1
|
Gervasoni S, Manelfi C, Adobati S, Talarico C, Biswas AD, Pedretti A, Vistoli G, Beccari AR. Target Prediction by Multiple Virtual Screenings: Analyzing the SARS-CoV-2 Phenotypic Screening by the Docking Simulations Submitted to the MEDIATE Initiative. Int J Mol Sci 2023; 25:450. [PMID: 38203621 PMCID: PMC10779154 DOI: 10.3390/ijms25010450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 12/15/2023] [Accepted: 12/21/2023] [Indexed: 01/12/2024] Open
Abstract
Phenotypic screenings are usually combined with deconvolution techniques to characterize the mechanism of action for the retrieved hits. These studies can be supported by various computational analyses, although docking simulations are rarely employed. The present study aims to assess if multiple docking calculations can prove successful in target prediction. In detail, the docking simulations submitted to the MEDIATE initiative are utilized to predict the viral targets involved in the hits retrieved by a recently published cytopathic screening. Multiple docking results are combined by the EFO approach to develop target-specific consensus models. The combination of multiple docking simulations enhances the performances of the developed consensus models (average increases in EF1% value of 40% and 25% when combining three and two docking runs, respectively). These models are able to propose reliable targets for about half of the retrieved hits (31 out of 59). Thus, the study emphasizes that docking simulations might be effective in target identification and provide a convincing validation for the collaborative strategies that inspire the MEDIATE initiative. Disappointingly, cross-target and cross-program correlations suggest that common scoring functions are not specific enough for the simulated target.
Collapse
Affiliation(s)
- Silvia Gervasoni
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (S.A.); (A.P.)
- Department of Physics, Università di Cagliari, I-09042 Monserrato, Italy
| | - Candida Manelfi
- EXSCALATE, Dompé Farmaceutici S.p.A., Via Tommaso De Amicis, 95, I-80131 Napoli, Italy; (C.M.); (C.T.); (A.D.B.); (A.R.B.)
| | - Sara Adobati
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (S.A.); (A.P.)
| | - Carmine Talarico
- EXSCALATE, Dompé Farmaceutici S.p.A., Via Tommaso De Amicis, 95, I-80131 Napoli, Italy; (C.M.); (C.T.); (A.D.B.); (A.R.B.)
| | - Akash Deep Biswas
- EXSCALATE, Dompé Farmaceutici S.p.A., Via Tommaso De Amicis, 95, I-80131 Napoli, Italy; (C.M.); (C.T.); (A.D.B.); (A.R.B.)
| | - Alessandro Pedretti
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (S.A.); (A.P.)
| | - Giulio Vistoli
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (S.A.); (A.P.)
| | - Andrea R. Beccari
- EXSCALATE, Dompé Farmaceutici S.p.A., Via Tommaso De Amicis, 95, I-80131 Napoli, Italy; (C.M.); (C.T.); (A.D.B.); (A.R.B.)
| |
Collapse
|
2
|
Huang CH, Lin ST. MARS Plus: An Improved Molecular Design Tool for Complex Compounds Involving Ionic, Stereo, and Cis-Trans Isomeric Structures. J Chem Inf Model 2023; 63:7711-7728. [PMID: 38100117 DOI: 10.1021/acs.jcim.3c01745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2023]
Abstract
MARS (Molecular Assembling and Representation Suite) (Hsu et al. J. Chem. Inf. Model. 2019, 59, 3703-3713) is a toolbox for the molecular design of organic molecules. MARS uses integer arrays to represent the elements and connectivity between elements of a molecule. It provides a collection of operations to manipulate the elemental composition and connectivity of a molecule (or a pair of molecules), enabling the creation of novel chemical compounds. In this work, the original MARS is extended to handle complex molecular structures, including geometric (cis-trans) isomers, stereo isomers, cyclic compounds, and ionic species. The extended version of MARS, referred to as MARS+, has a more comprehensive coverage of the chemical space and therefore can explore molecules with a greater chemical and physical diversity. Compared to other molecular design tools, MARS+ is designed to perform all possible manipulations on a given molecule or a pair of molecules. Molecular structure manipulation can be conducted in either a controlled or a random fashion. Furthermore, every structure manipulation has a counterpart so that the operation can be reversed. Nearly any possible chemical structure can be generated with MARS+ via a combination of molecular operations. The capabilities of MARS+ are examined by the design of new ionic liquids (ILs). The results show that MARS+ is a useful tool for computer-aided molecular design (CAMD) and molecular structure enumeration.
Collapse
Affiliation(s)
- Chen-Hsuan Huang
- Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan
| | - Shiang-Tai Lin
- Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan
| |
Collapse
|
3
|
Vittorio S, Lunghini F, Pedretti A, Vistoli G, Beccari AR. Ensemble of structure and ligand-based classification models for hERG liability profiling. Front Pharmacol 2023; 14:1148670. [PMID: 37033661 PMCID: PMC10076575 DOI: 10.3389/fphar.2023.1148670] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 03/13/2023] [Indexed: 04/11/2023] Open
Abstract
Drug-induced cardiotoxicity represents one of the most critical safety concerns in the early stages of drug development. The blockade of the human ether-à-go-go-related potassium channel (hERG) is the most frequent cause of cardiotoxicity, as it is associated to long QT syndrome which can lead to fatal arrhythmias. Therefore, assessing hERG liability of new drugs candidates is crucial to avoid undesired cardiotoxic effects. In this scenario, computational approaches have emerged as useful tools for the development of predictive models able to identify potential hERG blockers. In the last years, several efforts have been addressed to generate ligand-based (LB) models due to the lack of experimental structural information about hERG channel. However, these methods rely on the structural features of the molecules used to generate the model and often fail in correctly predicting new chemical scaffolds. Recently, the 3D structure of hERG channel has been experimentally solved enabling the use of structure-based (SB) strategies which may overcome the limitations of the LB approaches. In this study, we compared the performances achieved by both LB and SB classifiers for hERG-related cardiotoxicity developed by using Random Forest algorithm and employing a training set containing 12789 hERG binders. The SB models were trained on a set of scoring functions computed by docking and rescoring calculations, while the LB classifiers were built on a set of physicochemical descriptors and fingerprints. Furthermore, models combining the LB and SB features were developed as well. All the generated models were internally validated by ten-fold cross-validation on the TS and further verified on an external test set. The former revealed that the best performance was achieved by the LB model, while the model combining the LB and the SB attributes displayed the best results when applied on the external test set highlighting the usefulness of the integration of LB and SB features in correctly predicting unseen molecules. Overall, our predictive models showed satisfactory performances providing new useful tools to filter out potential cardiotoxic drug candidates in the early phase of drug discovery.
Collapse
Affiliation(s)
- Serena Vittorio
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milano, Italy
| | | | - Alessandro Pedretti
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milano, Italy
| | - Giulio Vistoli
- Dipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milano, Italy
| | - Andrea R. Beccari
- EXSCALATE, Dompé Farmaceutici SpA, Napoli, Italy
- *Correspondence: Andrea R. Beccari,
| |
Collapse
|
4
|
Zaliani A, Vangeel L, Reinshagen J, Iaconis D, Kuzikov M, Keminer O, Wolf M, Ellinger B, Esposito F, Corona A, Tramontano E, Manelfi C, Herzog K, Jochmans D, De Jonghe S, Chiu W, Francken T, Schepers J, Collard C, Abbasi K, Claussen C, Summa V, Beccari AR, Neyts J, Gribbon P, Leyssen P. Cytopathic SARS-CoV-2 screening on VERO-E6 cells in a large-scale repurposing effort. Sci Data 2022; 9:405. [PMID: 35831315 PMCID: PMC9279437 DOI: 10.1038/s41597-022-01532-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 06/29/2022] [Indexed: 01/13/2023] Open
Abstract
Worldwide, there are intensive efforts to identify repurposed drugs as potential therapies against SARS-CoV-2 infection and the associated COVID-19 disease. To date, the anti-inflammatory drug dexamethasone and (to a lesser extent) the RNA-polymerase inhibitor remdesivir have been shown to be effective in reducing mortality and patient time to recovery, respectively, in patients. Here, we report the results of a phenotypic screening campaign within an EU-funded project (H2020-EXSCALATE4COV) aimed at extending the repertoire of anti-COVID therapeutics through repurposing of available compounds and highlighting compounds with new mechanisms of action against viral infection. We screened 8702 molecules from different repurposing libraries, to reveal 110 compounds with an anti-cytopathic IC50 < 20 µM. From this group, 18 with a safety index greater than 2 are also marketed drugs, making them suitable for further study as potential therapies against COVID-19. Our result supports the idea that a systematic approach to repurposing is a valid strategy to accelerate the necessary drug discovery process. Measurement(s) | Cytopathic Effect | Technology Type(s) | confocal fluorescence microscopy | Factor Type(s) | Cellular toxicity | Sample Characteristic - Organism | Chlorocebus sabaeus | Sample Characteristic - Environment | continuant | Sample Characteristic - Location | Belgium |
Collapse
Affiliation(s)
- Andrea Zaliani
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525, Hamburg, Germany. .,Fraunhofer Cluster of Excellence for Immune-Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany.
| | - Laura Vangeel
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Jeanette Reinshagen
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525, Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune-Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Daniela Iaconis
- Dompé Farmaceutici SpA, via Campo di Pile, 67100, L'Aquila, Italy
| | - Maria Kuzikov
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525, Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune-Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Oliver Keminer
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525, Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune-Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Markus Wolf
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525, Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune-Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Bernhard Ellinger
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525, Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune-Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Francesca Esposito
- Dipartimento di Scienze della vita e dell'ambiente, Cittadella Universitaria di Monserrato, SS554, 09042, Monserrato, Cagliari, Italy
| | - Angela Corona
- Dipartimento di Scienze della vita e dell'ambiente, Cittadella Universitaria di Monserrato, SS554, 09042, Monserrato, Cagliari, Italy
| | - Enzo Tramontano
- Dipartimento di Scienze della vita e dell'ambiente, Cittadella Universitaria di Monserrato, SS554, 09042, Monserrato, Cagliari, Italy
| | - Candida Manelfi
- Dompé Farmaceutici SpA, via Campo di Pile, 67100, L'Aquila, Italy
| | - Katja Herzog
- EU-OPENSCREEN ERIC, Campus Berlin Buch, Robert-Rössle-Str. 10, 13125, Berlin, Germany
| | - Dirk Jochmans
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Steven De Jonghe
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Winston Chiu
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Thibault Francken
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Joost Schepers
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Caroline Collard
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Kayvan Abbasi
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Carsten Claussen
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525, Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune-Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Vincenzo Summa
- Department of Excellence of Pharmacy, University of Naples Federico II, Via D. Montesano, 49, 80131, Naples, Italy
| | - Andrea R Beccari
- Dompé Farmaceutici SpA, via Campo di Pile, 67100, L'Aquila, Italy
| | - Johan Neyts
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| | - Philip Gribbon
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Discovery Research ScreeningPort, Schnackenburgallee 114, 22525, Hamburg, Germany.,Fraunhofer Cluster of Excellence for Immune-Mediated Diseases CIMD, Theodor-Stern-Kai 7, 60596, Frankfurt am Main, Germany
| | - Pieter Leyssen
- KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, Herestraat 49 - box 1043, 3000, Leuven, Belgium
| |
Collapse
|
5
|
Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel. Int J Mol Sci 2022; 23:ijms23147558. [PMID: 35886905 PMCID: PMC9317601 DOI: 10.3390/ijms23147558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 06/30/2022] [Accepted: 07/04/2022] [Indexed: 11/27/2022] Open
Abstract
(1) Background: Virtual screening campaigns require target structures in which the pockets are properly arranged for binding. Without these, MD simulations can be used to relax the available target structures, optimizing the fine architecture of their binding sites. Among the generated frames, the best structures can be selected based on available experimental data. Without experimental templates, the MD trajectories can be filtered by energy-based criteria or sampled by systematic analyses. (2) Methods: A blind and methodical analysis was performed on the already reported MD run of the hTRPM8 tetrameric structures; a total of 50 frames underwent docking simulations by using a set of 1000 ligands including 20 known hTRPM8 modulators. Docking runs were performed by LiGen program and involved the frames as they are and after optimization by SCRWL4.0. For each frame, all four monomers were considered. Predictive models were developed by the EFO algorithm based on the sole primary LiGen scores. (3) Results: On average, the MD simulation progressively enhances the performance of the extracted frames, and the optimized structures perform better than the non-optimized frames (EF1% mean: 21.38 vs. 23.29). There is an overall correlation between performances and volumes of the explored pockets and the combination of the best performing frames allows to develop highly performing consensus models (EF1% = 49.83). (4) Conclusions: The systematic sampling of the entire MD run provides performances roughly comparable with those previously reached by using rationally selected frames. The proposed strategy appears to be helpful when the lack of experimental data does not allow an easy selection of the optimal structures for docking simulations. Overall, the reported docking results confirm the relevance of simulating all the monomers of an oligomer structure and emphasize the efficacy of the SCRWL4.0 method to optimize the protein structures for docking calculations.
Collapse
|
6
|
Murugan NA, Podobas A, Gadioli D, Vitali E, Palermo G, Markidis S. A Review on Parallel Virtual Screening Softwares for High-Performance Computers. Pharmaceuticals (Basel) 2022; 15:63. [PMID: 35056120 PMCID: PMC8780228 DOI: 10.3390/ph15010063] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 12/19/2021] [Accepted: 12/28/2021] [Indexed: 02/01/2023] Open
Abstract
Drug discovery is the most expensive, time-demanding, and challenging project in biopharmaceutical companies which aims at the identification and optimization of lead compounds from large-sized chemical libraries. The lead compounds should have high-affinity binding and specificity for a target associated with a disease, and, in addition, they should have favorable pharmacodynamic and pharmacokinetic properties (grouped as ADMET properties). Overall, drug discovery is a multivariable optimization and can be carried out in supercomputers using a reliable scoring function which is a measure of binding affinity or inhibition potential of the drug-like compound. The major problem is that the number of compounds in the chemical spaces is huge, making the computational drug discovery very demanding. However, it is cheaper and less time-consuming when compared to experimental high-throughput screening. As the problem is to find the most stable (global) minima for numerous protein-ligand complexes (on the order of 106 to 1012), the parallel implementation of in silico virtual screening can be exploited to ensure drug discovery in affordable time. In this review, we discuss such implementations of parallelization algorithms in virtual screening programs. The nature of different scoring functions and search algorithms are discussed, together with a performance analysis of several docking softwares ported on high-performance computing architectures.
Collapse
Affiliation(s)
- Natarajan Arul Murugan
- Department of Computer Science, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden;
| | - Artur Podobas
- Department of Computer Science, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden;
| | - Davide Gadioli
- Dipartimento di Elettronica, Infomazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy; (D.G.); (E.V.); (G.P.)
| | - Emanuele Vitali
- Dipartimento di Elettronica, Infomazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy; (D.G.); (E.V.); (G.P.)
| | - Gianluca Palermo
- Dipartimento di Elettronica, Infomazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy; (D.G.); (E.V.); (G.P.)
| | - Stefano Markidis
- Department of Computer Science, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden;
| |
Collapse
|
7
|
Chatzigoulas A, Cournia Z. Rational design of allosteric modulators: Challenges and successes. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1529] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Alexios Chatzigoulas
- Biomedical Research Foundation Academy of Athens Athens Greece
- Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens Greece
| | - Zoe Cournia
- Biomedical Research Foundation Academy of Athens Athens Greece
| |
Collapse
|
8
|
Kuzikov M, Costanzi E, Reinshagen J, Esposito F, Vangeel L, Wolf M, Ellinger B, Claussen C, Geisslinger G, Corona A, Iaconis D, Talarico C, Manelfi C, Cannalire R, Rossetti G, Gossen J, Albani S, Musiani F, Herzog K, Ye Y, Giabbai B, Demitri N, Jochmans D, Jonghe SD, Rymenants J, Summa V, Tramontano E, Beccari AR, Leyssen P, Storici P, Neyts J, Gribbon P, Zaliani A. Identification of Inhibitors of SARS-CoV-2 3CL-Pro Enzymatic Activity Using a Small Molecule in Vitro Repurposing Screen. ACS Pharmacol Transl Sci 2021; 4:1096-1110. [PMID: 35287429 PMCID: PMC7986981 DOI: 10.1021/acsptsci.0c00216] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Indexed: 02/08/2023]
Abstract
Compound repurposing is an important strategy for the identification of effective treatment options against SARS-CoV-2 infection and COVID-19 disease. In this regard, SARS-CoV-2 main protease (3CL-Pro), also termed M-Pro, is an attractive drug target as it plays a central role in viral replication by processing the viral polyproteins pp1a and pp1ab at multiple distinct cleavage sites. We here report the results of a repurposing program involving 8.7 K compounds containing marketed drugs, clinical and preclinical candidates, and small molecules regarded as safe in humans. We confirmed previously reported inhibitors of 3CL-Pro and have identified 62 additional compounds with IC50 values below 1 μM and profiled their selectivity toward chymotrypsin and 3CL-Pro from the Middle East respiratory syndrome virus. A subset of eight inhibitors showed anticytopathic effect in a Vero-E6 cell line, and the compounds thioguanosine and MG-132 were analyzed for their predicted binding characteristics to SARS-CoV-2 3CL-Pro. The X-ray crystal structure of the complex of myricetin and SARS-Cov-2 3CL-Pro was solved at a resolution of 1.77 Å, showing that myricetin is covalently bound to the catalytic Cys145 and therefore inhibiting its enzymatic activity.
Collapse
Affiliation(s)
- Maria Kuzikov
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Elisa Costanzi
- Elettra-Sincrotrone
Trieste S.C.p.A., SS 14 - km 163, 5 in AREA Science Park, 34149 Basovizza, Trieste, Italy
| | - Jeanette Reinshagen
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Francesca Esposito
- Dipartimento
di Scienze della vita e dell’ambiente, Cittadella Universitaria di Monserrato, SS-554 Monserrato, Cagliari, Italy
| | - Laura Vangeel
- Department
of Microbiology, Immunology and Transplantation, Rega Institute for
Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Markus Wolf
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Bernhard Ellinger
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Carsten Claussen
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Gerd Geisslinger
- Fraunhofer Institute for Translational Medicine and
Pharmacology
ITMP, Theodor Stern Kai
7, 60596 Frankfurt
am Main, Germany
- Institute
of Clinical Pharmacology, Goethe-University, Theodor Stern Kai 7, 60590 Frankfurt, Germany
| | - Angela Corona
- Dipartimento
di Scienze della vita e dell’ambiente, Cittadella Universitaria di Monserrato, SS-554 Monserrato, Cagliari, Italy
| | - Daniela Iaconis
- Dompé
Farmaceutici SpA, via Campo di Pile, 67100 L’Aquila, Italy
| | - Carmine Talarico
- Dompé
Farmaceutici SpA, via Campo di Pile, 67100 L’Aquila, Italy
| | - Candida Manelfi
- Dompé
Farmaceutici SpA, via Campo di Pile, 67100 L’Aquila, Italy
| | - Rolando Cannalire
- Department
of Pharmacy, University of Naples Federico
II, Via D. Montesano,
49, 80131 Naples, Italy
| | - Giulia Rossetti
- Institute
of Neuroscience and Medicine (INM-9)/Institute for Advanced Simulation
(IAS-5) and Jülich Supercomputing Centre (JSC) Forschungszentrum
Jülich, D-52425 Jülich, Germany
- Faculty
of Medicine, RWTH Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Jonas Gossen
- Institute
of Neuroscience and Medicine (INM-9)/Institute for Advanced Simulation
(IAS-5) and Jülich Supercomputing Centre (JSC) Forschungszentrum
Jülich, D-52425 Jülich, Germany
| | - Simone Albani
- Institute
of Neuroscience and Medicine (INM-9)/Institute for Advanced Simulation
(IAS-5) and Jülich Supercomputing Centre (JSC) Forschungszentrum
Jülich, D-52425 Jülich, Germany
| | - Francesco Musiani
- Laboratory
of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology, University of Bologna, 40216 Bologna, Italy
| | - Katja Herzog
- EU-OPENSCREEN
ERIC, Robert-Rössle-Straße
10, 13125 Berlin, Germany
| | - Yang Ye
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Barbara Giabbai
- Elettra-Sincrotrone
Trieste S.C.p.A., SS 14 - km 163, 5 in AREA Science Park, 34149 Basovizza, Trieste, Italy
| | - Nicola Demitri
- Elettra-Sincrotrone
Trieste S.C.p.A., SS 14 - km 163, 5 in AREA Science Park, 34149 Basovizza, Trieste, Italy
| | - Dirk Jochmans
- Department
of Microbiology, Immunology and Transplantation, Rega Institute for
Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Steven De Jonghe
- Department
of Microbiology, Immunology and Transplantation, Rega Institute for
Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Jasper Rymenants
- Department
of Microbiology, Immunology and Transplantation, Rega Institute for
Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Vincenzo Summa
- Department
of Pharmacy, University of Naples Federico
II, Via D. Montesano,
49, 80131 Naples, Italy
| | - Enzo Tramontano
- Dipartimento
di Scienze della vita e dell’ambiente, Cittadella Universitaria di Monserrato, SS-554 Monserrato, Cagliari, Italy
| | | | - Pieter Leyssen
- Department
of Microbiology, Immunology and Transplantation, Rega Institute for
Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Paola Storici
- Elettra-Sincrotrone
Trieste S.C.p.A., SS 14 - km 163, 5 in AREA Science Park, 34149 Basovizza, Trieste, Italy
| | - Johan Neyts
- Department
of Microbiology, Immunology and Transplantation, Rega Institute for
Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Philip Gribbon
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Andrea Zaliani
- Fraunhofer
Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| |
Collapse
|
9
|
Kuzikov M, Costanzi E, Reinshagen J, Esposito F, Vangeel L, Wolf M, Ellinger B, Claussen C, Geisslinger G, Corona A, Iaconis D, Talarico C, Manelfi C, Cannalire R, Rossetti G, Gossen J, Albani S, Musiani F, Herzog K, Ye Y, Giabbai B, Demitri N, Jochmans D, Jonghe SD, Rymenants J, Summa V, Tramontano E, Beccari AR, Leyssen P, Storici P, Neyts J, Gribbon P, Zaliani A. Identification of Inhibitors of SARS-CoV-2 3CL-Pro Enzymatic Activity Using a Small Molecule in Vitro Repurposing Screen. ACS Pharmacol Transl Sci 2021; 4:1096-1110. [PMID: 35287429 DOI: 10.1101/2020.12.16.422677] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Indexed: 05/18/2023]
Abstract
Compound repurposing is an important strategy for the identification of effective treatment options against SARS-CoV-2 infection and COVID-19 disease. In this regard, SARS-CoV-2 main protease (3CL-Pro), also termed M-Pro, is an attractive drug target as it plays a central role in viral replication by processing the viral polyproteins pp1a and pp1ab at multiple distinct cleavage sites. We here report the results of a repurposing program involving 8.7 K compounds containing marketed drugs, clinical and preclinical candidates, and small molecules regarded as safe in humans. We confirmed previously reported inhibitors of 3CL-Pro and have identified 62 additional compounds with IC50 values below 1 μM and profiled their selectivity toward chymotrypsin and 3CL-Pro from the Middle East respiratory syndrome virus. A subset of eight inhibitors showed anticytopathic effect in a Vero-E6 cell line, and the compounds thioguanosine and MG-132 were analyzed for their predicted binding characteristics to SARS-CoV-2 3CL-Pro. The X-ray crystal structure of the complex of myricetin and SARS-Cov-2 3CL-Pro was solved at a resolution of 1.77 Å, showing that myricetin is covalently bound to the catalytic Cys145 and therefore inhibiting its enzymatic activity.
Collapse
Affiliation(s)
- Maria Kuzikov
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Elisa Costanzi
- Elettra-Sincrotrone Trieste S.C.p.A., SS 14 - km 163, 5 in AREA Science Park, 34149 Basovizza, Trieste, Italy
| | - Jeanette Reinshagen
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Francesca Esposito
- Dipartimento di Scienze della vita e dell'ambiente, Cittadella Universitaria di Monserrato, SS-554 Monserrato, Cagliari, Italy
| | - Laura Vangeel
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Markus Wolf
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Bernhard Ellinger
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Carsten Claussen
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Gerd Geisslinger
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Theodor Stern Kai 7, 60596 Frankfurt am Main, Germany
- Institute of Clinical Pharmacology, Goethe-University, Theodor Stern Kai 7, 60590 Frankfurt, Germany
| | - Angela Corona
- Dipartimento di Scienze della vita e dell'ambiente, Cittadella Universitaria di Monserrato, SS-554 Monserrato, Cagliari, Italy
| | - Daniela Iaconis
- Dompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy
| | - Carmine Talarico
- Dompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy
| | - Candida Manelfi
- Dompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy
| | - Rolando Cannalire
- Department of Pharmacy, University of Naples Federico II, Via D. Montesano, 49, 80131 Naples, Italy
| | - Giulia Rossetti
- Institute of Neuroscience and Medicine (INM-9)/Institute for Advanced Simulation (IAS-5) and Jülich Supercomputing Centre (JSC) Forschungszentrum Jülich, D-52425 Jülich, Germany
- Faculty of Medicine, RWTH Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Jonas Gossen
- Institute of Neuroscience and Medicine (INM-9)/Institute for Advanced Simulation (IAS-5) and Jülich Supercomputing Centre (JSC) Forschungszentrum Jülich, D-52425 Jülich, Germany
| | - Simone Albani
- Institute of Neuroscience and Medicine (INM-9)/Institute for Advanced Simulation (IAS-5) and Jülich Supercomputing Centre (JSC) Forschungszentrum Jülich, D-52425 Jülich, Germany
| | - Francesco Musiani
- Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology, University of Bologna, 40216 Bologna, Italy
| | - Katja Herzog
- EU-OPENSCREEN ERIC, Robert-Rössle-Straße 10, 13125 Berlin, Germany
| | - Yang Ye
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Barbara Giabbai
- Elettra-Sincrotrone Trieste S.C.p.A., SS 14 - km 163, 5 in AREA Science Park, 34149 Basovizza, Trieste, Italy
| | - Nicola Demitri
- Elettra-Sincrotrone Trieste S.C.p.A., SS 14 - km 163, 5 in AREA Science Park, 34149 Basovizza, Trieste, Italy
| | - Dirk Jochmans
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Steven De Jonghe
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Jasper Rymenants
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Vincenzo Summa
- Department of Pharmacy, University of Naples Federico II, Via D. Montesano, 49, 80131 Naples, Italy
| | - Enzo Tramontano
- Dipartimento di Scienze della vita e dell'ambiente, Cittadella Universitaria di Monserrato, SS-554 Monserrato, Cagliari, Italy
| | - Andrea R Beccari
- Dompé Farmaceutici SpA, via Campo di Pile, 67100 L'Aquila, Italy
| | - Pieter Leyssen
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Paola Storici
- Elettra-Sincrotrone Trieste S.C.p.A., SS 14 - km 163, 5 in AREA Science Park, 34149 Basovizza, Trieste, Italy
| | - Johan Neyts
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Virology and Chemotherapy, KU Leuven, Herestraat 49, Box 1043, 3000 Leuven, Belgium
| | - Philip Gribbon
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| | - Andrea Zaliani
- Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525 Hamburg, Germany
| |
Collapse
|
10
|
Manelfi C, Gossen J, Gervasoni S, Talarico C, Albani S, Philipp BJ, Musiani F, Vistoli G, Rossetti G, Beccari AR, Pedretti A. Combining Different Docking Engines and Consensus Strategies to Design and Validate Optimized Virtual Screening Protocols for the SARS-CoV-2 3CL Protease. Molecules 2021; 26:molecules26040797. [PMID: 33557115 PMCID: PMC7913849 DOI: 10.3390/molecules26040797] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 01/20/2021] [Accepted: 01/26/2021] [Indexed: 02/06/2023] Open
Abstract
The 3CL-Protease appears to be a very promising medicinal target to develop anti-SARS-CoV-2 agents. The availability of resolved structures allows structure-based computational approaches to be carried out even though the lack of known inhibitors prevents a proper validation of the performed simulations. The innovative idea of the study is to exploit known inhibitors of SARS-CoV 3CL-Pro as a training set to perform and validate multiple virtual screening campaigns. Docking simulations using four different programs (Fred, Glide, LiGen, and PLANTS) were performed investigating the role of both multiple binding modes (by binding space) and multiple isomers/states (by developing the corresponding isomeric space). The computed docking scores were used to develop consensus models, which allow an in-depth comparison of the resulting performances. On average, the reached performances revealed the different sensitivity to isomeric differences and multiple binding modes between the four docking engines. In detail, Glide and LiGen are the tools that best benefit from isomeric and binding space, respectively, while Fred is the most insensitive program. The obtained results emphasize the fruitful role of combining various docking tools to optimize the predictive performances. Taken together, the performed simulations allowed the rational development of highly performing virtual screening workflows, which could be further optimized by considering different 3CL-Pro structures and, more importantly, by including true SARS-CoV-2 3CL-Pro inhibitors (as learning set) when available.
Collapse
Affiliation(s)
- Candida Manelfi
- Dompé Farmaceutici SpA, Via Campo di Pile, 67100 L’Aquila, Italy; (C.M.); (C.T.); (A.R.B.)
| | - Jonas Gossen
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany; (J.G.); (S.A.); (B.J.P.); (G.R.)
- Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen, 52062 Aachen, Germany
| | - Silvia Gervasoni
- Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (G.V.)
| | - Carmine Talarico
- Dompé Farmaceutici SpA, Via Campo di Pile, 67100 L’Aquila, Italy; (C.M.); (C.T.); (A.R.B.)
| | - Simone Albani
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany; (J.G.); (S.A.); (B.J.P.); (G.R.)
- Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen, 52062 Aachen, Germany
| | - Benjamin Joseph Philipp
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany; (J.G.); (S.A.); (B.J.P.); (G.R.)
- Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen, 52062 Aachen, Germany
| | - Francesco Musiani
- Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology, University of Bologna, 40127 Bologna, Italy;
| | - Giulio Vistoli
- Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (G.V.)
| | - Giulia Rossetti
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany; (J.G.); (S.A.); (B.J.P.); (G.R.)
- Jülich Supercomputing Center (JSC), Forschungszentrum Jülich, 52425 Jülich, Germany
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation University Hospital Aachen, RWTH Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Andrea Rosario Beccari
- Dompé Farmaceutici SpA, Via Campo di Pile, 67100 L’Aquila, Italy; (C.M.); (C.T.); (A.R.B.)
| | - Alessandro Pedretti
- Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (G.V.)
- Correspondence: ; Tel.: +39-02-5031-9332
| |
Collapse
|
11
|
|
12
|
Binding Mode Exploration of B1 Receptor Antagonists' by the Use of Molecular Dynamics and Docking Simulation-How Different Target Engagement Can Determine Different Biological Effects. Int J Mol Sci 2020; 21:ijms21207677. [PMID: 33081372 PMCID: PMC7590058 DOI: 10.3390/ijms21207677] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 10/10/2020] [Accepted: 10/12/2020] [Indexed: 01/24/2023] Open
Abstract
The kinin B1 receptor plays a critical role in the chronic phase of pain and inflammation. The development of B1 antagonists peaked in recent years but almost all promising molecules failed in clinical trials. Little is known about these molecules' mechanisms of action and additional information will be necessary to exploit the potential of the B1 receptor. With the aim of contributing to the available knowledge of the pharmacology of B1 receptors, we designed and characterized a novel class of allosteric non-peptidic inhibitors with peculiar binding characteristics. Here, we report the binding mode analysis and pharmacological characterization of a new allosteric B1 antagonist, DFL20656. We analyzed the binding of DFL20656 by single point mutagenesis and radioligand binding assays and we further characterized its pharmacology in terms of IC50, B1 receptor internalization and in vivo activity in comparison with different known B1 antagonists. We highlighted how different binding modes of DFL20656 and a Merck compound (compound 14) within the same molecular pocket can affect the biological and pharmacological properties of B1 inhibitors. DFL20656, by its peculiar binding mode, involving tight interactions with N114, efficiently induced B1 receptor internalization and evoked a long-lasting effect in an in vivo model of neuropathic pain. The pharmacological characterization of different B1 antagonists highlighted the effects of their binding modes on activity, receptor occupancy and internalization. Our results suggest that part of the failure of most B1 inhibitors could be ascribed to a lack of knowledge about target function and engagement.
Collapse
|
13
|
Polishchuk P. CReM: chemically reasonable mutations framework for structure generation. J Cheminform 2020; 12:28. [PMID: 33430959 PMCID: PMC7178718 DOI: 10.1186/s13321-020-00431-w] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 04/15/2020] [Indexed: 12/12/2022] Open
Abstract
Structure generators are widely used in de novo design studies and their performance substantially influences an outcome. Approaches based on the deep learning models and conventional atom-based approaches may result in invalid structures and fail to address their synthetic feasibility issues. On the other hand, conventional reaction-based approaches result in synthetically feasible compounds but novelty and diversity of generated compounds may be limited. Fragment-based approaches can provide both better novelty and diversity of generated compounds but the issue of synthetic complexity of generated structure was not explicitly addressed before. Here we developed a new framework of fragment-based structure generation that, by design, results in the chemically valid structures and provides flexible control over diversity, novelty, synthetic complexity and chemotypes of generated compounds. The framework was implemented as an open-source Python module and can be used to create custom workflows for the exploration of chemical space.
Collapse
Affiliation(s)
- Pavel Polishchuk
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University and University Hospital in Olomouc, Hnevotinska 5, 77900, Olomouc, Czech Republic.
| |
Collapse
|
14
|
Wei L, Wen W, Rao L, Huang Y, Lei M, Liu K, Hu S, Song R, Ren Y, Wan J. Cov_FB3D: A De Novo Covalent Drug Design Protocol Integrating the BA-SAMP Strategy and Machine-Learning-Based Synthetic Tractability Evaluation. J Chem Inf Model 2020; 60:4388-4402. [PMID: 32233478 DOI: 10.1021/acs.jcim.9b01197] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
De novo drug design actively seeks to use sets of chemical rules for the fast and efficient identification of structurally new chemotypes with the desired set of biological properties. Fragment-based de novo design tools have been successfully applied in the discovery of noncovalent inhibitors. Nevertheless, these tools are rarely applied in the field of covalent inhibitor design. Herein, we present a new protocol, called Cov_FB3D, which involves the in silico assembly of potential novel covalent inhibitors by identifying the active fragments in the covalently binding site of the target protein. In this protocol, we propose a BA-SAMP strategy, which combines the noncovalent moiety score with the X-Score as the molecular mechanism (MM) level, and the covalent candidate score with the PM7 as the QM level. The synthetic accessibility of each suggested compound could be further evaluated with machine-learning-based synthetic complexity evaluation (SCScore). An in-depth test of this protocol against the crystal structures of 15 covalent complexes consisting of BTK inhibitors, KRAS inhibitors, EGFR inhibitors, EphB1 inhibitors, MAGL inhibitors, and MAPK inhibitors revealed that most of these inhibitors could be de novo reproduced from the fragments by Cov_FB3D. The binding modes of most generated reference poses could accurately reproduce the known binding mode of most of the reference covalent adduct in the binding site (RMSD ≤ 2 Å). In particular, most of these inhibitors were ranked in the top 2%, using the BA-SAMP strategy. Notably, the novel human ALDOA inhibitor (T1) with potent inhibitory activity (0.34 ± 0.03 μM) and greater synthetic accessibility was successfully de novo designed by this protocol. The positive results confirm the abilities of Cov_FB3D protocol.
Collapse
Affiliation(s)
- Lin Wei
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| | - Wuqiang Wen
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| | - Li Rao
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| | - Yunyuan Huang
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| | - Mengting Lei
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| | - Kai Liu
- Institute of Marine Drugs, Guangxi University of Chinese Medicine, Nanning, 530200, People's Republic of China
| | - Saiya Hu
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| | - Rongrong Song
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| | - Yanliang Ren
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| | - Jian Wan
- International Cooperation Base of Pesticide and Green Synthesis (Hubei), Key Laboratory of Pesticide & Chemical Biology (CCNU), Ministry of Education, Department of Chemistry, Central China Normal University, Wuhan 430079, China
| |
Collapse
|
15
|
Talarico C, Gervasoni S, Manelfi C, Pedretti A, Vistoli G, Beccari AR. Combining Molecular Dynamics and Docking Simulations to Develop Targeted Protocols for Performing Optimized Virtual Screening Campaigns on The hTRPM8 Channel. Int J Mol Sci 2020; 21:E2265. [PMID: 32218173 PMCID: PMC7177470 DOI: 10.3390/ijms21072265] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 02/19/2020] [Accepted: 03/20/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND There is an increasing interest in TRPM8 ligands of medicinal interest, the rational design of which can be nowadays supported by structure-based in silico studies based on the recently resolved TRPM8 structures. Methods: The study involves the generation of a reliable hTRPM8 homology model, the reliability of which was assessed by a 1.0 μs MD simulation which was also used to generate multiple receptor conformations for the following structure-based virtual screening (VS) campaigns; docking simulations utilized different programs and involved all monomers of the selected frames; the so computed docking scores were combined by consensus approaches based on the EFO algorithm. Results: The obtained models revealed very satisfactory performances; LiGen™ provided the best results among the tested docking programs; the combination of docking results from the four monomers elicited a markedly beneficial effect on the computed consensus models. Conclusions: The generated hTRPM8 model appears to be amenable for successful structure-based VS studies; cross-talk modulating effects between interacting monomers on the binding sites can be accounted for by combining docking simulations as performed on all the monomers; this strategy can have general applicability for docking simulations involving quaternary protein structures with multiple identical binding pockets.
Collapse
Affiliation(s)
- Carmine Talarico
- Dompé Farmaceutici SpA, Via Campo di Pile, 67100 L’Aquila, Italy; (C.T.); (C.M.)
| | - Silvia Gervasoni
- Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (A.P.); (G.V.)
| | - Candida Manelfi
- Dompé Farmaceutici SpA, Via Campo di Pile, 67100 L’Aquila, Italy; (C.T.); (C.M.)
| | - Alessandro Pedretti
- Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (A.P.); (G.V.)
| | - Giulio Vistoli
- Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Mangiagalli, 25, I-20133 Milano, Italy; (S.G.); (A.P.); (G.V.)
| | - Andrea R. Beccari
- Dompé Farmaceutici SpA, Via Campo di Pile, 67100 L’Aquila, Italy; (C.T.); (C.M.)
| |
Collapse
|
16
|
D'Angelo R, Mangini M, Fonderico J, Fulle S, Mayo E, Aramini A, Mariggiò S. Inhibition of osteoclast activity by complement regulation with DF3016A, a novel small-molecular-weight C5aR inhibitor. Biomed Pharmacother 2019; 123:109764. [PMID: 31901551 DOI: 10.1016/j.biopha.2019.109764] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 11/18/2019] [Accepted: 11/29/2019] [Indexed: 12/11/2022] Open
Abstract
Recent insights have indicated an active role of the complex complement system not only in immunity, but also in bone remodeling. Evidence from knockout mice and observations from skeletal diseases have drawn attention to the C5a/C5aR axis of the complement cascade in the modulation of osteoclast functions and as potential therapeutic targets for treatment of bone pathologies. With the aim to identify novel C5aR regulators, a medicinal chemistry program was initiated, driven by structural information on a minor pocket of C5aR that has been proposed to be a key motif for C5aR intracellular activation. The impact of the peptidomimetic orthosteric C5aR antagonist (PMX-53), of two newly synthesized allosteric C5aR antagonists (DF2593A, DF3016A), and of C5aR down-regulation by specific siRNAs, were examined for regulation of osteoclastogenesis, using a well-validated in-vitro model starting from RAW264.7 precursor cells. Both pharmacological and molecular approaches reduced osteoclast maturation of RAW264.7 cells induced by receptor-activator of nuclear factor kappa-B ligand (RANKL), which limited the transcription of several differentiation markers evaluated by real-time PCR, including nuclear factor of activated T-cell 1, matrix metalloproteinase-9, cathepsin-K, and tartrate-resistant acid phosphatase. These treatments were ineffective on the subsequent step of osteoclast syncytium formation, apparently as a consequence of reduction of C5aR mRNA levels in the course of osteoclastogenesis, as monitored by real-time PCR. Among the C5aR antagonists analyzed, DF3016A inhibited osteoclast degradation activity through inhibition of C5aR signal transduction and transcription. These data confirm the preclinical relevance of this novel therapeutic candidate.
Collapse
Affiliation(s)
- Rosa D'Angelo
- Institute of Protein Biochemistry, National Research Council, Naples, Italy
| | - Maria Mangini
- Institute of Protein Biochemistry, National Research Council, Naples, Italy
| | - Jole Fonderico
- Dept Neuroscience Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy
| | - Stefania Fulle
- Dept Neuroscience Imaging and Clinical Sciences, 'G. d'Annunzio' University of Chieti-Pescara, Italy
| | - Emilia Mayo
- Institute of Protein Biochemistry, National Research Council, Naples, Italy
| | - Andrea Aramini
- Research and Early Development Dompé Farmaceutici S.p.A, Naples, Italy
| | - Stefania Mariggiò
- Institute of Protein Biochemistry, National Research Council, Naples, Italy.
| |
Collapse
|
17
|
Brown BP, Mendenhall J, Meiler J. BCL::MolAlign: Three-Dimensional Small Molecule Alignment for Pharmacophore Mapping. J Chem Inf Model 2019; 59:689-701. [PMID: 30707580 DOI: 10.1021/acs.jcim.9b00020] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Small molecule flexible alignment is a critical component of both ligand- and structure-based methods in computer-aided drug discovery. Despite its importance, the availability of high-quality flexible alignment software packages is limited. Here, we present BCL::MolAlign, a freely available property-based molecular alignment program. BCL::MolAlign accommodates ligand flexibility through a combination of pregenerated conformers and on-the-fly bond rotation. BCL::MolAlign converges on alignment poses by sampling the relative orientations of mutually matching atom pairs between molecules through Monte Carlo Metropolis sampling. Across six diverse ligand data sets, BCL::MolAlign flexible alignment outperforms MOE, ROCS, and FLEXS in recovering native ligand binding poses. Moreover, the BCL::MolAlign alignment score is more predictive of ligand activity than maximum common substructure similarity across 10 data sets. Finally, on a recently published benchmark set of 20 high quality congeneric ligand-protein complexes, BCL::MolAlign is able to recover a larger fraction of native binding poses than maximum common substructure-based alignment and RosettaLigand. BCL::MolAlign can be obtained as part of the Biology and Chemistry Library (BCL) software package freely with an academic license or can be accessed via Web server at http://meilerlab.org/index.php/servers/molalign .
Collapse
Affiliation(s)
- Benjamin P Brown
- Chemical and Physical Biology Program, Medical Scientist Training Program, Center for Structural Biology , Vanderbilt University , Nashville , Tennessee 37232 , United States
| | - Jeffrey Mendenhall
- Department of Chemistry, Center for Structural Biology , Vanderbilt University , Nashville , Tennessee 37232 , United States
| | - Jens Meiler
- Department of Chemistry, Center for Structural Biology , Vanderbilt University , Nashville , Tennessee 37232 , United States.,Departments of Pharmacology and Biomedical Informatics , Vanderbilt University , Nashville , Tennessee 37212 , United States
| |
Collapse
|
18
|
Hoffer L, Muller C, Roche P, Morelli X. Chemistry-driven Hit-to-lead Optimization Guided by Structure-based Approaches. Mol Inform 2018; 37:e1800059. [PMID: 30051601 DOI: 10.1002/minf.201800059] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 06/24/2018] [Indexed: 12/17/2022]
Abstract
For several decades, hit identification for drug discovery has been facilitated by developments in both fragment-based and high-throughput screening technologies. However, a major bottleneck in drug discovery projects continues to be the optimization of primary hits from screening campaigns in order to derive lead compounds. Computational chemistry or molecular modeling can play an important role during this hit-to-lead (H2L) stage by both suggesting putative optimizations and decreasing the number of compounds to be experimentally synthesized and evaluated. However, it is also crucial to consider the feasibility of organically synthesizing these virtually designed compounds. Furthermore, the generated molecules should have reasonable physicochemical properties and be medicinally relevant. This review focuses on chemistry-driven and structure-based computational methods that can be used to tackle the difficult problem of H2L optimization, with emphasis being placed on the strategy developed in our laboratory.
Collapse
Affiliation(s)
- Laurent Hoffer
- CNRS, Inserm, Institut Paoli-Calmettes, Aix-Marseille Univ, CRCM, Marseille, France
| | | | - Philippe Roche
- CNRS, Inserm, Institut Paoli-Calmettes, Aix-Marseille Univ, CRCM, Marseille, France
| | - Xavier Morelli
- CNRS, Inserm, Institut Paoli-Calmettes, Aix-Marseille Univ, CRCM, Marseille, France.,Institut Paoli-Calmettes, IPC Drug Discovery, Marseille, France
| |
Collapse
|
19
|
Allen WJ, Fochtman BC, Balius TE, Rizzo RC. Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets. J Comput Chem 2017; 38:2641-2663. [PMID: 28940386 DOI: 10.1002/jcc.25052] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Accepted: 08/03/2017] [Indexed: 12/12/2022]
Abstract
De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from-scratch construction of molecules is not limited to compounds in pre-existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X-ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug-like compounds (generic libraries), and (3) application to a challenging protein-protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- William J Allen
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, 11794
| | - Brian C Fochtman
- Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, New York, 11794
| | - Trent E Balius
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, 94158
| | - Robert C Rizzo
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, 11794.,Institute of Chemical Biology and Drug Discovery, Stony Brook University, Stony Brook, New York, 11794.,Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, 11794
| |
Collapse
|
20
|
Novel selective, potent naphthyl TRPM8 antagonists identified through a combined ligand- and structure-based virtual screening approach. Sci Rep 2017; 7:10999. [PMID: 28887460 PMCID: PMC5591244 DOI: 10.1038/s41598-017-11194-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2017] [Accepted: 07/21/2017] [Indexed: 02/03/2023] Open
Abstract
Transient receptor potential melastatin 8 (TRPM8), a nonselective cation channel, is the predominant mammalian cold temperature thermosensor and it is activated by cold temperatures and cooling compounds, such as menthol and icilin. Because of its role in cold allodynia, cold hyperalgesia and painful syndromes TRPM8 antagonists are currently being pursued as potential therapeutic agents for the treatment of pain hypersensitivity. Recently TRPM8 has been found in subsets of bladder sensory nerve fibres, providing an opportunity to understand and treat chronic hypersensitivity. However, most of the known TRPM8 inhibitors lack selectivity, and only three selective compounds have reached clinical trials to date. Here, we applied two virtual screening strategies to find new, clinics suitable, TRPM8 inhibitors. This strategy enabled us to identify naphthyl derivatives as a novel class of potent and selective TRPM8 inhibitors. Further characterization of the pharmacologic properties of the most potent compound identified, compound 1, confirmed that it is a selective, competitive antagonist inhibitor of TRPM8. Compound 1 also proved itself active in a overreactive bladder model in vivo. Thus, the novel naphthyl derivative compound identified here could be optimized for clinical treatment of pain hypersensitivity in bladder disorders but also in different other pathologies.
Collapse
|
21
|
Jindalertudomdee J, Hayashida M, Akutsu T. Enumeration Method for Structural Isomers Containing User-Defined Structures Based on Breadth-First Search Approach. J Comput Biol 2016; 23:625-40. [PMID: 27348756 DOI: 10.1089/cmb.2016.0056] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Enumeration of chemical structures satisfying given conditions is an important step in the discovery of new compounds and drugs, as well as the elucidation of the structure. One of the most frequently used conditions in the enumeration is the number of chemical elements that corresponds to the chemical formula. In this work, we propose a novel efficient enumeration algorithm, BfsStructEnum, which allows users to define desired cyclic structures and enumerates all nonredundant chemical compounds containing only defined structures as cyclic structures from a given chemical formula. To evaluate the performance, we confirm the number of enumerated structures of BfsStructEnum and MOLGEN 5.0, the latest version of a general-purpose structure generator. We also compare the computation time of BfsStructEnum with that of MOLGEN 5.0. The findings show that, given the same number of enumerated structures as MOLGEN 5.0, BfsStructEnum is significantly faster. By compressing a cyclic structure into a single node and representing chemical compounds by tree structures instead of normal graphs, the enumeration can be executed more efficiently.
Collapse
Affiliation(s)
- Jira Jindalertudomdee
- Laboratory of Mathematical Bioinformatics, Bioinformatics Center, Institute for Chemical Research, Kyoto University , Kyoto, Japan
| | - Morihiro Hayashida
- Laboratory of Mathematical Bioinformatics, Bioinformatics Center, Institute for Chemical Research, Kyoto University , Kyoto, Japan
| | - Tatsuya Akutsu
- Laboratory of Mathematical Bioinformatics, Bioinformatics Center, Institute for Chemical Research, Kyoto University , Kyoto, Japan
| |
Collapse
|
22
|
Li Y, Zhao Z, Liu Z, Su M, Wang R. AutoT&T v.2: An Efficient and Versatile Tool for Lead Structure Generation and Optimization. J Chem Inf Model 2016; 56:435-53. [DOI: 10.1021/acs.jcim.5b00691] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Yan Li
- State
Key Laboratory of Bioorganic and Natural Products Chemistry, Collaborative
Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People’s Republic of China
| | - Zhixiong Zhao
- State
Key Laboratory of Bioorganic and Natural Products Chemistry, Collaborative
Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People’s Republic of China
| | - Zhihai Liu
- State
Key Laboratory of Bioorganic and Natural Products Chemistry, Collaborative
Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People’s Republic of China
| | - Minyi Su
- State
Key Laboratory of Bioorganic and Natural Products Chemistry, Collaborative
Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People’s Republic of China
| | - Renxiao Wang
- State
Key Laboratory of Bioorganic and Natural Products Chemistry, Collaborative
Innovation Center of Chemistry for Life Sciences, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032, People’s Republic of China
- State
Key Laboratory of Quality Research in Chinese Medicine, Macau Institute
for Applied Research in Medicine and Health, Macau University of Science and Technology, Macau, People’s Republic of China
| |
Collapse
|
23
|
Yuriev E, Holien J, Ramsland PA. Improvements, trends, and new ideas in molecular docking: 2012-2013 in review. J Mol Recognit 2015; 28:581-604. [PMID: 25808539 DOI: 10.1002/jmr.2471] [Citation(s) in RCA: 159] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2014] [Revised: 01/16/2015] [Accepted: 02/05/2015] [Indexed: 12/11/2022]
Abstract
Molecular docking is a computational method for predicting the placement of ligands in the binding sites of their receptor(s). In this review, we discuss the methodological developments that occurred in the docking field in 2012 and 2013, with a particular focus on the more difficult aspects of this computational discipline. The main challenges and therefore focal points for developments in docking, covered in this review, are receptor flexibility, solvation, scoring, and virtual screening. We specifically deal with such aspects of molecular docking and its applications as selection criteria for constructing receptor ensembles, target dependence of scoring functions, integration of higher-level theory into scoring, implicit and explicit handling of solvation in the binding process, and comparison and evaluation of docking and scoring methods.
Collapse
Affiliation(s)
- Elizabeth Yuriev
- Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Jessica Holien
- ACRF Rational Drug Discovery Centre and Structural Biology Laboratory, St. Vincent's Institute of Medical Research, Fitzroy, Victoria, 3065, Australia
| | - Paul A Ramsland
- Centre for Biomedical Research, Burnet Institute, Melbourne, Victoria, 3004, Australia.,Department of Surgery Austin Health, University of Melbourne, Melbourne, Victoria, 3084, Australia.,Department of Immunology, Monash University, Alfred Medical Research and Education Precinct, Melbourne, Victoria, 3004, Australia.,School of Biomedical Sciences, CHIRI Biosciences, Curtin University, Perth, Western Australia, 6845, Australia
| |
Collapse
|
24
|
Pirard B, Ertl P. Evaluation of a semi-automated workflow for fragment growing. J Chem Inf Model 2015; 55:180-93. [PMID: 25514394 DOI: 10.1021/ci5006355] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Intelligent Automatic Design (IADE) is an expert system developed at Novartis to identify nonclassical bioisosteres. In addition to bioisostere searching, one could also use IADE to grow a fragment bound to a protein. Here we report an evaluation of IADE as a tool for fragment growing. Three examples from the literature served as test cases. In all three cases, IADE generated close analogues of the published compounds and reproduced their crystallographic binding modes. This exercise validated the use of the IADE system for fragment growing. We have also gained experience in optimizing the performance of IADE for this type of application.
Collapse
Affiliation(s)
- Bernard Pirard
- Novartis Institutes for BioMedical Research , Novartis Campus, CH-4056 Basel, Switzerland
| | | |
Collapse
|
25
|
A Mini-review on Chemoinformatics Approaches for Drug Discovery. JOURNAL OF COMPUTER AIDED CHEMISTRY 2015. [DOI: 10.2751/jcac.16.15] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
|
26
|
Foscato M, Occhipinti G, Venkatraman V, Alsberg BK, Jensen VR. Automated Design of Realistic Organometallic Molecules from Fragments. J Chem Inf Model 2014; 54:767-80. [DOI: 10.1021/ci4007497] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Marco Foscato
- Department
of Chemistry, University of Bergen, Allégaten 41, N-5007 Bergen, Norway
| | - Giovanni Occhipinti
- Department
of Chemistry, University of Bergen, Allégaten 41, N-5007 Bergen, Norway
| | - Vishwesh Venkatraman
- Department
of Chemistry, Norwegian University of Science and Technology, N-7491 Trondheim, Norway
| | - Bjørn K. Alsberg
- Department
of Chemistry, Norwegian University of Science and Technology, N-7491 Trondheim, Norway
| | - Vidar R. Jensen
- Department
of Chemistry, University of Bergen, Allégaten 41, N-5007 Bergen, Norway
| |
Collapse
|
27
|
Kawai K, Nagata N, Takahashi Y. De novo design of drug-like molecules by a fragment-based molecular evolutionary approach. J Chem Inf Model 2014; 54:49-56. [PMID: 24372539 DOI: 10.1021/ci400418c] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
This paper describes a similarity-driven simple evolutionary approach to producing candidate molecules of new drugs. The aim of the method is to explore the candidates that are structurally similar to the reference molecule and yet somewhat different in not only peripheral chains but also their scaffolds. The method employs a known active molecule of our interest as a reference molecule which is used to navigate a huge chemical space. The reference molecule is also used to obtain seed fragments. An initial set of individual structures is prepared with the seed fragments and additional fragments using several connection rules. The fragment library is preferably prepared from a collection of known molecules related to the target of the reference molecule. Every fragment of the library can be used for fragment-based mutation. All the fragments are categorized into three classes; rings, linkers, and side chains. New individuals are produced by the crossover and the fragment-based mutation with the fragment library. Computer experiments with our own fragment library prepared from GPCR SARfari verified the feasibility of our approach to drug discovery.
Collapse
Affiliation(s)
- Kentaro Kawai
- Central Research Laboratories, Kaken Pharmaceutical Co. Ltd. , 14, Shinomiya Minamikawara-cho, Yamashina, Kyoto 607-8042, Japan
| | | | | |
Collapse
|
28
|
Beato C, Beccari AR, Cavazzoni C, Lorenzi S, Costantino G. Use of experimental design to optimize docking performance: the case of LiGenDock, the docking module of LiGen, a new de novo design program. J Chem Inf Model 2013; 53:1503-17. [PMID: 23590204 DOI: 10.1021/ci400079k] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
On route toward a novel de novo design program, called LiGen, we developed a docking program, LiGenDock, based on pharmacophore models of binding sites, including a non-enumerative docking algorithm. In this paper, we present the functionalities of LiGenDock and its accompanying module LiGenPocket, aimed at the binding site analysis and structure-based pharmacophore definition. We also report the optimization procedure we have carried out to improve the cognate docking and virtual screening performance of LiGenDock. In particular, we applied the design of experiments (DoE) methodology to screen the set of user-adjustable parameters to identify those having the largest influence on the accuracy of the results (which ensure the best performance in pose prediction and in virtual screening approaches) and then to choose their optimal values. The results are also compared with those obtained by two popular docking programs, namely, Glide and AutoDock for pose prediction, and Glide and DOCK6 for Virtual Screening.
Collapse
Affiliation(s)
- Claudia Beato
- Dipartimento di Farmacia, Università degli Studi di Parma, Viale Area delle Scienze, 27/A, 43124 Parma, Italy
| | | | | | | | | |
Collapse
|