Related papers: Drug Repurposing For SARS-COV-2 Using Molecular Do…
SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this, outbreak specific preventive and therapeutic interventions are urgently needed. It must be said that,…
Presently, there are no approved drugs or vaccines to treat COVID-19 which has spread to over 200 countries and is responsible for over 3,65,000 deaths worldwide. Recent studies have shown that two human proteases, TMPRSS2 and cathepsin L,…
Extracting molecular structure-activity relationships (SARs) from scientific literature and patents is essential for drug discovery and materials research. However, this task remains challenging due to heterogeneous document formats and…
The SARS-CoV-2 virus has resulted in a devastating pandemic of COVID-19. Exploring compounds that could offer a breakthrough in treatment is the need of the hour. Re-positioning cheap, freely available and safe drugs is a priority. The…
Genomic surveillance of infectious diseases allows monitoring circulating and emerging variants and quantifying their epidemic potential. However, due to the high costs associated with genomic sequencing, only a limited number of samples…
The discovery of novel inhibitor molecules for emerging drug-target proteins is widely acknowledged as a challenging inverse design problem: Exhaustive exploration of the vast chemical search space is impractical, especially when the target…
Objectives. This review gathers information on the potential role of antihistamines as anti-infective agents and identifies gaps in research that have impaired its applicability in human health. Methods. The literature search encompassed…
Virtual screening (VS) is a critical step in computer-aided drug discovery, aiming to identify molecules that bind to a specific target receptor like protein. Traditional VS methods, such as docking, are often too time-consuming for…
Since the rise of the SARS-CoV-2 pandemic in the winter of 2019, the need for an affordable and efficient drug has not yet been met. Leveraging its unique, fast and precise binding free energy prediction technology, Aqemia screened and…
Effective and efficient management of human betacoronavirus severe acute respiratory syndrome (SARS)-CoV-2 infection i.e., COVID-19 pandemic, required sensitive sensors with short sample-to-result durations for performing diagnostics. In…
This work formulates antiviral repositioning as a matrix completion problem where the antiviral drugs are along the rows and the viruses along the columns. The input matrix is partially filled, with ones in positions where the antiviral has…
Since the classification of COVID-19 as a global pandemic, there have been many attempts to treat and contain the virus. Although there is no specific antiviral treatment recommended for COVID-19, there are several drugs that can…
Testing individuals for the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen causing the coronavirus disease 2019 (COVID-19), is crucial for curtailing transmission chains. Moreover, rapidly testing…
Structure-based Deep Fusion models were recently shown to outperform several physics- and machine learning-based protein-ligand binding affinity prediction methods. As part of a multi-institutional COVID-19 pandemic response, over 500…
Over the past 150 years, vaccines have revolutionized the relationship between people and disease. During the COVID-19 pandemic, technologies such as mRNA vaccines have received attention due to their novelty and successes. However, more…
The widely used gene quantisation technique, Lateral Flow Device (LFD), is now commonly used to detect the presence of SARS-CoV-2. It is enabling the control and prevention of the spread of the virus. Depending on the viral load, LFD have…
Single-cell and single-nucleus RNA sequencing (scRNA-seq /snRNA-seq) are widely used to reveal heterogeneity in cells, showing a growing potential for precision and personalized medicine. Nonetheless, sustainable drug discovery must be…
The COVID-19 pandemic response relied heavily on statistical and machine learning models to predict key outcomes such as case prevalence and fatality rates. These predictions were instrumental in enabling timely public health interventions…
The current COVID-19 global pandemic caused by the SARS-CoV-2 betacoronavirus has resulted in over a million deaths and is having a grave socio-economic impact, hence there is an urgency to find solutions to key research challenges. Much of…
The accurate prediction of B-cell epitopes is critical for guiding vaccine development against infectious diseases, including SARS and COVID-19. This study explores the use of a deep neural network (DNN) model to predict B-cell epitopes for…