1
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Hang NT, My TTK, Van Anh LT, Van Anh PT, Anh TDH, Van Phuong N. Identification of potential FAK inhibitors using mol2vec molecular descriptor-based QSAR, molecular docking, ADMET study, and molecular dynamics simulation. Mol Divers 2024:10.1007/s11030-024-10839-3. [PMID: 38582821 DOI: 10.1007/s11030-024-10839-3] [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: 11/05/2023] [Accepted: 03/07/2024] [Indexed: 04/08/2024]
Abstract
This study aims to identify potential focal adhesion kinase (FAK) inhibitors through an integrated computational approach, combining mol2vec descriptor-based QSAR, molecular docking, ADMET study, and molecular dynamics simulation. A dataset of 437 compounds with known FAK inhibitory activities was used to develop QSAR models using machine learning algorithms combined with mol2vec descriptors. Subsequently, the most promising compounds were subjected to molecular docking against FAK to evaluate their binding affinities and key interactions. ADMET study and molecular dynamics simulation were also employed to investigate the pharmacokinetic, drug-like properties, and the stability of the protein-ligand complexes. The results showed that the mol2vec descriptor-based QSAR model established by support vector regression demonstrated good predictive performance (R2 = 0.813, RMSE = 0.453, MAE = 0.263 in case of training set, and R2 = 0.729, RMSE = 0.635, MAE = 0.477 in case of test set), indicating their reliability in identifying potent FAK inhibitors. Using this QSAR model and molecular docking, compound 21 (ZINC000004523722) was identified as the most potential compound, with predicted logIC50 value and binding energy of 2.59 and - 9.3 kcal/mol, respectively. The results of molecular dynamics simulation and ADMET study also further suggested its potential as a promising drug candidate. However, because our research was merely theoretical, additional in vitro and in vivo studies are required for the verification of these results.
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Affiliation(s)
- Nguyen Thu Hang
- Department of Pharmacognosy, Faculty of Pharmacognosy and Traditional Medicine, Hanoi University of Pharmacy, Hanoi, 11000, Vietnam
| | - Than Thi Kieu My
- Department of Pharmacognosy, Faculty of Pharmacognosy and Traditional Medicine, Hanoi University of Pharmacy, Hanoi, 11000, Vietnam
| | - Le Thi Van Anh
- Department of Pharmacognosy, Faculty of Pharmacognosy and Traditional Medicine, Hanoi University of Pharmacy, Hanoi, 11000, Vietnam
| | - Phan Thi Van Anh
- Department of Pharmacognosy, Faculty of Pharmacognosy and Traditional Medicine, Hanoi University of Pharmacy, Hanoi, 11000, Vietnam
| | - Thai Doan Hoang Anh
- Department of Pharmacognosy, Faculty of Pharmacognosy and Traditional Medicine, Hanoi University of Pharmacy, Hanoi, 11000, Vietnam
| | - Nguyen Van Phuong
- Department of Pharmacognosy, Faculty of Pharmacognosy and Traditional Medicine, Hanoi University of Pharmacy, Hanoi, 11000, Vietnam.
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2
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Er-Rajy M, El Fadili M, Faris A, Zarougui S, Elhallaoui M. Design of potential anti-cancer agents as COX-2 inhibitors, using 3D-QSAR modeling, molecular docking, oral bioavailability proprieties, and molecular dynamics simulation. Anticancer Drugs 2024; 35:117-128. [PMID: 38018861 DOI: 10.1097/cad.0000000000001492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2023]
Abstract
Modeling the structural properties of novel morpholine-bearing 1, 5-diaryl-diazole derivatives as potent COX-2 inhibitor, two proposed models based on CoMFA and CoMSIA were evaluated by external and internal validation methods. Partial least squares analysis produced statistically significant models with Q 2 values of 0.668 and 0.652 for CoMFA and CoMSIA, respectively, and also a significant non-validated correlation coefficient R² with values of 0.882 and 0.878 for CoMFA and CoMSIA, respectively. Both models met the requirements of Golbraikh and Tropsha, which means that both models are consistent with all validation techniques. Analysis of the CoMFA and CoMSIA contribution maps and molecular docking revealed that the R1 substituent has a very significant effect on their biological activity. The most active molecules were evaluated for their thermodynamic stability by performing MD simulations for 100 ns; it was revealed that the designed macromolecular ligand complex with 3LN1 protein exhibits a high degree of structural and conformational stability. Based on these results, we predicted newly designed compounds, which have acceptable oral bioavailability properties and would have high synthetic accessibility.
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Affiliation(s)
- Mohammed Er-Rajy
- LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco
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3
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Guo C, Li Q, Xiao J, Ma F, Xia X, Shi M. Identification of defactinib derivatives targeting focal adhesion kinase using ensemble docking, molecular dynamics simulations and binding free energy calculations. J Biomol Struct Dyn 2023; 41:8654-8670. [PMID: 36281703 DOI: 10.1080/07391102.2022.2135601] [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: 07/08/2022] [Accepted: 10/08/2022] [Indexed: 10/31/2022]
Abstract
Focal adhesion kinase (FAK) belongs to the nonreceptor tyrosine kinases, which selectively phosphorylate tyrosine residues on substrate proteins. FAK is associated with bladder, esophageal, gastric, neck, breast, ovarian and lung cancers. Thus, FAK has been considered as a potential target for tumor treatment. Currently, there are six adenosine triphosphate (ATP)-competitive FAK inhibitors tested in clinical trials but no approved inhibitors targeting FAK. Defactinib (VS-6063) is a second-generation FAK inhibitor with an IC50 of 0.6 nM. The binding model of VS-6063 with FAK may provide a reference model for developing new antitumor FAK-targeting drugs. In this study, the VS-6063/FAK binding model was constructed using ensemble docking and molecular dynamics simulations. Furthermore, the molecular mechanics/generalized Born (GB) surface area (MM/GBSA) method was employed to estimate the binding free energy between VS-6063 and FAK. The key residues involved in VS-6063/FAK binding were also determined using per-residue energy decomposition analysis. Based on the binding model, VS-6063 could be separated into seven regions to enhance its binding affinity with FAK. Meanwhile, 60 novel defactinib-based compounds were designed and verified using ensemble docking. Overall, the present study improves our understanding of the binding mechanism of human FAK with VS-6063 and provides new insights into future drug designs targeting FAK.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Chuan Guo
- Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
| | - Qinxuan Li
- Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
| | - Jiujia Xiao
- Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
| | - Feng Ma
- Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
| | - Xun Xia
- Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
| | - Mingsong Shi
- State Key Laboratory of Biotherapy, Sichuan University, Chengdu, Sichuan, China
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4
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El Alaouy MA, Alaqarbeh M, Ouabane M, Zaki H, ElBouhi M, Badaoui H, Moukhliss Y, Sbai A, Maghat H, Lakhlifi T, Bouachrine M. Computational Prediction of 3,5-Diaryl-1H-Pyrazole and spiropyrazolines derivatives as potential acetylcholinesterase inhibitors for alzheimer disease treatment by 3D-QSAR, molecular docking, molecular dynamics simulation, and ADME-Tox. J Biomol Struct Dyn 2023:1-14. [PMID: 37655700 DOI: 10.1080/07391102.2023.2252116] [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: 09/03/2022] [Accepted: 08/20/2023] [Indexed: 09/02/2023]
Abstract
The efficacy of 40 synthesized variants of 3,5-diaryl-1H-pyrazole and spiropyrazoline' derivatives as acetylcholinesterase inhibitors is verified using a quantitative three-dimensional structure-activity relationship (3D-QSAR) by comparative molecular field analysis (CoMFA) and molecular similarity index analysis (CoMSIA) models. In this research, different field models proved that CoMSIA/SE model is the best model with high predictive power compared to several models (Qved2 = O.65; R2 = 0.980; R2test = 0.727). Also, contour maps produced by CoMSIA/SE model have been employed to prove the key structural needs of the activity. Consequently, six new compounds have been generated. Among these compounds, M4 and M5 were the most active but remained toxic and had poor absorption capacities. While the M1, M2, M3 and M6 remained highly active while respecting ADMET's characteristics. Molecular docking results showed compound M2 better with acetylcholinesterase than compound 22. The interactions are classical hydrogen bonding with residues TYR:124, TYR:72, and SER:293, which play a critical role in the biological activity as AChE inhibitors. MD results confirmed the docking results and showed that compound M2 had satisfactory stability with (ΔGbinding = -151.225 KJ/mol) in the active site of AChE receptor compared with compound 22 (ΔGbinding = -133.375 KJ/mol). In addition, both compounds had good stability regarding RMSD, Rg, and RMSF. The previous results show that the newly designed compound M2 is more active in the active site of AChE receptor than compound 22.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Moulay Ahfid El Alaouy
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
| | | | - Mohamed Ouabane
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
| | - Hanane Zaki
- BIO Laboratory, EST Khenifra, Sultan Moulay Slimane University Beni Mellal, Morocco
| | - Mohamed ElBouhi
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
| | - Hassan Badaoui
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
| | - Youness Moukhliss
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
| | - Abdelouahid Sbai
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
| | - Hamid Maghat
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
| | - Tahar Lakhlifi
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
| | - Mohammed Bouachrine
- Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
- EST Khenifra, Sultan Moulay Sliman University, Benimellal, Morocco
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5
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Fu L, Zhao L, Liang M, Ran K, Fu J, Qiu H, Li F, Shu M. Identification of potential CAMKK2 inhibitors based on virtual screening and molecular dynamics simulation. MOLECULAR SIMULATION 2022. [DOI: 10.1080/08927022.2022.2123945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
- Le Fu
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, People’s Republic of China
- Qianjiang Central Hospital of Chongqing, Chongqing, People’s Republic of China
| | - Linan Zhao
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, People’s Republic of China
| | - Meichen Liang
- Qianjiang Central Hospital of Chongqing, Chongqing, People’s Republic of China
| | - Kun Ran
- Qianjiang Central Hospital of Chongqing, Chongqing, People’s Republic of China
| | - Jing Fu
- Qianjiang Central Hospital of Chongqing, Chongqing, People’s Republic of China
| | - Haoyu Qiu
- Qianjiang Central Hospital of Chongqing, Chongqing, People’s Republic of China
| | - Fei Li
- Qianjiang Central Hospital of Chongqing, Chongqing, People’s Republic of China
| | - Mao Shu
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, People’s Republic of China
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6
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Shi M, Chen T, Wei S, Zhao C, Zhang X, Li X, Tang X, Liu Y, Yang Z, Chen L. Molecular Docking, Molecular Dynamics Simulations, and Free Energy Calculation Insights into the Binding Mechanism between VS-4718 and Focal Adhesion Kinase. ACS OMEGA 2022; 7:32442-32456. [PMID: 36119979 PMCID: PMC9476166 DOI: 10.1021/acsomega.2c03951] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/24/2022] [Indexed: 05/17/2023]
Abstract
Focal adhesion kinase (FAK) is a 125 kDa nonreceptor tyrosine kinase that plays an important role in many carcinomas. Thus, the targeting of FAK by small molecules is considered to be promising for cancer therapy. Some FAK inhibitors have been reported as potential anticancer drugs and have entered into clinical development; for example, VS-4718 is currently undergoing clinical trials. However, the lack of crystal structural data for the binding of VS-4718 with FAK has hindered the optimization of this anticancer agent. In this work, the VS-4718/FAK interaction model was obtained by molecular docking and molecular dynamics simulations. The binding free energies of VS-4718/FAK were also calculated using the molecular mechanics generalized Born surface area method. It was found that the aminopyrimidine group formed hydrogen bonds with the C502 residue of the hinge loop, while the D564 residue of the T-loop interacted with the amide group. In addition, I428, A452, V484, M499, G505, and L553 residues formed hydrophobic interactions with VS-4718. The obtained results therefore provide an improved understanding of the interaction between human FAK and VS-4718. Based on the obtained binding mechanism, 47 novel compounds were designed to target the adenosine 5'-triphosphate-binding pocket of human FAK, and ensemble docking was performed to assess the effects of these modifications on the inhibitor binding affinity. This work is also expected to provide additional insights into potential future target design strategies based on VS-4718.
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Affiliation(s)
- Mingsong Shi
- State
Key Laboratory of Biotherapy, West China
Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Tao Chen
- State
Key Laboratory of Biotherapy, West China
Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Siping Wei
- Key
Laboratory for Chemistry and Molecular Engineering of Medicinal Resources, Guangxi Normal University, Guilin 541004, China
- Department
of Medicinal Chemistry, School of Pharmacy, Southwest Medical University, Luzhou 646000, China
| | - Chenyu Zhao
- West
China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu 610041, China
| | - Xinyu Zhang
- West
China School of Pharmacy, Sichuan University, Chengdu 610041, Sichuan, China
| | - Xinghui Li
- West
China School of Pharmacy, Sichuan University, Chengdu 610041, Sichuan, China
| | - Xinyi Tang
- West
China School of Pharmacy, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yan Liu
- State
Key Laboratory of Biotherapy, West China
Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Zhuang Yang
- State
Key Laboratory of Biotherapy, West China
Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Lijuan Chen
- State
Key Laboratory of Biotherapy, West China
Hospital of Sichuan University, Chengdu 610041, Sichuan, China
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7
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Abdullahi M, Uzairu A, Shallangwa GA, Mamza PA, Ibrahim MT. Computational modelling studies of some 1,3-thiazine derivatives as anti-influenza inhibitors targeting H1N1 neuraminidase via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions. BENI-SUEF UNIVERSITY JOURNAL OF BASIC AND APPLIED SCIENCES 2022; 11:104. [PMID: 36000144 PMCID: PMC9389500 DOI: 10.1186/s43088-022-00280-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/27/2022] [Indexed: 12/19/2022] Open
Abstract
Abstract
Background
Influenza virus disease remains one of the most contagious diseases that aided the deaths of many patients, especially in this COVID-19 pandemic era. Recent discoveries have shown that the high prevalence of influenza and SARS-CoV-2 coinfection can rapidly increase the death rate of patients. Hence, it became necessary to search for more potent inhibitors for influenza disease therapy. The present study utilized some computational modeling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions of some 1,3-thiazine derivatives as inhibitors of influenza neuraminidase (NA).
Results
The 2D-QSAR modeling results showed GFA-MLR ($$R_{{\text{train }}}^{2}$$
R
train
2
= 0.9192, Q2 = 0.8767, R2adj = 0.8991, RMSE = 0.0959, $$R_{{{\text{test}}}}^{2}$$
R
test
2
= 0.8943, $$R_{{{\text{pred}}}}^{2}$$
R
pred
2
= 0.7745) and GFA-ANN ($$R_{{\text{train }}}^{2}$$
R
train
2
= 0.9227, Q2 = 0.9212, RMSE = 0.0940, $$R_{{{\text{test}}}}^{2}$$
R
test
2
= 0.8831, $$R_{{{\text{pred}}}}^{2}$$
R
pred
2
= 0.7763) models with the computed descriptors as ATS7s, SpMax5_Bhv, nHBint6, and TDB9m for predicting the NA inhibitory activities of compounds which have passed the global criteria of accepting QSAR model. The 3D-QSAR modeling was carried out based on the comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA). The CoMFA_ES ($$R_{{\text{train }}}^{2}$$
R
train
2
= 0.9620, Q2 = 0.643) and CoMSIA_SED ($$R_{{\text{train }}}^{2}$$
R
train
2
= 0.8770, Q2 = 0.702) models were found to also have good and reliable predicting ability. The compounds were also virtually screened based on their binding scores via molecular docking simulations with the active site of the NA (H1N1) target receptor which also confirms their resilient potency. Four potential lead compounds (4, 7, 14, and 15) with the relatively high inhibitory rate (> 50%) and docking (> − 6.3 kcal/mol) scores were identified as the possible lead candidates for in silico exploration of improved anti-influenza agents.
Conclusion
The drug-likeness and ADMET predictions of the lead compounds revealed non-violation of Lipinski’s rule and good pharmacokinetic profiles as important guidelines for rational drug design. Hence, the outcome of this research set a course for the in silico design and exploration of novel NA inhibitors with improved potency.
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8
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Abdullahi M, Uzairu A, Shallangwa GA, Mamza PA, Ibrahim MT. In-silico modelling studies of 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase inhibitors via 2D-QSAR, 3D-QSAR, molecular docking, and ADMET predictions. Heliyon 2022; 8:e10101. [PMID: 36016519 PMCID: PMC9396554 DOI: 10.1016/j.heliyon.2022.e10101] [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: 05/12/2022] [Revised: 06/22/2022] [Accepted: 07/26/2022] [Indexed: 01/12/2023] Open
Abstract
Influenza virus disease is one of the most infectious diseases responsible for many human deaths, and the high mutability of the virus causes drug resistance effects in recent times. As such, it became necessary to explore more inhibitors that could avert future influenza pandemics. The present research utilized some in-silico modelling concepts such as 2D-QSAR, 3D-QSAR, molecular docking simulation, and ADMET predictions on some 5-benzyl-4-thiazolinone derivatives as influenza neuraminidase (NA) inhibitors. The 2D-QSAR modelling results revealed GFA-MLR (R train 2 =0.8414, Q2 = 0.7680) and GFA-ANN (R train 2 =0.8754, Q2 = 0.8753) models with the most relevant descriptors (MATS3i, SpMax5_Bhe, minsOH and VE3_D) for predicting the inhibitory activities of the molecules which has passed the global criteria of accepting QSAR models. The results of the 3D-QSAR modelling results showed that CoMFA_ES (R train 2 =0.9030, Q2 = 0.5390) and CoMSIA_EA (R train 2 =0.880, Q2 = 0.547) models are having good predicting ability among other developed models. The molecules were virtually screened via molecular docking simulation with the active site of NA protein receptor (pH1N1) which confirms their resilient potency when compared with zanamivir standard drug. Molecule 11 as the most potent molecule formed more H-bond interactions with the key residues such as TRP178, ARG152, ARG292, ARG371, and TYR406 that triggered the catalytic reactions for NA inhibition. Furthermore, six (6) molecules (9, 10, 11, 17, 22, and 31) with relatively high inhibitory activities and docking scores were identified as the possible leads for in-silico exploration of novel NA inhibitors. The drug-likeness and ADMET predictions of the lead molecules revealed non-violation of Lipinski's rule and good pharmacokinetic profiles respectively, which are important guidelines for rational drug design. Hence, the outcome of this study overlaid a solid foundation for the in-silico design and exploration of novel NA inhibitors with improved potency.
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Affiliation(s)
- Mustapha Abdullahi
- Faculty of Physical Sciences, Department of Chemistry, Ahmadu Bello University, P.M.B. 1044, Zaria, Kaduna State, Nigeria
- Faculty of Sciences, Department of Pure and Applied Chemistry, Kaduna State University, Tafawa Balewa Way, Kaduna, Nigeria
| | - Adamu Uzairu
- Faculty of Physical Sciences, Department of Chemistry, Ahmadu Bello University, P.M.B. 1044, Zaria, Kaduna State, Nigeria
| | - Gideon Adamu Shallangwa
- Faculty of Physical Sciences, Department of Chemistry, Ahmadu Bello University, P.M.B. 1044, Zaria, Kaduna State, Nigeria
| | - Paul Andrew Mamza
- Faculty of Physical Sciences, Department of Chemistry, Ahmadu Bello University, P.M.B. 1044, Zaria, Kaduna State, Nigeria
| | - Muhammad Tukur Ibrahim
- Faculty of Physical Sciences, Department of Chemistry, Ahmadu Bello University, P.M.B. 1044, Zaria, Kaduna State, Nigeria
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9
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Zhao L, Fu L, Li G, Yu Y, Wang J, Liang H, Shu M, Lin Z, Wang Y. Three-dimensional quantitative structural-activity relationship and molecular dynamics study of multivariate substituted 4-oxyquinazoline HDAC6 inhibitors. Mol Divers 2022:10.1007/s11030-022-10474-w. [PMID: 35767128 DOI: 10.1007/s11030-022-10474-w] [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: 04/06/2022] [Accepted: 05/30/2022] [Indexed: 01/18/2023]
Abstract
3D-QSAR models were established by collecting 46 multivariate-substituted 4-oxyquinazoline HDAC6 inhibitors. The relationship of molecular structure and inhibitory activity was studied by comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). The results showed the models established by CoMFA (q2 = 0.590, r2 = 0.965) and CoMSIA (q2 = 0.594, r2 = 0.931) had good prediction ability. At the same time, 3D-QSAR models met the internal verification, external verification and AD test. Ten new compounds were designed based on CoMFA and CoMSIA contour maps and their pharmacokinetic/toxic properties (ADME/T) were evaluated. It was found that most compounds have well safety profile and pharmacokinetic property. Then, we explored the interaction between HDAC6 and compounds by molecular docking. The results showed that the binding mode of the new compounds with HDAC6 was the same as the template compound 46, and the hydrogen bond and hydrophobic bond played a vital role in the binding process. Molecular dynamics simulation results showed that residues Ser531, His574 and Tyr745 played key roles in the binding process. All newly designed compounds had lower energy gap and binding energy than compound 46 according to DFT analysis and free energy analysis. This study provided a theoretical reference for designing compounds of higher activity and a new idea for the development of novel HDAC6 inhibitors.
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Affiliation(s)
- Linan Zhao
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Le Fu
- Qianjiang Central Hospital of Chongqing, Chongqing, 409099, China
| | - Guangping Li
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Yongxin Yu
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Juan Wang
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.,Chongqing Key Laboratory of Medicinal Chemistry and Molecular Pharmacology, Chongqing University of Technology, Chongqing, 400054, China.,Chongqing Key Laboratory of Target Based Drug Screening and Activity Evaluation, Chongqing University of Technology, Chongqing, 400054, China
| | - Haoran Liang
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China. .,Chongqing Key Laboratory of Medicinal Chemistry and Molecular Pharmacology, Chongqing University of Technology, Chongqing, 400054, China. .,Chongqing Key Laboratory of Target Based Drug Screening and Activity Evaluation, Chongqing University of Technology, Chongqing, 400054, China.
| | - Mao Shu
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China. .,Chongqing Key Laboratory of Medicinal Chemistry and Molecular Pharmacology, Chongqing University of Technology, Chongqing, 400054, China. .,Chongqing Key Laboratory of Target Based Drug Screening and Activity Evaluation, Chongqing University of Technology, Chongqing, 400054, China.
| | - Zhihua Lin
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.,Chongqing Key Laboratory of Medicinal Chemistry and Molecular Pharmacology, Chongqing University of Technology, Chongqing, 400054, China.,Chongqing Key Laboratory of Target Based Drug Screening and Activity Evaluation, Chongqing University of Technology, Chongqing, 400054, China
| | - Yuanqiang Wang
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China. .,Chongqing Key Laboratory of Medicinal Chemistry and Molecular Pharmacology, Chongqing University of Technology, Chongqing, 400054, China. .,Chongqing Key Laboratory of Target Based Drug Screening and Activity Evaluation, Chongqing University of Technology, Chongqing, 400054, China.
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