scholarly journals Supercomputer-aided Drug Repositioning at Scale: Virtual Screening for SARS-CoV-2 Protease Inhibitor

2020 ◽  
Author(s):  
Sangjae Seo ◽  
Jung Woo Park ◽  
Dosik An ◽  
Junwon Yoon ◽  
Hyojung Paik ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Protease Inhibitor ◽  
Binding Affinity ◽  
High Throughput ◽  
Active Site ◽  
High Throughput Screening ◽  
Drug Repositioning ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Drug Candidates

Coronavirus diseases (COVID-19) outbreak has been labelled a pandemic. For the prioritization of treatments to cope with COVID-19, it is important to conduct rapid high-throughput screening of chemical compounds to repurposing the approved drugs, such as repositioning of chloroquine (Malaria drug) for COVID-19. In this study, exploiting supercomputer resource, we conducted high-throughput virtual screening for potential repositioning candidates of the protease inhibitor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Using the three dimensional structure of main protease (Mpro) of SARS-CoV-2, we evaluated binding affinity between Mpro and drug candidates listed in SWEETLEAD library and ChEMBL database. Docking scores of 19,168 drug molecules at the active site of Mpro were calculated using Autodock Vina package. Among the calculated result, we selected 43 drug candidates and ran molecular dynamics (MD) simulation to further investigate protein-drug interaction. Among compounds that bind to the active site of SARS-CoV-2, we finally selected the 8 drugs showing the highest binding affinity; asunaprevir, atazanavir, dasabuvir, doravirine, fosamprenavir, ritonavir, voxilaprevir and amprenavir, which are the antiviral drugs of hepatitis C virus or human immunodeficiency virus. We expect that the present study provides comprehensive insights into the development of antiviral medication, especially for the treatment of COVID-19.<div><br></div><div>* Attached excel file contains a full list of results of docking calculations</div>

scholarly journals Supercomputer-aided Drug Repositioning at Scale: Virtual Screening for SARS-CoV-2 Protease Inhibitor

2020 ◽  
Author(s):  
Sangjae Seo ◽  
Jung Woo Park ◽  
Dosik An ◽  
Junwon Yoon ◽  
Hyojung Paik ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Protease Inhibitor ◽  
Binding Affinity ◽  
High Throughput ◽  
Active Site ◽  
High Throughput Screening ◽  
Drug Repositioning ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Drug Candidates

Coronavirus diseases (COVID-19) outbreak has been labelled a pandemic. For the prioritization of treatments to cope with COVID-19, it is important to conduct rapid high-throughput screening of chemical compounds to repurposing the approved drugs, such as repositioning of chloroquine (Malaria drug) for COVID-19. In this study, exploiting supercomputer resource, we conducted high-throughput virtual screening for potential repositioning candidates of the protease inhibitor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Using the three dimensional structure of main protease (Mpro) of SARS-CoV-2, we evaluated binding affinity between Mpro and drug candidates listed in SWEETLEAD library and ChEMBL database. Docking scores of 19,168 drug molecules at the active site of Mpro were calculated using Autodock Vina package. Among the calculated result, we selected 43 drug candidates and ran molecular dynamics (MD) simulation to further investigate protein-drug interaction. Among compounds that bind to the active site of SARS-CoV-2, we finally selected the 8 drugs showing the highest binding affinity; asunaprevir, atazanavir, dasabuvir, doravirine, fosamprenavir, ritonavir, voxilaprevir and amprenavir, which are the antiviral drugs of hepatitis C virus or human immunodeficiency virus. We expect that the present study provides comprehensive insights into the development of antiviral medication, especially for the treatment of COVID-19.<div><br></div><div>* Attached excel file contains a full list of results of docking calculations</div>

scholarly journals Virtual High Throughput Screening Based Prediction of Potential Drugs for COVID-19

2020 ◽  
Author(s):  
Sekhar Talluri
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Viral Infections ◽  
Genomic Sequence ◽  
Reproduction Number ◽  
Three Dimensional ◽  
Drug Repurposing ◽  
Dimensional Structure ◽  
Main Protease ◽  
Approved Drugs

SARS-CoV-2 is a betacoronavirus that was first identified during the Wuhan COVID-19 epidemic in 2019. It was listed as a potential global health threat by WHO due to high mortality, high basic reproduction number and lack of clinically approved drugs and vaccines for COVID-19. The genomic sequence of the virus responsible for COVID-19, as well as the experimentally determined three dimensional structure of the Main protease (Mpro) are available. The reported structure of the target Mpro was utilized in this study to identify potential drugs for COVID-19 using virtual high throughput screening. The results of this study confirm earlier preliminary reports based on studies of homologs that some of the drugs approved for treatment of other viral infections also have the potential for treatment of COVID-19. Approved anti-viral drugs that target proteases were ranked for potential effectiveness against COVID-19 and novel candidates for drug repurposing were identified.

High throughput virtual screening based discovery of dengue protease inhibitor

2017 ◽  
Vol 4 (3) ◽  
pp. 35-40
Author(s):  
Sounak Bagchi ◽  
Uzma Alia ◽  
Faiz Mohammad ◽  
Mohd Usman Mohd Siddique
Keyword(s):  
Virtual Screening ◽  
Drug Design ◽  
Protease Inhibitor ◽  
Protease Inhibitors ◽  
High Throughput ◽  
Active Site ◽  
Binding Mode ◽  
Mode Analysis ◽  
Active Site Residues ◽  
High Throughput Virtual Screening

High throughput virtual screening (HTVS) has been proved a successful tool for getting LEADs in drug design and discovery. In an attempt to design new Dengue protease inhibitors, we performed HTVS using Zinc13 database containing 13,195,609 drug-like molecules. ZINC42678127 was identified as potential HIT against Dengue protease. It’s shape and electrostatic complimentary was found to be 0.608 and 0.078, respectively. Qikprop analysis of the compound complied with the Rule of Five (Ro5) and other drug- likeliness properties. Binding mode analysis of docked conformer of ZINC42678127, displayed favorable interaction with the active site residues of DENV protease. The identified HIT has a potential to become a LEAD against Dengue protease.

scholarly journals A Novel Multiparametric Drug-Scoring Method for High-Throughput Screening of 3D Multicellular Tumor Spheroids Using the Celigo Image Cytometer

2017 ◽  
Vol 22 (5) ◽  
pp. 547-557 ◽  
Author(s):  
Scott Cribbes ◽  
Sarah Kessel ◽  
Scott McMenemy ◽  
Jean Qiu ◽  
Leo Li-Ying Chan
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Screening Method ◽  
Three Dimensional ◽  
Cancer Drug ◽  
Multicellular Tumor Spheroids ◽  
Tumor Spheroids ◽  
Scoring Method ◽  
Drug Candidates ◽  
Drug Compounds

Three-dimensional (3D) tumor models have been increasingly used to investigate and characterize cancer drug compounds. The ability to perform high-throughput screening of 3D multicellular tumor spheroids (MCTS) can highly improve the efficiency and cost-effectiveness of discovering potential cancer drug candidates. Previously, the Celigo Image Cytometer has demonstrated a novel method for high-throughput screening of 3D multicellular tumor spheroids. In this work, we employed the Celigo Image Cytometer to examine the effects of 14 cancer drug compounds on 3D MCTS of the glioblastoma cell line U87MG in 384-well plates. Using parameters such as MCTS diameter and invasion area, growth and invasion were monitored for 9 and 3 d, respectively. Furthermore, fluorescent staining with calcein AM, propidium iodide, Hoechst 33342, and caspase 3/7 was performed at day 9 posttreatment to measure viability and apoptosis. Using the kinetic and endpoint data generated, we created a novel multiparametric drug-scoring system for 3D MCTS that can be used to identify and classify potential drug candidates earlier in the drug discovery process. Furthermore, the combination of quantitative and qualitative image data can be used to delineate differences between drugs that induce cytotoxic and cytostatic effects. The 3D MCTS-based multiparametric scoring method described here can provide an alternative screening method to better qualify tested drug compounds.

scholarly journals Structural Features of a Bacteroidetes-Affiliated Cellulase Linked with a Polysaccharide Utilization Locus

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
A.E. Naas ◽  
A.K. MacKenzie ◽  
B. Dalhus ◽  
V.G.H. Eijsink ◽  
P.B. Pope
Keyword(s):  
Active Site ◽  
Three Dimensional ◽  
Structural Features ◽  
Structure And Function ◽  
Dimensional Structure ◽  
Active Site Cleft ◽  
Polysaccharide Utilization Locus ◽  
And Function ◽  
Rumen Metagenome

Abstract Previous gene-centric analysis of a cow rumen metagenome revealed the first potentially cellulolytic polysaccharide utilization locus, of which the main catalytic enzyme (AC2aCel5A) was identified as a glycoside hydrolase (GH) family 5 endo-cellulase. Here we present the 1.8 Å three-dimensional structure of AC2aCel5A and characterization of its enzymatic activities. The enzyme possesses the archetypical (β/α)8-barrel found throughout the GH5 family and contains the two strictly conserved catalytic glutamates located at the C-terminal ends of β-strands 4 and 7. The enzyme is active on insoluble cellulose and acts exclusively on linear β-(1,4)-linked glucans. Co-crystallization of a catalytically inactive mutant with substrate yielded a 2.4 Å structure showing cellotriose bound in the −3 to −1 subsites. Additional electron density was observed between Trp178 and Trp254, two residues that form a hydrophobic “clamp”, potentially interacting with sugars at the +1 and +2 subsites. The enzyme’s active-site cleft was narrower compared to the closest structural relatives, which in contrast to AC2aCel5A, are also active on xylans, mannans and/or xyloglucans. Interestingly, the structure and function of this enzyme seem adapted to less-substituted substrates such as cellulose, presumably due to the insufficient space to accommodate the side-chains of branched glucans in the active-site cleft.

scholarly journals Clarifying intact 3D tissues on a microfluidic chip for high-throughput structural analysis

2016 ◽  
Vol 113 (52) ◽  
pp. 14915-14920 ◽  
Author(s):  
Yih Yang Chen ◽  
Pamuditha N. Silva ◽  
Abdullah Muhammad Syed ◽  
Shrey Sindhwani ◽  
Jonathan V. Rocheleau ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Three Dimensional ◽  
Microfluidic System ◽  
High Throughput Drug Screening ◽  
Image Analysis Algorithm ◽  
Screening Assays ◽  
On Chip ◽  
Tissue Models

On-chip imaging of intact three-dimensional tissues within microfluidic devices is fundamentally hindered by intratissue optical scattering, which impedes their use as tissue models for high-throughput screening assays. Here, we engineered a microfluidic system that preserves and converts tissues into optically transparent structures in less than 1 d, which is 20× faster than current passive clearing approaches. Accelerated clearing was achieved because the microfluidic system enhanced the exchange of interstitial fluids by 567-fold, which increased the rate of removal of optically scattering lipid molecules from the cross-linked tissue. Our enhanced clearing process allowed us to fluorescently image and map the segregation and compartmentalization of different cells during the formation of tumor spheroids, and to track the degradation of vasculature over time within extracted murine pancreatic islets in static culture, which may have implications on the efficacy of beta-cell transplantation treatments for type 1 diabetes. We further developed an image analysis algorithm that automates the analysis of the vasculature connectivity, volume, and cellular spatial distribution of the intact tissue. Our technique allows whole tissue analysis in microfluidic systems, and has implications in the development of organ-on-a-chip systems, high-throughput drug screening devices, and in regenerative medicine.

PREDICTION OF THE THREE-DIMENSIONAL STRUCTURE OF THE ENZYMATIC PART OF T-PA

1987 ◽  
Author(s):  
A Heckel ◽  
K M Hasselbach
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Active Site ◽  
Serine Proteases ◽  
Three Dimensional ◽  
Amino Acid Sequences ◽  
Dimensional Structure ◽  
Salt Bridges ◽  
Three Dimensional Structure ◽  
Insertions And Deletions

Up to now the three-dimensional structure of t-PA or parts of this enzyme is unknown. Using computer graphical methods the spatial structure of the enzymatic part of t-PA is predicted on the hypothesis, the three-dimensional backbone structure of t-PA being similar to that of other serine proteases. The t-PA model was built up in three steps:1) Alignment of the t-PA sequence with other serine proteases. Comparison of enzyme structures available from Brookhaven Protein Data Bank proved elastase as a basis for modeling.2) Exchange of amino acids of elastase differing from the t-PA sequence. The replacement of amino acids was performed such that backbone atoms overlapp completely and side chains superpose as far as possible.3) Modeling of insertions and deletions. To determine the spatial arrangement of insertions and deletions parts of related enzymes such as chymotrypsin or trypsin were used whenever possible. Otherwise additional amino acid sequences were folded to a B-turn at the surface of the proteine, where all insertions or deletions are located. Finally the side chain torsion angles of amino acids were optimised to prevent close contacts of neigh bouring atoms and to improve hydrogen bonds and salt bridges.The resulting model was used to explain binding of arginine 560 of plasminogen to the active site of t-PA. Arginine 560 interacts with Asp 189, Gly 19 3, Ser 19 5 and Ser 214 of t-PA (chymotrypsin numbering). Furthermore interaction of chromo-genic substrate S 2288 with the active site of t-PA was studied. The need for D-configuration of the hydrophobic amino acid at the N-terminus of this tripeptide derivative could be easily explained.

scholarly journals The three-dimensional structure of a class-Pi glutathione S-transferase complexed with glutathione: the active-site hydration provides insights into the reaction mechanism

1998 ◽  
Vol 333 (3) ◽  
pp. 811-816 ◽  
Author(s):  
Antonio PÁRRAGA ◽  
Isabel GARCÍA-SÁEZ ◽  
Sinead B. WALSH ◽  
Timothy J. MANTLE ◽  
Miquel COLL
Keyword(s):  
Conformational Changes ◽  
Active Site ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Water Molecules ◽  
X Ray Diffraction ◽  
Glutathione S Transferase ◽  
X Ray ◽  
The Right

The structure of mouse liver glutathione S-transferase P1-1 complexed with its substrate glutathione (GSH) has been determined by X-ray diffraction analysis. No conformational changes in the glutathione moiety or in the protein, other than small adjustments of some side chains, are observed when compared with glutathione adduct complexes. Our structure confirms that the role of Tyr-7 is to stabilize the thiolate by hydrogen bonding and to position it in the right orientation. A comparison of the enzyme–GSH structure reported here with previously described structures reveals rearrangements in a well-defined network of water molecules in the active site. One of these water molecules (W0), identified in the unliganded enzyme (carboxymethylated at Cys-47), is displaced by the binding of GSH, and a further water molecule (W4) is displaced following the binding of the electrophilic substrate and the formation of the glutathione conjugate. The possibility that one of these water molecules participates in the proton abstraction from the glutathione thiol is discussed.

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