DNA binding analysis of rare variants in homeodomains reveals homeodomain specificity-determining residues.

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and are the TF structural class with the largest number of disease-associated mutations in the Human Gene Mutation Database (HGMD). Despite numerous structural studies and large-scale analyses of HD DNA binding specificity, HD-DNA recognition is still not fully understood. Here, we analyze 92 human HD mutants, including disease-associated variants and variants of uncertain significance (VUS), for their effects on DNA binding activity. Many of the variants alter DNA binding affinity and/or specificity. Detailed biochemical analysis and structural modeling identifies 14 previously unknown specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibits different effects on DNA binding activity. Variant effect prediction tools perform moderately well in distinguishing variants with altered DNA binding affinity, but poorly in identifying those with altered binding specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and the development of clinical diagnostics and precision therapies.

Determining Protein Structures Using X-Ray Crystallography.

X-ray crystallography is a robust and widely used technique that facilitates the three-dimensional structure determination of proteins at an atomic scale. This methodology entails the growth of protein crystals under controlled conditions followed by their exposure to X-ray beams and the subsequent analysis of the resulting diffraction patterns via computational tools to determine the three-dimensional architecture of the protein. However, achieving high-resolution structures through X-ray crystallography can be quite challenging due to complexities associated with protein purity, crystallization efficiency, and crystal quality.In this chapter, we provide a detailed overview of the gene to structure determination pipeline used in X-ray crystallography, a crucial tool for understanding protein structures. The chapter covers the steps in protein crystallization, along with the processes of data collection, processing, structure determination, and refinement. The most commonly faced challenges throughout this procedure are also addressed. Finally, the importance of standardized protocols for reproducibility and accuracy is emphasized, as they are crucial for advancing the understanding of protein structure and function.

Capture-and-release of a sulfoquinovose-binding protein on sulfoquinovose-modified agarose.

The solute-binding protein (SBP) components of periplasmic binding protein-dependent ATP-binding cassette (ABC)-type transporters often possess exquisite selectivity for their cognate ligands. Maltose binding protein (MBP), the best studied of these SBPs, has been extensively used as a fusion partner to enable the affinity purification of recombinant proteins. However, other SBPs and SBP-ligand based affinity systems remain underexplored. The sulfoquinovose-binding protein SmoF, is a substrate-binding protein component of the ABC transporter cassette in Agrobacterium tumefaciens involved in importing sulfoquinovose (SQ) and its derivatives for SQ catabolism. Here, we show that SmoF binds with high affinity to the octyl glycoside of SQ (octyl-SQ), demonstrating remarkable tolerance to extension of the anomeric substituent. The 3D X-ray structure of the SmoF·octyl-SQ complex reveals accommodation of the octyl chain, which projects to the protein surface, providing impetus for the synthesis of a linker-equipped SQ-amine using a thiol-ene reaction as a key step, and its conjugation to cyanogen bromide modified agarose. We demonstrate the successful capture and release of SmoF from SQ-agarose resin using SQ as competitive eluant, and selectivity for release versus other organosulfonates. We show that SmoF can be captured and purified from a cell lysate, demonstrating the utility of SQ-agarose in capturing SQ binding proteins from complex mixtures. The present work provides a pathway for development of 'capture-and-release' affinity resins for the discovery and study of SBPs.

Synthetic access to diverse thiazetidines via a one-pot microwave assisted telescopic approach and their interaction with biomolecules.

A one-pot microwave assisted telescopic approach is reported for the chemo-selective synthesis of substituted 1,3-thiazetidines using readily available 2-aminopyridines/pyrazines/pyrimidine, substituted isothiocyanates and 1,2-dihalomethanes. The procedure involves thiourea formation from 2-aminopyridines/pyrazines/pyrimidine with the substituted isothiocyanates followed by a base catalysed nucleophilic attack of the CS bond on the 1,2-dihalomethane. Subsequently, a cyclization reaction occurs to yield substituted 1,3-thiazetidines. These four membered strained ring systems are reported to possess broad substrate scope with high functional group tolerance. The above synthetic sequence for the formation of four membered heterocycles is proven to be a modular and straightforward approach. Further the mechanistic pathway for the formation of 1,3-thiazetidines was supported by computational evaluations and X-ray crystallography analyses. The relevance of these thiazetidines in biological applications is evaluated by studying their ability to bind bio-macromolecules like proteins and nucleic acids.

NMR characterization of RNA binding property of the DEAD-box RNA helicase DDX3X and its implications for helicase activity.

The DEAD-box RNA helicase (DDX) plays a central role in many aspects of RNA metabolism by remodeling the defined structure of RNA molecules. While a number of structural studies have revealed the atomistic details of the interaction between DDX and RNA ligands, the molecular mechanism of how this molecule unwinds a structured RNA into an unstructured single-stranded RNA (ssRNA) has largely remained elusive. This is due to challenges in structurally characterizing the unwinding intermediate state and the lack of thermodynamic details underlying this process. In this study, we use solution nuclear magnetic resonance (NMR) spectroscopy to characterize the interaction of human DDX3X, a member of the DDX family, with various RNA ligands. Our results show that the inherent binding affinity of DDX3X for ssRNA is significantly higher than that for structured RNA elements. This preferential binding, accompanied by the formation of a domain-closed conformation in complex with ssRNA, effectively stabilizes the denatured ssRNA state and thus underlies the unwinding activity of DDX3X. Our results provide a thermodynamic and structural basis for the DDX function, whereby DDX can recognize and remodel a distinct set of structured RNAs to participate in a wide range of physiological processes.

Modeling Zinc Complexes Using Neural Networks.

Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build potential energy surfaces and explore chemical space. However, most of this work has focused on organic molecules due to the simplicity of their electronic structures as well as the availability of data sets. In this work, we build a deep learning architecture to model the energetics of zinc organometallic complexes. To achieve this, we have compiled a configurationally and conformationally diverse data set of zinc complexes using metadynamics to overcome the limitations of traditional sampling methods. In terms of the neural network potentials, our results indicate that for zinc complexes, partial charges play an important role in modeling the long-range interactions with a neural network. Our developed model outperforms semiempirical methods in predicting the relative energy of zinc conformers, yielding a mean absolute error (MAE) of 1.32 kcal/mol with reference to the double-hybrid PWPB95 method.

High Charge Density in Peptide Dendrimers is Required to Destabilize Membranes: Insights into Endosome Evasion.

Peptide dendrimers are a type of branched, symmetric, and topologically well-defined molecule that have already been used as delivery systems for nucleic acid transfection. Several of the most promising sequences showed high efficiency in many key steps of transfection, namely, binding siRNA, entering cells, and evading the endosome. However, small changes to the peptide dendrimers, such as in the hydrophobic core, the amino acid chirality, or the total available charges, led to significantly different experimental results with unclear mechanistic insights. In this work, we built a computational model of several of those peptide dendrimers (MH18, MH13, and MH47) and some of their variants to study the molecular details of the structure and function of these molecules. We performed CpHMD simulations in the aqueous phase and in interaction with a lipid bilayer to assess how conformation and protonation are affected by pH in different environments. We found that while the different peptide dendrimer sequences lead to no substantial structural differences in the aqueous phase, the total charge and, more importantly, the total charge density are key for the capacity of the dendrimer to interact and destabilize the membrane. These dendrimers become highly charged when the pH changes from 7.5 to 4.5, and the presence of a high charge density, which is decreased for MH47 that has four fewer titratable lysines, is essential to trigger membrane destabilization. These findings are in excellent agreement with the experimental data and help us to understand the high efficiency of some dendrimers and why the dendrimer MH47 is unable to complete the transfection process. This evidence provides further understanding of the mode of action of these peptide dendrimers and will be pivotal for the future design of new sequences with improved transfection capabilities.

Emergence of fractal geometries in the evolution of a metabolic enzyme.

Fractals are patterns that are self-similar across multiple length-scales1. Macroscopic fractals are common in nature2-4; however, so far, molecular assembly into fractals is restricted to synthetic systems5-12. Here we report the discovery of a natural protein, citrate synthase from the cyanobacterium Synechococcus elongatus, which self-assembles into Sierpinski triangles. Using cryo-electron microscopy, we reveal how the fractal assembles from a hexameric building block. Although different stimuli modulate the formation of fractal complexes and these complexes can regulate the enzymatic activity of citrate synthase in vitro, the fractal may not serve a physiological function in vivo. We use ancestral sequence reconstruction to retrace how the citrate synthase fractal evolved from non-fractal precursors, and the results suggest it may have emerged as a harmless evolutionary accident. Our findings expand the space of possible protein complexes and demonstrate that intricate and regulatable assemblies can evolve in a single substitution.

Structure-Based Protein Assembly Simulations Including Various Binding Sites and Conformations.

Many biological functions are mediated by large complexes formed by multiple proteins and other cellular macromolecules. Recent progress in experimental structure determination, as well as in integrative modeling and protein structure prediction using deep learning approaches, has resulted in a rapid increase in the number of solved multiprotein assemblies. However, the assembly process of large complexes from their components is much less well-studied. We introduce a rapid computational structure-based (SB) model, GoCa, that allows to follow the assembly process of large multiprotein complexes based on a known native structure. Beyond existing SB Go̅-type models, it distinguishes between intra- and intersubunit interactions, allowing us to include coupled folding and binding. It accounts automatically for the permutation of identical subunits in a complex and allows the definition of multiple minima (native) structures in the case of proteins that undergo global transitions during assembly. The model is successfully tested on several multiprotein complexes. The source code of the GoCa program including a tutorial is publicly available on Github: https://github.com/ZachariasLab/GoCa. We also provide a web source that allows users to quickly generate the necessary input files for a GoCa simulation: https://goca.t38webservices.nat.tum.de.

Structural studies of a serum amyloid A octamer that is primed to scaffold lipid nanodiscs.

Serum amyloid A (SAA) is a highly conserved acute-phase protein that plays roles in activating multiple pro-inflammatory pathways during the acute inflammatory response and is commonly used as a biomarker of inflammation. It has been linked to beneficial roles in tissue repair through improved clearance of lipids and cholesterol from sites of damage. In patients with chronic inflammatory diseases, elevated levels of SAA may contribute to increased severity of the underlying condition. The majority of circulating SAA is bound to lipoproteins, primarily high-density lipoprotein (HDL). Interaction with HDL not only stabilizes SAA but also alters its functional properties, likely through altered accessibility of protein-protein interaction sites on SAA. While high-resolution structures for lipid-free, or apo-, forms of SAA have been reported, their relationship with the HDL-bound form of the protein, and with other possible mechanisms of SAA binding to lipids, has not been established. Here, we have used multiple biophysical techniques, including SAXS, TEM, SEC-MALS, native gel electrophoresis, glutaraldehyde crosslinking, and trypsin digestion to characterize the lipid-free and lipid-bound forms of SAA. The SAXS and TEM data show the presence of soluble octamers of SAA with structural similarity to the ring-like structures reported for lipid-free ApoA-I. These SAA octamers represent a previously uncharacterized structure for lipid-free SAA and are capable of scaffolding lipid nanodiscs with similar morphology to those formed by ApoA-I. The SAA-lipid nanodiscs contain four SAA molecules and have similar exterior dimensions as the lipid-free SAA octamer, suggesting that relatively few conformational rearrangements may be required to allow SAA interactions with lipid-containing particles such as HDL. This study suggests a new model for SAA-lipid interactions and provides new insight into how SAA might stabilize protein-lipid nanodiscs or even replace ApoA-I as a scaffold for HDL particles during inflammation.

Structural insights into the potential binding sites of Cathepsin D using molecular modelling techniques.

Alzheimer's disease (AD) is the most prevalent type of dementia caused by the accumulation of amyloid beta (Aß) peptides. The extracellular deposition of Aß peptides in human AD brain causes neuronal death. Therefore, it has been found that Aß peptide degradation is a possible therapeutic target for AD. CathD has been known to breakdown amyloid beta peptides. However, the structural role of CathD is not yet clear. Hence, for the purpose of gaining a deeper comprehension of the structure of CathD, the present computational investigation was performed using virtual screening technique to predict CathD's active site residues and substrate binding mode. Ligand-based virtual screening was implemented on small molecules from ZINC database against crystal structure of CathD. Further, molecular docking was utilised to investigate the binding mechanism of CathD with substrates and virtually screened inhibitors. Localised compounds obtained through screening performed by PyRx and AutoDock 4.2 with CathD receptor and the compounds having highest binding affinities were picked as; ZINC00601317, ZINC04214975 and ZINCC12500925 as our top choices. The hydrophobic residues Viz. Gly35, Val31, Thr34, Gly128, Ile124 and Ala13 help stabilising the CathD-ligand complexes, which in turn emphasises substrate and inhibitor selectivity. Further, MM-GBSA approach has been used to calculate binding free energy between CathD and selected compounds. Therefore, it would be beneficial to understand the active site pocket of CathD with the assistance of these discoveries. Thus, the present study would be helpful to identify active site pocket of CathD, which could be beneficial to develop novel therapeutic strategies for the AD.

Structural insights into the GTP-driven monomerization and activation of a bacterial LRRK2 homolog using allosteric nanobodies.

Roco proteins entered the limelight after mutations in human LRRK2 were identified as a major cause of familial Parkinson's disease. LRRK2 is a large and complex protein combining a GTPase and protein kinase activity, and disease mutations increase the kinase activity, while presumably decreasing the GTPase activity. Although a cross-communication between both catalytic activities has been suggested, the underlying mechanisms and the regulatory role of the GTPase domain remain unknown. Several structures of LRRK2 have been reported, but structures of Roco proteins in their activated GTP-bound state are lacking. Here, we use single-particle cryo-electron microscopy to solve the structure of a bacterial Roco protein (CtRoco) in its GTP-bound state, aided by two conformation-specific nanobodies: NbRoco1 and NbRoco2. This structure presents CtRoco in an active monomeric state, featuring a very large GTP-induced conformational change using the LRR-Roc linker as a hinge. Furthermore, this structure shows how NbRoco1 and NbRoco2 collaborate to activate CtRoco in an allosteric way. Altogether, our data provide important new insights into the activation mechanism of Roco proteins, with relevance to LRRK2 regulation, and suggest new routes for the allosteric modulation of their GTPase activity.

Exploring nonlinear optical properties in a hybrid dihydrogen phosphate system: an experimental and theoretical approach.

CONTEXT: The controlled slow evaporation process conducted at room temperature has produced a novel hybrid material denoted as (2-hydroxyethyl) trimethylammonium dihydrogen phosphate [2-HDETDHP] (C5H14NO+, H2PO4-), synthesized through the solution growth method. X-ray crystallography analysis reveals a triclinic structure with a filling rate of P and a Z value of 2. This hybrid material displays noteworthy absorption characteristics in the middle and far ultraviolet regions. UV-visible spectroscopy further establishes its transparency in the visible and near-visible ultraviolet domains. FT-IR spectroscopy examines various vibration modes, elucidating their relationships with the functional groups within the structure. Two- and three-dimensional fingerprint maps, coupled with three-dimensional crystal structures through Hirshfeld Surface Analysis, unveil the dominance of O•••H and H•••H interactions in the structure, comprising 49.40% and 50.40%, respectively. Fingerprint plots derived from the Hirshfeld surface assess the percentages of hydrogen bonding interactions, with 80.6% attributed to a fragment patch. The experiment of antimicrobial efficacy of a synthesized product, conducted in triplicate, demonstrated the synthesized product's potential antimicrobial activity. METHODS: Hirshfeld surfaces are employed to investigate intermolecular hydrogen bonding, specifically within single phosphate groups. The molecular structure of 2-HDETDHP was refined using single-crystal X-ray analysis, while its optical characteristics were examined through UV-visible spectroscopy. FT-IR spectroscopy is employed for the assignment of molecular vibrations of functional groups in the affined structure. Quantum calculations were executed with the GAUSSIAN 09 software package at B3LYP/6-311G level of theory, to optimize the molecular geometries. The antimicrobial efficacy of a synthesized product was evaluated using the disc diffusion method against antibiotic-resistant Candida albicans, Candida tropicalis, Aspergillus niger, Staphylococcus aureus, and Escherichia coli. Microorganisms were cultured on nutrient agar, and inhibition zones were measured after incubation, with streptomycin and amphotericin as positive controls.

Mechanical activation opens a lipid-lined pore in OSCA ion channels.

OSCA/TMEM63 channels are the largest known family of mechanosensitive channels1-3, playing critical roles in plant4-7 and mammalian8,9 mechanotransduction. Here we determined 44 cryogenic electron microscopy structures of OSCA/TMEM63 channels in different environments to investigate the molecular basis of OSCA/TMEM63 channel mechanosensitivity. In nanodiscs, we mimicked increased membrane tension and observed a dilated pore with membrane access in one of the OSCA1.2 subunits. In liposomes, we captured the fully open structure of OSCA1.2 in the inside-in orientation, in which the pore shows a large lateral opening to the membrane. Unusually for ion channels, structural, functional and computational evidence supports the existence of a 'proteo-lipidic pore' in which lipids act as a wall of the ion permeation pathway. In the less tension-sensitive homologue OSCA3.1, we identified an 'interlocking' lipid tightly bound in the central cleft, keeping the channel closed. Mutation of the lipid-coordinating residues induced OSCA3.1 activation, revealing a conserved open conformation of OSCA channels. Our structures provide a global picture of the OSCA channel gating cycle, uncover the importance of bound lipids and show that each subunit can open independently. This expands both our understanding of channel-mediated mechanotransduction and channel pore formation, with important mechanistic implications for the TMEM16 and TMC protein families.

Molecular insights into capsular polysaccharide secretion.

Capsular polysaccharides (CPSs) fortify the cell boundaries of many commensal and pathogenic bacteria1. Through the ABC-transporter-dependent biosynthesis pathway, CPSs are synthesized intracellularly on a lipid anchor and secreted across the cell envelope by the KpsMT ABC transporter associated with the KpsE and KpsD subunits1,2. Here we use structural and functional studies to uncover crucial steps of CPS secretion in Gram-negative bacteria. We show that KpsMT has broad substrate specificity and is sufficient for the translocation of CPSs across the inner bacterial membrane, and we determine the cell surface organization and localization of CPSs using super-resolution fluorescence microscopy. Cryo-electron microscopy analyses of the KpsMT-KpsE complex in six different states reveal a KpsE-encaged ABC transporter, rigid-body conformational rearrangements of KpsMT during ATP hydrolysis and recognition of a glycolipid inside a membrane-exposed electropositive canyon. In vivo CPS secretion assays underscore the functional importance of canyon-lining basic residues. Combined, our analyses suggest a molecular model of CPS secretion by ABC transporters.

ALDELE: All-Purpose Deep Learning Toolkits for Predicting the Biocatalytic Activities of Enzymes.

Rapidly predicting enzyme properties for catalyzing specific substrates is essential for identifying potential enzymes for industrial transformations. The demand for sustainable production of valuable industry chemicals utilizing biological resources raised a pressing need to speed up biocatalyst screening using machine learning techniques. In this research, we developed an all-purpose deep-learning-based multiple-toolkit (ALDELE) workflow for screening enzyme catalysts. ALDELE incorporates both structural and sequence representations of proteins, alongside representations of ligands by subgraphs and overall physicochemical properties. Comprehensive evaluation demonstrated that ALDELE can predict the catalytic activities of enzymes, and particularly, it identifies residue-based hotspots to guide enzyme engineering and generates substrate heat maps to explore the substrate scope for a given biocatalyst. Moreover, our models notably match empirical data, reinforcing the practicality and reliability of our approach through the alignment with confirmed mutation sites. ALDELE offers a facile and comprehensive solution by integrating different toolkits tailored for different purposes at affordable computational cost and therefore would be valuable to speed up the discovery of new functional enzymes for their exploitation by the industry.

Structural basis of ligand specificity and channel activation in an insect gustatory receptor.

Gustatory receptors (GRs) are critical for insect chemosensation and are potential targets for controlling pests and disease vectors, making their structural investigation a vital step toward such applications. We present structures of Bombyx mori Gr9 (BmGr9), a fructose-gated cation channel, in agonist-free and fructose-bound states. BmGr9 forms a tetramer similar to distantly related insect odorant receptors (ORs). Upon fructose binding, BmGr9's channel gate opens through helix S7b movements. In contrast to ORs, BmGr9's ligand-binding pocket, shaped by a kinked helix S4 and a shorter extracellular S3-S4 loop, is larger and solvent accessible in both agonist-free and fructose-bound states. Also, unlike ORs, fructose binding by BmGr9 involves helix S5 and a pocket lined with aromatic and polar residues. Structure-based sequence alignments reveal distinct patterns of ligand-binding pocket residue conservation in GR subfamilies associated with different ligand classes. These data provide insight into the molecular basis of GR ligand specificity and function.

Physicochemical properties as a function of lomefloxacin biological activity.

OBJECTIVE: Aim: The goal is to discover QSAR of Lomefloxacin as antibacterial activity. PATIENTS AND METHODS: Materials and Methods: A number of lomefloxacins analogs activities were studied by program Windows Chem SW. The analogues were obtained and energy minimization was carried out through Molecular Modeling Program, the calculations were performed using General Atomic and Molecular Electronic Structure System (GAMESS) software. RESULTS: Results: There were six descriptions (N-quinoline more (-) ev charge, Kinetic Energy, Potential Energy, Log p, Log S, F6 charge) results have highly compatible of physicochemical properties with lomefloxacin analogs activities. It can be used to estimate the activities depending on QSAR equation of lomefloxacin analogs. CONCLUSION: Conclusions: The parameters used for calculation were depending on the quantum chemical was employed in deriving from computational study of properties and can used to predict the activities of certain analogs of Lomefloxacins as antibacterial compounds.

In vitro and in silico investigation of FDA-approved drugs to be repurposed against Alzheimer's disease.

Alzheimer's disease (AD), one of the main causes of dementia, is a neurodegenerative disorder. Cholinesterase inhibitors are used in the treatment of AD, but prolonged use of these drugs can lead to serious side effects. Drug repurposing is an approach that aims to reveal the effectiveness of drugs in different diseases beyond their clinical uses. In this work, we investigated in vitro and in silico inhibitory effects of 11 different drugs on cholinesterases. The results showed that trimebutine, theophylline, and levamisole had the highest acetylcholinesterase inhibitory actions among the tested drugs, and these drugs inhibited by 68.70 ± 0.46, 53.25 ± 3.40, and 44.03 ± 1.20%, respectively at 1000 µM. In addition, these drugs are bound to acetylcholinesterase via competitive manner. Molecular modeling predicted good fitness in acetylcholinesterase active site for these drugs and possible central nervous system action for trimebutine. All of these results demonstrated that trimebutine was determined to be the drug with the highest potential for use in AD.