| | - Shakti Sahi
- School of Biotechnology, Gautam Buddha University, Greater Noida, India
| | - Dong-Qing Wei
- State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic & Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, People's Republic of China.
- Peng Cheng Laboratory, Shenzhen, Guangdong, People's Republic of China.
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11
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Rehman AU, Lu S, Khan AA, Khurshid B, Rasheed S, Wadood A, Zhang J. Hidden allosteric sites and De-Novo drug design. Expert Opin Drug Discov 2021; 17:283-295. [PMID: 34933653 DOI: 10.1080/17460441.2022.2017876] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Hidden allosteric sites are not visible in apo-crystal structures, but they may be visible in holo-structures when a certain ligand binds and maintains the ligand intended conformation. Several computational and experimental techniques have been used to investigate these hidden sites but identifying them remains a challenge. AREAS COVERED This review provides a summary of the many theoretical approaches for predicting hidden allosteric sites in disease-related proteins. Furthermore, promising cases have been thoroughly examined to reveal the hidden allosteric site and its modulator. EXPERT OPINION In the recent past, with the development in scientific techniques and bioinformatics tools, the number of drug targets for complex human diseases has significantly increased but unfortunately most of these targets are undruggable due to several reasons. Alternative strategies such as finding cryptic (hidden) allosteric sites are an attractive approach for exploitation of the discovery of new targets. These hidden sites are difficult to recognize compared to allosteric sites, mainly due to a lack of visibility in the crystal structure. In our opinion, after many years of development, MD simulations are finally becoming successful for obtaining a detailed molecular description of drug-target interaction.
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Affiliation(s)
- Ashfaq Ur Rehman
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Shaoyong Lu
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China
| | - Abdul Aziz Khan
- Bio-X Institutes, Key Laboratory for the Genetics of Development and Neuropsychiatric Disorders (Ministry of Education), Shanghai Key Laboratory of Psychotic Disorders, and Brain Science and Technology Research Center, Institute of Psychology and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - Beenish Khurshid
- Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan
| | - Salman Rasheed
- National Center for Bioinformatics, Quaid-e-Azam University, Islamabad, Pakistan
| | - Abdul Wadood
- Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan
| | - Jian Zhang
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Clinical and Fundamental Research Center, Renji Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China.,School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
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12
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Ciancetta A, Gill AK, Ding T, Karlov DS, Chalhoub G, McCormick PJ, Tikhonova IG. Probe Confined Dynamic Mapping for G Protein-Coupled Receptor Allosteric Site Prediction. ACS CENTRAL SCIENCE 2021; 7:1847-1862. [PMID: 34841058 PMCID: PMC8614102 DOI: 10.1021/acscentsci.1c00802] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Indexed: 05/06/2023]
Abstract
Targeting G protein-coupled receptors (GPCRs) through allosteric sites offers advantages over orthosteric sites in identifying drugs with increased selectivity and potentially reduced side effects. In this study, we developed a probe confined dynamic mapping protocol that allows the prediction of allosteric sites at both the GPCR extracellular and intracellular sides, as well as at the receptor-lipid interface. The applied harmonic wall potential enhanced sampling of probe molecules in a selected area of a GPCR while preventing membrane distortion in molecular dynamics simulations. The specific probes derived from GPCR allosteric ligand structures performed better in allosteric site mapping compared to commonly used cosolvents. The M2 muscarinic, β2 adrenergic, and P2Y1 purinergic receptors were selected for the protocol's retrospective validation. The protocol was next validated prospectively to locate the binding site of [5-fluoro-4-(hydroxymethyl)-2-methoxyphenyl]-(4-fluoro-1H-indol-1-yl)methanone at the D2 dopamine receptor, and subsequent mutagenesis confirmed the prediction. The protocol provides fast and efficient prediction of key amino acid residues surrounding allosteric sites in membrane proteins and facilitates the structure-based design of allosteric modulators.
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Affiliation(s)
- Antonella Ciancetta
- School
of Pharmacy, Medical Biology Centre, Queen’s
University Belfast, Belfast, Northern Ireland BT9 7BL, U.K.
| | - Amandeep Kaur Gill
- Centre
for Endocrinology, William Harvey Research Institute, Bart’s
and the London School of Medicine and Dentistry, Queen
Mary, University of London, London, EC1M 6BQ, U.K.
| | - Tianyi Ding
- School
of Pharmacy, Medical Biology Centre, Queen’s
University Belfast, Belfast, Northern Ireland BT9 7BL, U.K.
| | - Dmitry S. Karlov
- School
of Pharmacy, Medical Biology Centre, Queen’s
University Belfast, Belfast, Northern Ireland BT9 7BL, U.K.
| | - George Chalhoub
- Centre
for Endocrinology, William Harvey Research Institute, Bart’s
and the London School of Medicine and Dentistry, Queen
Mary, University of London, London, EC1M 6BQ, U.K.
| | - Peter J. McCormick
- Centre
for Endocrinology, William Harvey Research Institute, Bart’s
and the London School of Medicine and Dentistry, Queen
Mary, University of London, London, EC1M 6BQ, U.K.
| | - Irina G. Tikhonova
- School
of Pharmacy, Medical Biology Centre, Queen’s
University Belfast, Belfast, Northern Ireland BT9 7BL, U.K.
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13
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Martí D, Alsina M, Alemán C, Bertran O, Turon P, Torras J. Unravelling the molecular interactions between the SARS-CoV-2 RBD spike protein and various specific monoclonal antibodies. Biochimie 2021; 193:90-102. [PMID: 34710552 PMCID: PMC8545699 DOI: 10.1016/j.biochi.2021.10.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/08/2021] [Accepted: 10/21/2021] [Indexed: 02/09/2023]
Abstract
Vaccination against SARS-CoV-2 just started in most of the countries. However, the development of specific vaccines against SARS-CoV-2 is not the only approach to control the virus and monoclonal antibodies (mAbs) start to merit special attention as a therapeutic option to treat COVID-19 disease. Here, the main conformations and interactions between the receptor-binding domain (RBD) of spike glycoprotein of SARS-CoV-2 (S protein) with two mAbs (CR3022 and S309) and the ACE2 cell receptor are studied as the main representatives of three different epitopes on the RBD of S protein. The combined approach of 1 μs accelerated molecular dynamics (aMD) and ab-initio hybrid molecular dynamics is used to identify the most predominant interactions under physiological conditions. Results allow to determine the main receptor-binding mapping, hydrogen bonding network and salt bridges in the most populated antigen-antibody interface conformations. The deep knowledge on the protein-protein interactions involving mAbs and ACE2 receptor with the spike glycoprotein of SARS-CoV-2 increases background knowledge to speed up the development of new vaccines and therapeutic drugs.
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Affiliation(s)
- Didac Martí
- Departament d'Enginyeria Química, EEBE, Universitat Politècnica de Catalunya, C/ Eduard Maristany, 10-14, Ed. I2, 08019, Barcelona, Spain; Barcelona Research Center in Multiscale Science and Engineering, Universitat Politècnica de Catalunya, C/ Eduard Maristany, 10-14, 08019, Barcelona, Spain
| | - Marc Alsina
- Departament d'Enginyeria Química, EEBE, Universitat Politècnica de Catalunya, C/ Eduard Maristany, 10-14, Ed. I2, 08019, Barcelona, Spain
| | - Carlos Alemán
- Departament d'Enginyeria Química, EEBE, Universitat Politècnica de Catalunya, C/ Eduard Maristany, 10-14, Ed. I2, 08019, Barcelona, Spain; Barcelona Research Center in Multiscale Science and Engineering, Universitat Politècnica de Catalunya, C/ Eduard Maristany, 10-14, 08019, Barcelona, Spain.
| | - Oscar Bertran
- Departament de Física EETAC, Universitat Politècnica de Catalunya, c/ Esteve Terrades, 7, 08860, Castelldefels, Spain
| | - Pau Turon
- B. Braun Surgical, S.A.U. Carretera de Terrassa 121, 08191, Rubí (Barcelona), Spain.
| | - Juan Torras
- Departament d'Enginyeria Química, EEBE, Universitat Politècnica de Catalunya, C/ Eduard Maristany, 10-14, Ed. I2, 08019, Barcelona, Spain; Barcelona Research Center in Multiscale Science and Engineering, Universitat Politècnica de Catalunya, C/ Eduard Maristany, 10-14, 08019, Barcelona, Spain.
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14
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Bartuzi D, Wróbel TM, Kaczor AA, Matosiuk D. Tuning Down the Pain - An Overview of Allosteric Modulation of Opioid Receptors: Mechanisms of Modulation, Allosteric Sites, Modulator Syntheses. Curr Top Med Chem 2020; 20:2852-2865. [PMID: 32479245 DOI: 10.2174/1568026620666200601155451] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 04/16/2020] [Accepted: 04/22/2020] [Indexed: 01/09/2023]
Abstract
Opioid signaling plays a central role in pain perception. As such, it remains the main target in the development of antinociceptive agents, despite serious side effects involved. In recent years, hopes for improved opioid painkillers are rising, together with our understanding of allosterism and biased signaling mechanisms. In this review, we focus on recently discovered allosteric modulators of opioid receptors, insights into phenomena underlying their action, as well as on how they extend our understanding of mechanisms of previously known compounds. A brief overlook of their synthesis is also presented.
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Affiliation(s)
- Damian Bartuzi
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modelling Lab, Medical University of Lublin, Lublin, Poland
| | - Tomasz M Wróbel
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modelling Lab, Medical University of Lublin, Lublin, Poland
| | - Agnieszka A Kaczor
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modelling Lab, Medical University of Lublin, Lublin, Poland
| | - Dariusz Matosiuk
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modelling Lab, Medical University of Lublin, Lublin, Poland
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15
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Li Q, Luo R, Chen HF. Dynamical important residue network (DIRN): network inference via conformational change. Bioinformatics 2019; 35:4664-4670. [PMID: 31038692 PMCID: PMC6853687 DOI: 10.1093/bioinformatics/btz298] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Revised: 03/19/2019] [Accepted: 04/18/2019] [Indexed: 01/18/2023] Open
Abstract
MOTIVATION Protein residue interaction network has emerged as a useful strategy to understand the complex relationship between protein structures and functions and how functions are regulated. In a residue interaction network, every residue is used to define a network node, adding noises in network post-analysis and increasing computational burden. In addition, dynamical information is often necessary in deciphering biological functions. RESULTS We developed a robust and efficient protein residue interaction network method, termed dynamical important residue network, by combining both structural and dynamical information. A major departure from previous approaches is our attempt to identify important residues most important for functional regulation before a network is constructed, leading to a much simpler network with the important residues as its nodes. The important residues are identified by monitoring structural data from ensemble molecular dynamics simulations of proteins in different functional states. Our tests show that the new method performs well with overall higher sensitivity than existing approaches in identifying important residues and interactions in tested proteins, so it can be used in studies of protein functions to provide useful hypotheses in identifying key residues and interactions. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Quan Li
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Ray Luo
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697, USA
- Department of Chemical and Biomolecular Engineering, University of California, Irvine, CA 92697, USA
- Department of Materials Science and Engineering, University of California, Irvine, CA 92697, USA
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, USA
- Department of Chemistry, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
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16
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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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17
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Analysis of tractable allosteric sites in G protein-coupled receptors. Sci Rep 2019; 9:6180. [PMID: 30992500 PMCID: PMC6467999 DOI: 10.1038/s41598-019-42618-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 03/28/2019] [Indexed: 11/21/2022] Open
Abstract
Allosteric modulation of G protein-coupled receptors represent a promising mechanism of pharmacological intervention. Dramatic developments witnessed in the structural biology of membrane proteins continue to reveal that the binding sites of allosteric modulators are widely distributed, including along protein surfaces. Here we restrict consideration to intrahelical and intracellular sites together with allosteric conformational locks, and show that the protein mapping tools FTMap and FTSite identify 83% and 88% of such experimentally confirmed allosteric sites within the three strongest sites found. The methods were also able to find partially hidden allosteric sites that were not fully formed in X-ray structures crystallized in the absence of allosteric ligands. These results confirm that the intrahelical sites capable of binding druglike allosteric modulators are among the strongest ligand recognition sites in a large fraction of GPCRs and suggest that both FTMap and FTSite are useful tools for identifying allosteric sites and to aid in the design of such compounds in a range of GPCR targets.
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18
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Wu Y, Tong J, Ding K, Zhou Q, Zhao S. GPCR Allosteric Modulator Discovery. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1163:225-251. [PMID: 31707706 DOI: 10.1007/978-981-13-8719-7_10] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
G protein-coupled receptors (GPCRs) influence virtually every aspect of human physiology; about one-third of all marketed drugs target members of this family. GPCR allosteric ligands hold the promise of improved subtype selectivity, spatiotemporal sensitivity, and possible biased property over typical orthosteric ligands. However, only a small number of GPCR allosteric ligands have been approved as drugs or in clinical trials since the discovery process is very challenging. The rapid development of GPCR structural biology leads to the discovery of several allosteric sites and sheds light on understanding the mechanism of GPCR allosteric ligands, which is critical for discovering novel therapeutics. This book chapter summarized different GPCR allosteric modulating mechanisms and discussed validated mechanisms based on allosteric modulator-GPCR complex structures.
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Affiliation(s)
- Yiran Wu
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Jiahui Tong
- iHuman Institute, ShanghaiTech University, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Kang Ding
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Qingtong Zhou
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Suwen Zhao
- iHuman Institute, ShanghaiTech University, Shanghai, China. .,School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
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19
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Ortiz Zacarías NV, Lenselink EB, IJzerman AP, Handel TM, Heitman LH. Intracellular Receptor Modulation: Novel Approach to Target GPCRs. Trends Pharmacol Sci 2018; 39:547-559. [PMID: 29653834 DOI: 10.1016/j.tips.2018.03.002] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 03/07/2018] [Accepted: 03/08/2018] [Indexed: 12/23/2022]
Abstract
Recent crystal structures of multiple G protein-coupled receptors (GPCRs) have revealed a highly conserved intracellular pocket that can be used to modulate these receptors from the inside. This novel intracellular site partially overlaps with the G protein and β-arrestin binding site, providing a new manner of pharmacological intervention. Here we provide an update of the architecture and function of the intracellular region of GPCRs, until now portrayed as the signaling domain. We review the available evidence on the presence of intracellular binding sites among chemokine receptors and other class A GPCRs, as well as different strategies to target it, including small molecules, pepducins, and nanobodies. Finally, the potential advantages of intracellular (allosteric) ligands over orthosteric ligands are also discussed.
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Affiliation(s)
- Natalia V Ortiz Zacarías
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Eelke B Lenselink
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Adriaan P IJzerman
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Tracy M Handel
- University of California, San Diego, Skaggs School of Pharmacy and Pharmaceutical Sciences, La Jolla, CA 92093, USA
| | - Laura H Heitman
- Division of Drug Discovery and Safety, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
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20
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Lu S, Zhang J. Small Molecule Allosteric Modulators of G-Protein-Coupled Receptors: Drug–Target Interactions. J Med Chem 2018; 62:24-45. [DOI: 10.1021/acs.jmedchem.7b01844] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Shaoyong Lu
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China
| | - Jian Zhang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, School of Medicine, Shanghai Jiao Tong University, Shanghai 200025, China
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21
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Velazquez HA, Riccardi D, Xiao Z, Quarles LD, Yates CR, Baudry J, Smith JC. Ensemble docking to difficult targets in early-stage drug discovery: Methodology and application to fibroblast growth factor 23. Chem Biol Drug Des 2018; 91:491-504. [PMID: 28944571 PMCID: PMC7983124 DOI: 10.1111/cbdd.13110] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 08/30/2017] [Accepted: 09/02/2017] [Indexed: 12/23/2022]
Abstract
Ensemble docking is now commonly used in early-stage in silico drug discovery and can be used to attack difficult problems such as finding lead compounds which can disrupt protein-protein interactions. We give an example of this methodology here, as applied to fibroblast growth factor 23 (FGF23), a protein hormone that is responsible for regulating phosphate homeostasis. The first small-molecule antagonists of FGF23 were recently discovered by combining ensemble docking with extensive experimental target validation data (Science Signaling, 9, 2016, ra113). Here, we provide a detailed account of how ensemble-based high-throughput virtual screening was used to identify the antagonist compounds discovered in reference (Science Signaling, 9, 2016, ra113). Moreover, we perform further calculations, redocking those antagonist compounds identified in reference (Science Signaling, 9, 2016, ra113) that performed well on drug-likeness filters, to predict possible binding regions. These predicted binding modes are rescored with the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) approach to calculate the most likely binding site. Our findings suggest that the antagonist compounds antagonize FGF23 through the disruption of protein-protein interactions between FGF23 and fibroblast growth factor receptor (FGFR).
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Affiliation(s)
- Hector A. Velazquez
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Demian Riccardi
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Zhousheng Xiao
- Department of Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Leigh Darryl Quarles
- Department of Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Charless Ryan Yates
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jerome Baudry
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Jeremy C. Smith
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
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22
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Sabatucci A, Tortolani D, Dainese E, Maccarrone M. In silico mapping of allosteric ligand binding sites in type-1 cannabinoid receptor. Biotechnol Appl Biochem 2018; 65:21-28. [PMID: 28833445 DOI: 10.1002/bab.1589] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 08/13/2017] [Indexed: 12/18/2022]
Abstract
The recent resolution of the crystal structure of type-1 cannabinoid receptor (CB1 ) and the discovery of novel modulators for this target open the way to the possibility of elucidating the structural requirements for CB1 binding, and thereby facilitate a rational drug design. Compounds that target the orthosteric site of CB1 in some cases have shown side effects. Allosteric modulators could potentially avoid these side effects by influencing binding and/or efficacy of orthosteric ligands. Here, we summarize and compare previous data on different putative allosteric binding sites observed in CB1 homology models with an in silico docking study of the recently published crystal structure of the same receptor on endogenous and natural hydrophobic ligands that act as positive allosteric modulators and negative allosteric modulators of CB1 . In particular, a lipid-exposed pocket targeted by most of the tested molecules is reported and discussed.
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Affiliation(s)
- Annalaura Sabatucci
- Faculty of Bioscience and Technology for Food Agriculture and Environment, University of Teramo, Teramo, Italy
| | - Daniel Tortolani
- Faculty of Veterinary Medicine, University of Teramo, Teramo, Italy
| | - Enrico Dainese
- Faculty of Bioscience and Technology for Food Agriculture and Environment, University of Teramo, Teramo, Italy.,European Center for Brain Research (CERC)/Santa Lucia Foundation IRCCS, Rome, Italy
| | - Mauro Maccarrone
- European Center for Brain Research (CERC)/Santa Lucia Foundation IRCCS, Rome, Italy.,Department of Medicine, Campus Bio-Medico University of Rome, Rome, Italy
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23
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Caliman AD, Miao Y, McCammon JA. Mapping the allosteric sites of the A 2A adenosine receptor. Chem Biol Drug Des 2018; 91:5-16. [PMID: 28639411 PMCID: PMC5741531 DOI: 10.1111/cbdd.13053] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Revised: 05/19/2017] [Accepted: 06/05/2017] [Indexed: 12/16/2022]
Abstract
The A2A adenosine receptor (A2A AR) is a G protein-coupled receptor that is pharmacologically targeted for the treatment of inflammation, sepsis, cancer, neurodegeneration, and Parkinson's disease. Recently, we applied long-timescale molecular dynamics simulations on two ligand-free receptor conformations, starting from the agonist-bound (PDB ID: 3QAK) and antagonist-bound (PDB ID: 3EML) X-ray structures. This analysis revealed four distinct conformers of the A2A AR: the active, intermediate 1, intermediate 2, and inactive. In this study, we apply the fragment-based mapping algorithm, FTMap, on these receptor conformations to uncover five non-orthosteric sites on the A2A AR. Two sites that are identified in the active conformation are located in the intracellular region of the transmembrane helices (TM) 3/TM4 and the G protein-binding site in the intracellular region between TM2/TM3/TM6/TM7. Three sites are identified in the intermediate 1 and intermediate 2 conformations, annexing a site in the lipid interface of TM5/TM6. Five sites are identified in the inactive conformation, comprising a site in the intracellular region of TM1/TM7 and in the extracellular region of TM3/TM4 of the A2A AR. We postulate that these sites on the A2A AR be screened for allosteric modulators for the treatment of inflammatory and neurological diseases.
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Affiliation(s)
- Alisha D Caliman
- Department of Pharmacology, University of California at San Diego, La Jolla, CA, USA
| | - Yinglong Miao
- Department of Pharmacology, University of California at San Diego, La Jolla, CA, USA
- Howard Hughes Medical Institute, University of California at San Diego, La Jolla, CA, USA
| | - James A McCammon
- Department of Pharmacology, University of California at San Diego, La Jolla, CA, USA
- Howard Hughes Medical Institute, University of California at San Diego, La Jolla, CA, USA
- Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, CA, USA
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24
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Abstract
Binding site identification and druggability evaluation are two essential steps in structure-based drug design. A druggable binding site tends to have high binding affinity to drug-like molecules. Predicting such sites can have a significant impact on a drug design campaign. This chapter focuses on summarizing the different methods that are used to predict druggable binding sites. The chapter also discusses the importance of including protein flexibility in the search process and the use of molecular dynamics simulations to address this aspect. Case studies from the literature are also summarized and discussed. We hope that this chapter would provide an overview on the different methods employed in binding site identification evaluation.
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Affiliation(s)
- Tianhua Feng
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada
| | - Khaled Barakat
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada.
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25
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Li Y, Yin C, Liu P, Li D, Lin J. Identification of a Different Agonist-Binding Site and Activation Mechanism of the Human P2Y 1 Receptor. Sci Rep 2017; 7:13764. [PMID: 29062134 PMCID: PMC5653743 DOI: 10.1038/s41598-017-14268-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Accepted: 10/09/2017] [Indexed: 02/03/2023] Open
Abstract
The human P2Y1 receptor (P2Y1R) is a purinergic G-protein-coupled receptor (GPCR) that functions as a receptor for adenosine 5'-diphosphate (ADP). An antagonist of P2Y1R might potentially have antithrombotic effects, whereas agonists might serve as antidiabetic agents. On the basis of the antagonist-bound MRS2500-P2Y1R crystal structure, we constructed computational models of apo-P2Y1R and the agonist-receptor complex 2MeSADP-P2Y1R. We then performed conventional molecular dynamics (cMD) and accelerated molecular dynamics (aMD) simulations to study the conformational dynamics after binding with agonist/antagonist as well as the P2Y1R activation mechanism. We identified a new agonist-binding site of P2Y1R that is consistent with previous mutagenesis data. This new site is deeper than those of the agonist ADP in the recently simulated ADP-P2Y1R structure and the antagonist MRS2500 in the MRS2500-P2Y1R crystal structure. During P2Y1R activation, the cytoplasmic end of helix VI shifts outward 9.1 Å, the Ser1463.47-Tyr2375.58 hydrogen bond breaks, a Tyr2375.58-Val2626.37 hydrogen bond forms, and the conformation of the χ1 rotamer of Phe2696.44 changes from parallel to perpendicular to helix VI. The apo-P2Y1R system and the MRS2500-P2Y1R system remain inactive. The newly identified agonist binding site and activation mechanism revealed in this study may aid in the design of P2Y1R antagonists/agonists as antithrombotic/antidiabetic agents, respectively.
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Affiliation(s)
- Yang Li
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin, 300353, China
| | - Can Yin
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin, 300353, China
- Pharmaceutical Intelligence Platform, Tianjin Joint Academy of Biomedicine and Technology, Tianjin, 300457, China
| | - Pi Liu
- Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China
| | - Dongmei Li
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin, 300353, China.
| | - Jianping Lin
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin, 300353, China.
- Pharmaceutical Intelligence Platform, Tianjin Joint Academy of Biomedicine and Technology, Tianjin, 300457, China.
- Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
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26
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Schrage R, Kostenis E. Functional selectivity and dualsteric/bitopic GPCR targeting. Curr Opin Pharmacol 2017; 32:85-90. [DOI: 10.1016/j.coph.2016.12.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Revised: 12/09/2016] [Accepted: 12/11/2016] [Indexed: 12/12/2022]
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27
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Xiao Z, Riccardi D, Velazquez HA, Chin AL, Yates CR, Carrick JD, Smith JC, Baudry J, Quarles LD. A computationally identified compound antagonizes excess FGF-23 signaling in renal tubules and a mouse model of hypophosphatemia. Sci Signal 2016; 9:ra113. [PMID: 27879395 PMCID: PMC6544179 DOI: 10.1126/scisignal.aaf5034] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Fibroblast growth factor-23 (FGF-23) interacts with a binary receptor complex composed of α-Klotho (α-KL) and FGF receptors (FGFRs) to regulate phosphate and vitamin D metabolism in the kidney. Excess FGF-23 production, which causes hypophosphatemia, is genetically inherited or occurs with chronic kidney disease. Among other symptoms, hypophosphatemia causes vitamin D deficiency and the bone-softening disorder rickets. Current therapeutics that target the receptor complex have limited utility clinically. Using a computationally driven, structure-based, ensemble docking and virtual high-throughput screening approach, we identified four novel compounds predicted to selectively inhibit FGF-23-induced activation of the FGFR/α-KL complex. Additional modeling and functional analysis found that Zinc13407541 bound to FGF-23 and disrupted its interaction with the FGFR1/α-KL complex; experiments in a heterologous cell expression system showed that Zinc13407541 selectivity inhibited α-KL-dependent FGF-23 signaling. Zinc13407541 also inhibited FGF-23 signaling in isolated renal tubules ex vivo and partially reversed the hypophosphatemic effects of excess FGF-23 in a mouse model. These chemical probes provide a platform to develop lead compounds to treat disorders caused by excess FGF-23.
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Affiliation(s)
- Zhousheng Xiao
- Department of Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38165, USA
| | - Demian Riccardi
- Department of Chemistry, Earlham College, 801 National Road West, Richmond, IN 47374, USA
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| | - Hector A Velazquez
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
- Department of Chemistry, Tennessee Technological University, 55 University Drive, Cookeville, TN 38501, USA
| | - Ai L Chin
- University of Tennessee/Oak Ridge National Laboratory Center for Molecular Biophysics, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830, USA
| | - Charles R Yates
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Jesse D Carrick
- University of Tennessee/Oak Ridge National Laboratory Center for Molecular Biophysics, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN 37830, USA
| | - Jeremy C Smith
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
- Department of Chemistry, Tennessee Technological University, 55 University Drive, Cookeville, TN 38501, USA
| | - Jerome Baudry
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
- Department of Chemistry, Tennessee Technological University, 55 University Drive, Cookeville, TN 38501, USA
| | - L Darryl Quarles
- Department of Medicine, College of Medicine, University of Tennessee Health Science Center, Memphis, TN 38165, USA.
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28
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Zheng L, Lin VC, Mu Y. Exploring Flexibility of Progesterone Receptor Ligand Binding Domain Using Molecular Dynamics. PLoS One 2016; 11:e0165824. [PMID: 27824891 PMCID: PMC5100906 DOI: 10.1371/journal.pone.0165824] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Accepted: 10/18/2016] [Indexed: 12/23/2022] Open
Abstract
Progesterone receptor (PR), a member of nuclear receptor (NR) superfamily, plays a vital role for female reproductive tissue development, differentiation and maintenance. PR ligand, such as progesterone, induces conformation changes in PR ligand binding domain (LBD), thus mediates subsequent gene regulation cascades. PR LBD may adopt different conformations upon an agonist or an antagonist binding. These different conformations would trigger distinct transcription events. Therefore, the dynamics of PR LBD would be of general interest to biologists for a deep understanding of its structure-function relationship. However, no apo-form (non-ligand bound) of PR LBD model has been proposed either by experiments or computational methods so far. In this study, we explored the structural dynamics of PR LBD using molecular dynamics simulations and advanced sampling tools in both ligand-bound and the apo-forms. Resolved by the simulation study, helix 11, helix 12 and loop 895–908 (the loop between these two helices) are quite flexible in antagonistic conformation. Several residues, such as Arg899 and Glu723, could form salt-bridging interaction between helix 11 and helix 3, and are important for the PR LBD dynamics. And we also propose that helix 12 in apo-form PR LBD, not like other NR LBDs, such as human estrogen receptor α (ERα) LBD, may not adopt a totally extended conformation. With the aid of umbrella sampling and metadynamics simulations, several stable conformations of apo-form PR LBD have been sampled, which may work as critical structural models for further large scale virtual screening study to discover novel PR ligands for therapeutic application.
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Affiliation(s)
- Liangzhen Zheng
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
| | - Valerie Chunling Lin
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
| | - Yuguang Mu
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
- * E-mail:
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29
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Janero DR, Thakur GA. Leveraging allostery to improve G protein-coupled receptor (GPCR)-directed therapeutics: cannabinoid receptor 1 as discovery target. Expert Opin Drug Discov 2016; 11:1223-1237. [PMID: 27712124 DOI: 10.1080/17460441.2016.1245289] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
INTRODUCTION Allosteric modulators of G-protein coupled receptors (GPCRs) hold the promise of improved pharmacology and safety over typical orthosteric GPCR ligands. These features are particularly relevant to the cannabinoid receptor 1 (CB1R) GPCR, since typical orthosteric CB1R ligands are associated with adverse events that limit their translational potential. Areas covered: The contextual basis for applying allostery to CB1R is considered from pharmacological, drug-discovery, and medicinal standpoints. Rational design of small-molecule CB1R allosteric modulators as potential pharmacotherapeutics would be greatly facilitated by direct experimental characterization of structure-function correlates underlying the biological activity of chemically-diverse CB1R allosteric modulators, CB1R allosteric ligand-binding binding pockets, and amino acid contact residues critical to allosteric ligand engagement and activity. In these regards, designer covalent probes exhibiting well-characterized molecular pharmacology as CB1R allosteric modulators are emerging as valuable molecular reporters enabling experimental interrogation of CB1R allosteric site(s) and informing the design of new CB1R agents as drugs. Expert opinion: Synthesis and pharmacological profiling of CB1R allosteric ligands will continue to provide valuable insights into CB1R structure-function correlates. The resulting data should expand the repertoire of novel agents capable of exerting therapeutic benefit by modulating CB1R-dependent signaling.
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Affiliation(s)
- David R Janero
- a Center for Drug Discovery; Department of Pharmaceutical Sciences, School of Pharmacy, Bouvé College of Health Sciences; Department of Chemistry and Chemical Biology, College of Science; and Health Sciences Entrepreneurs , Northeastern University , Boston , MA , USA
| | - Ganesh A Thakur
- b Department of Pharmaceutical Sciences, School of Pharmacy, Bouvé College of Health Sciences , Northeastern University , Boston , MA , USA
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30
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Ma X, Meng H, Lai L. Motions of Allosteric and Orthosteric Ligand-Binding Sites in Proteins are Highly Correlated. J Chem Inf Model 2016; 56:1725-33. [DOI: 10.1021/acs.jcim.6b00039] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Xiaomin Ma
- Center for Quantitative Biology, ‡BNLMS, State Key
Laboratory for Structural
Chemistry of Unstable and Stable Species, College of Chemistry and
Molecular Engineering, and §Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Hu Meng
- Center for Quantitative Biology, ‡BNLMS, State Key
Laboratory for Structural
Chemistry of Unstable and Stable Species, College of Chemistry and
Molecular Engineering, and §Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Luhua Lai
- Center for Quantitative Biology, ‡BNLMS, State Key
Laboratory for Structural
Chemistry of Unstable and Stable Species, College of Chemistry and
Molecular Engineering, and §Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
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Accelerated structure-based design of chemically diverse allosteric modulators of a muscarinic G protein-coupled receptor. Proc Natl Acad Sci U S A 2016; 113:E5675-84. [PMID: 27601651 DOI: 10.1073/pnas.1612353113] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Design of ligands that provide receptor selectivity has emerged as a new paradigm for drug discovery of G protein-coupled receptors, and may, for certain families of receptors, only be achieved via identification of chemically diverse allosteric modulators. Here, the extracellular vestibule of the M2 muscarinic acetylcholine receptor (mAChR) is targeted for structure-based design of allosteric modulators. Accelerated molecular dynamics (aMD) simulations were performed to construct structural ensembles that account for the receptor flexibility. Compounds obtained from the National Cancer Institute (NCI) were docked to the receptor ensembles. Retrospective docking of known ligands showed that combining aMD simulations with Glide induced fit docking (IFD) provided much-improved enrichment factors, compared with the Glide virtual screening workflow. Glide IFD was thus applied in receptor ensemble docking, and 38 top-ranked NCI compounds were selected for experimental testing. In [(3)H]N-methylscopolamine radioligand dissociation assays, approximately half of the 38 lead compounds altered the radioligand dissociation rate, a hallmark of allosteric behavior. In further competition binding experiments, we identified 12 compounds with affinity of ≤30 μM. With final functional experiments on six selected compounds, we confirmed four of them as new negative allosteric modulators (NAMs) and one as positive allosteric modulator of agonist-mediated response at the M2 mAChR. Two of the NAMs showed subtype selectivity without significant effect at the M1 and M3 mAChRs. This study demonstrates an unprecedented successful structure-based approach to identify chemically diverse and selective GPCR allosteric modulators with outstanding potential for further structure-activity relationship studies.
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Vaidehi N, Bhattacharya S. Allosteric communication pipelines in G-protein-coupled receptors. Curr Opin Pharmacol 2016; 30:76-83. [PMID: 27497048 DOI: 10.1016/j.coph.2016.07.010] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Revised: 07/12/2016] [Accepted: 07/14/2016] [Indexed: 11/29/2022]
Abstract
The binding of ligands to G-protein-coupled receptors (GPCRs) in the extracellular region transmits the signal to the intracellular region to initiate coupling to effector proteins. The mechanism of this allosteric communication remains largely unexplored. Knowledge of the residues involved in the pipeline of the allosteric communication from the extracellular to the intracellular region will provide means to (a) design ligands with bias in potency towards one signaling pathway over others, and (b) design allosteric modulators that show subtype selectivity in GPCRs. In this review we describe the current state of the computational methods that provide insights into the allosteric communication in GPCRs and elucidate how this information can be used to design allosteric modulators.
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Affiliation(s)
- Nagarajan Vaidehi
- Department of Molecular Immunology, Beckman Research Institute of the City of Hope, 1500 East Duarte Road, Duarte, CA 91010, USA.
| | - Supriyo Bhattacharya
- Department of Molecular Immunology, Beckman Research Institute of the City of Hope, 1500 East Duarte Road, Duarte, CA 91010, USA
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33
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G-protein coupled receptors: advances in simulation and drug discovery. Curr Opin Struct Biol 2016; 41:83-89. [PMID: 27344006 DOI: 10.1016/j.sbi.2016.06.008] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2016] [Accepted: 06/07/2016] [Indexed: 11/21/2022]
Abstract
G-protein coupled receptors (GPCRs), the largest family of human membrane proteins, mediate cellular signaling and represent primary targets of about one third of currently marketed drugs. GPCRs undergo highly dynamic structural transitions during signal transduction, from binding of extracellular ligands to coupling with intracellular effector proteins. Molecular dynamics (MD) simulations have been utilized to investigate GPCR signaling mechanisms (such as pathways of ligand binding and receptor activation/deactivation) and to design novel small-molecule drug candidates. Future research directions point towards modeling cooperative binding of multiple orthosteric and allosteric ligands to GPCRs, GPCR oligomerization and interactions of GPCRs with different intracellular signaling proteins. Through methodological and supercomputing advances, MD simulations will continue to provide important insights into GPCR signaling mechanisms and further facilitate structure-based drug design.
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Li Y, Sun J, Li D, Lin J. Activation and conformational dynamics of a class B G-protein-coupled glucagon receptor. Phys Chem Chem Phys 2016; 18:12642-50. [PMID: 27094704 DOI: 10.1039/c6cp00798h] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The human glucagon receptor (GCGR) is a class B G-protein-coupled receptor (GPCR). The GCGR can be activated by glucagon and regulates the release of glucose. The GCGR has been proposed to be an important drug target for type 2 diabetes. Based on the structural model of a full-length glucagon-bound GCGR (glu-GCGR), we performed accelerated molecular dynamics (aMD) simulations, potential of mean force (PMF) calculations, cross-correlation analysis and community network analysis to study the activation mechanism and the conformational dynamics during the activation process. The PMF map depicts three different conformational states of the GCGR: the inactive, intermediate and active states. The activation of the GCGR is characterized by the outward movement of the intracellular side of helix VI. In the active state of the GCGR, the Arg173(2.46)-Ser350(6.41) and Glu245(3.50)-Thr351(6.42) hydrogen bonds break, and the χ1 rotamer of Phe322(5.54) changes from perpendicular to parallel to helix VI. The binding of the agonist glucagon decreases the correlated motions of the extracellular loops (ELCs) and the helices around the glucagon-binding site. During the activation of the GCGR, the connections between the intracellular sides of helices become weaker, and the connections between glucagon and ECLs and the extracellular sides of helices become stronger. These facilitate G-protein coupling on the intracellular side and glucagon binding on the extracellular side, and stabilize the GCGR in the active state. We expect that this study can provide useful information on the activation mechanism of the GCGR and facilitate the future design of GCGR inhibitors.
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Affiliation(s)
- Yang Li
- State Key Laboratory of Medicinal Chemical Biology, College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research, Nankai University, Haihe Education Park, 38 Tongyan Road, Tianjin 300353, People's Republic of China.
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Núñez-Vivanco G, Valdés-Jiménez A, Besoaín F, Reyes-Parada M. Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach. J Cheminform 2016; 8:19. [PMID: 27092185 PMCID: PMC4834829 DOI: 10.1186/s13321-016-0131-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 04/04/2016] [Indexed: 11/15/2022] Open
Abstract
Background Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures. Results Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility of Geomfinder, which was able to discriminate between similar and different 3D patterns related to binding sites of common substrates in a range of diverse proteins. Conclusions Geomfinder allows detecting similar 3D patterns between any two pair of protein structures, regardless of the divergency among their amino acids sequences. Although the software is not intended for simultaneous multiple comparisons in a large number of proteins, it can be particularly useful in cases such as the structure-based design of multitarget drugs, where a detailed analysis of 3D patterns similarities between a few selected protein targets is essential. Electronic supplementary material The online version of this article (doi:10.1186/s13321-016-0131-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gabriel Núñez-Vivanco
- Escuela de Ingeniería Civil en Bioinformática, Universidad de Talca, Avenida Lircay s/n, Talca, Chile ; Centro de Bioinformática y Simulación Molecular, Universidad de Talca, 2 Norte 685, Talca, Chile
| | - Alejandro Valdés-Jiménez
- Escuela de Ingeniería Civil en Bioinformática, Universidad de Talca, Avenida Lircay s/n, Talca, Chile
| | - Felipe Besoaín
- Escuela de Ingeniería Civil en Bioinformática, Universidad de Talca, Avenida Lircay s/n, Talca, Chile ; Estudis d'Informática, Multimedia i Telecomunicacio, Universitat Oberta de Catalunya, Rambla del Poblenou 15, Barcelona, Spain ; Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Av. Carl Friedrich Gauss, 5, Castelldefels, Barcelona, Spain
| | - Miguel Reyes-Parada
- School of Medicine, Faculty of Medical Sciences, Universidad de Santiago de Chile, Avenida Libertador Bernardo O'Higgins 3363, Santiago, Chile ; Facultad de Ciencias de la Salud, Universidad Autonóma de Chile, 5 Poniente 1670, Talca, Chile
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Maximova T, Moffatt R, Ma B, Nussinov R, Shehu A. Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics. PLoS Comput Biol 2016; 12:e1004619. [PMID: 27124275 PMCID: PMC4849799 DOI: 10.1371/journal.pcbi.1004619] [Citation(s) in RCA: 132] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.
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Affiliation(s)
- Tatiana Maximova
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
| | - Ryan Moffatt
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
| | - Buyong Ma
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America
| | - Ruth Nussinov
- Basic Science Program, Leidos Biomedical Research, Inc. Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland, United States of America
- Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Amarda Shehu
- Department of Computer Science, George Mason University, Fairfax, Virginia, United States of America
- Department of Biongineering, George Mason University, Fairfax, Virginia, United States of America
- School of Systems Biology, George Mason University, Manassas, Virginia, United States of America
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37
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Grove LE, Vajda S, Kozakov D. Computational Methods to Support Fragment-based Drug Discovery. FRAGMENT-BASED DRUG DISCOVERY LESSONS AND OUTLOOK 2016. [DOI: 10.1002/9783527683604.ch09] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
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38
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Biggin PC, Aldeghi M, Bodkin MJ, Heifetz A. Beyond Membrane Protein Structure: Drug Discovery, Dynamics and Difficulties. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2016; 922:161-181. [PMID: 27553242 DOI: 10.1007/978-3-319-35072-1_12] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Most of the previous content of this book has focused on obtaining the structures of membrane proteins. In this chapter we explore how those structures can be further used in two key ways. The first is their use in structure based drug design (SBDD) and the second is how they can be used to extend our understanding of their functional activity via the use of molecular dynamics. Both aspects now heavily rely on computations. This area is vast, and alas, too large to consider in depth in a single book chapter. Thus where appropriate we have referred the reader to recent reviews for deeper assessment of the field. We discuss progress via the use of examples from two main drug target areas; G-protein coupled receptors (GPCRs) and ion channels. We end with a discussion of some of the main challenges in the area.
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Affiliation(s)
- Philip C Biggin
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK.
| | - Matteo Aldeghi
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK
| | - Michael J Bodkin
- Evotec Ltd, 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire, OX14 4RZ, UK
| | - Alexander Heifetz
- Evotec Ltd, 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire, OX14 4RZ, UK
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39
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Keller M, Tränkle C, She X, Pegoli A, Bernhardt G, Buschauer A, Read RW. M2 Subtype preferring dibenzodiazepinone-type muscarinic receptor ligands: Effect of chemical homo-dimerization on orthosteric (and allosteric?) binding. Bioorg Med Chem 2015; 23:3970-90. [PMID: 25650309 DOI: 10.1016/j.bmc.2015.01.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Revised: 12/21/2014] [Accepted: 01/07/2015] [Indexed: 10/24/2022]
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40
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What is the potential of G protein-coupled receptor [corrected] allosteric sites in drug design? Future Med Chem 2015; 6:729-32. [PMID: 24941868 DOI: 10.4155/fmc.14.32] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
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41
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Pei J, Yin N, Ma X, Lai L. Systems Biology Brings New Dimensions for Structure-Based Drug Design. J Am Chem Soc 2014; 136:11556-65. [DOI: 10.1021/ja504810z] [Citation(s) in RCA: 64] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Jianfeng Pei
- Center
for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Ning Yin
- Center
for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Xiaomin Ma
- Center
for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Luhua Lai
- Center
for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Beijing
National Laboratory for Molecular Science, State Key Laboratory for
Structural Chemistry of Unstable and Stable Species, College of Chemistry
and Molecular Engineering, Peking University, Beijing 100871, China
- Peking-Tsinghua
Center for Life Sciences, Peking University, Beijing 100871, China
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42
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Miao Y, Sinko W, Pierce L, Bucher D, Walker RC, McCammon JA. Improved Reweighting of Accelerated Molecular Dynamics Simulations for Free Energy Calculation. J Chem Theory Comput 2014; 10:2677-2689. [PMID: 25061441 PMCID: PMC4095935 DOI: 10.1021/ct500090q] [Citation(s) in RCA: 311] [Impact Index Per Article: 31.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2014] [Indexed: 12/16/2022]
Abstract
![]()
Accelerated
molecular dynamics (aMD) simulations greatly improve
the efficiency of conventional molecular dynamics (cMD) for sampling
biomolecular conformations, but they require proper reweighting for
free energy calculation. In this work, we systematically compare the
accuracy of different reweighting algorithms including the exponential
average, Maclaurin series, and cumulant expansion on three model systems:
alanine dipeptide, chignolin, and Trp-cage. Exponential average reweighting
can recover the original free energy profiles easily only when the
distribution of the boost potential is narrow (e.g., the range ≤20kBT) as found in dihedral-boost aMD simulation
of alanine dipeptide. In dual-boost aMD simulations of the studied
systems, exponential average generally leads to high energetic fluctuations,
largely due to the fact that the Boltzmann reweighting factors are
dominated by a very few high boost potential frames. In comparison,
reweighting based on Maclaurin series expansion (equivalent to cumulant
expansion on the first order) greatly suppresses the energetic noise
but often gives incorrect energy minimum positions and significant
errors at the energy barriers (∼2–3kBT). Finally, reweighting using cumulant expansion to
the second order is able to recover the most accurate free energy
profiles within statistical errors of ∼kBT, particularly when the distribution of the boost potential
exhibits low anharmonicity (i.e., near-Gaussian distribution), and
should be of wide applicability. A toolkit of Python scripts for aMD
reweighting “PyReweighting” is distributed free of charge
at http://mccammon.ucsd.edu/computing/amdReweighting/.
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Affiliation(s)
- Yinglong Miao
- Howard Hughes Medical Institute, Department of Pharmacology, Department of Chemistry and Biochemistry and San Diego Supercomputer Center, University of California at San Diego , La Jolla, California 92093, United States
| | - William Sinko
- Howard Hughes Medical Institute, Department of Pharmacology, Department of Chemistry and Biochemistry and San Diego Supercomputer Center, University of California at San Diego , La Jolla, California 92093, United States
| | - Levi Pierce
- Schrodinger Inc., New York, New York 10036, United States
| | - Denis Bucher
- Howard Hughes Medical Institute, Department of Pharmacology, Department of Chemistry and Biochemistry and San Diego Supercomputer Center, University of California at San Diego , La Jolla, California 92093, United States
| | - Ross C Walker
- Howard Hughes Medical Institute, Department of Pharmacology, Department of Chemistry and Biochemistry and San Diego Supercomputer Center, University of California at San Diego , La Jolla, California 92093, United States ; Howard Hughes Medical Institute, Department of Pharmacology, Department of Chemistry and Biochemistry and San Diego Supercomputer Center, University of California at San Diego , La Jolla, California 92093, United States
| | - J Andrew McCammon
- Howard Hughes Medical Institute, Department of Pharmacology, Department of Chemistry and Biochemistry and San Diego Supercomputer Center, University of California at San Diego , La Jolla, California 92093, United States ; Howard Hughes Medical Institute, Department of Pharmacology, Department of Chemistry and Biochemistry and San Diego Supercomputer Center, University of California at San Diego , La Jolla, California 92093, United States ; Howard Hughes Medical Institute, Department of Pharmacology, Department of Chemistry and Biochemistry and San Diego Supercomputer Center, University of California at San Diego , La Jolla, California 92093, United States
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