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Molecules
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Selected Papers from Computational Structural Bioinformatics Workshop 2020 (CSBW-2020)
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Selected Papers from Computational Structural Bioinformatics Workshop 2020 (CSBW-2020)

A special issue of Molecules (ISSN 1420-3049).

Deadline for manuscript submissions: closed (15 March 2021) | Viewed by 15110

Special Issue Editors

Dr. Filip Jagodzinski

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Guest Editor
Computer Science, Western Washington University, Bellingham, WA, USA
Special Issues, Collections and Topics in MDPI journals
Dr. Kevin Molloy

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Guest Editor
Computer Science, James Madison University, Harrisonburg, VA, USA

Special Issue Information

Dear Colleagues,

The three-dimensional structure and function of molecules present many challenges and opportunities for developing an understanding of biological systems. With the increasing availability of molecular structures and the advancing accuracy of structure predictions and molecular simulations, the space for algorithmic advancement in many analytical and predictive problems is both broad and deep. CSBW provided a forum for discussing cutting-edge computational results in computational structural bioinformatics.

The list of topics from the workshop, from which keywords can be extracted, is as follows:

  • Structure representation, prediction, and alignment
  • Interaction and docking
  • Molecular simulations
  • Coarse-grained modeling
  • Biomolecular graphics
  • Data mining
  • Structural genomics, and optimization in structural problems
  • High-performance computing in modeling
  • Graph theory applied to structural problems
  • Structure-based drug design and QSAR

Dr. Filip Jagodzinski
Dr. Kevin Molloy
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 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.

Published Papers (4 papers)

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Research

16 pages, 2584 KiB  
Article
Combining Cryo-EM Density Map and Residue Contact for Protein Secondary Structure Topologies
by Maytha Alshammari and Jing He
Molecules 2021, 26(22), 7049; https://doi.org/10.3390/molecules26227049 - 22 Nov 2021
Viewed by 2352
Abstract
Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a [...] Read more.
Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments and a set of traces of secondary structures in three-dimensional space. In order to enhance accuracy in ranking secondary structure topologies, we explored a method that combines three sources of information: a set of sequence segments in 1D, a set of amino acid contact pairs in 2D, and a set of traces in 3D at the secondary structure level. A test of fourteen cases shows that the accuracy of predicted secondary structures is critical for deriving topologies. The use of significant long-range contact pairs is most effective at enriching the rank of the maximum-match topology for proteins with a large number of secondary structures, if the secondary structure prediction is fairly accurate. It was observed that the enrichment depends on the quality of initial topology candidates in this approach. We provide detailed analysis in various cases to show the potential and challenge when combining three sources of information. Full article
(This article belongs to the Special Issue Selected Papers from Computational Structural Bioinformatics Workshop 2020 (CSBW-2020))
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14 pages, 5131 KiB  
Article
An Effective MM/GBSA Protocol for Absolute Binding Free Energy Calculations: A Case Study on SARS-CoV-2 Spike Protein and the Human ACE2 Receptor
by Negin Forouzesh and Nikita Mishra
Molecules 2021, 26(8), 2383; https://doi.org/10.3390/molecules26082383 - 20 Apr 2021
Cited by 56 | Viewed by 8124
Abstract
The binding free energy calculation of protein–ligand complexes is necessary for research into virus–host interactions and the relevant applications in drug discovery. However, many current computational methods of such calculations are either inefficient or inaccurate in practice. Utilizing implicit solvent models in the [...] Read more.
The binding free energy calculation of protein–ligand complexes is necessary for research into virus–host interactions and the relevant applications in drug discovery. However, many current computational methods of such calculations are either inefficient or inaccurate in practice. Utilizing implicit solvent models in the molecular mechanics generalized Born surface area (MM/GBSA) framework allows for efficient calculations without significant loss of accuracy. Here, GBNSR6, a new flavor of the generalized Born model, is employed in the MM/GBSA framework for measuring the binding affinity between SARS-CoV-2 spike protein and the human ACE2 receptor. A computational protocol is developed based on the widely studied Ras–Raf complex, which has similar binding free energy to SARS-CoV-2/ACE2. Two options for representing the dielectric boundary of the complexes are evaluated: one based on the standard Bondi radii and the other based on a newly developed set of atomic radii (OPT1), optimized specifically for protein–ligand binding. Predictions based on the two radii sets provide upper and lower bounds on the experimental references: −14.7(ΔGbindBondi)<−10.6(ΔGbindExp.)<−4.1(ΔGbindOPT1) kcal/mol. The consensus estimates of the two bounds show quantitative agreement with the experiment values. This work also presents a novel truncation method and computational strategies for efficient entropy calculations with normal mode analysis. Interestingly, it is observed that a significant decrease in the number of snapshots does not affect the accuracy of entropy calculation, while it does lower computation time appreciably. The proposed MM/GBSA protocol can be used to study the binding mechanism of new variants of SARS-CoV-2, as well as other relevant structures. Full article
(This article belongs to the Special Issue Selected Papers from Computational Structural Bioinformatics Workshop 2020 (CSBW-2020))
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15 pages, 1241 KiB  
Article
Integrating Rigidity Analysis into the Exploration of Protein Conformational Pathways Using RRT* and MC
by Fatemeh Afrasiabi, Ramin Dehghanpoor and Nurit Haspel
Molecules 2021, 26(8), 2329; https://doi.org/10.3390/molecules26082329 - 16 Apr 2021
Viewed by 1733
Abstract
To understand how proteins function on a cellular level, it is of paramount importance to understand their structures and dynamics, including the conformational changes they undergo to carry out their function. For the aforementioned reasons, the study of large conformational changes in proteins [...] Read more.
To understand how proteins function on a cellular level, it is of paramount importance to understand their structures and dynamics, including the conformational changes they undergo to carry out their function. For the aforementioned reasons, the study of large conformational changes in proteins has been an interest to researchers for years. However, since some proteins experience rapid and transient conformational changes, it is hard to experimentally capture the intermediate structures. Additionally, computational brute force methods are computationally intractable, which makes it impossible to find these pathways which require a search in a high-dimensional, complex space. In our previous work, we implemented a hybrid algorithm that combines Monte-Carlo (MC) sampling and RRT*, a version of the Rapidly Exploring Random Trees (RRT) robotics-based method, to make the conformational exploration more accurate and efficient, and produce smooth conformational pathways. In this work, we integrated the rigidity analysis of proteins into our algorithm to guide the search to explore flexible regions. We demonstrate that rigidity analysis dramatically reduces the run time and accelerates convergence. Full article
(This article belongs to the Special Issue Selected Papers from Computational Structural Bioinformatics Workshop 2020 (CSBW-2020))
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16 pages, 31895 KiB  
Article
Identification of Potential HCV Inhibitors Based on the Interaction of Epigallocatechin-3-Gallate with Viral Envelope Proteins
by Fareena Shahid, Noreen, Roshan Ali, Syed Lal Badshah, Syed Babar Jamal, Riaz Ullah, Ahmed Bari, Hafiz Majid Mahmood, Muhammad Sohaib and Siddique Akber Ansari
Molecules 2021, 26(5), 1257; https://doi.org/10.3390/molecules26051257 - 26 Feb 2021
Cited by 9 | Viewed by 2012
Abstract
Hepatitis C is affecting millions of people around the globe annually, which leads to death in very high numbers. After many years of research, hepatitis C virus (HCV) remains a serious threat to the human population and needs proper management. The in silico [...] Read more.
Hepatitis C is affecting millions of people around the globe annually, which leads to death in very high numbers. After many years of research, hepatitis C virus (HCV) remains a serious threat to the human population and needs proper management. The in silico approach in the drug discovery process is an efficient method in identifying inhibitors for various diseases. In our study, the interaction between Epigallocatechin-3-gallate, a component of green tea, and envelope glycoprotein E2 of HCV is evaluated. Epigallocatechin-3-gallate is the most promising polyphenol approved through cell culture analysis that can inhibit the entry of HCV. Therefore, various in silico techniques have been employed to find out other potential inhibitors that can behave as EGCG. Thus, the homology modelling of E2 protein was performed. The potential lead molecules were predicted using ligand-based as well as structure-based virtual screening methods. The compounds obtained were then screened through PyRx. The drugs obtained were ranked based on their binding affinities. Furthermore, the docking of the topmost drugs was performed by AutoDock Vina, while its 2D interactions were plotted in LigPlot+. The lead compound mms02387687 (2-[[5-[(4-ethylphenoxy) methyl]-4-prop-2-enyl-1,2,4-triazol-3-yl] sulfanyl]-N-[3(trifluoromethyl) phenyl] acetamide) was ranked on top, and we believe it can serve as a drug against HCV in the future, owing to experimental validation. Full article
(This article belongs to the Special Issue Selected Papers from Computational Structural Bioinformatics Workshop 2020 (CSBW-2020))
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