Este trabalho apresenta o estudo e caracterização de dois complexos moleculares, hRXRálfadeltaAB e hemocianina de Acanthoscurria gomesiana, através de técnicas estruturais e biofísicas. O uso da técnica de crio-microscopia eletrônica para o estudo da hemocianina de Acanthoscurria gomesiana, resultou em um modelo estrutural com resolução de 14 angstron- pelo métodode Fourier Shell Correlation com critério de 1/2 bit. Neste limite de resolução, já é possível observar detalhes estruturais que o mostram como sendo comptível com outros modelos de hemocianinas. Com relação ao estudo de hRXRalfadeltaAB, mostrou-se, através das técnicas de cromatografia analítica de exclusão por tamanho, eletroforese de gel de poliacrilamida e SAXS, que a proteína pode se apresentar no estado dimérico em solução, mesmo na ausência do seu ligante, 9-cis-RA. Também foi estudado a associação de hRXRalfadeltaAB a elementos responsivos: DR1, DR4, F2 e PAL. Suas constantes de dissociação foram calculadas através da técnica de espectroscopia por anisotropia de fluorescência. Os resultados obtidos mostram maior afinidade por DR1 e DR2 e indicam uma origem entrópica para o processo de associação / This work describes characterization of two biomolecular complexes: hRXR deltaAB and a hemocyanin from Acanthoscurria gomesiana using structural and biophysical techniques. Application of cryo-electron microscopy to studies of a hemocyanin from Acanthoscurria gomesiana resulted in its structural model to 14Å resolution, which was calculated by Fourier Shell Correlation with cut-off of 1/2 bit. At this resolution limit one can observe structural details of the complex which are compatible with other hemocyanin models. With respect to hRXR deltaAB, we showed using analytic size exclusion chromatography, SDS PAGE and SAXS, that the protein is dimeric in solution even at the absence of its ligand, 9-cis-RA. hRXR deltaAB binding to the responsive elements of DNA, DR1, DR4, F2 and PAL was investigated and the binding constants to these responsive elements have been determined using fluorescence anisotropy technique. Our results show higher affinity of the receptor to DR1 and DR4 and indicate entropic mechanism of DNA binding

Photoelectrochemical cells have been intensively studied in recent years with regard to using thylakoid and photosynthesis system I/II. BBY membrane is another protein complex that has potential to be utilized to build photoelectrochemical cells. Within the BBY membrane lies the highly active photosynthesis system II complex, which upon light activation, generates electrons transported within the electron transport chain during photosynthesis in green plants. This study presents an approach of immobilizing thylakoid or BBY membrane onto gold nanoparticle modified gold plate or multi-walled carbon nanotube (MWCNT) modified indium tin oxide vi (ITO) coated glass substrate. The results show that BBY membrane has higher activity with a value of 168 ± 12 μmol DCIP/(mg Chl*hr) than the thylakoid, which has an activity of 67 ± 7 μmol DCIP/(mg Chl*hr). Further amperometric tests also show that BBY membrane generates a higher current than the thylakoid. We used gold based materials to build the cell first since gold has high electrical conductivity. However, in order to minimize the construction cost of cells, relatively cheap materials such as ITO coated glass and MWCNT were used instead. The surface morphology of cells was characterized using atomic force microscope (AFM) throughout cell modification. When comparing to the cell with gold material, the cell constructed with ITO and MWCNT generated a higher current density. The highest current density was found as 20.44 ± 1.58 μA/cm2 with a system of ITO/MWCNT/BBY. More, the stability of the system was examined and the result shows a decreasing rate of 0.78 %/hour.

Abstract The correct three dimensional structures of proteins are essential for their ability to function properly. Proteins start to fold as soon as they are synthesized in the ribosomes from activated amino acids. Many secreted, cell-surface, secretory pathway and endoplasmic reticulum (ER) lumenal proteins have in their amino acid sequence cysteine residues which form intra- and intermolecular disulfide bridges that stabilize the overall fold of the proteins and protein complexes. The formation of correct disulfide bonds is a complex process which takes place within the ER. Protein disulfide isomerase (PDI) is the key enzyme in the formation and rearrangement of correct disulfide bonds in the ER. It is an archetypal and the best studied member of the PDI family, i.e. a group of ER proteins that resemble thioredoxin (TRX), a protein reductase, in their structure. PDI has a four domain a-b-b'-a' structure the a and a' domains having the catalytic activity and amino acid sequence similarity to TRX. In addition to its function as a thiol-disulfide oxidoreductase, PDI acts as the β subunit in two protein complexes: collagen prolyl 4-hydroxylase (C-P4H) and microsomal triglyceride transfer protein (MTP). The closest homologue of PDI is the multifunctional enzyme and chaperone ERp57 that functions in concert with two lectins, calnexin (CNX) and calreticulin (CRT) specifically in the folding of proteins that have sugar moieties linked to them. ERp57 is 56% similar to PDI in its amino acid sequence and has also the four-domain architecture. Despite the high similarity in their structures ERp57 cannot substitute for PDI as the β subunit of C-P4H. The minimum requirement for the C-P4H tetramer assembly is fulfilled by domains b' and a' of PDI, while domains a and b enhance this function and can be substituted in part by those of ERp57. Until very recently the structural information of any of the PDI family members, which contains the TRX active site was limited to solution structures of human PDI domains a and b. In this research the domain boundaries of the full length ERp57 were defined and the individual domains characterized. Furthermore the solution structures of the catalytically active domains a and a' of ERp57 were studied by nuclear magnetic resonance (NMR).

Understanding the energetic and dynamic behavior of natural protein fluctuations is critical to elucidating important information associated with a multitude of protein functions including signaling processes, enzyme behavior, aggregation pathways etc... This information is also critically important in the development of novel and effective strategies aimed at target proteins associated with pathologies and disease. In order to obtain such useful information, tools and techniques are lacking that: 1) permit the efficient quantitative analysis of fluctuation behavior of existing protein structure ensembles and 2) permit computationally generated natural fluctuation states of proteins at relatively large timescales demanded by the need for biologically relevant results. This thesis presents such methods as well as the results of their application to a case study of Aβ40 and pathogenic Aβ42 where we identify key differences in energy interactions between those two isoforms. Additionally, our detailed atom-level analysis, was able to identify very minute differences in Ramachandran angles between the two strains as the cause for these interaction energy differences. We also demonstrate the efficacy of our implicit solvent algorithm in recovering independently, experimentally identified domain motion over a variety of protein systems. Such a system that is medically significant is the HIV-1 protease for which we identified significant motion of a flap domain known to be pharmaceutically important to the protease’s active site in drug targeting strategies. Lastly, we employ the insights thus acquired from the Aβ40/42 case study to see if Aβ42 aggregation inhibitors can be rationally developed and then tested in vitro for their efficacy. Results were very promising with Aβ42 aggregate sizes being significantly reduced by statistically significant margins by the inhibitor compounds. Due to these encouraging results, we have consequently obtained a provisional patent application for our inhibitors.

<p>  Acute myeloid leukemia (AML) is a devastating cancer with an overall 5-year survival rate of approximately 30%, despite efforts to develop therapeutics to combat this disease. AML is caused by various mutations, and frequent genetic errors found in 30% of AML patients are mutations in the FMS-like tyrosine kinase 3 (FLT3). Recently two FLT3 drugs for AML, Midostaurin and Gilteritinib, have been approved by the FDA, but resistance to these drugs, such as FLT3D835Y/V and F691L, mutations have limited the efficacies of both of these drugs. Thus, there is a need for newer generation FLT3 inhibitors that cover mutations encountered in the clinic. The Sintim laboratory has developed a FLT3 inhibitor, HSN748, which has shown remarkable efficacies against the majority of the FLT3 mutants. Pre-IND studies are now ongoing to support a potential clinical trial of HSN748 for AML treatment that is resistant to the approved therapeutics midostaurin and gilteritinib. The characterization of HSN748 on the proteome and phosphoproteome level was undertaken to provide a more granular view on how this potential AML therapeutic affects key cellular processes. Global proteomic and phosphoproteomic analysis revealed that HSN748 may play a role in cell cycle regulation, spindle formation, leukemic stem cell maintenance, and transcription and confirmed previous in vitro studies that showed inhibition of other kinases relevant to AML treatment, such as AURKB and Raf-1.</p> <p>Recently, there have been efforts to improve the timespan of therapeutic efficiency of FLT3 inhibitors by combining FLT3 inhibitors with other drugs that target other processes essential to AML. Clinical trials (e.g. NCT03735875) are ongoing to evaluate FLT3 inhibitors combined with venetoclax against AML. The second part of this thesis project evaluated the combination of HSN748 analogs with venetoclax and discovered that the combinations synergize to increase apoptotic activity in AML cells harboring FLT3-ITD with secondary mutations D835Y or F691L, which are two clinically important genetic alterations that lead to drug resistance against current FLT3 inhibitors. We determined that the nicotinamide analog, HSL468, synergized with venetoclax with a coefficient of inhibition of 0.23 for the combination with HSL468 at 1.25 nM and venetoclax at 80 nM against an AML cell line that has both the FLT3-ITD and F691L mutations, which are responsible for resistance to most current FLT3-targeted AML therapeutics, including the combination therapy of gilterinitib and venetoclax.</p>

<p>  </p> <p>Using a version of the Povarov-Doebner reaction, we were able to identify and develop a novel kinase inhibitor scaffold that is tunable, selective, and able to target drug-resistant mutant kinases. The 3H-pyrazolo[4,3-f]quinoline moiety was shown to be a privileged kinase inhibitor scaffold with a strong inhibition several different kinases. Herein, various 3H-pyrazolo[4,3-f]quinoline-containing compounds were synthesized quickly via the Povarov-Doebner multicomponent reaction. Our scaffold has demonstrated to potently inhibit FLT3 and CDK2 with nanomolar IC50 values. These FLT3 inhibitors were also shown to inhibit leukemic cell growth in a mouse disseminated AML model, establishing these 3H-pyrazolo[4,3-f]quinoline-containing compounds as lead compounds to develop into anti-cancer agents. The 3H-pyrazolo[4,3-f]quinoline moiety has potently inhibited ROCK1/2 with single digit nanomolar IC50 values, newly synthesized analogs with replacement of the boronic acid moiety with an amide also displayed inhibition of ROCK1/2. The most active compound (<strong>HSH3107</strong>) potently inhibits ROCK1/2 and although it did not display any antiproliferative effects against MDA-MB-231 (triple negative breast cancer cell line) at 1 µM, it did slow cell migration for up to 48 hours compared to DMSO control and Fasudil. Acyclic amide analogs of this scaffold have also led to the discovery of CDK12 and CDK13 inhibitors which can serve as a potential therapeutic in cancers where there may be no treatment strategy available or where resistance has emerged.</p>

No / This paper presents the results of the chemical analysis of materials recovered from two of the earliest agricultural villages in southwestern Iran and a late Neolithic pastoral encampment in nearby Khuzistan. Gas chromatography - mass spectrometry (GC-MS) revealed biomarker compounds characteristic of bitumen in residues from ceramic vessels supporting the excavators¿ contention that the interior surfaces of some vessels were coated with a thin layer of such material and confirmed that ¿fragments¿ collected during excavation were indeed bitumen. Biomolecular and isotopic analysis of the bitumen indicated that the sources utilized lie in the Susa and Deh Luran regions of southwestern Iran. / NERC (MSc); AHRC (PhD)

OF THE DOCTORAL THESIS Title: Functional biomolecular coatings for affinity biosensors for medical diagnostics Author: Erika Hemmerová Department: Institute of Photonics and Electronics of the Czech Academy of Sciences Chaberská 1014/57, 182 51 Prague, Czech Republic Supervisor: Prof. Ing. Jiří Homola, CSc., DSc. Institute of Photonics and Electronics of the Czech Academy of Sciences Chaberská 1014/57, 182 51 Prague, Czech Republic Abstract: Detection and identification of diseases in their early stages represents one of the major goals of the contemporary medical diagnostics. This need drives a research of biomolecular processes behind the particular diseases and development of analytical devices for routine and long-term monitoring of the individuals' health. Surface plasmon resonance biosensors (SPR) have potential to contribute to addressing both of these challenges. This work aims at advancing multiple aspects of SPR biosensor method. It involves study and optimization of selected functional biomolecular coatings in order to improve the performance characteristics of SPR biosensors. It demonstrates utilization of these coatings in novel detection platforms for sensitive monitoring of multiple analytes, and in research of selected biomolecular interactions related to Alzheimer's disease. The...

<div>Artificial Intelligence (AI) plays an increasingly pivotal role in drug discovery. In particular, artificial neural networks such as deep neural networks drive this area of research. The research presented in this thesis is considered a synergistic combination of physicochemical models of protein-ligand interactions such as molecular dynamics simulation, novel machine learning concepts and the use of big data for solving fundamental problems in Structure-Based Drug Design (SBDD). This area of research involves the use of three-dimensional (3D) structural data of biomolecules to assist lead discovery and optimization in a time- and cost-efficient manner. </div><div>The main focus of the thesis research is the development of models, algorithms and methods to facilitate binding-mode elucidation, affinity prediction for congeneric series of molecules and flexible docking. </div><div><br></div><div>For pose-prediction, we developed a Convolutional Neural Network model incorporating hydration information, named DeepWatsite, which displays accurate binding-mode prediction and the capability to highlight different roles of water molecules in protein-ligand binding. In order to train the neural network model, we created a comprehensive database for hydration information of thousands of protein systems. This was made possible through the development of an efficient GPU-accelerated version of Watsite, a program for generating hydration profiles of protein systems through molecular dynamics simulations.\newline</div><div>\indent For accurate affinity prediction for congeneric series of compounds, we developed a new methodological platform for mixed-solvent simulation based on the lambda-dynamics concept. Additionally, we developed a deep-learning model that combines molecular dynamics simulations and a distance-aware graph attention algorithm. Validation studies using this method revealed that its accuracy is competitive to resource-intensive free energy perturbation (FEP) calculations. To train the model, we generated a synthetic database of congeneric series of compounds extracted from the highest-quality medicinal chemistry articles. Molecular-dynamics simulations were used to simulate all the generated systems as method for data augmentation.\newline</div><div>\indent For flexible docking, we developed a machine-learning assisted docking strategy that relies on protein-ligand distance matrix predictions. This technique is built upon Weisfeiler-Lehman neural network concept with an attention mechanism. Comprehensive validation on docking and cross-docking datasets demonstrated the potential of this method to become a docking concept with higher accuracy and efficiency than existing state-of-the-art flexible docking techniques. </div><div><br></div><div>In summary, the thesis proved the general applicability of deep-learning to various tasks in SBDD. Furthermore, it demonstrates that treating biomolecules as dynamic entities can improve the quality of computational methods in structure-based drug design.</div>

<p>Achieving control over the construction and operation of microfabricated label-free DNA biosensors would be a big leap in the quest for highly reliable clinical laboratory tests. Reliable outcomes of critical medical tests mean less need for repetitions and earlier isolation of outbreaks. Nanotechnology has lent itself well to this purpose, with a plethora of work that attempt to produce highly sensitive nano-biosensors for detection of DNA strands. The problem of achieving a repeatable outcome is crude at best. Additionally, the mechanism of sensing in label-free Field-Effect based DNA sensors is still a matter of dispute. Simulation of the sensors using physical models can shed light into these mechanisms and help answer this question. Computational calculations can also allow designers to assess the importance of several parameters involved in the fabrication.</p> <p>In this thesis, the problem of modeling FET-based DNA hybridization sensors (named BioFET) is approached. Using the Finite-Element Method, a scalable model for the BioFET is produced and solved in 3D. The results are compared to an earlier work and we find that higher dimension physical modeling is essential for more realistic results. Additionally, we present a model for the impedance of the BioFET which allows the calculation of parasitic components that can contaminate the impedance measurements.</p> <p>The issue of variations in the sensed signal from the BioFET is addressed by performing hybrid Finite-Element/Monte Carlo simulations on the conformation of single-stranded DNA. From electrostatic considerations alone, it is concluded that the change of conformation upon hybridization is a main contributor to the induced signal. We also simulate the positional variations of the DNA molecules on the sensitive surface. This computation yields an estimate for the amount of variation in the sensed signal due to the random placement of DNA molecules, and an estimate for the total signal-to-noise ratio is deduced.</p> / Doctor of Philosophy (PhD)