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1. Status of GPCR modeling and docking as reflected by community-wide GPCR Dock 2010 assessment

Author

Victor Solovyev, Umesh Ghoshdastider, Patrick Sexton, Andrei Lomize, Nathan Hall, Vladimir Yarov-Yarovoy, Stefano Costanzi, William Church, Nikolay Dokholyan, Robert Mach, David Chalmers, Srinivas Ramachandran, Vsevolod Katritch, Joseph Rebehmed, Chris De Graaf, David Reichert, Henri Xhaard, Slawomir Filipek, John Simms, Supriyo Bhattacharya, Jens Carlsson, Bartosz Trzaskowski, I.J.P. De Esch, Lei Shi, Dorota Latek, Woody Sherman, Liliana Halip, Manuel Rueda, Irina Kufareva, Elizabeth Yuriev, Jana Selent, Denise Wootten, Medicinal chemistry, and AIMMS

Subjects
Chemical and physical biology [NCMLS 7], Models, Molecular, Quantitative structure–activity relationship, Receptors, CXCR4, Genetics and epigenetic pathways of disease [NCMLS 6], Molecular model, Molecular Sequence Data, Computational biology, Biology, Crystallography, X-Ray, 01 natural sciences, Article, Receptors, G-Protein-Coupled, 03 medical and health sciences, Chemokine receptor, Structural Biology, DOCK, Salicylamides, Humans, Computer Simulation, Homology modeling, Amino Acid Sequence, Molecular Biology, 030304 developmental biology, G protein-coupled receptor, 0303 health sciences, Binding Sites, 010405 organic chemistry, Receptors, Dopamine D3, Thiourea, Small molecule, Peptide Fragments, 0104 chemical sciences, Biochemistry, Docking (molecular), Protein Binding
Abstract

The community-wide GPCR Dock assessment is conducted to evaluate the status of molecular modeling and ligand docking for human G protein-coupled receptors. The present round of the assessment was based on the recent structures of dopamine D3 and CXCR4 chemokine receptors bound to small molecule antagonists and CXCR4 with a synthetic cyclopeptide. Thirty-five groups submitted their receptor-ligand complex structure predictions prior to the release of the crystallographic coordinates. With closely related homology modeling templates, as for dopamine D3 receptor, and with incorporation of biochemical and QSAR data, modern computational techniques predicted complex details with accuracy approaching experimental. In contrast, CXCR4 complexes that had less-characterized interactions and only distant homology to the known GPCR structures still remained very challenging. The assessment results provide guidance for modeling and crystallographic communities in method development and target selection for further expansion of the structural coverage of the GPCR universe. © 2011 Elsevier Ltd. All rights reserved.

Published
2011
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2. Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis

Author

Ruth Nussinov, Pritam Ganguly, Son Tung Ngo, Carol K. Hall, John E. Straub, Laura Dominguez, Alfonso De Simone, Guanghong Wei, Bikash R. Sahoo, Brianna Hnath, Ayyalusamy Ramamoorthy, Sylvain Lesné, Fabio Sterpone, Simone Melchionna, Nikolay V. Dokholyan, Yiming Wang, Jie Zheng, Rakez Kayed, Jiaxing Chen, Birgit Habenstein, Peter Faller, Philippe Derreumaux, Antoine Loquet, Mara Chiricotto, Birgit Strodel, Buyong Ma, Stepan Timr, James McCarty, Phuong H. Nguyen, Mai Suan Li, Andrew J. Doig, Joan-Emma Shea, Saeed Najafi, Yifat Miller, Nguyen, P. H., Ramamoorthy, A., Sahoo, B. R., Zheng, J., Faller, P., Straub, J. E., Dominguez, L., Shea, J. -E., Dokholyan, N. V., De Simone, A., Ma, B., Nussinov, R., Najafi, S., Ngo, S. T., Loquet, A., Chiricotto, M., Ganguly, P., Mccarty, J., Li, M. S., Hall, C., Wang, Y., Miller, Y., Melchionna, S., Habenstein, B., Timr, S., Chen, J., Hnath, B., Strodel, B., Kayed, R., Lesne, S., Wei, G., Sterpone, F., Doig, A. J., Derreumaux, P., Laboratoire de biochimie théorique [Paris] (LBT (UPR_9080)), Institut de biologie physico-chimique (IBPC (FR_550)), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Laura Dominguez gratefully acknowledges the support of PAIP 5000-9155, LANCAD-UNAM-DGTIC-306, and CONACyT Ciencia Básica A1-S-8866. John E. Straub gratefully acknowledges the generous support of the National Science Foundation (Grant No. CHE-1900416) and the National Institutes of Health (Grant No. R01 GM107703). Alfonso De Simone acknowledges funding from the European Research Council (ERC), Consolidator Grant (CoG) 'BioDisOrder' (819644). Yiming Wang and Carol K. Hall acknowledge the support of a Cheney Visiting Scholar Fellowship from the University of Leeds. The work was also supported by NSF Division of Chemical, Bioengineering, Environmental, and Transport Systems Grants 1743432 and 1512059. Antoine Loquet thanks the ERC starting Grant no. 639020. For Buyong Ma and Ruth Nussinov, this project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under contract HHSN26120080001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. This Research was supported [in part] by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. Birgit Strodel acknowledges funding by a Helmholtz ERC Recognition Award. Jie Zheng acknowledges funding from NSF (1806138 and 1825122). Stepan Timr acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 840395. Fabio Sterpone acknowledges funding from the ERC (FP7/2007-2013) Grant Agreement no. 258748. Nikolay Dokholyan acknowledges support from the National Institutes for Health grants 1R35 GM134864 and UL1 TR002014 and the Passan Foundation. Joan-Emma Shea acknowledges computational support from the Extreme Science and Engineering Discovery Environment (XSEDE) through the National Science Foundation (NSF) grant number TG-MCA05S027. J.-E. Shea acknowledges the support from the National Science Foundation (NSF Grant MCB-1716956). The funding from the National Institutes of Health (NIH grant R01-GM118560-01A) and partial support from the National Science Foundation MRSEC grant No. DMR 1720256 is also acknowledged. She thanks the Center for Scientific Computing at the California Nanosystems Institute (NSF Grant CNS-1725797). The work of Sylvain Lesné was supported by grants from the National Institutes of Health (NIH) to (RF1-AG044342, R21-AG065693, R01-NS092918, R01-AG062135, and R56-NS113549). Additional support included start-up funds from the University of Minnesota Foundation and bridge funds from the Institute of Translational Neuroscience to S.L. Rakez Kayed was supported by National Institute of Health grants R01AG054025 and R01NS094557. Mai Suan Li was supported by Narodowe Centrum Nauki in Poland (grant 2019/35/B/ST4/02086) and the Department of Science and Technology, Ho Chi Minh City, Vietnam (grant 07/2019/HĐ-KHCNTT). Yifat Miller thanks the Israel Science Foundation, grant no. 532/15 and FP7-PEOPLE-2011-CIG, research grant no. 303741. Son Tung Ngo was supported by Vietnam National Foundation for Science & Technology Development (NAFOSTED) grant #104.99-2019.57. Research in the Ramamoorthy lab is supported by NIH (AG048934). Guanghong Wei acknowledges the financial support from the National Science Foundation of China (Grant Nos. 11674065 and 11274075) and National Key Research and Development Program of China (2016YFA0501702). Philippe Derreumaux acknowledges the support of the Université de Paris, ANR SIMI7 GRAL 12-BS07-0017, 'Initiative d’Excellence' program from the French State (Grant 'DYNAMO', ANR- 11-LABX-0011-01) and the CNRS Institute of Chemistry (INC) for two years of délégation in 2017 and 2018., and Nguyen, Phuong

Subjects
Models, Molecular, Amyloid, Parkinson's disease, [SDV]Life Sciences [q-bio], Central nervous system, tau Proteins, Disease, Protein aggregation, 010402 general chemistry, Protein Aggregation, Pathological, 01 natural sciences, Article, Superoxide dismutase, Superoxide Dismutase-1, Alzheimer Disease, Diabetes mellitus, medicine, Animals, Humans, [CHIM]Chemical Sciences, Proteostasis Deficiencies, Amyotrophic lateral sclerosis, Glycoproteins, Amyloid beta-Peptides, biology, 010405 organic chemistry, Chemistry, Amyotrophic Lateral Sclerosis, Neurodegenerative Diseases, Parkinson Disease, General Chemistry, Aluminum compounds, medicine.disease, Islet Amyloid Polypeptide, 3. Good health, 0104 chemical sciences, Enzymes, [SDV] Life Sciences [q-bio], medicine.anatomical_structure, Diabetes Mellitus, Type 2, Oligomers, ddc:540, alpha-Synuclein, biology.protein, Neuroscience
Abstract

International audience; Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D) and amyotrophic lateral sclerosis (ALS) research, respectively for over many years.

Published
2021
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