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Biomolecular Simulations
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Biomolecular Simulations

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

Deadline for manuscript submissions: closed (1 March 2017) | Viewed by 50661

Special Issue Editor

Prof. Dr. Roberta Galeazzi

E-Mail Website
Guest Editor
Dipartimento di Scienze della Vita e dell'Ambiente, Universita Politecnica delle Marche, Ancona, Italy
Interests: computer aided drug design; molecular dynamics simulation of membrane receptors and lipid bilayers; rational drug design; bacterial efflux pumps' inhibitors; computational design of novel nanovectors for drug delivery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the past few decades, the field of molecular simulations has evolved from picosecond studies of single macromolecules (mostly proteins) in vacuum to studies of complex, structurally heterogeneous biological systems consisting of millions of atoms. The simulation time scales have been extended up to milliseconds, and even to seconds. As a consequence, biomolecular modeling has increased its potentiality, and such simulations are now a fundamental discipline in many research fields, covering the areas of biochemistry, molecular biology, medicinal chemistry, and biophysics.

In this Special Issue of Molecules, expert researchers are invited to present original papers that consider any advances in “Biomolecular Simulations”. Special emphasis is placed on simulations of proteins, lipids and nucleic acids. Select topics covered are: Protein folding and unfolding, Protein–Protein and Protein–DNA associations; membrane transporters and macromolecular targets in cancer, membrane transporters and antimicrobial resistance, membrane receptors structure and drug design; and lipid bilayer structure and function. Application studies should illustrate many of the methods commonly used in molecular modeling of biological systems, including methods for electronic structure calculations, and classical and coarse-grained molecular dynamics simulations are welcome. Submissions of manuscripts from various fields of research are strongly encouraged.

Prof. Dr. Roberta Galeazzi
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. Molecules is an international peer-reviewed open access semimonthly 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 2700 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

  • membrane receptor structure and dynamics
  • protein structures, properties and functionalities
  • protein–receptor interactions
  • protein folding
  • molecular dynamics simulation (atomistic and coarse grained)
  • lipid bilayers structure and properties
  • membrane transport
  • drug design targeting key macromolecules in cancer

Published Papers (8 papers)

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Research

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4254 KiB  
Article
Molecular Dynamics Simulations of the Host Defense Peptide Temporin L and Its Q3K Derivative: An Atomic Level View from Aggregation in Water to Bilayer Perturbation
by Andrea Farrotti, Paolo Conflitti, Saurabh Srivastava, Jimut Kanti Ghosh, Antonio Palleschi, Lorenzo Stella and Gianfranco Bocchinfuso
Molecules 2017, 22(7), 1235; https://doi.org/10.3390/molecules22071235 - 22 Jul 2017
Cited by 12 | Viewed by 6421
Abstract
Temporin L (TempL) is a 13 residue Host Defense Peptide (HDP) isolated from the skin of frogs. It has a strong affinity for lipopolysaccharides (LPS), which is related to its high activity against Gram-negative bacteria and also to its strong tendency to neutralize [...] Read more.
Temporin L (TempL) is a 13 residue Host Defense Peptide (HDP) isolated from the skin of frogs. It has a strong affinity for lipopolysaccharides (LPS), which is related to its high activity against Gram-negative bacteria and also to its strong tendency to neutralize the pro-inflammatory response caused by LPS release from inactivated bacteria. A designed analog with the Q3K substitution shows an enhancement in both these activities. In the present paper, Molecular Dynamics (MD) simulations have been used to investigate the origin of these improved properties. To this end, we have studied the behavior of the peptides both in water solution and in the presence of LPS lipid-A bilayers, demonstrating that the main effect through which the Q3K substitution improves the peptide activities is the destabilization of peptide aggregates in water. Full article
(This article belongs to the Special Issue Biomolecular Simulations)
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9188 KiB  
Article
Mechanism Exploration of Arylpiperazine Derivatives Targeting the 5-HT2A Receptor by In Silico Methods
by Feng Lin, Feng Li, Chao Wang, Jinghui Wang, Yinfeng Yang, Ling Yang and Yan Li
Molecules 2017, 22(7), 1064; https://doi.org/10.3390/molecules22071064 - 26 Jun 2017
Cited by 16 | Viewed by 7704
Abstract
As a G-protein coupled receptor, the 5-hydroxytryptamine 2A (5-HT2A) receptor is known for its critical role in the cognitive, behavioural and physiological functions, and thus is a primary molecular target to treat psychiatric diseases, including especially depression. With purpose to explore [...] Read more.
As a G-protein coupled receptor, the 5-hydroxytryptamine 2A (5-HT2A) receptor is known for its critical role in the cognitive, behavioural and physiological functions, and thus is a primary molecular target to treat psychiatric diseases, including especially depression. With purpose to explore the structural traits affecting the inhibitory activity, currently a dataset of 109 arylpiperazine derivatives as promising 5-HT2A antagonists was built, based on which the ligand-based three-dimensional quantitative structure-activity relationship (3D-QSAR) study by using both comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches was carried out. The resultant optimal CoMSIA model displays proper validity and predictability with cross-validated correlation coefficient Q2 = 0.587, non-cross-validated correlation coefficient R2ncv = 0.900 and predicted correlation coefficient for the test set of compounds R2pre = 0.897, respectively. Besides, molecular docking was also conducted to investigate the binding mode between these ligands and the active site of the 5-HT2A receptor. Meanwhile, as a docking supplementary tool to study the antagonists’ conformation in the binding cavity, molecular dynamics (MD) simulation was also performed, providing further elucidation about the changes in the ligand-receptor complex. Lastly, some new molecules were also newly-designed based on the above results that are potential arylpiperazine antagonists of 5-HT2A receptor. We hope that the present models and derived information may be of help for facilitating the optimization and design of novel potent antagonists as antidepressant drugs as well as exploring the interaction mechanism of 5-HT2A antagonists. Full article
(This article belongs to the Special Issue Biomolecular Simulations)
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20087 KiB  
Article
Protein Stability and Unfolding Following Glycine Radical Formation
by Michael C. Owen,, Imre G. Csizmadia, Béla Viskolcz and Birgit Strodel
Molecules 2017, 22(4), 655; https://doi.org/10.3390/molecules22040655 - 19 Apr 2017
Cited by 6 | Viewed by 5368
Abstract
Glycine (Gly) residues are particularly susceptible to hydrogen abstraction; which results in the formation of the capto-dative stabilized Cα-centered Gly radical (GLR) on the protein backbone. We examined the effect of GLR formation on the structure of the Trp cage; tryptophan [...] Read more.
Glycine (Gly) residues are particularly susceptible to hydrogen abstraction; which results in the formation of the capto-dative stabilized Cα-centered Gly radical (GLR) on the protein backbone. We examined the effect of GLR formation on the structure of the Trp cage; tryptophan zipper; and the villin headpiece; three fast-folding and stable miniproteins; using all-atom (OPLS-AA) molecular dynamics simulations. Radicalization changes the conformation of the GLR residue and affects both neighboring residues but did not affect the stability of the Trp zipper. The stability of helices away from the radical center in villin were also affected by radicalization; and GLR in place of Gly15 caused the Trp cage to unfold within 1 µs. These results provide new evidence on the destabilizing effects of protein oxidation by reactive oxygen species. Full article
(This article belongs to the Special Issue Biomolecular Simulations)
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11964 KiB  
Article
Computational Identification of Antibody Epitopes on the Dengue Virus NS1 Protein
by Martina L. Jones, Fiona S. Legge, Kebaneilwe Lebani, Stephen M. Mahler, Paul R. Young, Daniel Watterson, Herbert R. Treutlein and Jun Zeng
Molecules 2017, 22(4), 607; https://doi.org/10.3390/molecules22040607 - 10 Apr 2017
Cited by 10 | Viewed by 5827
Abstract
We have previously described a method to predict antigenic epitopes on proteins recognized by specific antibodies. Here we have applied this method to identify epitopes on the NS1 proteins of the four Dengue virus serotypes (DENV1–4) that are bound by a small panel [...] Read more.
We have previously described a method to predict antigenic epitopes on proteins recognized by specific antibodies. Here we have applied this method to identify epitopes on the NS1 proteins of the four Dengue virus serotypes (DENV1–4) that are bound by a small panel of monoclonal antibodies 1H7.4, 1G5.3 and Gus2. Several epitope regions were predicted for these antibodies and these were found to reflect the experimentally observed reactivities. The known binding epitopes on DENV2 for the antibodies 1H7.4 and 1G5.3 were identified, revealing the reasons for the serotype specificity of 1H7.4 and 1G5.3, and the non-selectivity of Gus2. As DENV NS1 is critical for virus replication and a key vaccine candidate, epitope prediction will be valuable in designing appropriate vaccine control strategies. The ability to predict potential epitopes by computational methods significantly reduces the amount of experimental work required to screen peptide libraries for epitope mapping. Full article
(This article belongs to the Special Issue Biomolecular Simulations)
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1609 KiB  
Article
The Performance of Several Docking Programs at Reproducing Protein–Macrolide-Like Crystal Structures
by Alejandro Castro-Alvarez, Anna M. Costa and Jaume Vilarrasa
Molecules 2017, 22(1), 136; https://doi.org/10.3390/molecules22010136 - 17 Jan 2017
Cited by 108 | Viewed by 9423
Abstract
The accuracy of five docking programs at reproducing crystallographic structures of complexes of 8 macrolides and 12 related macrocyclic structures, all with their corresponding receptors, was evaluated. Self-docking calculations indicated excellent performance in all cases (mean RMSD values ≤ 1.0) and confirmed the [...] Read more.
The accuracy of five docking programs at reproducing crystallographic structures of complexes of 8 macrolides and 12 related macrocyclic structures, all with their corresponding receptors, was evaluated. Self-docking calculations indicated excellent performance in all cases (mean RMSD values ≤ 1.0) and confirmed the speed of AutoDock Vina. Afterwards, the lowest-energy conformer of each molecule and all the conformers lying 0–10 kcal/mol above it (as given by Macrocycle, from MacroModel 10.0) were subjected to standard docking calculations. While each docking method has its own merits, the observed speed of the programs was as follows: Glide 6.6 > AutoDock Vina 1.1.2 > DOCK 6.5 >> AutoDock 4.2.6 > AutoDock 3.0.5. For most of the complexes, the five methods predicted quite correct poses of ligands at the binding sites, but the lower RMSD values for the poses of highest affinity were in the order: Glide 6.6 ≈ AutoDock Vina ≈ DOCK 6.5 > AutoDock 4.2.6 >> AutoDock 3.0.5. By choosing the poses closest to the crystal structure the order was: AutoDock Vina > Glide 6.6 ≈ DOCK 6.5 ≥ AutoDock 4.2.6 >> AutoDock 3.0.5. Re-scoring (AutoDock 4.2.6//AutoDock Vina, Amber Score and MM-GBSA) improved the agreement between the calculated and experimental data. For all intents and purposes, these three methods are equally reliable. Full article
(This article belongs to the Special Issue Biomolecular Simulations)
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8659 KiB  
Article
Intrinsic Dynamics Analysis of a DNA Octahedron by Elastic Network Model
by Guang Hu, Lei He, Federico Iacovelli and Mattia Falconi
Molecules 2017, 22(1), 145; https://doi.org/10.3390/molecules22010145 - 16 Jan 2017
Cited by 10 | Viewed by 5345
Abstract
DNA is a fundamental component of living systems where it plays a crucial role at both functional and structural level. The programmable properties of DNA make it an interesting building block for the construction of nanostructures. However, molecular mechanisms for the arrangement of [...] Read more.
DNA is a fundamental component of living systems where it plays a crucial role at both functional and structural level. The programmable properties of DNA make it an interesting building block for the construction of nanostructures. However, molecular mechanisms for the arrangement of these well-defined DNA assemblies are not fully understood. In this paper, the intrinsic dynamics of a DNA octahedron has been investigated by using two types of Elastic Network Models (ENMs). The application of ENMs to DNA nanocages include the analysis of the intrinsic flexibilities of DNA double-helices and hinge sites through the calculation of the square fluctuations, as well as the intrinsic collective dynamics in terms of cross-collective map calculation coupled with global motions analysis. The dynamics profiles derived from ENMs have then been evaluated and compared with previous classical molecular dynamics simulation trajectories. The results presented here revealed that ENMs can provide useful insights into the intrinsic dynamics of large DNA nanocages and represent a useful tool in the field of structural DNA nanotechnology. Full article
(This article belongs to the Special Issue Biomolecular Simulations)
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4517 KiB  
Article
Multi-Layer Identification of Highly-Potent ABCA1 Up-Regulators Targeting LXRβ Using Multiple QSAR Modeling, Structural Similarity Analysis, and Molecular Docking
by Meimei Chen, Fafu Yang, Jie Kang, Xuemei Yang, Xinmei Lai and Yuxing Gao
Molecules 2016, 21(12), 1639; https://doi.org/10.3390/molecules21121639 - 29 Nov 2016
Cited by 8 | Viewed by 4667
Abstract
In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, [...] Read more.
In this study, in silico approaches, including multiple QSAR modeling, structural similarity analysis, and molecular docking, were applied to develop QSAR classification models as a fast screening tool for identifying highly-potent ABCA1 up-regulators targeting LXRβ based on a series of new flavonoids. Initially, four modeling approaches, including linear discriminant analysis, support vector machine, radial basis function neural network, and classification and regression trees, were applied to construct different QSAR classification models. The statistics results indicated that these four kinds of QSAR models were powerful tools for screening highly potent ABCA1 up-regulators. Then, a consensus QSAR model was developed by combining the predictions from these four models. To discover new ABCA1 up-regulators at maximum accuracy, the compounds in the ZINC database that fulfilled the requirement of structural similarity of 0.7 compared to known potent ABCA1 up-regulator were subjected to the consensus QSAR model, which led to the discovery of 50 compounds. Finally, they were docked into the LXRβ binding site to understand their role in up-regulating ABCA1 expression. The excellent binding modes and docking scores of 10 hit compounds suggested they were highly-potent ABCA1 up-regulators targeting LXRβ. Overall, this study provided an effective strategy to discover highly potent ABCA1 up-regulators. Full article
(This article belongs to the Special Issue Biomolecular Simulations)
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Review

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2315 KiB  
Review
Molecular Simulations of Disulfide-Rich Venom Peptides with Ion Channels and Membranes
by Evelyne Deplazes
Molecules 2017, 22(3), 362; https://doi.org/10.3390/molecules22030362 - 27 Feb 2017
Cited by 11 | Viewed by 5111
Abstract
Disulfide-rich peptides isolated from the venom of arthropods and marine animals are a rich source of potent and selective modulators of ion channels. This makes these peptides valuable lead molecules for the development of new drugs to treat neurological disorders. Consequently, much effort [...] Read more.
Disulfide-rich peptides isolated from the venom of arthropods and marine animals are a rich source of potent and selective modulators of ion channels. This makes these peptides valuable lead molecules for the development of new drugs to treat neurological disorders. Consequently, much effort goes into understanding their mechanism of action. This paper presents an overview of how molecular simulations have been used to study the interactions of disulfide-rich venom peptides with ion channels and membranes. The review is focused on the use of docking, molecular dynamics simulations, and free energy calculations to (i) predict the structure of peptide-channel complexes; (ii) calculate binding free energies including the effect of peptide modifications; and (iii) study the membrane-binding properties of disulfide-rich venom peptides. The review concludes with a summary and outlook. Full article
(This article belongs to the Special Issue Biomolecular Simulations)
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