Understanding How Coronavirus Disguises Itself to Hide Inside Host Cells and Replicate May Help Develop COVID-19 Treatment
|
By HospiMedica International staff writers Posted on 28 Jul 2020 |

Illustration
Researchers have discovered that the SARS-CoV-2 virus molecules make themselves unrecognizable to host cells by tricking the immune system with camouflage, thus paving the way for drug development for the treatment of COVID-19.
Researchers at The University of Texas Health Science Center (San Antonio, TX, USA) resolved the structure of an enzyme called nsp16, which the coronavirus produces and then uses to modify its messenger RNA cap. These modifications fool the cell, as a result of which the viral messenger RNA becomes considered as part of the cell’s own code and not foreign. Deciphering the 3D structure of nsp16 paves the way for rational design of antiviral drugs for COVID-19 and other emerging coronavirus infections, according to Dr. Yogesh Gupta, PhD, the study lead author from the Joe R. and Teresa Lozano Long School of Medicine at UT Health San Antonio. The drugs, new small molecules, would inhibit nsp16 from making the modifications. The immune system would then pounce on the invading virus, recognizing it as foreign.
“Yogesh’s work discovered the 3D structure of a key enzyme of the COVID-19 virus required for its replication and found a pocket in it that can be targeted to inhibit that enzyme. This is a fundamental advance in our understanding of the virus,” said study coauthor Robert Hromas, MD, professor and dean of the Long School of Medicine.
Related Links:
The University of Texas Health Science Center
Researchers at The University of Texas Health Science Center (San Antonio, TX, USA) resolved the structure of an enzyme called nsp16, which the coronavirus produces and then uses to modify its messenger RNA cap. These modifications fool the cell, as a result of which the viral messenger RNA becomes considered as part of the cell’s own code and not foreign. Deciphering the 3D structure of nsp16 paves the way for rational design of antiviral drugs for COVID-19 and other emerging coronavirus infections, according to Dr. Yogesh Gupta, PhD, the study lead author from the Joe R. and Teresa Lozano Long School of Medicine at UT Health San Antonio. The drugs, new small molecules, would inhibit nsp16 from making the modifications. The immune system would then pounce on the invading virus, recognizing it as foreign.
“Yogesh’s work discovered the 3D structure of a key enzyme of the COVID-19 virus required for its replication and found a pocket in it that can be targeted to inhibit that enzyme. This is a fundamental advance in our understanding of the virus,” said study coauthor Robert Hromas, MD, professor and dean of the Long School of Medicine.
Related Links:
The University of Texas Health Science Center
Latest COVID-19 News
- Low-Cost System Detects SARS-CoV-2 Virus in Hospital Air Using High-Tech Bubbles
- World's First Inhalable COVID-19 Vaccine Approved in China
- COVID-19 Vaccine Patch Fights SARS-CoV-2 Variants Better than Needles
- Blood Viscosity Testing Can Predict Risk of Death in Hospitalized COVID-19 Patients
- ‘Covid Computer’ Uses AI to Detect COVID-19 from Chest CT Scans
- MRI Lung-Imaging Technique Shows Cause of Long-COVID Symptoms
- Chest CT Scans of COVID-19 Patients Could Help Distinguish Between SARS-CoV-2 Variants
- Specialized MRI Detects Lung Abnormalities in Non-Hospitalized Long COVID Patients
- AI Algorithm Identifies Hospitalized Patients at Highest Risk of Dying From COVID-19
- Sweat Sensor Detects Key Biomarkers That Provide Early Warning of COVID-19 and Flu
- Study Assesses Impact of COVID-19 on Ventilation/Perfusion Scintigraphy
- CT Imaging Study Finds Vaccination Reduces Risk of COVID-19 Associated Pulmonary Embolism
- Third Day in Hospital a ‘Tipping Point’ in Severity of COVID-19 Pneumonia
- Longer Interval Between COVID-19 Vaccines Generates Up to Nine Times as Many Antibodies
- AI Model for Monitoring COVID-19 Predicts Mortality Within First 30 Days of Admission
- AI Predicts COVID Prognosis at Near-Expert Level Based Off CT Scans
Channels
Artificial Intelligence
view channel
AI Model Uses Eye Imaging to Identify Risk of Major Systemic Diseases
Early detection of systemic disease risk remains a persistent challenge in population health screening. Cardiometabolic conditions such as diabetes, heart disease, and stroke often progress without symptoms... Read more
AI Platform Interprets Real-Time Wearable Data for Parkinson’s Management
Parkinson’s disease presents fluctuating motor and non-motor symptoms that complicate day-to-day self-management and clinical decision-making. Care teams require timely, longitudinal insight into medication... Read moreCritical Care
view channel
Minimally Invasive Probe Measures Key Metabolic Markers Simultaneously
Continuous monitoring of metabolic biomarkers is vital in intensive care and emergency settings, yet many methods rely on separate devices and delayed laboratory analysis. Glucose trends guide diabetes... Read more
Flexible Plastic Film Uses Nanostructures to Destroy Viruses
High-touch surfaces in hospitals and clinics are key vectors for respiratory virus transmission despite routine disinfection. Human parainfluenza virus 3 (hPIV-3), which can cause bronchiolitis and pneumonia,... Read moreSurgical Techniques
view channel
Less Invasive Microcurrent Cardiac Device Improves Heart Failure Outcomes
Clinicians managing heart failure continue to seek interventions that improve cardiac function and daily activity without the burdens of major surgery. Early microcurrent therapies showed benefits but... Read more
Smart Fracture Implant Monitors Healing and Delivers Adaptive Support
Fracture care is hindered by a monitoring gap between fixation and the first follow-up radiograph, leaving clinicians without early, objective feedback on healing. Delayed detection of impaired union can... Read morePatient Care
view channel
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read moreHealth IT
view channel
Continuous Monitoring Platform Detects Infection Risk Across Care Transitions
Patients leaving skilled nursing facilities often lose continuous physiologic monitoring, increasing the risk of undetected infection and delayed intervention. Nursing home residents are seven times more... Read more
Automated System Classifies and Tracks Cardiogenic Shock Across Hospital Settings
Cardiogenic shock remains a difficult, time-sensitive emergency, with delayed identification driving poor outcomes and persistently high mortality. Many cases go undocumented even at advanced stages, hindering... Read morePoint of Care
view channelBusiness
view channel
Johnson & Johnson Launches AI-Driven Cardiac Mapping System
Johnson & Johnson has introduced the CARTOSOUND SONATA Module for the CARTO System at the Heart Rhythm Society (HRS) 2026 meeting in Chicago. The module uses artificial intelligence with the CARTO... Read more








