6 resultados para Computational Docking

em Bucknell University Digital Commons - Pensilvania - USA


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Breast cancer is the most common cancer among women, and tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment. Many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Consequently, there is an ongoing need for breast cancer drugs that have different molecular targets. Previous work has shown that 8-mer and cyclic 9-mer peptides inhibit breast cancer in mouse and rat models, interacting with an unsolved receptor, while peptides smaller than eight amino acids did not. We show that the use of replica exchange molecular dynamics predicts the structure and dynamics of active peptides, leading to the discovery of smaller peptides with full biological activity. Simulations identified smaller peptide analogues with the same conserved reverse turn demonstrated in the larger peptides. These analogues were synthesized and shown to inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition.

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Background: Breast cancer is the most common cancer among women. Tamoxifen is the preferred drug for estrogen receptor-positive breast cancer treatment, yet many of these cancers are intrinsically resistant to tamoxifen or acquire resistance during treatment. Therefore, scientists are searching for breast cancer drugs that have different molecular targets. Methodology: Recently, a computational approach was used to successfully design peptides that are new lead compounds against breast cancer. We used replica exchange molecular dynamics to predict the structure and dynamics of active peptides, leading to the discovery of smaller bioactive peptides. Conclusions: These analogs inhibit estrogen-dependent cell growth in a mouse uterine growth assay, a test showing reliable correlation with human breast cancer inhibition. We outline the computational methods that were tried and used along with the experimental information that led to the successful completion of this research.

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We have investigated the thermodynamics of sulfuric acid dimer hydration using ab initio quantum mechanical methods. For (H2SO4)2(H2O)n where n = 0−6, we employed high-level ab initio calculations to locate the most stable minima for each cluster size. The results presented herein yield a detailed understanding of the first deprotonation of sulfuric acid as a function of temperature for a system consisting of two sulfuric acid molecules and up to six waters. At 0 K, a cluster of two sulfuric acid molecules and one water remains undissociated. Addition of a second water begins the deprotonation of the first sulfuric acid leading to the di-ionic species (the bisulfate anion HSO4−, the hydronium cation H3O+, an undissociated sulfuric acid molecule, and a water). Upon the addition of a third water molecule, the second sulfuric acid molecule begins to dissociate. For the (H2SO4)2(H2O)3 cluster, the di-ionic cluster is a few kcal mol−1 more stable than the neutral cluster, which is just slightly more stable than the tetra-ionic cluster (two bisulfate anions, two hydronium cations, and one water). With four water molecules, the tetra-ionic cluster, (HSO4−)2(H3O+)2(H2O)2, becomes as favorable as the di-ionic cluster H2SO4(HSO4−)(H3O+)(H2O)3 at 0 K. Increasing the temperature favors the undissociated clusters, and at room temperature we predict that the di-ionic species is slightly more favorable than the neutral cluster once three waters have been added to the cluster. The tetra-ionic species competes with the di-ionic species once five waters have been added to the cluster. The thermodynamics of stepwise hydration of sulfuric acid dimer is similar to that of the monomer; it is favorable up to n = 4−5 at 298 K. A much more thermodynamically favorable pathway forming sulfuric acid dimer hydrates is through the combination of sulfuric acid monomer hydrates, but the low concentration of sulfuric acid relative to water vapor at ambient conditions limits that process.

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Collision-induced dissociation (CID) of peptides using tandem mass spectrometry (MS) has been used to determine the identity of peptides and other large biological molecules. Mass spectrometry (MS) is a useful tool for determining the identity of molecules based on their interaction with electromagnetic fields. If coupled with another method like infrared (IR) vibrational spectroscopy, MS can provide structural information, but in its own right, MS can only provide the mass-to-charge (m/z) ratio of the fragments produced, which may not be enough information to determine the mechanism of the collision-induced dissociation (CID) of the molecule. In this case, theoretical calculations provide a useful companion for MS data and yield clues about the energetics of the dissociation. In this study, negative ion electrospray tandem MS was used to study the CID of the deprotonated dipeptide glycine-serine (Gly-Ser). Though negative ion MS is not as popular a choice as positive ion MS, studies by Bowie et al. show that it yields unique clues about molecular structure which complement positive ion spectroscopy, such as characteristic fragmentations like the loss of formaldehyde from the serine residue.2 The increase in the collision energy in the mass spectrometer alters the flexibility of the dipeptide backbone, enabling isomerizations (reactions not resulting in a fragment loss) and dissociations to take place. The mechanism of the CID of Gly-Ser was studied using two computational methods, B3LYP/6-311+G* and M06-2X/6-311++G**. The main pathway for molecular dissociation was analyzed in 5 conformers in an attempt to verify the initial mechanism proposed by Dr. James Swan after examination of the MS data. The results suggest that the loss of formaldehyde from serine, which Bowie et al. indicates is a characteristic of the presence of serine in a protein residue, is an endothermic reaction that is made possible by the conversion of the translational energy of the ion into internal energy as the ion collides with the inert collision gas. It has also been determined that the M06-2X functional¿s improved description of medium and long-range correlation makes it more effective than the B3LYP functional at finding elusive transition states. M06-2X also more accurately predicts the energy of those transition states than does B3LYP. A second CID mechanism, which passes through intermediates with the same m/z ratio as the main pathway for molecular dissociation, but different structures, including a diketopiperazine intermediate, was also studied. This pathway for molecular dissociation was analyzed with 3 conformers and the M06-2X functional, due to its previously determined effectiveness. The results suggest that the latter pathway, which meets the same intermediate masses as the first mechanism, is lower in overall energy and therefore a more likely pathway of dissociation than the first mechanism.

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Cold-formed steel (CFS) combined with wood sheathing, such as oriented strand board (OSB), forms shear walls that can provide lateral resistance to seismic forces. The ability to accurately predict building deformations in damaged states under seismic excitations is a must for modern performance-based seismic design. However, few static or dynamic tests have been conducted on the non-linear behavior of CFS shear walls. Thus, the purpose of this research work is to provide and demonstrate a fastener-based computational model of CFS wall models that incorporates essential nonlinearities that may eventually lead to improvement of the current seismic design requirements. The approach is based on the understanding that complex interaction of the fasteners with the sheathing is an important factor in the non-linear behavior of the shear wall. The computational model consists of beam-column elements for the CFS framing and a rigid diaphragm for the sheathing. The framing and sheathing are connected with non-linear zero-length fastener elements to capture the OSB sheathing damage surrounding the fastener area. Employing computational programs such as OpenSees and MATLAB, 4 ft. x 9 ft., 8 ft. x 9 ft. and 12 ft. x 9 ft. shear wall models are created, and monotonic lateral forces are applied to the computer models. The output data are then compared and analyzed with the available results of physical testing. The results indicate that the OpenSees model can accurately capture the initial stiffness, strength and non-linear behavior of the shear walls.