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 Tool Predicts Chronic Kidney Disease Risk in Diabetes
Chronic kidney disease is a common and serious complication of type 2 diabetes and often progresses without obvious early symptoms, increasing morbidity and straining health systems. Many risk models were... Read more
AI Trends Report Guides Responsible, Effective Healthcare Deployment
Hospitals are under growing pressure to adopt artificial intelligence tools that improve safety, efficiency, and continuity of care without compromising quality. At the same time, clinicians need clearer... Read moreCritical Care
view channel
AI-Guided Outreach System Improves Colorectal Cancer Screening
Colorectal cancer is the second-leading cause of cancer deaths in the United States. Early detection improves survival, yet many eligible adults remain overdue for recommended screening.... Read more
Multi-Night Home Monitoring Reduces Sleep Apnea Misdiagnosis
Obstructive sleep apnea is a common disorder in which breathing repeatedly stops and starts during sleep. Diagnosis often relies on a single-night polysomnography study, yet patients’ sleep can vary widely... Read more
FDA Breakthrough Device Targets Brain Hemorrhage Complications
Subarachnoid hemorrhage, bleeding into the space around the brain most often caused by a ruptured aneurysm, frequently leads to cerebral vasospasm during intensive care. This secondary narrowing of blood... Read more
ECG-Based Screening Framework Aims to Standardize Cardiac Evaluation in Military Personnel
Sudden cardiac death, the unexpected loss of heart function, can occur during intense exertion and remains a concern in physically demanding occupations. Military personnel face additional environmental... Read moreSurgical Techniques
view channel
Novel Microparticles Break Down Biofilms and Boost Antibiotic Activity
Biofilms are dense matrices of bacteria and proteins that shield microbes from disinfectants and drugs. They complicate wound care and the reprocessing of surgical instruments because standard agents often... Read more
Nerve Block Technique Reduces Opioid Use After Cardiac Surgery
Opioid exposure after open-heart surgery is associated with delirium, nausea, and other complications, and may contribute to longer-term dependence. Because cardiac procedures often still require high... Read morePatient Care
view channel
AI Avatar Doctor Improves Patient Understanding Before Radiotherapy
Radiation oncology consultations require patients to grasp complex concepts quickly, yet anxiety and information overload often undermine understanding and informed consent. Poor comprehension can also... Read more
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 moreHealth IT
view channel
Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation
Atrial fibrillation is an erratic, quivering heartbeat and a leading cause of stroke. Catheter ablation is widely used to interrupt arrhythmogenic tissue, yet many patients—especially with persistent ... Read moreAI Framework Helps Clinicians Create Trustworthy Risk Prediction Tools
Artificial intelligence (AI) is increasingly used to estimate risks for conditions such as sepsis, heart disease, and cancer, yet many models remain difficult for clinicians to interpret or trust.... Read morePoint of Care
view channel
New Brain Ultrasound Platform Enables Bedside Postoperative Imaging
Transporting postoperative patients for CT or MRI can create operational burdens, delays, and disruptions in care. Bedside visualization may help reduce transport demands, lower radiation exposure, and... Read more








