1
|
Wu J, Lv J, Zhao L, Zhao R, Gao T, Xu Q, Liu D, Yu Q, Ma F. Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167028. [PMID: 37704131 DOI: 10.1016/j.scitotenv.2023.167028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Revised: 09/03/2023] [Accepted: 09/10/2023] [Indexed: 09/15/2023]
Abstract
Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.
Collapse
Affiliation(s)
- Jieting Wu
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Jin Lv
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Lei Zhao
- State Key Laboratory of Urban Water Resources & Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Ruofan Zhao
- School of Environment, Beijing Normal University, Beijing 100875, China
| | - Tian Gao
- Key Laboratory of Integrated Regulation and Resource Development of Shallow Lakes, Ministry of Education, College of Environment, Hohai University, Xikang Road #1, Nanjing 210098, China
| | - Qi Xu
- PetroChina Fushun Petrochemical Company, Fushun 113000, China
| | - Dongbo Liu
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Qiqi Yu
- School of Environmental Science, Liaoning University, Shenyang 110036, China
| | - Fang Ma
- State Key Laboratory of Urban Water Resources & Environment, Harbin Institute of Technology, Harbin 150090, China.
| |
Collapse
|
2
|
Tavasolikejani S, Farazin A. The effect of increasing temperature on simulated nanocomposites reinforced with SWBNNs and its effect on characteristics related to mechanics and the physical attributes using the MDs approach. Heliyon 2023; 9:e21022. [PMID: 37867868 PMCID: PMC10587535 DOI: 10.1016/j.heliyon.2023.e21022] [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: 08/07/2023] [Revised: 10/12/2023] [Accepted: 10/12/2023] [Indexed: 10/24/2023] Open
Abstract
This study examines the effect of increasing temperature (300, 350, 400, 450 and 500 K) on simulated nanocomposites reinforced with exploration of the impact of single-walled boron nitride nanotubes (SWBNNTs) on both the mechanical properties (including Young's modulus, Poisson's ratio, shear modulus, and bulk modulus) and the physical property of density, achieved through molecular dynamics (MDs) simulations. MDs utilized to simulate nanocomposite models consisting of five case studies of SWBNNs with different chiralities (5, 0), (10, 0), (15, 0), (20, 0), and (25, 0) as the reinforcement and using thermoplastic polyurethane (TPU) as the common matrix. The results reveal that with increasing temperature and chiralities of SWBNNTs, the density and Poisson's ratio increase dramatically, and Young's, shear, and bulk moduli decrease continuously. At a consistent temperature, there is a noteworthy trend in the mechanical properties of SWBNNTs with various chiralities. This includes the increase in Young's modulus, Poisson's ratio, shear modulus, and bulk modulus in the simulated nanocomposite, ranging from SWBNNTs (5, 0) to (25, 0). Similarly, the physical property of density exhibits an increasing trend from SWBNNTs (5, 0) to (20, 0) and then decreases at SWBNNTs (25, 0). To validate the accuracy of these findings, a Radial Distribution Function (RDF) diagram is generated using Materials Studio software.
Collapse
Affiliation(s)
| | - Ashkan Farazin
- Department of Solid Mechanics, Faculty of Mechanical Engineering, University of Kashan, P.O. Box 87317-53153, Kashan, Iran
| |
Collapse
|
3
|
Ravi L, Kumar K A, Kumari G R S, S H, Sam Raj JB, R L, Chinnaiyan P, K C DJ, J K M, Sudhakara D, Dar MS, D M Y, G S. Stearyl palmitate a multi-target inhibitor against breast cancer: in-silico, in-vitro & in-vivo approach. J Biomol Struct Dyn 2023:1-18. [PMID: 37691453 DOI: 10.1080/07391102.2023.2255271] [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: 03/17/2023] [Accepted: 08/30/2023] [Indexed: 09/12/2023]
Abstract
Multi-target inhibitors are currently trending in the pharmaceutical research, as they possess increased efficacy and reduced toxicity. In this study multi-target inhibitors for breast cancer are explored from a curated list of natural products, i.e. 4,670 phytochemicals belonging to 360 medicinal plants. In-silico screening of phytochemicals using SeeSAR and AutoDock Vina resulted in identification of Stearyl Palmitate as a potential drug molecule that inhibits three drug targets, i.e. HER-2, MEK-1 and PARP-1 proteins. Molecular Dynamics Simulation for 100 ns each for these three protein-ligand complexes using Desmond, Maestro platform also confirmed the prediction of multi-target inhibition by Stearyl Palmitate. Further in-vitro MTT assay demonstrated that Stearyl Palmitate has a significant IC50 value of 40 µM against MCF-7 cells and >1000 µM against L929 cells. This confirmed that Stearyl Palmitate is having selective cytotoxicity towards breast cancer cells in comparison to non-cancerous cells. Fluorescence staining and flow cytometry analysis confirmed that, Stearyl Palmitate is inducing apoptosis in MCF-7 cells at IC50 concentration. Finally, in-vivo efficacy and toxicity studies were performed using zebrafishes (Danio rerio). It was observed that the fishes treated with IC50 concentration of Stearyl Palmitate demonstrated 2x folds reduction in tumour size, while double dose resulted in 4x folds reduction in tumour size. Stearyl Palmitate did not demonstrate any toxicity or side effects in the zebrafishes. It is concluded that, Stearyl Palmitate, a phytochemical reported to be present in Althea officinalis is a potential anti-breast cancer agent, with ability to inhibit multiple targets such as HER-2, MEK-1 and PARP-2 proteins.Communicated by Ramaswamy H. Sarma.
Collapse
Affiliation(s)
- Lokesh Ravi
- Department of Food Technology, Faculty of Life and Allied Health Sciences, MS Ramaiah University of Applied Sciences, Bengaluru, Karnataka, India
| | - Ajith Kumar K
- Department of Life Sciences, Kristu Jayanti College (Autonomous), Bengaluru, Karnataka, India
| | - Shree Kumari G R
- School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Harsha S
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - Jabin B Sam Raj
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - Likitha R
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - Prawin Chinnaiyan
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - David Jonnes K C
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - Megha J K
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - Dhanush Sudhakara
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - Musaib Shafi Dar
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - Yashaswini D M
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| | - Sathvik G
- Department of Botany, School of Life Sciences, St Joseph's University, Bengaluru, Karnataka, India
| |
Collapse
|
4
|
Pharmacophore modeling, docking and molecular dynamics simulation for identification of novel human protein kinase C beta (PKCβ) inhibitors. Struct Chem 2022; 34:1157-1171. [PMID: 36248344 PMCID: PMC9553083 DOI: 10.1007/s11224-022-02075-y] [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: 04/24/2022] [Accepted: 10/01/2022] [Indexed: 12/02/2022]
Abstract
Protein kinase Cβ (PKCβ) is considered as an attractive molecular target for the treatment of COVID-19-related acute respiratory distress syndrome (ARDS). Several classes of inhibitors have been already identified. In this article, we developed and validated ligand-based PKCβ pharmacophore models based on the chemical structures of the known inhibitors. The most accurate pharmacophore model, which correctly predicted more than 70% active compounds of test set, included three aromatic pharmacophore features without vectors, one hydrogen bond acceptor pharmacophore feature, one hydrophobic pharmacophore feature and 158 excluded volumes. This pharmacophore model was used for virtual screening of compound collection in order to identify novel potent PKCβ inhibitors. Also, molecular docking of compound collection was performed and 28 compounds which were selected simultaneously by two approaches as top-scored were proposed for further biological research.
Collapse
|