Bioinspired 3D flexible devices and functional systems.

Flexible devices and functional systems with elaborated three-dimensional (3D) architectures can endow better mechanical/electrical performances, more design freedom, and unique functionalities, when compared to their two-dimensional (2D) counterparts. Such 3D flexible devices/systems are rapidly evolving in three primary directions, including the miniaturization, the increasingly merged physical/artificial intelligence and the enhanced adaptability and capabilities of heterogeneous integration. Intractable challenges exist in this emerging research area, such as relatively poor controllability in the locomotion of soft robotic systems, mismatch of bioelectronic interfaces, and signal coupling in multi-parameter sensing. By virtue of long-time-optimized materials, structures and processes, natural organisms provide rich sources of inspiration to address these challenges, enabling the design and manufacture of many bioinspired 3D flexible devices/systems. In this Review, we focus on bioinspired 3D flexible devices and functional systems, and summarize their representative design concepts, manufacturing methods, principles of structure-function relationship and broad-ranging applications. Discussions on existing challenges, potential solutions and future opportunities are also provided to usher in further research efforts toward realizing bioinspired 3D flexible devices/systems with precisely programmed shapes, enhanced mechanical/electrical performances, and high-level physical/artificial intelligence.

Structural and functional insight into a new emerging target IP3R in cancer.

Calcium signaling has been identified as an important phenomenon in a plethora of cellular processes. Inositol 1,4,5-trisphosphate receptors (IP3Rs) are ER-residing intracellular calcium (Ca2+) release channels responsible for cell bioenergetics by transferring calcium from the ER to the mitochondria. The recent availability of full-length IP3R channel structure has enabled the researchers to design the IP3 competitive ligands and reveal the channel gating mechanism by elucidating the conformational changes induced by ligands. However, limited knowledge is available for IP3R antagonists and the exact mechanism of action of these antagonists within a tumorigenic environment of a cell. Here in this review a summarized information about the role of IP3R in cell proliferation and apoptosis has been discussed. Moreover, structure and gating mechanism of IP3R in the presence of antagonists have been provided in this review. Additionally, compelling information about ligand-based studies (both agonists and antagonists) has been discussed. The shortcomings of these studies and the challenges toward the design of potent IP3R modulators have also been provided in this review. However, the conformational changes induced by antagonists for channel gating mechanism still display some major drawbacks that need to be addressed. However, the design, synthesis and availability of isoform-specific antagonists is a rather challenging one due to intra-structural similarity within the binding domain of each isoform. HighlightsThe intricate complexity of IP3R's in cellular processes declares them an important target whereby, the recently solved structure depicts the receptor's potential involvement in a complex network of processes spanning from cell proliferation to cell death.Pharmacological inhibition of IP3R attenuates the proliferation or invasiveness of cancers, thus inducing necrotic cell death.Despite significant advancements, there is a tremendous need to design new potential hits to target IP3R, based upon 3D structural features and pharmacophoric patterns.Communicated by Ramaswamy H. Sarma.

Plant-TFClass: a structural classification for plant transcription factors.

Transcription factors (TFs) bind DNA at specific sequences to regulate gene expression. This universal process is achieved via their DNA-binding domain (DBD). In mammals, the vast diversity of DBD structural conformations and the way in which they contact DNA has been used to organize TFs in the TFClass hierarchical classification. However, the numerous DBD types present in plants but absent from mammalian genomes were missing from this classification. We reviewed DBD 3D structures and models available for plant TFs to classify most of the 56 recognized plant TF types within the TFClass framework. This extended classification adds eight new classes and 37 new families corresponding to DBD structures absent in mammals. Plant-TFClass provides a unique resource for TF comparison across families and organisms.

Application of PolyPRep tools on HIV protease polyproteins using molecular docking

Abstract In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their size and length. The prepare for studies using state-of-the-art techniques such as Machine Learning, a good representation of such proteins is a must. We present an alternative to this problem, implementing a fragmentation and modeling protocol to prepare those polyproteins in the form of peptide fragments. Such procedure is made by several scripts, implemented together on the workflow we call PolyPRep, a tool written in Python script and available in GitHub. This software is freely available only for noncommercial users.

Resumo Nos últimos anos, o desenvolvimento de tecnologias de alto rendimento para obtenção de dados sequenciais potencializou a possibilidade de análise de dados proteicos in silico. No entanto, quando se trata de estudos de interação de poliproteínas virais, existe uma lacuna na representação dessas proteínas, devido ao seu tamanho e comprimento. Para estudos utilizando técnicas de ponta como o Aprendizado de Máquina, uma boa representação dessas proteínas é imprescindível. Apresentamos uma alternativa para este problema, implementando um protocolo de fragmentação e modelagem para preparar essas poliproteínas na forma de fragmentos de peptídeos. Tal procedimento é feito por diversos scripts, implementados em conjunto no workflow que chamamos de PolyPRep, uma ferramenta escrita em script Python e disponível no GitHub. Este software está disponível gratuitamente apenas para usuários não comerciais.

Application of PolyPRep tools on HIV protease polyproteins using molecular docking / Aplicação da ferramenta PolyPRep em poliproteínas de protease de HIV usando docking molecular

Abstract In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their size and length. The prepare for studies using state-of-the-art techniques such as Machine Learning, a good representation of such proteins is a must. We present an alternative to this problem, implementing a fragmentation and modeling protocol to prepare those polyproteins in the form of peptide fragments. Such procedure is made by several scripts, implemented together on the workflow we call PolyPRep, a tool written in Python script and available in GitHub. This software is freely available only for noncommercial users.

Resumo Nos últimos anos, o desenvolvimento de tecnologias de alto rendimento para obtenção de dados sequenciais potencializou a possibilidade de análise de dados proteicos in silico. No entanto, quando se trata de estudos de interação de poliproteínas virais, existe uma lacuna na representação dessas proteínas, devido ao seu tamanho e comprimento. Para estudos utilizando técnicas de ponta como o Aprendizado de Máquina, uma boa representação dessas proteínas é imprescindível. Apresentamos uma alternativa para este problema, implementando um protocolo de fragmentação e modelagem para preparar essas poliproteínas na forma de fragmentos de peptídeos. Tal procedimento é feito por diversos scripts, implementados em conjunto no workflow que chamamos de PolyPRep, uma ferramenta escrita em script Python e disponível no GitHub. Este software está disponível gratuitamente apenas para usuários não comerciais.

PANDORA v2.0: Benchmarking peptide-MHC II models and software improvements.

T-cell specificity to differentiate between self and non-self relies on T-cell receptor (TCR) recognition of peptides presented by the Major Histocompatibility Complex (MHC). Investigations into the three-dimensional (3D) structures of peptide:MHC (pMHC) complexes have provided valuable insights of MHC functions. Given the limited availability of experimental pMHC structures and considerable diversity of peptides and MHC alleles, it calls for the development of efficient and reliable computational approaches for modeling pMHC structures. Here we present an update of PANDORA and the systematic evaluation of its performance in modelling 3D structures of pMHC class II complexes (pMHC-II), which play a key role in the cancer immune response. PANDORA is a modelling software that can build low-energy models in a few minutes by restraining peptide residues inside the MHC-II binding groove. We benchmarked PANDORA on 136 experimentally determined pMHC-II structures covering 44 unique αß chain pairs. Our pipeline achieves a median backbone Ligand-Root Mean Squared Deviation (L-RMSD) of 0.42 Å on the binding core and 0.88 Å on the whole peptide for the benchmark dataset. We incorporated software improvements to make PANDORA a pan-allele framework and improved the user interface and software quality. Its computational efficiency allows enriching the wealth of pMHC binding affinity and mass spectrometry data with 3D models. These models can be used as a starting point for molecular dynamics simulations or structure-boosted deep learning algorithms to identify MHC-binding peptides. PANDORA is available as a Python package through Conda or as a source installation at https://github.com/X-lab-3D/PANDORA.

Genome-Wide Identification and Expression Analysis of the Copper Transporter (COPT/Ctr) Gene Family in Kandelia obovata, a Typical Mangrove Plant.

The copper transporter (COPT/Ctr) gene family plays a critical part in maintaining the balance of the metal, and many diverse species depend on COPT to move copper (Cu) across the cell membrane. In Arabidopsis thaliana, Oryza sativa, Medicago sativa, Zea mays, Populus trichocarpa, Vitis vinifera, and Solanum lycopersicum, a genome-wide study of the COPT protein family was performed. To understand the major roles of the COPT gene family in Kandelia obovata (Ko), a genome-wide study identified four COPT genes in the Kandelia obovata genome for the first time. The domain and 3D structural variation, phylogenetic tree, chromosomal distributions, gene structure, motif analysis, subcellular localization, cis-regulatory elements, synteny and duplication analysis, and expression profiles in leaves and Cu were all investigated in this research. Structural and sequence investigations show that most KoCOPTs have three transmembrane domains (TMDs). According to phylogenetic research, these KoCOPTs might be divided into two subgroups, just like Populus trichocarpa. KoCOPT gene segmental duplications and positive selection pressure were discovered by universal analysis. According to gene structure and motif analysis, most KoCOPT genes showed consistent exon-intron and motif organization within the same group. In addition, we found five hormones and four stress- and seven light-responsive cis-elements in the KoCOPTs promoters. The expression studies revealed that all four genes changed their expression levels in response to copper (CuCl2) treatments. In summary, our study offers a thorough overview of the Kandelia obovata COPT gene family's expression pattern and functional diversity, making it easier to characterize each KoCOPT gene's function in the future.

On-Demand Tunability of Microphase Separation Structure of 3D Printing Material by Reversible Addition/Fragmentation Chain Transfer Polymerization.

Controlling the phase-separated structure of polymer alloys is a promising method for tailoring the properties of polymers. However, controlling the morphology of phase-separated structures is challenging. Recently, phase-separated structures have been fabricated via 3D printing; however, only a few methods that enable on-demand control of phase separation have been reported. In this study, laser-scanning stereolithography, a vat photopolymerization method, is used to form a phase-separated structure via polymerization-induced microphase separation by varying the scanning speed and using macro-reversible addition/fragmentation chain transfer (macro-RAFT) agents with different average molar masses, along with multiarmed macro-RAFT agents; such structures were used to fabricate 3D-printed parts. Various phase-separated morphologies including sea-island and reverse sea-island were achieved by controlling the laser scanning speed and RAFT type. Heterogeneous structures with different material properties were also achieved by simply changing the laser scanning speed. As the deformation due to shrinkage in the process of cleaning 3D-printed parts depends on the laser scanning speed, shape correction was introduced to suppress the effect of shrinkage and obtain the desired shape.

Using PlaPPISite to Predict and Analyze Plant Protein-Protein Interaction Sites.

Proteome-wide characterization of protein-protein interactions (PPIs) is crucial to understand the functional roles of protein machinery within cells systematically. With the accumulation of PPI data in different plants, the interaction details of binary PPIs, such as the three-dimensional (3D) structural contexts of interaction sites/interfaces, are urgently demanded. To meet this requirement, we have developed a comprehensive and easy-to-use database called PlaPPISite ( http://zzdlab.com/plappisite/index.php ) to present interaction details for 13 plant interactomes. Here, we provide a clear guide on how to search and view protein interaction details through the PlaPPISite database. Firstly, the running environment of our database is introduced. Secondly, the input file format is briefly introduced. Moreover, we discussed which information related to interaction sites can be achieved through several examples. In addition, some notes about PlaPPISite are also provided. More importantly, we would like to emphasize the importance of interaction site information in plant systems biology through this user guide of PlaPPISite. In particular, the easily accessible 3D structures of PPIs in the coming post-AlphaFold2 era will definitely boost the application of plant interactome to decipher the molecular mechanisms of many fundamental biological issues.

3D structures of the Plasmodium vivax subtilisin-like drug target SUB1 reveal conformational changes to accommodate a substrate-derived α-ketoamide inhibitor.

The constant selection and propagation of multi-resistant Plasmodium sp. parasites require the identification of new antimalarial candidates involved in as-yet untargeted metabolic pathways. Subtilisin-like protease 1 (SUB1) belongs to a new generation of drug targets because it plays a crucial role during egress of the parasite from infected host cells at different stages of its life cycle. SUB1 is characterized by an unusual pro-region that tightly interacts with its cognate catalytic domain, thus precluding 3D structural analysis of enzyme-inhibitor complexes. In the present study, to overcome this limitation, stringent ionic conditions and controlled proteolysis of recombinant full-length P. vivax SUB1 were used to obtain crystals of an active and stable catalytic domain (PvS1Cat) without a pro-region. High-resolution 3D structures of PvS1Cat, alone and in complex with an α-ketoamide substrate-derived inhibitor (MAM-117), showed that, as expected, the catalytic serine of SUB1 formed a covalent bond with the α-keto group of the inhibitor. A network of hydrogen bonds and hydrophobic interactions stabilized the complex, including at the P1' and P2' positions of the inhibitor, although P' residues are usually less important in defining the substrate specificity of subtilisins. Moreover, when associated with a substrate-derived peptidomimetic inhibitor, the catalytic groove of SUB1 underwent significant structural changes, particularly in its S4 pocket. These findings pave the way for future strategies for the design of optimized SUB1-specific inhibitors that may define a novel class of antimalarial candidates.

Computational Modeling of DNA 3D Structures: From Dynamics and Mechanics to Folding.

DNA carries the genetic information required for the synthesis of RNA and proteins and plays an important role in many processes of biological development. Understanding the three-dimensional (3D) structures and dynamics of DNA is crucial for understanding their biological functions and guiding the development of novel materials. In this review, we discuss the recent advancements in computer methods for studying DNA 3D structures. This includes molecular dynamics simulations to analyze DNA dynamics, flexibility, and ion binding. We also explore various coarse-grained models used for DNA structure prediction or folding, along with fragment assembly methods for constructing DNA 3D structures. Furthermore, we also discuss the advantages and disadvantages of these methods and highlight their differences.

Use of 4-D proteomics to differentiate between bovine and camel lactoferrin.

Lactoferrin is a multifunctional protein that has various biological activities and applications. However, different sources of lactoferrin may have different properties and characteristics. In this study, we hypothesized that ultra-performance liquid chromatography quadrupole time-of-flight mass spectroscopy (UPLC-QTOF-IMS) coupled with UNIFI software can differentiate bovine lactoferrin from camel lactoferrin based on the unique peptides produced by trypsin digestion. We enzymatically digested the proteins using trypsin and analyzed the resulting peptides using Uniport software and in silico digestion. We identified 14 marker peptides that were unique to bovine lactoferrin and could be used to distinguish it from camel lactoferrin. We also demonstrated the advantages of 4D proteomics over 3D proteomics in separating and identifying peptides based on their mass, retention time, intensity, and ion mobility. This method can be applied to other lactoferrin sources and improve the quality control and authentication of lactoferrin products.

Assessment of Covalently Binding Warhead Compounds in the Validation of the Cytomegalovirus Nuclear Egress Complex as an Antiviral Target.

Herpesviral nuclear egress is a regulated process of viral capsid nucleocytoplasmic release. Due to the large capsid size, a regular transport via the nuclear pores is unfeasible, so that a multistage-regulated export pathway through the nuclear lamina and both leaflets of the nuclear membrane has evolved. This process involves regulatory proteins, which support the local distortion of the nuclear envelope. For human cytomegalovirus (HCMV), the nuclear egress complex (NEC) is determined by the pUL50-pUL53 core that initiates multicomponent assembly with NEC-associated proteins and capsids. The transmembrane NEC protein pUL50 serves as a multi-interacting determinant that recruits regulatory proteins by direct and indirect contacts. The nucleoplasmic core NEC component pUL53 is strictly associated with pUL50 in a structurally defined hook-into-groove complex and is considered as the potential capsid-binding factor. Recently, we validated the concept of blocking the pUL50-pUL53 interaction by small molecules as well as cell-penetrating peptides or an overexpression of hook-like constructs, which can lead to a pronounced degree of antiviral activity. In this study, we extended this strategy by utilizing covalently binding warhead compounds, originally designed as binders of distinct cysteine residues in target proteins, such as regulatory kinases. Here, we addressed the possibility that warheads may likewise target viral NEC proteins, building on our previous crystallization-based structural analyses that revealed distinct cysteine residues in positions exposed from the hook-into-groove binding surface. To this end, the antiviral and NEC-binding properties of a selection of 21 warhead compounds were investigated. The combined findings are as follows: (i) warhead compounds exhibited a pronounced anti-HCMV potential in cell-culture-based infection models; (ii) computational analysis of NEC primary sequences and 3D structures revealed cysteine residues exposed to the hook-into-groove interaction surface; (iii) several of the active hit compounds exhibited NEC-blocking activity, as shown at the single-cell level by confocal imaging; (iv) the clinically approved warhead drug ibrutinib exerted a strong inhibitory impact on the pUL50-pUL53 core NEC interaction, as demonstrated by the NanoBiT assay system; and (v) the generation of recombinant HCMV ∆UL50-ΣUL53, allowing the assessment of viral replication under conditional expression of the viral core NEC proteins, was used for characterizing viral replication and a mechanistic evaluation of ibrutinib antiviral efficacy. Combined, the results point to a rate-limiting importance of the HCMV core NEC for viral replication and to the option of exploiting this determinant by the targeting of covalently NEC-binding warhead compounds.

All-In-One Evaporators for Efficient Solar-Driven Simultaneous Collection of Water and Electricity.

The shortage of fossil fuels and freshwater resources has become a serious global issue. Using solar energy to extract clean water with a photothermal conversion technology is a green and sustainable desalination method. Integrated electricity generation during the desalination process maximizes energy utilization efficiency. Herein, a solar-driven steam and electricity generation (SSEG) system based on an all-in-one evaporator is prepared via a scalable technology. Carbon black is selected as the absorber for solar energy harvesting as well as the functional substance for simultaneous electricity generation. Fabric substrate with flexible structure, porous channel, and capillary effect is vital for directional brine supply, multiple solar absorption, and thermal management. The high evaporation rate (1.87 kg m-2  h-1 ) and voltage output (324 mV) can be achieved with an all-in-one device. The stable electricity output can be maintained over 40000 s. The SSEG performance remains constant after 15 operation cycles or 20 wash cycles. The integrated device balances excellent effectiveness and practicality, providing a viable path for clean desalination and electricity generation.

Omics-assisted characterization of two-component system genes from Gossypium Raimondii in response to salinity and molecular interaction with abscisic acid.

The two-component system (TCS) genes are involved in a wide range of physiological processes in prokaryotes and eukaryotes. In plants, the TCS elements help in a variety of functions, including cell proliferation, response to abiotic and biotic stresses, leaf senescence, nutritional signaling, and division of chloroplasts. Three different kinds of proteins make up the TCS system in plants. These are known as HKs (histidine kinases), HPs (histidine phosphotransfer), and RRs (response regulators). We investigated the genome of Gossypium raimondii and discovered a total of 59 GrTCS candidates, which include 23 members of the HK family, 8 members of the HP family, and 28 members of the RR family. RR candidates are further classified as type-A (6 members), type-B (11 members), type-C (2 members), and pseudo-RRs (9 members). The GrTCS genes were analyzed in comparison with the TCS components of other plant species such as Arabidopsis thaliana, Cicer arietinum, Sorghum bicolor, Glycine max, and Oryza sativa. This analysis revealed both conservation and changes in their structures. We identified 5 pairs of GrTCS syntenic homologs in the G. raimondii genome. All 59 TCS genes in G. raimondii are located on all thirteen chromosomes. The GrTCS promoter regions have several cis-regulatory elements, which function as switches and respond to a wide variety of abiotic stresses. RNA-seq and real-time qPCR analysis showed that the majority of GrTCS genes are differentially regulated in response to salt and cold stress. 3D structures of GrTCS proteins were predicted to reveal the specific function. GrTCSs were docked with abscisic acid to assess their binding interactions. This research establishes the groundwork for future functional studies of TCS elements in G. raimondii, which will further focus on stress resistance and overall development.

Algorithmic Graph Theory, Reinforcement Learning and Game Theory in MD Simulations: From 3D Structures to Topological 2D-Molecular Graphs (2D-MolGraphs) and Vice Versa.

This paper reviews graph-theory-based methods that were recently developed in our group for post-processing molecular dynamics trajectories. We show that the use of algorithmic graph theory not only provides a direct and fast methodology to identify conformers sampled over time but also allows to follow the interconversions between the conformers through graphs of transitions in time. Examples of gas phase molecules and inhomogeneous aqueous solid interfaces are presented to demonstrate the power of topological 2D graphs and their versatility for post-processing molecular dynamics trajectories. An even more complex challenge is to predict 3D structures from topological 2D graphs. Our first attempts to tackle such a challenge are presented with the development of game theory and reinforcement learning methods for predicting the 3D structure of a gas-phase peptide.

Structural Strategies for Supramolecular Hydrogels and Their Applications.

Supramolecular structures are of great interest due to their applicability in various scientific and industrial fields. The sensible definition of supramolecular molecules is being set by investigators who, because of the different sensitivities of their methods and observational timescales, may have different views on as to what constitutes these supramolecular structures. Furthermore, diverse polymers have been found to offer unique avenues for multifunctional systems with properties in industrial medicine applications. Aspects of this review provide different conceptual strategies to address the molecular design, properties, and potential applications of self-assembly materials and the use of metal coordination as a feasible and useful strategy for constructing complex supramolecular structures. This review also addresses systems that are based on hydrogel chemistry and the enormous opportunities to design specific structures for applications that demand enormous specificity. According to the current research status on supramolecular hydrogels, the central ideas in the present review are classic topics that, however, are and will be of great importance, especially the hydrogels that have substantial potential applications in drug delivery systems, ophthalmic products, adhesive hydrogels, and electrically conductive hydrogels. The potential interest shown in the technology involving supramolecular hydrogels is clear from what we can retrieve from the Web of Science.

Self-Powered Wireless Flexible Ionogel Wearable Devices.

Ionogels are promising soft materials for flexible wearable devices because of their unique features such as ionic conductivity and thermal stability. Ionogels reported to date show excellent sensing sensitivity; however, they suffer from a complicated external power supply. Herein, we report a self-powered wearable device based on an ionogel incorporating poly(vinylidene fluoride) (PVDF). The three-dimensional (3D) printed PVDF-ionogel exhibits amazing stretchability (1500%), high conductivity (0.36 S/m at 105 Hz), and an extremely low glass transition temperature (-84 °C). Moreover, the flexible wearable devices assembled from the PVDF-ionogel can precisely detect physiological signals (e.g., wrist, gesture, running, etc.) with a self-powered supply. Most significantly, a self-powered wireless flexible wearable device based on our PVDF-ionogel achieves monitoring healthcare of a human by transmitting obtained signals with a Bluetooth module timely and accurately. This work provides a facile and efficient method for fabricating cost-effective wireless wearable devices with a self-powered supply, enabling their potential applications for healthcare, motion detection, human-machine interfaces, etc.

Systematic analyses of the sequence conservation and ligand interaction patterns of purinergic P1 and P2Y receptors provide a structural basis for receptor selectivity.

Purinergic receptors are membrane proteins that regulate numerous cellular functions by catalyzing reactions involving purine nucleotides or nucleosides. Among the three receptor families, i.e., P1, P2X, and P2Y, the P1 and P2Y receptors share common structural features of class A GPCR. Comprehensive sequence and structural analysis revealed that the P1 and P2Y receptors belong to two distinct groups. They exhibit different ligand-binding site features that can distinguish between specific activators. These specific amino acid residues in the binding cavity may be involved in the selectivity and unique pharmacological behavior of each subtype. In this study, we conducted a structure-based analysis of purinergic P1 and P2Y receptors to identify their evolutionary signature and obtain structural insights into ligand recognition and selectivity. The structural features of the P1 and P2Y receptor classes were compared based on sequence conservation and ligand interaction patterns. Orthologous protein sequences were collected for the P1 and P2Y receptors, and sequence conservation was calculated based on Shannon entropy to identify highly conserved residues. To analyze the ligand interaction patterns, we performed docking studies on the P1 and P2Y receptors using known ligand information extracted from the ChEMBL database. We analyzed how the conserved residues are related to ligand-binding sites and how the key interacting residues differ between P1 and P2Y receptors, or between agonists and antagonists. We extracted new similarities and differences between the receptor subtypes, and the results can be used for designing new ligands by predicting hotspot residues that are important for functional selectivity.