scholarly journals Designing a Network Proximity-Based Drug Repurposing Strategy for COVID-19

2020 ◽  
Vol 8 ◽  
Author(s):  
Paola Stolfi ◽  
Luigi Manni ◽  
Marzia Soligo ◽  
Davide Vergni ◽  
Paolo Tieri
Keyword(s):  
Drug Repurposing ◽  
Network Proximity

scholarly journals Network medicine framework for identifying drug-repurposing opportunities for COVID-19

2021 ◽  
Vol 118 (19) ◽  
pp. e2025581118
Author(s):  
Deisy Morselli Gysi ◽  
Ítalo do Valle ◽  
Marinka Zitnik ◽  
Asher Ameli ◽  
Xiao Gan ◽  
...  
Keyword(s):  
Viral Infection ◽  
De Novo ◽  
Drug Repurposing ◽  
Ground Truth ◽  
Neglected Diseases ◽  
Network Medicine ◽  
Novel Treatments ◽  
Predictive Algorithm ◽  
Predictive Methods ◽  
Network Proximity

The COVID-19 pandemic has highlighted the need to quickly and reliably prioritize clinically approved compounds for their potential effectiveness for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Here, we deployed algorithms relying on artificial intelligence, network diffusion, and network proximity, tasking each of them to rank 6,340 drugs for their expected efficacy against SARS-CoV-2. To test the predictions, we used as ground truth 918 drugs experimentally screened in VeroE6 cells, as well as the list of drugs in clinical trials that capture the medical community’s assessment of drugs with potential COVID-19 efficacy. We find that no single predictive algorithm offers consistently reliable outcomes across all datasets and metrics. This outcome prompted us to develop a multimodal technology that fuses the predictions of all algorithms, finding that a consensus among the different predictive methods consistently exceeds the performance of the best individual pipelines. We screened in human cells the top-ranked drugs, obtaining a 62% success rate, in contrast to the 0.8% hit rate of nonguided screenings. Of the six drugs that reduced viral infection, four could be directly repurposed to treat COVID-19, proposing novel treatments for COVID-19. We also found that 76 of the 77 drugs that successfully reduced viral infection do not bind the proteins targeted by SARS-CoV-2, indicating that these network drugs rely on network-based mechanisms that cannot be identified using docking-based strategies. These advances offer a methodological pathway to identify repurposable drugs for future pathogens and neglected diseases underserved by the costs and extended timeline of de novo drug development.

Drug Repurposing Studies Targeting SARS-nCoV2: An Ensemble Docking Approach on Drug Target 3C-like Protease (3CLpro)

2020 ◽  
Author(s):  
Shruti Koulgi ◽  
Vinod Jani ◽  
Mallikarjunachari Uppuladinne ◽  
Uddhavesh Sonavane ◽  
Asheet Kumar Nath ◽  
...  
Keyword(s):  
Drug Repurposing ◽  
Drug Binding ◽  
Ensemble Docking ◽  
Drug Molecules ◽  
Drug Binding Site ◽  
Main Protease ◽  
Docking Approach ◽  
Novel Coronavirus ◽  
Markov State Modeling ◽  
Viral Polyprotein

<p>The COVID-19 pandemic has been responsible for several deaths worldwide. The causative agent behind this disease is the Severe Acute Respiratory Syndrome – novel Coronavirus 2 (SARS-nCoV2). SARS-nCoV2 belongs to the category of RNA viruses. The main protease, responsible for the cleavage of the viral polyprotein is considered as one of the hot targets for treating COVID-19. Earlier reports suggest the use of HIV anti-viral drugs for targeting the main protease of SARS-CoV, which caused SARS in the year 2002-03. Hence, drug repurposing approach may prove to be useful in targeting the main protease of SARS-nCoV2. The high-resolution crystal structure of 3CL<sup>pro</sup> (main protease) of SARS-nCoV2 (PDB ID: 6LU7) was used as the target. The Food and Drug Administration (FDA) approved and SWEETLEAD database of drug molecules were screened. The apo form of the main protease was simulated for a cumulative of 150 ns and 10 μs open source simulation data was used, to obtain conformations for ensemble docking. The representative structures for docking were selected using RMSD-based clustering and Markov State Modeling analysis. This ensemble docking approach for main protease helped in exploring the conformational variation in the drug binding site of the main protease leading to efficient binding of more relevant drug molecules. The drugs obtained as best hits from the ensemble docking possessed anti-bacterial and anti-viral properties. Small molecules with these properties may prove to be useful to treat symptoms exhibited in COVID-19. This <i>in-silico</i> ensemble docking approach would support identification of potential candidates for repurposing against COVID-19.</p>

Sitagliptin: a potential drug for the treatment of SARS-CoV-2?

2020 ◽  
Author(s):  
Sanaa Bardaweel
Keyword(s):  
Clinical Trials ◽  
Drug Discovery ◽  
Antimalarial Drug ◽  
Drug Repurposing ◽  
Spike Protein ◽  
Diabetic Patients ◽  
Potential Drug ◽  
Chemokine Production ◽  
Drug Discovery And Development ◽  
Sequence Identity

Recently, an outbreak of fatal coronavirus, SARS-CoV-2, has emerged from China and is rapidly spreading worldwide. As the coronavirus pandemic rages, drug discovery and development become even more challenging. Drug repurposing of the antimalarial drug chloroquine and its hydroxylated form had demonstrated apparent effectiveness in the treatment of COVID-19 associated pneumonia in clinical trials. SARS-CoV-2 spike protein shares 31.9% sequence identity with the spike protein presents in the Middle East Respiratory Syndrome Corona Virus (MERS-CoV), which infects cells through the interaction of its spike protein with the DPP4 receptor found on macrophages. Sitagliptin, a DPP4 inhibitor, that is known for its antidiabetic, immunoregulatory, anti-inflammatory, and beneficial cardiometabolic effects has been shown to reverse macrophage responses in MERS-CoV infection and reduce CXCL10 chemokine production in AIDS patients. We suggest that Sitagliptin may be beneficial alternative for the treatment of COVID-19 disease especially in diabetic patients and patients with preexisting cardiovascular conditions who are already at higher risk of COVID-19 infection.

Recent Advances in Drug Repurposing for Parkinson’s Disease

2019 ◽  
Vol 26 (28) ◽  
pp. 5340-5362 ◽  
Author(s):  
Xin Chen ◽  
Giuseppe Gumina ◽  
Kristopher G. Virga
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Drug Discovery ◽  
De Novo ◽  
Drug Repositioning ◽  
Drug Repurposing ◽  
Cost Effective ◽  
New Drugs ◽  
Recent Advances ◽  
Clinical Drugs

:As a long-term degenerative disorder of the central nervous system that mostly affects older people, Parkinson’s disease is a growing health threat to our ever-aging population. Despite remarkable advances in our understanding of this disease, all therapeutics currently available only act to improve symptoms but cannot stop the disease progression. Therefore, it is essential that more effective drug discovery methods and approaches are developed, validated, and used for the discovery of disease-modifying treatments for Parkinson’s disease. Drug repurposing, also known as drug repositioning, or the process of finding new uses for existing or abandoned pharmaceuticals, has been recognized as a cost-effective and timeefficient way to develop new drugs, being equally promising as de novo drug discovery in the field of neurodegeneration and, more specifically for Parkinson’s disease. The availability of several established libraries of clinical drugs and fast evolvement in disease biology, genomics and bioinformatics has stimulated the momentums of both in silico and activity-based drug repurposing. With the successful clinical introduction of several repurposed drugs for Parkinson’s disease, drug repurposing has now become a robust alternative approach to the discovery and development of novel drugs for this disease. In this review, recent advances in drug repurposing for Parkinson’s disease will be discussed.

Web-based Tools for Drug Repurposing: Successful Examples of Collaborative Research

2020 ◽  
Vol 28 (1) ◽  
pp. 181-195
Author(s):  
Quentin Vanhaelen
Keyword(s):  
User Interfaces ◽  
Collaborative Research ◽  
Meta Analysis ◽  
A Priori ◽  
Drug Repurposing ◽  
Data Access ◽  
Estimation Methods ◽  
Large Set ◽  
Computational Tools ◽  
Web Based

: Computational approaches have been proven to be complementary tools of interest in identifying potential candidates for drug repurposing. However, although the methods developed so far offer interesting opportunities and could contribute to solving issues faced by the pharmaceutical sector, they also come with their constraints. Indeed, specific challenges ranging from data access, standardization and integration to the implementation of reliable and coherent validation methods must be addressed to allow systematic use at a larger scale. In this mini-review, we cover computational tools recently developed for addressing some of these challenges. This includes specific databases providing accessibility to a large set of curated data with standardized annotations, web-based tools integrating flexible user interfaces to perform fast computational repurposing experiments and standardized datasets specifically annotated and balanced for validating new computational drug repurposing methods. Interestingly, these new databases combined with the increasing number of information about the outcomes of drug repurposing studies can be used to perform a meta-analysis to identify key properties associated with successful drug repurposing cases. This information could further be used to design estimation methods to compute a priori assessment of the repurposing possibilities.

Drug Repurposing in Human Cancers

2020 ◽  
Vol 27 (42) ◽  
pp. 7213-7213
Author(s):  
Gabriele Grassi ◽  
Mario Grassi
Keyword(s):  
Drug Repurposing ◽  
Human Cancers

The Antiviral and Antimalarial Drug Repurposing in Quest of Chemotherapeutics to Combat COVID-19 Utilizing Structure-Based Molecular Docking

2020 ◽  
Vol 23 ◽  
Author(s):  
Sisir Nandi ◽  
Mohit Kumar ◽  
Mridula Saxena ◽  
Anil Kumar Saxena
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Drug Repurposing ◽  
Clinical Settings ◽  
The Novel ◽  
In Silico Docking ◽  
Biochemical Mechanisms ◽  
Novel Coronavirus ◽  
In Silico Molecular Docking

Background: The novel coronavirus disease (COVID-19) is caused by a new strain (SARS-CoV-2) erupted in 2019. Nowadays, it is a great threat that claims uncountable lives worldwide. There is no specific chemotherapeutics developed yet to combat COVID-19. Therefore, scientists have been devoted in the quest of the medicine that can cure COVID- 19. Objective: Existing antivirals such as ASC09/ritonavir, lopinavir/ritonavir with or without umifenovir in combination with antimalarial chloroquine or hydroxychloroquine have been repurposed to fight the current coronavirus epidemic. But exact biochemical mechanisms of these drugs towards COVID-19 have not been discovered to date. Method: In-silico molecular docking can predict the mode of binding to sort out the existing chemotherapeutics having a potential affinity towards inhibition of the COVID-19 target. An attempt has been made in the present work to carry out docking analyses of 34 drugs including antivirals and antimalarials to explain explicitly the mode of interactions of these ligands towards the COVID-19protease target. Results: 13 compounds having good binding affinity have been predicted towards protease binding inhibition of COVID-19. Conclusion: Our in silico docking results have been confirmed by current reports from clinical settings through the citation of suitable experimental in vitro data available in the published literature.

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