Collection of X-Ray Diffraction Data from Macromolecular Crystals

Resonant multiphoton processes and excitation limits to structural dynamics

Understanding the chemical reactions that give rise to functional biological systems is at the core of structural biology. As techniques are developed to study the chemical reactions that drive biological processes, it must be ensured that the reaction occurring is indeed a biologically relevant pathway. There is mounting evidence indicating that there has been a propagation of systematic error in the study of photoactive biological processes; the optical methods used to probe the structural dynamics of light activated protein functions have failed to ensure that the photoexcitation prepares a well-defined initial state relevant to the biological process of interest. Photoexcitation in nature occurs in the linear (one-photon per chromophore) regime; however, the extreme excitation conditions used experimentally give rise to biologically irrelevant multiphoton absorption. To evaluate and ensure the biological relevance of past and future experiments, a theoretical framework has been developed to determine the excitation conditions, which lead to resonant multiphoton absorption (RMPA) and thus define the excitation limit in general for the study of structural dynamics within the 1-photon excitation regime. Here, we apply the theoretical model to bacteriorhodopsin (bR) and show that RMPA occurs when excitation conditions exceed the linear saturation threshold, well below typical excitation conditions used in this class of experiments. This work provides the guidelines to ensure excitation in the linear 1-photon regime is relevant to biological and chemical processes.

BioCARS: Synchrotron facility for probing structural dynamics of biological macromolecules

A major goal in biomedical science is to move beyond static images of proteins and other biological macromolecules to the internal dynamics underlying their function. This level of study is necessary to understand how these molecules work and to engineer new functions and modulators of function. Stemming from a visionary commitment to this problem by Keith Moffat decades ago, a community of structural biologists has now enabled a set of x-ray scattering technologies for observing intramolecular dynamics in biological macromolecules at atomic resolution and over the broad range of timescales over which motions are functionally relevant. Many of these techniques are provided by BioCARS, a cutting-edge synchrotron radiation facility built under Moffat leadership and located at the Advanced Photon Source at Argonne National Laboratory. BioCARS enables experimental studies of molecular dynamics with time resolutions spanning from 100 ps to seconds and provides both time-resolved x-ray crystallography and small- and wide-angle x-ray scattering. Structural changes can be initiated by several methods-UV/Vis pumping with tunable picosecond and nanosecond laser pulses, substrate diffusion, and global perturbations, such as electric field and temperature jumps. Studies of dynamics typically involve subtle perturbations to molecular structures, requiring specialized computational techniques for data processing and interpretation. In this review, we present the challenges in experimental macromolecular dynamics and describe the current state of experimental capabilities at this facility. As Moffat imagined years ago, BioCARS is now positioned to catalyze the scientific community to make fundamental advances in understanding proteins and other complex biological macromolecules.

A deep learning method for drug-target affinity prediction based on sequence interaction information mining

Background

A critical aspect of in silico drug discovery involves the prediction of drug-target affinity (DTA). Conducting wet lab experiments to determine affinity is both expensive and time-consuming, making it necessary to find alternative approaches. In recent years, deep learning has emerged as a promising technique for DTA prediction, leveraging the substantial computational power of modern computers.

Methods

We proposed a novel sequence-based approach, named KC-DTA, for predicting drug-target affinity (DTA). In this approach, we converted the target sequence into two distinct matrices, while representing the molecule compound as a graph. The proposed method utilized k-mers analysis and Cartesian product calculation to capture the interactions and evolutionary information among various residues, enabling the creation of the two matrices for target sequence. For molecule, it was represented by constructing a molecular graph where atoms serve as nodes and chemical bonds serve as edges. Subsequently, the obtained target matrices and molecule graph were utilized as inputs for convolutional neural networks (CNNs) and graph neural networks (GNNs) to extract hidden features, which were further used for the prediction of binding affinity.

Results

In order to evaluate the effectiveness of the proposed method, we conducted several experiments and made a comprehensive comparison with the state-of-the-art approaches using multiple evaluation metrics. The results of our experiments demonstrated that the KC-DTA method achieves high performance in predicting drug-target affinity (DTA). The findings of this research underscore the significance of the KC-DTA method as a valuable tool in the field of in silico drug discovery, offering promising opportunities for accelerating the drug development process. All the data and code are available for access on https://github.com/syc2017/KCDTA.

Non-Canonical Amino Acids in Analyses of Protease Structure and Function

All known organisms encode 20 canonical amino acids by base triplets in the genetic code. The cellular translational machinery produces proteins consisting mainly of these amino acids. Several hundred natural amino acids serve important functions in metabolism, as scaffold molecules, and in signal transduction. New side chains are generated mainly by post-translational modifications, while others have altered backbones, such as the β- or γ-amino acids, or they undergo stereochemical inversion, e.g., in the case of D-amino acids. In addition, the number of non-canonical amino acids has further increased by chemical syntheses. Since many of these non-canonical amino acids confer resistance to proteolytic degradation, they are potential protease inhibitors and tools for specificity profiling studies in substrate optimization and enzyme inhibition. Other applications include in vitro and in vivo studies of enzyme kinetics, molecular interactions and bioimaging, to name a few. Amino acids with bio-orthogonal labels are particularly attractive, enabling various cross-link and click reactions for structure-functional studies. Here, we cover the latest developments in protease research with non-canonical amino acids, which opens up a great potential, e.g., for novel prodrugs activated by proteases or for other pharmaceutical compounds, some of which have already reached the clinical trial stage.

Structural biology and public health response to biomedical threats

Over the course of the pandemic caused by SARS-CoV-2, structural biologists have worked hand in hand with groups developing vaccines and treatments. However, relying solely on in vitro and clinical studies may be insufficient to guide vaccination and treatment developments, and other healthcare policies during virus mutations or peaks in infections and fatalities. Therefore, it is crucial to track statistical data related to the number of infections, deaths, and vaccinations in specific regions and present it in an easy-to-understand way.

Genome-wide analysis of the Populus trichocarpa laccase gene family and functional identification of PtrLAC23

INTRODUCTION

Biofuel is a kind of sustainable, renewable and environment friendly energy. Lignocellulose from the stems of woody plants is the main raw material for "second generation biofuels". Lignin content limits fermentation yield and is therefore a major obstacle in biofuel production. Plant laccase plays an important role in the final step of lignin formation, which provides a new strategy for us to obtain ideal biofuels by regulating the expression of laccase genes to directly gain the desired lignin content or change the composition of lignin.

METHODS

Multiple sequence alignment and phylogenetic analysis were used to classify PtrLAC genes; sequence features of PtrLACs were revealed by gene structure and motif composition analysis; gene duplication, interspecific collinearity and Ka/Ks analysis were conducted to identify ancient PtrLACs; expression levels of PtrLAC genes were measured by RNA-Seq data and qRT-PCR; domain analysis combine with cis-acting elements prediction together showed the potential function of PtrLACs. Furthermore, Alphafold2 was used to simulate laccase 3D structures, proLAC23::LAC23-eGFP transgenic Populus stem transects were applied to fluorescence observation.

RESULTS

A comprehensive analysis of the P. trichocarpa laccase gene (PtLAC) family was performed. Some ancient PtrLAC genes such as PtrLAC25, PtrLAC19 and PtrLAC41 were identified. Gene structure and distribution of conserved motifs clearly showed sequence characteristics of each PtrLAC. Combining published RNA-Seq data and qRT-PCR analysis, we revealed the expression pattern of PtrLAC gene family. Prediction results of cis-acting elements show that PtrLAC gene regulation was closely related to light. Through above analyses, we selected 5 laccases and used Alphafold2 to simulate protein 3D structures, results showed that PtrLAC23 may be closely related to the lignification. Fluorescence observation of proLAC23::LAC23-eGFP transgenic Populus stem transects and qRT-PCR results confirmed our hypothesis again.

DISCUSSION

In this study, we fully analyzed the Populus trichocarpa laccase gene family and identified key laccase genes related to lignification. These findings not only provide new insights into the characteristics and functions of Populus laccase, but also give a new understanding of the broad prospects of plant laccase in lignocellulosic biofuel production.

Crystallographic-Morphological Connections in Star Shaped Metal-Organic Frameworks

The symmetry of a crystal's morphology usually reflects the symmetry of the crystallographic packing. For single crystals, the space and point groups allow only a limited number of mathematical descriptions of the morphology (forms), all of which are convex polyhedrons. In contrast, concave polyhedrons are a hallmark of twinning and polycrystallinity and are typically inconsistent with single crystallinity. Here we report a new type of structure: a concave polyhedron shape single crystal having a multidomain appearance and a rare space group (P622). Despite these unusual structural features, the hexagonal symmetry is revealed at the morphological levels.

Fungal dual-domain LysM effectors undergo chitin-induced intermolecular, and not intramolecular, dimerization

Chitin is a homopolymer of β-(1,4)-linked N-acetyl-D-glucosamine (GlcNAc) and a major structural component of fungal cell walls. In plants, chitin acts as a microbe-associated molecular pattern (MAMP) that is recognized by lysin motif (LysM)-containing plant cell surface-localized pattern recognition receptors (PRRs) that activate a plethora of downstream immune responses. To deregulate chitin-induced plant immunity and successfully establish infection, many fungal pathogens secrete LysM domain-containing effector proteins during host colonization. The LysM effector Ecp6 from the tomato (Solanum lycopersicum) leaf mold fungus Cladosporium fulvum can outcompete plant PRRs for chitin binding because two of its three LysM domains cooperate to form a composite groove with ultra-high (pM) chitin-binding affinity. However, most functionally characterized LysM effectors contain only two LysMs, including Magnaporthe oryzae MoSlp1, Verticillium dahliae Vd2LysM, and Colletotrichum higginsianum ChElp1 and ChElp2. Here, we performed modeling, structural, and functional analyses to investigate whether such dual-domain LysM effectors can also form ultra-high chitin-binding affinity grooves through intramolecular LysM dimerization. However, our study suggests that intramolecular LysM dimerization does not occur. Rather, our data support the occurrence of intermolecular LysM dimerization for these effectors, associated with a substantially lower chitin binding affinity than monitored for Ecp6. Interestingly, the intermolecular LysM dimerization allows for the formation of polymeric complexes in the presence of chitin. Possibly, such polymers may precipitate at infection sites to eliminate chitin oligomers, and thus suppress the activation of chitin-induced plant immunity.

Molecular storytelling for online structural biology outreach and education

Knowledge about the structure and function of biomolecules continues to grow exponentially, enabling us to "see" structural snapshots of biomolecular interactions and functional assemblies. At PDB-101, the educational portal of the RCSB Protein Data Bank, we have taken a storytelling approach to make this body of knowledge accessible and comprehensible to a wide community of students, educators, and the general public. For over 20 years, the Molecule of the Month series has utilized a traditional illustrated storytelling approach that is regularly adapted for classroom instruction. Similar visual and interactive storytelling approaches are used to present topical subjects at PDB-101 and full curricular materials and case studies for building a detailed narrative around topics of particular interest. This emphasis on storytelling led to the Video Challenge for High School students, now in its 8th year. In this Article, we will present some of the lessons we have learned for teaching and communicating structural biology using the PDB archive of biomolecular structures.

Computational formulation and immune dynamics of a multi-peptide vaccine candidate against Crimean-Congo hemorrhagic fever virus

The sole objective of this research is to devise an epitope-based vaccine candidate as prophylaxis for the Crimean-Congo hemorrhagic fever virus (CCHFV) using the knowledge of immunoinformatics and structural biology. Importantly, CCHFV outbreaks have increased in several countries resulting in increased mortality up to 40% due to the lack of prospective medication and an efficient vaccine. In this study, we have used several immunoinformatic tools and servers to anticipate potent B-cell and T-cell epitopes from the CCHFV glycoprotein with the highest antigenicity. After a comprehensive evaluation, a vaccine candidate was designed using 6 CD8⁺, 3 CD4⁺, and 7 B-cell epitopes with appropriate linkers. To enhance the vaccine's efficiency, we added Mycobacterium tuberculosis lipoprotein LprG (Rv1411c) to the vaccine as an adjuvant. The final construct was composed of a total of 468 amino acid residues. The epitope included in the construct showed 98% worldwide population coverage. Importantly, the construct appeared as antigenic, immunogenic, soluble, and non-allergenic in nature. To explore further, we modelled the three-dimensional (3D) structure of the constructed vaccine. Our chimeric vaccine showed stable and strong interactions for toll-like receptor 2 (TLR2) found on the cell surface. Moreover, the dynamics simulation of immune response showed elevated levels of cellular immune activity and faster clearance of antigen from the body upon repetitive exposure. Finally, the optimized codon (CAI≈1) ensured the marked translation efficiency of the vaccine protein in E. coli strain K12 bacterium followed by the insertion of construct DNA into the cloning vector pET28a (+). We believe that the designed vaccine chimera could be useful in vaccine development to fight CCHFV outbreaks.

JUNGFRAU detector for brighter x-ray sources: Solutions for IT and data science challenges in macromolecular crystallography

In this paper, we present a data workflow developed to operate the adJUstiNg Gain detector FoR the Aramis User station (JUNGFRAU) adaptive gain charge integrating pixel-array detectors at macromolecular crystallography beamlines. We summarize current achievements for operating at 9 GB/s data-rate a JUNGFRAU with 4 Mpixel at 1.1 kHz frame-rate and preparations to operate at 46 GB/s data-rate a JUNGFRAU with 10 Mpixel at 2.2 kHz in the future. In this context, we highlight the challenges for computer architecture and how these challenges can be addressed with innovative hardware including IBM POWER9 servers and field-programmable gate arrays. We discuss also data science challenges, showing the effect of rounding and lossy compression schemes on the MX JUNGFRAU detector images.

The Integrated Resource for Reproducibility in Macromolecular Crystallography: Experiences of the first four years

It has been increasingly recognized that preservation and public accessibility of primary experimental data are cornerstones necessary for the reproducibility of empirical sciences. In the field of molecular crystallography, many journals now recommend that authors of manuscripts presenting a new crystal structure should deposit their primary experimental data (X-ray diffraction images) to one of the dedicated resources created in recent years. Here, we describe our experiences developing the Integrated Resource for Reproducibility in Molecular Crystallography (IRRMC) and describe several examples of a crucial role that diffraction data can play in improving previously determined protein structures. In its first four years, several hundred crystallographers have deposited data from over 5200 diffraction experiments performed at over 60 different synchrotron beamlines or home sources all over the world. In addition to improving the resource and curating submitted data, we have been building a pipeline for extraction or, in some cases, reconstruction of the metadata necessary for seamless automated processing. Preliminary analysis indicates that about 95% of the archived data can be automatically reprocessed. A high rate of reprocessing success shows the feasibility of using the automated metadata extraction and automated processing as a validation step for the deposition of raw diffraction images. The IRRMC is guided by the Findable, Accessible, Interoperable, and Reusable data management principles.

Recent innovations in membrane-protein structural biology

Innovations are expanding the capabilities of experimental investigations of the structural properties of membrane proteins. Traditionally, three-dimensional structures have been determined by measuring x-ray diffraction using protein crystals with a size of least 100 μm. For membrane proteins, achieving crystals suitable for these measurements has been a significant challenge. The availabilities of micro-focus x-ray beams and the new instrumentation of x-ray free-electron lasers have opened up the possibility of using submicrometer-sized crystals. In addition, advances in cryo-electron microscopy have expanded the use of this technique for studies of protein crystals as well as studies of individual proteins as single particles. Together, these approaches provide unprecedented opportunities for the exploration of structural properties of membrane proteins, including dynamical changes during protein function.