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Poonia P, Sharma M, Jha P, Chopra M. Pharmacophore-based virtual screening of ZINC database, molecular modeling and designing new derivatives as potential HDAC6 inhibitors. Mol Divers 2023; 27:2053-2071. [PMID: 36214962 DOI: 10.1007/s11030-022-10540-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Accepted: 09/30/2022] [Indexed: 11/25/2022]
Abstract
To date, many HDAC6 inhibitors have been identified and developed but none is clinically approved as of now. Through this study, we aim to obtain novel HDAC6 selective inhibitors and provide new insights into the detailed structural design of potential HDAC6 inhibitors. A HypoGen-based 3D QSAR HDAC6 pharmacophore was built and used as a query model to screen approximately 8 million ZINC database compounds. First, the ZINC Database was filtered using ADMET, followed by pharmacophore-based library screening. Using fit value and estimated activity cutoffs, a final set of 54 ZINC hits was obtained that were further investigated using molecular docking with the crystal structure of human histone deacetylase 6 catalytic domain 2 in complex with Trichostatin A (PDB ID: 5EDU). Through detailed in silico screening of the ZINC database, we shortlisted three hits as the lead molecules for designing novel HDAC6 inhibitors with better efficacy. Docking with 5EDU, followed by ADMET and TOPKAT analysis of modified ZINC hits provided 9 novel potential HDAC6 inhibitors that possess better docking scores and 2D interactions as compared to the control ZINC hit molecules. Finally, a 50 ns MD analysis run followed by Protein-Ligand Interaction Energy (PLIE) analysis of the top scored hits provided a novel molecule N1 that showed promisingly similar results to that of Ricolinostat (a known HDAC6 inhibitor). The comparable result of the designed hits to established HDAC6 inhibitors suggests that these compounds might prove to be successful HDAC6 inhibitors in future. Designed novel hits that might act as good HDAC6 inhibitors derived from ZINC database using combined molecular docking and modeling approaches.
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Affiliation(s)
- Priya Poonia
- Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, 110036, India
| | - Monika Sharma
- Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, 110036, India
| | - Prakash Jha
- Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, 110036, India
| | - Madhu Chopra
- Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, 110036, India.
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2
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Yin Z, Liu S, Yang X, Chen M, Du J, Liu H, Yang L. LSD1-Based Reversible Inhibitors Virtual Screening and Binding Mechanism Computational Study. Molecules 2023; 28:5315. [PMID: 37513188 PMCID: PMC10383809 DOI: 10.3390/molecules28145315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 07/02/2023] [Accepted: 07/04/2023] [Indexed: 07/30/2023] Open
Abstract
As one of the crucial targets of epigenetics, histone lysine-specific demethylase 1 (LSD1) is significant in the occurrence and development of various tumors. Although several irreversible covalent LSD1 inhibitors have entered clinical trials, the large size and polarity of the FAD-binding pocket and undesired toxicity have focused interest on developing reversible LSD1 inhibitors. In this study, targeting the substrate-binding pocket of LSD1, structure-based and ligand-based virtual screenings were adopted to expand the potential novel structures with molecular docking and pharmacophore model strategies, respectively. Through drug-likeness evaluation, ADMET screening, molecular dynamics simulations, and binding free energy screening, we screened out one and four hit compounds from the databases of 2,029,554 compounds, respectively. Generally, these hit compounds can be divided into two categories, amide (Lig2 and Comp2) and 1,2,4-triazolo-4,3-α-quinazoline (Comp3, Comp4, Comp7). Among them, Comp4 exhibits the strongest binding affinity. Finally, the binding mechanisms of the hit compounds were further calculated in detail by the residue free energy decomposition. It was found that van der Waals interactions contribute most to the binding, and FAD is also helpful in stabilizing the binding and avoiding off-target effects. We believe this work not only provides a solid theoretical foundation for the design of LSD1 substrate reversible inhibitors, but also expands the diversity of parent nucleus, offering new insights for synthetic chemists.
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Affiliation(s)
- Zhili Yin
- School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Shaohui Liu
- School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Xiaoyue Yang
- School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Mengguo Chen
- School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Jiangfeng Du
- School of Life Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Hongmin Liu
- School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
- Key Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, Zhengzhou University, Zhengzhou 450001, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou 450001, China
- Key Laboratory of Henan Province for Drug Quality and Evaluation, Zhengzhou University, Zhengzhou 450001, China
- Institute of Drug Discovery and Development, Zhengzhou University, Zhengzhou 450001, China
| | - Longhua Yang
- School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China
- Key Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, Zhengzhou University, Zhengzhou 450001, China
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3
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Chaudhary N, Aparoy P. Application of per-residue energy decomposition to identify the set of amino acids critical for in silico prediction of COX-2 inhibitory activity. Heliyon 2020; 6:e04944. [PMID: 33083581 PMCID: PMC7550918 DOI: 10.1016/j.heliyon.2020.e04944] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 05/31/2020] [Accepted: 09/11/2020] [Indexed: 12/29/2022] Open
Abstract
The enormous magnitude of scientific research carried out in the field of NSAIDs and cyclooxygenases (COXs) is known. They are crucial in pain management. COX-2 inhibitors have evolved over the years; from traditional NSAIDs to isoform-specific. The present study is aimed to identify a cluster of amino acids in the catalytic site whose energy contribution can better explain COX-2 inhibitory activity accurately than the binding energy of the whole protein. Initially, MD simulations (25 ns) and MM-PBSA calculations were performed for 8 diarylheterocyclic inhibitors. Per-residue energy decomposition studies were carried out to elucidate the energy contribution of each amino acid, and their correlation with COX-2 inhibitory activity was enumerated. A cluster of catalytic amino acids whose free energy sum has a high correlation with biological data was identified. The cluster of Gln178, Ser339, Tyr341, Arg499, Phe504, Val509 and Ala513 showed the correlation of -0.60. Further, the study was extended to a total of 26 COX-2 inhibitors belonging to different classes to validate the applicability of the cluster of amino acids identified. Results clearly suggest that the cluster of amino acids identified provide accurate screening method, and can be applied to predict COX-2 inhibitory activity of small molecules.
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Affiliation(s)
- Neha Chaudhary
- Centre for Computational Biology and Bioinformatics, School of Life Sciences, Central University of Himachal Pradesh, Dharamshala, Himachal Pradesh, 176215, India
| | - Polamarasetty Aparoy
- Centre for Computational Biology and Bioinformatics, School of Life Sciences, Central University of Himachal Pradesh, Dharamshala, Himachal Pradesh, 176215, India.,Faculty of Biology, Indian Institute of Petroleum & Energy, Visakhapatnam, Andhra Pradesh, India
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4
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Li S, Zhang S, Chen D, Jiang X, Liu B, Zhang H, Rachakunta M, Zuo Z. Identification of Novel TRPC5 Inhibitors by Pharmacophore-Based and Structure-Based Approaches. Comput Biol Chem 2020; 87:107302. [PMID: 32554176 DOI: 10.1016/j.compbiolchem.2020.107302] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 05/15/2020] [Accepted: 06/02/2020] [Indexed: 01/13/2023]
Abstract
Canonical transient receptor potential-5 (TRPC5), which belongs to the subfamily of transient receptor potential (TRP) channels, is a non-selective cation channel mainly expressed in the central nervous system and shows more restricted expression in the periphery. TRPC5 plays a crucial role in human physiology and pathology, for instance, anxiety, depression, epilepsy, pain, memory and chronic kidney disease (CKD). However, due to lack of the effective and selective inhibitors, its physiological and pathological mechanism remains so far unknown. It is therefore pivotal to identify potential TRPC5 inhibitors. We have applied ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) methods. The pharmacophore models of TRPC5 antagonists generated by using the HypoGen and HipHop algorithms were used as a query model for the screening of potential inhibitors against the Specs database. The resultant hits from LBVS were further screened by SBVS. SBVS was carried out based on the homology model generation of human TRPC5, binding site identification, molecular dynamics optimization and molecular docking studies. In our systematic screening approaches, we have identified 7 hits compounds with comparable dock score after Lipinski and Veber rules, ADMET, PAINS analysis, cluster analysis, and similarity analysis. In conclusion, the current research provides novel backbones for the new-generation of TRPC5 inhibitors.
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Affiliation(s)
- Shuxiang Li
- Key Laboratory of Medicinal Chemistry for Natural Resources, Ministry of Education and Yunnan Province, School of Chemical Science and Technology, Yunnan University, Kunming, China; State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Shuqun Zhang
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Dingyuan Chen
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Xuan Jiang
- Key Laboratory of Medicinal Chemistry for Natural Resources, Ministry of Education and Yunnan Province, School of Chemical Science and Technology, Yunnan University, Kunming, China
| | - Bin Liu
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Hongbin Zhang
- Key Laboratory of Medicinal Chemistry for Natural Resources, Ministry of Education and Yunnan Province, School of Chemical Science and Technology, Yunnan University, Kunming, China
| | - Munikishore Rachakunta
- State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Zhili Zuo
- Key Laboratory of Medicinal Chemistry for Natural Resources, Ministry of Education and Yunnan Province, School of Chemical Science and Technology, Yunnan University, Kunming, China; State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.
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Tseng TS, Chuang SM, Hsiao NW, Chen YW, Lee YC, Lin CC, Huang C, Tsai KC. Discovery of a potent cyclooxygenase-2 inhibitor, S4, through docking-based pharmacophore screening, in vivo and in vitro estimations. MOLECULAR BIOSYSTEMS 2016; 12:2541-51. [DOI: 10.1039/c6mb00229c] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Cyclooxygenase (COX; EC: 1.14.99.1), the key enzyme in prostaglandin production in the human body, is a major pharmacological target for developing anti-inflammatory agents.
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Affiliation(s)
- Tien-Sheng Tseng
- National Research Institute of Chinese Medicine
- Ministry of Health and Welfare
- Taipei
- Taiwan
- Institute of Biomedical Sciences
| | - Show-Mei Chuang
- Institute of Biomedical Sciences
- National Chung Hsing University
- Taichung
- Taiwan
| | - Nai-Wan Hsiao
- Institute of Biotechnology
- National Changhua University of Education
- Changhua
- Taiwan
| | | | - Yu-Ching Lee
- The Center of Translational Medicine
- Taipei Medical University
- Taipei
- Taiwan
- The Ph.D. Program for Medical Biotechnology
| | - Chi-Chen Lin
- Institute of Biomedical Sciences
- National Chung Hsing University
- Taichung
- Taiwan
| | - Cheng Huang
- National Research Institute of Chinese Medicine
- Ministry of Health and Welfare
- Taipei
- Taiwan
| | - Keng-Chang Tsai
- National Research Institute of Chinese Medicine
- Ministry of Health and Welfare
- Taipei
- Taiwan
- The Ph.D. Program for Medical Biotechnology
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6
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Kumar SP, Jha PC, Jasrai YT, Pandya HA. The effect of various atomic partial charge schemes to elucidate consensus activity-correlating molecular regions: a test case of diverse QSAR models. J Biomol Struct Dyn 2015; 34:540-59. [PMID: 25997097 DOI: 10.1080/07391102.2015.1044474] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
The estimation of atomic partial charges of the small molecules to calculate molecular interaction fields (MIFs) is an important process in field-based quantitative structure-activity relationship (QSAR). Several studies showed the influence of partial charge schemes that drastically affects the prediction accuracy of the QSAR model and focused on the selection of appropriate charge models that provide highest cross-validated correlation coefficient ([Formula: see text] or q(2)) to explain the variation in chemical structures against biological endpoints. This study shift this focus in a direction to understand the molecular regions deemed to explain SAR in various charge models and recognize a consensus picture of activity-correlating molecular regions. We selected eleven diverse dataset and developed MIF-based QSAR models using various charge schemes including Gasteiger-Marsili, Del Re, Merck Molecular Force Field, Hückel, Gasteiger-Hückel, and Pullman. The generalized resultant QSAR models were then compared with Open3DQSAR model to interpret the MIF descriptors decisively. We suggest the regions of activity contribution or optimization can be effectively determined by studying various charge-based models to understand SAR precisely.
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Affiliation(s)
- Sivakumar Prasanth Kumar
- a Department of Bioinformatics , Applied Botany Centre (ABC), University School of Sciences, Gujarat University , Ahmedabad 380 009 , India
| | - Prakash C Jha
- b School of Chemical Sciences, Central University of Gujarat , Sector-30, Gandhinagar 382030 , India
| | - Yogesh T Jasrai
- a Department of Bioinformatics , Applied Botany Centre (ABC), University School of Sciences, Gujarat University , Ahmedabad 380 009 , India
| | - Himanshu A Pandya
- a Department of Bioinformatics , Applied Botany Centre (ABC), University School of Sciences, Gujarat University , Ahmedabad 380 009 , India
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7
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Kumar A, Roy S, Tripathi S, Sharma A. Molecular docking based virtual screening of natural compounds as potential BACE1 inhibitors: 3D QSAR pharmacophore mapping and molecular dynamics analysis. J Biomol Struct Dyn 2015; 34:239-49. [DOI: 10.1080/07391102.2015.1022603] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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8
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Paliwal S, Mittal A, Sharma M, pandey A, Singh A, Paliwal S. Pharmacophore and molecular docking based identification of novel structurally diverse PDE-5 inhibitors. Med Chem Res 2014. [DOI: 10.1007/s00044-014-1144-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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9
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Lin CY, Wang YL. Novel design strategy for checkpoint kinase 2 inhibitors using pharmacophore modeling, combinatorial fusion, and virtual screening. BIOMED RESEARCH INTERNATIONAL 2014; 2014:359494. [PMID: 24864236 PMCID: PMC4017722 DOI: 10.1155/2014/359494] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2013] [Accepted: 02/19/2014] [Indexed: 11/24/2022]
Abstract
Checkpoint kinase 2 (Chk2) has a great effect on DNA-damage and plays an important role in response to DNA double-strand breaks and related lesions. In this study, we will concentrate on Chk2 and the purpose is to find the potential inhibitors by the pharmacophore hypotheses (PhModels), combinatorial fusion, and virtual screening techniques. Applying combinatorial fusion into PhModels and virtual screening techniques is a novel design strategy for drug design. We used combinatorial fusion to analyze the prediction results and then obtained the best correlation coefficient of the testing set (r test) with the value 0.816 by combining the Best(train)Best(test) and Fast(train)Fast(test) prediction results. The potential inhibitors were selected from NCI database by screening according to Best(train)Best(test) + Fast(train)Fast(test) prediction results and molecular docking with CDOCKER docking program. Finally, the selected compounds have high interaction energy between a ligand and a receptor. Through these approaches, 23 potential inhibitors for Chk2 are retrieved for further study.
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Affiliation(s)
- Chun-Yuan Lin
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
- Research Center for Emerging Viral Infections, Chang Gung University, Taoyuan 33302, Taiwan
| | - Yen-Ling Wang
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
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Wang YL, Lin CY, Shih KC, Huang JW, Tang CY. Design checkpoint kinase 2 inhibitors by pharmacophore modeling and virtual screening techniques. Bioorg Med Chem Lett 2013; 23:6286-91. [PMID: 24144850 DOI: 10.1016/j.bmcl.2013.09.080] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2013] [Revised: 08/26/2013] [Accepted: 09/25/2013] [Indexed: 01/09/2023]
Abstract
Damage to DNA is caused by ionizing radiation, genotoxic chemicals or collapsed replication forks. When DNA is damaged or cells fail to respond, a mutation that is associated with breast or ovarian cancer may occur. Mammalian cells control and stabilize the genome using a cell cycle checkpoint to prevent damage to DNA or to repair damaged DNA. Checkpoint kinase 2 (Chk2) is one of the important kinases, which strongly affects DNA-damage and plays an important role in the response to the breakage of DNA double-strands and related lesions. Therefore, this study concerns Chk2. Its purpose is to find potential inhibitors using the pharmacophore hypotheses (PhModels) and virtual screening techniques. PhModels can identify inhibitors with high biological activities and virtual screening techniques are used to screen the database of the National Cancer Institute (NCI) to retrieve compounds that exhibit all of the pharmacophoric features of potential inhibitors with high interaction energy. Ten PhModels were generated using the HypoGen best algorithm. The established PhModel, Hypo01, was evaluated by performing a cost function analysis of its correlation coefficient (r), root mean square deviation (RMSD), cost difference, and configuration cost, with the values 0.955, 1.28, 192.51, and 16.07, respectively. The result of Fischer's cross-validation test for the Hypo01 model yielded a 95% confidence level, and the correlation coefficient of the testing set (rtest) had a best value of 0.81. The potential inhibitors were then chosen from the NCI database by Hypo01 model screening and molecular docking using the cdocker docking program. Finally, the selected compounds exhibited the identified pharmacophoric features and had a high interaction energy between the ligand and the receptor. Eighty-three potential inhibitors for Chk2 are retrieved for further study.
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Affiliation(s)
- Yen-Ling Wang
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
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11
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Theoretical evaluation of flotation performance of carboxyl hydroxamic acids with different number of polar groups on the surfaces of diaspore (010) and kaolinite (001). J Mol Model 2013; 19:3135-42. [PMID: 23609224 DOI: 10.1007/s00894-013-1843-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2012] [Accepted: 04/01/2013] [Indexed: 10/26/2022]
Abstract
The adsorption behaviors of three carboxyl hydroxamic acids on diaspore (010) and kaolinite (001) have been studied by density functional theory (DFT) and molecular dynamics (MD) method. The results indicated that carboxyl hydroxamic acids could adsorb on diaspore surface by ionic bonds and hydrogen bonds, and adsorb on kaolinite surface by hydrogen bonds. The models of carboxyl hydroxamic acids adsorbed on diaspore and kaolinite surfaces are proposed.
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12
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Yadav D, Paliwal S, Yadav R, Pal M, Pandey A. Identification of novel HIV 1--protease inhibitors: application of ligand and structure based pharmacophore mapping and virtual screening. PLoS One 2012; 7:e48942. [PMID: 23145032 PMCID: PMC3493599 DOI: 10.1371/journal.pone.0048942] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2012] [Accepted: 10/01/2012] [Indexed: 01/27/2023] Open
Abstract
A combined ligand and structure-based drug design approach provides a synergistic advantage over either methods performed individually. Present work bestows a good assembly of ligand and structure-based pharmacophore generation concept. Ligand-oriented study was accomplished by employing the HypoGen module of Catalyst in which we have translated the experimental findings into 3-D pharmacophore models by identifying key features (four point pharmacophore) necessary for interaction of the inhibitors with the active site of HIV-1 protease enzyme using a training set of 33 compounds belonging to the cyclic cyanoguanidines and cyclic urea derivatives. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, two hydrogen bond acceptors and two hydrophobic, showed a correlation (r) of 0.90 and a root mean square of 0.71 and cost difference of 56.59 bits between null cost and fixed cost. The model was validated using CatScramble technique, internal and external test set prediction. In the second phase of our study, a structure-based five feature pharmacophore hypothesis was generated which signifies the importance of hydrogen bond donor, hydrogen bond acceptors and hydrophobic interaction between the HIV-1 protease enzyme and its inhibitors. This work has taken a significant step towards the full integration of ligand and structure-based drug design methodologies as pharmacophoric features retrieved from structure-based strategy complemented the features from ligand-based study hence proving the accuracy of the developed models. The ligand-based pharmacophore model was used in virtual screening of Maybridge and NCI compound database resulting in the identification of four structurally diverse druggable compounds with nM activities.
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Affiliation(s)
- Divya Yadav
- Department of Pharmacy, Banasthali University, Banasthali, Rajasthan, India
| | - Sarvesh Paliwal
- Department of Pharmacy, Banasthali University, Banasthali, Rajasthan, India
| | - Rakesh Yadav
- Department of Pharmacy, Banasthali University, Banasthali, Rajasthan, India
| | - Mahima Pal
- Department of Pharmacy, Banasthali University, Banasthali, Rajasthan, India
| | - Anubhuti Pandey
- Department of Pharmacy, Banasthali University, Banasthali, Rajasthan, India
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Development of energetic pharmacophore for the designing of 1,2,3,4-tetrahydropyrimidine derivatives as selective cyclooxygenase-2 inhibitors. J Comput Aided Mol Des 2012; 26:267-77. [PMID: 22218727 DOI: 10.1007/s10822-011-9540-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2011] [Accepted: 12/29/2011] [Indexed: 12/29/2022]
Abstract
We present here the Energetic pharmacophore model representing complementary features of the 1,2,3,4-tetrahydropyrimidine for selective cyclooxygenase-2 (COX-2) inhibition. For the development of pharmacophore hypothesis, a total of 43 previously reported compounds were docked on active site of COX-2 enzyme. The generated pharmacophore features were ranked using energetic terms of Glide XP docking for 1,2,3,4-tetrahydropyrimidine scaffold to optimize its structure requirement for COX-2 inhibition. The thirty new 4,5,6-triphenyl-1,2,3,4-tetrahydropyrimidine derivatives were synthesized and assessed for selective COX-2 inhibitory activity. Two compounds 4B1 and 4B11 were found to be potent and selective COX-2 inhibitors. The molecular docking studies revealed that the newly synthesized compounds can be docked into COX-2 binding site and also provide the molecular basis for their activity.
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14
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Shih KC, Lin CY, Chi HC, Hwang CS, Chen TS, Tang CY, Hsiao NW. Design of novel FLT-3 inhibitors based on dual-layer 3D-QSAR model and fragment-based compounds in silico. J Chem Inf Model 2011; 52:146-55. [PMID: 22142286 DOI: 10.1021/ci200434f] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
FMS-like tyrosine kinase 3 (FLT-3) is strongly correlated with acute myeloid leukemia, but no FLT-3-inhibitor cocomplex structure is available to assist the design of therapeutic inhibitors. Hence, we propose a dual-layer 3D-QSAR model for FLT-3 that integrates the pharmacophore, CoMFA, and CoMSIA. We then coupled the model with the fragment-based design strategy to identify novel FLT-3 inhibitors. In the first layer, the previously established model, Hypo02, was evaluated in terms of its correlation coefficient (r), RMS, cost difference, and configuration cost, with values of 0.930, 1.24, 106.45, and 16.44, respectively. Moreover, Fischer's cross-validation test of data generated by Hypo02 yielded a 98% confidence level, and the validation of the testing set yielded a best r value of 0.87. The features of Hypo02 were separated into two parts and then used to screen the MiniMaybridge fragment compound database. Nine novel FLT-3 inhibitors were generated in this layer. In the second layer, Hypo02 was subjected to an alignment rule to generate CoMFA- and CoMSIA-based models, for which the partial least-squares validation method was utilized. The values of q(2), r(2), and predictive r(2) were 0.58, 0.98, and 0.76, respectively, derived from the CoMFA model with steric and electrostatic fields. The CoMSIA model with five different fields yielded values of 0.54, 0.97, and 0.76 for q(2), r(2), and predictive r(2), respectively. The CoMFA and CoMSIA models were used to constrain 3D structures of the nine novel FLT-3 inhibitors. This dual-layer 3D-QSAR model constitutes a valuable tool to easily and quickly screen and optimize novel potential FLT-3 inhibitors for the treatment of acute myeloid leukemia.
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Affiliation(s)
- Kuei-Chung Shih
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
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15
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Xu D, Sun H, Chen Y, Sun L, You Q. Pharmacophore Modeling and in Silico Screening Studies to Design Potential KDR Kinase Inhibitors. CHINESE J CHEM 2011. [DOI: 10.1002/cjoc.201190208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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16
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Wang DH, Qu WL, Shi LQ, Wei J. Molecular docking and pharmacophore model studies of Rho kinase inhibitors. MOLECULAR SIMULATION 2011. [DOI: 10.1080/08927022.2011.554548] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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17
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Insight into analysis of interactions of GW9508 to wild-type and H86F and H137F GPR40: A combined QM/MM study and pharmacophore modeling. J Mol Graph Model 2011; 29:818-25. [DOI: 10.1016/j.jmgm.2011.01.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2010] [Revised: 01/13/2011] [Accepted: 01/13/2011] [Indexed: 02/06/2023]
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18
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Shih KC, Lin CY, Zhou J, Chi HC, Chen TS, Wang CC, Tseng HW, Tang CY. Development of Novel 3D-QSAR Combination Approach for Screening and Optimizing B-Raf Inhibitors in silico. J Chem Inf Model 2010; 51:398-407. [DOI: 10.1021/ci100351s] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Affiliation(s)
- Kuei-Chung Shih
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Chun-Yuan Lin
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
- Research Center for Emerging Viral Infections, Chang Gung University, Taoyuan 33302, Taiwan
| | - Jiayi Zhou
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Hsiao-Chieh Chi
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ting-Shou Chen
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Chun-Chung Wang
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Hsiang-Wen Tseng
- Biomedical Engineering Research Laboratories, Industrial Technology Research Institute, Chutung, Hsinchu, 31040, Taiwan
| | - Chuan-Yi Tang
- Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan
- Department of Computer Science and Information Engineering, Providence University, Taichung 43301, Taiwan
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Jiang Q, Yang Q, Liao C, Zan W, Zang Z. Pharmacophore Modeling and Virtual Screening of Novel Inhibitors for c-Kit Kinase. CHINESE J CHEM 2010. [DOI: 10.1002/cjoc.201090208] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Chen JJ, Liu TL, Yang LJ, Li LL, Wei YQ, Yang SY. Pharmacophore modeling and virtual screening studies of checkpoint kinase 1 inhibitors. Chem Pharm Bull (Tokyo) 2009; 57:704-9. [PMID: 19571415 DOI: 10.1248/cpb.57.704] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
In this study, chemical feature-based 3-dimensional (3D) pharmacophore models of Checkpoint kinase 1 (Chk1) inhibitors were developed based on the known inhibitors of Chk1. The best pharmacophore model Hypo1 was characterized by the best correlation coefficient (0.9577), and the lowest root mean square deviation (0.8871). Hypo1 consists of one hydrogen-bond acceptor, one hydrogen-bond donor, and two hydrophobic features, as well as one excluded volume. This pharmacophore model was further validated by both test set and cross validation methods. A comparison analysis of Hypo1 with chemical features in the active site of Chk1 indicates that the pharmacophore model Hypo1 can correctly reflect the interactions between Chk1 and its ligands. Then Hypo1 was used to screen chemical databases, including Specs and Chinese Nature Product Database (CNPD) for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits. Finally some of the most potent (estimated) compounds were selected from the final refined hits and suggested for further experimental investigation.
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Affiliation(s)
- Jin-Juan Chen
- State Key Laboratory of Biotherapy, West China Hospital, West China School of Pharmacy, Sichuan University
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