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Rommie Amaro - UC San Diego. San Diego, CA, US

Rommie Amaro Rommie Amaro

Professor and Shuler Scholar, Chemistry and Biochemistry | UC San Diego

San Diego, CA, UNITED STATES

Her research focuses on development of computational methods in biophysics for applications to drug discovery.

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Protein Dynamics in Cellular Environments ǀ Rommie Amaro, UC San Diego Plenary: UCSD’s Rommie Amaro, Bio-IT World Conference & Expo 2017 Plenary Keynote Rommie Amaro, Physical Sciences at UC San Diego UCSD’s Rommie Amaro, Bio-IT World Conference & Expo 2017 Plenary Keynote

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Biography

Rommie E. Amaro is a professor of chemistry and biochemistry and the director of the National Biomedical Computation Resource at the University of California San Diego. Her research focuses on development of computational methods in biophysics for applications to drug discovery.

Areas of Expertise (7)

Computational Methods in Drug Discovery

Coronavirus

COVID-19

H1N1

Biochemistry

Chemistry

Molecular Biophysics

Education (2)

University of Illinois at Urbana-Champaign: Ph.D., Chemistry 2005

University of Illinois at Urbana-Champaign: B.S., Chemical Engineering 1999

Media Appearances (5)

Scientists Scan for Weaknesses in the SARS-CoV-2 Spike Protein

The Scientist  online

2020-04-09

This point must be in an “open” or “up” position, flexed and ready to attach itself to the host cell receptor, says Rommie Amaro, a biophysical chemist at the University of California, San Diego. An animation posted online by Greg Bowman, a biophysicist at Washington University School of Medicine, reveals that this looks like a creature opening its jaws.

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To Beat Covid-19, Scientists Try to 'See' the Invisible Enemy

WIRED  online

2020-04-08

Rommie Amaro has barely slept over the last month. Her voice buzzes with restless energy; her long sentences are punctuated with abrupt pauses as she recovers her train of thought. “Oh my God, can you tell I’m getting tired?” the UC San Diego biophysicist asks.

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Supercomputing speed proves crucial in the race against COVID-19

Medical Xpress  online

2020-04-03

"It's a brilliant test of our methods and our abilities to adapt to new data and to get this up and running right off the fly," said Rommie Amaro, professor at the University of California, San Diego and the researcher leading efforts to create the full model of COVID-19.

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Coronavirus massive simulations completed on Frontera supercomputer

Tech Xplore  online

2020-03-24

Rommie Amaro is leading efforts to build the first complete all-atom model of the SARS-COV-2 coronavirus envelope, its exterior component. "If we have a good model for what the outside of the particle looks like and how it behaves, we're going to get a good view of the different components that are involved in molecular recognition."

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Scientists Using Supercomputer to Build All-Atom Model of SARS-CoV-2 Coronavirus Envelope

Sci News  online

2020-03-24

“If we have a good model for what the outside of the particle looks like and how it behaves, we’re going to get a good view of the different components that are involved in molecular recognition,” said Professor Rommie Amaro, from the University of California, San Diego.

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Research Focus (3)

Computational Translational Research

The Amaro Lab

With petascale computing power on the immediate horizon and exascale computing not far behind, computational studies have the opportunity to make unprecedented contributions to drug discovery efforts. Large-scale simulations of increasingly realistic biological systems will allow us to investigate protein function and molecular recognition in atomic detail. These investigations will help drive discovery efforts and experimental work on these systems in collaboration with leading experimentalists. Our current investigations concern the neglected tropical diseases borne by the trypanosome organisms, potentially pandemic avian influenza, cancer, Chlamydia, and the cytochrome P450s.

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Addressing Complexity in Molecular Recognition

The Amaro

The current model for computer-aided drug design is simply to take one or a few crystallographic structure(s) of a protein receptor and design a single molecule to block its activity. Though this model has had some success, more sophisticated drug discovery and design methodologies will significantly increase the chances of scientists being able to design more effective drugs faster. Our work in this area focuses primarily on three major goals: the incorporation of receptor flexibility, investigating mechanisms of drug and antiviral resistance, and disease network pharmacology.

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Computational Virology

The Amaro Lab

With advances in the acquisition of biological structures, researchers can resolve near-atomic resolution structure of viral components. These studies give valuable information about what these proteins look like, which is important for understanding the infection process as well as to develop therapeutic options such as vaccines and drugs. However, because of experimental limitations, these datasets, though immensely informative, cannot give us a complete picture of these molecular machines. For example, mutations of various residues often need to be introduced to improve protein expression or to trap the molecule in a particular state. Regions that are highly dynamic are often removed, and, in addition, some biological components, such as lipid membranes and glycans, are difficult if not impossible to structurally resolve. Computational simulations, on the other hand, are not subject to the same limitations as experiment, and thus can be used to augment and extend experimental datasets. Biophysical molecular dynamics simulations are one such technique that allow researchers to restore the structures of experimentally determined biomolecular machines back to their original state, as well as add components that eluded experimental characterization. The Amaro lab uses such tools to explore the structure and dynamics of viruses and their interactions with the host cell at never-before-seen detail, ranging in scale from single protein investigations to whole virion studies.

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Articles (5)

An Open-Source Mesh Generation Platform for Biophysical Modeling Using Realistic Cellular Geometries Biophysical Journal

2020 Advances in imaging methods such as electron microscopy, tomography, and other modalities are enabling high-resolution reconstructions of cellular and organelle geometries. Such advances pave the way for using these geometries for biophysical and mathematical modeling once these data can be represented as a geometric mesh, which, when carefully conditioned, enables the discretization and solution of partial differential equations.

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Multiscale simulation approaches to modeling drug–protein binding Current Opinion in Structural Biology

2020 Simulations can provide detailed insight into the molecular processes involved in drug action, such as protein–ligand binding, and can therefore be a valuable tool for drug design and development. Processes with a large range of length and timescales may be involved, and understanding these different scales typically requires different types of simulation methodology.

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Mesoscale All-Atom Influenza Virus Simulations Suggest New Substrate Binding Mechanism ACS Cent. Sci.

2020 Influenza virus circulates in human, avian, and swine hosts, causing seasonal epidemic and occasional pandemic outbreaks. Influenza neuraminidase, a viral surface glycoprotein, has two sialic acid binding sites. The catalytic (primary) site, which also binds inhibitors such as oseltamivir carboxylate, is responsible for cleaving the sialic acid linkages that bind viral progeny to the host cell.

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Active site plasticity and possible modes of chemical inhibition of the human DNA deaminase APOBEC3B FASEB

2020 The single‐stranded DNA cytosine deaminase APOBEC3B (A3B) functions in innate immunity against viruses, but it is also strongly implicated in eliciting mutations in cancer genomes. Because of the critical role of A3B in promoting virus and tumor evolution, small molecule inhibitors are desirable.

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Molecular Docking of Broad-Spectrum Antibodies on Hemagglutinins of Influenza A Virus Evolutionary Bioinformatics

2019 Influenza A has caused several deadly pandemics throughout human history. The virus is often resistant to developed treatments because of its genetic drift or shift property. Broad-spectrum antibodies show a promising potential to overcome the resistance of influenza viruses.

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