scholarly journals Non-covalent TMPRSS2 inhibitors identified from virtual screening

2020 ◽  
Author(s):  
Xin Hu ◽  
Jonathan H. Shrimp ◽  
Hui Guo ◽  
Alexey Zakharov ◽  
Sankalp Jain ◽  
...  
Keyword(s):  
Life Cycle ◽  
Virtual Screening ◽  
Membrane Fusion ◽  
Large Scale ◽  
Spike Protein ◽  
Binding Model ◽  
Drug Candidates ◽  
Database Screening ◽  
Further Development ◽  
Significant Attention

AbstractThe SARS-CoV-2 pandemic has prompted researchers to pivot their efforts to finding anti-viral compounds and vaccines. In this study, we focused on the human host cell transmembrane protease serine 2 (TMPRSS2), which plays an important role in the viral life cycle by cleaving the spike protein to initiate membrane fusion. TMPRSS2 is an attractive target and has received significant attention for the development of drugs against SARS and MERS. Starting with comparative structural modeling and binding model analysis, we developed an efficient pharmacophore-based approach and applied in a large-scale in silico database screening for small molecule inhibitors against TMPRSS2. A number of novel inhibitors were identified, providing starting points for further development of drug candidates for the treatment of COVID-19.

scholarly journals A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening

2020 ◽  
Author(s):  
Christoph Gorgulla ◽  
Krishna PadmanabhaDas ◽  
Kendra E. Leigh ◽  
Marco Cespugli ◽  
Patrick D. Fischer ◽  
...  
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Active Sites ◽  
Large Scale ◽  
Protein Protein Interaction ◽  
The Face ◽  
Computing Platforms ◽  
Screening Platform ◽  
Novel Coronavirus ◽  
Further Development

<p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed <i>in silico</i> screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 <i>in silico</i> hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development.</p>

Neutralization of SARS-CoV-2 Spike Protein via Natural Compounds: A Multilayered High Throughput Virtual Screening Approach

2020 ◽  
Vol 26 (41) ◽  
pp. 5300-5309 ◽  
Author(s):  
Anupam Dhasmana ◽  
Vivek K. Kashyap ◽  
Swati Dhasmana ◽  
Sudhir Kotnala ◽  
Shafiul Haque ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Digital Libraries ◽  
Methodological Approach ◽  
Natural Compounds ◽  
Therapeutic Interventions ◽  
Spike Protein ◽  
Human Society ◽  
Emerging Viruses ◽  
Screening Process ◽  
Drug Candidates

Background: Previously human society has faced various unprecedented pandemics in the history and viruses have majorly held the responsibilities of those outbreaks. Furthermore, due to amplified global connection and speedy modernization, epidemic outbreaks caused by novel and re-emerging viruses signify potential risk to community health. Despite great advancements in immunization and drug discovery processes, various viruses still lack prophylactic vaccines and efficient antiviral therapies. Although, vaccine is a prophylaxes option, but it cannot be applied to infected patients, hence therapeutic interventions are urgently needed to control the ongoing global SARS- CoV-2 pandemic condition. To spot the novel antiviral therapy is of decisive importance and Mother Nature is an excellent source for such discoveries. Methodology: In this article, prompt high through-put virtual screening for vetting the best possible drug candidates from natural compounds’ databases has been implemented. Herein, time tested rigorous multi-layered drug screening process to narrow down 66,969 natural compounds for the identification of potential lead(s) is implemented. Druggability parameters, different docking approaches and neutralization tendency of the natural products were employed in this study to screen the best possible natural compounds from the digital libraries. Conclusion: The results of this study conclude that compounds PALA and HMCA are potential inhibitors of SARS-CoV-2 spike protein and can be further explored for experimental validation. Overall, the methodological approach reported in this article can be suitably used to find the potential drug candidates against SARS-CoV2 in the burning situation of COVID-19 with less expenditure and a concise span of time.

scholarly journals A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening

2020 ◽  
Author(s):  
Christoph Gorgulla ◽  
Krishna PadmanabhaDas ◽  
Kendra E. Leigh ◽  
Marco Cespugli ◽  
Patrick D. Fischer ◽  
...  
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Active Sites ◽  
Large Scale ◽  
Protein Protein Interaction ◽  
The Face ◽  
Computing Platforms ◽  
Screening Platform ◽  
Novel Coronavirus ◽  
Further Development

<p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed <i>in silico</i> screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 <i>in silico</i> hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development.</p>

scholarly journals Environmental Product Declarations for plants and soils: how to quantify carbon uptake in landscape design and construction?

2021 ◽  
Author(s):  
Matti Kuittinen ◽  
Ranja Hautamäki ◽  
Eeva-Maria Tuhkanen ◽  
Anu Riikonen ◽  
Mari Ariluoma
Keyword(s):  
Life Cycle ◽  
Green Infrastructure ◽  
Landscape Design ◽  
Climate Impacts ◽  
Mitigation Potential ◽  
Environmental Product Declarations ◽  
Construction Products ◽  
Further Development ◽  
Change Mitigation ◽  
Design And Construction

Abstract Purpose Currently, no clear guidance exists for ISO and EN standards of calculating, verifying, and reporting the climate impacts of plants, mulches, and soils used in landscape design and construction. In order to optimise the potential of ecosystem services in the mitigation of greenhouse gas emissions in the built environment, we unequivocally propose their inclusion when assessing sustainability. Methods We analysed the life cycle phases of plants, soils, and mulches from the viewpoint of compiling standard-based Environmental Product Declarations. In comparison to other construction products, the differences of both mass and carbon flows were identified in these products. Results Living and organic products of green infrastructure require an LCA approach of their own. Most importantly, if conventional life cycle guidance for Environmental Product Declarations were to be followed, over time, the asymmetric mass and carbon flows would lead to skewed conclusions. Moreover, the ability of plants to reproduce raises additional questions for allocating environmental impacts. Conclusions We present a set of recommendations that are required for compiling Environmental Product Declarations for the studied products of green infrastructure. In order to enable the quantification of the climate change mitigation potential of these products, it is essential that work for further development of LCA guidance be mandated.

scholarly journals A novel ligand of the translationally controlled tumor protein (TCTP) identified by virtual drug screening for cancer differentiation therapy

2021 ◽  
Author(s):  
Nicolas Fischer ◽  
Ean-Jeong Seo ◽  
Sara Abdelfatah ◽  
Edmond Fleischer ◽  
Anette Klinger ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Virtual Screening ◽  
Small Molecules ◽  
Large Scale ◽  
Differentiation Therapy ◽  
P53 Expression ◽  
Microscale Thermophoresis ◽  
Cycle Arrest ◽  
G1 Cell Cycle Arrest ◽  
Mcf 7

SummaryIntroduction Differentiation therapy is a promising strategy for cancer treatment. The translationally controlled tumor protein (TCTP) is an encouraging target in this context. By now, this field of research is still at its infancy, which motivated us to perform a large-scale screening for the identification of novel ligands of TCTP. We studied the binding mode and the effect of TCTP blockade on the cell cycle in different cancer cell lines. Methods Based on the ZINC-database, we performed virtual screening of 2,556,750 compounds to analyze the binding of small molecules to TCTP. The in silico results were confirmed by microscale thermophoresis. The effect of the new ligand molecules was investigated on cancer cell survival, flow cytometric cell cycle analysis and protein expression by Western blotting and co-immunoprecipitation in MOLT-4, MDA-MB-231, SK-OV-3 and MCF-7 cells. Results Large-scale virtual screening by PyRx combined with molecular docking by AutoDock4 revealed five candidate compounds. By microscale thermophoresis, ZINC10157406 (6-(4-fluorophenyl)-2-[(8-methoxy-4-methyl-2-quinazolinyl)amino]-4(3H)-pyrimidinone) was identified as TCTP ligand with a KD of 0.87 ± 0.38. ZINC10157406 revealed growth inhibitory effects and caused G0/G1 cell cycle arrest in MOLT-4, SK-OV-3 and MCF-7 cells. ZINC10157406 (2 × IC50) downregulated TCTP expression by 86.70 ± 0.44% and upregulated p53 expression by 177.60 ± 12.46%. We validated ZINC10157406 binding to the p53 interaction site of TCTP and replacing p53 by co-immunoprecipitation. Discussion ZINC10157406 was identified as potent ligand of TCTP by in silico and in vitro methods. The compound bound to TCTP with a considerably higher affinity compared to artesunate as known TCTP inhibitor. We were able to demonstrate the effect of TCTP blockade at the p53 binding site, i.e. expression of TCTP decreased, whereas p53 expression increased. This effect was accompanied by a dose-dependent decrease of CDK2, CDK4, CDK, cyclin D1 and cyclin D3 causing a G0/G1 cell cycle arrest in MOLT-4, SK-OV-3 and MCF-7 cells. Our findings are supposed to stimulate further research on TCTP-specific small molecules for differentiation therapy in oncology.

scholarly journals Immunization with RBD-P2 and N protects against SARS-CoV-2 in nonhuman primates

2021 ◽  
Vol 7 (22) ◽  
pp. eabg7156
Author(s):  
So-Hee Hong ◽  
Hanseul Oh ◽  
Yong Wook Park ◽  
Hye Won Kwak ◽  
Eun Young Oh ◽  
...  
Keyword(s):  
Nucleocapsid Protein ◽  
Nonhuman Primates ◽  
Vaccine Candidate ◽  
Statistical Significance ◽  
Neutralizing Antibody ◽  
Spike Protein ◽  
Vaccine Candidates ◽  
Cell Responses ◽  
Antibody Levels ◽  
Further Development

Since the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), various vaccines are being developed, with most vaccine candidates focusing on the viral spike protein. Here, we developed a previously unknown subunit vaccine comprising the receptor binding domain (RBD) of the spike protein fused with the tetanus toxoid epitope P2 (RBD-P2) and tested its efficacy in rodents and nonhuman primates (NHPs). We also investigated whether the SARS-CoV-2 nucleocapsid protein (N) could increase vaccine efficacy. Immunization with N and RBD-P2 (RBDP2/N) + alum increased T cell responses in mice and neutralizing antibody levels in rats compared with those obtained using RBD-P2 + alum. Furthermore, in NHPs, RBD-P2/N + alum induced slightly faster SARS-CoV-2 clearance than that induced by RBD-P2 + alum, albeit without statistical significance. Our study supports further development of RBD-P2 as a vaccine candidate against SARS-CoV-2. Also, it provides insights regarding the use of N in protein-based vaccines against SARS-CoV-2.

scholarly journals Comparative Analysis of the Life-Cycle Cost of Robot Substitution: A Case of Automobile Welding Production in China

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 226
Author(s):  
Xuyang Zhao ◽  
Cisheng Wu ◽  
Duanyong Liu
Keyword(s):  
Life Cycle ◽  
Systems Engineering ◽  
Life Cycle Cost ◽  
Manufacturing Systems ◽  
Large Scale ◽  
Cost Allocation ◽  
Industrial Robot ◽  
Case Analysis ◽  
Industrial Robots ◽  
Analysis Model

Within the context of the large-scale application of industrial robots, methods of analyzing the life-cycle cost (LCC) of industrial robot production have shown considerable developments, but there remains a lack of methods that allow for the examination of robot substitution. Taking inspiration from the symmetry philosophy in manufacturing systems engineering, this article further establishes a comparative LCC analysis model to compare the LCC of the industrial robot production with traditional production at the same time. This model introduces intangible costs (covering idle loss, efficiency loss and defect loss) to supplement the actual costs and comprehensively uses various methods for cost allocation and variable estimation to conduct total cost and the cost efficiency analysis, together with hierarchical decomposition and dynamic comparison. To demonstrate the model, an investigation of a Chinese automobile manufacturer is provided to compare the LCC of welding robot production with that of manual welding production; methods of case analysis and simulation are combined, and a thorough comparison is done with related existing works to show the validity of this framework. In accordance with this study, a simple template is developed to support the decision-making analysis of the application and cost management of industrial robots. In addition, the case analysis and simulations can provide references for enterprises in emerging markets in relation to robot substitution.

scholarly journals Enabling Large-Scale Simulations of Quantum Transport with Manycore Computing

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 253
Author(s):  
Yosang Jeong ◽  
Hoon Ryu
Keyword(s):  
Quantum Transport ◽  
Large Scale ◽  
Performance Enhancement ◽  
Silicon Nanowire ◽  
Matrix Multiplication ◽  
Tight Binding ◽  
Optimization Techniques ◽  
Wide Energy Range ◽  
Processing Unit ◽  
Binding Model

The non-equilibrium Green’s function (NEGF) is being utilized in the field of nanoscience to predict transport behaviors of electronic devices. This work explores how much performance improvement can be driven for quantum transport simulations with the aid of manycore computing, where the core numerical operation involves a recursive process of matrix multiplication. Major techniques adopted for performance enhancement are data restructuring, matrix tiling, thread scheduling, and offload computing, and we present technical details on how they are applied to optimize the performance of simulations in computing hardware, including Intel Xeon Phi Knights Landing (KNL) systems and NVIDIA general purpose graphic processing unit (GPU) devices. With a target structure of a silicon nanowire that consists of 100,000 atoms and is described with an atomistic tight-binding model, the effects of optimization techniques on the performance of simulations are rigorously tested in a KNL node equipped with two Quadro GV100 GPU devices, and we observe that computation is accelerated by a factor of up to ∼20 against the unoptimized case. The feasibility of handling large-scale workloads in a huge computing environment is also examined with nanowire simulations in a wide energy range, where good scalability is procured up to 2048 KNL nodes.

A large-scale study of ionic liquids employed in chemistry and energy research to reveal cytotoxicity mechanisms and to develop safe design guide

2021 ◽  
Author(s):  
Lilya U. Dzhemileva ◽  
Vladimir Anatolievich D'yakonov ◽  
Marina M. Seitkalieva ◽  
Natalia Kulikovskaya ◽  
Ksenia S. Egorova ◽  
...  
Keyword(s):  
Ionic Liquids ◽  
Life Cycle ◽  
Large Scale ◽  
Energy Research ◽  
Organic Electrolytes ◽  
Large Scale Study ◽  
Design Guide ◽  
Scientific Potential

Device-level applications of organic electrolytes unavoidably imply extensive contacts with the environment. Despite their excellent scientific potential, ionic liquids (ILs) cannot be approved for practical usage until their life cycle...

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