Search

Discrete dynamical modeling shows promise in prioritizing drug combinations for screening efforts by reducing the experimental workload inherent to the vast numbers of possible drug combinations. We have investigated approaches to predict combination responses across different cancer cell lines using logic models generated from one generic prior-knowledge network representing 144 nodes covering major cancer signaling pathways. Cell-line specific models were configured to agree with baseline activity data from each unperturbed cell line. Testing against experimental data demonstrated a high number of true positive and true negative predictions, including also cell-specific responses. We demonstrate the possible enhancement of predictive capability of models by curation of literature knowledge further detailing subtle biologically founded signaling mechanisms in the model topology. In silico model analysis pinpointed a subset of network nodes highly influencing model predictions. Our results indicate that the performance of logic models can be improved by focusing on high-influence node protein activity data for model configuration and that these nodes accommodate high information flow in the regulatory network. Copyright © 2020 Niederdorfer, Touré, Vazquez, Thommesen, Kuiper, Lægreid and Flobak. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

The biological functions of proteins often rely on structural changes and the rates at which these conformational changes occur. Studies show that regions of a protein which are known to be involved in enzyme catalysis or in contact with the substrate are identifiable by NMR spectroscopy to be more flexible, evidenced through measuring order parameters of specific bond vectors. While generalized NMR can allow for detailed characterization of the extent and time scales of these conformational fluctuations, NMR cannot easily produce the structures of sparsely populated intermediates nor can it produce explicit complex atomistic-level mechanisms needed for the full understanding of such processes. Practically, preparing a protein with appropriate isotropic enrichment to study a set of specific bond vectors experimentally is challenging as well. Oftentimes, measuring the dynamics of neighboring bond vectors are necessitated. Detailed studies of the coupling interactions among specific residues and protein regions can be fulfilled by the use of molecular dynamics (MD) simulations. However, MD simulations rely on the ergodic hypothesis to mimic experimental conditions, requiring long simulation times. Simulations are additionally limited by the availability of accurate and reliable molecular mechanics force fields, which continue to be improved to better match experimental data. Much can also be learned from chemical theory and simulations to improve the methods in which experimental data is processed and analyzed. The overarching goals of this thesis are to improve upon the results generated by existing methods in NMR spin relaxation spectroscopy, whether that be through: (i) improving analytical techniques of raw NMR data or through (ii) supporting experimental results with atomistically-detailed MD simulations. The majority of this work is exemplified through the protein Escherichia coli ribonuclease HI (ecRNH). Ribonuclease HI (RNase H) is a conserved endonuclease responsible for cleaving the RNA strand of DNA/RNA hybrids in many biological processes, including reverse transcription of the viral genome in retroviral reverse transcriptases and Okazaki fragment processing during DNA replication of the lagging strand. RNase H belongs to a broader superfamily of nucleotidyl-transferases with conserved structure and mechanism, including retroviral integrases, Holliday junction resolvases, and transposases. RNase H has historically been the subject of many investigations in folding, structure, and dynamics. In support of the first aim, we discuss new methods of obtaining more precise experimental results for order parameters and time constants for the ILV methyl groups. Deuterium relaxation rate constants are determined by the spectral density function for reorientation of the C-D bond vector at zero, single-quantum, and double-quantum 2H frequencies. We interpolate relaxation rates measured at available NMR spectrometer frequencies in order to perform a joint single/double-quantum analysis. This yields approximately 10-15% more precise estimates of model-free parameters and consequently provides a general strategy for further interpolation and extrapolation of data gathered from existing NMR spectrometers for analysis of 2H spin relaxation data in biological macromolecules. In support of the second aim, we calculate autocorrelation functions and generalized order parameters for the ILV methyl side chain groups from MD simulation trajectories to assess the orientational motions of the side chain bond vectors. We demonstrate that motions of the side chain bond vectors can be separated into: (i) fluctuations within a given dihedral angle rotamer, (ii) jumps among the different rotamers, and (iii) motions from the protein backbone itself, through the C-alpha carbon. We are able to match order parameters of constitutive motions to conventionally calculated order parameters with an R2= 0.9962, 0.9708, and 0.9905 for Valine, Leucine, and Isoleucine residues, respectively. Some longer side chain residues such as Leucine and Isoleucine have correlated χ1 and χ2 dihedral angle rotational motions. This provides a method of evaluating the relative contributions of each constitutive motion towards the overall flexibility of a side chain. Multiple contributors of motion are possible for intermediate and low order parameters, signifying more flexible residues. While developing protocols for MD simulations, we evaluate the effects of running 1-microsecond long simulations and compare them to solution state NMR spectroscopy. If the overall tumbling time is removed from the simulation, then analysis blocks of 5-10 times the tumbling time is optimal to eliminate contributions from slower dynamics, which would not normally be measured in solution state NMR spectroscopy. We also assess the quality of the TIP4P(-EW) water model over TIP3P; although TIP4P simulates the isotropic tumbling time well for ecRNH, internal motions are equally not affected by either water model due to well-segregated motions. Additionally, the TIP4P water model does not appear to be able to replicate an axially symmetric shape for ecRNH (ecRNH is mostly spherical and only slightly axially symmetric). The final work of this thesis returns to the first overarching aim; we develop a specialized method that utilizes probability distribution functions to model spectral density functions. We derive the inverse Gaussian probability distribution function from general properties of spectral density functions at low and high frequencies for macromolecules in solution, using the principle of maximum entropy. The resulting model-free spectral density functions are finite at a frequency of zero and can be used to describe distributions of either overall or internal correlation times using the model-free ansatz. The approach is validated using 15N backbone relaxation data for the intrinsically disordered, DNA-binding region of the bZip transcription factor domain of the Saccharomyces cerevisiae protein GCN4, in the absence of cognate DNA.

Thixotropy is a material property that describes how a substance can 'soften' upon continues deformation and heal back to the 'thicker' state over time when left to rest. It is also a fundamental soil behavior mechanism that governs multiple time-dependent engineering properties of soft clays (e.g., the evolution of stiffness, strength, and sensitivity over time).While significant understanding of thixotropy of colloid systems has been achieved since the initiation of the field of thixotropy in the early 1920s, current knowledge on soil thixotropy is still based primarily on some pioneering work performed in and prior to the 1960s and, since then, new developments have been scarce and fragmental. Such a paucity of new findings and the disparity in thixotropy research and advancement between colloid science and soil mechanics provide an impetus to this research. Therefore, this project that integrates multiscale computational and experimental efforts is to study soft clay thixotropy. The work done in this study aims to examine and simulate the clay particle-scale development of thixotropy under various environmental conditions (time, water chemistry, and temperature) and at different size scales. This innovative bottom-up multiscale modeling approach serves to understand the physics underlying macroscopic soft clay thixotropic behavior. The overall goal of the project is to create the enabling knowledge on the macroscale mechanical and microscale structural mechanisms of soft clay thixotropy and hence to append some new time-dependent soil behavior to the geotechnical knowledge base. It is to develop an understanding of the micro- to macro-linkage of soft clay thixotropy through the development of a versatile molecular dynamics (MD) simulation tool to accurately duplicate the time-dependent interactions between clay particles and to provide a framework for the study of the three-dimensional mechanical behavior of soft clays. The value of this project stems from three aspects: (1) the geotechnical knowledge base on soil thixotropy will be expanded with new understanding, particularly the effects of physico-chemical factors such as temperature and porewater chemistry; (2) both the macroscale mechanical and microscale structural mechanisms of thixotropic hardening of soft clays will be uncovered via multiscale computational research; and (3) the linkage between quantitative time-dependent clay fabric evolution and macroscale thixotropic processes will be developed. Because soil thixotropy plays an important role in many engineering problems, the project also can generate significant practical impacts to geotechnical engineering, particularly the design and construction of engineering systems involving soft clays. Examples include evaluation of pile and suction caisson setup, design of wind farm foundations, and disposal of dredged materials, among others. Moreover, the multiscale investigation methodology developed through this project can be generalized to other more complex soil research topics and can also serve as a generic approach for other basic research queries.

Since their discovery in 2011, MXenes, two-dimensional transition metal carbides and/or nitrides, have been explored for uses in a wide range of applications due to their unique properties and facile synthesis methods. Despite this attention, there is a relative lack of understanding with regards to their fundamental mechanical properties. Here, nanoindentation of the MXene system Tin+1CnTx was studied via atomistic simulations utilizing a parametrization of the ReaxFF interatomic potential, to understand the influence of point defects. From force-displacement curves, the Young's moduli of pristine Ti3C2O2 and Ti2CO2 were calculated to be 466 GPa and 983 GPa, respectively. The influences of both titanium and carbon vacancies on Ti3C2O2 were also quantified using simulated nanoindentation of a set of samples containing both 1% VTi and 10% VC, resulting in a reduction of the calculated Young's modulus to 386 ± 31 GPa. Of particular importance, is that these results are in good agreement with recent experimental findings indicating the important role defects play in determining the mechanical behavior of MXenes. The calculated Young's modulus in this work for the defect-containing Ti3C2O2 surpasses that of graphene oxide establishing it as a new benchmark in strength for solution-processed, 2D materials. Results here also indicate improvements can be made in current MXene processing methods to better approach the theoretical strength of pristine 2D materials.

Three isomeric ionene polymers containing 1,4-diazabicyclo[2.2.2]octane (DABCO) and N,N’-(x-phenylene)dibenzamide (x= ortho- / meta- / para-) linkages have been used as dopant agents to produce n-doped poly(3,4-ethylenedioxythiophene) (PEDOT) electrodes by reducing already dedoped conducting polymer (CP) films. This work focuses on the influence of the ionene topology in both the properties of n-doped PEDOT:ionene electrodes and the success of the in situ thermal gelation of the ionene inside the CP matrix. The highest doping level is reached for the para-isomeric ionene-containing electrode, even though the content of ortho- and meta-topomers into the corresponding n-doped PEDOT:ionene electrodes is greater. Thus, many of the incorporated ionene units are not directly interacting with CP chains and, therefore, do not play an active role as n-dopant agent but they are crucial for the in situ formation of ionene hydrogels. The effect of the ionene topology is practically inexistent in properties like the specific capacitance and wettability of PEDOT:ionene films, and it is small but non-negligible in the electrochemical and thermal stability. In contrast, the surface morphology, topography, and distribution of dopant molecules significantly depend on the ionene topology. In situ thermal gelation was successful in PEDOT films n-doped with the ortho- and para-topomers, even though this assembly process was much faster for the former than for the latter. The gelation considerably improved the mechanical response of electropolymerized PEDOT film, which was practically non-existent before it. Molecular dynamics simulations prove that the strength and abundance of PEDOT···ionene specific interactions (i.e. ¿-¿ stacking, N–H···S hydrogen bonds and both N+···O and N+···S interactions) are higher for the meta-isomeric ionene, for which the in situ gelation was not achieved, than for the ortho- and para-ones.

Proton dependent oligopeptide transporters (POTs) play a central role in nitrogen homeostasis by coupling the uptake of dipeptides and tripeptides to the proton electrochemical gradient across the plasma membrane. In human, members of this transporter family, PepT1 and PepT2, are critical modulators of drug pharmacokinetics as they facilitate the uptake and retention of numerous orally administered drugs including the β-lactam antibiotics. Rationally designing drugs to target these transporters is therefore an attractive approach to improving bioavailability. To this end, the binding of peptides to a bacterial homolog, PepTSt, was modelled based on recently determined crystal structures. A range of computational methods to predict the free energy of binding were evaluated and a hybrid approach, where the end-point methods were used to classify peptides into strong and poor binders and a theoretically exact method for refinement, was able to accurately predict ligand affinities. This approach was utilised to investigate the substrate preference of PepTSt and the results were validated using in vitro transport assays. To extend this study to the human peptide transporters, homology models of PepT1 and PepT2 were built using the crystal structures of PepTSo and mouse and rat extracellular domains (ECDs) as the templates. Essential residues as proposed by various mutational studies align well with the binding cavity, suggesting that the models are structurally sound. Applying the free energy methods to predict the affinities of peptides and drugs to the homology model of PepT1, however, resulted in discrepancies with experimental data, highlighting the importance of a high-resolution crystal structure in binding affinity predictions. Based on the results for PepTSt, a binding model for peptide prodrugs and β-lactam antibiotics to the human PepT1 was proposed. Overall, this thesis provides a framework for future computational studies using free energy methods to understand drug interactions with pharmaceutically relevant transporters.

Proteins and DNA are essential to life as we know it and understanding their function is understanding their structure and dynamics. The importance of the latter is being appreciated more in recent years and has led to the development of novel interdisciplinary techniques and approaches to studying protein function. Three techniques to study protein structure and dynamics have been used and combined in different ways in the context of this thesis and have led to a better understanding of the three systems described herein. X-ray crystallography is the oldest and still arguably most popular technique to study macromolecular structures. Nuclear magnetic resonance (NMR) spectroscopy is a not much younger technique that is a powerful tool not only to probe molecular structure but also dynamics. The last technique described herein are molecular dynamics (MD) simulations, which are only just growing out of their infancy. MD simulations are computer simulations of macromolecules based on structures solved by X-ray crystallography or NMR spectroscopy, that can give mechanistic insight into dynamic processes of macromolecules whose amplitudes can be estimated by the former two techniques. MD simulations of the model protein GB3 (B3 immunoglobulin-binding domain of streptococcal protein G) were conducted to identify origins of discrepancies between order parameters derived from different sets of MD simulations and NMR relaxation experiments.The results highlight the importance of time scales as well as sampling when comparing MD simulations to NMR experiments. Discrepancies are seen for unstructured regions like loops and termini and often correspond to nanosecond time scale transitions between conformational substates that are either over- or undersampled in simulation. Sampling biases can be somewhat remedied by running longer (microsecond time scale) simulations. However, some discrepancies persist over even very long trajectories. We show that these discrepancies can be due to the choice of the starting structure and more specifically even differences in protonation procedures. A test for convergence on the nanosecond time scale is shown to be able to correct for many of the observed discrepancies. Next, MD simulations were used to predict in vitro thermostability of members of the bacterial Ribonuclease HI (RNase H) family of endonucleases. Thermodynamic stability is a central requirement for protein function and a goal of protein engineering is improvement of stability, particularly for applications in biotechnology. The temperature dependence of the generalized order parameter, S, for four RNase H homologs, from psychrotrophic, mesophilic and thermophilic organisms, is highly correlated with experimentally determined melting temperatures and with calculated free energies of folding at the midpoint temperature of the simulations. This study provides an approach for in silico mutational screens to improve thermostability of biologically and industrially relevant enzymes. Lastly, we used a combination of X-ray crystallography, NMR spectroscopy and MD simulations to study specificity of the interaction between Drosophila Hox proteins and their DNA target sites. Hox proteins are transcription factors specifying segment identity during embryogenesis of bilaterian animals. The DNA binding homeodomains have been shown to confer specificity to the different Hox paralogs, while being very similar in sequence and structure. Our results underline earlier findings about the importance of the N-terminal arm and linker region of Hox homeodomains, the cofactor Exd, as well as DNA shape, for specificity. A comparison of predicted DNA shapes based on sequence alone with the shapes observed for different DNA target sequences in four crystal structures when in complex with the Drosophila Hox protein AbdB and the cofactor Exd, shows that a combined ”induced fit”/”conformational selection” mechanism is the most likely mechanism by which Hox homeodomains recognize DNA shape and achieve specificity. The minor groove widths for all sequences is close to identical for all ternary complexes found in the different crystal structures, whereas predicted shapes vary between the different DNA sequences. The sequences that have shown higher affinity to AbdB in vitro have a predicted DNA shape that matches the observed DNA shape in the ternary complexes more closely than the sequences that show low in vitro affinity to AbdB. This strongly suggests that the AbdB-Exd complex selects DNA sequences with a higher propensity to adopt the final shape in their unbound form, leading to higher affinity. An additional AbdB monomer binding site with a strongly preformed binding competent shape is observed for one of the oligomers in the reverse complement strand of one of the canonical (weak) Hox-Exd complex binding site. The shape preference seems strong enough for AbdB monomer binding to compete with AbdB-Exd dimer binding to that same oligomer, suggested by the presence of both binding modes in the same crystal. The monomer binding site is essentially able to compete with the dimer binding site, even though binding with the cofactor is not possible, because its shape is very close to the ideal shape. A comparison of different crystal structures solved herein and in the literature as well as a set of molecular dynamics simulations was performed and led to insights about the importance of residues in the Hox N-terminal arm for the preference of certain Hox paralogs to certain DNA shapes. Taken together all these insights contribute to our understanding of Hox specificity in particular as well as protein-DNA interactions in general.

The swelling behaviour of poly(styrene-co-divinylbenzene), P(S-DVB), ion exchange resins in 1-butanol (BuOH) has been studied by means of atomistic classical molecular dynamics simulations (MD). The topological characteristics reported for the resin in the dry state, which exhibited complex internal loops (macropores), were considered for the starting models used to examine the swelling induced by BuOH contents ranging from 10% to 50% w/w. Experimental measurements using a laser diffraction particle size analyzer indicate that swelling causes a volume variation with respect to the dry resin of 21%. According to MD simulations, such a volume increment corresponds to a BuOH absorption of 31-32% w/w, which is in excellent agreement with the indirect experimental estimation (i.e. 31% w/w). Simulations reveal that, independently of the content of BuOH, the density of the swelled resin is higher than that of the dry resin, evidencing that the alcohol provokes important structural changes in the polymeric matrix. Thus, BuOH molecules cause a collapse of the resin macropores when the content of alcohol is

The aggregation properties of two Ala-based pentapeptides were investigated by spectroscopic techniques and molecular dynamics (MD) simulations. The two peptides, both functionalized at the N-terminus with a pyrenyl group, differ in the insertion of an alpha-aminoisobutyric acid residue at position 4. We showed that this single modification of the homo-peptide sequence inhibits the aggregation of the pentapeptide in aqueous solutions. Atomic force microscopy imaging revealed that the two peptides form mesoscopic aggregates of very different morphologies when deposited on mica. MD experiments showed that the two peptides have a very different propensity to form beta-pleated sheet structures, as confirmed by our spectroscopic measurements. The implications of these findings for our understanding of the mechanism leading to the formation of amyloid structures, primary responsible for numerous neurodegenerative diseases, are also discussed.

Ankara : The Department of Physics and the Graduate School of Engineering and Science of Bilkent University, 2014. Thesis (Master's) -- Bilkent University, 2014. Includes bibliographical references leaves 40-42. Microscopic swimmers, for example chemotactic bacteria and cells, are capable of directed motion by exerting a force on their environment. In some cases, including bacteria and spermatozoa swimming near boundaries, or many asymmetrical artificial microswimmers, the driving force and propulsion direction are misaligned. In those situations a torque acting on the microswimmers arises, resulting in motion with a well-defined chirality which is circular in two dimensions and helicoidal in three dimensions. In this thesis, I demonstrate with numerical simulations in two dimensions, how the chirality of the circular motion can couple to chiral features present in the microswimmer environment. I show that by employing static chiral pattern of elliptical obstacles in their environment, microswimmers can be separated on the basis of their motion parameters. In particular, levogyre and dextrogyre microswimmers as small as 50nm can be separated and selectively trapped in chiral flowers of ellipses. Patterned microchannels can be used as funnels to rectify the microswimmer motion, as sorters to separate microswimmers based on their linear and angular velocities, and as sieves to trap microswimmers with specific parameters. I also demonstrate that these results can be extended to helicoidal motion in three dimensions. Mijalkov, Mite M.S.

Neuropilin-1 (NRP-1) is a hub receptor that plays an essential role in angiogenesis and vascular perme- ability. It is over-expres sed in the new blood vessels grown by tumor cells and is a target for anti-tumor treatment s. Peptides that expose the consensus sequence R/K/ XX R/K at the C-terminus ( C-end rule or CendR peptides) bind to NRP-1 and are internalized into the cell. We used peptide phage display binding assays and molecular dynamics (MD) simulations to study the potential role of the central residues of CendR peptides in binding and activa tion of the NRP-1 receptor. The high stability of RPAR–receptor domain complex stems from the formation of a characteristic pattern of three hydrogen bonds between the peptide C-terminus and the residues in the NRP-1 loop III. Any changes in the peptide structure that fail to preserve this triad result in a less-stable complex. We performed a systematic study of R XX R mutants, where X = A/D/S/R/P, in order to test the effect of replacement of A or P on the binding capabil- ities. Our results, both experimental and computational, show that RRAR, RDAR, RPDR, RPRR and RPPR are capable of binding NRP-1. However, only RPPR and RPRR segments form an optimal organization around loop III with low potential energy. In other analogs, the absence of these stabilizing interactions always results in higher potential energy of the complexes. The binding of RPAR analogs does not guarantee receptor activation; only stable complexes that are properly stabilized via loop III appear able to trigger NRP-1 activati on