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Special Issue "Computational Design: A New Approach to Drug and Molecular Discovery"

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

Deadline for manuscript submissions: closed (30 April 2016)

Special Issue Editors

Guest Editor
Dr. James W. Gauld

Department of Chemistry and Biochemistry, University of Windsor, Windsor, Ontario N9B 3P4, Canada
Website | E-Mail
Interests: computational chemistry; quantum mechanics/molecular mechanics; molecular dynamics; docking; catalysis; enzymology; thermochemistry; reaction mechanisms; sulfur biochemistry
Guest Editor
Prof. Leif A. Eriksson

Department of Chemistry and Molecular Biology, University of Gothenburg, SE-405 30 Göteborg, Sweden
Website | E-Mail
Interests: computational chemistry; drug design; homology modeling; virtual screening; protein-protein interactions; photochemistry; DNA damage processes; enzymatic reactions; membrane and lipsome simulations

Special Issue Information

Dear Colleagues,

Computational chemistry is well-established as an invaluable approach to studying the properties and/or reactions of a diverse array of chemical and biochemical problems. This is due, in part, to the increasing power of computers and the broad range of computational methods available, such as QSAR, bioinformatics, Docking, molecular dynamics simulations, density functional theory, and quantum mechanics/molecular mechanics (QM/MM). Perhaps most importantly, these methods, or a complementary combination thereof, are often highly reliable and accurate. This power and potential, however, is not limited to known chemical systems. In fact, there is considerable and increasing interest in using such methods to design new and novel chemical systems such as therapeutic drugs, catalysts, and nanomaterials.

This Special Issue of Molecules, “Computational Design: A New Approach to Drug and Molecular Discovery”, highlights both recent developments and applications, as well as the potential of computational chemistry for in silico molecular design.

Dr. James W. Gauld
Prof. Leif A. Eriksson
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. Molecules 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 1800 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

  • Computational Chemistry
  • Molecular Design
  • Biomaterials
  • Therapeutic Drugs
  • Nanomaterials
  • In silico
  • Catalyst

Published Papers (10 papers)

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Research

Jump to: Review

Open AccessArticle Virtual Screening for Potential Allosteric Inhibitors of Cyclin-Dependent Kinase 2 from Traditional Chinese Medicine
Molecules 2016, 21(9), 1259; doi:10.3390/molecules21091259
Received: 19 July 2016 / Revised: 1 September 2016 / Accepted: 17 September 2016 / Published: 21 September 2016
Cited by 3 | PDF Full-text (4098 KB) | HTML Full-text | XML Full-text
Abstract
Cyclin-dependent kinase 2 (CDK2), a member of Cyclin-dependent kinases (CDKs), plays an important role in cell division and DNA replication. It is regarded as a desired target to treat cancer and tumor by interrupting aberrant cell proliferation. Compared to lower subtype selectivity of
[...] Read more.
Cyclin-dependent kinase 2 (CDK2), a member of Cyclin-dependent kinases (CDKs), plays an important role in cell division and DNA replication. It is regarded as a desired target to treat cancer and tumor by interrupting aberrant cell proliferation. Compared to lower subtype selectivity of CDK2 ATP-competitive inhibitors, CDK2 allosteric inhibitor with higher subtype selectivity has been used to treat CDK2-related diseases. Recently, the first crystal structure of CDK2 with allosteric inhibitor has been reported, which provides new opportunities to design pure allosteric inhibitors of CDK2. The binding site of the ATP-competition inhibitors and the allosteric inhibitors are partially overlapped in space position, so the same compound might interact with the two binding sites. Thus a novel screening strategy was essential for the discovery of pure CDK2 allosteric inhibitors. In this study, pharmacophore and molecular docking were used to screen potential CDK2 allosteric inhibitors and ATP-competition inhibitors from Traditional Chinese Medicine (TCM). In the docking result of the allosteric site, the compounds which can act with the CDK2 ATP site were discarded, and the remaining compounds were regarded as the potential pure allosteric inhibitors. Among the results, prostaglandin E1 and nordihydroguaiaretic acid (NDGA) were available and their growth inhibitory effect on human HepG2 cell lines was determined by MTT assay. The two compounds could substantially inhibit the growth of HepG2 cell lines with an estimated IC50 of 41.223 μmol/L and 45.646 μmol/L. This study provides virtual screening strategy of allosteric compounds and a reliable method to discover potential pure CDK2 allosteric inhibitors from TCM. Prostaglandin E1 and NDGA could be regarded as promising candidates for CDK2 allosteric inhibitors. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
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Open AccessArticle Glutamine Synthetase Drugability beyond Its Active Site: Exploring Oligomerization Interfaces and Pockets
Molecules 2016, 21(8), 1028; doi:10.3390/molecules21081028
Received: 8 June 2016 / Revised: 1 August 2016 / Accepted: 4 August 2016 / Published: 8 August 2016
Cited by 2 | PDF Full-text (6027 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Background: Glutamine synthetase (GS) is a crucial enzyme to the nitrogen cycle with great commercial and pharmaceutical value. Current inhibitors target the active site, affecting GS activity indiscriminately in all organisms. As the active site is located at the interface between two
[...] Read more.
Background: Glutamine synthetase (GS) is a crucial enzyme to the nitrogen cycle with great commercial and pharmaceutical value. Current inhibitors target the active site, affecting GS activity indiscriminately in all organisms. As the active site is located at the interface between two monomers, the protein-protein interface (PPI) of GSs gains a new role, by providing new targets for enzyme inhibition. Exploring GSs PPI could allow for the development of inhibitors selective for specific organisms. Here we map the PPI of three GSs—human (hsGS), maize (zmGS) and Mycobacterium tuberculosis (mtGS)—and unravel new drugable pockets. Methods: The PPI binding free energy coming from key residues on three GSs from different organisms were mapped by computational alanine scan mutagenesis, applying a multiple dielectric constant MM-PBSA methodology. The most relevant residues for binding are referred as hot-spots. Drugable pockets on GS were detected with the Fpocket software. Results and Conclusions: A total of 23, 19 and 30 hot-spots were identified on hsGS, zmGS and mtGS PPI. Even possessing differences in the hot-spots, hsGS and zmGS PPI are overall very similar. On the other hand, mtGS PPI differs greatly from hsGS and zmGS PPI. A novel drugable pocket was detected on the mtGS PPI. It seems particularly promising for the development of selective anti-tuberculosis drugs given its location on a PPI region that is highly populated with hot-spots and is completely different from the hsGS and zmGS PPIs. Drugs targeting this pockets should be inactive on eukaryotic GS II enzymes. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
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Open AccessArticle Computational Evaluation of Nucleotide Insertion Opposite Expanded and Widened DNA by the Translesion Synthesis Polymerase Dpo4
Molecules 2016, 21(7), 822; doi:10.3390/molecules21070822
Received: 16 May 2016 / Revised: 8 June 2016 / Accepted: 14 June 2016 / Published: 23 June 2016
PDF Full-text (3958 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Expanded (x) and widened (y) deoxyribose nucleic acids (DNA) have an extra benzene ring incorporated either horizontally (xDNA) or vertically (yDNA) between a natural pyrimidine base and the deoxyribose, or between the 5- and 6-membered rings of a natural purine. Far-reaching applications for
[...] Read more.
Expanded (x) and widened (y) deoxyribose nucleic acids (DNA) have an extra benzene ring incorporated either horizontally (xDNA) or vertically (yDNA) between a natural pyrimidine base and the deoxyribose, or between the 5- and 6-membered rings of a natural purine. Far-reaching applications for (x,y)DNA include nucleic acid probes and extending the natural genetic code. Since modified nucleobases must encode information that can be passed to the next generation in order to be a useful extension of the genetic code, the ability of translesion (bypass) polymerases to replicate modified bases is an active area of research. The common model bypass polymerase DNA polymerase IV (Dpo4) has been previously shown to successfully replicate and extend past a single modified nucleobase on a template DNA strand. In the current study, molecular dynamics (MD) simulations are used to evaluate the accommodation of expanded/widened nucleobases in the Dpo4 active site, providing the first structural information on the replication of (x,y)DNA. Our results indicate that the Dpo4 catalytic (palm) domain is not significantly impacted by the (x,y)DNA bases. Instead, the template strand is displaced to accommodate the increased C1’–C1’ base-pair distance. The structural insights unveiled in the present work not only increase our fundamental understanding of Dpo4 replication, but also reveal the process by which Dpo4 replicates (x,y)DNA, and thereby will contribute to the optimization of high fidelity and efficient polymerases for the replication of modified nucleobases. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
Open AccessArticle Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking
Molecules 2016, 21(7), 823; doi:10.3390/molecules21070823
Received: 10 May 2016 / Revised: 8 June 2016 / Accepted: 18 June 2016 / Published: 23 June 2016
Cited by 2 | PDF Full-text (17125 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O6 position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have
[...] Read more.
DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O6 position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O6-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR) study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment) were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Qcv2 = 0.672 and Rncv2 = 0.997) and CoMSIA (Qcv2 = 0.703 and Rncv2 = 0.946) models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Qext2 = 0.691, Rpred2 = 0.738 and slope k = 0.91) was observed with acceptable external test-set validation values rather than the CoMSIA model (Qext2 = 0.307, Rpred2 = 0.4 and slope k = 0.719). Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
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Open AccessArticle In Silico Investigation of Traditional Chinese Medicine for Potential Lead Compounds as SPG7 Inhibitors against Coronary Artery Disease
Molecules 2016, 21(5), 588; doi:10.3390/molecules21050588
Received: 22 March 2016 / Revised: 22 April 2016 / Accepted: 29 April 2016 / Published: 5 May 2016
PDF Full-text (14859 KB) | HTML Full-text | XML Full-text
Abstract
Coronary artery disease (CAD) is the most common cause of heart attack and the leading cause of mortality in the world. It is associated with mitochondrial dysfunction and increased level of reactive oxygen species production. According to the Ottawa Heart Genomics Study genome-wide
[...] Read more.
Coronary artery disease (CAD) is the most common cause of heart attack and the leading cause of mortality in the world. It is associated with mitochondrial dysfunction and increased level of reactive oxygen species production. According to the Ottawa Heart Genomics Study genome-wide association study, a recent research identified that Q688 spastic paraplegia 7 (SPG7) variant is associated with CAD as it bypasses the regulation of tyrosine phosphorylation of AFG3L2 and enhances the processing and maturation of SPG7 protein. This study aims to identify potential compounds isolated from Traditional Chinese Medicines (TCMs) as potential lead compounds for paraplegin (SPG7) inhibitors. For the crystallographic structure of paraplegin, the disordered disposition of key amino acids in the binding site was predicted using the PONDR-Fit protocol before virtual screening. The TCM compounds saussureamine C and 3-(2-carboxyphenyl)-4(3H)-quinazolinone, have potential binding affinities with stable H-bonds and hydrophobic contacts with key residues of paraplegin. A molecular dynamics simulation was performed to validate the stability of the interactions between each candidate and paraplegin under dynamic conditions. Hence, we propose these compounds as potential candidates as lead drug from the compounds isolated from TCM for further study in drug development process with paraplegin protein for coronary artery disease. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
Open AccessArticle Calculation of Relative Binding Free Energy in the Water-Filled Active Site of Oligopeptide-Binding Protein A
Molecules 2016, 21(4), 499; doi:10.3390/molecules21040499
Received: 1 March 2016 / Revised: 30 March 2016 / Accepted: 11 April 2016 / Published: 15 April 2016
Cited by 2 | PDF Full-text (3685 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The periplasmic oligopeptide binding protein A (OppA) represents a well-known example of water-mediated protein-ligand interactions. Here, we perform free-energy calculations for three different ligands binding to OppA, using a thermodynamic integration approach. The tripeptide ligands share a high structural similarity (all have the
[...] Read more.
The periplasmic oligopeptide binding protein A (OppA) represents a well-known example of water-mediated protein-ligand interactions. Here, we perform free-energy calculations for three different ligands binding to OppA, using a thermodynamic integration approach. The tripeptide ligands share a high structural similarity (all have the sequence KXK), but their experimentally-determined binding free energies differ remarkably. Thermodynamic cycles were constructed for the ligands, and simulations conducted in the bound and (freely solvated) unbound states. In the unbound state, it was observed that the difference in conformational freedom between alanine and glycine leads to a surprisingly slow convergence, despite their chemical similarity. This could be overcome by increasing the softness parameter during alchemical transformations. Discrepancies remained in the bound state however, when comparing independent simulations of the three ligands. These difficulties could be traced to a slow relaxation of the water network within the active site. Fluctuations in the number of water molecules residing in the binding cavity occur mostly on a timescale larger than the simulation time along the alchemical path. After extensive simulations, relative binding free energies that were converged to within thermal noise could be obtained, which agree well with available experimental data. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
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Open AccessArticle Improved Homology Model of the Human all-trans Retinoic Acid Metabolizing Enzyme CYP26A1
Molecules 2016, 21(3), 351; doi:10.3390/molecules21030351
Received: 17 February 2016 / Revised: 7 March 2016 / Accepted: 9 March 2016 / Published: 15 March 2016
PDF Full-text (7066 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A new CYP26A1 homology model was built based on the crystal structure of cyanobacterial CYP120A1. The model quality was examined for stereochemical accuracy, folding reliability, and absolute quality using a variety of different bioinformatics tools. Furthermore, the docking capabilities of the model were
[...] Read more.
A new CYP26A1 homology model was built based on the crystal structure of cyanobacterial CYP120A1. The model quality was examined for stereochemical accuracy, folding reliability, and absolute quality using a variety of different bioinformatics tools. Furthermore, the docking capabilities of the model were assessed by docking of the natural substrate all-trans-retinoic acid (atRA), and a group of known azole- and tetralone-based CYP26A1 inhibitors. The preferred binding pose of atRA suggests the (4S)-OH-atRA metabolite production, in agreement with recently available experimental data. The distances between the ligands and the heme group iron of the enzyme are in agreement with corresponding distances obtained for substrates and azole inhibitors for other cytochrome systems. The calculated theoretical binding energies agree with recently reported experimental data and show that the model is capable of discriminating between natural substrate, strong inhibitors (R116010 and R115866), and weak inhibitors (liarozole, fluconazole, tetralone derivatives). Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
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Open AccessArticle Exploration of Scaffolds from Natural Products with Antiplasmodial Activities, Currently Registered Antimalarial Drugs and Public Malarial Screen Data
Molecules 2016, 21(1), 104; doi:10.3390/molecules21010104
Received: 9 November 2015 / Revised: 6 January 2016 / Accepted: 12 January 2016 / Published: 16 January 2016
Cited by 1 | PDF Full-text (3501 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In light of current resistance to antimalarial drugs, there is a need to discover new classes of antimalarial agents with unique mechanisms of action. Identification of unique scaffolds from natural products with in vitro antiplasmodial activities may be the starting point for such
[...] Read more.
In light of current resistance to antimalarial drugs, there is a need to discover new classes of antimalarial agents with unique mechanisms of action. Identification of unique scaffolds from natural products with in vitro antiplasmodial activities may be the starting point for such new classes of antimalarial agents. We therefore conducted scaffold diversity and comparison analysis of natural products with in vitro antiplasmodial activities (NAA), currently registered antimalarial drugs (CRAD) and malaria screen data from Medicine for Malaria Ventures (MMV). The scaffold diversity analyses on the three datasets were performed using scaffold counts and cumulative scaffold frequency plots. Scaffolds from the NAA were compared to those from CRAD and MMV. A Scaffold Tree was also generated for each of the datasets and the scaffold diversity of NAA was found to be higher than that of MMV. Among the NAA compounds, we identified unique scaffolds that were not contained in any of the other compound datasets. These scaffolds from NAA also possess desirable drug-like properties making them ideal starting points for antimalarial drug design considerations. The Scaffold Tree showed the preponderance of ring systems in NAA and identified virtual scaffolds, which may be potential bioactive compounds. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
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Review

Jump to: Research

Open AccessReview Computational Approaches to Toll-Like Receptor 4 Modulation
Molecules 2016, 21(8), 994; doi:10.3390/molecules21080994
Received: 23 May 2016 / Revised: 22 July 2016 / Accepted: 22 July 2016 / Published: 30 July 2016
Cited by 6 | PDF Full-text (6357 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Toll-like receptor 4 (TLR4), along with its accessory protein myeloid differentiation factor 2 (MD-2), builds a heterodimeric complex that specifically recognizes lipopolysaccharides (LPS), which are present on the cell wall of Gram-negative bacteria, activating the innate immune response. Some TLR4 modulators are undergoing
[...] Read more.
Toll-like receptor 4 (TLR4), along with its accessory protein myeloid differentiation factor 2 (MD-2), builds a heterodimeric complex that specifically recognizes lipopolysaccharides (LPS), which are present on the cell wall of Gram-negative bacteria, activating the innate immune response. Some TLR4 modulators are undergoing preclinical and clinical evaluation for the treatment of sepsis, inflammatory diseases, cancer and rheumatoid arthritis. Since the relatively recent elucidation of the X-ray crystallographic structure of the extracellular domain of TLR4, research around this fascinating receptor has risen to a new level, and thus, new perspectives have been opened. In particular, diverse computational techniques have been applied to decipher some of the basis at the atomic level regarding the mechanism of functioning and the ligand recognition processes involving the TLR4/MD-2 system at the atomic level. This review summarizes the reported molecular modeling and computational studies that have recently provided insights into the mechanism regulating the activation/inactivation of the TLR4/MD-2 system receptor and the key interactions modulating the molecular recognition process by agonist and antagonist ligands. These studies have contributed to the design and the discovery of novel small molecules with promising activity as TLR4 modulators. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
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Open AccessFeature PaperReview Computational Approaches for the Discovery of Human Proteasome Inhibitors: An Overview
Molecules 2016, 21(7), 927; doi:10.3390/molecules21070927
Received: 9 May 2016 / Revised: 11 July 2016 / Accepted: 12 July 2016 / Published: 16 July 2016
Cited by 2 | PDF Full-text (2768 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Proteasome emerged as an important target in recent pharmacological research due to its pivotal role in degrading proteins in the cytoplasm and nucleus of eukaryotic cells, regulating a wide variety of cellular pathways, including cell growth and proliferation, apoptosis, DNA repair, transcription, immune
[...] Read more.
Proteasome emerged as an important target in recent pharmacological research due to its pivotal role in degrading proteins in the cytoplasm and nucleus of eukaryotic cells, regulating a wide variety of cellular pathways, including cell growth and proliferation, apoptosis, DNA repair, transcription, immune response, and signaling processes. The last two decades witnessed intensive efforts to discover 20S proteasome inhibitors with significant chemical diversity and efficacy. To date, the US FDA approved to market three proteasome inhibitors: bortezomib, carfilzomib, and ixazomib. However new, safer and more efficient drugs are still required. Computer-aided drug discovery has long being used in drug discovery campaigns targeting the human proteasome. The aim of this review is to illustrate selected in silico methods like homology modeling, molecular docking, pharmacophore modeling, virtual screening, and combined methods that have been used in proteasome inhibitors discovery. Applications of these methods to proteasome inhibitors discovery will also be presented and discussed to raise improvements in this particular field. Full article
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
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