Differential performance of RoseTTAFold in antibody modeling.

Antibodies are essential to life, and knowing their structures can facilitate the understanding of antibody-antigen recognition mechanisms. Precise antibody structure prediction has been a core challenge for a prolonged period, especially the accuracy of H3 loop prediction. Despite recent progress, existing methods cannot achieve atomic accuracy, especially when the homologous structures required for these methods are not available. Recently, RoseTTAFold, a deep learning-based algorithm, has shown remarkable breakthroughs in predicting the 3D structures of proteins. To assess the antibody modeling ability of RoseTTAFold, we first retrieved the sequences of 30 antibodies as the test set and used RoseTTAFold to model their 3D structures. We then compared the models constructed by RoseTTAFold with those of SWISS-MODEL in a different way, in which we stratified Global Model Quality Estimate (GMQE) into three different ranges. The results indicated that RoseTTAFold could achieve results similar to SWISS-MODEL in modeling most CDR loops, especially the templates with a GMQE score under 0.8. In addition, we also compared the structures modeled by RoseTTAFold, SWISS-MODEL and ABodyBuilder. In brief, RoseTTAFold could accurately predict 3D structures of antibodies, but its accuracy was not as good as the other two methods. However, RoseTTAFold exhibited better accuracy for modeling H3 loop than ABodyBuilder and was comparable to SWISS-MODEL. Finally, we discussed the limitations and potential improvements of the current RoseTTAFold, which may help to further the accuracy of RoseTTAFold's antibody modeling.

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies.

SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.

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.

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.

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.

Assessment of the van der Waals, Hubbard U parameter and spin-orbit coupling corrections on the 2D/3D structures from metal gold congeners clusters.

The coinage-metal clusters possess a natural complexity in their theoretical treatment that may be accompanied by inherent shortcomings in the methodological approach. Herein, we performed a scalar-relativistic density functional theory study, considering Perdew, Burke, and Ernzerhof (PBE) with (empirical and semi empirical) van der Waals (vdW), spin-orbit coupling (SOC), +U (Hubbard term), and their combinations, to treat the Cu 13 , Ag 13 , and Au 13 clusters in different structural motifs. The energetic scenario is given by the confirmation of the 3D lowest energy configurations for Cu 13 and Ag 13 within all approaches, while for Au 13 there is a 2D/3D competition, depending on the applied correction. The 2D geometry is 0.43 eV more stable with plain PBE than the 3D one, the SOC, +U, and/or vdW inclusion decreases the overestimated stability of the planar configurations, where the most surprising result is found by the D3 and D3BJ vdW corrections, for which the 3D configuration is 0.29 and 0.11 eV, respectively, more stable than the 2D geometry (with even higher values when SOC and/or +U are added). The D3 dispersion correction represents 7.9% (4.4%) of the total binding energy for the 3D (2D) configuration, (not) being enough to change the sd hybridization and the position of the occupied d -states. Our predictions are in agreement with experimental results and in line with the best results obtained for bulk systems, as well as with hybrid functionals within D3 corrections. The properties description undergoes small corrections with the different approaches, where general trends are maintained, that is, the average bond length is smaller (larger) for lower (higher)-coordinated structures, since a same number of electrons are shared by a smaller (larger) number of bonds, consequently, the bonds are stronger (weaker) and shorter (longer) and the sd hybridization index is larger (smaller). Thus, Au has a distinct behavior in relation to its lighter congeners, with a complex potential energy surface, where in addition to the relevant relativistic effects, correlation and dispersion effects must also be considered.

Engineering Stress in Thin Films: An Innovative Pathway Toward 3D Micro and Nanosystems.

Transformation of conventional 2D platforms into unusual 3D configurations provides exciting opportunities for sensors, electronics, optical devices, and biological systems. Engineering material properties or controlling and modulating stresses in thin films to pop-up 3D structures out of standard planar surfaces has been a highly active research topic over the last decade. Implementation of 3D micro and nanoarchitectures enables unprecedented functionalities including multiplexed, monolithic mechanical sensors, vertical integration of electronics components, and recording of neuron activities in 3D organoids. This paper provides an overview on stress engineering approaches to developing 3D functional microsystems. The paper systematically presents the origin of stresses generated in thin films and methods to transform a 2D design into an out-of-plane configuration. Different types of 3D micro and nanostructures, along with their applications in several areas are discussed. The paper concludes with current technical challenges and potential approaches and applications of this fast-growing research direction.

On the predictibility of A-minor motifs from their local contexts.

This study investigates the importance of the structural context in the formation of a type I/II A-minor motif. This very frequent structural motif has been shown to be important in the spatial folding of RNA molecules. We developed an automated method to classify A-minor motif occurrences according to their 3D context similarities, and we used a graph approach to represent both the structural A-minor motif occurrences and their classes at different scales. This approach leads us to uncover new subclasses of A-minor motif occurrences according to their local 3D similarities. The majority of classes are composed of homologous occurrences, but some of them are composed of non-homologous occurrences. The different classifications we obtain allow us to better understand the importance of the context in the formation of A-minor motifs. In a second step, we investigate how much knowledge of the context around an A-minor motif can help to infer its presence (and position). More specifically, we want to determine what kind of information, contained in the structural context, can be useful to characterize and predict A-minor motifs. We show that, for some A-minor motifs, the topology combined with a sequence signal is sufficient to predict the presence and the position of an A-minor motif occurrence. In most other cases, these signals are not sufficient for predicting the A-minor motif, however we show that they are good signals for this purpose. All the classification and prediction pipelines rely on automated processes, for which we describe the underlying algorithms and parameters.

Analyses of Botrytis cinerea-responsive LrWRKY genes from Lilium regale reveal distinct roles of two LrWRKY transcription factors in mediating responses to B. cinerea.

KEY MESSAGE: Botrytis cinerea induced expression of 15 LrWRKY genes; overexpression of LrWRKY39 and LrWRKY41a increased resistance and susceptibility, respectively, to B. cinerea in a manner related to SA and JA signaling. WRKY transcription factors (TFs), a large family, play important roles in coping with biotic stresses. Lilium regale Wilson is a lily species with strong resistance to fungi and viruses; however, functional characterization of LrWRKY TFs remains very limited. Here, a total of 25 LrWRKY members were identified from the L. regale transcriptome, and 15 LrWRKY genes were significantly induced by Botrytis cinerea. Based on their structural features, B. cinerea-responsive LrWRKY genes could be classified into six subgroups (Groups I, IIa-d, and III), and sequence alignment showed that 12 LrWRKY proteins have a well-conserved WRKYGQK domain, while 3 LrWRKYs have a variant sequence (WRKYGKK or WRMYEQK). Quantitative RT-PCR analysis revealed tissue-specific expression of B. cinerea-responsive LrWRKY genes and their expression profiles in response to defense-related hormones salicylic acid (SA), methyl jasmonate (MeJA) and hydrogen peroxide. LrWRKY39 and LrWRKY41a, which encode two LrWRKY TFs with different three-dimensional (3D) models of the WRKY domain, were cloned, and both proteins were targeted to the nucleus. Overexpression of LrWRKY39 and LrWRKY41a in Arabidopsis thaliana increased the resistance and susceptibility to B. cinerea, respectively, compared to the wild type. Similar results were also observed in tobacco and lily (L. longiflorum 'Snow Queen') by transient transformation analyses. Their distinct roles may be related to changes in the transcript levels of SA-/JA-responsive genes. Our results provide new insights into B. cinerea-responsive LrWRKY members and the biological functions of two different 3D models of LrWRKY TFs in defense responses to B. cinerea infection.

Computational Methods for Drug Repurposing.

The wealth of knowledge and multi-omics data available in drug research has allowed the rise of several computational methods in the drug discovery field, resulting in a novel and exciting strategy called drug repurposing. Drug repurposing consists in finding new applications for existing drugs. Numerous computational methods perform a high-level integration of different knowledge sources to facilitate the discovery of unknown mechanisms. In this chapter, we present a survey of data resources and computational tools available for drug repositioning.

Harnessing the interface mechanics of hard films and soft substrates for 3D assembly by controlled buckling.

Techniques for forming sophisticated, 3D mesostructures in advanced, functional materials are of rapidly growing interest, owing to their potential uses across a broad range of fundamental and applied areas of application. Recently developed approaches to 3D assembly that rely on controlled buckling mechanics serve as versatile routes to 3D mesostructures in a diverse range of high-quality materials and length scales of relevance for 3D microsystems with unusual function and/or enhanced performance. Nonlinear buckling and delamination behaviors in materials that combine both weak and strong interfaces are foundational to the assembly process, but they can be difficult to control, especially for complex geometries. This paper presents theoretical and experimental studies of the fundamental aspects of adhesion and delamination in this context. By quantifying the effects of various essential parameters on these processes, we establish general design diagrams for different material systems, taking into account 4 dominant delamination states (wrinkling, partial delamination of the weak interface, full delamination of the weak interface, and partial delamination of the strong interface). These diagrams provide guidelines for the selection of engineering parameters that avoid interface-related failure, as demonstrated by a series of examples in 3D helical mesostructures and mesostructures that are reconfigurable based on the control of loading-path trajectories. Three-dimensional micromechanical resonators with frequencies that can be selected between 2 distinct values serve as demonstrative examples.

Cysteine 467 of the ASCT2 Amino Acid Transporter Is a Molecular Determinant of the Antiport Mechanism.

The plasma membrane transporter ASCT2 is a well-known Na+-dependent obligatory antiporter of neutral amino acids. The crucial role of the residue C467 in the recognition and binding of the ASCT2 substrate glutamine, has been highlighted by structure/function relationship studies. The reconstitution in proteoliposomes of the human ASCT2 produced in P. pastoris is here employed to unveil another role of the C467 residue in the transport reaction. Indeed, the site-directed mutant C467A displayed a novel property of the transporter, i.e., the ability of mediating a low but measurable unidirectional transport of [3H]-glutamine. This reaction conforms to the main features of the ASCT2-mediated transport, namely the Na+-dependence, the pH dependence, the stimulation by cholesterol included in the proteoliposome membrane, and the specific inhibition by other common substrates of the reconstituted human ASCT2. Interestingly, the WT protein cannot catalyze the unidirectional transport of [3H]-glutamine, demonstrating an unspecific phenomenon. This difference is in favor of a structural conformational change between a WT and C467A mutant that triggers the appearance of the unidirectional flux; this feature has been investigated by comparing the available 3D structures in two different conformations, and two homology models built on the basis of hEAAT1 and GLTPh.

Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models.

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies. Here, we introduce a computational pipeline dedicated to reference-free high-throughput comparative analysis of 3D RNA structures. We show its application in the RNA-Puzzles challenge, in which five participating groups attempted to predict the three-dimensional structures of 5'- and 3'-untranslated regions (UTRs) of the SARS-CoV-2 genome. We report the results of this puzzle and discuss the structural motifs obtained from the analysis. All simulated models and tools incorporated into the pipeline are open to scientific and academic use.

Porcine Circovirus Type 4 Strains Circulating in China Are Relatively Stable and Have Higher Homology with Mink Circovirus than Other Porcine Circovirus Types.

Porcine circovirus type 4 (PCV4) is a newly identified porcine circovirus (PCV) belonging to the Circovirus genus Circoviridae family. Although several groups have conducted epidemiological investigations on PCV4 and found that PCV4 also exists widely in pigs, there are few reports on the origin and evolution of PCV4. In this study, the genetic relationship between PCV4, mink circovirus (MiCV), bat circovirus (BtCV), PCV1, PCV2, and PCV3 was analyzed, and the consistency of viral proteins in three-dimensional (3D) structure and epitopes was predicted. We found that the genome and protein structure of PCV4 was relatively stable among current circulating PCV4 strains. Furthermore, PCV4 was more similar to MiCV in terms of its genome, protein structure, and epitope levels than other PCVs and BtCVs, suggesting that PCV4 may be derived from MiCV or have a common origin with MiCV, or mink may be an intermediate host of PCV4, which may pose a great threat to other animals and/or even human beings. Therefore, it is necessary to continuously monitor the infection and variation of PCV4, analyze the host spectrum of PCV4, and establish the prevention and treatment methods of PCV4 infection in advance.

Human-induced pluripotent stem cell-derived cardiomyocytes, 3D cardiac structures, and heart-on-a-chip as tools for drug research.

Development of new drugs is of high interest for the field of cardiac and cardiovascular diseases, which are a dominant cause of death worldwide. Before being allowed to be used and distributed, every new potentially therapeutic compound must be strictly validated during preclinical and clinical trials. The preclinical studies usually involve the in vitro and in vivo evaluation. Due to the increasing reporting of discrepancy in drug effects in animal and humans and the requirement to reduce the number of animals used in research, improvement of in vitro models based on human cells is indispensable. Primary cardiac cells are difficult to access and maintain in cell culture for extensive experiments; therefore, the human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) became an excellent alternative. This technology enables a production of high number of patient- and disease-specific cardiomyocytes and other cardiac cell types for a large-scale research. The drug effects can be extensively evaluated in the context of electrophysiological responses with a use of well-established tools, such as multielectrode array (MEA), patch clamp, or calcium ion oscillation measurements. Cardiotoxicity, which is a common reason for withdrawing drugs from marketing or rejection at final stages of clinical trials, can be easily verified with a use of hiPSC-CM model providing a prediction of human-specific responses and higher safety of clinical trials involving patient cohort. Abovementioned studies can be performed using two-dimensional cell culture providing a high-throughput and relatively lower costs. On the other hand, more complex structures, such as engineered heart tissue, organoids, or spheroids, frequently applied as co-culture systems, represent more physiological conditions and higher maturation rate of hiPSC-derived cells. Furthermore, heart-on-a-chip technology has recently become an increasingly popular tool, as it implements controllable culture conditions, application of various stimulations and continuous parameters read-out. This paper is an overview of possible use of cardiomyocytes and other cardiac cell types derived from hiPSC as in vitro models of heart in drug research area prepared on the basis of latest scientific reports and providing thorough discussion regarding their advantages and limitations.

Controlled molecular self-assembly of complex three-dimensional structures in soft materials.

Many applications in tissue engineering, flexible electronics, and soft robotics call for approaches that are capable of producing complex 3D architectures in soft materials. Here we present a method using molecular self-assembly to generate hydrogel-based 3D architectures that resembles the appealing features of the bottom-up process in morphogenesis of living tissues. Our strategy effectively utilizes the three essential components dictating living tissue morphogenesis to produce complex 3D architectures: modulation of local chemistry, material transport, and mechanics, which can be engineered by controlling the local distribution of polymerization inhibitor (i.e., oxygen), diffusion of monomers/cross-linkers through the porous structures of cross-linked polymer network, and mechanical constraints, respectively. We show that oxygen plays a role in hydrogel polymerization which is mechanistically similar to the role of growth factors in tissue growth, and the continued growth of hydrogel enabled by diffusion of monomers/cross-linkers into the porous hydrogel similar to the mechanisms of tissue growth enabled by material transport. The capability and versatility of our strategy are demonstrated through biomimetics of tissue morphogenesis for both plants and animals, and its application to generate other complex 3D architectures. Our technique opens avenues to studying many growth phenomena found in nature and generating complex 3D structures to benefit diverse applications.

PSC-db: A Structured and Searchable 3D-Database for Plant Secondary Compounds.

Plants synthesize a large number of natural products, many of which are bioactive and have practical values as well as commercial potential. To explore this vast structural diversity, we present PSC-db, a unique plant metabolite database aimed to categorize the diverse phytochemical space by providing 3D-structural information along with physicochemical and pharmaceutical properties of the most relevant natural products. PSC-db may be utilized, for example, in qualitative estimation of biological activities (Quantitative Structure-Activity Relationship, QSAR) or massive docking campaigns to identify new bioactive compounds, as well as potential binding sites in target proteins. PSC-db has been implemented using the open-source PostgreSQL database platform where all compounds with their complementary and calculated information (classification, redundant names, unique IDs, physicochemical properties, etc.) were hierarchically organized. The source organism for each compound, as well as its biological activities against protein targets, cell lines and different organism were also included. PSC-db is freely available for public use and is hosted at the Universidad de Talca.

The CYSMA web server: An example of integrative tool for in silico analysis of missense variants identified in Mendelian disorders.

Exome sequencing used for molecular diagnosis of Mendelian disorders considerably increases the number of missense variants of unclear significance, whose pathogenicity can be assessed by a variety of prediction tools. As the performance of algorithms may vary according to the datasets, complementary specific resources are needed to improve variant interpretation. As a model, we were interested in the cystic fibrosis transmembrane conductance regulator gene (CFTR) causing cystic fibrosis, in which at least 40% of missense variants are reported. Cystic fibrosis missense analysis (CYSMA) is a new web server designed for online estimation of the pathological relevance of CFTR missense variants. CYSMA generates a set of computationally derived data, ranging from evolutionary conservation to functional observations from three-dimensional structures, provides all available allelic frequencies, clinical observations, and references for functional studies. Compared to software classically used in analysis pipelines on a dataset of 141 well-characterized missense variants, CYSMA was the most efficient tool to discriminate benign missense variants, with a specificity of 85%, and very good sensitivity of 89%. These results suggest that such integrative tools could be adapted to numbers of genes involved in Mendelian disorders to improve the interpretation of missense variants identified in the context of diagnosis.

PlaPPISite: a comprehensive resource for plant protein-protein interaction sites.

BACKGROUND: Protein-protein interactions (PPIs) play very important roles in diverse biological processes. Experimentally validated or predicted PPI data have become increasingly available in diverse plant species. To further explore the biological functions of PPIs, understanding the interaction details of plant PPIs (e.g., the 3D structural contexts of interaction sites) is necessary. By integrating bioinformatics algorithms, interaction details can be annotated at different levels and then compiled into user-friendly databases. In our previous study, we developed AraPPISite, which aimed to provide interaction site information for PPIs in the model plant Arabidopsis thaliana. Considering that the application of AraPPISite is limited to one species, it is very natural that AraPPISite should be evolved into a new database that can provide interaction details of PPIs in multiple plants. DESCRIPTION: PlaPPISite (http://zzdlab.com/plappisite/index.php) is a comprehensive, high-coverage and interaction details-oriented database for 13 plant interactomes. In addition to collecting 121 experimentally verified structures of protein complexes, the complex structures of experimental/predicted PPIs in the 13 plants were also constructed, and the corresponding interaction sites were annotated. For the PPIs whose 3D structures could not be modelled, the associated domain-domain interactions (DDIs) and domain-motif interactions (DMIs) were inferred. To facilitate the reliability assessment of predicted PPIs, the source species of interolog templates, GO annotations, subcellular localizations and gene expression similarities are also provided. JavaScript packages were employed to visualize structures of protein complexes, protein interaction sites and protein interaction networks. We also developed an online tool for homology modelling and protein interaction site annotation of protein complexes. All data contained in PlaPPISite are also freely available on the Download page. CONCLUSION: PlaPPISite provides the plant research community with an easy-to-use and comprehensive data resource for the search and analysis of protein interaction details from the 13 important plant species.

Ferrimagnetic Ordering and Anomalous Stoichiometry Observed for the Cubic, Extended 3D Prussian Blue Analogues (NEt3 Me)2 MnII 5 (CN)12 and (NEt2 Me2 )2 MnII 5 (CN)12 : A Cation-Adaptive Structure.

The reactions of MnII (O2 CCH3 )2 with NEt3 Me+ CN- and NEt2 Me2 + CN- form (NEt3 Me)2 MnII 5 (CN)12 (1) and (NEt2 Me2 )2 MnII 5 (CN)12 (2), respectively. Structure model-building and Rietveld refinement of high-resolution synchrotron powder diffraction data revealed a cubic [a=24.0093 Š(1), 23.8804 Š(2)] 3D extended structural motif with adjacent tetrahedral and octahedral MnII sites in a 3:2 ratio. Each tetrahedral MnII site is surrounded by four low-spin octahedral MnII sites, and each octahedral MnII site is surrounded by six high-spin tetrahedral MnII sites; adjacent sites are antiferromagnetically coupled in 3D. Compensation does not occur, and magnetic ordering as a ferrimagnet is observed at Tc =13 K for 2 based on the temperature at which remnant magnetization, Mr (T)→0. The hysteresis has an unusual constricted shape with inflection points around 50 and 1.2 kOe with a 5 K coercivity of 16 Oe and remnant magnetization, Mr , of 2050 emuOe mol-1 . The unusual structure and stoichiometry are attributed to the very ionic nature of the high-spin N-bonded MnII ion, which enables the maximization of the attractive van der Waals interactions through minimization of void space via a reduced ∠ MnNC. This results in an additional example of the Ax MnII y (CN)x+2y (x=0, y=1; x=1, y=3; x=2, y=1; x=2, y=2; x=2, y=3; x=3, y=5; and x=4, y=1) family of compounds possessing an unprecedented stoichiometry and lattice motif that are cation adaptive structured materials.