scholarly journals Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254374
Author(s):  
Emiko Desvaux ◽  
Antoine Hamon ◽  
Sandra Hubert ◽  
Cheïma Boudjeniba ◽  
Bastien Chassagnol ◽  
...  
Keyword(s):  
Lung Inflammation ◽  
Drug Targets ◽  
Cost Effective ◽  
Economic Consequences ◽  
Network Computing ◽  
Drug Candidates ◽  
Therapeutic Drugs ◽  
Cost Effective Approach ◽  
Related Proteins ◽  
Airways Inflammation

While establishing worldwide collective immunity with anti SARS-CoV-2 vaccines, COVID-19 remains a major health issue with dramatic ensuing economic consequences. In the transition, repurposing existing drugs remains the fastest cost-effective approach to alleviate the burden on health services, most particularly by reducing the incidence of the acute respiratory distress syndrome associated with severe COVID-19. We undertook a computational repurposing approach to identify candidate therapeutic drugs to control progression towards severe airways inflammation during COVID-19. Molecular profiling data were obtained from public sources regarding SARS-CoV-2 infected epithelial or endothelial cells, immune dysregulations associated with severe COVID-19 and lung inflammation induced by other respiratory viruses. From these data, we generated a protein-protein interactome modeling the evolution of lung inflammation during COVID-19 from inception to an established cytokine release syndrome. This predictive model assembling severe COVID-19-related proteins supports a role for known contributors to the cytokine storm such as IL1β, IL6, TNFα, JAK2, but also less prominent actors such as IL17, IL23 and C5a. Importantly our analysis points out to alarmins such as TSLP, IL33, members of the S100 family and their receptors (ST2, RAGE) as targets of major therapeutic interest. By evaluating the network-based distances between severe COVID-19-related proteins and known drug targets, network computing identified drugs which could be repurposed to prevent or slow down progression towards severe airways inflammation. This analysis confirmed the interest of dexamethasone, JAK2 inhibitors, estrogens and further identified various drugs either available or in development interacting with the aforementioned targets. We most particularly recommend considering various inhibitors of alarmins or their receptors, currently receiving little attention in this indication, as candidate treatments for severe COVID-19.

scholarly journals Rapid Identification of Potential Drug Candidates from Multi-Million Compounds’ Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening

Molecules ◽  
2021 ◽  
Vol 26 (18) ◽  
pp. 5593
Author(s):  
Katalin Szilágyi ◽  
Beáta Flachner ◽  
István Hajdú ◽  
Mária Szaszkó ◽  
Krisztina Dobi ◽  
...  
Keyword(s):  
Similarity Search ◽  
Pharmacophore Model ◽  
Cost Effective ◽  
Rapid Identification ◽  
Drug Candidates ◽  
Hit Rate ◽  
Physico Chemical ◽  
Cost Effective Approach ◽  
3D Methods

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost-effective approach in early drug discovery. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compounds’ databases. This approach can be combined with physico-chemical parameter and diversity filtering, bioisosteric replacements, and fragment-based approaches for performing a first round biological screening. Our objectives were to investigate the combination of 2D similarity search with various 3D ligand and structure-based methods for hit expansion and validation, in order to increase the hit rate and novelty. In the present account, six case studies are described and the efficiency of mixing is evaluated. While sequentially combined 2D/3D similarity approach increases the hit rate significantly, sequential combination of 2D similarity with pharmacophore model or 3D docking enriched the resulting focused library with novel chemotypes. Parallel integrated approaches allowed the comparison of the various 2D and 3D methods and revealed that 2D similarity-based and 3D ligand and structure-based techniques are often complementary, and their combinations represent a powerful synergy. Finally, the lessons we learnt including the advantages and pitfalls of the described approaches are discussed.

What's next in translational medicine?

2007 ◽  
Vol 112 (4) ◽  
pp. 217-227 ◽  
Author(s):  
Bruce H. Littman ◽  
Linda Di Mario ◽  
Mario Plebani ◽  
Francesco M. Marincola
Keyword(s):  
Clinical Research ◽  
Translational Research ◽  
Translational Medicine ◽  
Drug Targets ◽  
Cost Effective ◽  
Therapeutic Index ◽  
Drug Candidates ◽  
Private And Public ◽  
Drug Regulatory Agencies ◽  
Effective Decision Making

Translational medicine is the integrated application of innovative pharmacology tools, biomarkers, clinical methods, clinical technologies and study designs to improve disease understanding, confidence in human drug targets and increase confidence in drug candidates, understand the therapeutic index in humans, enhance cost-effective decision making in exploratory development and increase phase II success. Translational research is one of the most important activities of translational medicine as it supports predictions about probable drug activities across species and is especially important when compounds with unprecedented drug targets are brought to humans for the first time. Translational research has the potential to deliver many practical benefits for patients and justify the extensive investments placed by the private and public sector in biomedical research. Translational research encompasses a complexity of scientific, financial, ethical, regulatory, legislative and practical hurdles that need to be addressed at several levels to make the process efficient. Several have resisted the idea of supporting translational research because of its high costs and the fear that it may re-direct funds from other biomedical disciplines. Resistance also comes from those more familiar with traditional clinical research methods. In this review, we argue that translational research should be seen as enabled by ongoing efforts in basic and clinical research and not competing with them. Translational research provides the knowledge necessary to draw important conclusions from clinical testing regarding disease and the viability of novel drug mechanisms. Advancing translational research requires education and new sources of funding. This could be achieved through public and congressional education by a joint coalition of patients' advocacy groups, academia, drug regulatory agencies and industry.

scholarly journals UAV IMAGES AND DEEP-LEARNING ALGORITHMS FOR DETECTING FLAVESCENCE DOREE DISEASE IN GRAPEVINE ORCHARDS

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1483-1489
Author(s):  
M. A. Musci ◽  
C. Persello ◽  
A. M. Lingua
Keyword(s):  
Preventive Measures ◽  
Cost Effective ◽  
Semantic Segmentation ◽  
Image Resolution ◽  
Economic Consequences ◽  
Flavescence Dorée ◽  
Cost Effective Approach ◽  
Precision Viticulture ◽  
Uav Images ◽  
Definition Of

Abstract. One of the major challenges in precision viticulture in Europe is the detection and mapping of flavescence dorée (FD) grapevine disease to monitor and contain its spread. The lack of effective cures and the need for sustainable preventive measures are nowadays crucial issues. Insecticides and the plants uprooting are commonly employed to withhold disease infection, even if these solutions imply serious economic consequences and a strong environmental impact. The development of a rapid strategy to identify the disease is required to cover large portions of the crop and thus to limit damages in a time-effective way. This paper investigates the use of Unmanned Aerial Vehicles (UAVs), a cost-effective approach to early detection of diseased areas. We address this task with an object detection deep network, Faster R-CNN, instead of a traditional pixel-wise classifier. This work tests Faster R-CNN performance on this specific application through a comparative analysis with a pixel-wise classification algorithm (Random Forest). To take advantage of the full image resolution, the experimental analysis is performed using the original UAV imagery acquired in real conditions (instead of the derived orthomosaic). The first result of this paper is the definition of a new dataset for FD disease identification by UAV original imagery at the canopy scale. Moreover, we demonstrate the feasibility of applying Faster-R-CNN as a quasi-real-time alternative solution to semantic segmentation. The trained Faster-R-CNN achieved an average precision of 82% on the test set.

scholarly journals When GWAS meets the Connectivity Map: drug repositioning for seven psychiatric disorders

2016 ◽  
Author(s):  
Hon-Cheong So ◽  
Carlos K.L. Chau ◽  
Wan-To Chiu ◽  
Kin-Sang Ho ◽  
Cho-Pong Lo ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Developmental Process ◽  
Drug Repositioning ◽  
Expression Profiles ◽  
Association Studies ◽  
Cost Effective ◽  
Genome Wide Association Studies ◽  
Connectivity Map ◽  
Drug Candidates ◽  
Cost Effective Approach

AbstractOur knowledge of disease genetics has advanced rapidly during the past decade, with the advent of high-throughput genotyping technologies such as genome-wide association studies (GWAS). However, few methodologies were developed and systemic studies performed to identify novel drug candidates utilizing GWAS data. In this study we focus on drug repositioning, which is a cost-effective approach to shorten the developmental process of new therapies. We proposed a novel framework of drug repositioning by comparing GWAS-imputed transcriptome with drug expression profiles from the Connectivity Map. The approach was applied to 7 psychiatric disorders. We discovered a number of novel repositioning candidates, many of which are supported by preclinical or clinical evidence. We found that the predicted drugs are significantly enriched for known psychiatric medications, or therapies considered in clinical trials. For example, drugs repurposed for schizophrenia are strongly enriched for antipsychotics (p = 4.69E-06), while those repurposed for bipolar disorder are enriched for antipsychotics (p = 2.26E-07) and antidepressants (p = 1.17E-05). These findings provide support to the usefulness of GWAS signals in guiding drug discoveries and the validity of our approach in drug repositioning. We also present manually curated lists of top repositioning candidates for each disorder, which we believe will serve as a useful resource for researchers.

E-Insurance :A Platform For Insurance Penetration In India

2019 ◽  
Vol 118 (6) ◽  
pp. 90-93
Author(s):  
L. Terina Grazy ◽  
Dr.G. Parimalarani
Keyword(s):  
Insurance Industry ◽  
Cost Effective ◽  
Online Marketing ◽  
Insurance Companies ◽  
The Internet ◽  
Insurance Sector ◽  
The People ◽  
Cost Effective Approach ◽  
Time And Energy ◽  
Work Done

E-commerce is a part of Internet Marketing. The arrival of Internet made the world very simple and dynamic in all the areas. Internet is the growing business as a result most of the people are using it in their day to day life. E-commerce is attractive and efficient way for both buyers and sellesr as it reduce cost, time and energy for the buyer. No surprise the insurance sector has become quite active within the internet sphere. Most insurance companies are offering policies to be brought online and also the portals for paying premiums. It actually saves from hassles involved in going to an insurance office and spend hours to get the insurance work done. Insurance has become an important and crucial aspect of life. Online insurance is the best and most cost effective approach of taking the insurance deal. This paper focused on influence of online marketing on the insurance industry in India, usage of internet in India , the internet penetration in India and the online sale of insurance product by the insurance sector.

Molecular characterization of SARS-CoV-2

2020 ◽  
Vol 20 ◽  
Author(s):  
Miribane Dërmaku-Sopjani ◽  
Mentor Sopjani
Keyword(s):  
Public Health ◽  
Drug Targets ◽  
Virus Genome ◽  
Health Crisis ◽  
Public Health Crisis ◽  
Therapeutic Drugs ◽  
New Public Health ◽  
New Public ◽  
And Function

Abstract:: The coronavirus disease 2019 (COVID-19) is currently a new public health crisis threatening the world. This pandemic disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus has been reported to be originated in bats and by yet unknown intermediary animals were transmitted to humans in China 2019. The SARSCoV- 2 spreads faster than its two ancestors the SARS-CoV and Middle East respiratory syndrome coronavirus (MERSCoV) but has reduced fatality. At present, the SARS-CoV-2 has caused about a 1.16 million of deaths with more than 43.4 million confirmed cases worldwide, resulting in a serious threat to public health globally with yet uncertain impact. The disease is transmitted by inhalation or direct contact with an infected person. The incubation period ranges from 1 to 14 days. COVID-19 is accompanied by various symptoms, including cough, fatigue. In most people the disease is mild, but in some other people, such as in elderly and people with chronic diseases, it may progress from pneumonia to a multi-organ dysfunction. Many people are reported asymptomatic. The virus genome is sequenced, but new variants are reported. Numerous biochemical aspects of its structure and function are revealed. To date, no clinically approved vaccines and/or specific therapeutic drugs are available to prevent or treat the COVID-19. However, there are reported intensive researches on the SARSCoV- 2 to potentially identify vaccines and/or drug targets, which may help to overcome the disease. In this review, we discuss recent advances in understanding the molecular structure of SARS-CoV-2 and its biochemical characteristics.

Polyamines and Related Nitrogen Compounds in the Chemotherapy of Neglected Diseases Caused by Kinetoplastids

2018 ◽  
Vol 18 (5) ◽  
pp. 321-368 ◽  
Author(s):  
Juan A. Bisceglia ◽  
Maria C. Mollo ◽  
Nadia Gruber ◽  
Liliana R. Orelli
Keyword(s):  
Drug Targets ◽  
Redox Homeostasis ◽  
Cost Effective ◽  
Structural Features ◽  
Mammalian Host ◽  
Neglected Diseases ◽  
Nitrogen Compounds ◽  
Chemical Structures

Neglected diseases due to the parasitic protozoa Leishmania and Trypanosoma (kinetoplastids) affect millions of people worldwide, and the lack of suitable treatments has promoted an ongoing drug discovery effort to identify novel nontoxic and cost-effective chemotherapies. Polyamines are ubiquitous small organic molecules that play key roles in kinetoplastid parasites metabolism, redox homeostasis and in the normal progression of cell cycles, which differ from those found in the mammalian host. These features make polyamines attractive in terms of antiparasitic drug development. The present work provides a comprehensive insight on the use of polyamine derivatives and related nitrogen compounds in the chemotherapy of kinetoplastid diseases. The amount of literature on this subject is considerable, and a classification considering drug targets and chemical structures were made. Polyamines, aminoalcohols and basic heterocycles designed to target the relevant parasitic enzyme trypanothione reductase are discussed in the first section, followed by compounds directed to less common targets, like parasite SOD and the aminopurine P2 transporter. Finally, the third section comprises nitrogen compounds structurally derived from antimalaric agents. References on the chemical synthesis of the selected compounds are reported together with their in vivo and/or in vitro IC50 values, and structureactivity relationships within each group are analyzed. Some favourable structural features were identified from the SAR analyses comprising protonable sites, hydrophobic groups and optimum distances between them. The importance of certain pharmacophoric groups or amino acid residues in the bioactivity of polyamine derived compounds is also discussed.

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