Massive X-ray screening reveals two allosteric drug binding sites of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous health problems and economical challenges for mankind. To date, no effective drug is available to directly treat the disease and prevent virus spreading. In a search for a drug against COVID-19, we have performed a massive X-ray crystallographic screen of repurposing drug libraries containing 5953 individual compounds against the SARS-CoV-2 main protease (Mpro), which is a potent drug target as it is essential for the virus replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds binding to Mpro. In subsequent cell-based viral reduction assays, one peptidomimetic and five non-peptidic compounds showed antiviral activity at non-toxic concentrations. Interestingly, two compounds bind outside the active site to the native dimer interface in close proximity to the S1 binding pocket. Another compound binds in a cleft between the catalytic and dimerization domain of Mpro. Neither binding site is related to the enzymatic active site and both represent attractive targets for drug development against SARS-CoV-2. This X-ray screening approach thus has the potential to help deliver an approved drug on an accelerated time-scale for this and future pandemics

X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput X-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (M^(pro)), which is essential for viral replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to M^(pro). In subsequent cell-based viral reduction assays, one peptidomimetic and six non-peptidic compounds showed antiviral activity at non-toxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2

Advancements in Diffraction Analysis Methods and Data Reduction Techniques for Serial Crystallography

Proteins play a crucial role in living cells. Their functions are determined by their three-dimensional (3D) structure. This atomic-scale structure is usually investigated by crystallography using X-ray sources such as an X-ray tube, synchrotron or Free Electron Laser (FEL). The conventional approach to macromolecular crystallography (MX) is to acquire diffraction patterns from a crystal as it is rotated about one or more axes to get the full 3D diffraction volume of the studied crystal. The total X-ray exposure of the crystal is limited by the accumulation of damage to the protein structure and crystal lattice by ionising radiation. Cryogenic cooling reduces the processes of radiolysis and extends the dose that can be tolerated. However, such cooling may alter the macromolecular structure and prevent the ability to measure dynamical processes by time-resolved methods. For efficient measurement at room temperature (RT) and investigating fast protein dynamics, serial crystallography (SX) comes into play. In this method, the studied crystals' 3D diffraction volume (reciprocal space) is merged from still diffraction patterns collected from small randomly oriented crystals exposed by X-rays. This technique must be capable of assembling a complete three-dimensional dataset of structure factor moduli using a large number of individual still diffraction patterns. SX enables a wide range of experiments, including measurements at room temperature, time-resolved studies on biological crystals, measuring sub-micron-sized crystals, and obtaining structures of radiation-sensitive proteins. Known problems in serial crystallography are the high threshold to enter the field, the lack of a user-friendly data processing pipeline, and the huge amount of data that must be processed and reduced to get the structure of the studied protein. This dissertation is dedicated to developing solutions for addressing the issues mentioned above.Recent advancements in X-ray facilities, including 4th generation synchrotrons and FELs, in combination with state-of-the-art X-ray detectors, have enabled conducting SX experiments at a remarkable rate, capturing more than 1000 images per second. However, this increased acquisition rate comes with a trade-off - an enormous volume of data, with some experiments already yielding up to 5 PB of measured data. As a result, novel data reduction strategies need to be developed and implemented to handle this vast amount of information efficiently. The most common method to reduce the size of the measured data is the usage of lossless compression. The compression rate and speed of different compression algorithms available for the HDF5 library were checked using different datasets. This extensive evaluation demonstrated that lossless compression methods maintain the original data without any alteration but cannot achieve a high compression ratio. Thus, some lossy compression and data reduction are needed. For this reason, the following approaches were successfully tested on different datasets: binning, quantisation (including quantisation using a non-uniform step), and non-hits rejection. Also, it was shown that such approaches as measuring less data or storing data within the area of identified Bragg peaks in a diffraction pattern may lead to data quality degradation and, therefore, are not recommended for general use. A set of data metrics capable of assessing the loss of information due to applying various compression schemes is used to evaluate the effect of any lossy compression schemes. Different data quality metrics are described and used for testing various data reduction schemes. A proper way to use each quality metric is also described in detail.Notably, non-hits rejection and binning process automation have been successfully implemented into the routine data processing pipeline and tested on data collected with the TapeDrive sample-delivery method at the P11 beamline, PETRA III. Furthermore, the presented non-uniform quantisation compression technique holds potential for application in other datasets, including electron or neutron diffraction.The enormous amount of measured data poses another challenge: it cannot be processed manually. Instead, an auto-processing pipeline has to be developed. Considering how the crystals are measured in MX and SX, the data analysis techniques differ for those two methods. Therefore, the existing pipelines used for MX are hardly applicable to the SX data. Despite significant progress in this field for SX over the past decade, establishing a universal, reliable processing pipeline compatible with different sample delivery systems remains a complex challenge. This dissertation aims to develop a well-established, robust and universally applicable data processing pipeline for SX, which constitutes the generation of various figures of merit and compiling overall statistics for proper data evaluation at each stage of data processing and for publishing purposes. Multiple experiments at FELs and synchrotrons were processed during the work on the dissertation, and some of the results are presented to illustrate the benefits of using the developed algorithms. This dissertation emphasised data with observable undesirable features, such as the presence of ice rings and salt reflections. To address these issues, a special software package was developed and used as a part of the developed data processing pipeline. This automatic data processing pipeline has been implemented in the control system of a drug-screening P09 beamline, PETRA III. This dissertation outlines a strategy to optimise SSX beamtimes using fixed-target sample delivery methods like chips. The approach involves two key steps: initially, a rapid raster scan of the chip identifies crystal positions via diffraction, followed by measuring a rotational series at these positions within a small range of angles. This method efficiently avoids empty positions during data acquisition, saving precious beam time and reducing data volume. It is particularly effective when the chip has few crystals, common with challenging-to-crystallise proteins. This approach is critical for maximising crystal utilisation and enhancing the likelihood of successfully determining protein structures.The dissertation contributes to the advancement of serial crystallography by establishing a reliable data processing and reduction framework, ensuring the reproducibility and reliability of obtained final results. Developed strategies open up new possibilities for carrying out the experiments in an efficient way and overcoming the problem with data storage

Tpp49Aa1 streamfiles from MHz SFX at EuXFEL

<p>Streamfiles and HKLs processed with CrystFEL from data collected at European XFEL. The processing parameters are at the end of the HKL-Files.</p&gt

An Optimized Approach for Serial Crystallography Using Chips

Serial crystallography is a rapidly developing field that makes it possible to determine the structure of biomolecules at room temperature with atomic resolution. Numerous advances in detectors, data analysis pipelines, sample delivery methods, and crystallization protocols expand the scope of structural biology to understand the fundamental processes that take place in living cells. At the same time, all stages of experiments should be maximally optimized to avoid loss of beamtime. Thus, this paper proposes a strategy for optimizing beamtime utilization while using a fixed target sample delivery method such as chips. The strategy consists of two steps: first, a fast raster scan of the chip is performed to determine the positions of the crystals, and then small rotational series are measured at predetermined positions. Such an approach skips empty positions during data acquisition, saving valuable beam time and, as an additional consequence, reducing the volume of measured data

<i>FDIP</i>—A Fast Diffraction Image Processing Library for X-ray Crystallography Experiments

Serial crystallography (SX) is a cutting-edge technique in structural biology, involving the systematic collection of X-ray diffraction data from numerous randomly oriented microcrystals. To extract comprehensive three-dimensional information about the studied system, SX utilises thousands of measured diffraction patterns. As such, SX takes advantages of the properties of modern X-ray sources, including Free Electron Lasers (FELs) and third and fourth generation synchrotrons, as well as contemporary high-repetition-rate detectors. Efficient analysis of the extensive datasets generated during SX experiments demands fast and effective algorithms. The FDIP library offers meticulously optimised functions tailored for preprocessing data obtained in SX experiments. This encompasses tasks such as background subtraction, identification and masking of parasitic streaks, elimination of unwanted powder diffraction (e.g., from ice or salt crystals), and pinpointing useful Bragg peaks in each diffraction pattern. The library is equipped with a user-friendly graphical interface for facile parameter adjustment tailored to specific datasets. Compatible with popular SX processing software like OnDA, Cheetah, CrystFEL, and Merge3D, the FDIP library enhances the capabilities of these tools for streamlined and precise serial crystallography analyses

JINXED: Just in time crystallization for easy structure determination of biological macromolecules

Macromolecular crystallography is a well-established method in the field of structure biology and has led to the majority of known protein structures to date. After focusing on static structures, the method is now developing towards the investigation of protein dynamics through time-resolved methods. These experiments often require multiple handling steps of the sensitive protein crystals, e.g. for ligand soaking and cryo-protection. These handling steps can cause significant crystal damage, causing a decrease in data quality. Furthermore, in time-resolved experiments based on serial crystallography that use micron-sized crystals for short diffusion times of ligands, certain crystal morphologies with small solvent channels can prevent sufficient ligand diffusion. Described here is a method combining protein crystallization and data collection in a novel one-step-process. Corresponding experiments were successfully performed as a proof-of-principle using hen egg white lysozyme and crystallization times of only a few seconds. This method called JINXED (Just in time crystallization for easy structure determination) promises to result in high-quality data due the avoidance of crystal handling and has the potential to enable time-resolved experiments with crystals containing small solvent channels by adding potential ligands to the crystallization buffer, simulating traditional co-crystallization approaches

JINXED: Just in time crystallization for easy structure determination of biological macromolecules

Macromolecular crystallography is a well-established method in the field of structure biology and has led to the majority of known protein structures to date. After focusing on static structures, the method is now developing towards the investigation of protein dynamics through time-resolved methods. These experiments often require multiple handling steps of the sensitive protein crystals, e.g. for ligand soaking and cryo-protection. These handling steps can cause significant crystal damage, causing a decrease in data quality. Furthermore, in time-resolved experiments based on serial crystallography that use micron-sized crystals for short diffusion times of ligands, certain crystal morphologies with small solvent channels can prevent sufficient ligand diffusion. Described here is a method combining protein crystallization and data collection in a novel one-step-process. Corresponding experiments were successfully performed as a proof-of-principle using hen egg white lysozyme and crystallization times of only a few seconds. This method called JINXED (Just in time crystallization for easy structure determination) promises to result in high-quality data due the avoidance of crystal handling and has the potential to enable time-resolved experiments with crystals containing small solvent channels by adding potential ligands to the crystallization buffer, simulating traditional co-crystallization approaches

An Optimized Approach for Serial Crystallography Using Chips

Serial crystallography is a rapidly developing method for the determination of the structure of biomolecules at room temperature at near-atomic resolution from an ensemble of small crystals. Numerous advances in detectors, data analysis pipelines, sample delivery methods, and crystallization protocols expand the scope of structural biology to understand the fundamental processes that take place in living cells. Many experimental strategies for serial crystallography are in use, depending on the type and sizes of the crystals or other needs of the experiment. Such strategies should ideally minimize the wastage of samples or beamtime without compromising experimental goals. This paper proposes a way to optimize beamtime utilization in serial crystallography experiments that use fixed-target sample delivery methods, such as chips. The strategy involves two key steps. Firstly, a fast raster scan of the chip is performed to determine the positions of the crystals based on their diffraction. Subsequently, a rotational series is collected at each identified crystal position, covering a narrow range of chip orientations. This approach enables the exclusion of empty positions during data acquisition, resulting in significant savings in beam time utilization and a reduced volume of measured data