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Life
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Protein-Protein and Protein-Ligand Interaction
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Protein-Protein and Protein-Ligand Interaction

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Proteins and Proteomics".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 12185

Special Issue Editor

Dr. Mateusz Banach

E-Mail Website1 Website2
Guest Editor
Department of Bioinformatics and Telemedicine, Faculty of Medicine, Jagiellonian University Medical College, Medyczna 7, 30-688 Kraków, Poland
Interests: bioinformatics; computational geometry; computer science; data analysis; data visualization; hydrophobic core; optimization algorithms; protein folding; protein-protein interaction; python programming; web services and databases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The biological function of many proteins depends on the formation of a multimeric quaternary structure or the binding of smaller molecules, or both. Other partners include nucleic acids and nearby segments of the cell wall. In addition to kind and number of substrates and their spatial arrangement, protein complexes also have a temporal context: being permanent or transitory. Finally, some proteins act only as monomers, with or without ligand-related activity.

Algorithms, simulations, models, and databases provide an invaluable support for experimental methods, allowing cost-effective, reproducible, large-scale analysis and prediction. Thanks to computers it is possible to gauge whether two or more proteins may interact, or if an introduction of additional factors (a mutation in the sequence or the presence of another molecule) could promote or hinder the construction of such complexes. This situation can be observed from a broad perspective, which is the purpose of protein–protein interaction networks, but also very focused—down to the atomic level—when one tries to pinpoint residues engaged in contact. Possibilities regarding ligand binding are similar, ranging from the exploration of structural features (binding pockets) and the search for molecules that may fit them, to the construction of compound databases for drug candidate screening.

In this Special Issue we are looking forward to submissions in the form of original articles, reviews, and communications presenting recent results of not necessarily purely in silico research, but contributing to the expansion of scientific knowledge in the areas of protein–protein and protein–ligand interaction. 

Dr. Mateusz Banach
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Life is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bioinformatics
  • computational biology
  • drug design
  • ligand binding
  • machine learning
  • molecular docking
  • molecular dynamics 
  • protein–protein interaction
  • proteomics
  • theoretical models

Published Papers (6 papers)

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Research

13 pages, 2077 KiB  
Article
Protein Binding: A Fuzzy Concept
by Mike P. Williamson
Life 2023, 13(4), 855; https://doi.org/10.3390/life13040855 - 23 Mar 2023
Viewed by 1194
Abstract
Our understanding of protein binding interactions has matured significantly over the last few years, largely as a result of trying to make sense of the binding interactions of intrinsically disordered proteins. Here, we bring together some disparate ideas that have largely developed independently, [...] Read more.
Our understanding of protein binding interactions has matured significantly over the last few years, largely as a result of trying to make sense of the binding interactions of intrinsically disordered proteins. Here, we bring together some disparate ideas that have largely developed independently, and show that they can be linked into a coherent picture that provides insight into quantitative aspects of protein interactions, in particular that transient protein interactions are often optimised for speed, rather than tight binding. Full article
(This article belongs to the Special Issue Protein-Protein and Protein-Ligand Interaction)
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15 pages, 12205 KiB  
Article
3D-QSAR Studies, Molecular Docking, Molecular Dynamic Simulation, and ADMET Proprieties of Novel Pteridinone Derivatives as PLK1 Inhibitors for the Treatment of Prostate Cancer
by Mohammed Er-rajy, Mohamed El fadili, Hamada Imtara, Aamir Saeed, Abid Ur Rehman, Sara Zarougui, Shaef A. Abdullah, Ahmad Alahdab, Mohammad Khalid Parvez and Menana Elhallaoui
Life 2023, 13(1), 127; https://doi.org/10.3390/life13010127 - 02 Jan 2023
Cited by 8 | Viewed by 2318
Abstract
Overexpression of polo-like kinase 1 (PLK1) has been found in many different types of cancers. With its essential role in cell proliferation, PLK1 has been determined to be a broad-spectrum anti-cancer target. In this study, 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations [...] Read more.
Overexpression of polo-like kinase 1 (PLK1) has been found in many different types of cancers. With its essential role in cell proliferation, PLK1 has been determined to be a broad-spectrum anti-cancer target. In this study, 3D-QSAR, molecular docking, and molecular dynamics (MD) simulations were applied on a series of novel pteridinone derivatives as PLK1 inhibitors to discover anti-cancer drug candidates. In this work, three models—CoMFA (Q² = 0.67, R² = 0.992), CoMSIA/SHE (Q² = 0.69, R² = 0.974), and CoMSIA/SEAH (Q² = 0.66, R² = 0.975)—of pteridinone derivatives were established. The three models that were established gave Rpred2 = 0.683, Rpred 2= 0.758, and Rpred 2= 0.767, respectively. Thus, the predictive abilities of the three proposed models were successfully evaluated. The relations between the different champs and activities were well-demonstrated by the contour chart of the CoMFA and CoMSIA/SEAH models. The results of molecular docking indicated that residues R136, R57, Y133, L69, L82, and Y139 were the active sites of the PLK1 protein (PDB code: 2RKU), in which the more active ligands can inhibit the enzyme of PLK1. The results of the molecular dynamic MD simulation diagram were obtained to reinforce the previous molecular docking results, which showed that both inhibitors remained stable in the active sites of the PLK1 protein (PDB code: 2RKU) for 50 ns. Finally, a check of the ADME-Tox properties of the two most active molecules showed that molecular N° 28 could represent a good drug candidate for the therapy of prostate cancer diseases. Full article
(This article belongs to the Special Issue Protein-Protein and Protein-Ligand Interaction)
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12 pages, 2535 KiB  
Article
MSALigMap—A Tool for Mapping Active-Site Amino Acids in PDB Structures onto Known and Novel Unannotated Homologous Sequences with Similar Function
by Sameer Hassan, Sameena Haleemath Sameer, Mats Töpel and Henrik Aronsson
Life 2022, 12(12), 2082; https://doi.org/10.3390/life12122082 - 12 Dec 2022
Viewed by 1499
Abstract
MSALigMap (Multiple Sequence Alignment Ligand Mapping) is a tool for mapping active-site amino-acid residues that bind selected ligands on to target protein sequences of interest. Users can also provide novel sequences (unavailable in public databases) for analysis. MSALigMap is written in Python. There [...] Read more.
MSALigMap (Multiple Sequence Alignment Ligand Mapping) is a tool for mapping active-site amino-acid residues that bind selected ligands on to target protein sequences of interest. Users can also provide novel sequences (unavailable in public databases) for analysis. MSALigMap is written in Python. There are several tools and servers available for comparing and mapping active-site amino-acid residues among protein structures. However, there has not previously been a tool for mapping ligand binding amino-acid residues onto protein sequences of interest. Using MSALigMap, users can compare multiple protein sequences, such as those from different organisms or clinical strains, with sequences of proteins with crystal structures in PDB that are bound with the ligand/drug and DNA of interest. This allows users to easily map the binding residues and to predict the consequences of different mutations observed in the binding site. The MSALigMap server can be accessed at https://albiorix.bioenv.gu.se/MSALigMap/HomePage.py. Full article
(This article belongs to the Special Issue Protein-Protein and Protein-Ligand Interaction)
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14 pages, 3263 KiB  
Article
1,2,3-Triazole-Benzofused Molecular Conjugates as Potential Antiviral Agents against SARS-CoV-2 Virus Variants
by Jehan Y. Al-Humaidi, Marwa M. Shaaban, Nadjet Rezki, Mohamed R. Aouad, Mohamed Zakaria, Mariusz Jaremko, Mohamed Hagar and Bassma H. Elwakil
Life 2022, 12(9), 1341; https://doi.org/10.3390/life12091341 - 29 Aug 2022
Cited by 20 | Viewed by 1774
Abstract
SARS-CoV-2 and its variants, especially the Omicron variant, remain a great threat to human health. The need to discover potent compounds that may control the SARS-CoV-2 virus pandemic and the emerged mutants is rising. A set of 1,2,3-triazole and/or 1,2,4-triazole was synthesized either [...] Read more.
SARS-CoV-2 and its variants, especially the Omicron variant, remain a great threat to human health. The need to discover potent compounds that may control the SARS-CoV-2 virus pandemic and the emerged mutants is rising. A set of 1,2,3-triazole and/or 1,2,4-triazole was synthesized either from benzimidazole or isatin precursors. Molecular docking studies and in vitro enzyme activity revealed that most of the investigated compounds demonstrated promising binding scores against the SARS-CoV-2 and Omicron spike proteins, in comparison to the reference drugs. In particular, compound 9 has the highest scoring affinity against the SARS-CoV-2 and Omicron spike proteins in vitro with its IC50 reaching 75.98 nM against the Omicron spike protein and 74.51 nM against the SARS-CoV-2 spike protein. The possible interaction between the synthesized triazoles and the viral spike proteins was by the prevention of the viral entry into the host cells, which led to a reduction in viral reproduction and infection. A cytopathic inhibition assay in the human airway epithelial cell line (Vero E6) infected with SARS-CoV-2 revealed the effectiveness and safety of the synthesized compound (compound 9) (EC50 and CC50 reached 80.4 and 1028.28 µg/mL, respectively, with a selectivity index of 12.78). Moreover, the antiinflammatory effect of the tested compound may pave the way to reduce the reported SARS-CoV-2-induced hyperinflammation. Full article
(This article belongs to the Special Issue Protein-Protein and Protein-Ligand Interaction)
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15 pages, 4176 KiB  
Article
Development of New Potential Inhibitors of β1 Integrins through In Silico Methods—Screening and Computational Validation
by Disraeli Vasconcelos, Beatriz Chaves, Aline Albuquerque, Luca Andrade, Andrielly Henriques, Geraldo Sartori, Wilson Savino, Ernesto Caffarena and João Herminio Martins-Da-Silva
Life 2022, 12(7), 932; https://doi.org/10.3390/life12070932 - 22 Jun 2022
Cited by 4 | Viewed by 1759
Abstract
Integrins are transmembrane receptors that play a critical role in many biological processes which can be therapeutically modulated using integrin blockers, such as peptidomimetic ligands. This work aimed to develop new potential β1 integrin antagonists using modeled receptors based on the aligned crystallographic [...] Read more.
Integrins are transmembrane receptors that play a critical role in many biological processes which can be therapeutically modulated using integrin blockers, such as peptidomimetic ligands. This work aimed to develop new potential β1 integrin antagonists using modeled receptors based on the aligned crystallographic structures and docked with three lead compounds (BIO1211, BIO5192, and TCS2314), widely known as α4β1 antagonists. Lead-compound complex optimization was performed by keeping intact the carboxylate moiety of the ligand, adding substituents in two other regions of the molecule to increase the affinity with the target. Additionally, pharmacokinetic predictions were performed for the ten best ligands generated, with the lowest docking interaction energy obtained for α4β1 and BIO5192. Results revealed an essential salt bridge between the BIO5192 carboxylate group and the Mg2+ MIDAS ion of the integrin. We then generated more than 200 new BIO5192 derivatives, some with a greater predicted affinity to α4β1. Furthermore, the significance of retaining the pyrrolidine core of the ligand and increasing the therapeutic potential of the new compounds is emphasized. Finally, one novel molecule (1592) was identified as a potential drug candidate, with appropriate pharmacokinetic profiles, similar dynamic behavior at the integrin interaction site compared with BIO5192, and a higher predicted affinity to VLA-4. Full article
(This article belongs to the Special Issue Protein-Protein and Protein-Ligand Interaction)
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20 pages, 12355 KiB  
Article
Identifying the Hot Spot Residues of the SARS-CoV-2 Main Protease Using MM-PBSA and Multiple Force Fields
by Jinyoung Byun and Juyong Lee
Life 2022, 12(1), 54; https://doi.org/10.3390/life12010054 - 31 Dec 2021
Cited by 3 | Viewed by 2291
Abstract
In this study, we investigated the binding affinities between the main protease of SARS-CoV-2 virus (Mpro) and its various ligands to identify the hot spot residues of the protease. To benchmark the influence of various force fields on hot spot [...] Read more.
In this study, we investigated the binding affinities between the main protease of SARS-CoV-2 virus (Mpro) and its various ligands to identify the hot spot residues of the protease. To benchmark the influence of various force fields on hot spot residue identification and binding free energy calculation, we performed MD simulations followed by MM-PBSA analysis with three different force fields: CHARMM36, AMBER99SB, and GROMOS54a7. We performed MD simulations with 100 ns for 11 protein–ligand complexes. From the series of MD simulations and MM-PBSA calculations, it is identified that the MM-PBSA estimations using different force fields are weakly correlated to each other. From a comparison between the force fields, AMBER99SB and GROMOS54a7 results are fairly correlated while CHARMM36 results show weak or almost no correlations with the others. Our results suggest that MM-PBSA analysis results strongly depend on force fields and should be interpreted carefully. Additionally, we identified the hot spot residues of Mpro, which play critical roles in ligand binding through energy decomposition analysis. It is identified that the residues of the S4 subsite of the binding site, N142, M165, and R188, contribute strongly to ligand binding. In addition, the terminal residues, D295, R298, and Q299 are identified to have attractive interactions with ligands via electrostatic and solvation energy. We believe that our findings will help facilitate developing the novel inhibitors of SARS-CoV-2. Full article
(This article belongs to the Special Issue Protein-Protein and Protein-Ligand Interaction)
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