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Ravnik V, Jukič M, Bren U. Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach. J Chem Inf Model 2023; 63:5204-5219. [PMID: 37557084 PMCID: PMC10466382 DOI: 10.1021/acs.jcim.3c00558] [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: 04/11/2023] [Indexed: 08/11/2023]
Abstract
In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS H2O (MD) methodology, for the identification of conserved water molecules. Our method uses experimental structures of proteins homologous to a query, which are subsequently superimposed upon it. Areas with a particular species present in a similar location among many homologous protein structures are identified using a clustering algorithm. Dense clusters likely represent positions containing species important to the query protein structure or function. We analyze well-characterized apo protein structures and show that the MADE approach can identify clusters corresponding to the expected positions of metal ions in their binding sites. The greatest advantage of our method lies in its generality. It can in principle be applied to any species found in protein records; it is not only limited to metal ions. We additionally demonstrate that the MADE approach can be successfully applied to predict the location of cofactors in computer-modeled structures, e.g., via AlphaFold. We also conduct a careful protein superposition method comparison and find our methodology robust and the results largely independent of the selected protein superposition algorithm. We postulate that with increasing structural data availability, additional applications of the MADE approach will be possible such as non-protein systems, water network identification, protein binding site elaboration, and analysis of binding events, all in a dynamic manner. We have implemented the MADE approach as a plugin for the PyMOL molecular visualization tool. The MADE plugin is available free of charge at https://gitlab.com/Jukic/made_software.
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Affiliation(s)
- Vid Ravnik
- Faculty
of Chemistry and Chemical Engineering, University
of Maribor, Smetanova
ulica 17, Maribor SI-2000, Slovenia
| | - Marko Jukič
- Faculty
of Chemistry and Chemical Engineering, University
of Maribor, Smetanova
ulica 17, Maribor SI-2000, Slovenia
- The
Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, Koper SI-6000, Slovenia
- Institute
for Environmental Protection and Sensors, Beloruska ulica 7, Maribor SI-2000, Slovenia
| | - Urban Bren
- Faculty
of Chemistry and Chemical Engineering, University
of Maribor, Smetanova
ulica 17, Maribor SI-2000, Slovenia
- The
Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, Koper SI-6000, Slovenia
- Institute
for Environmental Protection and Sensors, Beloruska ulica 7, Maribor SI-2000, Slovenia
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2
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Nagaraju EV. In-silico Prediction of Maximum Binding Affinity of Disease-Modifying Antirheumatic Drugs with Homo sapiens Acrosomal Protein SP-10. INTERNATIONAL JOURNAL OF PHARMACEUTICAL RESEARCH AND ALLIED SCIENCES 2023. [DOI: 10.51847/ptup5schcd] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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3
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Pavlin A, Lovše A, Bajc G, Otoničar J, Kujović A, Lengar Ž, Gutierrez-Aguirre I, Kostanjšek R, Konc J, Fornelos N, Butala M. A small bacteriophage protein determines the hierarchy over co-residential jumbo phage in Bacillus thuringiensis serovar israelensis. Commun Biol 2022; 5:1286. [PMID: 36434275 PMCID: PMC9700832 DOI: 10.1038/s42003-022-04238-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 11/08/2022] [Indexed: 11/26/2022] Open
Abstract
Bacillus thuringiensis serovar israelensis is the most widely used biopesticide against insects, including vectors of animal and human diseases. Among several extrachromosomal elements, this endospore-forming entomopathogen harbors two bacteriophages: a linear DNA replicon named GIL01 that does not integrate into the chromosome during lysogeny and a circular-jumbo prophage known as pBtic235. Here, we show that GIL01 hinders the induction of cohabiting prophage pBtic235. The GIL01-encoded small protein, gp7, which interacts with the host LexA repressor, is a global transcription regulator and represses the induction of pBtic235 after DNA damage to presumably allow GIL01 to multiply first. In a complex with host LexA in stressed cells, gp7 down-regulates the expression of more than 250 host and pBtic235 genes, many of which are involved in the cellular functions of genome maintenance, cell-wall transport, and membrane and protein stability. We show that gp7 homologs that are found exclusively in bacteriophages act in a similar fashion to enhance LexA's binding to DNA, while likely also affecting host gene expression. Our results provide evidence that GIL01 influences both its host and its co-resident bacteriophage.
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Affiliation(s)
- Anja Pavlin
- grid.8954.00000 0001 0721 6013Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Anže Lovše
- grid.8954.00000 0001 0721 6013Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia ,Genialis, Inc., Boston, MA USA
| | - Gregor Bajc
- grid.8954.00000 0001 0721 6013Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Jan Otoničar
- grid.8954.00000 0001 0721 6013Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Amela Kujović
- grid.8954.00000 0001 0721 6013Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Živa Lengar
- grid.419523.80000 0004 0637 0790Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Ion Gutierrez-Aguirre
- grid.419523.80000 0004 0637 0790Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia
| | - Rok Kostanjšek
- grid.8954.00000 0001 0721 6013Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Janez Konc
- grid.454324.00000 0001 0661 0844Theory Department, National Institute of Chemistry, Ljubljana, Slovenia
| | - Nadine Fornelos
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Matej Butala
- grid.8954.00000 0001 0721 6013Department of Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
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4
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Konc J, Lešnik S, Škrlj B, Sova M, Proj M, Knez D, Gobec S, Janežič D. ProBiS-Dock: A Hybrid Multitemplate Homology Flexible Docking Algorithm Enabled by Protein Binding Site Comparison. J Chem Inf Model 2022; 62:1573-1584. [PMID: 35289616 DOI: 10.1021/acs.jcim.1c01176] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The protein data bank (PDB) is a rich source of protein ligand structures, but ligands are not explicitly used in current docking algorithms. We have developed ProBiS-Dock, a docking algorithm complementary to the ProBiS-Dock Database (J. Chem. Inf. Model. 2021, 61, 4097-4107) that treats small molecules and proteins as fully flexible entities and allows conformational changes in both after ligand binding. A new scoring function is described that consists of a binding site-specific scoring function (ProBiS-Score) and a general statistical scoring function. ProBiS-Dock enables rapid docking of small molecules to proteins and has been successfully validated in silico against standard benchmarks. It enables rapid search for new active ligands by leveraging existing knowledge in the PDB. The potential of the software for drug development has been confirmed in vitro by the discovery of new inhibitors of human indoleamine 2,3-dioxygenase 1, an enzyme that is an attractive target for cancer therapy and catalyzes the first rate-determining step of l-tryptophan metabolism via the kynurenine pathway. The software is freely available to academic users at http://insilab.org/probisdock.
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Affiliation(s)
- Janez Konc
- National Institute of Chemistry, Theory Department, Hajdrihova 19, SI-1001 Ljubljana, Slovenia
| | - Samo Lešnik
- National Institute of Chemistry, Theory Department, Hajdrihova 19, SI-1001 Ljubljana, Slovenia
| | - Blaž Škrlj
- National Institute of Chemistry, Theory Department, Hajdrihova 19, SI-1001 Ljubljana, Slovenia.,Jozef Stefan International Postgraduate School, Jamova cesta 39, SI-1000 Ljubljana, Slovenia.,Jozef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana, Slovenia
| | - Matej Sova
- Faculty of Pharmacy, The Chair of Pharmaceutical Chemistry, Aškerčeva cesta 7, SI-1000 Ljubljana, Slovenia
| | - Matic Proj
- Faculty of Pharmacy, The Chair of Pharmaceutical Chemistry, Aškerčeva cesta 7, SI-1000 Ljubljana, Slovenia
| | - Damijan Knez
- Faculty of Pharmacy, The Chair of Pharmaceutical Chemistry, Aškerčeva cesta 7, SI-1000 Ljubljana, Slovenia
| | - Stanislav Gobec
- Faculty of Pharmacy, The Chair of Pharmaceutical Chemistry, Aškerčeva cesta 7, SI-1000 Ljubljana, Slovenia
| | - Dušanka Janežič
- Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška ulica 8, SI-6000 Koper, Slovenia
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5
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Virtual Screening in Search for a Chemical Probe for Angiotensin-Converting Enzyme 2 (ACE2). Molecules 2021; 26:molecules26247584. [PMID: 34946667 PMCID: PMC8707431 DOI: 10.3390/molecules26247584] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 12/09/2021] [Accepted: 12/10/2021] [Indexed: 01/09/2023] Open
Abstract
We elaborate new models for ACE and ACE2 receptors with an excellent prediction power compared to previous models. We propose promising workflows for working with huge compound collections, thereby enabling us to discover optimized protocols for virtual screening management. The efficacy of elaborated roadmaps is demonstrated through the cost-effective molecular docking of 1.4 billion compounds. Savings of up to 10-fold in CPU time are demonstrated. These developments allowed us to evaluate ACE2/ACE selectivity in silico, which is a crucial checkpoint for developing chemical probes for ACE2.
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6
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Bai B, Zou R, Chan HCS, Li H, Yuan S. MolADI: A Web Server for Automatic Analysis of Protein-Small Molecule Dynamic Interactions. Molecules 2021; 26:molecules26154625. [PMID: 34361778 PMCID: PMC8347168 DOI: 10.3390/molecules26154625] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/28/2021] [Accepted: 07/28/2021] [Indexed: 11/16/2022] Open
Abstract
Protein-ligand interaction analysis is important for drug discovery and rational protein design. The existing online tools adopt only a single conformation of the complex structure for calculating and displaying the interactions, whereas both protein residues and ligand molecules are flexible to some extent. The interactions evolved with time in the trajectories are of greater interest. MolADI is a user-friendly online tool which analyzes the protein-ligand interactions in detail for either a single structure or a trajectory. Interactions can be viewed easily with both 2D graphs and 3D representations. MolADI is available as a web application.
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Affiliation(s)
- Bing Bai
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China; (B.B.); (R.Z.); (H.C.S.C.)
- Shenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China
| | - Rongfeng Zou
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China; (B.B.); (R.Z.); (H.C.S.C.)
- Shenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China
- AlphaMol Science Ltd., 1068 Xueyuan Avenue, Shenzhen 518055, China
| | - H. C. Stephen Chan
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China; (B.B.); (R.Z.); (H.C.S.C.)
- Shenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China
| | - Hongchun Li
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China; (B.B.); (R.Z.); (H.C.S.C.)
- Shenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China
- Correspondence: (H.L.); (S.Y.)
| | - Shuguang Yuan
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China; (B.B.); (R.Z.); (H.C.S.C.)
- Shenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, China
- AlphaMol Science Ltd., 1068 Xueyuan Avenue, Shenzhen 518055, China
- Correspondence: (H.L.); (S.Y.)
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7
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Konc J, Lešnik S, Škrlj B, Janežič D. ProBiS-Dock Database: A Web Server and Interactive Web Repository of Small Ligand-Protein Binding Sites for Drug Design. J Chem Inf Model 2021; 61:4097-4107. [PMID: 34319727 DOI: 10.1021/acs.jcim.1c00454] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
We have developed a new system, ProBiS-Dock, which can be used to determine the different types of protein binding sites for small ligands. The binding sites identified this way are then used to construct a new binding site database, the ProBiS-Dock Database, that allows for the ranking of binding sites according to their utility for drug development. The newly constructed database currently has more than 1.4 million binding sites and offers the possibility to investigate potential drug targets originating from different biological species. The interactive ProBiS-Dock Database, a web server and repository that consists of all small-molecule ligand binding sites in all of the protein structures in the Protein Data Bank, is freely available at http://probis-dock-database.insilab.org. The ProBiS-Dock Database will be regularly updated to keep pace with the growth of the Protein Data Bank, and our anticipation is that it will be useful in drug discovery.
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Affiliation(s)
- Janez Konc
- Theory Department, National Institute of Chemistry, Hajdrihova 19, SI-1000 Ljubljana, Slovenia
| | - Samo Lešnik
- Theory Department, National Institute of Chemistry, Hajdrihova 19, SI-1000 Ljubljana, Slovenia
| | - Blaž Škrlj
- Theory Department, National Institute of Chemistry, Hajdrihova 19, SI-1000 Ljubljana, Slovenia.,Jozef Stefan International Postgraduate School, Jamova cesta 39, SI-1000 Ljubljana, Slovenia
| | - Dušanka Janežič
- Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška ulica 8, SI-6000 Koper, Slovenia
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8
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Pinzi L, Tinivella A, Gagliardelli L, Beneventano D, Rastelli G. LigAdvisor: a versatile and user-friendly web-platform for drug design. Nucleic Acids Res 2021; 49:W326-W335. [PMID: 34023895 PMCID: PMC8262749 DOI: 10.1093/nar/gkab385] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/19/2021] [Accepted: 04/27/2021] [Indexed: 12/17/2022] Open
Abstract
Although several tools facilitating in silico drug design are available, their results are usually difficult to integrate with publicly available information or require further processing to be fully exploited. The rational design of multi-target ligands (polypharmacology) and the repositioning of known drugs towards unmet therapeutic needs (drug repurposing) have raised increasing attention in drug discovery, although they usually require careful planning of tailored drug design strategies. Computational tools and data-driven approaches can help to reveal novel valuable opportunities in these contexts, as they enable to efficiently mine publicly available chemical, biological, clinical, and disease-related data. Based on these premises, we developed LigAdvisor, a data-driven webserver which integrates information reported in DrugBank, Protein Data Bank, UniProt, Clinical Trials and Therapeutic Target Database into an intuitive platform, to facilitate drug discovery tasks as drug repurposing, polypharmacology, target fishing and profiling. As designed, LigAdvisor enables easy integration of similarity estimation results with clinical data, thereby allowing a more efficient exploitation of information in different drug discovery contexts. Users can also develop customizable drug design tasks on their own molecules, by means of ligand- and target-based search modes, and download their results. LigAdvisor is publicly available at https://ligadvisor.unimore.it/.
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Affiliation(s)
- Luca Pinzi
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Annachiara Tinivella
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy.,Clinical and Experimental Medicine, PhD Program, University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Luca Gagliardelli
- Department of Engineering "Enzo Ferrari", University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Domenico Beneventano
- Department of Engineering "Enzo Ferrari", University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Giulio Rastelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy
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Chaudhari R, Fong LW, Tan Z, Huang B, Zhang S. An up-to-date overview of computational polypharmacology in modern drug discovery. Expert Opin Drug Discov 2020; 15:1025-1044. [PMID: 32452701 PMCID: PMC7415563 DOI: 10.1080/17460441.2020.1767063] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 05/06/2020] [Indexed: 12/30/2022]
Abstract
INTRODUCTION In recent years, computational polypharmacology has gained significant attention to study the promiscuous nature of drugs. Despite tremendous challenges, community-wide efforts have led to a variety of novel approaches for predicting drug polypharmacology. In particular, some rapid advances using machine learning and artificial intelligence have been reported with great success. AREAS COVERED In this article, the authors provide a comprehensive update on the current state-of-the-art polypharmacology approaches and their applications, focusing on those reports published after our 2017 review article. The authors particularly discuss some novel, groundbreaking concepts, and methods that have been developed recently and applied to drug polypharmacology studies. EXPERT OPINION Polypharmacology is evolving and novel concepts are being introduced to counter the current challenges in the field. However, major hurdles remain including incompleteness of high-quality experimental data, lack of in vitro and in vivo assays to characterize multi-targeting agents, shortage of robust computational methods, and challenges to identify the best target combinations and design effective multi-targeting agents. Fortunately, numerous national/international efforts including multi-omics and artificial intelligence initiatives as well as most recent collaborations on addressing the COVID-19 pandemic have shown significant promise to propel the field of polypharmacology forward.
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Affiliation(s)
- Rajan Chaudhari
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
| | - Long Wolf Fong
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
- MD Anderson UTHealth Graduate School of Biomedical Sciences, 6767 Bertner Avenue, Houston, Texas 77030, United States
| | - Zhi Tan
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
| | - Beibei Huang
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
| | - Shuxing Zhang
- Intelligent Molecular Discovery Laboratory, Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030, United States
- MD Anderson UTHealth Graduate School of Biomedical Sciences, 6767 Bertner Avenue, Houston, Texas 77030, United States
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10
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Chakraborti S, Bheemireddy S, Srinivasan N. Repurposing drugs against the main protease of SARS-CoV-2: mechanism-based insights supported by available laboratory and clinical data. Mol Omics 2020; 16:474-491. [PMID: 32696772 DOI: 10.1039/d0mo00057d] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The ongoing global pandemic of COVID-19 has brought life to almost a standstill with the implementation of lockdowns and social distancing as some of the preventive measures in the absence of any approved specific therapeutic interventions. To combat this crisis, research communities worldwide are falling back on the existing repertoire of approved/investigational drugs to probe into their anti-coronavirus properties. In this report, we describe our unique efforts in identifying potential drugs that could be repurposed against the main protease of SARS-CoV-2 (SARS-CoV-2 Mpro). To achieve this goal, we have primarily exploited the principles of 'neighbourhood behaviour' in the protein 3D (workflow-I) and chemical 2D structural space (workflow-II) coupled with docking simulations and insights into the possible modes of action of the selected candidates from the available literature. This integrative approach culminated in prioritizing 29 potential repurpose-able agents (20 approved drugs and 9 investigational molecules) against SARS-CoV-2 Mpro. Apart from the approved/investigational anti-viral drugs, other notable hits include anti-bacterial, anti-inflammatory, anti-cancer and anti-coagulant drugs. Our analysis suggests that some of these drugs have the potential to simultaneously modulate the functions of viral proteins and the host response system. Interestingly, many of these identified candidates (12 molecules from workflow-I and several molecules, belonging to the chemical classes of alkaloids, tetracyclines, peptidomimetics, from workflow-II) are suggested to possess anti-viral properties, which is supported by laboratory and clinical data. Furthermore, this work opens a new avenue of research to probe into the molecular mechanism of action of many drugs, which are known to demonstrate anti-viral activity but are so far not known to target viral proteases.
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Affiliation(s)
- Sohini Chakraborti
- Molecular Biophysics Unit, Indian Institute of Science, Bengaluru 560012, India.
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11
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Chintha C, Carlesso A, Gorman AM, Samali A, Eriksson LA. Molecular modeling provides a structural basis for PERK inhibitor selectivity towards RIPK1. RSC Adv 2020; 10:367-375. [PMID: 35558862 PMCID: PMC9092956 DOI: 10.1039/c9ra08047c] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 12/14/2019] [Indexed: 12/25/2022] Open
Abstract
Molecular modelling explains the lack of selectivity for inhibitors GSK2606414 and GSK2656157, as compared to inhibitor AMG44.
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Affiliation(s)
- Chetan Chintha
- Apoptosis Research Centre
- National University of Ireland Galway
- Galway
- Ireland
| | - Antonio Carlesso
- Department of Chemistry and Molecular Biology
- University of Gothenburg
- 405 30 Göteborg
- Sweden
| | - Adrienne M. Gorman
- Apoptosis Research Centre
- National University of Ireland Galway
- Galway
- Ireland
| | - Afshin Samali
- Apoptosis Research Centre
- National University of Ireland Galway
- Galway
- Ireland
| | - Leif A. Eriksson
- Department of Chemistry and Molecular Biology
- University of Gothenburg
- 405 30 Göteborg
- Sweden
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12
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In Silico Laboratory: Tools for Similarity-Based Drug Discovery. Methods Mol Biol 2019. [PMID: 31773644 DOI: 10.1007/978-1-0716-0163-1_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Computational methods that predict and evaluate binding of ligands to receptors implicated in different pathologies have become crucial in modern drug design and discovery. Here, we describe protocols for using the recently developed package of computational tools for similarity-based drug discovery. The ProBiS stand-alone program and web server allow superimposition of protein structures against large protein databases and predict ligands based on detected binding site similarities. GenProBiS allows mapping of human somatic missense mutations related to cancer and non-synonymous single nucleotide polymorphisms and subsequent visual exploration of specific interactions in connection to these mutations. We describe protocols for using LiSiCA, a fast ligand-based virtual screening software that enables easy screening of large databases containing billions of small molecules. Finally, we show the use of BoBER, a web interface that enables user-friendly access to a large database of bioisosteric and scaffold hopping replacements.
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13
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The major secreted protein of the whipworm parasite tethers to matrix and inhibits interleukin-13 function. Nat Commun 2019; 10:2344. [PMID: 31138806 PMCID: PMC6538607 DOI: 10.1038/s41467-019-09996-z] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Accepted: 04/12/2019] [Indexed: 12/19/2022] Open
Abstract
Infection by soil transmitted parasitic helminths, such as Trichuris spp, are ubiquitous in humans and animals but the mechanisms determining persistence of chronic infections are poorly understood. Here we show that p43, the single most abundant protein in T. muris excretions/secretions, is non-immunogenic during infection and has an unusual sequence and structure containing subdomain homology to thrombospondin type 1 and interleukin (IL)−13 receptor (R) α2. Binding of p43 to IL-13, the key effector cytokine responsible for T. muris expulsion, inhibits IL-13 function both in vitro and in vivo. Tethering of p43 to matrix proteoglycans presents a bound source of p43 to facilitate interaction with IL-13, which may underpin chronic intestinal infection. Our results suggest that exploiting the biology of p43 may open up new approaches to modulating IL-13 function and control of Trichuris infections. In the study, the authors identify a protein excreted by the parasite Trichuris muris, p43, which can modulate IL-13 function, a key cytokine involved in host protection. These data suggest that p43 may be a novel therapeutic target for both whipworm infections and IL13 mediated pathologies.
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14
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Gilberg E, Gütschow M, Bajorath J. Promiscuous Ligands from Experimentally Determined Structures, Binding Conformations, and Protein Family-Dependent Interaction Hotspots. ACS OMEGA 2019; 4:1729-1737. [PMID: 31459430 PMCID: PMC6648413 DOI: 10.1021/acsomega.8b03481] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 01/10/2019] [Indexed: 05/06/2023]
Abstract
Compound promiscuity is often attributed to nonspecific binding or assay artifacts. On the other hand, it is well-known that many pharmaceutically relevant compounds are capable of engaging multiple targets in vivo, giving rise to polypharmacology. To explore and better understand promiscuous binding characteristics of small molecules, we have searched X-ray structures (and very few qualifying solution structures) for ligands that bind to multiple distantly related or unrelated target proteins. Experimental structures of a given ligand bound to different targets represent high-confidence data for exploring promiscuous binding events. A total of 192 ligands were identified that formed crystallographic complexes with proteins from different families and for which activity data were available. These "multifamily" compounds included endogenous ligands and were often more polar than other bound compounds and active in the submicromolar range. Unexpectedly, many promiscuous ligands displayed conserved or similar binding conformations in different active sites. Others were found to conformationally adjust to binding sites of different architectures. A comprehensive analysis of ligand-target interactions revealed that multifamily ligands frequently formed different interaction hotspots in binding sites, even if their bound conformations were similar, thus providing a rationale for promiscuous binding events at the molecular level of detail. As a part of this work, all multifamily ligands we have identified and associated activity data are made freely available.
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Affiliation(s)
- Erik Gilberg
- Department
of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology
and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany
- Pharmaceutical
Institute, Rheinische Friedrich-Wilhelms-Universität, An der Immenburg 4, D-53121 Bonn, Germany
| | - Michael Gütschow
- Pharmaceutical
Institute, Rheinische Friedrich-Wilhelms-Universität, An der Immenburg 4, D-53121 Bonn, Germany
| | - Jürgen Bajorath
- Department
of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology
and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany
- E-mail: .
Phone: 49-228-2699-306 (J.B.)
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15
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Junqueira LO, Costa MOLD, Rando DGG. N-Myristoyltransferases as antileishmanial targets: a piggyback approach with benzoheterocyclic analogues. BRAZ J PHARM SCI 2019. [DOI: 10.1590/s2175-97902019000218087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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16
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Ehrt C, Brinkjost T, Koch O. A benchmark driven guide to binding site comparison: An exhaustive evaluation using tailor-made data sets (ProSPECCTs). PLoS Comput Biol 2018; 14:e1006483. [PMID: 30408032 PMCID: PMC6224041 DOI: 10.1371/journal.pcbi.1006483] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 09/02/2018] [Indexed: 11/24/2022] Open
Abstract
The automated comparison of protein-ligand binding sites provides useful insights into yet unexplored site similarities. Various stages of computational and chemical biology research can benefit from this knowledge. The search for putative off-targets and the establishment of polypharmacological effects by comparing binding sites led to promising results for numerous projects. Although many cavity comparison methods are available, a comprehensive analysis to guide the choice of a tool for a specific application is wanting. Moreover, the broad variety of binding site modeling approaches, comparison algorithms, and scoring metrics impedes this choice. Herein, we aim to elucidate strengths and weaknesses of binding site comparison methodologies. A detailed benchmark study is the only possibility to rationalize the selection of appropriate tools for different scenarios. Specific evaluation data sets were developed to shed light on multiple aspects of binding site comparison. An assembly of all applied benchmark sets (ProSPECCTs–Protein Site Pairs for the Evaluation of Cavity Comparison Tools) is made available for the evaluation and optimization of further and still emerging methods. The results indicate the importance of such analyses to facilitate the choice of a methodology that complies with the requirements of a specific scientific challenge. Binding site similarities are useful in the context of promiscuity prediction, drug repurposing, the analysis of protein-ligand and protein-protein complexes, function prediction, and further fields of general interest in chemical biology and biochemistry. Many years of research have led to the development of a multitude of methods for binding site analysis and comparison. On the one hand, their availability supports research. On the other hand, the huge number of methods hampers the efficient selection of a specific tool. Our research is dedicated to the analysis of different cavity comparison tools. We use several binding site data sets to establish guidelines which can be applied to ensure a successful application of comparison methods by circumventing potential pitfalls.
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Affiliation(s)
- Christiane Ehrt
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany
| | - Tobias Brinkjost
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany
- Department of Computer Science, TU Dortmund University, Dortmund, Germany
| | - Oliver Koch
- Faculty of Chemistry and Chemical Biology, TU Dortmund University, Dortmund, Germany
- * E-mail: ,
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17
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Ranking Enzyme Structures in the PDB by Bound Ligand Similarity to Biological Substrates. Structure 2018; 26:565-571.e3. [PMID: 29551288 PMCID: PMC5890617 DOI: 10.1016/j.str.2018.02.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Revised: 01/26/2018] [Accepted: 02/09/2018] [Indexed: 11/22/2022]
Abstract
There are numerous applications that use the structures of protein-ligand complexes from the PDB, such as 3D pharmacophore identification, virtual screening, and fragment-based drug design. The structures underlying these applications are potentially much more informative if they contain biologically relevant bound ligands, with high similarity to the cognate ligands. We present a study of ligand-enzyme complexes that compares the similarity of bound and cognate ligands, enabling the best matches to be identified. We calculate the molecular similarity scores using a method called PARITY (proportion of atoms residing in identical topology), which can conveniently be combined to give a similarity score for all cognate reactants or products in the reaction. Thus, we generate a rank-ordered list of related PDB structures, according to the biological similarity of the ligands bound in the structures. We present PARITY, matching atoms in identical topology to gauge ligand similarity Bound-cognate ligand similarity is a useful metric for ranking PDB structures Only 26% of enzyme structures in the PDB have bound-cognate ligand similarity ≥0.7 We provide rank-ordered lists of PDBs with the most biologically relevant ligands
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18
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Škrlj B, Kunej T, Konc J. Insights from Ion Binding Site Network Analysis into Evolution and Functions of Proteins. Mol Inform 2018; 37:e1700144. [PMID: 29418080 DOI: 10.1002/minf.201700144] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 02/01/2018] [Indexed: 01/05/2023]
Abstract
Many biological phenomena can be represented as complex networks. Using a protein binding site comparison approach, we generated a network of ion binding sites on the scale of all known protein structures from the Protein Data Bank. We found that this ion binding site similarity network is scale-free, indicating a network in which a few ion binding site scaffolds are the network hubs, and these are connected to hundreds of nodes, whereas the vast majority of nodes have only a few neighbors. Enrichment and statistical analysis of the network components and communities yielded insights into underlying processes from the functional and the structural perspective. Largest components and communities were observed to be closely related to basic metabolic processes and some of the most common structural folds, which, from the evolutionary point of view, indicates that they may be the oldest ones. Further, we derived the first comprehensive map of ion interchangeability, based on binding site similarity. Several highly interchangeable protein-ion binding site pairs emerged (e.g., Ca2+ and Mg2+ ), as well as structurally distinct ones. The constructed network of ion binding site similarities will aid in understanding the general principles of protein-ion binding sites structure, function and evolution. We demonstrate potential uses of the network on proteins involved in cancer development and immune response, where individual ions play prominent roles in disease development.
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Affiliation(s)
- Blaž Škrlj
- Department of molecular modeling, National Institute of Chemistry, Hajdrihova 19, Ljubljana, Slovenia.,Jožef Stefan International Postgraduate School, Jamova cesta 39, 1000, Ljubljana, Slovenia
| | - Tanja Kunej
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Slovenia
| | - Janez Konc
- Department of molecular modeling, National Institute of Chemistry, Hajdrihova 19, Ljubljana, Slovenia
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19
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BoBER: web interface to the base of bioisosterically exchangeable replacements. J Cheminform 2017; 9:62. [PMID: 29234984 PMCID: PMC5727005 DOI: 10.1186/s13321-017-0251-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Accepted: 12/04/2017] [Indexed: 11/10/2022] Open
Abstract
We describe a novel freely available web server Base of Bioisosterically Exchangeable Replacements (BoBER), which implements an interface to a database of bioisosteric and scaffold hopping replacements. Bioisosterism and scaffold hopping are key concepts in drug design and optimization, and can be defined as replacements of biologically active compound's fragments with other fragments to improve activity, reduce toxicity, change bioavailability or to diversify the scaffold space. Our web server enables fast and user-friendly searches for bioisosteric and scaffold replacements which were obtained by mining the whole Protein Data Bank. The working of the web server is presented on an existing MurF inhibitor as example. BoBER web server enables medicinal chemists to quickly search for and get new and unique ideas about possible bioisosteric or scaffold hopping replacements that could be used to improve hit or lead drug-like compounds.
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20
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Jukič M, Konc J, Gobec S, Janežič D. Identification of Conserved Water Sites in Protein Structures for Drug Design. J Chem Inf Model 2017; 57:3094-3103. [DOI: 10.1021/acs.jcim.7b00443] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Marko Jukič
- Faculty of Pharmacy, University of Ljubljana, Aškerčeva 7, SI−1000, Ljubljana, Slovenia
| | - Janez Konc
- National Institute of Chemistry, Hajdrihova 19, SI−1000, Ljubljana, Slovenia
- Faculty of
Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI−6000 Koper, Slovenia
| | - Stanislav Gobec
- Faculty of Pharmacy, University of Ljubljana, Aškerčeva 7, SI−1000, Ljubljana, Slovenia
| | - Dušanka Janežič
- Faculty of
Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI−6000 Koper, Slovenia
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21
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Sam E, Athri P. Web-based drug repurposing tools: a survey. Brief Bioinform 2017; 20:299-316. [DOI: 10.1093/bib/bbx125] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Indexed: 12/15/2022] Open
Affiliation(s)
- Elizabeth Sam
- Department of Computer Science & Engineering Amrita, University Bengaluru, India
| | - Prashanth Athri
- Department of Computer Science & Engineering Amrita, University Bengaluru, India
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22
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Lee J, Konc J, Janežič D, Brooks BR. Global organization of a binding site network gives insight into evolution and structure-function relationships of proteins. Sci Rep 2017; 7:11652. [PMID: 28912495 PMCID: PMC5599562 DOI: 10.1038/s41598-017-10412-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 08/07/2017] [Indexed: 01/06/2023] Open
Abstract
The global organization of protein binding sites is analyzed by constructing a weighted network of binding sites based on their structural similarities and detecting communities of structurally similar binding sites based on the minimum description length principle. The analysis reveals that there are two central binding site communities that play the roles of the network hubs of smaller peripheral communities. The sizes of communities follow a power-law distribution, which indicates that the binding sites included in larger communities may be older and have been evolutionary structural scaffolds of more recent ones. Structurally similar binding sites in the same community bind to diverse ligands promiscuously and they are also embedded in diverse domain structures. Understanding the general principles of binding site interplay will pave the way for improved drug design and protein design.
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Affiliation(s)
- Juyong Lee
- Department of Chemistry, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon, 24341, Republic of Korea. .,Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, 20892, United States.
| | - Janez Konc
- Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000, Koper, Slovenia.,National Institute of Chemistry, Hajdrihova 19, SI-1000, Ljubljana, Slovenia
| | - Dušanka Janežič
- Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000, Koper, Slovenia
| | - Bernard R Brooks
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, 20892, United States
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23
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Trafalis DT, Polonifi A, Dalezis P, Nikoleousakos N, Katsamakas S, Sarli V. Targeting on poly(ADP-ribose) polymerase activity with DNA-damaging hybrid lactam-steroid alkylators in wild-type and BRCA1-mutated ovarian cancer cells. Chem Biol Drug Des 2017; 90:854-866. [PMID: 28432813 DOI: 10.1111/cbdd.13006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Revised: 03/25/2017] [Accepted: 04/05/2017] [Indexed: 12/28/2022]
Abstract
Conjugated lactam-steroid alkylators (LSA) have been shown to exhibit superior activity at controlling cancer models and overlap drug resistance to conventional chemjournalapy. Hybrid LSA combine two active compounds in a single molecule and incorporate modified steroids bearing lactam moiety in one or more steroid rings functioning as vectors for cytotoxic agents. We first describe a novel class of LSA that generate excellent anticancer activity against UWB1.289 and UWB1.289 + BRCA1 human ovarian cancer cell lines. Both UWB1.289 and UWB1.289 + BRCA1 cells carry mutations in the tumor suppressor gene TP53 while UWB1.289 cell line carries a germline BRCA1 mutation. In vitro, in vivo, and in silico, experimental methods were utilized to determine the poly(ADP-ribose) polymerases (PARPs) activity and mRNA transcription, DNA damage, cytostatic and cytotoxic effects, and virtual molecular interactions, in order to study the molecular mechanisms of activity of the tested LSA. LSA produce anticancer activity through dual action by combining the direct induction of cellular DNA damage with the inhibition of PARP activity and consecutive DNA repair activity. BRCA1-mutated UWB1.289 ovarian cancer cells with defective PARP-oriented repair mechanism show significantly higher sensitivity to these agents. Combined drug effect on DNA damage and repair is a novel approach in cancer therapeutics.
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Affiliation(s)
- Dimitrios T Trafalis
- Laboratory of Pharmacology, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Aikaterini Polonifi
- Laboratory of Pharmacology, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Panayiotis Dalezis
- Laboratory of Pharmacology, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Nikolaos Nikoleousakos
- Laboratory of Pharmacology, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Sotirios Katsamakas
- Department of Pharmaceutical Chemistry, School of Pharmacy, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Vasiliki Sarli
- Department of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece
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24
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ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2017; 128:24-32. [PMID: 28212856 DOI: 10.1016/j.pbiomolbio.2017.02.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Revised: 12/14/2016] [Accepted: 02/07/2017] [Indexed: 01/30/2023]
Abstract
ProBiS (Protein Binding Sites) Tools consist of algorithm, database, and web servers for prediction of binding sites and protein ligands based on the detection of structurally similar binding sites in the Protein Data Bank. In this article, we review the operations that ProBiS Tools perform, provide comments on the evolution of the tools, and give some implementation details. We review some of its applications to biologically interesting proteins. ProBiS Tools are freely available at http://probis.cmm.ki.si and http://probis.nih.gov.
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25
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Abstract
The dramatic increase in the number of protein sequences and structures deposited in biological databases has led to the development of many bioinformatics tools and programs to manage, validate, compare, and interpret this large volume of data. In addition, powerful tools are being developed to use this sequence and structural data to facilitate protein classification and infer biological function of newly identified proteins. This chapter covers freely available bioinformatics resources on the World Wide Web that are commonly used for protein structure analysis.
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Affiliation(s)
- Jason J Paxman
- Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Rm 521, LIMS1, Kingsbury Drive, Bundoora, Melbourne, VIC, 3086, Australia
| | - Begoña Heras
- Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Rm 521, LIMS1, Kingsbury Drive, Bundoora, Melbourne, VIC, 3086, Australia.
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26
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Štular T, Lešnik S, Rožman K, Schink J, Zdouc M, Ghysels A, Liu F, Aldrich CC, Haupt VJ, Salentin S, Daminelli S, Schroeder M, Langer T, Gobec S, Janežič D, Konc J. Discovery of Mycobacterium tuberculosis InhA Inhibitors by Binding Sites Comparison and Ligands Prediction. J Med Chem 2016; 59:11069-11078. [PMID: 27936766 DOI: 10.1021/acs.jmedchem.6b01277] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Drug discovery is usually focused on a single protein target; in this process, existing compounds that bind to related proteins are often ignored. We describe ProBiS plugin, extension of our earlier ProBiS-ligands approach, which for a given protein structure allows prediction of its binding sites and, for each binding site, the ligands from similar binding sites in the Protein Data Bank. We developed a new database of precalculated binding site comparisons of about 290000 proteins to allow fast prediction of binding sites in existing proteins. The plugin enables advanced viewing of predicted binding sites, ligands' poses, and their interactions in three-dimensional graphics. Using the InhA query protein, an enoyl reductase enzyme in the Mycobacterium tuberculosis fatty acid biosynthesis pathway, we predicted its possible ligands and assessed their inhibitory activity experimentally. This resulted in three previously unrecognized inhibitors with novel scaffolds, demonstrating the plugin's utility in the early drug discovery process.
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Affiliation(s)
- Tanja Štular
- National Institute of Chemistry , Hajdrihova 19, SI-1000 Ljubljana, Slovenia
| | - Samo Lešnik
- National Institute of Chemistry , Hajdrihova 19, SI-1000 Ljubljana, Slovenia
| | - Kaja Rožman
- Faculty of Pharmacy, University of Ljubljana , Aškerčeva cesta 7, SI-1000 Ljubljana, Slovenia
| | - Julia Schink
- Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska , Glagoljaška 8, SI-6000 Koper, Slovenia
| | - Mitja Zdouc
- Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska , Glagoljaška 8, SI-6000 Koper, Slovenia
| | - An Ghysels
- Center for Molecular Modeling, Ghent University , Technologiepark 903, 9052 Zwijnaarde, Belgium
| | - Feng Liu
- AAT Bioquest, Inc. , 520 Mercury Drive, Sunnyvale, California 94085, United States
| | - Courtney C Aldrich
- Department of Medicinal Chemistry, University of Minnesota , 308 Harvard Street Southeast, Minneapolis, Minnesota 55455, United States
| | - V Joachim Haupt
- Biotechnology Center (BIOTEC), Technische Universität Dresden , 01307 Dresden, Germany
| | - Sebastian Salentin
- Biotechnology Center (BIOTEC), Technische Universität Dresden , 01307 Dresden, Germany
| | - Simone Daminelli
- Biotechnology Center (BIOTEC), Technische Universität Dresden , 01307 Dresden, Germany
| | - Michael Schroeder
- Biotechnology Center (BIOTEC), Technische Universität Dresden , 01307 Dresden, Germany
| | - Thierry Langer
- Department of Pharmaceutical Chemistry, Faculty of Life Sciences, University of Vienna , Althanstrasse 14, A-1090 Vienna, Austria
| | - Stanislav Gobec
- Faculty of Pharmacy, University of Ljubljana , Aškerčeva cesta 7, SI-1000 Ljubljana, Slovenia
| | - Dušanka Janežič
- Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska , Glagoljaška 8, SI-6000 Koper, Slovenia
| | - Janez Konc
- National Institute of Chemistry , Hajdrihova 19, SI-1000 Ljubljana, Slovenia.,Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska , Glagoljaška 8, SI-6000 Koper, Slovenia
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27
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Elucidating a chemical defense mechanism of Antarctic sponges: A computational study. J Mol Graph Model 2016; 71:104-115. [PMID: 27894019 DOI: 10.1016/j.jmgm.2016.11.004] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Revised: 10/21/2016] [Accepted: 11/06/2016] [Indexed: 11/22/2022]
Abstract
In 2000, a novel secondary metabolite (erebusinone, Ereb) was isolated from the Antarctic sea sponge, Isodictya erinacea. The bioactivity of Ereb was investigated, and it was found to inhibit molting when fed to the arthropod species Orchomene plebs. Xanthurenic acid (XA) is a known endogenous molt regulator present in arthropods. Experimental studies have confirmed that XA inhibits molting by binding to either (or both) of two P450 enzymes (CYP315a1 or CYP314a1) that are responsible for the final two hydroxylations in the production of the molt-inducing hormone, 20-hydroxyecdysone (20E). The lack of crystal structures and biochemical assays for CYP315a1 or CYP314a1, has prevented further experimental exploration of XA and Ereb's molt inhibition mechanisms. Herein, a wide array of computational techniques - homology modeling, molecular dynamics simulations, binding site bioinformatics, flexible receptor-flexible ligand docking, and molecular mechanics-generalized Born surface area calculations - have been employed to elucidate the structure-function relationships between the aforementioned P450s and the two described small molecule inhibitors (Ereb and XA). Results indicate that Ereb likely targets CYP315a1 by interacting with a network of aromatic residues in the binding site, while XA may inhibit both CYP315a1 and CYP314a1 because of its aromatic, as well as charged nature.
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28
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Tibaut T, Borišek J, Novič M, Turk D. Comparison of in silico tools for binding site prediction applied for structure-based design of autolysin inhibitors. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2016; 27:573-587. [PMID: 27686112 DOI: 10.1080/1062936x.2016.1217271] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Accepted: 07/22/2016] [Indexed: 06/06/2023]
Abstract
Autolysin E (AtlE) is a bacteriolytic enzyme which plays an important role in division and growth of bacterial cells and therefore represents a promising potential drug target. Its 3D structure has been recently elucidated. We used in silico prediction tools to study substrate or ligand (inhibitor) binding regions of AtlE. We applied several freely available tools and a commercial tool for binding site identification and compared results of the prediction. Calculation time, number of predictions and output data provided by specific software vary according to the different approaches utilized by specific method categories. Despite different approaches, binding sites in similar locations on the protein were predicted. Specific amino acid residues that form these binding sites were predicted as binding residues. The predicted residues, especially those with predicted highest conservation score, could theoretically have catalytic and binding properties. According to our results, we assume that E138, which has the highest conservation score, is the catalytic residue and F161, G162 and Y224, which are also highly conserved, are responsible for substrate binding. Ligands developed with binding specificity towards these residues could inhibit the catalysis and binding of the substrate of AtlE. The molecules with inhibitory potency could therefore represent potential new antibacterial agents.
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Affiliation(s)
- T Tibaut
- a Laboratory of Chemometrics , National Institute of Chemistry , Ljubljana , Slovenia
| | - J Borišek
- a Laboratory of Chemometrics , National Institute of Chemistry , Ljubljana , Slovenia
| | - M Novič
- a Laboratory of Chemometrics , National Institute of Chemistry , Ljubljana , Slovenia
| | - D Turk
- b Department of Biochemistry and Molecular and Structural Biology , Institute Jozef Stefan , Ljubljana , Slovenia
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29
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Lee HS, Im W. G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design. Protein Sci 2016; 25:865-76. [PMID: 26813336 DOI: 10.1002/pro.2890] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2015] [Revised: 01/20/2016] [Accepted: 01/21/2016] [Indexed: 11/11/2022]
Abstract
Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/.
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Affiliation(s)
- Hui Sun Lee
- Higuchi Biosciences Center, University of Kansas, Lawrence, Kansas, 66047
| | - Wonpil Im
- Department of Molecular Biosciences and Center for Computational Biology, University of Kansas, Lawrence, Kansas, 66047
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30
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Konc J, Miller BT, Štular T, Lešnik S, Woodcock HL, Brooks BR, Janežič D. ProBiS-CHARMMing: Web Interface for Prediction and Optimization of Ligands in Protein Binding Sites. J Chem Inf Model 2015; 55:2308-14. [DOI: 10.1021/acs.jcim.5b00534] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Janez Konc
- Laboratory
for Molecular Modeling, National Institute of Chemistry, Hajdrihova
19, SI-1000, Ljubljana, Slovenia
- Faculty
of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000, Koper, Slovenia
| | - Benjamin T. Miller
- Laboratory
of Computational Biology, Biochemistry and Biophysics Center, National
Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Tanja Štular
- Faculty
of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000, Koper, Slovenia
| | - Samo Lešnik
- Laboratory
for Molecular Modeling, National Institute of Chemistry, Hajdrihova
19, SI-1000, Ljubljana, Slovenia
| | - H. Lee Woodcock
- Department
of Chemistry, University of South Florida, 4202 East Fowler Ave., Tampa, Florida 33620, United States
| | - Bernard R. Brooks
- Laboratory
of Computational Biology, Biochemistry and Biophysics Center, National
Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Dušanka Janežič
- Faculty
of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, SI-6000, Koper, Slovenia
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31
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Hu GM, Mai TL, Chen CM. Clustering and visualizing similarity networks of membrane proteins. Proteins 2015; 83:1450-61. [PMID: 26011797 DOI: 10.1002/prot.24832] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2015] [Revised: 04/23/2015] [Accepted: 05/17/2015] [Indexed: 01/05/2023]
Abstract
We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information.
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Affiliation(s)
- Geng-Ming Hu
- Department of Physics, National Taiwan Normal University, Taipei, Taiwan
| | - Te-Lun Mai
- Department of Physics, National Taiwan Normal University, Taipei, Taiwan
| | - Chi-Ming Chen
- Department of Physics, National Taiwan Normal University, Taipei, Taiwan
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32
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Salentin S, Schreiber S, Haupt VJ, Adasme MF, Schroeder M. PLIP: fully automated protein-ligand interaction profiler. Nucleic Acids Res 2015; 43:W443-7. [PMID: 25873628 PMCID: PMC4489249 DOI: 10.1093/nar/gkv315] [Citation(s) in RCA: 1193] [Impact Index Per Article: 132.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Accepted: 03/28/2015] [Indexed: 11/14/2022] Open
Abstract
The characterization of interactions in protein-ligand complexes is essential for research in structural bioinformatics, drug discovery and biology. However, comprehensive tools are not freely available to the research community. Here, we present the protein-ligand interaction profiler (PLIP), a novel web service for fully automated detection and visualization of relevant non-covalent protein-ligand contacts in 3D structures, freely available at projects.biotec.tu-dresden.de/plip-web. The input is either a Protein Data Bank structure, a protein or ligand name, or a custom protein-ligand complex (e.g. from docking). In contrast to other tools, the rule-based PLIP algorithm does not require any structure preparation. It returns a list of detected interactions on single atom level, covering seven interaction types (hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation interactions, salt bridges, water bridges and halogen bonds). PLIP stands out by offering publication-ready images, PyMOL session files to generate custom images and parsable result files to facilitate successive data processing. The full python source code is available for download on the website. PLIP's command-line mode allows for high-throughput interaction profiling.
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Affiliation(s)
- Sebastian Salentin
- Biotechnology Center (BIOTEC), TU Dresden, Tatzberg 47-49, 01307 Dresden, Germany
| | - Sven Schreiber
- Biotechnology Center (BIOTEC), TU Dresden, Tatzberg 47-49, 01307 Dresden, Germany
| | - V Joachim Haupt
- Biotechnology Center (BIOTEC), TU Dresden, Tatzberg 47-49, 01307 Dresden, Germany
| | - Melissa F Adasme
- Biotechnology Center (BIOTEC), TU Dresden, Tatzberg 47-49, 01307 Dresden, Germany Escuela de Ingeniería en Bioinformática, Universidad de Talca, Avda. Lircay s/n Talca, 3460000, Chile
| | - Michael Schroeder
- Biotechnology Center (BIOTEC), TU Dresden, Tatzberg 47-49, 01307 Dresden, Germany
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33
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Zhang Y, Zhao Z, Liu H. Deriving Chemically Essential Interactions Based on Active Site Alignments and Quantum Chemical Calculations: A Case Study on Glycoside Hydrolases. ACS Catal 2015. [DOI: 10.1021/cs501709d] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Yinliang Zhang
- School
of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China
| | - Zheng Zhao
- Hefei
Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China
| | - Haiyan Liu
- School
of Life Sciences, University of Science and Technology of China, 443 Huangshan Road, Hefei, Anhui 230027, China
- Hefei National Laboratory for Physical Sciences at the Microscales, Hefei, Anhui 230027, China
- Hefei
Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China
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34
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Salentin S, Haupt VJ, Daminelli S, Schroeder M. Polypharmacology rescored: protein-ligand interaction profiles for remote binding site similarity assessment. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2014; 116:174-86. [PMID: 24923864 DOI: 10.1016/j.pbiomolbio.2014.05.006] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2014] [Revised: 05/20/2014] [Accepted: 05/26/2014] [Indexed: 11/27/2022]
Abstract
Detection of remote binding site similarity in proteins plays an important role for drug repositioning and off-target effect prediction. Various non-covalent interactions such as hydrogen bonds and van-der-Waals forces drive ligands' molecular recognition by binding sites in proteins. The increasing amount of available structures of protein-small molecule complexes enabled the development of comparative approaches. Several methods have been developed to characterize and compare protein-ligand interaction patterns. Usually implemented as fingerprints, these are mainly used for post processing docking scores and (off-)target prediction. In the latter application, interaction profiles detect similarities in the bound interactions of different ligands and thus identify essential interactions between a protein and its small molecule ligands. Interaction pattern similarity correlates with binding site similarity and is thus contributing to a higher precision in binding site similarity assessment of proteins with distinct global structure. This renders it valuable for existing drug repositioning approaches in structural bioinformatics. Current methods to characterize and compare structure-based interaction patterns - both for protein-small-molecule and protein-protein interactions - as well as their potential in target prediction will be reviewed in this article. The question of how the set of interaction types, flexibility or water-mediated interactions, influence the comparison of interaction patterns will be discussed. Due to the wealth of protein-ligand structures available today, predicted targets can be ranked by comparing their ligand interaction pattern to patterns of the known target. Such knowledge-based methods offer high precision in comparison to methods comparing whole binding sites based on shape and amino acid physicochemical similarity.
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35
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Konc J, Janežič D. ProBiS-ligands: a web server for prediction of ligands by examination of protein binding sites. Nucleic Acids Res 2014; 42:W215-20. [PMID: 24861616 PMCID: PMC4086080 DOI: 10.1093/nar/gku460] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
The ProBiS-ligands web server predicts binding of ligands to a protein structure. Starting with a protein structure or binding site, ProBiS-ligands first identifies template proteins in the Protein Data Bank that share similar binding sites. Based on the superimpositions of the query protein and the similar binding sites found, the server then transposes the ligand structures from those sites to the query protein. Such ligand prediction supports many activities, e.g. drug repurposing. The ProBiS-ligands web server, an extension of the ProBiS web server, is open and free to all users at http://probis.cmm.ki.si/ligands.
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Affiliation(s)
- Janez Konc
- National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
| | - Dušanka Janežič
- University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška 8, 6000 Koper, Slovenia
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36
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Hargis JC, Vankayala SL, White JK, Woodcock HL. Identification and Characterization of Noncovalent Interactions That Drive Binding and Specificity in DD-Peptidases and β-Lactamases. J Chem Theory Comput 2014; 10:855-864. [PMID: 24803854 PMCID: PMC3985439 DOI: 10.1021/ct400968v] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2013] [Indexed: 11/29/2022]
Abstract
![]()
Bacterial
resistance to standard (i.e., β-lactam-based) antibiotics
has become a global pandemic. Simultaneously, research into the underlying
causes of resistance has slowed substantially, although its importance
is universally recognized. Key to unraveling critical details is characterization
of the noncovalent interactions that govern binding and specificity
(DD-peptidases, antibiotic targets, versus β-lactamases, the
evolutionarily
derived enzymes that play a major role in resistance) and ultimately
resistance as a whole. Herein, we describe a detailed investigation
that elicits new chemical insights into these underlying intermolecular
interactions. Benzylpenicillin and a novel β-lactam peptidomimetic
complexed to the Stremptomyces R61
peptidase are examined using an arsenal of computational techniques:
MD simulations, QM/MM calculations, charge perturbation analysis,
QM/MM orbital analysis, bioinformatics, flexible receptor/flexible
ligand docking, and computational ADME predictions. Several key molecular
level interactions are identified that not only shed light onto fundamental
resistance mechanisms, but also offer explanations for observed specificity.
Specifically, an extended π–π network is elucidated
that suggests antibacterial resistance has evolved, in part, due to
stabilizing aromatic interactions. Additionally, interactions between
the protein and peptidomimetic substrate are identified and characterized.
Of particular interest is a water-mediated salt bridge between Asp217
and the positively charged N-terminus of the peptidomimetic, revealing
an interaction that may significantly contribute to β-lactam
specificity. Finally, interaction information is used to suggest modifications
to current β-lactam compounds that should both improve binding
and specificity in DD-peptidases and their physiochemical properties.
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Affiliation(s)
- Jacqueline C Hargis
- Department of Chemistry, University of South Florida , 4202 East Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
| | - Sai Lakshmana Vankayala
- Department of Chemistry, University of South Florida , 4202 East Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
| | - Justin K White
- Department of Chemistry, University of South Florida , 4202 East Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
| | - H Lee Woodcock
- Department of Chemistry, University of South Florida , 4202 East Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
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37
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Konc J, Janežič D. Binding site comparison for function prediction and pharmaceutical discovery. Curr Opin Struct Biol 2013; 25:34-9. [PMID: 24878342 DOI: 10.1016/j.sbi.2013.11.012] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2013] [Revised: 11/26/2013] [Accepted: 11/27/2013] [Indexed: 11/30/2022]
Abstract
While structural genomics resulted in thousands of new protein crystal structures, we still do not know the functions of most of these proteins. One reason for this shortcoming is their unique sequences or folds, which leaves them assigned as proteins of 'unknown function'. Recent advances in and applications of cutting edge binding site comparison algorithms for binding site detection and function prediction have begun to shed light on this problem. Here, we review these algorithms and their use in function prediction and pharmaceutical discovery. Finding common binding sites in weakly related proteins may lead to the discovery of new protein functions and to novel ways of drug discovery.
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Affiliation(s)
- Janez Konc
- National Institute of Chemistry, Ljubljana, Slovenia
| | - Dušanka Janežič
- University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies, Koper, Slovenia.
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38
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Vankayala SL, Hargis JC, Woodcock HL. How does catalase release nitric oxide? A computational structure-activity relationship study. J Chem Inf Model 2013; 53:2951-61. [PMID: 24087936 DOI: 10.1021/ci400395c] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Hydroxyurea (HU) is the only FDA approved medication for treating sickle cell disease in adults. The primary mechanism of action is pharmacological elevation of nitric oxide (NO) levels which induces propagation of fetal hemoglobin. HU is known to undergo redox reactions with heme based enzymes like hemoglobin and catalase to produce NO. However, specific details about the HU based NO release remain unknown. Experimental studies indicate that interaction of HU with human catalase compound I produces NO. Presently, we combine flexible receptor-flexible substrate induced fit docking (IFD) with energy decomposition analyses to examine the atomic level details of a possible key step in the clinical conversion of HU to NO. Substrate binding modes of nine HU analogs with catalase compound I were investigated to determine the essential properties necessary for effective NO release. Three major binding orientations were found that provide insight into the possible reaction mechanisms for producing NO. Further results show that anion/radical intermediates produced as part of these mechanisms would be stabilized by hydrogen bonding interactions from distal residues His75, Asn148, Gln168, and oxoferryl-heme. These details will ideally contribute to both a clearer mechanistic picture and provide insights for future structure based drug design efforts.
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Affiliation(s)
- Sai Lakshmana Vankayala
- Department of Chemistry, University of South Florida , 4202 E. Fowler Avenue, CHE205, Tampa, Florida 33620-5250, United States
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39
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Villoutreix BO, Lagorce D, Labbé CM, Sperandio O, Miteva MA. One hundred thousand mouse clicks down the road: selected online resources supporting drug discovery collected over a decade. Drug Discov Today 2013; 18:1081-9. [PMID: 23831439 DOI: 10.1016/j.drudis.2013.06.013] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2013] [Revised: 06/18/2013] [Accepted: 06/26/2013] [Indexed: 12/17/2022]
Abstract
Online resources enabling and supporting drug discovery have blossomed during the past ten years. However, drug hunters commonly find themselves overwhelmed by the proliferation of these computer-based resources. Ten years ago, we, the authors of this review, felt that a comprehensive list of in silico resources relating to drug discovery was needed. Especially because the internet provides a wealth of inspiring tools that, if fully exploited, could greatly assist the process. We present here a compilation of online tools and databases collected over the past decade. The tools were essentially found through literature and internet searches and, currently, our list contains over 1500 URLs. We also briefly highlight some recently reported services and comment about ongoing and future efforts in the field.
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Affiliation(s)
- Bruno O Villoutreix
- Université Paris Diderot, Sorbonne Paris Cité, Inserm UMR-S 973, Molécules Thérapeutiques In Silico, 39 rue Helene Brion, 75013 Paris, France.
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40
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Haupt VJ, Daminelli S, Schroeder M. Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key. PLoS One 2013; 8:e65894. [PMID: 23805191 PMCID: PMC3689763 DOI: 10.1371/journal.pone.0065894] [Citation(s) in RCA: 107] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2012] [Accepted: 04/30/2013] [Indexed: 11/19/2022] Open
Abstract
Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) – a drug’s ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor influence.
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Affiliation(s)
| | | | - Michael Schroeder
- Biotechnology Center (BIOTEC), TU Dresden, Dresden, Germany
- * E-mail:
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41
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Verma R, Schwaneberg U, Roccatano D. Computer-Aided Protein Directed Evolution: a Review of Web Servers, Databases and other Computational Tools for Protein Engineering. Comput Struct Biotechnol J 2012; 2:e201209008. [PMID: 24688649 PMCID: PMC3962222 DOI: 10.5936/csbj.201209008] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2012] [Revised: 10/07/2012] [Accepted: 10/12/2012] [Indexed: 12/01/2022] Open
Abstract
The combination of computational and directed evolution methods has proven a winning strategy for protein engineering. We refer to this approach as computer-aided protein directed evolution (CAPDE) and the review summarizes the recent developments in this rapidly growing field. We will restrict ourselves to overview the availability, usability and limitations of web servers, databases and other computational tools proposed in the last five years. The goal of this review is to provide concise information about currently available computational resources to assist the design of directed evolution based protein engineering experiment.
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Affiliation(s)
- Rajni Verma
- School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany ; Department of Biotechnology, RWTH Aachen University, Worringer Weg 1, 52074 Aachen, Germany
| | - Ulrich Schwaneberg
- Department of Biotechnology, RWTH Aachen University, Worringer Weg 1, 52074 Aachen, Germany
| | - Danilo Roccatano
- School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany
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42
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Konc J, Depolli M, Trobec R, Rozman K, Janežič D. Parallel-ProBiS: fast parallel algorithm for local structural comparison of protein structures and binding sites. J Comput Chem 2012; 33:2199-203. [PMID: 22718529 DOI: 10.1002/jcc.23048] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2012] [Revised: 05/10/2012] [Accepted: 05/25/2012] [Indexed: 11/12/2022]
Abstract
The ProBiS algorithm performs a local structural comparison of the query protein surface against the nonredundant database of protein structures. It finds proteins that have binding sites in common with the query protein. Here, we present a new parallelized algorithm, Parallel-ProBiS, for detecting similar binding sites on clusters of computers. The obtained speedups of the parallel ProBiS scale almost ideally with the number of computing cores up to about 64 computing cores. Scaling is better for larger than for smaller query proteins. For a protein with almost 600 amino acids, the maximum speedup of 180 was achieved on two interconnected clusters with 248 computing cores. Source code of Parallel-ProBiS is available for download free for academic users at http://probis.cmm.ki.si/download.
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Affiliation(s)
- Janez Konc
- Laboratory for Molecular Modeling, National Institute of Chemistry, Hajdrihova 19, SI-1000, Ljubljana, Slovenia
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43
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Konc J, Janezic D. ProBiS-2012: web server and web services for detection of structurally similar binding sites in proteins. Nucleic Acids Res 2012; 40:W214-21. [PMID: 22600737 PMCID: PMC3394329 DOI: 10.1093/nar/gks435] [Citation(s) in RCA: 72] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The ProBiS web server is a web server for detection of structurally similar binding sites in the PDB and for local pairwise alignment of protein structures. In this article, we present a new version of the ProBiS web server that is 10 times faster than earlier versions, due to the efficient parallelization of the ProBiS algorithm, which now allows significantly faster comparison of a protein query against the PDB and reduces the calculation time for scanning the entire PDB from hours to minutes. It also features new web services, and an improved user interface. In addition, the new web server is united with the ProBiS-Database and thus provides instant access to pre-calculated protein similarity profiles for over 29 000 non-redundant protein structures. The ProBiS web server is particularly adept at detection of secondary binding sites in proteins. It is freely available at http://probis.cmm.ki.si/old-version, and the new ProBiS web server is at http://probis.cmm.ki.si.
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Affiliation(s)
- Janez Konc
- National Institute of Chemistry, Ljubljana, Slovenia
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44
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Vankayala SL, Hargis JC, Woodcock HL. Unlocking the binding and reaction mechanism of hydroxyurea substrates as biological nitric oxide donors. J Chem Inf Model 2012; 52:1288-97. [PMID: 22519847 DOI: 10.1021/ci300035c] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Hydroxyurea is the only FDA approved treatment of sickle cell disease. It is believed that the primary mechanism of action is associated with the pharmacological elevation of nitric oxide in the blood; however, the exact details of this are still unclear. In the current work, we investigate the atomic level details of this process using a combination of flexible-ligand/flexible-receptor virtual screening coupled with energetic analysis that decomposes interaction energies. Utilizing these methods, we were able to elucidate the previously unknown substrate binding modes of a series of hydroxyurea analogs to hemoglobin and the concomitant structural changes of the enzyme. We identify a backbone carbonyl that forms a hydrogen bond with bound substrates. Our results are consistent with kinetic and electron paramagnetic resonance (EPR) measurements of hydroxyurea-hemoglobin reactions, and a full mechanism is proposed that offers new insights into possibly improving substrate binding and/or reactivity.
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Affiliation(s)
- Sai Lakshmana Vankayala
- Department of Chemistry and Center for Molecular Diversity in Drug Design, Discovery, and Delivery, University of South Floridar, Tampa, Florida 33620, USA
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