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In this work, we report an unexplored heterostructured catalyst consisting of Ni–Co-phosphate/sulphide phases (NCPSP) on carbon fibre paper through a single-step gas–solid reaction route for hydrogen evolution reaction (HER) in an acidic medium. The heterostructured electrode film of NCPSP depicted considerably enhanced electrochemical HER performance compared to the heterostructured controlled catalyst films consisting of Ni–Co-phosphide phases (NCPP), Ni–Co-sulphide phases (NCSP), and Ni–Co-phosphate/phosphide phases (NCPPP). Electrochemical and structural characterization reveals that superior catalytic credentials of NCPSP can be attributed to kinetically favourable H binding on the sulphur sites of transition metal (TM) sulphides and their beneficial heterostructure with TM phosphate component. Specifically, the minimum overpotential of 53 mV and 97 mV is observed for cathodic HER current of 10 mA cm−2 and 100 mA cm−2, respectively. The low Tafel slope of 43 mV dec−1 reveals the favourable Volmer–Heyrovsky mechanism. Also, superior kinetics was revealed by the low charge transfer resistance of 28 Ω. The catalytic credentials of NCPSP are also well in alignment with the highest values reported for the best state of art catalysts. [ABSTRACT FROM AUTHOR]

A novel cellulose microfibril swelling (Cms) gene of Bacillus sp. AY8 was successfully cloned and sequenced using a set of primers designed based on the conserved region of the gene from the genomic database. The molecular cloning of the Cms gene revealed that the gene consisted of 679 bp sequences encoding 225 amino acids. Further in silico analysis unveiled that the Cms gene contained the NlpC/P60 conserved region that exhibited a homology of 98% with the NlpC/P60 family proteins found in both the strains, Burkholderialata sp. and Burkholderia vietnamiensis. The recombinant Cms enzyme had a significant impact on the reduction of crystallinity indices (CrI) of various substrates including a 3%, a 3.97%, a 4.66%, and a substantial 14.07% for filter paper, defatted cotton fiber, avicel, and alpha cellulose, respectively. Additionally, notable changes in the spectral features were observed among the substrates treated with recombinant Cms enzymes compared to the untreated control. Specifically, there was a decrease in band intensities within the spectral regions of 3000–3450 cm−1, 2900 cm−1, 1429 cm−1, and 1371 cm−1 for the treated filter paper, cotton fiber, avicel, and alpha cellulose, respectively. Furthermore, the recombinant Cms enzyme exhibited a maximum cellulose swelling activity at a pH of 7.0 along with a temperature of 40 °C. The molecular docking data revealed that ligand molecules, such as cellobiose, dextrin, maltose 1-phosphate, and feruloyated xyloglucan, effectively bonded to the active site of the Cms enzyme. The molecular dynamics simulations of the Cms enzyme displayed stable interactions with cellobiose and dextrin molecules up to 100 ns. It is noteworthy to mention that the conserved region of the Cms enzyme did not match with those of the bioadditives like expansins and swollenin proteins. This study is the initial report of a bacterial cellulose microfibril swellase enzyme, which could potentially serve as an additive to enhance biofuel production by releasing fermentable sugars from cellulose. [ABSTRACT FROM AUTHOR]

Protein and nucleic acid binding site prediction is a critical computational task that benefits a wide range of biological processes. Previous studies have shown that feature selection holds particular significance for this prediction task, making the generation of more discriminative features a key area of interest for many researchers. Recent progress has shown the power of protein language models in handling protein sequences, in leveraging the strengths of attention networks, and in successful applications to tasks such as protein structure prediction. This naturally raises the question of the applicability of protein language models in predicting protein and nucleic acid binding sites. Various approaches have explored this potential. This paper first describes the development of protein language models. Then, a systematic review of the latest methods for predicting protein and nucleic acid binding sites is conducted by covering benchmark sets, feature generation methods, performance comparisons, and feature ablation studies. These comparisons demonstrate the importance of protein language models for the prediction task. Finally, the paper discusses the challenges of protein and nucleic acid binding site prediction and proposes possible research directions and future trends. The purpose of this survey is to furnish researchers with actionable suggestions for comprehending the methodologies used in predicting protein–nucleic acid binding sites, fostering the creation of protein-centric language models, and tackling real-world obstacles encountered in this field. [ABSTRACT FROM AUTHOR]

Schiefer and Winfree recently introduced the chemical reaction network-controlled tile assembly model (CRN-TAM), a variant of the abstract tile assembly model (aTAM). In the CRN-TAM, tile reactions are mediated via non-local chemical signals controlled by a chemical reaction network. This paper introduces ALCH, an imperative programming language for specifying CRN-TAM programs that can be compiled and simulated. ALCH includes standard language features such as Boolean variables, conditionals, loops, and CRN-TAM-specific constructs such as adding and removing tiles. ALCH also includes the branch and parallel structures which harness the nondeterministic and parallel nature of the CRN-TAM. ALCH also supports functional tileset specification. Using ALCH, we show that the discrete Sierpinski triangle and the discrete Sierpinski carpet can be strictly self-assembled in the CRN-TAM, which shows the CRN-TAM can self-assemble infinite shapes at scale 1 that the aTAM cannot. ALCH allows us to present these constructions at a high level, abstracting species and reactions into C-like code that is simpler to understand. We employ two new CRN-TAM techniques in our constructions. First, we use ALCH's nondeterministic branching feature to probe previously placed tiles of the assembly and detect the presence and absence of tiles. Second, we use scaffolding tiles to precisely control tile placement by occluding any undesired binding sites. This paper is an extension of our previous work, updated to include a Sierpinski carpet construction and the parallel command. [ABSTRACT FROM AUTHOR]

Two novel, discrete lanthanide–macrocycle binary complexes for the detection of hydrogen sulfide are reported. The hydrogen sulfide sensing mechanism utilises the copper sequestration at a secondary binding site, with resulting bimetallic lanthanide(III)/copper(II) complexes (Ln = Eu3+ and Tb3+) exhibiting high selectivity, good sensitivity and excellent reversibility for aqueous hydrogen sulfide. The inclusion of the DO2A macrocycle and 4-(2-pyridyl)-1,2,3-triazole dipicolinic acid ligand, results in a complex with good solubility and stability. The europium(III) complex also displayed a low limit of detection (665 ppb) with a response time of 30 seconds with gaseous hydrogen sulfide. The improved water solubility and stability over a previous complex results in these sensors having the potential for use in environmental monitoring and biological studies for various functional settings. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNA) exert regulatory actions via base pairing with their binding sites on target mRNAs. Cooperative binding, i.e., synergism, among binding sites on an mRNA is biochemically well characterized. We studied whether this synergism is reflected in the global relationship between miRNA-mediated regulatory activity and miRNA binding site count on the target mRNAs, i.e., leading to a non-linear relationship between the two. Recently, using our own and public datasets, we have enquired into miRNA regulatory actions: first, we analyzed the power-law distribution pattern of miRNA binding sites; second, we found that, strikingly, mRNAs for core miRNA regulatory apparatus proteins have extraordinarily high binding site counts, forming self-feedback-control loops; third, we revealed that tumor suppressor mRNAs generally have more sites than oncogene mRNAs; and fourth, we characterized enrichment of miRNA-targeted mRNAs in translationally less active polysomes relative to more active polysomes. In these four studies, we qualitatively observed obvious positive correlation between the extent to which an mRNA is miRNA-regulated and its binding site count. This paper summarizes the datasets used. We also quantitatively analyzed the correlation by comparative linear and non-linear regression analyses. Non-linear relationships, i.e., accelerating rise of regulatory activity as binding site count increases, fit the data much better, conceivably a transcriptome-level reflection of cooperative binding among miRNA binding sites on a target mRNA. This observation is potentially a guide for integrative quantitative modeling of the miRNA regulatory system. [ABSTRACT FROM AUTHOR]

Calcium is one of the essential macro-elements in the human body. The scientific calcium supplementation is greatly significant to maintaining life and health. The peptide-calcium chelates with good calcium binding capacity and high bioavailability have attracted more attention. This work reviews the binding sites, binding modes, and intermolecular forces between calcium and peptides in peptide-calcium chelates. Compared with free calcium, chelated calcium is more easily absorbed in the intestine according to the summarization of the calcium absorption pathways. Peptide-calcium chelates, as a new generation of calcium supplements, have a rich source of raw materials, high bioavailability, good economic value, and broad development prospects. Further research is needed on the safety, physicochemical stability, digestive stability, and Ca2+ release mechanism of peptide-calcium chelates after intestinal absorption. This paper aims to provide new insight into the development of novel calcium supplements. [ABSTRACT FROM AUTHOR]

Gene expression levels in rice (Oryza sativa L.) and other plant species are determined by the promoters, which directly control phenotypic characteristics. As essential components of genes, promoters regulate the intensity, location, and timing of gene expression. They contain numerous regulatory elements and serve as binding sites for proteins that modulate transcription, including transcription factors and RNA polymerases. Genome editing can alter promoter sequences, thereby precisely modifying the expression patterns of specific genes, and ultimately affecting the morphology, quality, and resistance of rice. This paper summarizes research on rice promoter editing conducted in recent years, focusing on improvements in yield, heading date, quality, and disease resistance. It is expected to inform the application of promoter editing and encourage further research and development in crop genetic improvement with promote. [ABSTRACT FROM AUTHOR]

Protein-Protein Interactions (PPIs) involves in various biological processes, which are of significant importance in cancer diagnosis and drug development. Computational based PPI prediction methods are more preferred due to their low cost and high accuracy. However, existing protein structure based methods are insufficient in the extraction of protein structural information. Furthermore, most methods are less interpretable, which hinder their practical application in the biomedical field. In this paper, we propose MGPPI, which is a Multiscale graph convolutional neural network model for PPI prediction. By incorporating multiscale module into the Graph Neural Network (GNN) and constructing multi convolutional layers, MGPPI can effectively capture both local and global protein structure information. For model interpretability, we introduce a novel visual explanation method named Gradient Weighted interaction Activation Mapping (Grad-WAM), which can highlight key binding residue sites. We evaluate the performance of MGPPI by comparing with state-of-the-arts methods on various datasets. Results shows that MGPPI outperforms other methods significantly and exhibits strong generalization capabilities on the multispecies dataset. As a practical case study, we predicted the binding affinity between the spike (S) protein of SARS-COV-2 and the human ACE2 receptor protein, and successfully identified key binding sites with known binding functions. Key binding sites mutation in PPIs can affect cancer patient survival statues. Therefore, we further verified Grad-WAM highlighted residue sites in separating patients survival groups in several different cancer type datasets. According to our results, some of the highlighted residues can be used as biomarkers in predicting patients survival probability. All these results together demonstrate the high accuracy and practical application value of MGPPI. Our method not only addresses the limitations of existing approaches but also can assists researchers in identifying crucial drug targets and help guide personalized cancer treatment. [ABSTRACT FROM AUTHOR]

The identification of co-regulated genes and their Transcription-Factor Binding Sites (TFBSs) are the key steps toward understanding transcription regulation. In addition to effective laboratory assays, various bi-clustering algorithms for the detection of the co-expressed genes have been developed. Bi-clustering methods are used to discover subgroups of genes with similar expression patterns under to-be-identified subsets of experimental conditions when applied to gene expression data. By building two fuzzy partition matrices of the gene expression data with the Axiomatic Fuzzy Set (AFS) theory, this paper proposes a novel fuzzy bi-clustering algorithm for the identification of co-regulated genes. Specifically, the gene expression data are transformed into two fuzzy partition matrices via the sub-preference relations theory of AFS at first. One of the matrices considers the genes as the universe and the conditions as the concept, and the other one considers the genes as the concept and the conditions as the universe. The identification of the co-regulated genes (bi-clusters) is carried out on the two partition matrices at the same time. Then, a novel fuzzy-based similarity criterion is defined based on the partition matrices, and a cyclic optimization algorithm is designed to discover the significant bi-clusters at the expression level. The above procedures guarantee that the generated bi-clusters have more significant expression values than those extracted by the traditional bi-clustering methods. Finally, the performance of the proposed method is evaluated with the performance of the three well-known bi-clustering algorithms on publicly available real microarray datasets. The experimental results are in agreement with the theoretical analysis and show that the proposed algorithm can effectively detect the co-regulated genes without any prior knowledge of the gene expression data. [ABSTRACT FROM AUTHOR]

Protein–calixarenes binding plays an increasingly central role in many applications, spanning from molecular recognition to drug delivery strategies and protein inhibition. These ligands obey a specific bio-supramolecular chemistry, which can be revealed by computational approaches, such as molecular dynamics simulations. In this paper, we rely on all-atom, explicit-solvent molecular dynamics simulations to capture the electrostatically driven association of a phosphonated calix-[4]-arene with cytochome-C, which critically relies on surface-exposed paired lysines. Beyond two binding sites identified in direct agreement with the x-ray structure, the association has a larger structural impact on the protein dynamics. Then, our simulations allow a direct comparison to analogous calixarenes, namely, sulfonato, similarly reported as "molecular glue." Our work can contribute to a robust in silico predictive tool to assess binding sites for any given protein of interest for crystallization, with the specificity of a macromolecular cage whose endo/exo orientation plays a role in the binding. [ABSTRACT FROM AUTHOR]

Competency-based physiology and biochemistry education can benefit from the creative integration of imaginative narratives into traditional teaching methods. This paper proposes an innovative model using a pen and palm analogy to visualize enzyme function theories. The pen (substrate) must fit snugly into the palm (enzyme's active site) for catalysis to occur, akin to induced-fit theory. Pressing the pen's top button with the thumb represents the strain needed to convert substrate (pen with nib inside) into product (pen with nub out, ready to write). By leveraging everyday objects creatively, students can enhance their understanding and engagement with enzymatic reactions. NEW & NOTEWORTHY: Understanding how enzymes work can be tricky, but a new teaching method using everyday objects like pens and palms helps make it easier. Two main theories explain this: the induced-fit model and the substrate-strain model. To visualize this, imagine a pen as the substrate and your palm as the enzyme. When you hold the pen with your fingers (induced-fit), it's like the enzyme changing shape to hold the substrate. Pressing the pen's button with your thumb (substrate-strain) is like the enzyme applying pressure to make the pen ready to write. This simple analogy helps students better understand these complex processes, making learning more engaging and accessible. [ABSTRACT FROM AUTHOR]

Transcription factor binding to a gene regulatory region induces or represses its expression. Binding and expression target analysis (BETA) integrates the binding and gene expression data to predict this function. First, the regulatory potential of the factor is modeled based on the distance of its binding sites from the transcription start sites in a decay function. Then the differential expression statistics from an experiment where this factor was perturbed represent the binding effect. The rank product of the two values is employed to order in importance. This algorithm was originally implemented in Python. We reimplemented the algorithm in R to take advantage of existing data structures and other tools for downstream analyses. Here, we attempted to replicate the findings in the original BETA paper. We applied the new implementation to the same datasets using default and varying inputs and cutoffs. We successfully replicated the original results. Moreover, we showed that the method was appropriately influenced by varying the input and was robust to choices of cutoffs in statistical testing. [ABSTRACT FROM AUTHOR]

Biological systems are noisy by nature. This aspect is reflected in our experimental measurements and should be reflected in the models we build to better understand these systems. Noise can be especially consequential when trying to interpret specific regulatory interactions, i.e. regulatory network edges. In this paper, we propose a method to explicitly encode edge-noise in Boolean dynamical systems by probabilistic edge-weight (PEW) operators. PEW operators have two important features: first, they introduce a form of edge-weight into Boolean models through the noise, second, the noise is dependent on the dynamical state of the system, which enables more biologically meaningful modeling choices. Moreover, we offer a simple-to-use implementation in the already well-established BooleanNet framework. In two application cases, we show how the introduction of just a few PEW operators in Boolean models can fine-tune the emergent dynamics and increase the accuracy of qualitative predictions. This includes fine-tuning interactions which cause non-biological behaviors when switching between asynchronous and synchronous update schemes in dynamical simulations. Moreover, PEW operators also open the way to encode more exotic cellular dynamics, such as cellular learning, and to implementing edge-weights for regulatory networks inferred from omics data. Author summary: The life and decision-making of cells is regulated by a complex web of dynamically interacting molecules. The strength and nature of individual interactions is very diverse, and it is especially important to understand such diversity when it comes to defects and disease. For example, the mutation of a protein binding site can critically alter the probability and strength of its interactions with its binding partners. Boolean network models have become an increasingly potent tool for understanding the complex dynamical interactions within cellular regulatory systems, however, there is no straightforward and explicit way to encode weights on individual interactions. In this paper we offer a way to add weights to interactions by simple noise operators which alter the behavior of edges (or groups of edges) in in-silico simulations of Boolean network models. We show with multiple applications that adding just a few PEW (probabilistic edge-weight) operators dramatically improves the biological plausibility of Boolean models and reproduces much more nuanced experimental results. [ABSTRACT FROM AUTHOR]

The enzyme nitrogenase converts N2 to NH3 with stoichiometry N2 + 8H+ + 8e− → 2NH3 + H2. The mechanism is chemically complex with multiple steps that must be consistent with much accumulated experimental information, including exchange of H2 and N2 and the N2-dependent hydrogenation of D2 to HD. Previous investigations have developed a collection of working hypotheses that guide ongoing density functional investigations of mechanistic steps and sequences. These include (i) hypotheses about the serial provision of protons and their conversion to H atoms bonded to S and Fe atoms of the FeMo-co catalytic site, (ii) the migration of H atoms over the surface of FeMo-co, (iii) the roles of His195, (iv) identification of three protein channels, one for the ingress of N2, a separate pathway for the passage of exogenous H2 (D2) and product H2 (HD), and a hydrophilic pathway for egress of product NH3. Two additional working hypotheses are described in this paper. N2 passing along the N2 channel approaches and binds end-on to the exo coordination position of Fe2, with favourable energetics when FeMo-co is pre-hydrogenated. This exo-Fe2–N2 is apparently not reduced but has a promotional role by expanding the reaction zone. A second N2 can enter via the N2 ingress channel and bind at the endo-Fe6 position, where it is surrounded by H atom donors suitable for the N2 → NH3 conversion. It is proposed that this endo-Fe6 position is also the binding site for H2 (generated or exogenous), accounting for the competitive inhibition of N2 reduction by H2. The HD reaction occurs at the endo-Fe6 site, promoted by N2 at the exo-Fe2 site. The second hypothesis concerns the most stable electronic states of FeMo-co with ligands bound at Fe2 and Fe6, and provides a protocol for management of electronic states in mechanism calculations. [ABSTRACT FROM AUTHOR]

The Hill functions, Hh(x) = xh/(1 + xh), have been widely used in biology for over a century but, with the exception of H1, they have had no justification other than as a convenient fit to empirical data. Here, we show that they are the universal limit for the sharpness of any input-output response arising from a Markov process model at thermodynamic equilibrium. Models may represent arbitrary molecular complexity, with multiple ligands, internal states, conformations, coregulators, etc, under core assumptions that are detailed in the paper. The model output may be any linear combination of steady-state probabilities, with components other than the chosen input ligand held constant. This formulation generalizes most of the responses in the literature. We use a coarse-graining method in the graph-theoretic linear framework to show that two sharpness measures for input-output responses fall within an effectively bounded region of the positive quadrant, Ωm ⊂ (R+)², for any equilibrium model with m input binding sites. Ωm exhibits a cusp which approaches, but never exceeds, the sharpness of Hm, but the region and the cusp can be exceeded when models are taken away from thermodynamic equilibrium. Such fundamental thermodynamic limits are called Hopfield barriers, and our results provide a biophysical justification for the Hill functions as the universal Hopfield barriers for sharpness. Our results also introduce an object, Ωm, whose structure may be of mathematical interest, and suggest the importance of characterizing Hopfield barriers for other forms of cellular information processing. [ABSTRACT FROM AUTHOR]

This paper focuses on the computationally assisted design of molecularly imprinted polymers (MIP), emphasizing the selected strategies and chosen methods of approach. In summary, this paper provides an overview of the MIP fabrication procedure, focusing on key factors and challenges, where the fabrication of MIP includes a step‐by‐step process with extensive experimental procedures. This brings challenges in optimizing experimental conditions, such as the selection of monomer, cross‐linker, and their relevant molar ratios to the template and solvent. Next, the principles of computational methods are elucidated to explore their potential applicability in solving the challenges. The computational approach can tackle the problems and optimize the MIP's design. Finally, the atomistic, quantum mechanical (QM), and combined methods in the recent research studies are overviewed with stress on strategies, analyses, and results. It is demonstrated that optimization of pre‐polymerization mixture by employing simulations significantly reduces the trial‐and‐error experiments. Besides, higher selectivity and sensitivity of MIP are observed. The polymerization and resulting binding sites by computational methods are considered. Several models of binding sites are formed and analyzed to assess the affinities representing the sensitivity and selectivity of modeled cavities. Combined QM/atomistic methods showed more flexibility and versatility for realistic modeling with higher accuracy. This methodological advancement aligns with the principles of green chemistry, offering cost‐effective and time‐efficient solutions in MIP design. This article is categorized under:Structure and Mechanism > Molecular StructuresStructure and Mechanism > Computational Materials ScienceMolecular and Statistical Mechanics > Molecular Interactions [ABSTRACT FROM AUTHOR]

Transcription factors (TFs) are proteins essential for regulating genetic transcriptions by binding to transcription factor binding sites (TFBSs) in DNA sequences. Accurate predictions of TFBSs can contribute to the design and construction of metabolic regulatory systems based on TFs. Although various deep-learning algorithms have been developed for predicting TFBSs, the prediction performance needs to be improved. This paper proposes a bidirectional encoder representations from transformers (BERT)-based model, called BERT-TFBS, to predict TFBSs solely based on DNA sequences. The model consists of a pre-trained BERT module (DNABERT-2), a convolutional neural network (CNN) module, a convolutional block attention module (CBAM) and an output module. The BERT-TFBS model utilizes the pre-trained DNABERT-2 module to acquire the complex long-term dependencies in DNA sequences through a transfer learning approach, and applies the CNN module and the CBAM to extract high-order local features. The proposed model is trained and tested based on 165 ENCODE ChIP-seq datasets. We conducted experiments with model variants, cross-cell-line validations and comparisons with other models. The experimental results demonstrate the effectiveness and generalization capability of BERT-TFBS in predicting TFBSs, and they show that the proposed model outperforms other deep-learning models. The source code for BERT-TFBS is available at https://github.com/ZX1998-12/BERT-TFBS. [ABSTRACT FROM AUTHOR]

1,2‐benzisothiazol‐3(2H)‐one derivatives are highly active against a broad spectrum of fungi as well as Gram positive and Gram negative bacteria. For this reason they are extensively used, for example, as additives in detergents, leather products, paper coatings, and antifouling paintings. In this paper experimental findings are reported proving that the sulfur atom of benzisothiazolinones have a remarkable tendency to form short and directional chalcogen bondings on the extension of the covalent N−S bond and, to a lesser extent, of the C−S bond. Analyses of the Cambridge Structural Database confirm the interaction as a primary recognition motif of these systems. The electrophilicity of sulfur is crucial in the chemical reactions initiating the cascade of events resulting in the biopharmacological activities of benzisothiazolinones. The reported results suggest that the electrophility of sulfur may play a role also at earlier stages than the reactive ones, namely it may pin the compounds at the active site of target enzymes via chalcogen bondings that preorganize the system in the conformation required for the bonds formation/cleavage determining the biopharmacological activity [ABSTRACT FROM AUTHOR]

In this paper, we report results of using molecular modeling to assign specific Zn(II) binding affinities to the known binding sites of the YiiP–zinc transporter. YiiP is a cation-diffusion facilitator. It facilitates the transmembrane exchange of Zn(II) ions and protons. The crystal structure of this protein is known. There are several zinc binding sites, and some of the Zn(II) binding affinities have been measured, but the value of all the binding/dissociation constants and the exact assignment of the sites with these affinities are not completely understood. We have recently developed a fast and accurate coarse-grain framework for predicting protein pKa shifts named PKA17. In this paper, we report extending of the same technique to produce a methodology capable of quickly predicting metal–protein binding affinities. The new software has been named M21. It has been tested on several zinc–protein binding cases, and the average unsigned error in the binding energies has been found to be 2.17 kcal/mol vs. the AMBER average error of 3.49 kcal/mol ( K d ratio of ca. 30 vs. the AMBER one of 330). We have then applied the M21 methodology to calculate and assign the YiiP–Zn(II) binding constants of − 2.31 − 13.28 kcal/mol ( K d values from 2. 0 4 × 1 0 − 2 to 1. 8 5 × 1 0 − 1 0 ). We have also undertaken additional modifications of parameters. On one hand, we have included another 11 zinc binding proteins in our target fitting set. These were the Uno Ferro single chain (UFsc) and its modifications created by the Professor Olga Makhlynets group. On the other hand, we have significantly reduced the number of fittable parameters in order to further reduce the possibility of overfitting and to demonstrate the stability of the technique. The final parameter set has only eight adjustable parameters (as opposed to the above case with 17 independent parameters). The average error for the binding cases compared with the same AMBER test set as above did not change much and was still very low at 2.17 kcal/mol. We believe that these results not only further validate the presented methodology but also point out a promising direction for potential multiple joint experimental and computational collaborative projects. Both PKA17 and M21 software have been deployed with web-based interfaces at http://kaminski.wpi.edu/PKA17/pka%5fcalc.html and http://kaminski.wpi.edu/METAL/metal%5fcalc.html , respectively. We have developed M21, a modification of the previously reported coarse grain PKA17 predictor of pKa values of protein residues. This new M21 software is designed to quickly assess protein-metal ion binding affinities. M21 and PKA17 can be run by using a website interface at http://kaminski.wpi.edu/METAL/metal%5fcalc.html and http://kaminski.wpi.edu/PKA17/pka%5fcalc.html , respectively. [ABSTRACT FROM AUTHOR]

Fabry disease (FD) is a rare, X-linked lysosomal storage disorder affecting both males and females caused by genetic abnormalities in the gene encoding the enzyme α-galactosidase A. FD-affected patients represent a highly variable clinical course with first symptoms already appearing in young age. The disease causes a progressive multiple organ dysfunction affecting mostly the heart, kidneys and nervous system, eventually leading to premature death. Disease-specific management of FD includes enzyme replacement therapy with agalsidase α and β or pharmacological oral chaperone migalastat. Migalastat is a low-molecular-mass iminosugar, that reversibly binds to active site of amenable enzyme variants, stabilizing their molecular structure and improving trafficking to the lysosome. Migalastat was approved in the EU in 2016 and is an effective therapy in the estimated 35–50% of all patients with FD with amenable GLA gene variants. This position statement is the first comprehensive review in Central and Eastern Europe of the current role of migalastat in the treatment of FD. The statement provides an overview of the pharmacology of migalastat and summarizes the current evidence from the clinical trial program regarding the safety and efficacy of the drug and its effects on organs typically involved in FD. The position paper also includes a practical guide for clinicians on the optimal selection of patients with FD who will benefit from migalastat treatment, recommendations on the optimal selection of diagnostic tests and the use of tools to identify patients with amenable GLA mutations. Areas for future migalastat clinical research have also been identified. [ABSTRACT FROM AUTHOR]

Bacteriophage λ's CI repressor protein controls a genetic switch between the virus's lysogenic and lytic lifecycles, in part, by selectively binding to six different DNA sequences within the phage genome—collectively referred to as operator sites. However, the minimal level of information needed for CI to recognize and specifically bind these six unique-but-related sequences is unclear. In a previous study, we introduced an algorithm that extracts the minimal direct readout information needed for λ-CI to recognize and bind its six binding sites. We further revealed direct readout information shared among three evolutionarily related lambdoid phages: λ-phage, Enterobacteria phage VT2-Sakai, and Stx2 converting phage I, suggesting that the λ-CI protein could bind to the operator sites of these other phages. In this study, we show that λ-CI can indeed bind the other two phages' cognate binding sites as predicted using our algorithm, validating the hypotheses from that paper. We go on to demonstrate the importance of specific hydrogen bond donors and acceptors that are maintained despite changes to the nucleobase itself, and another that has an important role in recognition and binding. This in vitro validation of our algorithm supports its use as a tool to predict alternative binding sites for DNA-binding proteins. [ABSTRACT FROM AUTHOR]

The widespread use of antibiotics in water has resulted in significant environmental contamination, posing potential health risks. This necessitates the development of efficient methods for their removal from wastewater. This review explores the potential of UiO (Universitetet i Oslo) metal–organic frameworks (MOFs) for the adsorption of dyes and pharmaceuticals from water. UiO MOFs possess exceptional characteristics, including ultra-high porosity and remarkable stability, making them ideal candidates for pollutant adsorption compared to traditional adsorbents. Studies have demonstrated the exceptional performance of UiO MOFs in removing antibiotics from water at various concentrations. This high adsorption efficiency is attributed to their extensive Brunauer–Emmett–Teller (BET) surface area and pore volume, offering numerous binding sites for pollutants. The adsorption affinity between UiO MOFs and antibiotics is governed by various interactions, such as electrostatic interactions, hydrogen bonding, and π–π stacking. These interactions are influenced by the surface charge of the target pollutant and the zeta potential of the MOF surface. Furthermore, the detection mechanisms for antibiotics including, fluorescence quenching, photocatalytic degradation, adsorption, sensing, and other methods, are discussed in this review. Overall, this review emphasizes the promising potential of UiO MOFs as efficient adsorbents for removing antibiotics from water, offering a viable solution for environmental cleanup. [ABSTRACT FROM AUTHOR]

Olivacine, a semisynthetic isomer of ellipticine, belongs to the family of natural alkaloids; which possess analgesic, antibacterial, and antipyretic properties. It is a model anticancer drug acting as topoisomerase II inhibitor. The mechanism of action and antineoplastic properties of olivacine are ascribed to its intercalative binding into DNA helices. The present paper reports DFT investigation of the molecular structure, electronic properties, and global reactivity descriptors of the drug. Frontier orbitals (HOMO and LUMO) and MEP surface of the olivacine molecule have been examined. Furthermore, inhibition activity and binding sites of olivacine with kinase protein (PDB Id: 3OG7) have been explored by molecular docking technique. Results have been used to elucidate physico‐chemical aspects and preferred binding patterns of the olivacine drug. [ABSTRACT FROM AUTHOR]

The postsynthetic metalation (PSM) of metal-organic frameworks (MOFs) with intrinsic metal binding sites is an intriguing strategy to introduce catalytic function into MOFs. The spatial distribution of the catalytic sites within the MOF crystal will affect the efficiency of the material, but the factors that govern depth distribution of the introduced metal sites are often not well understood. Herein, we employ Rutherford backscattering spectrometry (RBS) to investigate the metal distribution in a series of post-synthetically metalated mixed linker bpdc/BPY UiO-67 (UiO = Universitet i Oslo, bpdc = biphenyl-dicarboxylate, BPY = 2,2'-bipyridine-5,5'-dicarboxylate) single crystals as a function of linker ratio and metalation time. The RBS spectra reveal large differences in the depth distribution of inserted Ni2+ ions, and core/shell architectures are observed in high BPY materials at shorter incubation times. The incubation times to achieve uniform metal incorporation increases with increasing BPY ratios in the materials, suggesting that the presence of the BPY linkers slow down metal uptake. We propose a combination of ionic interactions and pore clogging, where coordinated ions reduce the available pore space for further ions to diffuse deeper into the framework as reasons for the observed trends. The observations are likely relevant for other mixed-linker MOF systems, and understanding the effect that linker ratios have on PSM and cation distribution will aid in future optimizations of catalytic MOFs. [ABSTRACT FROM AUTHOR]

Covalent organic frameworks (COFs) are a novel type of nanoporous and crystalline polymers with a precise and highly conjugated skeleton, making them promising candidates for constructing emissive materials. However, the strong high conjugation structures between adjacent layers easily lead to aggregation-caused quenching (ACQ) of emission properties. In this study, we have designed COFs with a flexible skeleton to suppress ACQ effects, enhancing their luminescence activity. In addition, the high density of nitrogen and oxygen atoms on these flexible walls serves as binding sites for hydrogen bonding interactions, indicating sensitivity and selectivity towards nitro-explosives. This strategy establishes a new approach for creating luminescent materials for chemical sensors. [ABSTRACT FROM AUTHOR]

Human serum albumin (HSA) is a multifunctional circulatory protein essential for many physiological processes including oncotic pressure maintenance, ligand/drug binding and transport, antioxidant activity, etc. Abnormal HSA levels in biological fluids have been reported in a variety of clinical disorders, making it a potential biomarker for early diagnosis. Low serum albumin levels have been linked to increased long- and short-term mortality rates in ICU patients. Therefore, quantifying HSA in biofluids such as serum and urine offers a convenient approach for the early identification of underlying clinical conditions and assessing the risk factors. Herein, we report a series of fluorescent 1,4-dihydropyridine (DHP) derivatives for the detection and quantification of HSA in biofluids. Their response towards HSA can be tuned by varying the substituents at the C-4 and the N-1 of the DHP ring. Depending on the nature of the substituents, they generated either a turn-on or ratiometric response with a LoD in low nanomolar or subnanomolar levels. A pair of enantiomers obtained by introducing a chiral center on the N-substituents highlighted the importance of stereochemistry in HSA-ligand interactions. Quantification of HSA in complex biofluids, such as blood serum and urine, was also accomplished using these probes. The high selectivity of some of the probes towards HSA over the homologous BSA allowed the discrimination of these two proteins. The preferred binding location of the probes was the hemin binding site and the detection mechanism was identified as the restriction of intramolecular rotation. Additionally, a prototype of a smartphone-integrated point-of-care device was also fabricated to demonstrate the feasibility of utilizing these probes in clinical settings. [ABSTRACT FROM AUTHOR]

Activating Transcription Factor 4 (ATF4) is an important regulator of gene expression in stress responses and developmental processes in many cell types. Here, we catalogued ATF4 binding sites in the human genome and identified overlaps with trait-associated genetic variants. We probed these genetic variants for allelic regulatory activity using a massively parallel reporter assay (MPRA) in HepG2 hepatoma cells exposed to tunicamycin to induce endoplasmic reticulum stress and ATF4 upregulation. The results revealed that in the majority of cases, the MPRA allelic activity of these SNPs was in agreement with the nucleotide preference seen in the ATF4 binding motif from ChIP-Seq. Luciferase and electrophoretic mobility shift assays in additional cellular models further confirmed ATF4-dependent regulatory effects for the SNPs rs532446 (GADD45A intronic; linked to hematological parameters), rs7011846 (LPL upstream; myocardial infarction), rs2718215 (diastolic blood pressure), rs281758 (psychiatric disorders) and rs6491544 (educational attainment). CRISPR-Cas9 disruption and/or deletion of the regulatory elements harboring rs532446 and rs7011846 led to the downregulation of GADD45A and LPL, respectively. Thus, these SNPs could represent examples of GWAS genetic variants that affect gene expression by altering ATF4-mediated transcriptional activation. Author summary: Genome-wide association studies (GWAS) have gathered a large amount of data connecting genetic variations (mostly single-nucleotide polymorphisms (SNPs)) to phenotypic traits, including diseases, but the molecular mechanisms through which the SNPs lead to phenotypic effects are often obscure. In this paper, we compiled a whole-genome catalogue of chromatin loci interacting with activating transcription factor 4 (ATF4), an important regulator of gene expression in cellular stress responses and other biological processes, and identified trait-associated SNPs overlapping ATF4 binding motifs. We then evaluated the consequences of more than 500 ATF4 binding motif-altering SNPs on allelic transcriptional activity using a massively parallel reporter assay in hepatoma cells in unstressed and stressful conditions. Further characterization of five selected SNPs in additional cellular models confirmed ATF4-dependent regulatory effects for the SNPs rs532446 (GADD45A intronic; linked to blood cell parameters), rs7011846 (LPL upstream; myocardial infarction), rs2718215 (diastolic blood pressure), rs281758 (psychiatric disorders) and rs6491544 (educational attainment). CRISPR/Cas9 technology was used to confirm the effect of rs532446 region on GADD45A and rs7011846 region on LPL gene expression. In conclusion, the data indicate that allelic variants of rs532446, rs7011846 and several other GWAS trait-linked SNPs located in ATF4 binding motifs differ in the ability to activate ATF4-mediated gene expression. [ABSTRACT FROM AUTHOR]

Antithrombin (AT) deficiency increases the risk for venous thromboembolism, therefore, a highly sensitive assay to identify this condition is crucial. The aim of this paper was to perform a meta-analysis comparing AT activities measured by different AT activity assays in patients with heparin binding site AT deficiency. In addition, the diagnostic sensitivity of selected assays was compared depending on the available data. An extensive literature search was performed considering results with publication date up to July 10, 2021. Seven relevant English-language observational studies, comparing AT activity measured by different AT activity assays in Caucasian Europeans with either the AT Budapest III or AT Padua I mutation were included in meta-analyses. There was no significant difference in AT activity between Labexpert and Innovance in patients with AT Budapest III (P = 0.567) and AT Padua I (P = 0.265), while AT activity determined by HemosIL was significantly higher compared to Innovance for both mutations (AT Budapest III: P < 0.001; AT Padua I: P < 0.001). These results are in line with the results of comparison of diagnostic sensitivity. In patients with AT Budapest III, the AT activity was also higher when measured with Berichrom compared to Innovance (P = 0.002), however, the results of comparison of diagnostic sensitivity across studies were variable. No significant difference (P = 0.117) in AT activity as well as diagnostic sensitivity was observed between Sta-Stachrom and Innovance. The results of our study suggest that Innovance, Labexpert and Sta-Stachrom are the most sensitive activity assays for detection of AT Budapest III and AT Padua I, whereas HemosIL showed considerably lower sensitivity for these two variants. As revealed in our study, the diagnostic sensitivity of AT activity assays to type II heparin binding site AT deficiency is different, and in some assays mutation dependent. [ABSTRACT FROM AUTHOR]

Combining phytochemicals with chemotherapeutic drugs has demonstrated the potential to surmount drug resistance. In this paper, we explore the efficacy of pentagalloyl glucose (PGG) in modulating P-gp and reversing multidrug resistance (MDR) in drug-resistant leukemic cells (K562/ADR). The cytotoxicity of PGG was evaluated using a CCK-8 assay, and cell apoptosis was assessed using flow cytometry. Western blotting was used to analyze protein expression levels. P-glycoprotein (P-gp) activity was evaluated by monitoring the kinetics of P-gp-mediated efflux of pirarubicin (THP). Finally, molecular docking, molecular dynamics simulation, and molecular mechanics with generalized Born and surface area solvation (MM-GBSA) calculation were conducted to investigate drug–protein interactions. We found that PGG selectively induced cytotoxicity in K562/ADR cells and enhanced sensitivity to doxorubicin (DOX), indicating its potential as a reversal agent. PGG reduced the expression of P-gp and its gene transcript levels. Additionally, PGG inhibited P-gp-mediated efflux and increased intracellular drug accumulation in drug-resistant cells. Molecular dynamics simulations and MM-GBSA calculation provided insights into the binding affinity of PGG to P-gp, suggesting that PGG binds tightly to both the substrate and the ATP binding sites of P-gp. These findings support the potential of PGG to target P-gp, reverse drug resistance, and enhance the efficacy of anticancer therapies. [ABSTRACT FROM AUTHOR]

Background/aim: Obesity is the fifth largest risk factor of death in the world. The ceramide produced by obesity is closely related to insulin resistance (IR) caused by obesity. At present, the commercially available weight loss products have large side effects and limited therapeutic effects. Therefore, it is particularly important to find effective natural nontoxic products to treat obesity and explore its possible pathways and mechanisms. Materials and methods: In this paper, a high-fat diet (HFD) mice model was established by intragastric administration of high-fat emulsion to investigate the intervention effect of Gooseberry anthocyanins (GA) on IR in HFD mice. We used molecular docking technology to find the binding sites and binding energy of anthocyanins on CerS6. Real-time PCR was used to detect the effect of GA on the expression of IL-6 and TNF-a mRNA in HFD mice. The expression of S1P/Cer signaling pathway in HFD mice with IR was detected by Western Blot. Results: The results showed that GA could effectively inhibit visceral fat, liver index, the level of TC, TG and the level of LDL-C (p < 0.05), and improved HDL-C, GSH-Px and SOD (p < 0.05). GA decreased the level of insulin sensitivity index from -5.15 to -4.54 and improved insulin sensitivity and IR in HFD mice. The binding energy of anthocyanins on CerS6 was in the range of -8.2 to 5.2 kcal/mol, with low energy parameters and good binding positions. GA could reduce mRNA levels of inflammatory factors IL-6 and TNF-a (p < 0.05), inhibit the expression of CerS6, PKCζ, PPARγ, CD36 (p < 0.05), and enhance the expression of SphK2, Akt, p-Akt/Akt, ISR (p < 0.05). Conclusion: This study investigated the effect and mechanism of GA on reducing ceramide content and reducing IR in mice, and provided an experimental basis for the prevention and treatment of obesity-related diseases. [ABSTRACT FROM AUTHOR]

Caffeoylquinic (5-CQA) and feruloylquinic (5-FQA) acids, found in coffee and other plant sources, are known to exhibit diverse biological activities, including potential antioxidant effects. However, the underlying mechanisms of these phenolic compounds remain elusive. This paper investigates the capacity and mode of action of 5-CQA and 5-FQA as natural antioxidants acting as hydroperoxyl radical scavengers and xanthine oxidase (XO) inhibitors. The hydroperoxyl radical scavenging potential was investigated using thermodynamic and kinetic calculations based on the DFT method, taking into account the influence of physiological conditions. Blind docking and molecular dynamics simulations were used to investigate the inhibition capacity toward the XO enzyme. The results showed that 5-CQA and 5-FQA exhibit potent hydroperoxyl radical scavenging capacity in both polar and lipidic physiological media, with rate constants higher than those of common antioxidants, such as Trolox and BHT. 5-CQA carrying catechol moiety was found to be more potent than 5-FQA in both physiological environments. Furthermore, both compounds show good affinity with the active site of the XO enzyme and form stable complexes. The hydrogen atom transfer (HAT) mechanism was found to be exclusive in lipid media, while both HAT and SET (single electron transfer) mechanisms are possible in water. 5-CQA and 5-FQA may, therefore, be considered potent natural antioxidants with potential health benefits. [ABSTRACT FROM AUTHOR]

The Wiseman fitting can be used to extract binding parameters from ITC data sets, such as heat of binding, number of binding sites, and the overall dissociation rate. The classical Wiseman fitting assumes a direct binding process and neglects the possibility of intermediate binding steps. In principle, it only provides thermodynamic information and not the kinetics of the process. In this article we show that a concentration dependent dissociation constant could possibly stem from intermediate binding steps. The mathematical form of this dependency can be exploited with the aid of the Robust Perron Cluster Cluster Analysis method. Our proposed extension of the Wiseman fitting rationalizes the concentration dependency, and can probably also be used to determine the kinetic parameters of intermediate binding steps of a multivalent binding process. The novelty of this paper is to assume that the binding rate varies per titration step due to the change of the ligand concentration and to use this information in the Wiseman fitting. We do not claim to produce the most accurate values of the binding parameters, we rather present a novel method of how to approach multivalent bindings from a different angle. [ABSTRACT FROM AUTHOR]

Southern blot analysis is an important molecular biology technique for identifying a specific sequence in DNA samples. Although it is no longer used extensively in recent years, the steps and underlying principles of Southern blot are applicable to modern biology. High sensitivity and limited background are keys to successful Southern blots, whereas obtaining good quality and quantity of genomic DNA as starting materials and detecting a single/low copy target sequence in the genome can be challenging. To ensure student success in performing the technique for the first time, a modified "plasmid‐to‐plasmid" Southern blot was implemented to confirm the presence of grape nucleotide‐binding site (nbs) sequences in cloned plasmids like those described previously. The plasmid DNA and a control plasmid, pSCA7 (T1‐T3‐W6) containing a known grape nbs sequence, were digested with restriction enzymes, followed by agarose gel electrophoresis. The DNA band corresponding to the nbs sequence of the pSCA7 (T1‐T3‐W6) was extracted from the gel for PCR digoxigenin (DIG) probe synthesis. At the same time, the cloned plasmid DNA and its digested DNA fragments were blotted from the gel onto nylon membranes to be hybridized with the DIG probe followed by the detection for nbs sequences. Students successfully performed Southern blots to confirm the presence of nbs sequences in their cloned plasmids and wrote up the results following the format of scientific research papers. They learned the principles and applications of Southern blot and gained hands‐on experience with associated techniques. [ABSTRACT FROM AUTHOR]