Genetically modified mice as a tool for the study of human diseases.

Modeling a human disease is an essential part of biomedical research. The recent advances in the field of molecular genetics made it possible to obtain genetically modified animals for the study of various diseases. Not only monogenic disorders but also chromosomal and multifactorial disorders can be mimicked in lab animals due to genetic modification. Even human infectious diseases can be studied in genetically modified animals. An animal model of a disease enables the tracking of its pathogenesis and, more importantly, to test new therapies. In the first part of this paper, we review the most common DNA modification technologies and provide key ideas on specific technology choices according to the task at hand. In the second part, we focus on the application of genetically modified mice in studying human diseases.

Noncovalent Self-Assembly of Single-Layer MoS2 Nanosheets and Zinc Porphyrin into Stable SURMOF Nanohybrids with Multimodal Photocatalytic Properties.

A noncovalent integration of nanosheets of molybdenum disulfide (MoS2) and the zinc porphyrin complex Zn(II) 5,10,15,20-tetrakis(4-carboxyphenyl)porphine (ZnTCPP) through coordination bonding with metal clusters of zinc acetate (Zn[OAc]2) was applied for synthesis of stable hybrid nanomaterial avoiding surface prefunctionalization. The X-ray powder diffraction in combination with the BET nitrogen adsorption method confirms formation of a ZnTCPP-based surface-attached metal-organic framework (SURMOF) with micropores of 1.63 nm on the MoS2 nanosheets. Fluorescence spectroscopy confirmed Forster resonance energy transfer (FRET) between MoS2 and ZnTCPP without contact quenching. Fluorescent trapping with terephthalic acid for hydroxyl radicals and Sensor Green for singlet oxygen was applied for studying the pathways of photodegradation of model organic pollutant 1,5-dihydroxynaphthalene (DHN) in the presence of SURMOF/MoS2. Visible light initiates sensitization through the excitation of ZnTCPP generating singlet oxygen, whereas UV-light promotes either aerobic FRET-mediated "Z scheme" or anaerobic "Type II heterojunction" mechanisms. Owing to its multimodal photochemistry, the SURMOF/MoS2 hybrid showed comparatively high photocatalytic activity in UV-assisted degradation of DHN (keffUV = 4.0 × 10-2 min-1) as well as the antibacterial activity confirmed by E. coli survival test under visible light. Noncovalent self-assembly utilizing coordination bonding in SURMOFs as supramolecular adhesive to avoid surface premodification provides a basis for new types of multicomponent nanosystems with switchable functionalities by combining different 2D materials and chromophores in one hybrid structure.

Cyclophilin A as a Pro-Inflammatory Factor Exhibits Embryotoxic and Teratogenic Effects during Fetal Organogenesis.

The precise balance of Th1, Th2, and Th17 cytokines is a key factor in successful pregnancy and normal embryonic development. However, to date, not all humoral factors that regulate and influence physiological pregnancy have been completely studied. Our data here pointed out cyclophilin A (CypA) as the adverse pro-inflammatory factor negatively affecting fetal development and associated with pregnancy complications. In different mouse models in vivo, we demonstrated dramatic embryotoxicity and teratogenicity of increased CypA levels during pregnancy. Using generated transgenic models, we showed that CypA overexpression in fetal tissues induced the death of all transgenic fetuses and complete miscarriage. Administration of recombinant human CypA in a high dose to pregnant females during fetal organogenesis (6.5-11.5 dpc) exhibited teratogenic effects, causing severe defects in the brain and bone development that could lead to malformations and postnatal behavioral and cognitive disorders in the offspring. Embryotoxic and teratogenic effects could be mediated by CypA-induced up-regulation of M1 macrophage polarization via activation of the STAT1/3 signaling pathways. Here, we propose secreted CypA as a novel marker of complicated pregnancy and a therapeutic target for the correction of pregnancy complications.

Antimicrobial activity of photosensitizers: arrangement in bacterial membrane matters.

Porphyrins are well-known photosensitizers (PSs) for antibacterial photodynamic therapy (aPDT), which is still an underestimated antibiotic-free method to kill bacteria, viruses, and fungi. In the present work, we developed a comprehensive tool for predicting the structure and assessment of the photodynamic efficacy of PS molecules for their application in aPDT. We checked it on a series of water-soluble phosphorus(V) porphyrin molecules with OH or ethoxy axial ligands and phenyl/pyridyl peripheral substituents. First, we used biophysical approaches to show the effect of PSs on membrane structure and their photodynamic activity in the lipid environment. Second, we developed a force field for studying phosphorus(V) porphyrins and performed all-atom molecular dynamics simulations of their interactions with bacterial lipid membranes. Finally, we obtained the structure-activity relationship for the antimicrobial activity of PSs and tested our predictions on two models of Gram-negative bacteria, Escherichia coli and Acinetobacter baumannii. Our approach allowed us to propose a new PS molecule, whose MIC50 values after an extremely low light dose of 5 J/cm2 (5.0 ± 0.4 µg/mL for E. coli and 4.9 ± 0.8 µg/mL for A. baumannii) exceeded those for common antibiotics, making it a prospective antimicrobial agent.

Limitations of Tamoxifen Application for In Vivo Genome Editing Using Cre/ERT2 System.

Inducible Cre-dependent systems are frequently used to produce both conditional knockouts and transgenic mice with regulated expression of the gene of interest. Induction can be achieved by doxycycline-dependent transcription of the wild type gene or OH-tamoxifen-dependent nuclear translocation of the chimeric Cre/ERT2 protein. However, both of these activation strategies have some limitations. We analyzed the efficiency of knockout in different tissues and found out that it correlates with the concentration of the hydroxytamoxifen and endoxifen-the active metabolites of tamoxifen-measured by LC-MS in these tissues. We also describe two cases of Cdk8floxed/floxed/Rosa-Cre-ERT2 mice tamoxifen-induced knockout limitations. In the first case, the standard scheme of tamoxifen administration does not lead to complete knockout formation in the brain or in the uterus. Tamoxifen metabolite measurements in multiple tissues were performed and it has been shown that low recombinase activity in the brain is due to the low levels of tamoxifen active metabolites. Increase of tamoxifen dosage (1.5 fold) and duration of activation (from 5 to 7 days) allowed us to significantly improve the knockout rate in the brain, but not in the uterus. In the second case, knockout induction during embryonic development was impossible due to the negative effect of tamoxifen on gestation. Although DNA editing in the embryos was achieved in some cases, the treatment led to different complications of the pregnancy in wild-type female mice. We propose to use doxycycline-induced Cre systems in such models.

Gene Transcription as a Therapeutic Target in Leukemia.

Blood malignancies often arise from undifferentiated hematopoietic stem cells or partially differentiated stem-like cells. A tight balance of multipotency and differentiation, cell division, and quiescence underlying normal hematopoiesis requires a special program governed by the transcriptional machinery. Acquisition of drug resistance by tumor cells also involves reprogramming of their transcriptional landscape. Limiting tumor cell plasticity by disabling reprogramming of the gene transcription is a promising strategy for improvement of treatment outcomes. Herein, we review the molecular mechanisms of action of transcription-targeted drugs in hematological malignancies (largely in leukemia) with particular respect to the results of clinical trials.

Cheminformatics-driven discovery of polymeric micelle formulations for poorly soluble drugs.

Many drug candidates fail therapeutic development because of poor aqueous solubility. We have conceived a computer-aided strategy to enable polymeric micelle-based delivery of poorly soluble drugs. We built models predicting both drug loading efficiency (LE) and loading capacity (LC) using novel descriptors of drug-polymer complexes. These models were employed for virtual screening of drug libraries, and eight drugs predicted to have either high LE and high LC or low LE and low LC were selected. Three putative positives, as well as three putative negative hits, were confirmed experimentally (implying 75% prediction accuracy). Fortuitously, simvastatin, a putative negative hit, was found to have the desired micelle solubility. Podophyllotoxin and simvastatin (LE of 95% and 87% and LC of 43% and 41%, respectively) were among the top five polymeric micelle-soluble compounds ever studied experimentally. The success of the strategy described herein suggests its broad utility for designing drug delivery systems.

QSAR Modeling and Prediction of Drug-Drug Interactions.

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

Existing and Developing Approaches for QSAR Analysis of Mixtures.

This review is devoted to the critical analysis of advantages and disadvantages of existing mixture descriptors and their usage in various QSAR/QSPR tasks. We describe good practices for the QSAR modeling of mixtures, data sources for mixtures, a discussion of various mixture descriptors and their application, recommendations about proper external validation specific for mixture QSAR modeling, and future perspectives of this field. The biggest problem in QSAR of mixtures is the lack of reliable data about the mixtures' properties. Various mixture descriptors are used for the modeling of different endpoints. However, these descriptors have certain disadvantages, such as applicability only to 1 : 1 binary mixtures, and additive nature. The field of QSAR of mixtures is still under development, and existing efforts could be considered as a foundation for future approaches and studies. The usage of non-additive mixture descriptors, which are sensitive to interaction effects, in combination with best practices of QSAR model development (e.g., thorough data collection and curation, rigorous external validation, etc.) will significantly improve the quality of QSAR studies of mixtures.

QSAR analysis of [(biphenyloxy)propyl]isoxazoles: agents against coxsackievirus B3.

BACKGROUND: Antiviral drugs are urgently needed for the treatment of acute and chronic diseases caused by enteroviruses such as coxsackievirus B3 (CVB3). The main goal of this study is quantitative structure-activity relationship (QSAR) analysis of anti-CVB3 activity (clinical CVB3 isolate 97927 [log IC50, µM]) and investigation of the selectivity of 25 ([biphenyloxy]propyl)isoxazoles, followed by computer-aided design and virtual screening of novel active compounds. DISCUSSION: The 2D QSAR obtained models are quite satisfactory (R(2) = 0.84-0.99, Q(2) = 0.76-0.92, R(2)(ext) = 0.62-0.79). Compounds with high antiviral activity and selectivity have to contain 5-trifluoromethyl-[1,2,4]oxadiazole or 2,4-difluorophenyl fragments. Insertion of 2,5-dimethylbenzene, napthyl and especially biphenyl substituents into investigated compounds substantially decreases both their antiviral activity and selectivity. Several compounds were proposed as a result of design and virtual screening. A high level of activity of 2-methoxy-1-phenyl-1H-imidazo[4,5-c]pyridine (sm428) was confirmed experimentally. CONCLUSION: Simplex representation of molecular structure allows successful QSAR analysis of anti-CVB3 activity of ([biphenyloxy]propyl)isoxazole derivatives. Two possible ways of battling CVB3 are considered as a future perspective.

Per aspera ad astra: application of Simplex QSAR approach in antiviral research.

This review explores the application of the Simplex representation of molecular structure (SiRMS) QSAR approach in antiviral research. We provide an introduction to and description of SiRMS, its application in antiviral research and future directions of development of the Simplex approach and the whole QSAR field. In the Simplex approach every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality and symmetry). The main advantages of SiRMS are consideration of the different physical-chemical properties of atoms, high adequacy and good interpretability of models obtained and clear procedures for molecular design. The reliability of developed QSAR models as predictive virtual screening tools and their ability to serve as the basis of directed drug design was validated by subsequent synthetic and biological experiments. The SiRMS approach is realized as the complex of the computer program 'HiT QSAR', which is available on request.