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Explore our cutting edge research, world-class patient care, career opportunities and more.
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Advanced imaging and computational capabilities are rewriting the boundaries of what can be observed in biology. But as increasing amounts of raw data are generated, care must also be taken to ensure this data is used to its maximum potential.
St. Jude researchers are ensuring no stone is left unturned by enhancing the capabilities of existing key technologies to extract a deeper understanding of biology’s fundamental processes. This steadfast commitment ensures scientific breakthroughs are not outpaced by their pursuit and that no valuable information is neglected along the way.
AlphaSync keeps protein structure prediction up to date
In 2022, the AlphaFold Protein Structure Database launched, providing predictions for nearly all known and cataloged protein sequences. However, AlphaFold does not automatically update when new protein sequences are discovered, nor when an existing sequence is corrected based on new data. This means the quality of the predicted models can decrease over time, leading to out-of-date predicted structures and potentially cascading errors.
Published in Nature Structural & Molecular Biology, co-corresponding author M. Madan Babu, PhD, FRS, senior vice president of data science, chief data scientist, Center of Excellence for Data-Driven Discovery director and Department of Structural Biology member, and first and co-corresponding author Benjamin Lang, PhD, formerly Department of Structural Biology, created AlphaSync, a free database that improves upon existing protein structure prediction resources through continuous revision.
In a rapidly evolving scientific landscape, having access to the most current and accurate information on protein structural models is essential for breakthroughs in medicine and biology.
Department of Structural Biology
“In a rapidly evolving scientific landscape, having access to the most current and accurate information on protein structural models is essential for breakthroughs in medicine and biology,” said Babu. “With AlphaSync, we ensure predicted protein structures stay continuously updated, and we also enrich the models with key information such as amino acid interaction networks, surface accessibility, and disorder status, so that researchers can move from sequence to insight faster than ever before.”
In addition to updating structures, AlphaSync provides pre-computed data and other ease-of-use features, including a modernized data format, to keep research free of bottlenecks and ensure discoveries are built upon the latest available information.
ColdBrew taps into protein water networks to inform drug discovery
As research endeavors become more data-intensive, putting as much information as possible to work is at the core of many innovations. This approach motivated Marcus Fischer, PhD, Department of Chemical Biology & Therapeutics, to bring a frequently overlooked feature of experimentally obtained protein structures into focus: their water network.
Proteins have evolved to fold precisely according to the repulsion and attraction of their amino acid building blocks to each other and to water. Water is also key to protein activity since it helps guide other molecules, including drug molecules, to bind effectively. Drug discovery efforts often use techniques such as X-ray crystallography and cryo-
electron microscopy for structure determination. However, these techniques involve freezing, or “cryogenic” temperatures, which can distort how water molecules appear in structural models. The severity of this practice is currently unappreciated, as water molecules are often seen as an inconvenience and routinely thrown out of analyses.
The importance of water in drug efficacy motivated tapping into this network. Published in Nature Methods, a computational tool called ColdBrew puts water to work by accurately predicting the likelihood that cryogenic water molecules would also appear at physiological temperatures within experimental protein structures. Importantly, the ColdBrew metric captures the ability of drugs to displace these water molecules.
“To enable the wide use of ColdBrew, we pre-calculated probabilities for over 46 million water molecules across 100,000 proteins in the Protein Data Bank,” Fischer, the study’s corresponding author, said. “Remarkably, our results show that drug designers unknowingly avoid tightly bound waters, so actually knowing which ones to avoid could guide the process.”
Parallel Rapid Exchange takes sample prep noise out of single-molecule data
As Fischer recaptures neglected information from X-ray crystallography and cryo-electron microscopy data, the complementary technique of single-molecule fluorescent imaging has matured into a powerful way to observe the finer details of protein dynamics. However, the technical issues that arise from working at such a small scale have become major barriers to observing fleeting states in single-molecule motion.
To address this, a technique called Parallel Rapid Exchange (PRE), published in Nature Methods, is bringing transient protein dynamics into clear view. Single-molecule imaging techniques usually require independent measurements to be taken. PRE introduces parallel data collection, which means multiple measurements can be set up at once under identical conditions, allowing subtle functional dynamics to be measured.
PRE eliminates the minute differences in experimental setup and execution, such as sample concentrations and noise, which traditionally mask equally minute molecular motions, giving greater sensitivity to the single-molecule data and higher experimental throughput.
“We found ways to improve the efficiency, reproducibility, sensitivity, and reliability of single-molecule microscopes,” explained corresponding author Scott Blanchard, PhD, Department of Structural Biology. “This method forms the basis of a generalizable and scalable approach for parallelized single-molecule imaging that we hope will reveal subtle, yet fundamentally important, functional distinctions in the molecules that support life at unprecedented resolution.”
With this approach, the researchers could uncover previously unseen protein dynamics behind fundamental processes. In one example, they studied how a major class of cell-surface proteins, called G protein-coupled receptors (GPCRs), convert signals from outside the cell into internal responses. GPCRs are managed by regulatory proteins, including β-arrestin1. By observing four β-arrestin1 sensors simultaneously, the researchers obtained the full picture of how the regulatory protein moves when it is activated.
“We knew there were three big structural changes that occur within β-arrestin1, but they have largely been reported as concerted events,” Blanchard said. “With parallelization, we could show that they don’t happen simultaneously; instead, two of them occur at about the same time, and only then, the slower, rate-limiting rotation, is allowed to happen. This was not possible to decisively determine before.”
Maximizing the value of data
These studies show how new technologies can deepen our understanding of biology’s most fundamental processes. As data becomes easier to generate, scientists must be mindful that what they collect is not only meaningful but also used to its fullest potential.
Technology improvements, such as AlphaSync, ColdBrew, and Parallel Rapid Exchange, ensure that any valuable information that might be overlooked along the path to discovery does not remain overlooked forever.