1
|
Ortore G, Poli G, Martinelli A, Tuccinardi T, Rizzolio F, Caligiuri I. From Anti-infective Agents to Cancer Therapy: a Drug Repositioning Study Revealed a New Use for Nitrofuran Derivatives. Med Chem 2021; 18:249-259. [PMID: 33992059 DOI: 10.2174/1573406417666210511001241] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 02/06/2021] [Accepted: 02/07/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND The progression of ovarian cancer seems to be related to HDAC1, HDAC3 and HDAC6 activity. A possible strategy for improving therapies for treating ovarian carcinoma, minimizing the preclinical screenings, is the repurposing of already approved pharmaceutical products as inhibitors of these enzymes. OBJECTIVE This work was aimed to implement a computational strategy for identifying new HDAC inhibitors for ovarian carcinoma treatment among approved drugs. METHOD The CHEMBL database was used to construct training, test and decoys sets for performing and validating HDAC1, HDAC3 and HDAC6 3D-QSAR models obtained by using FLAP program. Docking and MD simulations were used in combination with the generated models to identify novel potential HDAC inhibitors. Cell viability assays and Western blot analyses were performed on normal and cancer cells for a direct evaluation of the anti-proliferative activity and an in vitro estimation of HDAC inhibition of the compounds selected through in silico screening. RESULT The best quantitative prediction was obtained for the HDAC6 3D-QSAR model. The screening of approved drugs highlighted a new potential use as HDAC inhibitors for some compounds, in particular nitrofuran derivatives, usually known for their antibacterial activity, and frequently used as antimicrobial adjuvant therapy in cancer treatment. Experimental evaluation of these derivatives highlighted a significant antiproliferative activity against cancer cell lines overexpressing HDAC6, and an increase in acetylated alpha-tubulin levels. CONCLUSION Experimental results support the hypothesis of a potential direct interaction of nitrofuran derivatives with HDACs. In addition to the possible repurposing of already approved drugs, this work suggests the nitro group as a new zinc binding group, able to interact with the catalytic zinc ion of HDACs.
Collapse
Affiliation(s)
| | - Giulio Poli
- Department of Pharmacy, Pisa University, Pisa, Italy
| | | | | | - Flavio Rizzolio
- Pathology Unit, Centro di Riferimento Oncologico (CRO) IRCCS, Aviano, Italy
| | - Isabella Caligiuri
- Pathology Unit, Centro di Riferimento Oncologico (CRO) IRCCS, Aviano, Italy
| |
Collapse
|
2
|
Celis S, Hobor F, James T, Bartlett GJ, Ibarra AA, Shoemark DK, Hegedüs Z, Hetherington K, Woolfson DN, Sessions RB, Edwards TA, Andrews DM, Nelson A, Wilson AJ. Query-guided protein-protein interaction inhibitor discovery. Chem Sci 2021; 12:4753-4762. [PMID: 34163731 PMCID: PMC8179539 DOI: 10.1039/d1sc00023c] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 02/19/2021] [Indexed: 12/04/2022] Open
Abstract
Protein-protein interactions (PPIs) are central to biological mechanisms, and can serve as compelling targets for drug discovery. Yet, the discovery of small molecule inhibitors of PPIs remains challenging given the large and typically shallow topography of the interacting protein surfaces. Here, we describe a general approach to the discovery of orthosteric PPI inhibitors that mimic specific secondary protein structures. Initially, hot residues at protein-protein interfaces are identified in silico or from experimental data, and incorporated into secondary structure-based queries. Virtual libraries of small molecules are then shape-matched against the queries, and promising ligands docked to target proteins. The approach is exemplified experimentally using two unrelated PPIs that are mediated by an α-helix (p53/hDM2) and a β-strand (GKAP/SHANK1-PDZ). In each case, selective PPI inhibitors are discovered with low μM activity as determined by a combination of fluorescence anisotropy and 1H-15N HSQC experiments. In addition, hit expansion yields a series of PPI inhibitors with defined structure-activity relationships. It is envisaged that the generality of the approach will enable discovery of inhibitors of a wide range of unrelated secondary structure-mediated PPIs.
Collapse
Affiliation(s)
- Sergio Celis
- Astbury Centre for Structural Molecular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
- School of Chemistry, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
| | - Fruzsina Hobor
- Astbury Centre for Structural Molecular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
- School of Molecular and Cellular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
| | - Thomas James
- Astbury Centre for Structural Molecular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
- School of Chemistry, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
| | - Gail J Bartlett
- School of Chemistry, University of Bristol Cantock's Close Bristol BS8 1TS UK
| | - Amaurys A Ibarra
- School of Biochemistry, University of Bristol Medical Sciences Building, University Walk Bristol BS8 1TD UK
| | - Deborah K Shoemark
- School of Biochemistry, University of Bristol Medical Sciences Building, University Walk Bristol BS8 1TD UK
- BrisSynBio, University of Bristol Life Sciences Building, Tyndall Avenue Bristol BS8 1TQ UK
| | - Zsófia Hegedüs
- Astbury Centre for Structural Molecular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
- School of Chemistry, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
| | - Kristina Hetherington
- Astbury Centre for Structural Molecular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
- School of Chemistry, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
| | - Derek N Woolfson
- School of Chemistry, University of Bristol Cantock's Close Bristol BS8 1TS UK
- School of Biochemistry, University of Bristol Medical Sciences Building, University Walk Bristol BS8 1TD UK
- BrisSynBio, University of Bristol Life Sciences Building, Tyndall Avenue Bristol BS8 1TQ UK
| | - Richard B Sessions
- School of Biochemistry, University of Bristol Medical Sciences Building, University Walk Bristol BS8 1TD UK
- BrisSynBio, University of Bristol Life Sciences Building, Tyndall Avenue Bristol BS8 1TQ UK
| | - Thomas A Edwards
- Astbury Centre for Structural Molecular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
- School of Molecular and Cellular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
| | - David M Andrews
- Early Oncology, AstraZeneca Hodgkin Building, Chesterford Research Campus, Saffron Walden Cambridge CB10 1XL UK
| | - Adam Nelson
- Astbury Centre for Structural Molecular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
- School of Chemistry, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
| | - Andrew J Wilson
- Astbury Centre for Structural Molecular Biology, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
- School of Chemistry, University of Leeds Woodhouse Lane Leeds LS2 9JT UK
| |
Collapse
|
3
|
Qian X, Zhou H, Chaminda Lakmal HH, Lucore J, Wang X, Valle HU, Donnadieu B, Xu X, Cui X. Fe(III)-Based Tandem Catalysis for Amidomethylative Multiple Substitution Reactions of α-Substituted Styrene Derivatives. ACS Catal 2020. [DOI: 10.1021/acscatal.0c02676] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Xiaolin Qian
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | - Hui Zhou
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | | | - James Lucore
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | - Xuesong Wang
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | - Henry U. Valle
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | - Bruno Donnadieu
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | - Xue Xu
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | - Xin Cui
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| |
Collapse
|
4
|
Türkmenoğlu B, Güzel Y. Molecular docking and 4D-QSAR studies of metastatic cancer inhibitor thiazoles. Comput Biol Chem 2018; 76:327-337. [PMID: 30145406 DOI: 10.1016/j.compbiolchem.2018.07.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 06/29/2018] [Accepted: 07/03/2018] [Indexed: 11/28/2022]
Abstract
By using the molecular docking and 4D-QSAR analysis, it is aimed to find the interaction points in the receptor binding site of transforming growth factor-beta (TGF-beta) used to inhibit invasion and metastasis. To elucidate the interaction points of receptor, different types of local reactive descriptor (LRD) of ligands have been used. Activity values related to interaction energy between the ligand-receptor (L-R) were determined by nonlinear least squares (NLLS) using the Levenberg-Marquardt (LM) algorithm. Using the Molecule Comparative Electron Topology (MCET) method, the 3D pharmacophore model (3D-PhaM) was obtained after alignment and superimposition of the molecules, and also confirmed by molecular docking method. With the leave one out-cross validation (LOO-CV) method, the best predictions are q2 or rCV2 = 0.789 for the 51 compounds in the internal training set and r2 = 0.785 for the 13 compounds in the external test set. Furthermore, the predictive capability of the advanced QSAR model is more precisely calculated with the rm2 metric (rm2 = 0.769).
Collapse
Affiliation(s)
- Burçin Türkmenoğlu
- Department of Chemistry, Faculty of Science, Erciyes University, 38039, Kayseri, Turkey.
| | - Yahya Güzel
- Department of Chemistry, Faculty of Science, Erciyes University, 38039, Kayseri, Turkey
| |
Collapse
|
5
|
Subramanian G, Poda G. In silico ligand-based modeling of hBACE-1 inhibitors. Chem Biol Drug Des 2017; 91:817-827. [PMID: 29139199 DOI: 10.1111/cbdd.13147] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 10/24/2017] [Accepted: 11/01/2017] [Indexed: 02/06/2023]
Abstract
Alzheimer's disease is a chronic neurodegenerative disease affecting more than 30 million people worldwide. Development of small molecule inhibitors of human β-secretase 1 (hBACE-1) is being the focus of pharmaceutical industry for the past 15-20 years. Here, we successfully applied multiple ligand-based in silico modeling techniques to understand the inhibitory activities of a diverse set of small molecule hBACE-1 inhibitors reported in the scientific literature. Strikingly, the use of only a small subset of 230 (13%) molecules allowed us to develop quality models that performed reasonably well on the validation set of 1,476 (87%) inhibitors. Varying the descriptor sets and the complexity of the modeling techniques resulted in only minor improvements to the model's performance. The current results demonstrate that predictive models can be built by choosing appropriate modeling techniques in spite of using small datasets consisting of diverse chemical classes, a scenario typical in triaging of high-throughput screening results to identify false negatives. We hope that these encouraging results will help the community to develop more predictive models that would support research efforts for the debilitating Alzheimer's disease. Additionally, the integrated diversity of the techniques employed will stimulate scientists in the field to use in silico statistical modeling techniques like these to derive better models to help advance the drug discovery projects faster.
Collapse
Affiliation(s)
| | - Gennady Poda
- Drug Discovery Program, Ontario Institute for Cancer Research, Toronto, ON, Canada.,Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
6
|
Wilkes JG, Stoyanova-Slavova IB, Buzatu DA. Alignment-independent technique for 3D QSAR analysis. J Comput Aided Mol Des 2016; 30:331-45. [PMID: 27026022 PMCID: PMC4833814 DOI: 10.1007/s10822-016-9909-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 03/08/2016] [Indexed: 11/25/2022]
Abstract
Molecular biochemistry is controlled by 3D phenomena but structure-activity models based on 3D descriptors are infrequently used for large data sets because of the computational overhead for determining molecular conformations. A diverse dataset of 146 androgen receptor binders was used to investigate how different methods for defining molecular conformations affect the performance of 3D-quantitative spectral data activity relationship models. Molecular conformations tested: (1) global minimum of molecules' potential energy surface; (2) alignment-to-templates using equal electronic and steric force field contributions; (3) alignment using contributions "Best-for-Each" template; (4) non-energy optimized, non-aligned (2D > 3D). Aggregate predictions from models were compared. Highest average coefficients of determination ranged from R Test (2) = 0.56 to 0.61. The best model using 2D > 3D (imported directly from ChemSpider) produced R Test (2) = 0.61. It was superior to energy-minimized and conformation-aligned models and was achieved in only 3-7 % of the time required using the other conformation strategies. Predictions averaged from models built on different conformations achieved a consensus R Test (2) = 0.65. The best 2D > 3D model was analyzed for underlying structure-activity relationships. For the compound strongest binding to the androgen receptor, 10 substructural features contributing to binding were flagged. Utility of 2D > 3D was compared for two other activity endpoints, each modeling a medium sized data set. Results suggested that large scale, accurate predictions using 2D > 3D SDAR descriptors may be produced for interactions involving endocrine system nuclear receptors and other data sets in which strongest activities are produced by fairly inflexible substrates.
Collapse
Affiliation(s)
- Jon G. Wilkes
- Division of Systems Biology, National Center for Toxicological Research, 3900 NCTR Road, Jefferson, AR 72079 USA
| | - Iva B. Stoyanova-Slavova
- Division of Systems Biology, National Center for Toxicological Research, 3900 NCTR Road, Jefferson, AR 72079 USA
| | - Dan A. Buzatu
- Division of Systems Biology, National Center for Toxicological Research, 3900 NCTR Road, Jefferson, AR 72079 USA
| |
Collapse
|
7
|
Aalizadeh R, Pourbasheer E, Ganjali MR. Analysis of B-Raf $$^{\mathrm{V600E}}$$ V 600 E inhibitors using 2D and 3D-QSAR, molecular docking and pharmacophore studies. Mol Divers 2015; 19:915-30. [DOI: 10.1007/s11030-015-9626-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2015] [Accepted: 07/27/2015] [Indexed: 12/14/2022]
|
8
|
Fernandez M, Ahmad S, Abreu JI, Sarai A. Large-scale recognition of high-affinity protease–inhibitor complexes using topological autocorrelation and support vector machines. MOLECULAR SIMULATION 2015. [DOI: 10.1080/08927022.2015.1059937] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
|
9
|
Synthesis and biological evaluation of piperazine derivatives as novel isoform selective voltage-gated sodium (Nav) 1.3 channel modulators. Med Chem Res 2014. [DOI: 10.1007/s00044-014-1300-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
10
|
Durrant JD, Votapka L, Sørensen J, Amaro RE. POVME 2.0: An Enhanced Tool for Determining Pocket Shape and Volume Characteristics. J Chem Theory Comput 2014; 10:5047-5056. [PMID: 25400521 PMCID: PMC4230373 DOI: 10.1021/ct500381c] [Citation(s) in RCA: 173] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Indexed: 02/08/2023]
Abstract
![]()
Analysis of macromolecular/small-molecule
binding pockets can provide
important insights into molecular recognition and receptor dynamics.
Since its release in 2011, the POVME (POcket Volume MEasurer) algorithm
has been widely adopted as a simple-to-use tool for measuring and
characterizing pocket volumes and shapes. We here present POVME 2.0,
which is an order of magnitude faster, has improved accuracy, includes
a graphical user interface, and can produce volumetric density maps
for improved pocket analysis. To demonstrate the utility of the algorithm,
we use it to analyze the binding pocket of RNA editing ligase 1 from
the unicellular parasite Trypanosoma brucei, the
etiological agent of African sleeping sickness. The POVME analysis
characterizes the full dynamics of a potentially druggable transient
binding pocket and so may guide future antitrypanosomal drug-discovery
efforts. We are hopeful that this new version will be a useful tool
for the computational- and medicinal-chemist community.
Collapse
Affiliation(s)
- Jacob D Durrant
- Department of Chemistry & Biochemistry, University of California San Diego , La Jolla, California 92093, United States ; National Biomedical Computation Resource, Center for Research in Biological Systems, University of California San Diego , La Jolla, California 92093, United States
| | - Lane Votapka
- Department of Chemistry & Biochemistry, University of California San Diego , La Jolla, California 92093, United States
| | - Jesper Sørensen
- Department of Chemistry & Biochemistry, University of California San Diego , La Jolla, California 92093, United States
| | - Rommie E Amaro
- Department of Chemistry & Biochemistry, University of California San Diego , La Jolla, California 92093, United States ; National Biomedical Computation Resource, Center for Research in Biological Systems, University of California San Diego , La Jolla, California 92093, United States
| |
Collapse
|
11
|
Pourbasheer E, Aalizadeh R, Shokouhi Tabar S, Ganjali MR, Norouzi P, Shadmanesh J. 2D and 3D Quantitative Structure–Activity Relationship Study of Hepatitis C Virus NS5B Polymerase Inhibitors by Comparative Molecular Field Analysis and Comparative Molecular Similarity Indices Analysis Methods. J Chem Inf Model 2014; 54:2902-14. [DOI: 10.1021/ci500216c] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Eslam Pourbasheer
- Department
of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697, Tehran, Iran
| | | | - Samira Shokouhi Tabar
- Department
of Chemistry, Payame Noor University (PNU), P. O. Box 19395-3697, Tehran, Iran
| | - Mohammad Reza Ganjali
- Center
of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, P.O. Box 143981-7435, Tehran, Iran
- Biosensor
Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences
Institute, Tehran University of Medical Sciences, P. O. Box,
14114-13137, Tehran, Iran
| | - Parviz Norouzi
- Center
of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, P.O. Box 143981-7435, Tehran, Iran
- Biosensor
Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences
Institute, Tehran University of Medical Sciences, P. O. Box,
14114-13137, Tehran, Iran
| | | |
Collapse
|
12
|
Wendt B, Cramer RD. Challenging the gold standard for 3D-QSAR: template CoMFA versus X-ray alignment. J Comput Aided Mol Des 2014; 28:803-24. [PMID: 24934658 DOI: 10.1007/s10822-014-9761-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2014] [Accepted: 06/05/2014] [Indexed: 11/26/2022]
Abstract
X-ray-based alignments of bioactive compounds are commonly used to correlate structural changes with changes in potencies, ultimately leading to three-dimensional quantitative structure-activity relationships such as CoMFA or CoMSIA models that can provide further guidance for the design of new compounds. We have analyzed data sets where the alignment of the compounds is entirely based on experimentally derived ligand poses from X-ray-crystallography. We developed CoMFA and CoMSIA models from these X-ray-determined receptor-bound conformations and compared the results with models generated from ligand-centric Template CoMFA, finding that the fluctuations in the positions and conformations of compounds dominate X-ray-based alignments can yield poorer predictions than those from the self-consistent template CoMFA alignments. Also, when there exist multiple different binding modes, structural interpretation in terms of binding site constraints can often be simpler with template-based alignments than with X-ray-based alignments.
Collapse
Affiliation(s)
- Bernd Wendt
- Certara, Martin-Kollar-Str. 17, 81829, Munich, Germany,
| | | |
Collapse
|
13
|
Sun XQ, Chen L, Li YZ, Li WH, Liu GX, Tu YQ, Tang Y. Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors. Acta Pharmacol Sin 2014; 35:301-10. [PMID: 24335842 PMCID: PMC4076596 DOI: 10.1038/aps.2013.148] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Accepted: 09/10/2013] [Indexed: 01/25/2023] Open
Abstract
AIM To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase (EGFR TK) and its inhibitors. METHODS One hundred thirty nine EGFR TK inhibitors were classified into 3 clusters. Ensemble docking of these inhibitors with 19 EGFR TK crystal structures was performed. Three protein structures that showed the best recognition of each cluster were selected based on the docking results. Then, a novel QSAR (ensemble-QSAR) building method was developed based on the ligand conformations determined by the corresponding protein structures. RESULTS Compared with the 3D-QSAR model, in which the ligand conformations were determined by a single protein structure, ensemble-QSAR exhibited higher R2 (0.87) and Q2 (0.78) values and thus appeared to be a more reliable and better predictive model. Ensemble-QSAR was also able to more accurately describe the interactions between the target and the ligands. CONCLUSION The novel ensemble-QSAR model built in this study outperforms the traditional 3D-QSAR model in rationality, and provides a good example of selecting suitable protein structures for docking prediction and for building structure-based QSAR using available protein structures.
Collapse
Affiliation(s)
- Xian-qiang Sun
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
- Division of Theoretical Chemistry and Biology, School of Biotechnology, KTH Royal Institute of Technology, S-106 91 Stockholm, Sweden
| | - Lei Chen
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yao-zong Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
- Department of Chemistry, Umeå University, S-90187 Umeå, Sweden
| | - Wei-hua Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Gui-xia Liu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| | - Yao-quan Tu
- Division of Theoretical Chemistry and Biology, School of Biotechnology, KTH Royal Institute of Technology, S-106 91 Stockholm, Sweden
| | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China
| |
Collapse
|
14
|
Crisan L, Pacureanu L, Avram S, Bora A, Avram S, Kurunczi L. PLS and shape-based similarity analysis of maleimides--GSK-3 inhibitors. J Enzyme Inhib Med Chem 2013; 29:599-610. [PMID: 24047148 DOI: 10.3109/14756366.2013.833196] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
CONTEXT Glycogen synthase kinase-3 (GSK-3) overactivity was correlated with several pathologies including type 2 diabetes mellitus, Alzheimer's disease, cancer, inflammation, obesity, etc. OBJECTIVE The aim of the current investigation was to model the inhibitory activity of maleimide derivatives--inhibitors of GSK-3, to evaluate the impact of alignment on statistical performances of the Quantitative Structure-Activity Relationship (QSAR) and the effect of the template on shape-similarity--binding affinity relationship. MATERIALS AND METHODS Dragon descriptors were used to generate Projection to Latent Structures (PLS) models in order to identify the structural prerequisites of maleimides to inhibit GSK-3. Additionally, shape/volume structural analysis of binding site interactions was evaluated. RESULTS Reliable statistics R(2)(Y(CUM)) = 0.938/0.920, Q((2)(Y)(CUM)) = 0.866/0.838 for aligned and alignment free QSAR models and significant (Pearson, Kendall and Spearman) correlations between shape/volume similarity and affinities were obtained. DISCUSSION AND CONCLUSIONS The crucial structural features modulating the activity of maleimides include topology, charge, geometry, 2D autocorrelations, 3D-MoRSE as well as shape/volume and molecular flexibility.
Collapse
Affiliation(s)
- Luminita Crisan
- Department of Computational Chemistry, Institute of Chemistry of Romanian Academy , Timisoara , Romania
| | | | | | | | | | | |
Collapse
|
15
|
Pinsetta FR, Taft CA, de Paula da Silva CHT. Structure- and ligand-based drug design of novel p38-alpha MAPK inhibitors in the fight against the Alzheimer's disease. J Biomol Struct Dyn 2013; 32:1047-63. [PMID: 23805842 DOI: 10.1080/07391102.2013.803441] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Alzheimer's disease (AD) is characterized microscopically by the presence of amyloid plaques, which are accumulations of beta-amyloid protein inter-neurons, and neurofibrillary tangles formed predominantly by highly phosphorylated forms of the microtubule-associated protein, tau, which form tangled masses that consume neuronal cell body, possibly leading to neuronal dysfunction and ultimately death. p38α mitogen-activated protein kinase (MAPK) has been implicated in both events associated with AD, tau phosphorylation and inflammation. p38α MAPK pathway is activated by a dual phosphorylation at Thr180 and Tyr182 residues. Drug design of p38α MAPK inhibitors is mainly focused on small molecules that compete for Adenosine triphosphate in the catalytic site. Here, we used different approaches of structure- and ligand-based drug design and medicinal chemistry strategies based on a selected p38α MAPK structure deposited in the Protein Data Bank in complex with inhibitor, as well as others reported in literature. As a result of the virtual screening experiments performed here, as well as molecular dynamics, molecular interaction fields studies, shape and electrostatic similarities, activity and toxicity predictions, and pharmacokinetic and physicochemical properties, we have selected 13 compounds that meet the criteria of low or no toxicity potential, good pharmacotherapeutic profile, predicted activities, and calculated values comparable with those obtained for the reference compounds, while maintaining the main interactions observed for the most potent inhibitors.
Collapse
Affiliation(s)
- Flávio Roberto Pinsetta
- a Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo , Av. do Café, s/n - Monte Alegre, Ribeirão Preto , SP 14040-903 , Brazil
| | | | | |
Collapse
|
16
|
Pérez-Castillo Y, Lazar C, Taminau J, Froeyen M, Cabrera-Pérez MÁ, Nowé A. GA(M)E-QSAR: A Novel, Fully Automatic Genetic-Algorithm-(Meta)-Ensembles Approach for Binary Classification in Ligand-Based Drug Design. J Chem Inf Model 2012; 52:2366-86. [DOI: 10.1021/ci300146h] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Affiliation(s)
- Yunierkis Pérez-Castillo
- Computational Modeling Lab (CoMo), Department
of Computer Sciences, Faculty
of Sciences, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussel, Belgium
- Molecular Simulations and Drug
Design Group, Centro de Bioactivos Químicos, Universidad Central “Marta Abreu” de Las Villas, Santa
Clara, Cuba
- Laboratory for
Medicinal Chemistry,
Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium
| | - Cosmin Lazar
- Computational Modeling Lab (CoMo), Department
of Computer Sciences, Faculty
of Sciences, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussel, Belgium
| | - Jonatan Taminau
- Computational Modeling Lab (CoMo), Department
of Computer Sciences, Faculty
of Sciences, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussel, Belgium
| | - Mathy Froeyen
- Laboratory for
Medicinal Chemistry,
Rega Institute for Medical Research, Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, Belgium
| | - Miguel Ángel Cabrera-Pérez
- Molecular Simulations and Drug
Design Group, Centro de Bioactivos Químicos, Universidad Central “Marta Abreu” de Las Villas, Santa
Clara, Cuba
- Engineering
Department, Pharmacy and Pharmaceutical Technology Area,
Faculty of Pharmacy, University Miguel Hernandez, Alicante 03550, Spain
| | - Ann Nowé
- Computational Modeling Lab (CoMo), Department
of Computer Sciences, Faculty
of Sciences, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussel, Belgium
| |
Collapse
|
17
|
Quantitative prediction of enantioselectivity of Candida antarctica lipase B by combining docking simulations and quantitative structure–activity relationship (QSAR) analysis. ACTA ACUST UNITED AC 2011. [DOI: 10.1016/j.molcatb.2011.06.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
|