1
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Structural Insights on Hyp-Gly-Containing Peptides as Antiplatelet Compounds through Topomer CoMFA and CoMSIA Analysis. Foods 2023; 12:foods12040777. [PMID: 36832851 PMCID: PMC9956102 DOI: 10.3390/foods12040777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/07/2023] [Accepted: 02/09/2023] [Indexed: 02/15/2023] Open
Abstract
Increasing evidence has shown collagen hydrolysate involves a variety of bioactivities. In our previous study, multiple antiplatelet peptides containing Hyp/Pro-Gly were identified in collagen hydrolysates from Salmo salar and silver carp skin and exhibited anti-thrombosis activity without bleeding risks in vivo. However, the relationship between structure and activity remains unknown. We performed 3D-QSAR studies on 23 Hyp/Pro-Gly-containing peptides in which 13 peptides were reported before. CoMFA, Topomer CoMFA and CoMSIA analyses were used to generate the QSAR models. Topomer CoMFA analysis showed a q2 value of 0.710, an r2 value of 0.826, an r2pred value of 0.930, and the results showed that Hyp instead of Pro was more important for improving the antiplatelet activity. CoMSIA analysis showed a q2 value of 0.461, an r2 value of 0.999, and an r2pred value of 0.999. Compared with the electrostatic field and hydrogen bond donor field, the steric field, hydrophobic field and hydrogen bond receptor field have great influence on the activity of antiplatelet peptides. The predicted peptide EOGE exhibited antiplatelet activity induced by ADP, and inhibited thrombus formation (300 μmol/kg bw) without bleeding risks. Combined results of these studies indicate that OG-containing peptides had a potential to be developed into an effective specific medical food in the prevention of thrombotic diseases.
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2
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Shah BM, Sagar SR, Trivedi P. Insights into the structural requirements of triazole derivatives as promising DPP IV inhibitors: computational investigations. J Biomol Struct Dyn 2022; 40:13778-13798. [PMID: 34738504 DOI: 10.1080/07391102.2021.1994876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Diabetes is one of the leading causes of death globally as per World Health Organization 2019. To cope up with side effects of current diabetes therapy, researchers have found several novel targets for the treatment of diabetes. Currently, dipeptidyl peptidase IV (DPP IV) has emerged as a target in modulating the diabetes physiology. In the present work, various 3D-Quantitative structure activity relationship (QSAR) techniques namely comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis, topomer CoMFA and molecular hologram QSAR are used to explore the structural requirements of triazole derivatives as DPP IV inhibitors. Different models generated by 3D QSAR studies had acceptable statistical values for further prediction of molecules. From the contour maps of QSAR results, important structural features are deduced. Substitutions on N1 and N2 of triazole ring with H-bond donor group enhances the biological activity. Aliphatic side chain, less bulky group, H-bond donor group and -COOH group on N3 of triazole ring are vital for the DPP IV inhibition. Moreover, electron withdrawing side chain on the triazole ring improves the biological activity. Further, novel triazole derivatives were designed and docking results of these compounds proved the efficiency of the developed 3D QSAR model. In future, results of this study may provide promising DPP IV inhibitors for the treatment of diabetes. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Bhumi M Shah
- Department of Pharmaceutical Chemistry, K. B. Institute of Pharmaceutical Education and Research, Gandhinagar, Gujarat, India.,Department of Pharmaceutical Chemistry, L. J. Institute of Pharmacy, L. J. University, Ahmedabad, Gujarat, India
| | - Sneha R Sagar
- Department of Pharmaceutical Chemistry, L. J. Institute of Pharmacy, L. J. University, Ahmedabad, Gujarat, India
| | - Priti Trivedi
- Department of Pharmaceutical Chemistry, K. B. Institute of Pharmaceutical Education and Research, Gandhinagar, Gujarat, India
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3
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Jian-Bo T, Xing Z, Shuai B, Ding L, Tian-Hao W. Topomer CoMFA and HQSAR Study on Benzimidazole Derivative as NS5B Polymerase Inhibitor. LETT DRUG DES DISCOV 2022. [DOI: 10.2174/1570180818666210804125607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
In recent years, the number of people infected with the hepatitis C virus
(HCV) is increasing rapidly. This has become a major threat to global health, therefore, new anti-
HCV drugs are urgently needed. HCV NS5B polymerase is an RNA-dependent RNA polymerase
(RdRp), which plays an important role in virus replication, and can effectively prevent the replication
of HCV sub-genomic RNA in daughter cells. It is considered a very promising HCV therapeutic
target for the design of anti-HCV drugs.
Methods:
In order to explore the relationship between the structure of benzimidazole derivative and
its inhibitory activity on NS5B polymerase, holographic quantitative structure-activity relationship
(HQSAR) and Topomer comparative molecular field analysis (CoMFA) were used to establish benzimidazole
QSAR model of derivative inhibitors.
Results:
The results show that for the Topomer CoMFA model, the cross-validation coefficient q2
value is 0.883, and the non-cross-validation coefficient r2 value is 0.975. The model is reasonable,
reliable, and has a good predictive ability. For the HQSAR model, the cross-validated q2 value is
0.922, and the uncross-validated r2 value is 0.971, indicating that the model data fit well and has a
high predictive ability. Through the analysis of the contour map and color code diagram, 40 new
benzimidazole inhibitor molecules were designed, and all of them have higher activity than template
molecules, and the new molecules have significant interaction sites with protein 3SKE.
Conclusion:
The 3D-QSAR model established by Topomer CoMFA and HQSAR has good prediction
results and the statistical verification is valid. The newly designed molecules and docking results
provide theoretical guidance for the synthesis of new NS5B polymerase inhibitors and for the identification
of key residues that the inhibitors bind to NS5B, which helps to better understand their inhibitory
mechanism. These findings are helpful for the development of new anti-HCV drugs.
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Affiliation(s)
- Tong Jian-Bo
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi\'an 710021, China
- Shaanxi Key Laboratory of Chemical Additives for Industry, Xi\'an, 710021, China
| | - Zhang Xing
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi\'an 710021, China
- Shaanxi Key Laboratory of Chemical Additives for Industry, Xi\'an, 710021, China
| | - Bian Shuai
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi\'an 710021, China
- Shaanxi Key Laboratory of Chemical Additives for Industry, Xi\'an, 710021, China
| | - Luo Ding
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi\'an 710021, China
- Shaanxi Key Laboratory of Chemical Additives for Industry, Xi\'an, 710021, China
| | - Wang Tian-Hao
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi\'an 710021, China
- Shaanxi Key Laboratory of Chemical Additives for Industry, Xi\'an, 710021, China
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4
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Luo D, Tong JB, Feng Y. 3D-QSAR and Molecular Docking Analysis for Natural Aurone Derivatives as Anti-Malarial Agents. Polycycl Aromat Compd 2021. [DOI: 10.1080/10406638.2021.1973519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Ding Luo
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, China
- Shaanxi Key Laboratory of Chemical Additives for Industry, Xi'an, China
| | - Jian-Bo Tong
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, China
- Shaanxi Key Laboratory of Chemical Additives for Industry, Xi'an, China
| | - Yi Feng
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, China
- Shaanxi Key Laboratory of Chemical Additives for Industry, Xi'an, China
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5
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Tong JB, Bian S, Zhang X, Luo D. QSAR analysis of 3-pyrimidin-4-yl-oxazolidin-2-one derivatives isocitrate dehydrogenase inhibitors using Topomer CoMFA and HQSAR methods. Mol Divers 2021; 26:1017-1037. [PMID: 33974175 DOI: 10.1007/s11030-021-10222-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 04/02/2021] [Indexed: 01/03/2023]
Abstract
A series of mIDH1 inhibitors derived from 3-pyrimidine-4-oxazolidin-2-ketone derivatives were studied by QSAR model to explore the key factors that inhibit mIDH1 activity. The generated model was cross-verified and non-cross-verified by Topomer CoMFA and HQSAR methods; the independent test set was verified by PLS method; the Topomer search technology was used for virtual screening and molecular design; and the Surflex-Dock method and ADMET technology were used for molecular docking, pharmacology and toxicity prediction of the designed drug molecules. The Topomer CoMFA and HQSAR cross-validation coefficients q2 are 0.783 and 0.784, respectively, and the non-cross-validation coefficients r2 are 0.978 and 0.934, respectively. Ten new drug molecules have been designed using Topomer search technology. The results of molecular docking and ADMET show that the newly designed drug molecules are effective. The docking situation, pharmacology and toxicity prediction results are good. The model can be used to predict the bioactivity of the same type of new compounds and their derivatives. The prediction results of molecular design, molecular docking and ADMET can provide some ideas for the design and development of novel mIDH1 inhibitor anticancer drugs, and provide certain theoretical basis of the experimental verification of new compounds in the future. Newly designed molecules after docking with corresponding proteins in the PDB library, it can explore the targets of drug molecules acting with large proteins and the related force, which is very helpful for the design of new drugs and the mechanism of drug action.
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Affiliation(s)
- Jian-Bo Tong
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, 710021, China. .,Shaanxi Key Laboratory of Chemical Additives for Industry, Xi'an, 710021, China.
| | - Shuai Bian
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, 710021, China.,Shaanxi Key Laboratory of Chemical Additives for Industry, Xi'an, 710021, China
| | - Xing Zhang
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, 710021, China.,Shaanxi Key Laboratory of Chemical Additives for Industry, Xi'an, 710021, China
| | - Ding Luo
- College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, 710021, China.,Shaanxi Key Laboratory of Chemical Additives for Industry, Xi'an, 710021, China
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6
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Tong JB, Luo D, Xu HY, Bian S, Zhang X, Xiao XC, Wang J. A computational approach for designing novel SARS-CoV-2 M pro inhibitors: combined QSAR, molecular docking, and molecular dynamics simulation techniques. NEW J CHEM 2021. [DOI: 10.1039/d1nj02127c] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
The promising compound T21 for treating COVID-19 at the active site of SARS-CoV-2 Mpro.
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Affiliation(s)
- Jian-Bo Tong
- College of Chemistry and Chemical Engineering
- Shaanxi University of Science and Technology
- Xi’an 710021
- China
- Shaanxi Key Laboratory of Chemical Additives for Industry
| | - Ding Luo
- College of Chemistry and Chemical Engineering
- Shaanxi University of Science and Technology
- Xi’an 710021
- China
- Shaanxi Key Laboratory of Chemical Additives for Industry
| | - Hai-Yin Xu
- College of Chemistry and Chemical Engineering
- Shaanxi University of Science and Technology
- Xi’an 710021
- China
- Shaanxi Key Laboratory of Chemical Additives for Industry
| | - Shuai Bian
- College of Chemistry and Chemical Engineering
- Shaanxi University of Science and Technology
- Xi’an 710021
- China
- Shaanxi Key Laboratory of Chemical Additives for Industry
| | - Xing Zhang
- College of Chemistry and Chemical Engineering
- Shaanxi University of Science and Technology
- Xi’an 710021
- China
- Shaanxi Key Laboratory of Chemical Additives for Industry
| | - Xue-Chun Xiao
- College of Chemistry and Chemical Engineering
- Shaanxi University of Science and Technology
- Xi’an 710021
- China
- Shaanxi Key Laboratory of Chemical Additives for Industry
| | - Jie Wang
- College of Chemistry and Chemical Engineering
- Shaanxi University of Science and Technology
- Xi’an 710021
- China
- Shaanxi Key Laboratory of Chemical Additives for Industry
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7
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Using Topomer Comparative Molecular Field Analysis to Elucidate Activity Differences of Aminomethylenethiophene Derivatives as Lysyl Oxidase Inhibitors: Implications for Rational Design of Antimetastatic Agents for Cancer Therapy. J CHEM-NY 2020. [DOI: 10.1155/2020/2036585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Topomer comparative molecular field analysis (topomer CoMFA) is applied to the quantitative structure-activity relationship (QSAR) study of aminomethylenethiophene (AMT) derivatives as lysyl oxidase (LOX) inhibitors. A total of thirty-six AMT derivatives were selected to build the QSAR model. The established topomer CoMFA model has the non-cross-validated correlation coefficient (r2) of 0.912 and the leave-one-out correlation coefficient (q2) of 0.540, which is statistically significant. The theoretically predicted anti-LOX potency agrees well with the experimentally observed inhibitory activity, proving the reasonable predictive ability of the QSAR model. The effect of molecular field information on the LOX inhibition of substituted aminomethylenethiophene was discussed in detail. The structural modification of the aminomethylenethiophene scaffold was carried out, and novel AMT derivatives with theoretically decent LOX inhibition were proposed. The topomer CoMFA modeling could provide a quantitative perspective into the structure-activity relationship of AMT derivatives and potentially speed up the rational design of LOX inhibitors as antimetastatic agents for cancer therapy.
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8
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Mishra RK, Deibler KK, Clutter MR, Vagadia PP, O'Connor M, Schiltz GE, Bergan R, Scheidt KA. Modeling MEK4 Kinase Inhibitors through Perturbed Electrostatic Potential Charges. J Chem Inf Model 2019; 59:4460-4466. [PMID: 31566378 DOI: 10.1021/acs.jcim.9b00490] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
MEK4, mitogen-activated protein kinase kinase 4, is overexpressed and induces metastasis in advanced prostate cancer lesions. However, the value of MEK4 as an oncology target has not been pharmacologically validated because selective chemical probes targeting MEK4 have not been developed. With advances in both computer and biological high-throughput screening, selective chemical entities can be discovered. Structure-based quantitative structure-activity relationship (QSAR) modeling often fails to generate accurate models due to poor alignment of training sets containing highly diverse compounds. Here we describe a highly predictive, nonalignment based robust QSAR model based on a data set of strikingly diverse MEK4 inhibitors. We computed the electrostatic potential (ESP) charges using a density functional theory (DFT) formalism of the donor and acceptor atoms of the ligands and hinge residues. Novel descriptors were then generated from the perturbation of the charge densities of the donor and acceptor atoms and were used to model a diverse set of 84 compounds, from which we built a robust predictive model.
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Affiliation(s)
- Rama K Mishra
- Center for Molecular Innovation and Drug Discovery , Northwestern University , 2145 Sheridan Road , Evanston , Illinois 60208 , United States.,Department of Pharmacology, Feinberg School of Medicine , Northwestern University , Chicago , Illinois 60611 , United States
| | - Kristine K Deibler
- Department of Chemistry , Northwestern University , Evanston , Illinois 60208 , United States
| | - Matthew R Clutter
- Chemistry of Life Processes Institute , Northwestern University , 2145 Sheridan Road , Evanston , Illinois 60208 , United States.,Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine , Northwestern University , Chicago , Illinois 60611 , United States
| | - Purav P Vagadia
- Center for Molecular Innovation and Drug Discovery , Northwestern University , 2145 Sheridan Road , Evanston , Illinois 60208 , United States
| | - Matthew O'Connor
- Department of Chemistry , Northwestern University , Evanston , Illinois 60208 , United States
| | - Gary E Schiltz
- Center for Molecular Innovation and Drug Discovery , Northwestern University , 2145 Sheridan Road , Evanston , Illinois 60208 , United States.,Department of Pharmacology, Feinberg School of Medicine , Northwestern University , Chicago , Illinois 60611 , United States.,Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine , Northwestern University , Chicago , Illinois 60611 , United States
| | - Raymond Bergan
- Knight Cancer Institute , Oregon Health & Science University , Portland , Oregon 97239 , United States
| | - Karl A Scheidt
- Center for Molecular Innovation and Drug Discovery , Northwestern University , 2145 Sheridan Road , Evanston , Illinois 60208 , United States.,Department of Pharmacology, Feinberg School of Medicine , Northwestern University , Chicago , Illinois 60611 , United States.,Department of Chemistry , Northwestern University , Evanston , Illinois 60208 , United States.,Chemistry of Life Processes Institute , Northwestern University , 2145 Sheridan Road , Evanston , Illinois 60208 , United States.,Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine , Northwestern University , Chicago , Illinois 60611 , United States
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9
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Two- and three-dimensional QSAR studies on hURAT1 inhibitors with flexible linkers: topomer CoMFA and HQSAR. Mol Divers 2019; 24:141-154. [PMID: 30868332 DOI: 10.1007/s11030-019-09936-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 03/01/2019] [Indexed: 12/20/2022]
Abstract
hURAT1 (human urate transporter 1) is a successful target for hyperuricemia. Recently, the modification work on hURAT1 inhibitors showed that the flexible linkers would benefit biological activity. The study aimed to investigate the contribution of the linkers and give modification strategies on this kind of structures based on QSAR models (HQSAR and topomer CoMFA). The most effective HQSAR and topomer CoMFA models were generated by applying the training set containing 63 compounds, with the cross-validated q2 values of 0.869/0.818 and the non-cross-validated correlation coefficients r2 of 0.951/0.978, respectively. The Y-randomization test was applied to ensure the robustness of the models. The external predictive correlation coefficient (rpred2) grounded on the external test set (21 compounds) of two models was 0.910 and 0.907, respectively. In addition, the models were validated by Golbraikh-Tropsha and Roy methods, as well as other statistical metrics. The results showed that both models were reliable. Topomer CoMFA steric/electrostatic contours and HQSAR atomic contribution maps illustrated the structural features which governed their inhibitory potency. The dependable results could provide important insights to guide the designing of more potential hURAT1 inhibitors.
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10
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Tong J, Jiang G, Li L, Li Y. Molecular Virtual Screening Studies of Herbicidal Sulfonylurea Analogues Using Molecular Docking and Topomer CoMFA Research. J STRUCT CHEM+ 2019. [DOI: 10.1134/s0022476619020057] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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11
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Tong J, Jiang G, Li L, Li Y. Molecular Docking and 3D QSAR Research of Indolocarbazole Series as Cyclin-Dependent Kinase Inhibitors. J STRUCT CHEM+ 2018. [DOI: 10.1134/s0022476618070065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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12
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Halder AK, Moura AS, Cordeiro MNDS. QSAR modelling: a therapeutic patent review 2010-present. Expert Opin Ther Pat 2018; 28:467-476. [DOI: 10.1080/13543776.2018.1475560] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Amit Kumar Halder
- LAQV@REQUIMTE/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, Porto, Portugal
| | - Ana S. Moura
- LAQV@REQUIMTE/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, Porto, Portugal
| | - M. Natalia D. S. Cordeiro
- LAQV@REQUIMTE/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, Porto, Portugal
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13
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Han D, Tan J, Zhou Z, Li C, Zhang X, Wang C. Combined topomer CoMFA and hologram QSAR studies of a series of pyrrole derivatives as potential HIV fusion inhibitors. Med Chem Res 2018. [DOI: 10.1007/s00044-018-2190-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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14
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Sadeghzadeh M, Salahinejad M, Zarezadeh N, Ghandi M, Baghery MK. Antitumor evaluation and 3D-QSAR studies of a new series of the spiropyrroloquinoline isoindolinone/aza-isoindolinone derivatives by comparative molecular field analysis (CoMFA). Mol Divers 2017; 21:821-830. [PMID: 28836075 DOI: 10.1007/s11030-017-9778-z] [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: 02/19/2017] [Accepted: 08/02/2017] [Indexed: 12/18/2022]
Abstract
In current study, antitumor activity of two series of the newly synthesized spiropyrroloquinoline isoindolinone and spiropyrroloquinoline aza-isoindolinone scaffolds was evaluated against three human breast normal and cancer cell lines (MCF-10A, MCF-7 and SK-BR-3) and compared with cytotoxicity values of doxorubicin and colchicine as the standard drugs. It was found that several compounds were endowed with cytotoxicity in the low micromolar range. Among these two series, compounds 6i, 6j, 6k and 7l, 7m, 7n, 7o containing 3-ethyl-1H-indole moiety were found to be highly effective against both cancer cell lines ranging from [Formula: see text] to [Formula: see text] in comparison with the corresponding analogs. Compared with human cancer cells, the most potent compounds did not show high cytotoxicity against human breast normal MCF-10A cells. Generally, most of the evaluated compounds 6a-l and 7a-o series showed more antitumor activity against SK-BR-3 than MCF-7 cells. Moreover, comparative molecular field analysis (CoMFA) as a popular tools of three-dimensional quantitative structure-activity relationship (3D-QSAR) studies was carried out on 27 spiropyrroloquinolineisoindolinone and spiropyrroloquinolineaza-isoindolinone derivatives with antitumor activity against on SK-BR-3 cells. The obtained CoMFA models showed statistically excellent performance, which also possessed good predictive ability for an external test set. The results confirm the important effect of molecular steric and electrostatic interactions of these compounds on in vitro cytotoxicity against SK-BR-3.
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Affiliation(s)
- Masoud Sadeghzadeh
- Radiation Application Research School, Nuclear Science and Technology Research Institute, AEOI, P.O. Box 11365-3486, Tehran, Iran.
| | - Maryam Salahinejad
- Radiation Application Research School, Nuclear Science and Technology Research Institute, AEOI, P.O. Box 11365-3486, Tehran, Iran
| | - Nahid Zarezadeh
- School of Chemistry, College of Science, University of Tehran, P.O. Box 14155 6455, Tehran, Iran
| | - Mehdi Ghandi
- School of Chemistry, College of Science, University of Tehran, P.O. Box 14155 6455, Tehran, Iran
| | - Maryam Keshavarz Baghery
- Radiation Application Research School, Nuclear Science and Technology Research Institute, AEOI, P.O. Box 11365-3486, Tehran, Iran
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15
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Combined HQSAR, topomer CoMFA, homology modeling and docking studies on triazole derivatives as SGLT2 inhibitors. Future Med Chem 2017. [DOI: 10.4155/fmc-2017-0002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Aim: Sodium–glucose cotransporter 2 (SGLT2) is a promising target for diabetes therapy. We aimed to develop computational approaches to identify structural features for more potential SGLT2 inhibitors. Materials & methods: In this work, 46 triazole derivatives as SGLT2 inhibitors were studied using a combination of several approaches, including hologram quantitative structure–activity relationships (HQSAR), topomer comparative molecular field analysis (CoMFA), homology modeling, and molecular docking. HQSAR and topomer CoMFA were used to construct models. Molecular docking was conducted to investigate the interaction of triazole derivatives and homology modeling of SGLT2, as well as to validate the results of the HQSAR and topomer CoMFA models. Results: The most effective HQSAR and topomer CoMFA models exhibited noncross-validated correlation coefficients of 0.928 and 0.891 for the training set, respectively. External predictions were made successfully on a test set and then compared with previously reported models. The graphical results of HQSAR and topomer CoMFA were proven to be consistent with the binding mode of the inhibitors and SGLT2 from molecular docking. Conclusion: The models and docking provided important insights into the design of potent inhibitors for SGLT2.
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16
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Kristam R, Rao SN, D’Cruz AS, Mahadevan V, Viswanadhan VN. TRPV1 antagonism by piperazinyl-aryl compounds: A Topomer-CoMFA study and its use in virtual screening for identification of novel antagonists. J Mol Graph Model 2017. [DOI: 10.1016/j.jmgm.2017.01.010 pmid: 28092830] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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17
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Kristam R, Rao SN, D'Cruz AS, Mahadevan V, Viswanadhan VN. TRPV1 antagonism by piperazinyl-aryl compounds: A Topomer-CoMFA study and its use in virtual screening for identification of novel antagonists. J Mol Graph Model 2017; 72:112-128. [PMID: 28092830 DOI: 10.1016/j.jmgm.2017.01.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2016] [Revised: 12/08/2016] [Accepted: 01/06/2017] [Indexed: 11/25/2022]
Abstract
Transient Receptor Potential Vanilloid, member 1 (TRPV1), is a non-selective cation channel belonging to the transient receptor potential (TRP) family of ion channels. It occurs in the peripheral and central nervous system, activated by a variety of exogenous and endogenous stimuli, thus playing a key role in transmission of pain. This has been a target for chronic pain since more than a decade and a number of antagonists that progressed into clinical trials have failed due to the unexpected side effect of core body temperature rise, thus halting progress in this field. Of late, there has been an upsurge in research on this target, with the rat TRPV1 structure being determined, many new antagonists discovered that are temperature-neutral and many new therapeutic avenues being discovered for TRPV1, including diseases of respiratory and digestive systems, skin and bladder. Towards identifying diverse compounds to decipher the role of this target in various indications, here we report a 3D-QSAR model built using the new topomer-CoMFA methodology on a series of piperazinyl-aryl TRPV1 antagonists and the use of this model, along with a pharmacophore model and the shape of one of the potent compounds of this series, to virtually screen a subset of the ZINC database to find novel and diverse hits. These can serve as starting points to develop modality-selective antagonists for chronic pain and to elucidate the critical role of TRPV1 in the various new therapeutic areas.
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Affiliation(s)
- Rajendra Kristam
- Department of Computational Chemistry, Jubilant Biosys Ltd. #96, Industrial Suburb, 2nd Stage, Yeshwanthpur, Bangalore 560 064, India; School of Chemical & Biotechnology, Shanmugha Arts, Science, Technology, and Research Academy (SASTRA University), Thanjavur, Tamil Nadu 613 402, India.
| | - Shashidhar N Rao
- Tripos International, A Certara Company, St. Louis, MO 63101, USA
| | - Anne Sudha D'Cruz
- Department of Computational Chemistry, Jubilant Biosys Ltd. #96, Industrial Suburb, 2nd Stage, Yeshwanthpur, Bangalore 560 064, India
| | - Vijayalakshmi Mahadevan
- School of Chemical & Biotechnology, Shanmugha Arts, Science, Technology, and Research Academy (SASTRA University), Thanjavur, Tamil Nadu 613 402, India
| | - Vellarkad N Viswanadhan
- Department of Computational Chemistry, Jubilant Biosys Ltd. #96, Industrial Suburb, 2nd Stage, Yeshwanthpur, Bangalore 560 064, India
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Tong JB, Bai M, Zhao X. 3D-QSAR and docking studies of HIV-1 protease inhibitors using R-group search and Surflex-dock. Med Chem Res 2016. [DOI: 10.1007/s00044-016-1701-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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19
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Xu C, Ren Y. Molecular modeling studies of [6,6,5] Tricyclic Fused Oxazolidinones as FXa inhibitors using 3D-QSAR, Topomer CoMFA, molecular docking and molecular dynamics simulations. Bioorg Med Chem Lett 2015; 25:4522-8. [PMID: 26343829 DOI: 10.1016/j.bmcl.2015.08.070] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2015] [Revised: 08/22/2015] [Accepted: 08/26/2015] [Indexed: 10/23/2022]
Abstract
Coagulation factor Xa (Factor Xa, FXa) is a particularly promising target for novel anticoagulant therapy. The first oral factor Xa inhibitor has been approved in the EU and Canada in 2008. In this work, 38 [6,6,5] Tricyclic Fused Oxazolidinones were studied using a combination of molecular modeling techniques including three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, molecular dynamics and Topomer CoMFA (comparative molecular field analysis) were used to build 3D-QSAR models. The results show that the best CoMFA model has q(2)=0.511 and r(2)=0.984, the best CoMSIA (comparative molecular similarity indices analysis) model has q(2)=0.700 and r(2)=0.993 and the Topomer CoMFA analysis has q(2)=0.377 and r(2)=0.886. The results indicated the steric, hydrophobic, H-acceptor and electrostatic fields play key roles in models. Molecular docking and molecular dynamics explored the binding relationship of the ligand and the receptor protein.
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Affiliation(s)
- Cheng Xu
- School of Chemical and Environmental Engineering, Shanghai Institute of Technology, Shanghai 201418, China
| | - Yujie Ren
- School of Chemical and Environmental Engineering, Shanghai Institute of Technology, Shanghai 201418, China.
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20
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Kumar S, Tiwari M. Topomer-CoMFA-based predictive modelling on 2,3-diaryl-substituted-1,3-thiazolidin-4-ones as non-nucleoside reverse transcriptase inhibitors. Med Chem Res 2014. [DOI: 10.1007/s00044-014-1105-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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21
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Cherkasov A, Muratov EN, Fourches D, Varnek A, Baskin II, Cronin M, Dearden J, Gramatica P, Martin YC, Todeschini R, Consonni V, Kuz'min VE, Cramer R, Benigni R, Yang C, Rathman J, Terfloth L, Gasteiger J, Richard A, Tropsha A. QSAR modeling: where have you been? Where are you going to? J Med Chem 2014; 57:4977-5010. [PMID: 24351051 PMCID: PMC4074254 DOI: 10.1021/jm4004285] [Citation(s) in RCA: 1036] [Impact Index Per Article: 103.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making.
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Affiliation(s)
- Artem Cherkasov
- Vancouver Prostate Centre, University of British Columbia, Vancouver, BC, V6H3Z6, Canada
| | - Eugene N. Muratov
- Laboratory for Molecular Modeling, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA
- Department of Molecular Structure and Cheminformatics, A.V. Bogatsky Physical-Chemical Institute National Academy of Sciences of Ukraine, Odessa, 65080, Ukraine
| | - Denis Fourches
- Laboratory for Molecular Modeling, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Alexandre Varnek
- Department of Chemistry, L. Pasteur University of Strasbourg, Strasbourg, 67000, France
| | - Igor I. Baskin
- Department of Physics, Lomonosov Moscow State University, Moscow, 119991, Russia
| | - Mark Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool L33AF, UK
| | - John Dearden
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool L33AF, UK
| | - Paola Gramatica
- Department of Structural and Functional Biology, University of Insubria, Varese, 21100, Italy
| | | | - Roberto Todeschini
- Milano Chemometrics and QSAR Research Group, University of Milano-Bicocca, Milan, 20126, Italy
| | - Viviana Consonni
- Milano Chemometrics and QSAR Research Group, University of Milano-Bicocca, Milan, 20126, Italy
| | - Victor E. Kuz'min
- Department of Molecular Structure and Cheminformatics, A.V. Bogatsky Physical-Chemical Institute National Academy of Sciences of Ukraine, Odessa, 65080, Ukraine
| | | | - Romualdo Benigni
- Environment and Health Department, Istituto Superiore di Sanita’, Rome, 00161, Italy
| | | | - James Rathman
- Altamira LLC, Columbus OH 43235, USA
- Department of Chemical and Biomolecular Engineering, the Ohio State University, Columbus, OH 43215, USA
| | | | | | - Ann Richard
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27519, USA
| | - Alexander Tropsha
- Laboratory for Molecular Modeling, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA
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22
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Tian Y, Shen Y, Zhang X, Ye L, Li Z, Liu Z, Zhang J, Wu S. Design Some New Type-I c-met Inhibitors Based on Molecular Docking and Topomer CoMFA Research. Mol Inform 2014; 33:536-43. [PMID: 27486039 DOI: 10.1002/minf.201300118] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2013] [Accepted: 01/07/2014] [Indexed: 11/08/2022]
Abstract
In this paper, a specific design strategy targeting c-met kinase was reported based on docking modeling and topomer comparative molecular field analysis (Topomer CoMFA). A novel U-shape conformation which is distinct from the literature was demonstrated by molecular docking among 68 U-shape c-met inhibitors. According to the docking results, two Topomer CoMFA models with high predictive ability were established based on the two fragment rule. The results from both docking and topomer CoMFA showed that the π-π stacking interaction with Tyr1230 and the hydrogen bond with hinge region play an important role in inhibitory activity. Furthermore, the flexible linker and the adjacent solvent group would be favorable to stabilize the conformation and to enhance the two interactions mentioned above. Based on our patent, 14 new compounds were designed by our design strategy. The binding mode exhibited as expected and their activities were predicted by topomer CoMFA model. The preliminary biological tests showed most of them have potent activity to c-met kinase. Our study would provide guidelines to design some new U-shaped c-met inhibitors with new scaffolds and optimize the current molecules.
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Affiliation(s)
- Yuanxin Tian
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, P. R. China
| | - Yudong Shen
- Guangdong Provincial Key Laboratory of Food Quality and Safety, South China Agricultural University, Guangzhou 510642, P. R. China
| | - Xianzuo Zhang
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, P. R. China
| | - Lianbao Ye
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, P. R. China
| | - Zhonghuang Li
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, P. R. China
| | - Zhong Liu
- Guangzhou Jinan Biomedicine Research and Development Center, Guangdong Provincial Key Laboratory of Bioengineering Medicine, Jinan University, Guangzhou, 510632, P. R. China
| | - Jiajie Zhang
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, P. R. China.
| | - Shuguang Wu
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, P. R. China.
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Abstract
Template CoMFA, a novel alignment methodology for training or test set structures in 3D-QSAR, is introduced. Its two most significant advantages are its complete automation and its ability to derive a single combined model from multiple structural series affecting a biological target. Its only two inputs are one or more "template" structures having 3D coordinates that share some Cartesian space, as may result from X-ray crystallography or pharmacophoric hypothesis, and one or more connectivity-only SAR tables associated with a common target. Template CoMFA also overcomes the major disadvantages of both existing 3D-QSAR alignment methodologies, specifically the tedium and subjectivity of familiar ad hoc approaches, and the awkwardness, occasional physicochemical heresies, and structural scope limitations of the purely topomer approach. The template CoMFA algorithms are described, and two of its application classes are presented. The first class, general models of binding to factor Xa and P38 map kinase, uses crystallographic structures as templates, with the encouraging result that the statistical qualities of each of these two combined models are equivalent to those of their constituent individual series models. The second, 15 data sets originally collected for validation of topomer CoMFA, with arbitrary structures as templates, confirms that the modeling power of template CoMFA resembles that of its predecessors.
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24
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Urniaż RD, Jóźwiak K. X-ray crystallographic structures as a source of ligand alignment in 3D-QSAR. J Chem Inf Model 2013; 53:1406-14. [PMID: 23705769 DOI: 10.1021/ci400004e] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Three-dimensional quantitative structure-activity relationships (3D-QSAR) analyses are methods correlating a pharmacological property with a mathematical representation of a molecular property distribution around three-dimensional molecular models for a set of congeners. 3D-QSAR methods are known to be highly sensitive to ligand conformation and alignment method. The current study collects 32 unique positions of congeneric ligands co-crystallized with the binding domain of AMPA receptors and aligns them using protein coordinates. Thus, it allows for a unique opportunity to consider a ligands' orientation aligned by their mode of binding in a native molecular target. Comparative molecular field analysis (CoMFA) models were generated for this alignment and compared with the results of analogous modeling using standard structure-based alignment or obtained in docking simulations of the ligands' molecules. In comparison with classically derived models, the model based on X-ray crystallographic studies showed much better performance and statistical significance. Although the 3D-QSAR methods are mainly employed when crystallographic information is limited, the current study underscores the importance that the selection of inappropriate molecular conformations and alignment methods can lead to generation of erroneous models and false conclusions.
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Affiliation(s)
- Rafał D Urniaż
- Medical University of Lublin, Laboratory of Medicinal Chemistry and Neuroengineering, Chodźki 4a Street, 20-093 Lublin, Poland
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25
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R-group template CoMFA combines benefits of "ad hoc" and topomer alignments using 3D-QSAR for lead optimization. J Comput Aided Mol Des 2012; 26:805-19. [PMID: 22661224 DOI: 10.1007/s10822-012-9583-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2012] [Accepted: 05/14/2012] [Indexed: 10/28/2022]
Abstract
Template CoMFA methodologies extend topomer CoMFA by allowing user-designated templates, for example the experimental receptor-bound conformation of a prototypical ligand, to help determine the alignment of training and test set structures for 3D-QSAR. The algorithms that generate its new structural modality, template-constrained topomers, are described. Template CoMFA's resolution of certain topomer CoMFA concerns, by providing user control of topological consistency and structural acceptability, is demonstrated for sixteen 3D-QSAR training sets, in particular the Selwood dataset.
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26
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Sun J, Mei H. Docking and 3D-QSAR investigations of pyrrolidine derivatives as potent neuraminidase inhibitors. Chem Biol Drug Des 2012; 79:863-8. [DOI: 10.1111/j.1747-0285.2012.01330.x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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27
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Abstract
QSAR approaches, including recent advances in 3D-QSAR, are advantageous during the lead optimization phase of drug discovery and complementary with bioinformatics and growing data accessibility. Hints for future QSAR practitioners are also offered.
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28
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Schnur DM, Beno BR, Tebben AJ, Cavallaro C. Methods for combinatorial and parallel library design. Methods Mol Biol 2011; 672:387-434. [PMID: 20838978 DOI: 10.1007/978-1-60761-839-3_16] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
Diversity has historically played a critical role in design of combinatorial libraries, screening sets and corporate collections for lead discovery. Large library design dominated the field in the 1990s with methods ranging anywhere from purely arbitrary through property based reagent selection to product based approaches. In recent years, however, there has been a downward trend in library size. This was due to increased information about the desirable targets gleaned from the genomics revolution and to the ever growing availability of target protein structures from crystallography and homology modeling. Creation of libraries directed toward families of receptors such as GPCRs, kinases, nuclear hormone receptors, proteases, etc., replaced the generation of libraries based primarily on diversity while single target focused library design has remained an important objective. Concurrently, computing grids and cpu clusters have facilitated the development of structure based tools that screen hundreds of thousands of molecules. Smaller "smarter" combinatorial and focused parallel libraries replaced those early un-focused large libraries in the twenty-first century drug design paradigm. While diversity still plays a role in lead discovery, the focus of current library design methods has shifted to receptor based methods, scaffold hopping/bio-isostere searching, and a much needed emphasis on synthetic feasibility. Methods such as "privileged substructures based design" and pharmacophore based design still are important methods for parallel and small combinatorial library design. This chapter discusses some of the possible design methods and presents examples where they are available.
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Affiliation(s)
- Dora M Schnur
- Computer Aided Drug Design, Pharmaceutical Research Institute, Bristol-Myers Squibb Company, Princeton, NJ, USA
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29
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Computational medicinal chemistry in fragment-based drug discovery: what, how and when. Future Med Chem 2011; 3:95-134. [DOI: 10.4155/fmc.10.277] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
The use of fragment-based drug discovery (FBDD) has increased in the last decade due to the encouraging results obtained to date. In this scenario, computational approaches, together with experimental information, play an important role to guide and speed up the process. By default, FBDD is generally considered as a constructive approach. However, such additive behavior is not always present, therefore, simple fragment maturation will not always deliver the expected results. In this review, computational approaches utilized in FBDD are reported together with real case studies, where applicability domains are exemplified, in order to analyze them, and then, maximize their performance and reliability. Thus, a proper use of these computational tools can minimize misleading conclusions, keeping the credit on FBDD strategy, as well as achieve higher impact in the drug-discovery process. FBDD goes one step beyond a simple constructive approach. A broad set of computational tools: docking, R group quantitative structure–activity relationship, fragmentation tools, fragments management tools, patents analysis and fragment-hopping, for example, can be utilized in FBDD, providing a clear positive impact if they are utilized in the proper scenario – what, how and when. An initial assessment of additive/non-additive behavior is a critical point to define the most convenient approach for fragments elaboration.
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30
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Abstract
The average error of pIC50 prediction reported for 140 structures in make-and-test applications of topomer CoMFA by four discovery organizations is 0.5. This remarkable accuracy can be understood to result from a topomer pose’s goal of generating field differences only at lattice intersections adjacent to intended structural change.
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31
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Yang SH, Van HTM, Le TN, Khadka DB, Cho SH, Lee KT, Lee ES, Lee YB, Ahn CH, Cho WJ. Development of 3-aryl-1-isoquinolinamines as potent antitumor agents based on CoMFA. Eur J Med Chem 2010; 45:5493-7. [DOI: 10.1016/j.ejmech.2010.08.042] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2010] [Revised: 08/03/2010] [Accepted: 08/17/2010] [Indexed: 11/26/2022]
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32
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Myint KZ, Xie XQ. Recent advances in fragment-based QSAR and multi-dimensional QSAR methods. Int J Mol Sci 2010; 11:3846-66. [PMID: 21152304 PMCID: PMC2996787 DOI: 10.3390/ijms11103846] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2010] [Revised: 09/17/2010] [Accepted: 09/23/2010] [Indexed: 12/13/2022] Open
Abstract
This paper provides an overview of recently developed two dimensional (2D) fragment-based QSAR methods as well as other multi-dimensional approaches. In particular, we present recent fragment-based QSAR methods such as fragment-similarity-based QSAR (FS-QSAR), fragment-based QSAR (FB-QSAR), Hologram QSAR (HQSAR), and top priority fragment QSAR in addition to 3D- and nD-QSAR methods such as comparative molecular field analysis (CoMFA), comparative molecular similarity analysis (CoMSIA), Topomer CoMFA, self-organizing molecular field analysis (SOMFA), comparative molecular moment analysis (COMMA), autocorrelation of molecular surfaces properties (AMSP), weighted holistic invariant molecular (WHIM) descriptor-based QSAR (WHIM), grid-independent descriptors (GRIND)-based QSAR, 4D-QSAR, 5D-QSAR and 6D-QSAR methods.
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Affiliation(s)
- Kyaw Zeyar Myint
- Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; E-Mail:
| | - Xiang-Qun Xie
- Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; E-Mail:
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Pittsburgh Chemical Methodologies & Library Development (PCMLD) and Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
- * Author to whom correspondence should be addressed; E-Mail: ; Tel.: +1-412-383-5276; Fax: +1-412-383-7436
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Abstract
3D ligand-based similarity approaches are widely used in the early phases of drug discovery for tasks such as hit finding by virtual screening or compound design with quantitative structure–activity relationships. Here in we review widely used software for performing such tasks. Some techniques are based on relatively mature technology, shape-based similarity for instance. Typically, these methods remained in the realm of the expert user, the experienced modeler. However, advances in implementation and speed have improved usability and allow these methods to be applied to databases comprising millions of compounds. There are now many reports of such methods impacting drug-discovery projects. As such, the medicinal chemistry community has become the intended market for some of these new tools, yet they may consider the wide array and choice of approaches somewhat disconcerting. Each method has subtle differences and is better suited to certain tasks than others. In this article we review some of the widely used computational methods via application, provide straightforward background on the underlying theory and provide examples for the interested reader to pursue in more detail. In the new era of preclinical drug discovery there will be ever more pressure to move faster and more efficiently, and computational approaches based on 3D ligand similarity will play an increasing role in in this process.
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34
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Cramer RD. Tautomers and topomers: challenging the uncertainties of direct physicochemical modeling. J Comput Aided Mol Des 2010; 24:617-20. [DOI: 10.1007/s10822-010-9330-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2010] [Accepted: 03/10/2010] [Indexed: 11/24/2022]
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35
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Herman Skolnik award symposium honoring Yvonne Martin. J Comput Aided Mol Des 2009; 23:831-6. [DOI: 10.1007/s10822-009-9310-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2009] [Accepted: 11/17/2009] [Indexed: 11/25/2022]
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