Two-step Computational Approach Research Articles

Structure-based peptide ligand design for improved epidermal growth factor receptor targeted gene delivery

The epidermal growth factor receptor EGFR allows targeted delivery of macromolecular drugs to tumors. Its ligand, epidermal growth factor, binds EGFR with high affinity but acts mitogenic. Non-mitogenic peptides are utilized as targeting ligands, like the dodecapeptide GE11, although its low binding affinity warrants improvement.We applied a two-step computational approach with database search and molecular docking to design GE11 variants with improved binding. Synthesized peptides underwent binding studies on immobilized EGFR using surface plasmon resonance. Conjugates of peptides coupled via heterobifunctional PEG linker to linear polyethylenimine (LPEI) were used for transfection studies on EGFR-overexpressing cells using reporter gene encoding plasmid DNA.Docking studies unraveled similarities between GE11 and the EGFR dimerization arm. By skipping non-overlapping amino acids, a less hydrophobic segment (YTPQNVI) was identified to be directly involved in EGFR binding. By replacing valine by tyrosine, a full-length version with proposed enhanced binding (GE11m3) was developed. While hydrophobic or hydrophilic segments and variations thereof exhibited low binding, GE11m3 exhibited 3-fold increase in binding compared to GE11, validating in silico predictions. In transfection studies, polyplexes with GE11m3 induced a significantly higher reporter gene expression when compared to GE11 polyplexes both on murine and human cancer cells overexpressing EGFR.

Machine Learning Reinforced Crystal Plasticity Modeling Under Experimental Uncertainty

This Paper addresses a two-step computational approach to building a robust modeling environment for the titanium–aluminum alloy, Ti-7Al, a candidate aerospace material owing to superior mechanical performance under high stresses. To be used in aerospace applications, the large deformation behavior of the alloy should be investigated with a high-fidelity crystal plasticity model. However, there is no universal agreement on the crystal plasticity parameters, and previous efforts are only based on deterministic techniques. Therefore, our goal is to build a crystal plasticity model for Ti-7Al, which is validated for the global (component-scale) and local (grain-level) features by considering the experimental uncertainty. In the first step, the lower and upper bounds of the crystal plasticity parameters are determined with an inverse problem that is solved to match the computations with the experimental stress-strain data. The second step validates the local features by solving an optimization problem that minimizes the difference between the simulated and experimental microstructural textures. The optimization is performed using an Artificial Neural Network (ANN-)based surrogate model that is trained within the lower and upper limits of the parameters obtained in the first step. The outcomes of the two-step approach demonstrate significant improvement over the previous deterministic solutions.

Investigating the influence of external restraint on welding distortion in thin-plate welded structures by means of numerical simulation technology

Welding-induced deformation not only degrades the fabrication accuracy of a welded structure but also decreases the productivity due to correction work. Accurate prediction of welding distortion will be helpful in controlling the dimension accuracy.In this study, the main objective is to clarify the influence of external restraint on welding distortion in three different thin-plate steel welded structures by means of numreical simulation technology. A two-step computational approach was employed to simulate welding distortion in each welded structure. In the first step, the theranal ealstic plastic finite element method (T-E-P FEM) was used to obtain inherent deformation for each typical joint. In the second step, an elastic FEM based on inherent strain theory was used to compute welding deformation for three thin-plate panels with different tihickness and shape. In addition, the effects of external restriant on welding deformation in a thin-plate panel with 5 mm thickness, a thin-plate panel with 10 mm thickness, and an asymmetric curved panel with 10 mm thickness were investigated.

Abstract 2810: Computationally predicted sensitivity of clinical cohorts identifies drug relationships and biomarkers associated with response to PCM-075, a PLK1 selective inhibitor

Abstract Polo-like kinase 1 (PLK1) is a serine-threonine kinase which regulates various cellular processes, including mitosis, DNA replication, and the stress response, and is over-expressed in many malignancies. PCM-075, a PLK1 selective inhibitor, is currently in a phase1b/2 clinical trial in AML in combination therapy with low dose cytarabine (LDAC) (NCT03303339). To identify potential drug relationships and biomarkers associated with response to PCM-075, a two-step computational approach was conducted. Using a modification of the ‘imputed drug-wide association study' (IDWAS) method(1), we first performed ridge regression model training on IC50 values and gene expression signatures for PCM-075 and 138 other drugs from the Genomics of Drug Sensitivity in Cancer (GDSC) database . In the second step, we applied these models to clinical patient datasets (The Cancer Genome Atlas (TCGA) populations containing 32 Cancer types and 9,968 total patients), generating a predicted sensitivity value to all drugs for each patient. Hierarchical clustering of imputed sensitivities across all patients showed that the PCM-075 activity profile is most closely related to cytarabine, etoposide and cisplatin, all of which are compounds that impact DNA replication and lead to apoptosis. Correlation of predicted response values was significant both within and between cancer types, with the acute myeloid leukemia (AML) cohort showing highest increased sensitivity to PCM-075, cytarabine and etoposide relative to the other 31 cancer types examined. Interestingly, other PLK1 inhibitors present in the GDSC (BI-2536 and GW843682X) do not closely cluster with PCM-075. Association of imputed TCGA sensitivity values with somatic variant data shows a high degree of concordance between predicted biomarkers, including TP53 mutation status, further suggesting a functional relationship. Given that this computational analysis suggests that similar pathways are affected by both cytarabine and PCM-075, we tested this experimentally by assessing the level of interaction between these two compounds within an AML cell line (HL-60). The combination resulted in statistically significant synergy (BRAID, k~2.7(1.31-4.25)) for anti-proliferative activity. The mechanistic cause of synergy may be related to DNA damage caused by cytarabine which is known to inhibit and degrade the PLK1 protein. In conclusion, we have identified a pathway signature that clusters PCM-075 with a subset of current oncology therapeutics. Synergy between these compounds in combination suggests the potential for use in treating AML and potentially other cancer types. 1.Genome Res. 27: 1743-1751 (2017). Citation Format: Penn Whitley, Peter J. Croucher, Barbara Valsasina, Dario Ballinari, Italo Beria, Jeffrey N. Miner, Mark G. Erlander. Computationally predicted sensitivity of clinical cohorts identifies drug relationships and biomarkers associated with response to PCM-075, a PLK1 selective inhibitor [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2810.

Prediction of riveting deformation for thin-walled structures using local-global finite element approach

Riveting is a crucial manufacturing process and widely used in the assembly of aeronautical thin-walled structures, such as wing panels and fuselage panels. However, the dimensional errors of final products often violate the allowed tolerance due to riveting-induced deformation, which significantly degrades the dynamic performance of aircraft and decreases the productivity. In this study, a two-step computational approach, which combines a full 3D dynamic explicit finite element model (FEM) and a local-global FEM with consideration of local bulging, is proposed to evaluate the riveting deformation for thin-walled structures. Firstly, a freedom expanding method was developed to eliminate additional stress, emerging in general connection of solid element and shell element. In addition, the plastic zone after riveting was determined by the cold expansion of hole. Secondly, the inherent deformations of nodes in typical riveted joints involved in thin-walled structure were calculated using the 3D dynamic explicit FEMs and their characteristics were also examined. Thirdly, based on the improved connection method and estimated plastic zone, the local-global FEM was built through equivalent model. Finally, three representative thin-walled riveted structures were simulated using the proposed method. By comparing predicted results and measurements, the accuracy and efficiency of the two-step computational approach are verified.

Monetary policy and large crises in a financial accelerator agent-based model

An accommodating monetary policy followed by a sudden increase of the short term interest rate often leads to a bubble burst and to an economic slowdown. Through the implementation of an Agent Based Model with a financial accelerator mechanism we are able to study the relationship between monetary policy and large-scale crisis events. A two-step computational approach is proposed which performs (i) a pattern search of “double dip” episodes and (ii) counter-factual simulations implementing unconventional monetary policy. The main results can be summarized as follow: a) sudden and sharp increases of the policy rate can generate recessions; b) after a crisis, returning too soon and too quickly to a normal monetary policy regime can generate a “double dip” recession, while c) keeping the short term interest rate anchored to the zero lower bound in the short run can successfully avoid a further slowdown.

Axial dispersion and pressure drop for single-phase flow in annular pulsed disc and doughnut columns: A CFD study

Computational Fluid Dynamics (CFD) simulations have been performed to understand the effects of different operating and geometric parameters on axial dispersion and pressure drop for single-phase flow in annular pulsed disc and doughnut columns (APDDCs) which are relevant for spent nuclear fuel reprocessing. The first step of the two-step computational approach involves solution of Reynolds Averaged Navier-Stokes (RANS) equations with standard k-ε model of turbulence in 2D axisymmetric computational domain to obtain velocity and pressure fields. In the next step, dilute species transport equation is additionally solved to obtain residence time distribution (RTD) and axial dispersion coefficient. The computational approach has been validated by using experimental data of pulsed disc and doughnut columns (PDDCs) reported in literature. The validated computational approach has been used to perform parametric analysis to understand the effects of flow velocity, amplitude of pulsing, disc spacing, percen open area, the ratio of outer diameter and inner diameter of the annulus and flow cross-sectional area on pressure drop and axial dispersion coefficient.

An integrated computational and experimental study uncovers FUT9 as a metabolic driver of colorectal cancer.

Metabolic alterations play an important role in cancer and yet, few metabolic cancer driver genes are known. Here we perform a combined genomic and metabolic modeling analysis searching for metabolic drivers of colorectal cancer. Our analysis predicts FUT9, which catalyzes the biosynthesis of Ley glycolipids, as a driver of advanced‐stage colon cancer. Experimental testing reveals FUT9's complex dual role; while its knockdown enhances proliferation and migration in monolayers, it suppresses colon cancer cells expansion in tumorspheres and inhibits tumor development in a mouse xenograft models. These results suggest that FUT9's inhibition may attenuate tumor‐initiating cells (TICs) that are known to dominate tumorspheres and early tumor growth, but promote bulk tumor cells. In agreement, we find that FUT9 silencing decreases the expression of the colorectal cancer TIC marker CD44 and the level of the OCT4 transcription factor, which is known to support cancer stemness. Beyond its current application, this work presents a novel genomic and metabolic modeling computational approach that can facilitate the systematic discovery of metabolic driver genes in other types of cancer.

A novel statistical approach for identification of the master regulator transcription factor

BackgroundTranscription factors are known to play key roles in carcinogenesis and therefore, are gaining popularity as potential therapeutic targets in drug development. A ‘master regulator’ transcription factor often appears to control most of the regulatory activities of the other transcription factors and the associated genes. This ‘master regulator’ transcription factor is at the top of the hierarchy of the transcriptomic regulation. Therefore, it is important to identify and target the master regulator transcription factor for proper understanding of the associated disease process and identifying the best therapeutic option.MethodsWe present a novel two-step computational approach for identification of master regulator transcription factor in a genome. At the first step of our method we test whether there exists any master regulator transcription factor in the system. We evaluate the concordance of two ranked lists of transcription factors using a statistical measure. In case the concordance measure is statistically significant, we conclude that there is a master regulator. At the second step, our method identifies the master regulator transcription factor, if there exists one.ResultsIn the simulation scenario, our method performs reasonably well in validating the existence of a master regulator when the number of subjects in each treatment group is reasonably large. In application to two real datasets, our method ensures the existence of master regulators and identifies biologically meaningful master regulators. An R code for implementing our method in a sample test data can be found in http://www.somnathdatta.org/software.ConclusionWe have developed a screening method of identifying the ‘master regulator’ transcription factor just using only the gene expression data. Understanding the regulatory structure and finding the master regulator help narrowing the search space for identifying biomarkers for complex diseases such as cancer. In addition to identifying the master regulator our method provides an overview of the regulatory structure of the transcription factors which control the global gene expression profiles and consequently the cell functioning.

Effect of Placing a Probe in an Acoustic Drop Levitator

In this paper, we use computational modeling to explore the effects of placing a probe within the active volume of an acoustic levitator. A two-step computational approach is used to visualize the levitation nodes using thousands of simulated particles driven by the acoustophoretic force and gravity. Our analysis shows that the size and position of a probe can strongly alter the shape, location, and intensity of existing levitation nodes. This has a direct impact on the ability to use acoustic levitation for drop suspension in the presence of disruptive probes.

Theoretical prediction of welding distortion in large and complex structures

Welding technology is widely used to assemble large thin plate structures such as ships, automobiles, and passenger trains because of its high productivity. However, it is impossible to avoid welding-induced distortion during the assembly process. Welding distortion not only reduces the fabrication accuracy of a weldment, but also decreases the productivity due to correction work. If welding distortion can be predicted using a practical method beforehand, the prediction will be useful for taking appropriate measures to control the dimensional accuracy to an acceptable limit. In this study, a two-step computational approach, which is a combination of a thermoelastic-plastic finite element method (FEM) and an elastic finite element with consideration for large deformation, is developed to estimate welding distortion for large and complex welded structures. Welding distortions in several representative large complex structures, which are often used in shipbuilding, are simulated using the proposed method. By comparing the predictions and the measurements, the effectiveness of the two-step computational approach is verified.

A Nearly Exhaustive Search for CpG Islands on Whole Chromosomes

CpG islands are genome subsequences with an unexpectedly high number of CG di-nucleotides. They are typically identified using filtering criteria (e.g., G+C% expected vs. observed CpG ratio and length) and are computed using sliding window methods. Most such studies illusively assume an exhaustive search of CpG islands are achieved on the genome sequence of interest. We devise a Lexis diagram and explicitly show that filtering criteria-based definitions of CpG islands are mathematically incomplete and non-operational. These facts imply that the sliding window methods frequently fail to identify a large percentage of subsequences that meet the filtering criteria. We also demonstrate that an exhaustive search is computationally expensive. We develop the Hierarchical Factor Segmentation (HFS) algorithm, a pattern recognition technique with an adaptive model selection device to overcome the incompleteness and non-operational drawbacks, and to achieve effective computations for identifying CpG-islands. The concept of a CpG island "core" is introduced and computed using the HFS algorithm, which is independent from any specific filtering criteria. Upon such a CpG island "core," a CpG-island is constructed using a Lexis diagram. This two-step computational approach provides a nearly exhaustive search for CpG islands that can be practically implemented on whole chromosomes. In a simulation study realistically mimicking CpG-island dynamics through a Hidden Markov Model we demonstrate that this approach retains very high sensitivity and specificity, that is, very low rates of false positives and false negatives. Finally, we apply the HFS algorithm to identify CpG island cores on human chromosome 21.

One-Electron Reduction Potential for Oxygen- and Sulfur-Centered Organic Radicals in Protic and Aprotic Solvents

We estimated one-electron reduction potentials of redox-active organic molecules for a spectrum of eight different functional groups (phenoxyl, p-benzoquinone, phenylthiyl, p-benzodithiyl, carboxyl, benzoyloxyl, carbthiyl, and benzoylthiyl) in protic (water) and aprotic (acetonitrile, N,N-dimethylacetamide) solvents. Electron affinities (EA) were evaluated in a vacuum with high level quantum chemical methods using Gaussian3-MP2 (G3MP2) and Becke 3 Lee, Yang, and Parr functional B3LYP with aug-cc-pVTZ basis set. To evaluate one-electron redox potentials, gas-phase free energies were combined with solvation energies obtained in a two-step computational approach. First, atomic partial charges were determined in a vacuum by the quantum chemical method B3LYP/6-31G(d,p). Second, solvation energies were determined, solving the Poisson equation with these atomic partial charges. Redox potentials computed this way, compared to experimental data for the 21 considered organic compounds in different solvents, yielded overall root-mean-square deviations of 0.058 and 0.131 V using G3MP2 or B3LYP to compute electronic energies, respectively, while B3LYP/6-31G(d,p) was used to compute solvation energies.

Collisional mixing: A two-step computational approach

A new computational approach to collisional mixing is described. Mixing is treated as a random walk process and the slowing down of recoils is treated separately by computer simulation. The method provides relocation cross sections and profiles, and is particularly suitable for studying various effects in marker broadening and marker shift including the role of various generations of recoils. The influences of the first-, second-, third- and higher-order generations are of same order of magnitude on the marker broadening and the shift. Ion-impurity mixing has only little effect on broadening and shift in the studied cases. The calculated ballistic mixing efficiencies are comparable with the experimentally measured mixing efficiencies. The possibility that mixing could be dominated by collisional mixing is discussed.