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Special Issue "Computational Studies of Biomolecules"

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biophysics".

Deadline for manuscript submissions: 20 January 2020.

Special Issue Editors

Research Associate Professor Tatyana Karabencheva-Christova
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Guest Editor
Department of Chemistry, Michigan Technological University, Houghton, MI 49931, USA
Interests: computational chemical biology; enzyme mechanisms; catalytic activity and inhibition; computer-aided drug design; conformational dynamics of proteins and nucleic acids; biomolecular spectroscopy; bioinorganic enzymology
Special Issues and Collections in MDPI journals
Associate Professor Christo Z. Christov
E-Mail
Guest Editor
Department of Chemistry, Michigan Technological University, Houghton, MI 49931, USA
Fax: +44 191 227 3519
Interests: computational biomolecular science; enzyme mechanisms; protein conformational dynamics; biomolecular spectroscopy; combined quantum mechanical and molecular mechanical methods (QM/MM); quantum chemistry; molecular dynamics; protein-ligands interactions; bioinorganic electronic structure and mechanisms
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the continuation of our previous special issue "Computational Studies of Structure-Dynamics-Function Relationships in Biomolecules".

Computational Chemistry Methods are nowadays widely applied for studying biomolecular structure, mechanisms, dynamics, and function. Molecular Dynamic (MD) simulations methods, Quantum Mechanic (QM) methods, Combined Quantum Mechanics/Molecular Mechanics (QM/MM), Molecular Docking and other computational techniques have proven to be very useful for fundamental understanding of structure–function relationships in biomolecules, but also very useful for application in drug design, chemical biology and biotechnology. Importantly, the increased computational power and the development of high-performance computing made further possible the growth in synergistic computational–experimental studies in the most actual areas of biomolecular sciences in timeliness manner.  

The current Special Issue aims to attract high quality contributions of modeling biomolecular structure, dynamics, function and interactions with potential of interpretation of experimental data and application in drug design and protein design.

Topics of interest:

  • Development and validation of new Computational Modeling Methods
  • Computational Studies of proteins structure-function relationships
  • Computational investigations of nucleic acids structure–function relationships
  • Modelling of protein and nucleic acids dynamics
  • Protein Docking
  • Protein-ligand interactions
  • Nucleic acid ligand interactions
  • Protein design
  • Computational enzymology–enzymatic reaction mechanisms
  • Proteins homology modeling

Research Associate Professor Tatyana Karabencheva-Christova
Associate Professor Christo Z. Christov
Guest Editors

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 papers will be 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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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.

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Published Papers (5 papers)

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Research

Open AccessArticle
Elucidating the Structural Basis of the Intracellular pH Sensing Mechanism of TASK-2 K2P Channels
Int. J. Mol. Sci. 2020, 21(2), 532; https://doi.org/10.3390/ijms21020532 - 14 Jan 2020
Abstract
Two-pore domain potassium (K2P) channels maintain the cell’s background conductance by stabilizing the resting membrane potential. They assemble as dimers possessing four transmembrane helices in each subunit. K2P channels were crystallized in “up” and “down” states. The movements of [...] Read more.
Two-pore domain potassium (K2P) channels maintain the cell’s background conductance by stabilizing the resting membrane potential. They assemble as dimers possessing four transmembrane helices in each subunit. K2P channels were crystallized in “up” and “down” states. The movements of the pore-lining transmembrane TM4 helix produce the aperture or closure of side fenestrations that connect the lipid membrane with the central cavity. When the TM4 helix is in the up-state, the fenestrations are closed, while they are open in the down-state. It is thought that the fenestration states are related to the activity of K2P channels and the opening of the channels preferentially occurs from the up-state. TASK-2, a member of the TALK subfamily of K2P channels, is opened by intracellular alkalization leading the deprotonation of the K245 residue at the end of the TM4 helix. This charge neutralization of K245 could be sensitive or coupled to the fenestration state. Here, we describe the relationship between the states of the intramembrane fenestrations and K245 residue in TASK-2 channel. By using molecular modeling and simulations, we show that the protonated state of K245 (K245+) favors the open fenestration state and, symmetrically, that the open fenestration state favors the protonated state of the lysine residue. We show that the channel can be completely blocked by Prozac, which is known to induce fenestration opening in TREK-2. K245 protonation and fenestration aperture have an additive effect on the conductance of the channel. The opening of the fenestrations with K245+ increases the entrance of lipids into the selectivity filter, blocking the channel. At the same time, the protonation of K245 introduces electrostatic potential energy barriers to ion entrance. We computed the free energy profiles of ion penetration into the channel in different fenestration and K245 protonation states, to show that the effects of the two transformations are summed up, leading to maximum channel blocking. Estimated rates of ion transport are in qualitative agreement with experimental results and support the hypothesis that the most important barrier for ion transport under K245+ and open fenestration conditions is the entrance of the ions into the channel. Full article
(This article belongs to the Special Issue Computational Studies of Biomolecules)
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Open AccessArticle
Structural Characterization of the CD44 Stem Region for Standard and Cancer-Associated Isoforms
Int. J. Mol. Sci. 2020, 21(1), 336; https://doi.org/10.3390/ijms21010336 - 03 Jan 2020
Abstract
CD44 is widely expressed in most vertebrate cells, whereas the expression of CD44v6 is restricted to only a few tissues and has been considered to be associated with tumor progression and metastasis. Thus, CD44v6 has been recognized as a promising prognostic biomarker and [...] Read more.
CD44 is widely expressed in most vertebrate cells, whereas the expression of CD44v6 is restricted to only a few tissues and has been considered to be associated with tumor progression and metastasis. Thus, CD44v6 has been recognized as a promising prognostic biomarker and therapeutic target for various cancers for more than a decade. However, despite many experimental studies, the structural dynamics and differences between CD44s and CD44v6, particularly in their stem region, still remain elusive. Here, a computational study was conducted to address these problems. We found that the stem of CD44s adopted predominantly two conformations, one featuring antiparallel β-sheets and the other featuring parallel β-sheets, whereas the stem of CD44v6 adopted mainly one conformation with relatively highly suppressed β-sheet contents. Moreover, Phe215 was found to be essential in the β-sheets of both CD44s and CD44v6. We finally found intramolecular Phe215–Trp224 hydrogen-bonding interactions and hydrophobic interactions with Phe215 that cooperatively drove conformational differences upon the addition of the v6 region to CD44. Our study elucidated the structural differences between the stem regions of CD44s and CD44v6 and thus can offer useful structural information for drug design to specifically target CD44v6 in promising clinical applications. Full article
(This article belongs to the Special Issue Computational Studies of Biomolecules)
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Open AccessArticle
Novel Descriptors and Digital Signal Processing- Based Method for Protein Sequence Activity Relationship Study
Int. J. Mol. Sci. 2019, 20(22), 5640; https://doi.org/10.3390/ijms20225640 - 11 Nov 2019
Abstract
The work aiming to unravel the correlation between protein sequence and function in the absence of structural information can be highly rewarding. We present a new way of considering descriptors from the amino acids index database for modeling and predicting the fitness value [...] Read more.
The work aiming to unravel the correlation between protein sequence and function in the absence of structural information can be highly rewarding. We present a new way of considering descriptors from the amino acids index database for modeling and predicting the fitness value of a polypeptide chain. This approach includes the following steps: (i) Calculating Q elementary numerical sequences (Ele_SEQ) depending on the encoding of the amino acid residues, (ii) determining an extended numerical sequence (Ext_SEQ) by concatenating the Q elementary numerical sequences, wherein at least one elementary numerical sequence is a protein spectrum obtained by applying fast Fourier transformation (FFT), and (iii) predicting a value of fitness for polypeptide variants (train and/or validation set). These new descriptors were tested on four sets of proteins of different lengths (GLP-2, TNF alpha, cytochrome P450, and epoxide hydrolase) and activities (cAMP activation, binding affinity, thermostability and enantioselectivity). We show that the use of multiple physicochemical descriptors coupled with the implementation of the FFT, taking into account the interactions between residues of amino acids within the protein sequence, could lead to very significant improvement in the quality of models and predictions. The choice of the descriptor or of the combination of descriptors and/or FFT is dependent on the couple protein/fitness. This approach can provide potential users with value added to existing mutant libraries where screening efforts have so far been unsuccessful in finding improved polypeptide mutants for useful applications. Full article
(This article belongs to the Special Issue Computational Studies of Biomolecules)
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Open AccessArticle
Molecular Cloning and Exploration of the Biochemical and Functional Analysis of Recombinant Glucose-6-Phosphate Dehydrogenase from Gluconoacetobacter diazotrophicus PAL5
Int. J. Mol. Sci. 2019, 20(21), 5279; https://doi.org/10.3390/ijms20215279 - 24 Oct 2019
Abstract
Gluconacetobacter diazotrophicus PAL5 (GDI) is an endophytic bacterium with potential biotechnological applications in industry and agronomy. The recent description of its complete genome and its principal metabolic enzymes suggests that glucose metabolism is accomplished through the pentose phosphate pathway (PPP); however, the enzymes [...] Read more.
Gluconacetobacter diazotrophicus PAL5 (GDI) is an endophytic bacterium with potential biotechnological applications in industry and agronomy. The recent description of its complete genome and its principal metabolic enzymes suggests that glucose metabolism is accomplished through the pentose phosphate pathway (PPP); however, the enzymes participating in this pathway have not yet been characterized in detail. The objective of the present work was to clone, purify, and biochemically and physicochemically characterize glucose-6-phosphate dehydrogenase (G6PD) from GDI. The gene was cloned and expressed as a tagged protein in E. coli to be purified by affinity chromatography. The native state of the G6PD protein in the solution was found to be a tetramer with optimal activity at pH 8.8 and a temperature between 37 and 50 °C. The apparent Km values for G6P and nicotinamide adenine dinucleotide phosphate (NADP+) were 63 and 7.2 μM, respectively. Finally, from the amino acid sequence a three-dimensional (3D) model was obtained, which allowed the arrangement of the amino acids involved in the catalytic activity, which are conserved (RIDHYLGKE, GxGGDLT, and EKPxG) with those of other species, to be identified. This characterization of the enzyme could help to identify new environmental conditions for the knowledge of the plant–microorganism interactions and a better use of GDI in new technological applications. Full article
(This article belongs to the Special Issue Computational Studies of Biomolecules)
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Open AccessArticle
Influence of the First Chromophore-Forming Residue on Photobleaching and Oxidative Photoconversion of EGFP and EYFP
Int. J. Mol. Sci. 2019, 20(20), 5229; https://doi.org/10.3390/ijms20205229 - 22 Oct 2019
Abstract
Enhanced green fluorescent protein (EGFP)—one of the most widely applied genetically encoded fluorescent probes—carries the threonine-tyrosine-glycine (TYG) chromophore. EGFP efficiently undergoes green-to-red oxidative photoconversion (“redding”) with electron acceptors. Enhanced yellow fluorescent protein (EYFP), a close EGFP homologue (five amino acid substitutions), has a [...] Read more.
Enhanced green fluorescent protein (EGFP)—one of the most widely applied genetically encoded fluorescent probes—carries the threonine-tyrosine-glycine (TYG) chromophore. EGFP efficiently undergoes green-to-red oxidative photoconversion (“redding”) with electron acceptors. Enhanced yellow fluorescent protein (EYFP), a close EGFP homologue (five amino acid substitutions), has a glycine-tyrosine-glycine (GYG) chromophore and is much less susceptible to redding, requiring halide ions in addition to the oxidants. In this contribution we aim to clarify the role of the first chromophore-forming amino acid in photoinduced behavior of these fluorescent proteins. To that end, we compared photobleaching and redding kinetics of EGFP, EYFP, and their mutants with reciprocally substituted chromophore residues, EGFP-T65G and EYFP-G65T. Measurements showed that T65G mutation significantly increases EGFP photostability and inhibits its excited-state oxidation efficiency. Remarkably, while EYFP-G65T demonstrated highly increased spectral sensitivity to chloride, it is also able to undergo redding chloride-independently. Atomistic calculations reveal that the GYG chromophore has an increased flexibility, which facilitates radiationless relaxation leading to the reduced fluorescence quantum yield in the T65G mutant. The GYG chromophore also has larger oscillator strength as compared to TYG, which leads to a shorter radiative lifetime (i.e., a faster rate of fluorescence). The faster fluorescence rate partially compensates for the loss of quantum efficiency due to radiationless relaxation. The shorter excited-state lifetime of the GYG chromophore is responsible for its increased photostability and resistance to redding. In EYFP and EYFP-G65T, the chromophore is stabilized by π-stacking with Tyr203, which suppresses its twisting motions relative to EGFP. Full article
(This article belongs to the Special Issue Computational Studies of Biomolecules)
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