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Journal of Chemical Information and Modeling

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https://www.readbyqxmd.com/read/28671456/picalculax-improved-prediction-of-isoelectric-point-for-modified-peptides
#1
Esben J Bjerrum, Jan H Jensen, Jakob L Tolborg
The isoelectric point of a peptide is a physicochemical property that can be accurately predicted from the sequence of the peptide when the peptide is built from natural amino acids. Peptides can however have chemical modifications, such as phosphorylations, amidations, and unnatural amino acids, which can result in erroneous predictions if not accounted for. Here we report on an open source program, pICalculax, which in an extensible way can handle pI calculations of modified peptides. Tests on a database of modified peptides and experimentally determined pI values show an improvement in pI predictions when taking the modifications into account...
July 21, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28727915/improving-accuracy-diversity-and-speed-with-prime-macrocycle-conformational-sampling
#2
Dan Sindhikara, Steven A Spronk, Tyler Day, Ken Borrelli, Daniel L Cheney, Shana L Posy
A novel method for exploring macrocycle conformational space, Prime Macrocycle Conformational Sampling (Prime-MCS), is introduced and evaluated in the context of other available algorithms (Molecular Dynamics, LowModeMD in MOE, and MacroModel Baseline Search). The algorithms were benchmarked on a dataset of 208 macrocycles which was curated for diversity from the Cambridge Structural Database, the Protein Databank, and the Biologically Interesting Molecule Reference Dictionary. The algorithms were evaluated in terms of accuracy (ability to reproduce the crystal structure), diversity (coverage of conformational space), and computational speed...
July 20, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28727421/shallow-representation-learning-via-kernel-pca-improves-qsar-modelability
#3
Stefano E Rensi, Russ B Altman
Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure activity relationships (QSAR), but have been eclipsed in performance by non-linear methods. Support vector machines (SVMs) and neural networks are currently among the most popular and accurate QSAR methods because they learn new representations of the data that greatly improve modelability. In this work we use shallow representation learning to improve the accuracy of L1 regularized logistic regression (LASSO) and meet the performance of Tanimoto SVM...
July 20, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28691805/how-does-the-p7c3-series-of-neuroprotective-small-molecules-prevent-membrane-disruption
#4
Amin Reza Zolghadr, Maryam Heydari Dokoohaki
Molecular dynamics (MD) simulations are conducted to suggest a mechanism of action for the aminopropyl dibromocarbazole derivative (P7C3) small molecule, which protects neurons from apoptotic cell death. At first, the influence of embedded Aβ42 stacks on the structure of membrane is studied. Then, the effect of P7C3 molecules on the Aβ42 fibril enriched membrane and Aβ42 fibril depleted membrane (when Aβ42 fibrils are originally dissolved in the aqueous phase) are evaluated. Also, the formation of an amyloid ion channel in the Aβ42 enriched membrane is examined by calculating deuterium order parameter, density profile, and surface thickness...
July 20, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28723151/fusion-of-structure-and-ligand-based-methods-for-identification-of-novel-cdk2-inhibitors
#5
Priya Mahajan, Gousia Chashoo, Monika Gupta, Amit Kumar, Parvinder Pal Singh, Amit Nargotra
Cyclin dependent kinases plays a central role in cell cycle regulation which makes them a promising target with multifarious therapeutic potential. CDK2 regulates various events of the eukaryotic cell division cycle and the pharmacological evidences indicated that over expression of CDK2 causes abnormal cell-cycle regulation, which was directly associated with hyper proliferation of cancer cells. Therefore, CDK2 is regarded as a potential target molecule for anti-cancer medication. Thus to decline CDK2 activity by potential lead compounds has proved to be an effective treatment for cancer...
July 19, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28723087/developing-collaborative-qsar-models-without-sharing-structures
#6
Peter Gedeck, Suzanne Skolnik, Stephane Rodde
It is widely understood that QSAR models greatly improve if more data are used. However, irrespective of model quality, once chemical structures diverge too far from the initial data set, the predictive performance of a model degrades quickly. To increase the applicability domain we need to increase the diversity of the training set. This can be achieved by combining data from diverse sources. Public data can be easily included, however proprietary data may be more difficult to add due to intellectual property concerns...
July 19, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28719212/proteochemometrics-based-prediction-of-peptide-binding-to-hla-dp-proteins
#7
Ventsislav Yordanov, Ivan Dimitrov, Irini Doytchinova
Human leukocyte antigens (HLA) class II proteins are involved in the antigen processing in the antigen presenting cells. They form complexes with antigen peptide fragments. The peptide-HLA protein complexes are presented on the cell surface where they are recognized by helper T cells (Th cells). HLA-DP is one of the three HLA class II loci. The HLA-DP proteins are associated with a significant number of autoimmune diseases, as well as with a susceptibility or resistance to a number of infectious agents. In the present study, we apply proteochemometrics - a method for bioactivity modeling of multiple ligands binding to multiple target proteins - to derive and validate a robust model for peptide binding prediction to 7 most frequent HLA-DP proteins...
July 18, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28718646/exploring-the-relationship-between-nicotinic-acetylcholine-receptor-ligand-size-efficiency-efficacy-and-c-loop-opening
#8
Qianyun Ma, Han-Shen Tae, Guanzhao Wu, Tao Jiang, Rilei Yu
Nicotinic acetylcholine receptors (nAChRs) are ligand-gated ion channels mediating fundamental physiological activities in the nervous system, and have become important targets for drug design. For a long time, the acetylcholine binding protein (AChBP) has been used as surrogate to study the nAChR structure-function. Taking advantage of more than 100 AChBP crystal structures in the Protein DataBank (PDB), we explored the relationship between the size, efficiency and efficacy of nAChR ligands and the C-loop movement...
July 18, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28718641/in-silico-skin-model-a-multiscale-simulation-study-of-drug-transport
#9
Kishore Gajula, Rakesh Gupta, D B Sridhar, Beena Rai
Accurate in-silico models are required to predict the release of drug molecules through skin in order to supplement the in-vivo experiments for faster development/testing of drugs. The upper most layer of the skin, stratum corneum (SC), offers main resistance for permeation of actives. Most of the SC's molecular level models comprise of cholesterol, and phospholipids only, which is far from the reality. In this study we have implemented a multiscale modelling framework to obtain the release profile of three drugs namely Caffeine, Fentanyl and Naphthol through skin SC...
July 18, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28657312/molecular-dynamics-flexible-fitting-simulations-identify-new-models-of-the-closed-state-of-the-cystic-fibrosis-transmembrane-conductance-regulator-protein
#10
Luba Simhaev, Nael A McCarty, Robert C Ford, Hanoch Senderowitz
Cystic fibrosis (CF) is a lethal, genetic disease found in particular in humans of European origin which is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel. The search for CF therapies acting by modulating the impaired function of mutant CFTR will be greatly advanced by high resolution structures of CFTR in different states. To date, two medium resolution electron microscopy (EM) structures of CFTR are available (one of a distant zebrafish (Danio rerio) CFTR ortholog and one of human CFTR)...
July 18, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28715209/comparison-of-the-predictive-performance-and-interpretability-of-random-forest-and-linear-models-on-benchmark-datasets
#11
Richard Liam Marchese Robinson, Anna Palczewska, Jan Palczewski, Nathan Kidley
The ability to interpret the predictions made by quantitative structure activity relationships (QSARs) offers a number of advantages. Whilst QSARs built using non-linear modelling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modelling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting non-linear QSAR models in general and Random Forest in particular...
July 17, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28715190/chemical-topic-modeling-exploring-molecular-datasets-using-a-common-text-mining-approach
#12
Nadine Schneider, Nikolas Fechner, Gregory A Landrum, Nikolaus Stiefl
Big data is one of the key transformative factors which are increasingly influencing all aspects of modern life. Although this transformation brings vast opportunities it also generates novel challenges, not the least of which is organizing and searching this data deluge. The field of medicinal chemistry is not different: more and more data are being generated, for instance by technologies such as DNA encoded libraries, peptide libraries, text mining of large literature corpora, and new in silico enumeration methods...
July 17, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28666387/toolkit-for-the-construction-of-reproducing-kernel-based-representations-of-data-application-to-multidimensional-potential-energy-surfaces
#13
Oliver T Unke, Markus Meuwly
In the early days of computation, slow processor speeds limited the amount of data that could be generated and used for scientific purposes. In the age of big data, the limiting factor usually is the method with which large amounts of data are analyzed and useful information is extracted. A typical example from chemistry are high-level ab initio calculations for small systems, which have nowadays become feasible even if energies at many different geometries are required. Molecular dynamics simulations often require several thousand distinct trajectories to be run...
July 17, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28708399/development-and-validation-of-a-computational-model-ensemble-for-the-early-detection-of-bcrp-abcg2-substrates-during-the-drug-design-stage
#14
Melisa Edith Gantner, Roxana Noemí Peroni, Juan Francisco Morales, María Luisa Villalba, María Esperanza Ruiz, Alan Talevi
Breast Cancer Resistance Protein (BCRP) is an ATP-dependent efflux transporter linked to the multidrug resistance phenomenon in many diseases such as epilepsy and cancer, and a potential source of drug interactions. For those reasons, the early identification of substrates and non-substrates of this transporter during the drug discovery stage is of great interest. We have developed a computational non-linear model ensemble based on conformational independent molecular descriptors using a combined strategy of genetic algorithms, J48 decision tree classifiers and data fusion...
July 14, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28700231/the-hpcadd-nddo-hamiltonian-parameterization
#15
Heike B Thomas, Matthias Hennemann, Patrick Kibies, Franziska Hoffgaard, Stefan Gussregen, Gerhard Hessler, Stefan M Kast, Timothy Clark
A Neglect of Diatomic Differential Overlap (NDDO) Hamiltonian has been parameterized as an electronic component of a polarizable force field. Coulomb and exchange potentials derived directly from the NDDO Hamiltonian in principle can be used with classical potentials, thus forming the basis for a new generation of efficiently applicable multipolar polarizable force fields. The new hpCADD Hamiltonian uses force-field like atom types and reproduces the electrostatic properties (dipole moment, molecular electrostatic potential) and Koopmans' Theorem ionization potentials closely, as demonstrated for a large training set and an independent test set of small molecules...
July 12, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28700230/ligq-a-webserver-to-select-and-prepare-ligands-for-virtual-screening
#16
Leandro Gabriel Radusky, Sergio Ruiz Carmona, Carlos Modenutti, Xavier Barril, Adrian Gustavo Turjanski, Marcelo A Marti
Virtual screening is a powerful methodology to search for new small molecule inhibitors against a desired molecular target. Usually, it involves evaluating thousand of compounds (derived from large databases) in order to select a set of potential binders that will be tested in the wet-lab. The number of tested compounds is directly proportional to the cost, and thus the best possible set of ligands is the one with the highest number of true binders, for the smallest possible compound set size. Therefore, methods that are able to trim down large universal datasets enriching them in potential binders are highly appreciated...
July 12, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28654262/machine-learning-consensus-scoring-improves-performance-across-targets-in-structure-based-virtual-screening
#17
Spencer S Ericksen, Haozhen Wu, Huikun Zhang, Lauren A Michael, Michael A Newton, F Michael Hoffmann, Scott A Wildman
In structure-based virtual screening, compound ranking through a consensus of scores from a variety of docking programs or scoring functions, rather than ranking by scores from a single program, provides better predictive performance and reduces target performance variability. Here we compare traditional consensus scoring methods with a novel, unsupervised gradient boosting approach. We also observed increased score variation among active ligands and developed a statistical mixture model consensus score based on combining score means and variances...
July 12, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28653850/discovery-and-evaluation-of-anti-fibrinolytic-plasmin-inhibitors-derived-from-5-4-piperidyl-isoxazol-3-ol-4-piol
#18
Thomas C Schmidt, Per-Olof Eriksson, David Gustafsson, David Cosgrove, Bente Frølund, Jonas Boström
Inhibition of plasmin has been found to effectively reduce fibrinolysis and to avoid hemorrhage. This can be achieved by addressing its kringle 1 domain with the known drug and lysine analogue tranexamic acid. Guided by shape similarities toward a previously discovered lead compound, 5-(4-piperidyl)isoxazol-3-ol, a set of 16 structurally similar compounds was assembled and investigated. Successfully, in vitro measurements revealed one compound, 5-(4-piperidyl)isothiazol-3-ol, superior in potency compared to the initial lead...
July 12, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28696688/convolutional-embedding-of-attributed-molecular-graphs-for-physical-property-prediction
#19
Connor W Coley, Regina Barzilay, William H Green, Tommi S Jaakkola, Klavs F Jensen
The task of learning an expressive molecular representation is central to developing quantitative structure-activity and property relationships. Traditional approaches rely on group additivity rules, empirical measurements or parameters, or generation of thousands of descriptors. In this paper, we employ a convolutional neural network for this embedding task by treating molecules as undirected graphs with attributed nodes and edges. Simple atom and bond attributes are used to construct atom-specific feature vectors that take into account the local chemical environment using different neighborhood radii...
July 11, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28696686/free-energy-coupling-between-dna-bending-and-base-flipping
#20
Ning Ma, Arjan van der Vaart
Free energy simulations are presented to probe the energetic coupling between DNA bending and the flipping of a central thymine in double stranded DNA 13mers. The energetics are shown to depend on the neighboring base pairs, and upstream C or T or downstream C tended to make flipping more costly. Flipping to the major groove side was generally preferred. Bending aids flipping, by pushing the system up in free energy, but for small and intermediate bending angles the two were uncorrelated. At higher bending angles, bending and flipping became correlated, and bending primed the system for base flipping toward the major groove...
July 11, 2017: Journal of Chemical Information and Modeling
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