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González-Esparragoza D, Carrasco-Carballo A, Rosas-Murrieta NH, Millán-Pérez Peña L, Luna F, Herrera-Camacho I. In Silico Analysis of Protein-Protein Interactions of Putative Endoplasmic Reticulum Metallopeptidase 1 in Schizosaccharomyces pombe. Curr Issues Mol Biol 2024; 46:4609-4629. [PMID: 38785548 PMCID: PMC11120530 DOI: 10.3390/cimb46050280] [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: 02/28/2024] [Revised: 04/26/2024] [Accepted: 05/07/2024] [Indexed: 05/25/2024] Open
Abstract
Ermp1 is a putative metalloprotease from Schizosaccharomyces pombe and a member of the Fxna peptidases. Although their function is unknown, orthologous proteins from rats and humans have been associated with the maturation of ovarian follicles and increased ER stress. This study focuses on proposing the first prediction of PPI by comparison of the interologues between humans and yeasts, as well as the molecular docking and dynamics of the M28 domain of Ermp1 with possible target proteins. As results, 45 proteins are proposed that could interact with the metalloprotease. Most of these proteins are related to the transport of Ca2+ and the metabolism of amino acids and proteins. Docking and molecular dynamics suggest that the M28 domain of Ermp1 could hydrolyze leucine and methionine residues of Amk2, Ypt5 and Pex12. These results could support future experimental investigations of other Fxna peptidases, such as human ERMP1.
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Affiliation(s)
- Dalia González-Esparragoza
- Laboratorio de Bioquímica y Biología Molecular, Centro de Química del Instituto de Ciencias (ICUAP), Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico; (D.G.-E.); (N.H.R.-M.); (L.M.-P.P.)
- Laboratorio de Elucidación y Síntesis en Química Orgánica, Instituto de Ciencias de la Universidad Autónoma de Puebla (ICUAP), Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico
| | - Alan Carrasco-Carballo
- Laboratorio de Elucidación y Síntesis en Química Orgánica, Instituto de Ciencias de la Universidad Autónoma de Puebla (ICUAP), Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico
- Consejo Nacional de Humanidades Ciencia y Tecnología, Instituto de Ciencias de la Universidad Autónoma de Puebla (ICUAP), Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico
| | - Nora H. Rosas-Murrieta
- Laboratorio de Bioquímica y Biología Molecular, Centro de Química del Instituto de Ciencias (ICUAP), Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico; (D.G.-E.); (N.H.R.-M.); (L.M.-P.P.)
| | - Lourdes Millán-Pérez Peña
- Laboratorio de Bioquímica y Biología Molecular, Centro de Química del Instituto de Ciencias (ICUAP), Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico; (D.G.-E.); (N.H.R.-M.); (L.M.-P.P.)
| | - Felix Luna
- Laboratorio de Neuroendocrinología, Facultad de Ciencias Químicas, Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico;
| | - Irma Herrera-Camacho
- Laboratorio de Bioquímica y Biología Molecular, Centro de Química del Instituto de Ciencias (ICUAP), Benemérita Universidad Autónoma de Puebla, Puebla 72570, Mexico; (D.G.-E.); (N.H.R.-M.); (L.M.-P.P.)
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Amala M, Nagarajan H, Ahila M, Nachiappan M, Veerapandiyan M, Vetrivel U, Jeyakanthan J. Unveiling the intricacies of allosteric regulation in aspartate kinase from the Wolbachia endosymbiont of Brugia Malayi: Mechanistic and therapeutic insights. Int J Biol Macromol 2024; 267:131326. [PMID: 38569988 DOI: 10.1016/j.ijbiomac.2024.131326] [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: 09/10/2023] [Revised: 03/04/2024] [Accepted: 03/31/2024] [Indexed: 04/05/2024]
Abstract
Aspartate kinase (AK), an enzyme from the Wolbachia endosymbiont of Brugia malayi (WBm), plays a pivotal role in the bacterial cell wall and amino acid biosynthesis, rendering it an attractive candidate for therapeutic intervention. Allosteric inhibition of aspartate kinase is a prevalent mode of regulation across microorganisms and plants, often modulated by end products such as lysine, threonine, methionine, or meso-diaminopimelate. The intricate and diverse nature of microbial allosteric regulation underscores the need for rigorous investigation. This study employs a combined experimental and computational approach to decipher the allosteric regulation of WBmAK. Molecular Dynamics (MD) simulations elucidate that ATP (cofactor) and ASP (substrate) binding induce a closed conformation, promoting enzymatic activity. In contrast, the binding of lysine (allosteric inhibitor) leads to enzyme inactivation and an open conformation. The enzymatic assay demonstrates the optimal activity of WBmAK at 28 °C and a pH of 8.0. Notably, the allosteric inhibition study highlights lysine as a more potent inhibitor compared to threonine. Importantly, this investigation sheds light on the allosteric mechanism governing WBmAK and imparts novel insights into structure-based drug discovery, paving the way for the development of effective inhibitors against filarial pathogens.
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Affiliation(s)
- Mathimaran Amala
- Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi 630004, Tamil Nadu, India
| | - Hemavathy Nagarajan
- Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi 630004, Tamil Nadu, India
| | - Mathimaran Ahila
- Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi 630004, Tamil Nadu, India
| | - Mutharasappan Nachiappan
- Structural and Computational Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), Aruna Asaf Ali Road, New Delhi 110 067, India
| | - Malaisamy Veerapandiyan
- Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi 630004, Tamil Nadu, India
| | - Umashankar Vetrivel
- Virology & Biotechnology/Bioinformatics Division, ICMR-National Institute for Research in Tuberculosis, Chennai, Tamil Nadu 600 031, India
| | - Jeyaraman Jeyakanthan
- Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi 630004, Tamil Nadu, India.
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Das S, Halder D, Jeyaprakash RS. Computational-guided approach for identification of PI3K alpha inhibitor in the treatment of hepatocellular carcinoma by virtual screening and water map analysis. J Biomol Struct Dyn 2024:1-23. [PMID: 38197431 DOI: 10.1080/07391102.2023.2300131] [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: 10/16/2023] [Accepted: 12/22/2023] [Indexed: 01/11/2024]
Abstract
Hepatocellular carcinoma (HCC) is one of the most deadly disorders, with a relative survival rate of 36% in the last 5 years. After an extensive literature survey and pathophysiology analysis, PI3Kα was found to be a promising biological target as PIK3CA gene upregulation was observed in HCC, resulting in the loss of apoptosis of cells, which leads to uncontrollable growth and proliferation. Due to superior selectivity and promising therapeutic activity, the PI3K-targeted molecule library was selected, and the ligand preparation was executed. The study mainly focused on e-pharmacophore development, virtual screening and receptor-ligand docking analysis. Then, MMGBSA and ADME prediction analysis was performed with the top 10 molecules; for further analysis of ligand-receptor binding affinity at the catalytic binding site, induced fit docking was performed with the top two molecules. The analysis of quantum chemical stability descriptors, i.e., frontier molecular orbital analysis, was performed followed by molecular dynamics simulation of 100 ns to better understand the ligand-receptor binding. In this study, water map analysis played a significant role in the hit optimization and analysis of the thermodynamic properties of the receptor-ligand complex. The two hit molecules K894-1435 and K894-1045 represented superior docking scores, enhanced stability, and inhibitory action targeting Valine 851 amino acid residue at the catalytic binding site. Hence, the study has significance for the quest for selective PI3Kα inhibitors through the process of hit-to-lead optimization.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Subham Das
- Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Debojyoti Halder
- Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - R S Jeyaprakash
- Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
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Kaczor AA, Zięba A, Matosiuk D. The application of WaterMap-guided structure-based virtual screening in novel drug discovery. Expert Opin Drug Discov 2024; 19:73-83. [PMID: 37807912 DOI: 10.1080/17460441.2023.2267015] [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: 07/17/2023] [Accepted: 10/02/2023] [Indexed: 10/10/2023]
Abstract
INTRODUCTION Nowadays, it is widely accepted that water molecules play a key role in binding a ligand to a molecular target. Neglecting water molecules in the process of molecular recognition was the result of several failures of the structure-based drug discovery campaigns. The application of WaterMap, in particular WaterMap-guided molecular docking, enables the reasonably accurate and quick description of the location and energetics of water molecules at the ligand-protein interface. AREAS COVERED In this review, the authors shortly discuss the importance of water in drug design and discovery and provide a brief overview of the computational approaches used to predict the solvent-related effects for the purposes of presenting WaterMap in the context of other available techniques and tools. A concise description of WaterMap concept is followed by the presentation of WaterMap-assisted virtual screening literature published between 2013 and 2023. EXPERT OPINION In recent years, WaterMap software has been extensively used to support structure-based drug design, in particular structure-based virtual screening. Indeed, it is a useful tool to rescore docking results considering water molecules in the binding pocket. Although WaterMap allows for the consideration of the dynamic behavior of water molecules in the binding site, for best accuracy, its application in conjunction with other techniques such as molecular mechanics-generalized Born surface area of FEP (Free Energy Perturbation) is recommended.
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Affiliation(s)
- Agnieszka A Kaczor
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modeling Laboratory, Faculty of Pharmacy, Lublin, Poland
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Agata Zięba
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modeling Laboratory, Faculty of Pharmacy, Lublin, Poland
| | - Dariusz Matosiuk
- Department of Synthesis and Chemical Technology of Pharmaceutical Substances with Computer Modeling Laboratory, Faculty of Pharmacy, Lublin, Poland
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Jin H, Kim J, Lee O, Kim H, No KT. Leveraging the Fragment Molecular Orbital Method to Explore the PLK1 Kinase Binding Site and Polo-Box Domain for Potent Small-Molecule Drug Design. Int J Mol Sci 2023; 24:15639. [PMID: 37958623 PMCID: PMC10650754 DOI: 10.3390/ijms242115639] [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: 09/15/2023] [Revised: 10/19/2023] [Accepted: 10/25/2023] [Indexed: 11/15/2023] Open
Abstract
Polo-like kinase 1 (PLK1) plays a pivotal role in cell division regulation and emerges as a promising therapeutic target for cancer treatment. Consequently, the development of small-molecule inhibitors targeting PLK1 has become a focal point in contemporary research. The adenosine triphosphate (ATP)-binding site and the polo-box domain in PLK1 present crucial interaction sites for these inhibitors, aiming to disrupt the protein's function. However, designing potent and selective small-molecule inhibitors can be challenging, requiring a deep understanding of protein-ligand interaction mechanisms at these binding sites. In this context, our study leverages the fragment molecular orbital (FMO) method to explore these site-specific interactions in depth. Using the FMO approach, we used the FMO method to elucidate the molecular mechanisms of small-molecule drugs binding to these sites to design PLK1 inhibitors that are both potent and selective. Our investigation further entailed a comparative analysis of various PLK1 inhibitors, each characterized by distinct structural attributes, helping us gain a better understanding of the relationship between molecular structure and biological activity. The FMO method was particularly effective in identifying key binding features and predicting binding modes for small-molecule ligands. Our research also highlighted specific "hot spot" residues that played a critical role in the selective and robust binding of PLK1. These findings provide valuable insights that can be used to design new and effective PLK1 inhibitors, which can have significant implications for developing anticancer therapeutics.
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Affiliation(s)
- Haiyan Jin
- The Interdisciplinary Graduate Program in Integrative Biotechnology & Translational Medicine, Yonsei University, Incheon 21983, Republic of Korea; (H.J.); (O.L.)
| | - Jongwan Kim
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
- Bioinformatics and Molecular Design Research Center (BMDRC), Incheon 21983, Republic of Korea;
| | - Onju Lee
- The Interdisciplinary Graduate Program in Integrative Biotechnology & Translational Medicine, Yonsei University, Incheon 21983, Republic of Korea; (H.J.); (O.L.)
| | - Hyein Kim
- Bioinformatics and Molecular Design Research Center (BMDRC), Incheon 21983, Republic of Korea;
| | - Kyoung Tai No
- The Interdisciplinary Graduate Program in Integrative Biotechnology & Translational Medicine, Yonsei University, Incheon 21983, Republic of Korea; (H.J.); (O.L.)
- Department of Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
- Bioinformatics and Molecular Design Research Center (BMDRC), Incheon 21983, Republic of Korea;
- Baobab AiBIO Co., Ltd., Incheon 21983, Republic of Korea
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Panchalingam S, Kasivelu G, Jayaraman M, Kumar R, Kalimuthu S, Jeyaraman J. Differential gene expression analysis combined with molecular dynamics simulation study to elucidate the novel potential biomarker involved in pulmonary TB. Microb Pathog 2023; 182:106266. [PMID: 37482113 DOI: 10.1016/j.micpath.2023.106266] [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: 05/31/2023] [Revised: 06/21/2023] [Accepted: 07/21/2023] [Indexed: 07/25/2023]
Abstract
Tuberculosis (TB) is a lethal multisystem disease that attacks the lungs' first line of defense. A substantial threat to public health and a primary cause of death is pulmonary TB. This study aimed to identify and investigate the probable differentially expressed genes (DEGs) primarily involved in Pulmonary TB. Accordingly, three independent gene expression data sets, numbered GSE139825, GSE139871, and GSE54992, were utilized for this purpose. The identified DEGs were used for bioinformatics-based analysis, including physical gene interaction, Gene Ontology (GO), network analysis and pathway studies using the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The computational analysis predicted that TNFAIP6 is the significant DEG in the gene expression profiling of TB datasets. According to gene ontology analysis, TNFAIP6 is also essential in injury and inflammation. Further, TNFA1P6 is strongly linked to arsenic poisoning, evident from the results of NetworkAnalyst, a comprehensive and interactive platform for gene expression profiling via network visual analytics. As a result, the TNFAIP6 gene was ultimately chosen as a candidate DEG and subsequently employed for in silico structural characterization studies. The tertiary structure of TNFAIP6 was modelled using the ROBETTA server, followed by validation with SAVES and ProSA webserver. Additionally, structural dynamic studies, including molecular dynamics simulation (MDS) and essential dynamics analysis, including principal component (PC) based free energy landscape (FEL) analysis, was used for checking the stability of TNFAIP6 models. The dynamics result established the structural rigidity of modelled TNFAIP6 through RMSD, RMSF and RoG results. The FEL analysis revealed the restricted conformational flexibility of TNFAIP6 by displaying a single minimum energy basin in the contour plot. The comprehensive computational analysis established that TNFAIP6 could serve as a viable biomarker to assess the severity of pulmonary TB.
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Affiliation(s)
- Santhiya Panchalingam
- Centre for Ocean Research, Sathyabama Institute of Science and Technology (Deemed to Be University), Chennai, 600 119, Tamil Nadu, India
| | - Govindaraju Kasivelu
- Centre for Ocean Research, Sathyabama Institute of Science and Technology (Deemed to Be University), Chennai, 600 119, Tamil Nadu, India.
| | - Manikandan Jayaraman
- Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630 004, Tamil Nadu, India
| | - Rajalakshmi Kumar
- Mahatma Gandhi Medical Advanced Research Institute, Sri Balaji Vidyapeeth (Deemed to Be University), Pillayarkuppam, Puducherry, 607 402, India
| | | | - Jeyakanthan Jeyaraman
- Structural Biology and Biocomputing Lab, Department of Bioinformatics, Alagappa University, Karaikudi, 630 004, Tamil Nadu, India.
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Pathfinder-Driven Chemical Space Exploration and Multiparameter Optimization in Tandem with Glide/IFD and QSAR-Based Active Learning Approach to Prioritize Design Ideas for FEP+ Calculations of SARS-CoV-2 PL pro Inhibitors. Molecules 2022; 27:molecules27238569. [PMID: 36500659 PMCID: PMC9741453 DOI: 10.3390/molecules27238569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 11/25/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022] Open
Abstract
A global pandemic caused by the SARS-CoV-2 virus that started in 2020 and has wreaked havoc on humanity still ravages up until now. As a result, the negative impact of travel restrictions and lockdowns has underscored the importance of our preparedness for future pandemics. The main thrust of this work was based on addressing this need by traversing chemical space to design inhibitors that target the SARS-CoV-2 papain-like protease (PLpro). Pathfinder-based retrosynthesis analysis was used to generate analogs of GRL-0617 using commercially available building blocks by replacing the naphthalene moiety. A total of 10 models were built using active learning QSAR, which achieved good statistical results such as an R2 > 0.70, Q2 > 0.64, STD Dev < 0.30, and RMSE < 0.31, on average for all models. A total of 35 ideas were further prioritized for FEP+ calculations. The FEP+ results revealed that compound 45 was the most active compound in this series with a ΔG of −7.28 ± 0.96 kcal/mol. Compound 5 exhibited a ΔG of −6.78 ± 1.30 kcal/mol. The inactive compounds in this series were compound 91 and compound 23 with a ΔG of −5.74 ± 1.06 and −3.11 ± 1.45 kcal/mol. The combined strategy employed here is envisaged to be of great utility in multiparameter lead optimization efforts, to traverse chemical space, maintaining and/or improving the potency as well as the property space of synthetically aware design ideas.
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Chen L, Hu B, Wang H, Li W, Wang S, Luan J, Liu H, Wang J, Cheng M. Selectivity mechanism of muscarinic acetylcholine receptor antagonism through in silico investigation. Phys Chem Chem Phys 2022; 24:26269-26287. [PMID: 36281693 DOI: 10.1039/d2cp02972c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Structures of muscarinic acetylcholine receptors illustrate the strikingly high degree of homology of the residues among isoforms, thus leading to difficulty in achieving subtype selectivity when targeting these receptors and causing undesired side effects when treating the corresponding diseases. Considering the urgent need for more selective and potency therapies, this study is aimed at revealing the selectivity mechanism against M4/5 via in silico strategies, revealing crucial molecular interactions such as hydrogen bonds and pi-cation interaction formed between the key residues TYR416, ASN417, and TRP435 of M4, respectively, hydrophobic pocket formed by the key residues, especially CYS484 of M5. Besides, the water around TYR416M4 and ASN459M5, which can be replaced by substituent groups which can form the hydrogen bond interaction network by simulated bridging water and the water around ASP112M4, whose replacement maybe not contribute to the increase in binding affinity of the compound, may affect the inhibitory selectivity among M4/5 in the aspect of the solvent. Moreover, from the point of inhibitors, compounds with a positively ionizable group could selectively bind to M4 receptors, while hydrophobic molecules may bind preferably to M5. We believe that the current study would provide a basis for the design of subsequent M4/5 selective antagonists.
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Affiliation(s)
- Lu Chen
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
| | - Baichun Hu
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
| | - Hanxun Wang
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
| | - Weixia Li
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
| | - Shizun Wang
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
| | - Jiasi Luan
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Medical Devices, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
| | - Haihan Liu
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
| | - Jian Wang
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
| | - Maosheng Cheng
- Key Laboratory of Structure-Based Drug Design & Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China.
- Key Laboratory of Intelligent Drug Design and New Drug Discovery of Liaoning Province, Shenyang Pharmaceutical University, Shenyang 110016, China
- School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People's Republic of China
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Jayaprakash P, Biswal J, Rangaswamy R, Jeyakanthan J. Designing of potent anti-diabetic molecules by targeting SIK2 using computational approaches. Mol Divers 2022:10.1007/s11030-022-10470-0. [PMID: 35727438 DOI: 10.1007/s11030-022-10470-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 05/27/2022] [Indexed: 10/18/2022]
Abstract
Diabetes mellitus (DM) is one of the major health problems worldwide. WHO have estimated that 439 million people may have DM by the year 2030. Several classes of drugs such as sulfonylureas, meglitinides, thiazolidinediones etc. are available to manage this disease, however, there is no cure for this disease. Salt inducible kinase 2 (SIK2) is expressed several folds in adipose tissue than in normal tissues and thus SIK2 is one of the attractive targets for DM treatment. SIK2 inhibition improves glucose homeostasis. Several analogues have been reported and experimentally proven against SIK for DM treatment. But, identifying potential SIK2 inhibitors with improved efficacy and good pharmacokinetic profiles will be helpful for the effective treatment of DM. The objective of the present study is to identify selective SIK2 inhibitors with good pharmacokinetic profiles. Due to the unavailability of SIK2 structure, the modeled structure of SIK2 will be an important to understand the atomic level of SIK2 inhibitors in the binding site pocket. In this study, different molecular modeling studies such as Homology Modeling, Molecular Docking, Pharmacophore-based virtual screening, MD simulations, Density Functional Theory calculations and WaterMap analysis were performed to identify potential SIK2 inhibitors. Five molecules from different databases such as Binding_4067, TosLab_837067, NCI_349155, Life chemicals_ F2565-0113, Enamine_7623111186 molecules were identified as possible SIK2 inhibitors.
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Affiliation(s)
- Prajisha Jayaprakash
- Structural Biology and Bio-Computing Laboratory, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India
| | - Jayashree Biswal
- Structural Biology and Bio-Computing Laboratory, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India
| | - Raghu Rangaswamy
- Structural Biology and Bio-Computing Laboratory, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India
| | - Jeyaraman Jeyakanthan
- Structural Biology and Bio-Computing Laboratory, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India.
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