1
|
Flachsenberg F, Ehrt C, Gutermuth T, Rarey M. Redocking the PDB. J Chem Inf Model 2024; 64:219-237. [PMID: 38108627 DOI: 10.1021/acs.jcim.3c01573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Molecular docking is a standard technique in structure-based drug design (SBDD). It aims to predict the 3D structure of a small molecule in the binding site of a receptor (often a protein). Despite being a common technique, it often necessitates multiple tools and involves manual steps. Here, we present the JAMDA preprocessing and docking workflow that is easy to use and allows fully automated docking. We evaluate the JAMDA docking workflow on binding sites extracted from the complete PDB and derive key factors determining JAMDA's docking performance. With that, we try to remove most of the bias due to manual intervention and provide a realistic estimate of the redocking performance of our JAMDA preprocessing and docking workflow for any PDB structure. On this large PDBScan22 data set, our JAMDA workflow finds a pose with an RMSD of at most 2 Å to the crystal ligand on the top rank for 30.1% of the structures. When applying objective structure quality filters to the PDBScan22 data set, the success rate increases to 61.8%. Given the prepared structures from the JAMDA preprocessing pipeline, both JAMDA and the widely used AutoDock Vina perform comparably on this filtered data set (the PDBScan22-HQ data set).
Collapse
Affiliation(s)
- Florian Flachsenberg
- Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Christiane Ehrt
- Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Torben Gutermuth
- Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| | - Matthias Rarey
- Universität Hamburg, ZBH - Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany
| |
Collapse
|
2
|
Eguida M, Rognan D. Estimating the Similarity between Protein Pockets. Int J Mol Sci 2022; 23:12462. [PMID: 36293316 PMCID: PMC9604425 DOI: 10.3390/ijms232012462] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 10/15/2022] [Accepted: 10/16/2022] [Indexed: 10/28/2023] Open
Abstract
With the exponential increase in publicly available protein structures, the comparison of protein binding sites naturally emerged as a scientific topic to explain observations or generate hypotheses for ligand design, notably to predict ligand selectivity for on- and off-targets, explain polypharmacology, and design target-focused libraries. The current review summarizes the state-of-the-art computational methods applied to pocket detection and comparison as well as structural druggability estimates. The major strengths and weaknesses of current pocket descriptors, alignment methods, and similarity search algorithms are presented. Lastly, an exhaustive survey of both retrospective and prospective applications in diverse medicinal chemistry scenarios illustrates the capability of the existing methods and the hurdle that still needs to be overcome for more accurate predictions.
Collapse
Affiliation(s)
| | - Didier Rognan
- Laboratoire d’Innovation Thérapeutique, UMR7200 CNRS-Université de Strasbourg, 67400 Illkirch, France
| |
Collapse
|
3
|
fingeRNAt—A novel tool for high-throughput analysis of nucleic acid-ligand interactions. PLoS Comput Biol 2022; 18:e1009783. [PMID: 35653385 PMCID: PMC9197077 DOI: 10.1371/journal.pcbi.1009783] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 06/14/2022] [Accepted: 05/06/2022] [Indexed: 11/19/2022] Open
Abstract
Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt—a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt)—a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction fingerprint-based similarity as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of interaction fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties. The fingeRNAt software is freely available at https://github.com/n-szulc/fingeRNAt.
Collapse
|
4
|
Kolodny R, Nepomnyachiy S, Tawfik DS, Ben-Tal N. Bridging Themes: Short Protein Segments Found in Different Architectures. Mol Biol Evol 2021; 38:2191-2208. [PMID: 33502503 PMCID: PMC8136508 DOI: 10.1093/molbev/msab017] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The vast majority of theoretically possible polypeptide chains do not fold, let alone confer function. Hence, protein evolution from preexisting building blocks has clear potential advantages over ab initio emergence from random sequences. In support of this view, sequence similarities between different proteins is generally indicative of common ancestry, and we collectively refer to such homologous sequences as "themes." At the domain level, sequence homology is routinely detected. However, short themes which are segments, or fragments of intact domains, are particularly interesting because they may provide hints about the emergence of domains, as opposed to divergence of preexisting domains, or their mixing-and-matching to form multi-domain proteins. Here we identified 525 representative short themes, comprising 20-80 residues that are unexpectedly shared between domains considered to have emerged independently. Among these "bridging themes" are ones shared between the most ancient domains, for example, Rossmann, P-loop NTPase, TIM-barrel, flavodoxin, and ferredoxin-like. We elaborate on several particularly interesting cases, where the bridging themes mediate ligand binding. Ligand binding may have contributed to the stability and the plasticity of these building blocks, and to their ability to invade preexisting domains or serve as starting points for completely new domains.
Collapse
Affiliation(s)
- Rachel Kolodny
- Department of Computer Science, University of Haifa, Haifa, Israel
| | | | - Dan S Tawfik
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Nir Ben-Tal
- George S. Wise Faculty of Life Sciences, Department of Biochemistry and Molecular Biology, Tel Aviv University, Tel Aviv, Israel
| |
Collapse
|
5
|
Computational Modeling to Explain Why 5,5-Diarylpentadienamides are TRPV1 Antagonists. Molecules 2021; 26:molecules26061765. [PMID: 33801115 PMCID: PMC8004144 DOI: 10.3390/molecules26061765] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 03/14/2021] [Accepted: 03/18/2021] [Indexed: 11/29/2022] Open
Abstract
Several years ago, the crystallographic structures of the transient receptor potential vanilloid 1 (TRPV1) in the presence of agonists and antagonists were reported, providing structural information about its chemical activation and inactivation. TRPV1’s activation increases the transport of calcium and sodium ions, leading to the excitation of sensory neurons and the perception of pain. On the other hand, its antagonistic inactivation has been explored to design analgesic drugs. The interactions between the antagonists 5,5-diarylpentadienamides (DPDAs) and TRPV1 were studied here to explain why they inactivate TRPV1. The present work identified the structural features of TRPV1–DPDA complexes, starting with a consideration of the orientations of the ligands inside the TRPV1 binding site by using molecular docking. After this, a chemometrics analysis was performed (i) to compare the orientations of the antagonists (by using LigRMSD), (ii) to describe the recurrent interactions between the protein residues and ligand groups in the complexes (by using interaction fingerprints), and (iii) to describe the relationship between topological features of the ligands and their differential antagonistic activities (by using a quantitative structure–activity relationship (QSAR) with 2D autocorrelation descriptors). The interactions between the DPDA groups and the residues Y511, S512, T550, R557, and E570 (with a recognized role in the binding of classic ligands), and the occupancy of isoquinoline or 3-hydroxy-3,4-dihydroquinolin-2(1H)-one groups of the DPDAs in the vanilloid pocket of TRPV1 were clearly described. Based on the results, the structural features that explain why DPDAs inactivate TRPV1 were clearly exposed. These features can be considered for the design of novel TRPV1 antagonists.
Collapse
|
6
|
Varela-Rial A, Majewski M, Cuzzolin A, Martínez-Rosell G, De Fabritiis G. SkeleDock: A Web Application for Scaffold Docking in PlayMolecule. J Chem Inf Model 2020; 60:2673-2677. [PMID: 32407111 DOI: 10.1021/acs.jcim.0c00143] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
SkeleDock is a scaffold docking algorithm which uses the structure of a protein-ligand complex as a template to model the binding mode of a chemically similar system. This algorithm was evaluated in the D3R Grand Challenge 4 pose prediction challenge, where it achieved competitive performance. Furthermore, we show that if crystallized fragments of the target ligand are available then SkeleDock can outperform rDock docking software at predicting the binding mode. This Application Note also addresses the capacity of this algorithm to model macrocycles and deal with scaffold hopping. SkeleDock can be accessed at https://playmolecule.org/SkeleDock/.
Collapse
Affiliation(s)
- Alejandro Varela-Rial
- Acellera Labs, Doctor Trueta 183, Barcelona, Spain.,Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Barcelona, Spain
| | - Maciej Majewski
- Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Barcelona, Spain
| | | | | | - Gianni De Fabritiis
- Acellera Labs, Doctor Trueta 183, Barcelona, Spain.,Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, Barcelona, Spain
| |
Collapse
|
7
|
Fogha J, Diharce J, Obled A, Aci-Sèche S, Bonnet P. Computational Analysis of Crystallization Additives for the Identification of New Allosteric Sites. ACS OMEGA 2020; 5:2114-2122. [PMID: 32064372 PMCID: PMC7016913 DOI: 10.1021/acsomega.9b02697] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 11/21/2019] [Indexed: 06/10/2023]
Abstract
Allosteric effect can modulate the biological activity of a protein. Thus, the discovery of new allosteric sites is very attractive for designing new modulators or inhibitors. Here, we propose an innovative way to identify allosteric sites, based on crystallization additives (CA), used to stabilize proteins during the crystallization process. Density and clustering analyses of CA, applied on protein kinase and nuclear receptor families, revealed that CA are not randomly distributed around protein structures, but they tend to aggregate near common sites. All orthosteric and allosteric cavities described in the literature are retrieved from the analysis of CA distribution. In addition, new sites were identified, which could be associated to putative allosteric sites. We proposed an efficient and easy way to use the structural information of CA to identify allosteric sites. This method could assist medicinal chemists for the design of new allosteric compounds targeting cavities of new drug targets.
Collapse
|
8
|
Jacquemard C, Tran-Nguyen VK, Drwal MN, Rognan D, Kellenberger E. Local Interaction Density (LID), a Fast and Efficient Tool to Prioritize Docking Poses. Molecules 2019; 24:molecules24142610. [PMID: 31323745 PMCID: PMC6681060 DOI: 10.3390/molecules24142610] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 07/11/2019] [Accepted: 07/16/2019] [Indexed: 12/18/2022] Open
Abstract
Ligand docking at a protein site can be improved by prioritizing poses by similarity to validated binding modes found in the crystal structures of ligand/protein complexes. The interactions formed in the predicted model are searched in each of the reference 3D structures, taken individually. We propose to merge the information provided by all references, creating a single representation of all known binding modes. The method is called LID, an acronym for Local Interaction Density. LID was benchmarked in a pose prediction exercise on 19 proteins and 1382 ligands using PLANTS as docking software. It was also tested in a virtual screening challenge on eight proteins, with a dataset of 140,000 compounds from DUD-E and PubChem. LID significantly improved the performance of the docking program in both pose prediction and virtual screening. The gain is comparable to that obtained with a rescoring approach based on the individual comparison of reference binding modes (the GRIM method). Importantly, LID is effective with a small number of references. LID calculation time is negligible compared to the docking time.
Collapse
Affiliation(s)
- Célien Jacquemard
- Laboratoire D'innovation Thérapeutique, UMR7200, CNRS, Université de Strasbourg, 67400 Illkirch, France
| | - Viet-Khoa Tran-Nguyen
- Laboratoire D'innovation Thérapeutique, UMR7200, CNRS, Université de Strasbourg, 67400 Illkirch, France
| | - Malgorzata N Drwal
- Laboratoire D'innovation Thérapeutique, UMR7200, CNRS, Université de Strasbourg, 67400 Illkirch, France
| | - Didier Rognan
- Laboratoire D'innovation Thérapeutique, UMR7200, CNRS, Université de Strasbourg, 67400 Illkirch, France
| | - Esther Kellenberger
- Laboratoire D'innovation Thérapeutique, UMR7200, CNRS, Université de Strasbourg, 67400 Illkirch, France.
| |
Collapse
|
9
|
Silvestri I, Lyu H, Fata F, Boumis G, Miele AE, Ardini M, Ippoliti R, Bellelli A, Jadhav A, Lea WA, Simeonov A, Cheng Q, Arnér ESJ, Thatcher GR, Petukhov PA, Williams DL, Angelucci F. Fragment-Based Discovery of a Regulatory Site in Thioredoxin Glutathione Reductase Acting as "Doorstop" for NADPH Entry. ACS Chem Biol 2018; 13:2190-2202. [PMID: 29800515 PMCID: PMC6905387 DOI: 10.1021/acschembio.8b00349] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Members of the FAD/NAD-linked reductase family are recognized as crucial targets in drug development for cancers, inflammatory disorders, and infectious diseases. However, individual FAD/NAD reductases are difficult to inhibit in a selective manner with off-target inhibition reducing usefulness of identified compounds. Thioredoxin glutathione reductase (TGR), a high molecular weight thioredoxin reductase-like enzyme, has emerged as a promising drug target for the treatment of schistosomiasis, a parasitosis afflicting more than 200 million people. Taking advantage of small molecules selected from a high-throughput screen and using X-ray crystallography, functional assays, and docking studies, we identify a critical secondary site of the enzyme. Compounds binding at this site interfere with well-known and conserved conformational changes associated with NADPH reduction, acting as a doorstop for cofactor entry. They selectively inhibit TGR from Schistosoma mansoni and are active against parasites in culture. Since many members of the FAD/NAD-linked reductase family have similar catalytic mechanisms, the unique mechanism of inhibition identified in this study for TGR broadly opens new routes to selectively inhibit homologous enzymes of central importance in numerous diseases.
Collapse
Affiliation(s)
- Ilaria Silvestri
- Dept. of Life, Health and Environmental Sciences, University of L’Aquila, Italy,These authors contributed equally
| | - Haining Lyu
- Dept. of Microbial Pathogens and Immunity, Rush University Medical Center, Chicago, IL USA,These authors contributed equally
| | - Francesca Fata
- Dept. of Life, Health and Environmental Sciences, University of L’Aquila, Italy
| | - Giovanna Boumis
- Dept. of Biochemical Sciences, Sapienza University of Rome, Italy
| | - Adriana E. Miele
- Dept. of Biochemical Sciences, Sapienza University of Rome, Italy,UMR5246 ICBMS – CNRS – UCBL, Université de Lyon, France
| | - Matteo Ardini
- Dept. of Life, Health and Environmental Sciences, University of L’Aquila, Italy
| | - Rodolfo Ippoliti
- Dept. of Life, Health and Environmental Sciences, University of L’Aquila, Italy
| | - Andrea Bellelli
- Dept. of Biochemical Sciences, Sapienza University of Rome, Italy
| | - Ajit Jadhav
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Wendy A. Lea
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA,Current address: The Jared Grantham Kidney Institute, University of Kansas Medical Center, Kansas City, KS 66160
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Qing Cheng
- Dept. of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Elias S. J. Arnér
- Dept. of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Gregory R. Thatcher
- Dept. of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago, Chicago, IL USA
| | - Pavel A. Petukhov
- Dept. of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago, Chicago, IL USA
| | - David L. Williams
- Dept. of Microbial Pathogens and Immunity, Rush University Medical Center, Chicago, IL USA,Senior authors,To whom correspondence should be addressed: David L. Williams (), Francesco Angelucci ()
| | - Francesco Angelucci
- Dept. of Life, Health and Environmental Sciences, University of L’Aquila, Italy,Senior authors,To whom correspondence should be addressed: David L. Williams (), Francesco Angelucci ()
| |
Collapse
|
10
|
Drwal MN, Bret G, Perez C, Jacquemard C, Desaphy J, Kellenberger E. Structural Insights on Fragment Binding Mode Conservation. J Med Chem 2018; 61:5963-5973. [PMID: 29906118 DOI: 10.1021/acs.jmedchem.8b00256] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Aiming at a deep understanding of fragment binding to ligandable targets, we performed a large scale analysis of the Protein Data Bank. Binding modes of 1832 drug-like ligands and 1079 fragments to 235 proteins were compared. We observed that the binding modes of fragments and their drug-like superstructures binding to the same protein are mostly conserved, thereby providing experimental evidence for the preservation of fragment binding modes during molecular growing. Furthermore, small chemical changes in the fragment are tolerated without alteration of the fragment binding mode. The exceptions to this observation generally involve conformational variability of the molecules. Our data analysis also suggests that, provided enough fragments have been crystallized within a protein, good interaction coverage of the binding pocket is achieved. Last, we extended our study to 126 crystallization additives and discuss in which cases they provide information relevant to structure-based drug design.
Collapse
Affiliation(s)
- Malgorzata N Drwal
- Laboratoire d'Innovation Thérapeutique , UMR7200, Université de Strasbourg , 74 Route du Rhin , 67401 Illkirch , France
| | - Guillaume Bret
- Laboratoire d'Innovation Thérapeutique , UMR7200, Université de Strasbourg , 74 Route du Rhin , 67401 Illkirch , France
| | - Carlos Perez
- Eli Lilly Research Laboratories , Avenida de la Industria, 30 , 28108 Alcobendas , Madrid , Spain
| | - Célien Jacquemard
- Laboratoire d'Innovation Thérapeutique , UMR7200, Université de Strasbourg , 74 Route du Rhin , 67401 Illkirch , France
| | - Jérémy Desaphy
- Lilly Research Laboratories, Eli Lilly and Company , Lilly Corporate Center , Indianapolis , Indiana 46285 , United States
| | - Esther Kellenberger
- Laboratoire d'Innovation Thérapeutique , UMR7200, Université de Strasbourg , 74 Route du Rhin , 67401 Illkirch , France
| |
Collapse
|
11
|
Bianchetti L, Wassmer B, Defosset A, Smertina A, Tiberti ML, Stote RH, Dejaegere A. Alternative dimerization interfaces in the glucocorticoid receptor-α ligand binding domain. Biochim Biophys Acta Gen Subj 2018; 1862:1810-1825. [PMID: 29723544 DOI: 10.1016/j.bbagen.2018.04.022] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 04/19/2018] [Accepted: 04/27/2018] [Indexed: 10/17/2022]
Abstract
BACKGROUND Nuclear hormone receptors (NRs) constitute a large family of multi-domain ligand-activated transcription factors. Dimerization is essential for their regulation, and both DNA binding domain (DBD) and ligand binding domain (LBD) are implicated in dimerization. Intriguingly, the glucocorticoid receptor-α (GRα) presents a DBD dimeric architecture similar to that of the homologous estrogen receptor-α (ERα), but an atypical dimeric architecture for the LBD. The physiological relevance of the proposed GRα LBD dimer is a subject of debate. METHODS We analyzed all GRα LBD homodimers observed in crystals using an energetic analysis based on the PISA and on the MM/PBSA methods and a sequence conservation analysis, using the ERα LBD dimer as a reference point. RESULTS Several dimeric assemblies were observed for GRα LBD. The assembly generally taken to be physiologically relevant showed weak binding free energy and no significant residue conservation at the contact interface, while an alternative homodimer mediated by both helix 9 and C-terminal residues showed significant binding free energy and residue conservation. However, none of the GRα LBD assemblies found in crystals are as stable or conserved as the canonical ERα LBD dimer. GRα C-terminal sequence (F-domain) forms a steric obstacle to the canonical dimer assembly in all available structures. CONCLUSIONS Our analysis calls for a re-examination of the currently accepted GRα homodimer structure and experimental investigations of the alternative architectures. GENERAL SIGNIFICANCE This work questions the validity of the currently accepted architecture. This has implications for interpreting physiological data and for therapeutic design pertaining to glucocorticoid research.
Collapse
Affiliation(s)
- Laurent Bianchetti
- Biocomputing and Molecular Modelling Laboratory, Integrated Structural Biology Department, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS UMR 7104 - Inserm U1258 - Université de Strasbourg, 1 rue Laurent Fries, 67404 Illkirch, France
| | - Bianca Wassmer
- Biocomputing and Molecular Modelling Laboratory, Integrated Structural Biology Department, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS UMR 7104 - Inserm U1258 - Université de Strasbourg, 1 rue Laurent Fries, 67404 Illkirch, France
| | - Audrey Defosset
- Biocomputing and Molecular Modelling Laboratory, Integrated Structural Biology Department, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS UMR 7104 - Inserm U1258 - Université de Strasbourg, 1 rue Laurent Fries, 67404 Illkirch, France
| | - Anna Smertina
- Biocomputing and Molecular Modelling Laboratory, Integrated Structural Biology Department, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS UMR 7104 - Inserm U1258 - Université de Strasbourg, 1 rue Laurent Fries, 67404 Illkirch, France
| | - Marion L Tiberti
- Biocomputing and Molecular Modelling Laboratory, Integrated Structural Biology Department, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS UMR 7104 - Inserm U1258 - Université de Strasbourg, 1 rue Laurent Fries, 67404 Illkirch, France
| | - Roland H Stote
- Biocomputing and Molecular Modelling Laboratory, Integrated Structural Biology Department, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS UMR 7104 - Inserm U1258 - Université de Strasbourg, 1 rue Laurent Fries, 67404 Illkirch, France
| | - Annick Dejaegere
- Biocomputing and Molecular Modelling Laboratory, Integrated Structural Biology Department, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS UMR 7104 - Inserm U1258 - Université de Strasbourg, 1 rue Laurent Fries, 67404 Illkirch, France.
| |
Collapse
|
12
|
Drwal MN, Bret G, Kellenberger E. Multi-target Fragments Display Versatile Binding Modes. Mol Inform 2017; 36. [PMID: 28691374 DOI: 10.1002/minf.201700042] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 06/30/2017] [Indexed: 11/10/2022]
Abstract
Promiscuity is an interesting concept in fragment-based drug design as fragments with low specificity can be advantageous for finding many screening hits. We present a PDB-wide analysis of multi-target fragments and their binding mode conservation. Focussing on multi-target fragments, we found that the majority shows non-conserved binding modes, even if they bind in a similar conformation or similar protein targets. Surprisingly, fragment properties alone are not able to predict whether a fragment will exhibit a versatile or conserved binding mode, emphasizing the interplay between protein and fragment features during a binding event and the importance of structure-based modelling.
Collapse
Affiliation(s)
- Malgorzata N Drwal
- UMR 7200 - Laboratoire d'Innovation Thérapeutique, Université de Strasbourg, Faculté de Pharmacie, 74 Route du Rhin, 67401, Illkirch, France phone: +33 3 68 85 42 21 fax: +33 3 68 85 43 10
| | - Guillaume Bret
- UMR 7200 - Laboratoire d'Innovation Thérapeutique, Université de Strasbourg, Faculté de Pharmacie, 74 Route du Rhin, 67401, Illkirch, France phone: +33 3 68 85 42 21 fax: +33 3 68 85 43 10
| | - Esther Kellenberger
- UMR 7200 - Laboratoire d'Innovation Thérapeutique, Université de Strasbourg, Faculté de Pharmacie, 74 Route du Rhin, 67401, Illkirch, France phone: +33 3 68 85 42 21 fax: +33 3 68 85 43 10
| |
Collapse
|
13
|
|