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Molecules
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Simulational and Computational Approaches to Enhance Protein Inhibitor Designs
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Simulational and Computational Approaches to Enhance Protein Inhibitor Designs

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 17755

Special Issue Editors

Prof. Dr. Yeng-Tseng Wang

E-Mail Website
Guest Editor
School of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 8070, Taiwan
Interests: bioinformatic; physical chemistry; computer-aided drug design; molecular dynamics; quantum mechanics; biochemistry; macromolecular
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wen-Wei Lin

E-Mail Website
Guest Editor
School of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 8070, Taiwan
Interests: genetic diagnosis; antibody drugs development; protein drugs development; molecular simulation

Special Issue Information

Dear Colleagues,

Protein inhibitors‘ (which include small compounds, proteins, peptides, and antibodies) interactions with drug targets commonly involve the surface of the protein inhibitor or a complex of proteins that can potentially be disrupted or stabilized by small compounds, proteins, peptides, or antibodies that penetrate the cell. This is in contrast to small compounds, proteins, peptides, or antibodies‘ target proteins, whose activity can be measured in a biophysical, biochemical, or theoretical assay. Due to the growing interest in this field, this Special Issue aims to publish high-quality original research papers on the experimental and theoretical applications of protein–inhibitor interactions.

Prof. Dr. Yeng-Tseng Wang
Prof. Dr. Wen-Wei Lin
Guest Editors

Manuscript Submission Information

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Keywords

  • protein–protein interaction
  • peptide–protein interaction
  • antibody–protein interaction
  • small compound–protein interaction
  • theoretical simulations
  • experimental approach

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Published Papers (3 papers)

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Research

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17 pages, 6506 KiB  
Article
Halogen-Based 17β-HSD1 Inhibitors: Insights from DFT, Docking, and Molecular Dynamics Simulation Studies
by Arulsamy Kulandaisamy, Murugesan Panneerselvam, Rajadurai Vijay Solomon, Madhavan Jaccob, Jaganathan Ramakrishnan, Kumaradhas Poomani, Muralikannan Maruthamuthu and Nagendran Tharmalingam
Molecules 2022, 27(12), 3962; https://doi.org/10.3390/molecules27123962 - 20 Jun 2022
Cited by 7 | Viewed by 2607
Abstract
The high expression of 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) mRNA has been found in breast cancer tissues and endometriosis. The current research focuses on preparing a range of organic molecules as 17β-HSD1 inhibitors. Among them, the derivatives of hydroxyphenyl naphthol steroidomimetics are reported [...] Read more.
The high expression of 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) mRNA has been found in breast cancer tissues and endometriosis. The current research focuses on preparing a range of organic molecules as 17β-HSD1 inhibitors. Among them, the derivatives of hydroxyphenyl naphthol steroidomimetics are reported as one of the potential groups of inhibitors for treating estrogen-dependent disorders. Looking at the recent trends in drug design, many halogen-based drugs have been approved by the FDA in the last few years. Here, we propose sixteen potential hydroxyphenyl naphthol steroidomimetics-based inhibitors through halogen substitution. Our Frontier Molecular Orbitals (FMO) analysis reveals that the halogen atom significantly lowers the Lowest Unoccupied Molecular Orbital (LUMO) level, and iodine shows an excellent capability to reduce the LUMO in particular. Tri-halogen substitution shows more chemical reactivity via a reduced HOMO–LUMO gap. Furthermore, the computed DFT descriptors highlight the structure–property relationship towards their binding ability to the 17β-HSD1 protein. We analyze the nature of different noncovalent interactions between these molecules and the 17β-HSD1 using molecular docking analysis. The halogen-derived molecules showed binding energy ranging from −10.26 to −11.94 kcal/mol. Furthermore, the molecular dynamics (MD) simulations show that the newly proposed compounds provide good stability with 17β-HSD1. The information obtained from this investigation will advance our knowledge of the 17β-HSD1 inhibitors and offer clues to developing new 17β-HSD1 inhibitors for future applications. Full article
(This article belongs to the Special Issue Simulational and Computational Approaches to Enhance Protein Inhibitor Designs)
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18 pages, 6293 KiB  
Article
In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators
by Jiayi Yuan, Chen Jiang, Junmei Wang, Chih-Jung Chen, Yixuan Hao, Guangyi Zhao, Zhiwei Feng and Xiang-Qun Xie
Molecules 2022, 27(2), 453; https://doi.org/10.3390/molecules27020453 - 11 Jan 2022
Cited by 15 | Viewed by 3433
Abstract
Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present [...] Read more.
Although the 3D structures of active and inactive cannabinoid receptors type 2 (CB2) are available, neither the X-ray crystal nor the cryo-EM structure of CB2-orthosteric ligand-modulator has been resolved, prohibiting the drug discovery and development of CB2 allosteric modulators (AMs). In the present work, we mainly focused on investigating the potential allosteric binding site(s) of CB2. We applied different algorithms or tools to predict the potential allosteric binding sites of CB2 with the existing agonists. Seven potential allosteric sites can be observed for either CB2-CP55940 or CB2-WIN 55,212-2 complex, among which sites B, C, G and K are supported by the reported 3D structures of Class A GPCRs coupled with AMs. Applying our novel algorithm toolset-MCCS, we docked three known AMs of CB2 including Ec2la (C-2), trans-β-caryophyllene (TBC) and cannabidiol (CBD) to each site for further comparisons and quantified the potential binding residues in each allosteric binding site. Sequentially, we selected the most promising binding pose of C-2 in five allosteric sites to conduct the molecular dynamics (MD) simulations. Based on the results of docking studies and MD simulations, we suggest that site H is the most promising allosteric binding site. We plan to conduct bio-assay validations in the future. Full article
(This article belongs to the Special Issue Simulational and Computational Approaches to Enhance Protein Inhibitor Designs)
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Review

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23 pages, 2996 KiB  
Review
Structural Insight and Development of EGFR Tyrosine Kinase Inhibitors
by Tasia Amelia, Rahmana Emran Kartasasmita, Tomohiko Ohwada and Daryono Hadi Tjahjono
Molecules 2022, 27(3), 819; https://doi.org/10.3390/molecules27030819 - 26 Jan 2022
Cited by 55 | Viewed by 11011
Abstract
Lung cancer has a high prevalence, with a growing number of new cases and mortality every year. Furthermore, the survival rate of patients with non-small-cell lung carcinoma (NSCLC) is still quite low in the majority of cases. Despite the use of conventional therapy [...] Read more.
Lung cancer has a high prevalence, with a growing number of new cases and mortality every year. Furthermore, the survival rate of patients with non-small-cell lung carcinoma (NSCLC) is still quite low in the majority of cases. Despite the use of conventional therapy such as tyrosine kinase inhibitor for Epidermal Growth Factor Receptor (EGFR), which is highly expressed in most NSCLC cases, there was still no substantial improvement in patient survival. This is due to the drug’s ineffectiveness and high rate of resistance among individuals with mutant EGFR. Therefore, the development of new inhibitors is urgently needed. Understanding the EGFR structure, including its kinase domain and other parts of the protein, and its activation mechanism can accelerate the discovery of novel compounds targeting this protein. This study described the structure of the extracellular, transmembrane, and intracellular domains of EGFR. This was carried out along with identifying the binding pose of commercially available inhibitors in the ATP-binding and allosteric sites, thereby clarifying the research gaps that can be filled. The binding mechanism of inhibitors that have been used clinically was also explained, thereby aiding the structure-based development of new drugs. Full article
(This article belongs to the Special Issue Simulational and Computational Approaches to Enhance Protein Inhibitor Designs)
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