1
|
Madhana Priya N, Balasundaram A, Sidharth Kumar N, Udhaya Kumar S, Thirumal Kumar D, Magesh R, Zayed H, George Priya Doss C. Controlling cell proliferation by targeting cyclin-dependent kinase 6 using drug repurposing approach. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2023; 135:97-124. [PMID: 37061342 DOI: 10.1016/bs.apcsb.2023.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2023]
Abstract
Cyclin-dependent kinase 6 (CDK6) is an essential kinase in cell cycle progression, which is a viable target for inhibitors in various malignancies, including breast cancer. This study aimed to virtually screen efficient compounds as new leads in treating breast cancer using a drug repurposing approach. Apoptosis regulatory compounds were taken from the seleckchem database. Molecular docking experiments were carried out in the presence of abemaciclib, a routinely used FDA drug. Compared to conventional drugs, the two compounds demonstrated a higher binding affinity for CDK6. Compounds (N-benzyl-6-[(4-hydroxyphenyl)methyl]-8-(naphthalen-1-ylmethyl)-4,7-dioxo-3,6,9,9a-tetrahydro-2H-pyrazino[1,2-a]pyrimidine-1-carboxamide) and (1'-[4-[1-(4-fluorophenyl)indol-3-yl]butyl]spiro[1H-2-benzofuran-3,4'-piperidine]) were discovered to have an inhibitory effect against CDK6 at -8.49 and -6.78kcal/mol, respectively, compared to -8.09kcal/mol of the control molecule, the interacting residues of these two new compounds were found to fall within the binding site of the CDK6 molecule. Both compounds exhibited equal ADME features compared with abemaciclib and would be well distributed and metabolized by the body with an appropriate druglikeness range. Lastly, molecular dynamics was initiated for 200ns for the selected potent inhibitors and abemaciclib as complexed with CDK6. The RMSD, RMSF, Rg, H-Bond interactions, SASA, PCA, FEL, and MM/PBSA analysis were performed for the complexes to assess the stability, fluctuations, radius of gyration, hydrogen bond interaction, solvent accessibility, essential dynamics, free energy landscape, and MM/PBSA. The selected two compounds are small molecules in the appropriate druglikeness range. The results observed in molecular docking and molecular dynamics simulations were most promising for two compounds, suggesting their potent inhibitory effect against CDK6. We propose that these candidate compounds can undergo in vitro validation and in vivo testing for their further use against cancer.
Collapse
|
2
|
Khan MI, Park T, Imran MA, Gowda Saralamma VV, Lee DC, Choi J, Baig MH, Dong JJ. Development of machine learning models for the screening of potential HSP90 inhibitors. Front Mol Biosci 2022; 9:967510. [PMID: 36339714 PMCID: PMC9626531 DOI: 10.3389/fmolb.2022.967510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 08/15/2022] [Indexed: 11/18/2022] Open
Abstract
Heat shock protein 90 (Hsp90) is a molecular chaperone playing a significant role in the folding of client proteins. This cellular protein is linked to the progression of several cancer types, including breast cancer, lung cancer, and gastrointestinal stromal tumors. Several oncogenic kinases are Hsp90 clients and their activity depends on this molecular chaperone. This makes HSP90 a prominent therapeutic target for cancer treatment. Studies have confirmed the inhibition of HSP90 as a striking therapeutic treatment for cancer management. In this study, we have utilized machine learning and different in silico approaches to screen the KCB database to identify the potential HSP90 inhibitors. Further evaluation of these inhibitors on various cancer cell lines showed favorable inhibitory activity. These inhibitors could serve as a basis for future development of effective HSP90 inhibitors.
Collapse
Affiliation(s)
- Mohd Imran Khan
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Taehwan Park
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Mohammad Azhar Imran
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | | | - Duk Chul Lee
- Department of Family Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Jaehyuk Choi
- BNJBiopharma, Yonsei University International Campus, Incheon, South Korea
| | - Mohammad Hassan Baig
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
- *Correspondence: Jae-June Dong, ; Mohammad Hassan Baig,
| | - Jae-June Dong
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
- *Correspondence: Jae-June Dong, ; Mohammad Hassan Baig,
| |
Collapse
|
3
|
Baig MH, Yousuf M, Khan MI, Khan I, Ahmad I, Alshahrani MY, Hassan MI, Dong JJ. Investigating the Mechanism of Inhibition of Cyclin-Dependent Kinase 6 Inhibitory Potential by Selonsertib: Newer Insights Into Drug Repurposing. Front Oncol 2022; 12:865454. [PMID: 35720007 PMCID: PMC9204300 DOI: 10.3389/fonc.2022.865454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 04/06/2022] [Indexed: 12/23/2022] Open
Abstract
Cyclin-dependent kinases (CDKs) play significant roles in numerous physiological, and are considered an attractive drug target for cancer, neurodegenerative, and inflammatory diseases. In the present study, we have aimed to investigate the binding affinity and inhibitory potential of selonsertib toward CDK6. Using the drug repurposing approach, we performed molecular docking of selonsertib with CDK6 and observed a significant binding affinity. To ascertain, we further performed essential dynamics analysis and free energy calculation, which suggested the formation of a stable selonsertib-CDK6 complex. The in-silico findings were further experimentally validated. The recombinant CDK6 was expressed, purified, and treated with selonsertib. The binding affinity of selonsertib to CDK6 was estimated by fluorescence binding studies and enzyme inhibition assay. The results indicated an appreciable binding of selonsertib against CDK6, which subsequently inhibits its activity with a commendable IC50 value (9.8 μM). We concluded that targeting CDK6 by selonsertib can be an efficient therapeutic approach to cancer and other CDK6-related diseases. These observations provide a promising opportunity to utilize selonsertib to address CDK6-related human pathologies.
Collapse
Affiliation(s)
- Mohammad Hassan Baig
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Mohd. Yousuf
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Mohd. Imran Khan
- Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Imran Khan
- Department of Molecular Biology, Beykoz Institute of Life Sciences and Biotechnology, BezmialemVakif University, Istanbul, Turkey
| | - Irfan Ahmad
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia
| | - Mohammad Y. Alshahrani
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia
| | - Md. Imtaiyaz Hassan
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India
| | - Jae-June Dong
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| |
Collapse
|
4
|
Khan MI, Taehwan P, Cho Y, Scotti M, Priscila Barros de Menezes R, Husain FM, Alomar SY, Baig MH, Dong JJ. Discovery of novel acetylcholinesterase inhibitors through integration of machine learning with genetic algorithm based in silico screening approaches. Front Neurosci 2022; 16:1007389. [PMID: 36937207 PMCID: PMC10020350 DOI: 10.3389/fnins.2022.1007389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 11/08/2022] [Indexed: 03/06/2023] Open
Abstract
Introduction Alzheimer's disease (AD) is the most studied progressive eurodegenerative disorder, affecting 40-50 million of the global population. This progressive neurodegenerative disease is marked by gradual and irreversible declines in cognitive functions. The unavailability of therapeutic drug candidates restricting/reversing the progression of this dementia has severed the existing challenge. The development of acetylcholinesterase (AChE) inhibitors retains a great research focus for the discovery of an anti-Alzheimer drug. Materials and methods This study focused on finding AChE inhibitors by applying the machine learning (ML) predictive modeling approach, which is an integral part of the current drug discovery process. In this study, we have extensively utilized ML and other in silico approaches to search for an effective lead molecule against AChE. Result and discussion The output of this study helped us to identify some promising AChE inhibitors. The selected compounds performed well at different levels of analysis and may provide a possible pathway for the future design of potent AChE inhibitors.
Collapse
Affiliation(s)
- Mohd Imran Khan
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Park Taehwan
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Yunseong Cho
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Marcus Scotti
- Postgraduate Program in Bioactive Natural and Synthetic Products, Federal University of Paraíba, João Pessoa, Brazil
| | | | - Fohad Mabood Husain
- Department of Food Science and Nutrition, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Suliman Yousef Alomar
- Department of Zoology, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Mohammad Hassan Baig
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
- Mohammad Hassan Baig,
| | - Jae-June Dong
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
- *Correspondence: Jae-June Dong,
| |
Collapse
|
5
|
Fourches D, Ash J. 4D- quantitative structure-activity relationship modeling: making a comeback. Expert Opin Drug Discov 2019; 14:1227-1235. [PMID: 31513441 DOI: 10.1080/17460441.2019.1664467] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Introduction: Predictive Quantitative Structure-Activity Relationship (QSAR) modeling has become an essential methodology for rapidly assessing various properties of chemicals. The vast majority of these QSAR models utilize numerical descriptors derived from the two- and/or three-dimensional structures of molecules. However, the conformation-dependent characteristics of flexible molecules and their dynamic interactions with biological target(s) is/are not encoded by these descriptors, leading to limited prediction performances and reduced interpretability. 2D/3D QSAR models are successful for virtual screening, but typically suffer at lead optimization stages. That is why conformation-dependent 4D-QSAR modeling methods were developed two decades ago. However, these methods have always suffered from the associated computational cost. Recently, 4D-QSAR has been experiencing a significant come-back due to rapid advances in GPU-accelerated molecular dynamic simulations and modern machine learning techniques. Areas covered: Herein, the authors briefly review the literature regarding 4D-QSAR modeling and describe its modern workflow called MD-QSAR. Challenges and current limitations are also highlighted. Expert opinion: The development of hyper-predictive MD-QSAR models could represent a disruptive technology for analyzing, understanding, and optimizing dynamic protein-ligand interactions with countless applications for drug discovery and chemical toxicity assessment. Therefore, there has never been a better time and relevance for molecular modeling teams to engage in hyper-predictive MD-QSAR modeling.
Collapse
Affiliation(s)
- Denis Fourches
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University , Raleigh , NC , USA
| | - Jeremy Ash
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University , Raleigh , NC , USA
| |
Collapse
|
6
|
Iglesias J, Saen‐oon S, Soliva R, Guallar V. Computational structure‐based drug design: Predicting target flexibility. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2018. [DOI: 10.1002/wcms.1367] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
| | | | | | - Victor Guallar
- Life Science DepartmentBarcelonaSpain
- ICREA, Passeig Lluís Companys 23BarcelonaSpain
| |
Collapse
|
7
|
Bertazzo M, Bernetti M, Recanatini M, Masetti M, Cavalli A. Fully Flexible Docking via Reaction-Coordinate-Independent Molecular Dynamics Simulations. J Chem Inf Model 2018; 58:490-500. [PMID: 29378136 DOI: 10.1021/acs.jcim.7b00674] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Predicting the geometry of protein-ligand binding complexes is of primary importance for structure-based drug discovery. Molecular dynamics (MD) is emerging as a reliable computational tool for use in conjunction with, or an alternative to, docking methods. However, simulating the protein-ligand binding process often requires very expensive simulations. This drastically limits the practical application of MD-based approaches. Here, we propose a general framework to accelerate the generation of putative protein-ligand binding modes using potential-scaled MD simulations. The proposed dynamical protocol has been applied to two pharmaceutically relevant systems (GSK-3β and the N-terminal domain of HSP90α). Our approach is fully independent of any predefined reaction coordinate (or collective variable). It identified the correct binding mode of several ligands and can thus save valuable computational time in dynamic docking simulations.
Collapse
Affiliation(s)
- Martina Bertazzo
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Università di Bologna , Via Belmeloro 6, 40126, Bologna, Italy.,CompuNet, Istituto Italiano di Tecnologia , Via Morego 30, 16163, Genova, Italy
| | - Mattia Bernetti
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Università di Bologna , Via Belmeloro 6, 40126, Bologna, Italy.,CompuNet, Istituto Italiano di Tecnologia , Via Morego 30, 16163, Genova, Italy
| | - Maurizio Recanatini
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Università di Bologna , Via Belmeloro 6, 40126, Bologna, Italy
| | - Matteo Masetti
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Università di Bologna , Via Belmeloro 6, 40126, Bologna, Italy
| | - Andrea Cavalli
- Department of Pharmacy and Biotechnology, Alma Mater Studiorum-Università di Bologna , Via Belmeloro 6, 40126, Bologna, Italy.,CompuNet, Istituto Italiano di Tecnologia , Via Morego 30, 16163, Genova, Italy
| |
Collapse
|
8
|
Redhead M, Satchell R, McCarthy C, Pollack S, Unitt J. Thermal Shift as an Entropy-Driven Effect. Biochemistry 2017; 56:6187-6199. [DOI: 10.1021/acs.biochem.7b00860] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Martin Redhead
- Bioscience
Department, Sygnature Discovery, Nottingham NG1 1GF, U.K
| | - Rupert Satchell
- Bioscience
Department, Sygnature Discovery, Nottingham NG1 1GF, U.K
| | - Ciara McCarthy
- Bioscience
Department, Sygnature Discovery, Nottingham NG1 1GF, U.K
| | - Scott Pollack
- Bioscience
Department, Sygnature Discovery, Nottingham NG1 1GF, U.K
| | - John Unitt
- Bioscience
Department, Sygnature Discovery, Nottingham NG1 1GF, U.K
| |
Collapse
|
9
|
Zhao Z, Xie L, Bourne PE. Insights into the binding mode of MEK type-III inhibitors. A step towards discovering and designing allosteric kinase inhibitors across the human kinome. PLoS One 2017; 12:e0179936. [PMID: 28628649 PMCID: PMC5476283 DOI: 10.1371/journal.pone.0179936] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Accepted: 06/06/2017] [Indexed: 11/18/2022] Open
Abstract
Protein kinases are critical drug targets for treating a large variety of human diseases. Type-III kinase inhibitors have attracted increasing attention as highly selective therapeutics. Thus, understanding the binding mechanism of existing type-III kinase inhibitors provides useful insights into designing new type-III kinase inhibitors. In this work, we have systematically studied the binding mode of MEK-targeted type-III inhibitors using structural systems pharmacology and molecular dynamics simulation. Our studies provide detailed sequence, structure, interaction-fingerprint, pharmacophore and binding-site information on the binding characteristics of MEK type-III kinase inhibitors. We hypothesize that the helix-folding activation loop is a hallmark allosteric binding site for type-III inhibitors. Subsequently, we screened and predicted allosteric binding sites across the human kinome, suggesting other kinases as potential targets suitable for type-III inhibitors.
Collapse
Affiliation(s)
- Zheng Zhao
- National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, Maryland, United States of America
| | - Lei Xie
- Department of Computer Science, Hunter College, The City University of New York, New York, United States of America
- The Graduate Center, The City University of New York, New York, United States of America
| | - Philip E. Bourne
- National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, Maryland, United States of America
- Office of the Director, National Institutes of Health, Bethesda, Maryland, United States of America
| |
Collapse
|
10
|
Sączewski F, Kornicka A, Balewski Ł. Imidazoline scaffold in medicinal chemistry: a patent review (2012–2015). Expert Opin Ther Pat 2016; 26:1031-48. [DOI: 10.1080/13543776.2016.1210128] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
|