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Shayanfar S, Shayanfar A. Comparison of various methods for validity evaluation of QSAR models. BMC Chem 2022; 16:63. [PMID: 35999611 PMCID: PMC9396839 DOI: 10.1186/s13065-022-00856-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Quantitative structure-activity relationship (QSAR) modeling is one of the most important computational tools employed in drug discovery and development. The external validation of QSAR models is the main point to check the reliability of developed models for the prediction activity of not yet synthesized compounds. It was performed by different criteria in the literature. METHODS In this study, 44 reported QSAR models for biologically active compounds reported in scientific papers were collected. Various statistical parameters of external validation of a QSAR model were calculated, and the results were discussed. RESULTS The findings revealed that employing the coefficient of determination (r2) alone could not indicate the validity of a QSAR model. The established criteria for external validation have some advantages and disadvantages which should be considered in QSAR studies. CONCLUSION This study showed that these methods alone are not only enough to indicate the validity/invalidity of a QSAR model.
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Affiliation(s)
- Shadi Shayanfar
- Student Research Committee, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Ali Shayanfar
- Pharmaceutical Analysis Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. .,Editorial Office of Pharmaceutical Sciences Journal, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.
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Hu Z, Lin Q, Liu H, Zhao T, Yang B, Tu G. Molecular dynamics-guided receptor-dependent 4D-QSAR studies of HDACs inhibitors. Mol Divers 2021; 26:757-768. [PMID: 33625673 DOI: 10.1007/s11030-021-10181-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 01/03/2021] [Indexed: 11/29/2022]
Abstract
Histone deacetylases (HDACs) were highlighted as a novel category of anticancer targets. Several HDACs inhibitors were approved for therapeutic use in cancer treatment. Comparatively, receptor-dependent 4D-QSAR, LQTA-QSAR, is a new approach which generates conformational ensemble profiles of compounds by molecular dynamics simulations at binding site of enzyme. This work describes a receptor-dependent 4D-QSAR studies on hydroxamate-based HDACs inhibitors. The 4D-QSAR model was generated by multiple linear regression method of QSARINS. Leave-N-out cross-validation (LNO) and Y-randomization were performed to analysis of the independent test set and to verify the robustness of the model. Best 4D-QSAR model showed the following statistics: R2 = 0.8117, Q2LOO = 0.6881, Q2LNO = 0.6830, R2Pred = 0.884. The results may be used for further virtual screening and design for novel HDACs inhibitors. The receptor dependent 4D-QSAR model was developed for the hydroxamate derivatives as HDAC inhibitors by making use of molecular dynamics simulation to obtain conformational ensemble profile for each compound. The multiple linear regression method was used to generate 4D-QSAR model with the suitable predictive ability and the excellent statistical parameters.
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Affiliation(s)
- Zhihao Hu
- Department of Medicinal Chemistry, School of Pharmaceutical Science, NanChang University, Nanchang, 330006, China
| | - Qianxia Lin
- Jiangxi University of Traditional Chinese Medicine, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Haiyun Liu
- Jiangxi University of Traditional Chinese Medicine, Nanchang, 330006, Jiangxi, People's Republic of China
| | - Tiansheng Zhao
- Department of Medicinal Chemistry, School of Pharmaceutical Science, NanChang University, Nanchang, 330006, China
| | - Bowen Yang
- Department of Medicinal Chemistry, School of Pharmaceutical Science, NanChang University, Nanchang, 330006, China
| | - Guogang Tu
- Department of Medicinal Chemistry, School of Pharmaceutical Science, NanChang University, Nanchang, 330006, China.
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Zambre VP, Khamkar SM, Gavhane DD, Khedkar SC, Chavan MR, Pandey MM, Sanap SB, Patil RB, Sawant SD. Patent landscape for discovery of promising acyltransferase DGAT and MGAT inhibitors. Expert Opin Ther Pat 2020; 30:873-896. [PMID: 32878484 DOI: 10.1080/13543776.2020.1815707] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION DGAT and MGAT enzymes play an important role in triacylglycerol (TGA) biosynthesis. Overexpression of these enzymes may lead to accumulation of TGA in adipose tissues causing development of diseases such as obesity and diabetes. High triglyceride levels increase risk factors for atherosclerosis, and increase the risk of heart attack, stroke and other heart diseases. DGAT and MGAT inhibitors are used for the treatment of such metabolic diseases. A number of DGAT and MGAT inhibitors entered into clinical and preclinical stages. However, some adverse effects are associated with them. Thus there is need to develop new, potent and safe DGAT and MGAT inhibitors. AREA COVERED In this review, the authors carefully searched patent literature and reviewed recent advances since the year 2014. Diverse chemical classes reported in the patents belonging to the category DGAT and MGAT inhibitors have been highlighted. EXPERT OPINION DGAT and MGAT inhibitors are now gaining significant importance in the treatment of metabolic diseases. Fused heterocycles with a combination of aromatic and aliphatic hydrophobic substituents could offer more potent DGAT and MGAT inhibitors. Previously reported chemical scaffolds and their DGAT and MGAT inhibitory activity could be employed as an input for some in silico studies to discover novel, potent and safe DGAT and MGAT inhibitors.
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Affiliation(s)
- Vishal P Zambre
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
| | - Shamali M Khamkar
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
| | - Dnyaneshwar D Gavhane
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
| | - Sagar C Khedkar
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
| | - Monali R Chavan
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
| | - Madhuri M Pandey
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
| | - Sonali B Sanap
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
| | - Rajesh B Patil
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
| | - Sanjay D Sawant
- Department of Pharmaceutical Chemistry, Smt. Kashibai Navale College of Pharmacy, Savitribai Phule Pune University , Pune, India
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Zhu T, Yan H, Singh RP, Wang Y, Cheng H. QSPR study on the polyacrylate-water partition coefficients of hydrophobic organic compounds. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2020; 27:17550-17560. [PMID: 31493082 DOI: 10.1007/s11356-019-06389-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 08/30/2019] [Indexed: 06/10/2023]
Abstract
The partition coefficient is essential for the analysis of organic chemicals using solid-phase microextraction (SPME) techniques. In this study, a quantitative structure-property relationship (QSPR) model was developed with chemical descriptors for the prediction of the polyacrylate (PA)-water partition coefficient (KPA-w). The major variables influencing KPA-w in the QSPR model were CrippenlogP (crippen octanal-water partition coefficient), RNCG (relative negative charge-most negative charge/total negative charge), VE2_Dzv (average coefficient sum of the last eigenvector from the Barysz matrix/weighted by van der Waals volume), and ATSC4v (centred Broto-Moreau autocorrelation-lag 4/weighted by van der Waals volume). The relative determination coefficient (R2) and cross-validation coefficient (Q2) were 0.898 and 0.858, respectively, which implied that the model had excellent robustness. Mechanistic interpretation suggested that the factors affecting the partitioning process between PA and water are the hydrophobicity, relative negative charge, and van der Waals volume of a chemical. The results of this study provide a good tool for predicting the log KPA-w values of diverse hydrophobic organic compounds (HOCs) within the applicability domain to reduce experimental costs and the time required for innovation.
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Affiliation(s)
- Tengyi Zhu
- Jiangsu Provincial Laboratory of Water Environmental Protection Engineering, School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 225127, Jiangsu, China.
| | - Heting Yan
- Jiangsu Provincial Laboratory of Water Environmental Protection Engineering, School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 225127, Jiangsu, China
| | | | - Yajun Wang
- School of Civil Engineering, Southeast University, Nanjing, 210096, China
| | - Haomiao Cheng
- Jiangsu Provincial Laboratory of Water Environmental Protection Engineering, School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 225127, Jiangsu, China.
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Zhu T, Jiang Y, Cheng H, Singh RP, Yan B. Development of pp-LFER and QSPR models for predicting the diffusion coefficients of hydrophobic organic compounds in LDPE. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2020; 190:110179. [PMID: 31927194 DOI: 10.1016/j.ecoenv.2020.110179] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Revised: 12/31/2019] [Accepted: 01/05/2020] [Indexed: 06/10/2023]
Abstract
Diffusion coefficient (D) is important to evaluate the performance of passive samplers and to monitor the concentration of chemicals effectively. Herein, we developed a polyparameter linear free energy relationship (pp-LFER) model and a quantitative structure-property relationship (QSPR) model for the prediction of diffusion coefficients of hydrophobic organic contaminants (HOCs) in low density polyethylene (LDPE). A dataset of 120 various chemicals was used to develop both models. The pp-LFER model was developed with two descriptors (V and E) and the statistical parameters of the model showed satisfactory results. As a further exploration of the diffusion behavior of the compounds, a QSPR model with five descriptors (ETA_Alpha, ASP-6, IC1, TDB6r and ATSC2v) was constructed with adjusted determination coefficient (R2) of 0.949 and cross-validation coefficient (QLoo2) of 0.941. The regression results indicated that both models had satisfactory goodness-of-fit and robustness. This study proves that pp-LFER and QSPR approaches are available for the prediction of log D values for the hydrophobic organic compounds within the applicability domain.
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Affiliation(s)
- Tengyi Zhu
- Jiangsu Provincial Laboratory of Water Environmental Protection Engineering, School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 225127, Jiangsu, China
| | - Yue Jiang
- Jiangsu Provincial Laboratory of Water Environmental Protection Engineering, School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 225127, Jiangsu, China
| | - Haomiao Cheng
- Jiangsu Provincial Laboratory of Water Environmental Protection Engineering, School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 225127, Jiangsu, China
| | | | - Bipeng Yan
- Jiangsu Provincial Laboratory of Water Environmental Protection Engineering, School of Environmental Science and Engineering, Yangzhou University, Yangzhou, 225127, Jiangsu, China.
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Stitou M, Toufik H, Bouachrine M, Lamchouri F. Quantitative structure–activity relationships analysis, homology modeling, docking and molecular dynamics studies of triterpenoid saponins as Kirsten rat sarcoma inhibitors. J Biomol Struct Dyn 2020; 39:152-170. [DOI: 10.1080/07391102.2019.1707122] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Mourad Stitou
- Materials, Natural Substances, Environment and Modeling Laboratory (LMSNEM), Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University of Fez, Taza, Morocco
| | - Hamid Toufik
- Materials, Natural Substances, Environment and Modeling Laboratory (LMSNEM), Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University of Fez, Taza, Morocco
| | - Mohammed Bouachrine
- Materials, Natural Substances, Environment and Modeling Laboratory (LMSNEM), Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University of Fez, Taza, Morocco
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail of Meknes, Meknes, Morocco
| | - Fatima Lamchouri
- Materials, Natural Substances, Environment and Modeling Laboratory (LMSNEM), Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University of Fez, Taza, Morocco
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Miranda PHDS, Lourenço EMG, Morais AMS, de Oliveira PIC, Silverio PSDSN, Jordão AK, Barbosa EG. Molecular modeling of a series of dehydroquinate dehydratase type II inhibitors of Mycobacterium tuberculosis and design of new binders. Mol Divers 2019; 25:1-12. [PMID: 31820222 DOI: 10.1007/s11030-019-10020-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 11/22/2019] [Indexed: 11/24/2022]
Abstract
Tuberculosis, caused by Mycobacterium tuberculosis (M. tuberculosis), is still responsible for a large number of fatal cases, especially in developing countries with alarming rates of incidence and prevalence worldwide. Mycobacterium tuberculosis has a remarkable ability to develop new resistance mechanisms to the conventional antimicrobials treatment. Because of this, there is an urgent need for novel bioactive compounds for its treatment. The dehydroquinate dehydratase II (DHQase II) is considered a key enzyme of shikimate pathway, and it can be used as a promising target for the design of new bioactive compounds with antibacterial action. The aim of this work was the construction of QSAR models to aid the design of new potential DHQase II inhibitors. For that purpose, various molecular modeling approaches, such as activity cliff, QSAR models and computer-aided ligand design were utilized. A predictive in silico 4D-QSAR model was built using a database comprising 86 inhibitors of DHQase II, and the model was used to predict the activity of the designed ligands. The obtained model proved to predict well the DHQase II inhibition for an external validation dataset ([Formula: see text] = 0.72). Also, the Activity Cliff analysis shed light on important structural features applied to the ligand design.
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Affiliation(s)
- Paulo H de S Miranda
- Departamento de Farmácia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | - Estela M G Lourenço
- Departamento de Farmácia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | - Alexander M S Morais
- Departamento de Farmácia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | - Pedro I C de Oliveira
- Programa de Pós-Graduação em Bioinformática, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | | | - Alessandro K Jordão
- Departamento de Farmácia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | - Euzébio G Barbosa
- Departamento de Farmácia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil. .,Programa de Pós-Graduação em Bioinformática, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil.
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Kumar P, Kumar A, Sindhu J. In silico design of diacylglycerol acyltransferase-1 (DGAT1) inhibitors based on SMILES descriptors using Monte-Carlo method. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2019; 30:525-541. [PMID: 31331203 DOI: 10.1080/1062936x.2019.1629998] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 06/06/2019] [Indexed: 06/10/2023]
Abstract
Diabetes, obesity and other diseases related to metabolism are worldwide health problems. These syndromes can be well treated when a particular enzyme-based therapy is developed. Diacylglycerol acyltransferase (DGAT; EC 2.3.1.20) is a microsomal enzyme which is responsible for the synthesis of triglycerides from 1,2-diacylglycerol by catalyzing the acyl-CoA-dependent acylation. The obesity and type-II diabetes can be checked by the inhibition of DGAT1 enzyme. Quantitative structure-activity relationship (QSAR) modelling is an essential technique in drug design and development. To study the aspect of DGAT1 inhibitors, Monte-Carlo method-based QSAR was developed for 197 DGAT1 inhibitors. QSAR models were derived by using the optimal descriptor based on SMILES notation. Different statistical parameters including the novel index of ideality of correlation were applied to validate the generated QSAR models. Four random splits were prepared from the data set. The statistical criteria r2 = 0.8129, CCC = 0.8979 and Q2 = 0.7962 of the validation set of split 1 were the best; therefore, the developed QSAR model of split 1 was decided to be the leading model. The molecular fragments, which were promoter of endpoint increase or decrease were also determined. Thirteen new DGAT1 inhibitors were designed from the lead compound DGAT011.
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Affiliation(s)
- P Kumar
- Department of Chemistry, Kurukshetra University , Kurukshetra , India
| | - A Kumar
- Department of Pharmaceutical Sciences, Guru Jambheshwar University of Science and Technology , Hisar , India
| | - J Sindhu
- Department of Chemsitry, COBS&H CCS Haryana Agriculture University , Hisar , India
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Erratum to "LQTA-R: A new 3D-QSAR methodology applied to a set of DGAT1 inhibitors" [Computat. Biol. Chem. 74 (2018) 123-131]. Comput Biol Chem 2018; 78:8. [PMID: 30476707 DOI: 10.1016/j.compbiolchem.2018.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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