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Nayarisseri A, Abdalla M, Joshi I, Yadav M, Bhrdwaj A, Chopra I, Khan A, Saxena A, Sharma K, Panicker A, Panwar U, Mendonça Junior FJB, Singh SK. Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer. Sci Rep 2024; 14:13251. [PMID: 38858458 PMCID: PMC11164920 DOI: 10.1038/s41598-024-63762-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 05/31/2024] [Indexed: 06/12/2024] Open
Abstract
Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked to persistent human papillomavirus infection. Biomarkers associated with cervical cancer, including VEGF-A, VEGF-B, VEGF-C, VEGF-D, and VEGF-E, show upregulation and are linked to angiogenesis and lymphangiogenesis. This research aims to employ in-silico methods to target tyrosine kinase receptor proteins-VEGFR-1, VEGFR-2, and VEGFR-3, and identify novel inhibitors for Vascular Endothelial Growth Factors receptors (VEGFRs). A comprehensive literary study was conducted which identified 26 established inhibitors for VEGFR-1, VEGFR-2, and VEGFR-3 receptor proteins. Compounds with high-affinity scores, including PubChem ID-25102847, 369976, and 208908 were chosen from pre-existing compounds for creating Deep Learning-based models. RD-Kit, a Deep learning algorithm, was used to generate 43 million compounds for VEGFR-1, VEGFR-2, and VEGFR-3 targets. Molecular docking studies were conducted on the top 10 molecules for each target to validate the receptor-ligand binding affinity. The results of Molecular Docking indicated that PubChem IDs-71465,645 and 11152946 exhibited strong affinity, designating them as the most efficient molecules. To further investigate their potential, a Molecular Dynamics Simulation was performed to assess conformational stability, and a pharmacophore analysis was also conducted for indoctrinating interactions.
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Affiliation(s)
- Anuraj Nayarisseri
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India.
- Bioinformatics Research Laboratory, LeGene Biosciences Pvt Ltd, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India.
| | - Mohnad Abdalla
- Key Laboratory of Chemical Biology (Ministry of Education), Department of Pharmaceutics, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, 44 Cultural West Road, Jinan, 250012, Shandong Province, People's Republic of China
| | - Isha Joshi
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
| | - Manasi Yadav
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
| | - Anushka Bhrdwaj
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India
| | - Ishita Chopra
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
- School of Medicine and Health Sciences, The George Washington University, Ross Hall, 2300 Eye Street, Washington, D.C., NW, 20037, USA
| | - Arshiya Khan
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India
| | - Arshiya Saxena
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
| | - Khushboo Sharma
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India
| | - Aravind Panicker
- In silico Research Laboratory, Eminent Biosciences, 91, Sector-A, Mahalakshmi Nagar, Indore, Madhya Pradesh, 452010, India
| | - Umesh Panwar
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India
| | | | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, 630003, India.
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Panwar U, Murali A, Khan MA, Selvaraj C, Singh SK. Virtual Screening Process: A Guide in Modern Drug Designing. Methods Mol Biol 2024; 2714:21-31. [PMID: 37676591 DOI: 10.1007/978-1-0716-3441-7_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Due to its capacity to drastically cut the cost and time necessary for experimental screening of compounds, virtual screening (VS) has grown to be a crucial component of drug discovery and development. VS is a computational method used in drug design to identify potential drugs from enormous libraries of chemicals. This approach makes use of molecular modeling and docking simulations to assess the small molecule's ability to bind to the desired protein. Virtual screening has a bright future, as high computational power and modern techniques are likely to further enhance the accuracy and speed of the process.
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Affiliation(s)
- Umesh Panwar
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Aarthy Murali
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Mohammad Aqueel Khan
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Chandrabose Selvaraj
- Center for Transdisciplinary Research, Department of Pharmacology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
- Department of Data Sciences, Centre of Biomedical Research, SGPGIMS Campus, Lucknow, Uttar Pradesh, India
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Murali A, Panwar U, Singh SK. Exploring the Role of Chemoinformatics in Accelerating Drug Discovery: A Computational Approach. Methods Mol Biol 2024; 2714:203-213. [PMID: 37676601 DOI: 10.1007/978-1-0716-3441-7_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Cheminformatics and its role in drug discovery is expected to be the privileged approach in handling large number of chemical datasets. This approach contributes toward the pharmaceutical development and assessment of chemical compounds at a faster rate efficiently. Additionally, as technological advancement impacts research, cheminformatics is being used more and more in the field of health science. This chapter describes the concepts of cheminformatics along with its involvement in drug discovery with a case study.
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Affiliation(s)
- Aarthy Murali
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Umesh Panwar
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
- Department of Data Sciences, Centre of Biomedical Research, SGPGIMS Campus, Lucknow, Uttar Pradesh, India
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Khan MA, Singh SK. Atom-based 3D-QSAR and DFT analysis of 5-substituted 2-acylaminothiazole derivatives as HIV-1 latency-reversing agents. J Biomol Struct Dyn 2022:1-16. [PMID: 35971967 DOI: 10.1080/07391102.2022.2112078] [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: 10/15/2022]
Abstract
HIV-1 latency consists of viral DNA; integrated inside the host genome; it remains transcriptional silent. Combined Antiretroviral Therapy (cART) and the host immune system fail to recognize the latency cells or reservoirs, representing a major barrier to eradicating the HIV-1 infection. The Shock and Kill emerged as a promising strategy to target these cells using Latency reversal agents (LRAs); partially succeeded in producing viral mRNA but failed to reduce the size of reservoirs. In this Context, 2-acylaminothiazole class derivatives appeared as promising HIV-1 latency-reversing agents. In this study, we have developed an atom-based 3 D-QSAR model by utilizing the 49 active compounds of the 5-substituted 2-acylaminothiazoles derivatives. These compounds are further randomly divided into training (37) and test (12) datasets, yielding statistically significant R2 (0.90) and Q2 (0.85) results, respectively. The internal and external validation of the model shows highly robust and reliable results. Next, the model was visualized to check the favourable and unfavourable groups in terms of hydrogen bond donor, electron-withdrawing and hydrophobic group on the most active compound 96 and least active compound 30. The investigated model reveals the structural insights required for obtaining more leads that are potent. Finally, DFT calculations on the most and least active compounds were performed to support the atom-based 3 D-QSAR model. Overall, this study will aid in understanding the minimum structural requirement and functional group required for screening the novel potent leads as HIV-1 latency reversal agents.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mohammad Aqueel Khan
- Department of Bioinformatics, Computer Aided Drug Design and Molecular Modelling Lab, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Department of Bioinformatics, Computer Aided Drug Design and Molecular Modelling Lab, Alagappa University, Karaikudi, Tamil Nadu, India
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Structural aspects of triazole derivatives as HSP90 inhibitors for the treatment of cancer: in silico studies. J Biomol Struct Dyn 2022:1-14. [PMID: 35665636 DOI: 10.1080/07391102.2022.2083686] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
HSP90, one important class of chaperons has been intensively investigated as a promising and novel class of drug target for cancer therapy from the past few decades. A series of 2-((4-resorcinolyl)-5-aryl-1, 2, 3-triazol-1-yl) acetate derivatives were taken in the present study for the generation of pharmacophore based models, predictive 3 D-QSAR models, docking and ZINC screening studies against HSP90. The investigation included 30 ligands which emerged DHRRR_1 having survival score of 5.59 was found the most effective pharmacophore model. The generated third PLS factor includes a model with significant Q2, R2, and R2 CV values as 0.62, 0.77, and 0.50, respectively. The molecular docking studies against HSP90 showed interactions with important amino acids such as GLY-97, ASN-106, THR-184, ASN-51, PHE-138 and SER-52 required for HSP90 inhibitory activity. According to the docking analysis compound 34 was the top scoring compound, had a docking score of -10.98 from the series and showed interactions with amino acids likeASP-93, GLY-97, AND ASP-102. Using pharmacophore characteristics, the virtual screening investigation was carried out and DHRRR_1 showed the potential ZINC compounds. The ZINC compounds ZINC72417069 and ZINC77522480 showed best XP docking scores (-8.205 and -7.103 consecutively) and the top-scoring compound ZINC72417069 displayed amino acid binding affinity with GLY-97, ASN-106, and THR-184 against HSP90, PDB ID: 2xjx. These ZINC compounds can be used as target for HSP90. The result of the study may further help to the scientist for the design and development of potential HSP90 inhibitors.
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In-silico studies for the development of novel RET inhibitors for cancer treatment. J Mol Struct 2022. [DOI: 10.1016/j.molstruc.2021.132040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Selvaraj C, Chandra I, Singh SK. Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries. Mol Divers 2021; 26:1893-1913. [PMID: 34686947 PMCID: PMC8536481 DOI: 10.1007/s11030-021-10326-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 09/24/2021] [Indexed: 12/27/2022]
Abstract
The global spread of COVID-19 has raised the importance of pharmaceutical drug development as intractable and hot research. Developing new drug molecules to overcome any disease is a costly and lengthy process, but the process continues uninterrupted. The critical point to consider the drug design is to use the available data resources and to find new and novel leads. Once the drug target is identified, several interdisciplinary areas work together with artificial intelligence (AI) and machine learning (ML) methods to get enriched drugs. These AI and ML methods are applied in every step of the computer-aided drug design, and integrating these AI and ML methods results in a high success rate of hit compounds. In addition, this AI and ML integration with high-dimension data and its powerful capacity have taken a step forward. Clinical trials output prediction through the AI/ML integrated models could further decrease the clinical trials cost by also improving the success rate. Through this review, we discuss the backend of AI and ML methods in supporting the computer-aided drug design, along with its challenge and opportunity for the pharmaceutical industry. From the available information or data, the AI and ML based prediction for the high throughput virtual screening. After this integration of AI and ML, the success rate of hit identification has gained a momentum with huge success by providing novel drugs.
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Affiliation(s)
- Chandrabose Selvaraj
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India.
| | - Ishwar Chandra
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India
| | - Sanjeev Kumar Singh
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India.
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Nayak C, Singh SK. In silico identification of natural product inhibitors against Octamer-binding transcription factor 4 (Oct4) to impede the mechanism of glioma stem cells. PLoS One 2021; 16:e0255803. [PMID: 34613998 PMCID: PMC8494328 DOI: 10.1371/journal.pone.0255803] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 07/23/2021] [Indexed: 02/07/2023] Open
Abstract
Octamer-binding transcription factor 4 (Oct4) is a core regulator in the retention of stemness, invasive, and self-renewal properties in glioma initiating cells (GSCs) and its overexpression inhibits the differentiation of glioma cells promoting tumor cell proliferation. The Pit-Oct-Unc (POU) domain comprising POU-specific domain (POUS) and POU-type homeodomain (POUHD) subdomains is the most critical part of the Oct4 for the generation of induced pluripotent stem cells from somatic cells that lead to tumor initiation, invasion, posttreatment relapse, and therapeutic resistance. Therefore, the present investigation hunts for natural product inhibitors (NPIs) against the POUHD domain of Oct4 by employing receptor-based virtual screening (RBVS) followed by binding free energy calculation and molecular dynamics simulation (MDS). RBVS provided 13 compounds with acceptable ranges of pharmacokinetic properties and good docking scores having key interactions with the POUHD domain. More Specifically, conformational and interaction stability analysis of 13 compounds through MDS unveiled two compounds ZINC02145000 and ZINC32124203 which stabilized the backbone of protein even in the presence of linker and POUS domain. Additionally, ZINC02145000 and ZINC32124203 exhibited stable and strong interactions with key residues W277, R242, and R234 of the POUHD domain even in dynamic conditions. Interestingly, ZINC02145000 and ZINC32124203 established communication not only with the POUHD domain but also with the POUS domain indicating their incredible potency toward thwarting the function of Oct4. ZINC02145000 and ZINC32124203 also reduced the flexibility and escalated the correlations between the amino acid residues of Oct4 evidenced by PCA and DCCM analysis. Finally, our examination proposed two NPIs that can impede the Oct4 function and may help to improve overall survival, diminish tumor relapse, and achieve a cure not only in deadly disease GBM but also in other cancers with minimal side effects.
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Affiliation(s)
- Chirasmita Nayak
- Computer-Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi Tamil Nadu, India
| | - Sanjeev Kumar Singh
- Computer-Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi Tamil Nadu, India
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Selvaraj C, Selvaraj G, Mohamed Ismail R, Vijayakumar R, Baazeem A, Wei DQ, Singh SK. Interrogation of Bacillus anthracis SrtA active site loop forming open/close lid conformations through extensive MD simulations for understanding binding selectivity of SrtA inhibitors. Saudi J Biol Sci 2021; 28:3650-3659. [PMID: 34220215 PMCID: PMC8241892 DOI: 10.1016/j.sjbs.2021.05.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 04/25/2021] [Accepted: 05/02/2021] [Indexed: 02/07/2023] Open
Abstract
Bacillus anthracis is a gram positive, deadly spore forming bacteria causing anthrax and these bacteria having the complex mechanism in the cell wall envelope, which can adopt the changes in environmental conditions. In this, the membrane bound cell wall proteins are said to progressive drug target for the inhibition of Bacillus anthracis. Among the cell wall proteins, the SrtA is one of the important mechanistic protein, which mediate the ligation with LPXTG motif by forming the amide bonds. The SrtA plays the vital role in cell signalling, cell wall formation, and biofilm formations. Inhibition of SrtA leads to rupture of the cell wall and biofilm formation, and that leads to inhibition of Bacillus anthracis and thus, SrtA is core important enzyme to study the inhibition mechanism. In this study, we have examined 28 compounds, which have the inhibitory activity against the Bacillus anthracis SrtA for developing the 3D-QSAR and also, compounds binding selectivity with both open and closed SrtA conformations, obtained from 100 ns of MD simulations. The binding site loop deviate in forming the open and closed gate mechanism is investigated to understand the inhibitory profile of reported compounds, and results show the closed state active site conformations are required for ligand binding specificity. Overall, the present study may offer an opportunity for better understanding of the mechanism of action and can be aided to further designing of a novel and highly potent SrtA inhibitors.
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Affiliation(s)
- Chandrabose Selvaraj
- Department of Bioinformatics, Computer Aided Drug Design and Molecular Modelling Lab, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
- Corresponding authors.
| | - Gurudeeban Selvaraj
- Centre for Research in Molecular Modelling, Concordia University, 5618 Montreal, Quebec, Canada
| | - Randa Mohamed Ismail
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia
- Department of Microbiology and Immunology, Veterinary Research Division, National Research Center (NRC), Giza, Egypt
| | - Rajendran Vijayakumar
- Department of Biology, College of Science in Zulfi, Majmaah University, Majmaah 11952, Saudi Arabia
| | - Alaa Baazeem
- Department of Biology, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
| | - Dong-Qing Wei
- Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Sanjeev Kumar Singh
- Department of Bioinformatics, Computer Aided Drug Design and Molecular Modelling Lab, Science Block, Alagappa University, Karaikudi, Tamil Nadu, India
- Corresponding authors.
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Chemoinformatics and QSAR. Adv Bioinformatics 2021. [DOI: 10.1007/978-981-33-6191-1_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Prabhu SV, Singh SK. Identification of Potential Dual Negative Allosteric Modulators of Group I mGluR Family: A Shape Based Screening, ADME Prediction, Induced Fit Docking and Molecular Dynamics Approach Against Neurodegenerative Diseases. Curr Top Med Chem 2020; 19:2687-2707. [PMID: 31702505 DOI: 10.2174/1568026619666191105112800] [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: 07/18/2019] [Revised: 09/02/2019] [Accepted: 10/01/2019] [Indexed: 01/17/2023]
Abstract
BACKGROUND Glutamate is the principal neurotransmitter in the human brain that exerts its effects through ionotropic glutamate receptors (iGluRs) and metabotropic glutamate receptors (mGluRs). The mGluRs are a class of C GPCRs that play a vital role in various neurobiological functions, mGluR1 and mGluR5 are the two receptors distributed throughout the brain involved in cognition, learning, memory, and other important neurological processes. Dysfunction of these receptors can cause neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, X-fragile syndrome, anxiety, depression, etc., hence these receptors are high profile targets for pharmaceutical industries. OBJECTIVE The objective of our study is to find the novel dual negative allosteric modulators to regulate both mGluR1 and mGluR5. METHODS In this study, shape screening protocol was used to find the dual negative allosteric modulators for both mGluR1 and mGluR5 followed by ADME prediction, induced-fit docking (IFD) and molecular dynamics simulations. Further, DFT analysis and MESP studies were carried out for the selected compounds. RESULTS Around 247 compounds were obtained from the eMolecules database and clustered through the CANVAS module and filtered with ADME properties. Furthermore, IFD revealed that the top four compounds (16059796, 25004252, 4667236 and 11670690) having good protein-ligand interactions and binding free energies. The molecular electrostatic potential of the top compounds shows interactions in the amine group and the oxygen atom in the negative potential regions. Finally, molecular dynamics simulations were performed with all the selected as well as the reported compound 29 indicates that the screened hits have better stability of protein ligand complex. CONCLUSION Hence, from the results, it is evident that top hits 16059796, 25004252, 4667236 and 11670690 could be a novel and potent dual negative allosteric modulators for mGluR1 and mGluR5.
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Affiliation(s)
- Sitrarasu Vijaya Prabhu
- Computer Aided Drug Designing and Molecular Modeling Laboratory, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu-630 004, India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Designing and Molecular Modeling Laboratory, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu-630 004, India
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Kovačević SZ, Karadžić MŽ, Vukić DV, Vukić VR, Podunavac-Kuzmanović SO, Jevrić LR, Ajduković JJ. Toward steroidal anticancer drugs: Non-parametric and 3D-QSAR modeling of 17-picolyl and 17-picolinylidene androstanes with antiproliferative activity on breast adenocarcinoma cells. J Mol Graph Model 2018; 87:240-249. [PMID: 30594032 DOI: 10.1016/j.jmgm.2018.12.010] [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: 09/16/2018] [Revised: 12/11/2018] [Accepted: 12/13/2018] [Indexed: 02/08/2023]
Abstract
The present study is aimed to analyze lipophilicity and ADMET profiles, and to develop field based 3D-QSAR and ligand-based pharmacophore hypothesis for a series of 17α-picolyl and 17(E)-picolinylidene androstane derivatives in order to give detailed structural insights and to highlight important binding features of novel androstane derivatives, as compounds with antiproliferative activity toward breast adenocarcinoma cells. This study can provide guidelines for the rational design of novel potent compounds. Sum of ranking differences (SRD), as a non-parametric method, was applied for compounds ranking. 3D-QSAR methods, including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), were applied to predict the antiproliferative effect on breast adenocarcinoma cells and provide the regions in space where interactive fields may influence the activity. The compounds are ranked so the compounds with the most favorable ADME and lipophilicity features together with significant anticancer activity can be distinguished. The established 3D-QSAR model could be used for design of new compounds with antiproliferative activity on the human ER- breast adenocarcinoma cells. The pharmacophore model is able to accurately predict antiproliferative activity. Generally, the present study provides significant guidelines for further selection, synthesis and rational design of new highly potential androstane derivatives as anticancer drugs.
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Affiliation(s)
- Strahinja Z Kovačević
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia.
| | - Milica Ž Karadžić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Dajana V Vukić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Vladimir R Vukić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | | | - Lidija R Jevrić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Jovana J Ajduković
- University of Novi Sad, Faculty of Sciences, Department of Chemistry, Biochemistry and Environmental Protection, Trg Dositeja Obradovića 3, 21000, Novi Sad, Serbia
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Nayak C, Chandra I, Singh SK. An
in silico
pharmacological approach toward the discovery of potent inhibitors to combat drug resistance HIV‐1 protease variants. J Cell Biochem 2018; 120:9063-9081. [DOI: 10.1002/jcb.28181] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 11/08/2018] [Indexed: 12/15/2022]
Affiliation(s)
- Chirasmita Nayak
- Computer Aided Drug Design and Molecular Modeling, Department of Bioinformatics Alagappa University Karaikudi India
| | - Ishwar Chandra
- Computer Aided Drug Design and Molecular Modeling, Department of Bioinformatics Alagappa University Karaikudi India
| | - Sanjeev Kumar Singh
- Computer Aided Drug Design and Molecular Modeling, Department of Bioinformatics Alagappa University Karaikudi India
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Vijaya Prabhu S, Singh SK. Atom-based 3D-QSAR, induced fit docking, and molecular dynamics simulations study of thieno[2,3-b]pyridines negative allosteric modulators of mGluR5. J Recept Signal Transduct Res 2018; 38:225-239. [PMID: 29806525 DOI: 10.1080/10799893.2018.1476542] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Atom-based three dimensional-quantitative structure-activity relationship (3D-QSAR) model was developed on the basis of 5-point pharmacophore hypothesis (AARRR) with two hydrogen bond acceptors (A) and three aromatic rings for the derivatives of thieno[2,3-b]pyridine, which modulates the activity to inhibit the mGluR5 receptor. Generation of a highly predictive 3D-QSAR model was performed using the alignment of predicted pharmacophore hypothesis for the training set (R2 = 0.84, SD = 0.26, F = 45.8, N = 29) and test set (Q2 = 0.74, RMSE = 0.235, Pearson-R = 0.94, N = 9). The best pharmacophore hypothesis AARRR was selected, and developed three dimensional-quantitative structure activity relationship (3D-QSAR) model also supported the outcome of this study by means of favorable and unfavorable electron withdrawing group and hydrophobic regions of most active compound 42d and least active compound 18b. Following, induced fit docking and binding free energy calculations reveals the reliable binding orientation of the compounds. Finally, molecular dynamics simulations for 100 ns were performed to depict the protein-ligand stability. We anticipate that the resulted outcome could be supportive to discover potent negative allosteric modulators for metabotropic glutamate receptor 5 (mGluR5).
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Affiliation(s)
- Sitrarasu Vijaya Prabhu
- a Department of Bioinformatics, Computer Aided Drug Design and Molecular Modeling Lab , Alagappa University , Karaikudi , India
| | - Sanjeev Kumar Singh
- a Department of Bioinformatics, Computer Aided Drug Design and Molecular Modeling Lab , Alagappa University , Karaikudi , India
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15
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Venkatesan A, Rambabu M, Jayanthi S, Febin Prabhu Dass J. Pharmacophore feature prediction and molecular docking approach to identify novel anti-HCV protease inhibitors. J Cell Biochem 2017; 119:960-966. [PMID: 28691304 DOI: 10.1002/jcb.26262] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 07/05/2017] [Indexed: 02/06/2023]
Abstract
Discovering a potential drug for HCV treatment is a challenging task in the field of drug research. This study initiates with computational screening and modeling of promising ligand molecules. The foremost modeling method involves the identification of novel compound and its molecular interaction based on pharmacophore features. A total of 197 HCV compounds for NS3/4A protein target were screened for our study. The pharmacophore models were generated using PHASE module implemented in Schrodinger suite. The pharmacophore features include one hydrogen bond acceptor, one hydrogen bond donor, and three hydrophobic sites. As a result, based on mentioned hypothesis the model ADHHH.159 corresponds to the CID 59533233. Furthermore, docking was performed using maestro for all the 197 compounds. Among these, the CID 59533313 and 59533233 possess the best binding energy of -11.75 and -10.40 kcal/mol, respectively. The interactions studies indicated that the CID complexed with the NS3/4A protein possess better binding affinity with the other compounds. Further the compounds were subjected to calculate the ADME properties. Therefore, it can be concluded that these two compounds could be a potential alternative drug for the development of HCV.
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Affiliation(s)
- Arthi Venkatesan
- Department of Integrative Biology, School of Biosciences and Technology, VIT University, Vellore, India
| | - Majji Rambabu
- Department of Integrative Biology, School of Biosciences and Technology, VIT University, Vellore, India
| | - Sivaraman Jayanthi
- Department of Integrative Biology, School of Biosciences and Technology, VIT University, Vellore, India
| | - J Febin Prabhu Dass
- Department of Integrative Biology, School of Biosciences and Technology, VIT University, Vellore, India
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Islam MA, Pillay TS. Structural requirements for potential HIV-integrase inhibitors identified using pharmacophore-based virtual screening and molecular dynamics studies. MOLECULAR BIOSYSTEMS 2016; 12:982-93. [PMID: 26809073 DOI: 10.1039/c5mb00767d] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Acquired immunodeficiency syndrome (AIDS) is a life-threatening disease which is a collection of symptoms and infections caused by a retrovirus, human immunodeficiency virus (HIV). There is currently no curative treatment and therapy is reliant on the use of existing anti-retroviral drugs. Pharmacoinformatics approaches have already proven their pivotal role in the pharmaceutical industry for lead identification and optimization. In the current study, we analysed the binding preferences and inhibitory activity of HIV-integrase inhibitors using pharmacoinformatics. A set of 30 compounds were selected as the training set of a total 540 molecules for pharmacophore model generation. The final model was validated by statistical parameters and further used for virtual screening. The best mapped model (R = 0.940, RMSD = 2.847, Q(2) = 0.912, se = 0.498, Rpred(2) = 0.847 and rm(test)(2) = 0.636) explained that two hydrogen bond acceptor and one aromatic ring features were crucial for the inhibition of HIV-integrase. From virtual screening, initial hits were sorted using a number of parameters and finally two compounds were proposed as promising HIV-integrase inhibitors. Drug-likeness properties of the final screened compounds were compared to FDA approved HIV-integrase inhibitors. HIV-integrase structure in complex with the most active and final screened compounds were subjected to 50 ns molecular dynamics (MD) simulation studies to check comparative stability of the complexes. The study suggested that the screened compounds might be promising HIV-integrase inhibitors. The new chemical entities obtained from the NCI database will be subjected to experimental studies to confirm potential inhibition of HIV integrase.
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Affiliation(s)
- Md Ataul Islam
- Department of Chemical Pathology, Faculty of Health Sciences, University of Pretoria and National Health Laboratory Service Tshwane Academic Division, Private Bag X323, Arcadia, Pretoria, 0007, South Africa.
| | - Tahir S Pillay
- Department of Chemical Pathology, Faculty of Health Sciences, University of Pretoria and National Health Laboratory Service Tshwane Academic Division, Private Bag X323, Arcadia, Pretoria, 0007, South Africa. and Division of Chemical Pathology, University of Cape Town, South Africa
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Exploring the inhibitory potential of bioactive compound from Luffa acutangula against NF-κB—A molecular docking and dynamics approach. Comput Biol Chem 2016; 62:29-35. [DOI: 10.1016/j.compbiolchem.2016.03.006] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Revised: 03/23/2016] [Accepted: 03/27/2016] [Indexed: 12/25/2022]
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18
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Bhayye SS, Roy K, Saha A. Pharmacophore generation, atom-based 3D-QSAR, HQSAR and activity cliff analyses of benzothiazine and deazaxanthine derivatives as dual A 2A antagonists/MAO‑B inhibitors. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2016; 27:183-202. [PMID: 26873265 DOI: 10.1080/1062936x.2015.1136840] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Dual inhibition of A2A and MAO-B is an emerging strategy in neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD). In this study, atom-based three-dimensional quantitative structure-activity relationship (3D-QSAR) and hologram quantitative structure-activity relationship (HQSAR) models were generated with benzothiazine and deazaxanthine derivatives. Based on activity against A2A and MAO-B, two statistically significant 3D-QSAR models (r2 = 0.96, q2 = 0.76 and r2 = 0.91, q2 = 0.63) and HQSAR models (r2 = 0.93, q2 = 0.68 and r2 = 0.97, q2 = 0.58) were developed. In an activity cliff analysis, structural outliers were identified by calculating the Mahalanobis distance for a pair of compounds with A2A and MAO-B inhibitory activities. The generated 3D-QSAR and HQSAR models, activity cliff analysis, molecular docking and dynamic studies for dual target protein inhibitors provide key structural scaffolds that serve as building blocks in designing drug-like molecules for neurodegenerative diseases.
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Affiliation(s)
- S S Bhayye
- a Department of Chemical Technology , University of Calcutta , Kolkata , West Bengal , India
| | - K Roy
- b Department of Pharmaceutical Technology , Jadavpur University , Kolkata , West Bengal , India
| | - A Saha
- a Department of Chemical Technology , University of Calcutta , Kolkata , West Bengal , India
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Vanajothi R, Srinivasan P. An anthraquinone derivative from Luffa acutangula induces apoptosis in human lung cancer cell line NCI-H460 through p53-dependent pathway. J Recept Signal Transduct Res 2015; 36:292-302. [PMID: 26585176 DOI: 10.3109/10799893.2015.1108335] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
The current study was designed to evaluate the in vitro antiproliferative activity of 1,8-dihydroxy-4-methylanthracene-9,10-dione (DHMA) isolated from the Luffa acutangula against human non-small cell lung cancer cell line (NCI-H460). Induction of apoptosis and reactive oxygen species (ROS) generation was determined through fluorescence microscopic technique. Quantitative real-time PCR and western blotting analysis was carried out to detect the expression of pro-apoptotic (p53, p21, caspase-3, Bax, GADD45A, and ATM) and anti-apoptotic (NF-κB) proteins in NCI-H460 cell line. In silico studies also performed to predict the binding mechanism of DHMA with MDM2-p53 protein. The DHMA inhibited the cell viability of NCI-H460 cells in a dose-dependent manner with an IC(50) of about 50 µg/ml. It significantly reduced cell viability correlated with induction of apoptosis, which was associated with ROS generation. The apoptotic cell death was further confirmed through dual staining and DNA fragmentation assay. DHMA significantly increased the expression of anti-apoptotic protein such as p53, p21, Bax, and caspase-3 but downregulated the expression of NF-κB in NCI-H460 cell line. In silico studies demonstrate that DHMA formed hydrogen bond interaction with key residues Trp26, Phe55 and Lys24 by which it disrupt the binding of p53 with MDM2 receptor. These findings suggested that DHMA induces apoptosis in NCI-H460 via a p53-dependent pathway. This the first study on cytotoxic and apoptosis inducing activity of DHMA from L. acutangula against NCI-H460 cell line. Therefore, DHMA has therapeutic potential for lung cancer treatment.
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Affiliation(s)
| | - Pappu Srinivasan
- a Department of Bioinformatics and.,b Department of Animal Health and Management , Alagappa University , Karaikudi , Tamilnadu , India
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20
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Su M, Tan J, Lin CY. Development of HIV-1 integrase inhibitors: recent molecular modeling perspectives. Drug Discov Today 2015. [PMID: 26220090 DOI: 10.1016/j.drudis.2015.07.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Of the three viral enzymes essential to HIV replication, HIV-1 integrase (IN) is gaining popularity as a target for the antiviral therapy of AIDS. Substantial work focusing on IN has been done over the past three decades, which has facilitated and led to the approval of three drugs. Here, we discuss in detail the development of IN inhibitors between January 2012 and May 2014, with a particular focus on molecular simulation. We highlight controversial aspects of computational drug design and refer to alternative practices where appropriate. The analysis of these computational approaches provides some useful clues to the possible future discovery of novel IN inhibitors.
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Affiliation(s)
- Min Su
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China
| | - Jianjun Tan
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China.
| | - Chun-Yuan Lin
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan.
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Atom-based QSAR and 3D QSAR using pharmacophore based alignment for discovery of nimesulide-derived SKBR-3 cell line inhibitors. Med Chem Res 2015. [DOI: 10.1007/s00044-014-1187-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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22
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Vijayalakshmi P, Selvaraj C, Shafreen RMB, Singh SK, Pandian SK, Daisy P. Ligand-based pharmacophore modelling and screening of DNA minor groove binders targeting Staphylococcus aureus. J Mol Recognit 2015; 27:429-37. [PMID: 24895275 DOI: 10.1002/jmr.2363] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2013] [Revised: 01/20/2014] [Accepted: 01/21/2014] [Indexed: 11/07/2022]
Abstract
The recognition of DNA by small molecules is of special importance in the design of new drugs. Many natural and synthetic compounds have the ability to interact with the minor groove of DNA. In the present study, identification of minor groove binding compounds was attained by the combined approach of pharmacophore modelling, virtual screening and molecular dynamics approach. Experimentally reported 32 minor groove binding compounds were used to develop the pharmacophore model. Based on the fitness score, best three pharmacophore hypotheses were selected and used as template for screening the compounds from drug bank database. This pharmacophore-based screening provides many compounds with the same pharmacological properties. All these compounds were subjected to four phases of docking protocols with combined Glide-quantum-polarized ligand docking approach. Molecular dynamics results indicated that selected compounds are more active and showed good interaction in the binding site of DNA. Based on the scoring parameters and energy values, the best compounds were selected, and antibacterial activity of these compounds was identified using in vitro antimicrobial techniques.
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Affiliation(s)
- Periyasamy Vijayalakshmi
- Bioinformatics Centre (BIF), PG and Research Department of Biotechnology and Bioinformatics, Holy Cross College (Autonomous), Tiruchirappalli, 620002, Tamil Nadu, India
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Suryanarayanan V, Singh SK. Assessment of dual inhibition property of newly discovered inhibitors against PCAF and GCN5 throughin silicoscreening, molecular dynamics simulation and DFT approach. J Recept Signal Transduct Res 2014; 35:370-80. [DOI: 10.3109/10799893.2014.956756] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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24
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Reddy KK, Singh SK. Combined ligand and structure-based approaches on HIV-1 integrase strand transfer inhibitors. Chem Biol Interact 2014; 218:71-81. [DOI: 10.1016/j.cbi.2014.04.011] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2014] [Revised: 04/11/2014] [Accepted: 04/16/2014] [Indexed: 11/25/2022]
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25
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Reddy KK, Singh P, Singh SK. Blocking the interaction between HIV-1 integrase and human LEDGF/p75: mutational studies, virtual screening and molecular dynamics simulations. MOLECULAR BIOSYSTEMS 2014; 10:526-36. [DOI: 10.1039/c3mb70418a] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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26
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Suryanarayanan V, Singh SK, Tripathi SK, Selvaraj C, Reddy KK, Karthiga A. A three-dimensional chemical phase pharmacophore mapping, QSAR modelling and electronic feature analysis of benzofuran salicylic acid derivatives as LYP inhibitors. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2013; 24:1025-1040. [PMID: 23987088 DOI: 10.1080/1062936x.2013.821421] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Lymphoid tyrosine phosphatase (LYP), encoded by the PTPN22 gene, has a critical negative regulatory role in T-cell antigen receptor (TCR) and emerged as a promising drug target for human autoimmune diseases. A five-point pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and two aromatic ring features was generated for a series of benzofuran salicylic acid derivatives as LYP inhibitors in order to elucidate their anti-autoimmune activity. The generated pharmacophore yielded a significant 3D-QSAR model with r(2) of 0.9146 for a training set of 27 compounds. The model also showed excellent predictive power with Q(2) of 0.7068 for a test set of eight compounds. The investigation of the 3D-QSAR model has revealed the structural insights which could lead to more potent analogues. The most active and inactive compounds were further subjected to electronic structure analysis using density functional theory (DFT) at B3LYP/3-21(∗)G level to support the 3D-QSAR predictions. The results obtained from this study are expected to be useful in the proficient design and development of benzofuran salicylic acid derivatives as inhibitors of LYP.
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Affiliation(s)
- V Suryanarayanan
- a Computer Aided Drug Design and Molecular Modelling Lab, Department of Bioinformatics , Alagappa University , Tamil Nadu , India
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27
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Selvaraj C, Singh SK. Validation of potential inhibitors for SrtA against Bacillus anthracis by combined approach of ligand-based and molecular dynamics simulation. J Biomol Struct Dyn 2013; 32:1333-49. [PMID: 23869520 DOI: 10.1080/07391102.2013.818577] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
The development of SrtA inhibitors targeting the biothreat organism namely Bacillus anthracis was achieved by the combined approach of pharmacophore modeling, binding interactions, electron transferring capacity, ADME, and Molecular dynamics studies. In this study, experimentally reported Ba-SrtA inhibitors (pyridazinone and pyrazolethione derivatives) were considered for the development of enhanced pharmacophoric model. The obtained AAAHR hypothesis was a pure theoretical concept that accounts for common molecular interaction network present in experimentally active pyridazinone and pyrazolethione derivatives. Pharmacophore-based screening of AAAHR hypothesis provides several new compounds, and those compounds were treated with four phases of docking protocols with combined Glide-QPLD docking approach. In this approach, scoring and charge accuracy variations were seen to be dominated by QM/MM approach through the allocation of partial charges. Finally, we reported the best compounds from binding db, Chembridge db, and Toslab based on scoring values, energy parameters, electron transfer reaction, ADME, and cell adhesion inhibition activity. The dynamic state of interaction and binding energy assess that new compounds are more active inside the binding pocket and these compounds on experimental validations will survive as better inhibitors for targeting the cell adhesion mechanism of Ba-SrtA.
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Affiliation(s)
- Chandrabose Selvaraj
- a Computer Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Science Block , Alagappa University , Karaikudi 630004 , Tamilnadu , India
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Reddy KK, Singh SK, Tripathi SK, Selvaraj C, Suryanarayanan V. Shape and pharmacophore-based virtual screening to identify potential cytochrome P450 sterol 14α-demethylase inhibitors. J Recept Signal Transduct Res 2013; 33:234-43. [PMID: 23638723 DOI: 10.3109/10799893.2013.789912] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Sterol 14α-demethylase (CYP51) is a cytochrome P450 heme thiolate containing enzyme involved in biosynthesis of membrane sterols, including sterol in animals, ergosterol in fungi, and a variety of C24-modified sterols in plants and protozoa. Several clinical drugs have been developed to reduce the impact of fungal diseases, but their clinical uses have been limited by the emergence of drug resistance and insufficiencies in their antifungal activity. Therefore, in order to identify potential CYP51 inhibitors, we have implemented a virtual screening (VS) protocol by using both phase shape and pharmacophore model (AHHRR) against Asinex, ChemBridge and Maybridge databases. A filtering protocol, including Lipinski filter, number of rotatable bonds and different precisions of molecular docking was applied in hits selection. The results indicated that both shape-based and pharmacophore-based screening yielded the best result with potential inhibitors. The searched compounds were also evaluated with ADME properties, which show excellent pharmacokinetic properties under the acceptable range. We identified potential CYP51 inhibitors for further investigation, they could also be employed to design ligands with enhanced inhibitory potencies and to predict the potencies of analogs to guide synthesis/or prepare synthetic antifungal analogs against CYP51.
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Affiliation(s)
- Karnati Konda Reddy
- Computer-Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, India
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29
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Structural features of GABAA receptor antagonists: pharmacophore modeling and 3D-QSAR studies. Med Chem Res 2013. [DOI: 10.1007/s00044-013-0583-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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30
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Reddy KK, Singh SK, Tripathi SK, Selvaraj C. Identification of potential HIV-1 integrase strand transfer inhibitors: in silico virtual screening and QM/MM docking studies. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2013; 24:581-595. [PMID: 23521430 DOI: 10.1080/1062936x.2013.772919] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
HIV-1 integrase (IN) is a retroviral enzyme that catalyses integration of the reverse-transcribed viral DNA into the host genome, which is necessary for efficient viral replication. In this study, we have performed an in silico virtual screening for the identification of potential HIV-1 IN strand transfer (ST) inhibitors. Pharmacophore modelling and atom-based 3D-QSAR studies were carried out for a series of compounds belonging to 3-Hydroxypyrimidine-2,4-diones. Based on the ligand-based pharmacophore model, we obtained a five-point pharmacophore with two hydrogen bond acceptors (A), one hydrogen bond donor (D), one hydrophobic group (H) and one aromatic ring (R) as pharmacophoric features. The pharmacophore hypothesis AADHR was used as a 3D query in a sequential virtual screening study to filter small molecule databases Maybridge, ChemBridge and Asinex. Hits matching with pharmacophore hypothesis AADHR were retrieved and passed progressively through Lipinski's rule of five filtering, molecular docking and hierarchical clustering. The five compounds with best hits with novel and diverse chemotypes were subjected to QM/MM docking, which showed improved docking accuracy. We further performed molecular dynamics simulation and found three compounds that form stable interactions with key residues. These compounds could be used as a leads for further drug development and rational design of HIV-1 IN inhibitors.
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Affiliation(s)
- K K Reddy
- Computer-Aided Drug Design and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi, Tamil Nadu, India
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31
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In silico screening of indinavir-based compounds targeting proteolytic activity in HIV PR: binding pocket fit approach. Med Chem Res 2011. [DOI: 10.1007/s00044-011-9941-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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