Exploiting cheminformatic and machine learning to navigate the available chemical space of potential small molecule inhibitors of SARS-CoV-2

Kumar, Ambak; Loharch, Saurabh; Kumar, Sunil; Ringe, Rajesh P.; Parkesh, Raman

doi:10.1016/j.csbj.2020.12.028

Cited by 29 publications

(20 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Again, Kumar A et. al., have used a cheminformatics approach to create different datasets and analyzed scaffold diversity to predict the SARS-CoV-2 inhibitors [49] . Recently, Beck B et al ., used a pre-trained deep learning-based drug-target interaction model called molecule transformer-drug target interaction (MT-DTI) to identify commercially available drugs that could act on SARS-CoV-2 proteins [50] .…”

Section: Discussionmentioning

confidence: 99%

Prediction of repurposed drugs for Coronaviruses using artificial intelligence and machine learning

Rajput

Thakur

Mukhopadhyay

et al. 2021

Computational and Structural Biotechnology Journal

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

Prediction of repurposed drugs for Coronaviruses using artificial intelligence and machine learning

Rajput

Thakur

Mukhopadhyay

et al. 2021

Computational and Structural Biotechnology Journal

View full text Add to dashboard Cite

show abstract

“…It has appeared only as a candidate SARS-CoV-2 inhibitor in a study that used chemoinformatics and machine learning to detect FDA-approved drugs that could target essential SARS-CoV-2 structures. [17] DISNET data showed a relationship between cefazolin and the SARS-CoV-2-associated-gene, IL2 .…”

Section: Cefazolinmentioning

confidence: 99%

“…More specifically, the DPP-4i sitagliptin has been proposed as a potential treatment for COVID-19 in a couple of computational DR studies. [17] , [54] In addition, it has been reported that diabetic patients treated with the DPP-4i sitagliptin at the time of hospitalization had a lower mortality rate, better clinical outcomes, and more hospital discharges than their diabetic counterparts not taking sitagliptin. [55] …”

Section: Sitagliptin and Vildagliptinmentioning

confidence: 99%

Integrating heterogeneous data to facilitate COVID-19 drug repurposing

Santamaría

Uzquiano

Carro

et al. 2022

Drug Discovery Today

View full text Add to dashboard Cite

In the COVID-19 pandemic, drug repositioning has presented itself as an alternative to the time-consuming process of generating new drugs. This review describes a drug repurposing process that is based on a new data-driven approach: we put forward five information paths that associate COVID-19-related genes and COVID-19 symptoms with drugs that directly target these gene products, that target the symptoms or that treat diseases that are symptomatically or genetically similar to COVID-19. The intersection of the five information paths results in a list of 13 drugs that we suggest as potential candidates against COVID-19. In addition, we have found information in published studies and in clinical trials that support the therapeutic potential of the drugs in our final list.

show abstract

“…Gliptins, especially sitagliptin, reduced the inflammation intensity and may control cytokine storms mostly via nuclear factor kappa B signaling pathway[ 190 , 191 ]. Nevertheless, cheminformatics suggested sitagliptin as anti-severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)[ 192 ] as a result of the expected potential molecular binding between sitagliptin and viral spikes[ 193 ]. Nar et al [ 194 ], showed the ineffectiveness of gliptins against SARS-CoV-2 protease[ 194 ].…”

Section: Dpp-iv Inhibitors (Gliptins)mentioning

confidence: 99%

Anti-diabetics and antimicrobials: Harmony of mutual interplay

Hegazy¹,

Rajab²,

Lila³

et al. 2021

WJD

View full text Add to dashboard Cite

Diabetes is one of the four major non-communicable diseases, and appointed by the world health organization as the seventh leading cause of death worldwide. The scientists have turned over every rock in the corners of medical sciences in order to come up with better understanding and hence more effective treatments of diabetes. The continuous research on the subject has elucidated the role of immune disorders and inflammation as definitive factors in the trajectory of diabetes, assuring that blood glucose adjustments would result in a relief in the systemic stress leading to minimizing inflammation. On a parallel basis, microbial infections usually take advantage of immunity disorders and propagate creating a pro-inflammatory environment, all of which can be reversed by antimicrobial treatment. Standing at the crossroads between diabetes, immunity and infection, we aim in this review at projecting the interplay between immunity and diabetes, shedding the light on the overlapping playgrounds for the activity of some antimicrobial and anti-diabetic agents. Furthermore, we focused on the anti-diabetic drugs that can confer antimicrobial or anti-virulence activities.

show abstract

Exploiting cheminformatic and machine learning to navigate the available chemical space of potential small molecule inhibitors of SARS-CoV-2

Abstract: Graphical abstract

Cited by 29 publications

References 53 publications

Prediction of repurposed drugs for Coronaviruses using artificial intelligence and machine learning

Prediction of repurposed drugs for Coronaviruses using artificial intelligence and machine learning

Integrating heterogeneous data to facilitate COVID-19 drug repurposing

Anti-diabetics and antimicrobials: Harmony of mutual interplay

Contact Info

Product

Resources

About