journal
MENU ▼
Read by QxMD icon Read
search

Journal of Chemical Information and Modeling

journal
https://www.readbyqxmd.com/read/30226987/in-silico-identification-of-jmjd3-demethylase-inhibitors
#1
Carmen Esposito, Lars Wiedmer, Amedeo Caflisch
In the search for new demethylase inhibitors we have developed a multi-step protocol for in silico screening. Millions of poses generated by high-throughput docking or 3D-pharmacophore search are first minimized by a classical force field and then filtered by semiempirical quantum mechanical calculations of the interaction energy with a selected set of functional groups in the binding site. The final ranking includes solvation effects, which are evaluated in the continuum dielectric approximation (finite-difference Poisson equation)...
September 18, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30223650/an-efficient-lossless-compression-algorithm-for-trajectories-of-atom-positions-and-volumetric-data
#2
Martin Brehm, Martin Thomas
We present our newly developed and highly efficient lossless compression algorithm for trajectories of atom positions and volumetric data. The algorithm is designed as a two-step approach. In a first step, efficient polynomial extrapolation schemes reduce the information entropy of the data by exploiting both spatial and temporal continuity. The second step processes the data by a series of transformations (Burrows-Wheeler, move-to-front, run length encoding), and finally compresses the stream with multi-table canonical Huffman coding...
September 18, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30223645/the-use-of-cluster-expansions-to-predict-the-structures-and-properties-of-surfaces-and-nanostructured-materials
#3
Liang Cao, Chenyang Li, Tim Mueller
The construction of cluster expansions parameterized by first-principles calculations is a powerful tool for calculating properties of materials. In this perspective, we discuss the application of cluster expansions to surfaces and nanomaterials. We review the fundamentals of the cluster expansion formalism and how machine learning is used to improve the predictive accuracy of cluster expansions. We highlight several representative applications of cluster expansions to surfaces and nanomaterials, demonstrating how cluster expansions help researchers build structure-property relationships and enable rational design to accelerate the discovery of new materials...
September 18, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30212210/trans-and-cis-conformations-of-the-antihypertensive-drug-valsartan-respectively-lock-the-inactive-and-active-like-states-of-angiotensin-ii-type-1-receptor-a-molecular-dynamics-study
#4
Lingyun Wang, Feng Yan
Angiotensin II type 1 receptor (AT1R) is the principal regulator of blood pressure in humans. The overactivation of AT1R by the stimulation of angiotensin II would result in high blood pressure. To prevent hypertension, non-peptide 'sartan' drugs, such as valsartan (VST), have been developed to competitively block the access of angiotensin II to the receptor. Nuclear magnetic resonance spectroscopy and molecular modeling studies have identified that VST in solution and in lipid micelles (a mimic membrane environment) has two distinct trans/cis conformations (VSTtrans/VSTcis) which can be transformed to each other through the isomerization of the amide bond...
September 13, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30212197/unique-physicochemical-patterns-of-residues-in-protein-protein-interfaces
#5
Tamas Lazar, Mainak Guharoy, Eva Schad, Peter Tompa
Protein-protein interactions can be characterized by high-resolution structures of complexes, from which diverse features of the interfaces can be derived. For the majority of protein-protein interactions identified, however, there is no information on the structure of the complex or the interface involved in the interaction. Understanding what surface properties drive certain interactions is crucial in the functional evaluation of protein complexes. Here we show that the local patterning of the physicochemical properties of amino acids within surface patches is characteristic of interfaces...
September 13, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30160959/an-orbital-overlap-complement-to-ligand-and-binding-site-electrostatic-potential-maps
#6
Arshad Mehmood, Stephanie I Jones, Peng Tao, Benjamin G Janesko
Orbitals and orbital overlap are important concepts in chemistry but are seldom incorporated into medicinal chemistry analyses of drug-target interactions. Our orbital overlap distance D(r) quantifies the size of the "test orbital" that best overlaps with a system's computed orbitals at point r. The overlap distance provides information about all of the occupied orbitals across a molecule, extending frontier orbital (Fukui) analysis and complementing widely used maps of the surface electrostatic potential...
September 12, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30137983/anion-%C3%AF-interactions-in-computer-aided-drug-design-modeling-the-inhibition-of-malate-synthase-by-phenyl-diketo-acids
#7
Jill F Ellenbarger, Inna V Krieger, Hsiao-Ling Huang, Silvia Gómez-Coca, Thomas R Ioerger, James C Sacchettini, Steven E Wheeler, Kim R Dunbar
Human infection by Mycobacterium tuberculosis (Mtb) continues to be a global epidemic. Computer-aided drug design (CADD) methods are used to accelerate traditional drug discovery efforts. One noncovalent interaction that is being increasingly identified in biological systems but is neglected in CADD is the anion-π interaction. The study reported herein supports the conclusion that anion-π interactions play a central role in directing the binding of phenyl-diketo acid (PDKA) inhibitors to malate synthase (GlcB), an enzyme required for Mycobacterium tuberculosis virulence...
September 12, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30205684/regression-modelability-index-a-new-index-for-the-prediction-of-the-modelability-of-the-datasets-in-the-development-of-qsar-regression-models
#8
Irene Luque Ruiz, Miguel Ángel Gómez-Nieto
The prediction of the capability of a dataset to be modeled by a statistic algorithm in the development of regression QSAR models is an important issue that allows researchers to avoid unnecessary tasks, waste time and/or to depurate the molecule composition of the dataset in order to achieve an improvement of the model's accuracy. In this paper we propose and formulate a new index correlating with the performances of QSAR models. This index, the regression modelability index, requires very low computational cost and is based on the rivality between the nearest neighbors of the molecules of the dataset...
September 11, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30205676/predicting-thermodynamic-properties-of-alkanes-by-high-throughput-force-field-simulation-and-machine-learning
#9
Zheng Gong, Yanze Wu, Liang Wu, Huai Sun
Knowledge of the thermodynamic properties of molecules is essential for chemical process design and the development of new materials. Experimental measurements are often expensive and not environmentally-friendly. In the past, studies using molecular simulations have focused on a specific class of molecules, owing to the lack of a con-sistent force field and simulation protocol. To solve this problem, we have developed a high-throughput force field simulation (HT-FFS) procedure by combining a recently de-veloped general force field with a validated simulation protocol to calculate thermody-namic properties for large number of molecules...
September 11, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30204440/an-analysis-of-different-components-of-a-high-throughput-screening-library
#10
Arjun Saha, Teena Varghese, Annie X Liu, Samantha J Allen, Taraneh Mirzadegan, Michael David Hack
Since many projects at pharmaceutical organizations get their start from a high-throughput screening (HTS) campaign, improving the quality of the HTS deck can improve the likelihood of discovering a high-quality lead molecule that can be progressed to a drug candidate. Over the last decade, Janssen has implemented several strategies for external compound acquisition to augment the screening deck beyond the chemical space and number of molecules synthesized for internal projects. In this report, we analyzed the performance of each of those compound collections in the screening campaigns performed internally within Janssen during the last five years...
September 11, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30199639/pywindow-automated-structural-analysis-of-molecular-pores
#11
Marcin Miklitz, Kim E Jelfs
Structural analysis of molecular pores can yield important information on their behaviour in solution and in the bulk. We developed pywindow, a python package that allows for the automated analysis of structural features of porous molecular materials, such as molecular cages. Our analysis includes the cavity diameter, number of windows, window diameters and average molecular diameter. Molecular dynamics trajectories of molecular pores can also be analysed to explore the influence of flexibility. We present the methodology, validation and application of pywindow for the analysis of molecular pores, metal-organic polyhedra and some instances of framework materials...
September 10, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30199633/gpu-accelerated-molecular-dynamics-and-free-energy-methods-in-amber18-performance-enhancements-and-new-features
#12
Tai-Sung Lee, David S Cerutti, Dan Mermelstein, Charles Lin, Scott LeGrand, Timothy J Giese, Adrian E Roitberg, David A Case, Ross C Walker, Darrin M York
We report progress in GPU-accelerated molecular dynamics and free energy methods in Amber18. Of particular interest is the development of alchemical free energy algorithms, including free energy perturbation and thermodynamic integration methods with support for non-linear softcore potential and parameter interpolation transformation pathways. These methods can be used in conjunction with enhanced sampling techniques such as replica exchange, constant pH molecular dynamics and new 12-6-4 potentials for metal ions...
September 10, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30130104/determinants-of-oligonucleotide-selectivity-of-apobec3b
#13
Jeffrey R Wagner, Özlem Demir, Michael A Carpenter, Hideki Aihara, Daniel A Harki, Reuben S Harris, Rommie E Amaro
APOBEC3B (A3B) is a prominent source of mutation in many cancers. To date, it has been difficult to capture the native protein-DNA interactions that confer A3B's substrate specificity by crystallography due to the highly dynamic nature of wild-type A3B active site. We use computational tools to restore a recent crystal structure of a DNA-bound A3B C-terminal domain mutant construct to its wild type sequence, and run molecular dynamics simulations to study its substrate recognition mechanisms. Analysis of these simulations reveal dynamics of the native A3Bctd-oligonucleotide interactions, including the experimentally inaccessible loop 1-oligonucleotide interactions...
September 10, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30130102/discovering-highly-potent-molecules-from-an-initial-set-of-inactives-using-iterative-screening
#14
Isidro Cortés-Ciriano, Nicholas C Firth, Andreas Bender, Oliver Watson
The versatility of similarity searching and quantitative structure-activity relationships to model the activity of compound sets within given bioactivity ranges (i.e., interpolation) is well established. However, their relative performance in the common scenario in early stage drug discovery where lots of inactive data but no active data points are available (i.e., extrapolation from the low-activity to the high-activity range) has not been thoroughly examined yet. To this aim, we have designed an iterative virtual screening strategy which was evaluated on 25 diverse bioactivity data sets from ChEMBL...
September 10, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30139249/perturbation-theory-machine-learning-study-of-zeolite-materials-desilication
#15
Vincent Blay, Toshiyuki Yokoi, Humbert González-Díaz
Zeolites are important materials for research and industrial applications. Mesopores are often introduced by desilication but other properties are also affected, making its optimization difficult. In this work, we demonstrate that Perturbation Theory and Machine Learning can be combined in a PTML multioutput model describing the effects of desilication. The PTML model achieves a notable accuracy ( R2 = 0.98) in the external validation and can be useful for the rational design of novel materials.
September 7, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30125501/prospectively-validated-proteochemometric-models-for-the-prediction-of-small-molecule-binding-to-bromodomain-proteins
#16
Kathryn A Giblin, Samantha J Hughes, Helen Boyd, Pia Hansson, Andreas Bender
The bromodomain-containing proteins are a ligandable family of epigenetic readers, which play important roles in oncological, cardiovascular, and inflammatory diseases. Achieving selective inhibition of specific bromodomains is challenging, due to the limited understanding of compound and target selectivity features. In this study we build and benchmark proteochemometric (PCM) classification models on bioactivity data for 15,350 data points across 31 bromodomains, using both compound fingerprints and binding site protein descriptors as input variables, achieving a maximum performance as measured by the Matthew's Correlation Coefficient (MCC) of 0...
September 7, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30188699/aflow-chull-cloud-oriented-platform-for-autonomous-phase-stability-analysis
#17
Corey Oses, Eric Gossett, David Hicks, Frisco Rose, Michael J Mehl, Eric Perim, Ichiro Takeuchi, Stefano Sanvito, Matthias Scheffler, Yoav Lederer, Ohad Levy, Cormac Toher, Stefano Curtarolo
A priori prediction of phase stability of materials is a challenging practice, requiring knowledge of all energetically-competing structures at formation conditions. Large materials repositories - housing properties of both experimental and hypothetical compounds - offer a path to prediction through the construction of informatics-based, ab-initio phase diagrams. However, limited access to relevant data and software infrastructure has rendered thermodynamic characterizations largely peripheral, despite their continued success in dictating synthesizability...
September 6, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30148964/only-a-subset-of-normal-modes-is-sufficient-to-identify-linear-correlations-in-proteins
#18
Mustafa Tekpinar, Ahmet Yildirim
Identification of correlated residues in proteins is very important for many areas of protein research such as drug design, protein domain classification, signal transmission, allostery and mutational studies. Pairwise residue correlations in proteins can be obtained from experimental and theoretical ensembles. Since it is difficult to obtain proteins in various conformational states experimentally, theoretical methods such as all-atom molecular dynamics simulations and normal-mode analysis are commonly used methods to obtain protein ensembles and, therefore, pairwise residue correlations...
September 6, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30137980/expanding-the-range-of-force-fields-available-for-oniom-calculations-the-sictwo-interface
#19
W M C Sameera, Feliu Maseras
The ONIOM scheme is one of the most popular QM/MM approaches, but its extended application has been so far hindered by the limited availability of force fields in most practical implementations. This paper describes a simple software code to overcome this limitation, and its application to three representative chemical problems. The "Shell Interface for Combining Tinker With ONIOM" (SICTWO) program gives access to all force fields available in the Tinker molecular mechanics program from a Gaussian09 or Gaussian16 calculation...
September 6, 2018: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/30134653/padfrag-a-database-built-for-the-exploration-of-bioactive-fragment-space-for-drug-discovery
#20
Jing-Fang Yang, Fan Wang, Wen Jiang, Guang-You Zhou, Cheng-Zhang Li, Xiao-Lei Zhu, Ge-Fei Hao, Guang-Fu Yang
Structural analyses of drugs and pesticides can enable the identification of new bioactive compounds with novel and diverse scaffolds as well as improve our understanding of the bioactive fragment space. The Pesticide And Drug Fragments (PADFrag) database is a unique bioinformatic-cheminformatic cross-referencing resource that combines detailed bioactive fragment data and potential targets with a strong focus on quantitative, analytic, and molecular-scale information for the exploration of bioactive fragment space for drug discovery ( http://chemyang...
September 6, 2018: Journal of Chemical Information and Modeling
journal
journal
40805
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"