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8.3
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Biomolecules
Special Issues
Protein Dynamics Simulations
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Protein Dynamics Simulations

A special issue of Biomolecules (ISSN 2218-273X).

Deadline for manuscript submissions: closed (1 August 2019) | Viewed by 13274

Special Issue Editor

Dr. Nadia Elghobashi-Meinhardt

E-Mail Website
Guest Editor
Biomolecular Modeling, Institute of Chemistry, Technical University Berlin, Berlin, Germany

Special Issue Information

Dear Colleagues,

Over the past 50 years, the simulation of proteins has experienced transformative growth due to advances in computational technology. GPU computing has allowed biological molecules to be simulated for longer times, enabling the investigation of long-range conformational changes that were previously inaccessible. As computational power has increased, simulation techniques such as accelerated molecular dynamics have enabled longer simulations of larger, more complex biological systems. For example, simulations of protein–nucleic acid complexes such as CRISPR-Cas9 now offer unprecedented access to the atomic details of intricate enzymatic reactions.

In addition to advances in computer hardware and simulation techniques, the emergence of high-resolution cryo-EM data over the past decade has ushered in a new era of the investigation of larger membrane-bound proteins. As these proteins are often the target of small-molecule drugs, the elucidation of their structure is the first step to understanding their complex functionality. Protein dynamics simulations based on cryo-EM data will offer further insight into the machinery of these membrane-bound proteins.

This Special Issue on protein dynamics simulations welcomes contributions that highlight method development as well as applications to novel biological systems. Relevant topics may include protein–ligand interactions (e.g., in the context of drug discovery and translational medicine), docking techniques, calculation of binding free energies, advances in developing polarizable force fields, hybrid quantum mechanical/molecular mechanical (QM/MM) MD approaches, development and improvement of force fields for biomolecules, coarse-grained models, solvation models, simulation of radiation–matter interactions, and enzymatic catalysis.

Research articles as well as reviews are welcome. We look forward to your contribution.

Dr. Nadia Elghobashi-Meinhardt
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. Biomolecules 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 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

  • protein–ligand interactions
  • molecular modeling and simulations
  • homology modeling
  • docking techniques
  • free-binding energy calculation
  • advances in developing polarizable force fields
  • coarse-grained models
  • solvation models
  • simulation of radiation-matter interactions
  • enzymatic catalysis

Published Papers (3 papers)

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Research

16 pages, 7838 KiB  
Article
Analyzing Fluctuation Properties in Protein Elastic Networks with Sequence-Specific and Distance-Dependent Interactions
by Romain Amyot, Yuichi Togashi and Holger Flechsig
Biomolecules 2019, 9(10), 549; https://doi.org/10.3390/biom9100549 - 30 Sep 2019
Cited by 3 | Viewed by 3093
Abstract
Simple protein elastic networks which neglect amino-acid information often yield reasonable predictions of conformational dynamics and are broadly used. Recently, model variants which incorporate sequence-specific and distance-dependent interactions of residue pairs have been constructed and demonstrated to improve agreement with experimental data. We [...] Read more.
Simple protein elastic networks which neglect amino-acid information often yield reasonable predictions of conformational dynamics and are broadly used. Recently, model variants which incorporate sequence-specific and distance-dependent interactions of residue pairs have been constructed and demonstrated to improve agreement with experimental data. We have applied the new variants in a systematic study of protein fluctuation properties and compared their predictions with those of conventional anisotropic network models. We find that the quality of predictions is frequently linked to poor estimations in highly flexible protein regions. An analysis of a large set of protein structures shows that fluctuations of very weakly connected network residues are intrinsically prone to be significantly overestimated by all models. This problem persists in the new models and is not resolved by taking into account sequence information. The effect becomes even enhanced in the model variant which takes into account very soft long-ranged residue interactions. Beyond these shortcomings, we find that model predictions are largely insensitive to the integration of chemical information, at least regarding the fluctuation properties of individual residues. One can furthermore conclude that the inherent drawbacks may present a serious hindrance when improvement of elastic network models are attempted. Full article
(This article belongs to the Special Issue Protein Dynamics Simulations)
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20 pages, 3288 KiB  
Article
Mutagenesis of DsbAss is Crucial for the Signal Recognition Particle Mechanism in Escherichia coli: Insights from Molecular Dynamics Simulations
by Faiza Gul Durrani, Roquyya Gul, Muhammad Usman Mirza, Naheed Nazly Kaderbhai, Matheus Froeyen and Mahjabeen Saleem
Biomolecules 2019, 9(4), 133; https://doi.org/10.3390/biom9040133 - 3 Apr 2019
Cited by 12 | Viewed by 4215
Abstract
The disulfide bond signal sequence (DsbAss) protein is characterized as an important virulence factor in gram-negative bacteria. This study aimed to analyze the “alanine” alteration in the hydrophobic (H) region of DsbAss and to understand the conformational DsbAss alteration(s) inside the fifty-four homolog [...] Read more.
The disulfide bond signal sequence (DsbAss) protein is characterized as an important virulence factor in gram-negative bacteria. This study aimed to analyze the “alanine” alteration in the hydrophobic (H) region of DsbAss and to understand the conformational DsbAss alteration(s) inside the fifty-four homolog (Ffh)-binding groove which were revealed to be crucial for translocation of ovine growth hormone (OGH) to the periplasmic space in Escherichia coli via the secretory (Sec) pathway. An experimental design was used to explore the hydrophobicity and alteration of alanine (Ala) to isoleucine (Ile) in the tripartite structure of DsbAss. As a result, two DsbAss mutants (Ala at positions -11 and -13) with same hydrophobicity of 1.539 led to the conflicting translocation of the active OGH gene. We performed molecular dynamics (MD) simulations and molecular mechanics generalized born surface area (MM-GBSA) binding free energy calculations to examine the interaction energetic and dynamic aspects of DsbAss/signal repetition particle 54 (SRP54) binding, which has a principle role in Escherichia coli Sec pathways. Although both DsbAss mutants retained helicity, the MD simulation analysis evidenced that altering Ala-13 changed the orientation of the signal peptide in the Ffh M binding domain groove, favored more stable interaction energies (MM-GBSA ΔGtotal = −140.62 kcal mol−1), and hampered the process of OGH translocation, while Ala-11 pointed outward due to unstable conformation and less binding energy (ΔGtotal = −124.24 kcal mol−1). Here we report the dynamic behavior of change of “alanine” in the H-domain of DsbAss which affects the process of translocation of OGH, where MD simulation and MM-GBSA can be useful initial tools to investigate the virulence of bacteria. Full article
(This article belongs to the Special Issue Protein Dynamics Simulations)
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24 pages, 11264 KiB  
Article
Inhibition of Oncogenic Kinases: An In Vitro Validated Computational Approach Identified Potential Multi-Target Anticancer Compounds
by Nazia Ikram, Muhammad Usman Mirza, Michiel Vanmeert, Matheus Froeyen, Outi M. H. Salo-Ahen, Muhammad Tahir, Aamer Qazi and Sarfraz Ahmad
Biomolecules 2019, 9(4), 124; https://doi.org/10.3390/biom9040124 - 28 Mar 2019
Cited by 25 | Viewed by 5417
Abstract
Tumorigenesis in humans is a multistep progression that imitates genetic changes leading to cell transformation and malignancy. Oncogenic kinases play a central role in cancer progression, rendering them putative targets for the design of anti-cancer drugs. The presented work aims to identify the [...] Read more.
Tumorigenesis in humans is a multistep progression that imitates genetic changes leading to cell transformation and malignancy. Oncogenic kinases play a central role in cancer progression, rendering them putative targets for the design of anti-cancer drugs. The presented work aims to identify the potential multi-target inhibitors of oncogenic receptor tyrosine kinases (RTKs) and serine/threonine kinases (STKs). For this, chemoinformatics and structure-based virtual screening approaches were combined with an in vitro validation of lead hits on both cancerous and non-cancerous cell lines. A total of 16 different kinase structures were screened against ~739,000 prefiltered compounds using diversity selection, after which the top hits were filtered for promising pharmacokinetic properties. This led to the identification of 12 and 9 compounds against RTKs and STKs, respectively. Molecular dynamics (MD) simulations were carried out to better comprehend the stability of the predicted hit kinase-compound complexes. Two top-ranked compounds against each kinase class were tested in vitro for cytotoxicity, with compound F34 showing the most promising inhibitory activity in HeLa, HepG2, and Vero cell lines with IC50 values of 145.46 μM, 175.48 μM, and 130.52 μM, respectively. Additional docking of F34 against various RTKs was carried out to support potential multi-target inhibition. Together with reliable MD simulations, these results suggest the promising potential of identified multi-target STK and RTK scaffolds for further kinase-specific anti-cancer drug development toward combinatorial therapies. Full article
(This article belongs to the Special Issue Protein Dynamics Simulations)
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