The Difficult Case of Crystallization and Structure Solution for the ParC55 Breakage-Reunion Domain of Topoisomerase IV from Streptococcus pneumoniae

BACKGROUND: Streptococcus pneumoniae is the major cause of community-acquired pneumonia and is also associated with bronchitis, meningitis, otitis and sinusitis. The emergence and increasing prevalence of resistance to penicillin and other antibiotics has led to interest in other anti-pneumonococcal drugs such as quinolones that target the enzymes DNA gyrase and topoisomerase IV. During crystallization and in the avenues to finding a method to determine phases for the structure of the ParC55 breakage-reunion domain of topoisomerase IV from Streptococcus pneumoniae, obstacles were faced at each stage of the process. These problems included: majority of the crystals being twinned, either non-diffracting or exhibiting a high mosaic spread. The crystals, which were grown under conditions that favoured diffraction, were difficult to flash-freeze without loosing diffraction. The initial structure solution by molecular replacement failed and the approach proved to be unviable due to the complexity of the problem. In the end the successful structure solution required an in-depth data analysis and a very detailed molecular replacement search. METHODOLOGY/PRINCIPAL FINDINGS: Crystal anti-twinning agents have been tested and two different methods of flash freezing have been compared. The fragility of the crystals did not allow the usual method of transferring the crystals into the heavy atom solution. Consequently, it was necessary to co-crystallize in the presence of the heavy atom compound. The multiple isomorphous replacement approach was unsuccessful because the 7 cysteine mutants which were engineered could not be successfully derivatized. Ultimately, molecular replacement was used to solve the structure by sorting through a large number of solutions in space group P1 using CNS. CONCLUSIONS/SIGNIFICANCE: The main objective of this paper is to describe the obstacles which were faced and overcome in order to acquire data sets on such difficult crystals and determine phases for successful structure solution

Predicting anticancer hyperfoods with graph convolutional networks

Background: Recent efforts in the field of nutritional science have allowed the discovery of disease-beating molecules within foods based on the commonality of bioactive food molecules to FDA-approved drugs. The pioneering work in this field used an unsupervised network propagation algorithm to learn the systemic-wide effect on the human interactome of 1962 FDA-approved drugs and a supervised algorithm to predict anticancer therapeutics using the learned representations. Then, a set of bioactive molecules within foods was fed into the model, which predicted molecules with cancer-beating potential.The employed methodology consisted of disjoint unsupervised feature generation and classification tasks, which can result in sub-optimal learned drug representations with respect to the classification task. Additionally, due to the disjoint nature of the tasks, the employed approach proved cumbersome to optimize, requiring testing of thousands of hyperparameter combinations and significant computational resources.To overcome the technical limitations highlighted above, we represent each drug as a graph (human interactome) with its targets as binary node features on the graph and formulate the problem as a graph classification task. To solve this task, inspired by the success of graph neural networks in graph classification problems, we use an end-to-end graph neural network model operating directly on the graphs, which learns drug representations to optimize model performance in the prediction of anticancer therapeutics. Results: The proposed model outperforms the baseline approach in the anticancer therapeutic prediction task, achieving an F1 score of 67.99%±2.52% and an AUPR of 73.91%±3.49%. It is also shown that the model is able to capture knowledge of biological pathways to predict anticancer molecules based on the molecules’ effects on cancer-related pathways. Conclusions: We introduce an end-to-end graph convolutional model to predict cancer-beating molecules within food. The introduced model outperforms the existing baseline approach, and shows interpretability, paving the way to the future of a personalized nutritional science approach allowing the development of nutrition strategies for cancer prevention and/or therapeutics

Interceptor effect of C₆₀ fullerene on the in vitro action of aromatic drug molecules

In this work we are focusing on studying the influence of the pristine C₆₀ fullerene on biological activity of some aromatic drug molecules in human buccal epithelial cells. Assessment of the heterochromatin structure in the cell nucleus as well as the barrier function of the cell membrane was performed. The methods of cell microelectrophoresis and atomic force microscopy were also applied. A concentration-dependent restoration of the functional activity of the cellular nucleus after exposure to DNA -binding drugs (doxorubicin, proflavine and ethidium bromide) has been observed in human buccal epithelial cells upon addition of C₆₀ fullerene at a concentration of ~10−5

Trapping of the transport-segment DNA by the ATPase domains of a type II topoisomerase

Type II topoisomerases alter DNA topology to control DNA supercoiling and chromosome segregation and are targets of clinically important anti-infective and anticancer therapeutics. They act as ATP-operated clamps to trap a DNA helix and transport it through a transient break in a second DNA. Here, we present the first X-ray crystal structure solved at 2.83 Å of a closed clamp complete with trapped T-segment DNA obtained by co-crystallizing the ATPase domain of S. pneumoniae topoisomerase IV with a nonhydrolyzable ATP analogue and 14-mer duplex DNA. The ATPase dimer forms a 22 Å protein hole occupied by the kinked DNA bound asymmetrically through positively charged residues lining the hole, and whose mutagenesis impacts the DNA decatenation, DNA relaxation and DNA-dependent ATPase activities of topo IV. These results and a side-bound DNA-ParE structure help explain how the T-segment DNA is captured and transported by a type II topoisomerase, and reveal a new enzyme–DNA interface for drug discovery

Exploring the active site of the Streptococcus pneumoniae topoisomerase IV-DNA cleavage complex with novel 7,8-bridged fluoroquinolones.

As part of a programme of synthesizing and investigating the biological properties of new fluoroquinolone antibacterials and their targeting of topoisomerase IV from Streptococcus pneumoniae, we have solved the X-ray structure of the complexes of two new 7,8-bridged fluoroquinolones (with restricted C7 group rotation favouring tight binding) in complex with the topoisomerase IV from S. pneumoniae and an 18-base-pair DNA binding site-the E-site-found by our DNA mapping studies to bind drug strongly in the presence of topoisomerase IV (Leo et al. 2005 J. Biol. Chem. 280, 14 252-14 263, doi:10.1074/jbc.M500156200). Although the degree of antibiotic resistance towards fluoroquinolones is much lower than that of β-lactams and a range of ribosome-bound antibiotics, there is a pressing need to increase the diversity of members of this successful clinically used class of drugs. The quinolone moiety of the new 7,8-bridged agents ACHN-245 and ACHN-454 binds similarly to that of clinafloxocin, levofloxacin, moxifloxacin and trovofloxacin but the cyclic scaffold offers the possibility of chemical modification to produce interactions with other topoisomerase residues at the active site

Structure of an 'open' clamp type II topoisomerase-DNA complex provides a mechanism for DNA capture and transport

Type II topoisomerases regulate DNA supercoiling and chromosome segregation. They act as ATP-operated clamps that capture a DNA duplex and pass it through a transient DNA break in a second DNA segment via the sequential opening and closure of ATPase-, G-DNA- and C-gates. Here, we present the first ‘open clamp’ structures of a 3-gate topoisomerase II-DNA complex, the seminal complex engaged in DNA recognition and capture. A high-resolution structure was solved for a (full-length ParE-ParC55)2 dimer of Streptococcus pneumoniae topoisomerase IV bound to two DNA molecules: a closed DNA gate in a B-A-B form double-helical conformation and a second B-form duplex associated with closed C-gate helices at a novel site neighbouring the catalytically important β-pinwheel DNA-binding domain. The protein N gate is present in an ‘arms-wide-open’ state with the undimerized N-terminal ParE ATPase domains connected to TOPRIM domains via a flexible joint and folded back allowing ready access both for gate and transported DNA segments and cleavage-stabilizing antibacterial drugs. The structure shows the molecular conformations of all three gates at 3.7 Å, the highest resolution achieved for the full complex to date, and illuminates the mechanism of DNA capture and transport by a type II topoisomerase

Alzheimer's disease: using gene/protein network machine learning for molecule discovery in olive oil

Alzheimer's disease (AD) poses a profound human, social, and economic burden. Previous studies suggest that extra virgin olive oil (EVOO) may be helpful in preventing cognitive decline. Here, we present a network machine learning method for identifying bioactive phytochemicals in EVOO with the highest potential to impact the protein network linked to the development and progression of the AD. A balanced classification accuracy of 70.3 ± 2.6% was achieved in fivefold cross-validation settings for predicting late-stage experimental drugs targeting AD from other clinically approved drugs. The calibrated machine learning algorithm was then used to predict the likelihood of existing drugs and known EVOO phytochemicals to be similar in action to the drugs impacting AD protein networks. These analyses identified the following ten EVOO phytochemicals with the highest likelihood of being active against AD: quercetin, genistein, luteolin, palmitoleate, stearic acid, apigenin, epicatechin, kaempferol, squalene, and daidzein (in the order from the highest to the lowest likelihood). This in silico study presents a framework that brings together artificial intelligence, analytical chemistry, and omics studies to identify unique therapeutic agents. It provides new insights into how EVOO constituents may help treat or prevent AD and potentially provide a basis for consideration in future clinical studies

BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology

Mass Spectrometry Imaging (MSI) holds significant promise in augmenting digital histopathologic analysis by generating highly robust big data about the metabolic, lipidomic and proteomic molecular content of the samples. In the process, a vast quantity of unrefined data, that can amount to several hundred gigabytes per tissue section, is produced. Managing, analysing and interpreting this data is a significant challenge and represents a major barrier to the translational application of MSI. Existing data analysis solutions for MSI rely on a set of heterogeneous bioinformatics packages that are not scalable for the reproducible processing of large-scale (hundreds to thousands) biological sample sets. Here, we present a computational platform (pyBASIS) capable of optimized and scalable processing of MSI data for improved information recovery and comparative analysis across tissue specimens using machine learning and related pattern recognition approaches. The proposed solution also provides a means of seamlessly integrating experimental laboratory data with downstream bioinformatics interpretation/analyses, resulting in a truly integrated system for translational MSI

Structural Basis of Gate-DNA Breakage and Resealing by Type II Topoisomerases

Type II DNA topoisomerases are ubiquitous enzymes with essential functions in DNA replication, recombination and transcription. They change DNA topology by forming a transient covalent cleavage complex with a gate-DNA duplex that allows transport of a second duplex though the gate. Despite its biological importance and targeting by anticancer and antibacterial drugs, cleavage complex formation and reversal is not understood for any type II enzyme. To address the mechanism, we have used X-ray crystallography to study sequential states in the formation and reversal of a DNA cleavage complex by topoisomerase IV from Streptococcus pneumoniae, the bacterial type II enzyme involved in chromosome segregation. A high resolution structure of the complex captured by a novel antibacterial dione reveals two drug molecules intercalated at a cleaved B-form DNA gate and anchored by drug-specific protein contacts. Dione release generated drug-free cleaved and resealed DNA complexes in which the DNA gate instead adopts an unusual A/B-form helical conformation with a Mg2+ ion repositioned to coordinate each scissile phosphodiester group and promote reversible cleavage by active-site tyrosines. These structures, the first for putative reaction intermediates of a type II topoisomerase, suggest how a type II enzyme reseals DNA during its normal reaction cycle and illuminate aspects of drug arrest important for the development of new topoisomerase-targeting therapeutics