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Journal of Chemical Information and Modeling

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https://www.readbyqxmd.com/read/28816453/modeling-of-oligosaccharides-within-glycoproteins-from-free-energy-landscapes
#1
Aysegül Turupcu, Chris Oostenbrink
In spite of the abundance of glycoproteins in biological processes, relatively little three-dimensional structural data is available for glycan structures. Here, we study the structure and flexibility of the vast majority of mammalian oligosaccharides appearing in N- and O- glycosylated proteins using a bottom up approach. We report the conformational free-energy landscapes of all relevant glycosidic linkages as obtained from local elevation simulations and subsequent umbrella sampling. To the best of our knowledge, this represents the first complete conformational library for the construction of N- and O-glycan structures...
August 17, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28813151/the-medicinal-and-biological-chemistry-mbc-library-an-efficient-source-on-new-hits
#2
Víctor Sebastián Pérez, Carlos Roca, Mahendra Awale, Jean-Louis Reymond, Ana Martínez, Carmen Gil, Nuria E Campillo
Identification of new hits is one of the biggest challenges in drug discovery. Creating a library of well-characterized drug-like compounds is a key step in this process. Our group has developed an in-house chemical library called Medicinal and Biological Chemistry (MBC) library. This collection has been successfully used to start several medicinal chemistry programs and developed in an accumulation of more than thirty years of experience in drug design and discovery of new drugs for unmet diseases. It contains over 1,000 compounds, mainly heterocyclic scaffolds...
August 16, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28812890/jaqpot-quattro-a-novel-computational-web-platform-for-modelling-and-analysis-in-nanoinformatics
#3
Charalampos Chomenidis, Georgios Drakakis, Georgia Tsiliki, Evangelia Anagnostopoulou, Angelos Valsamis, Philip Doganis, Pantelis Sopasakis, Haralambos Sarimveis
Engineered nanomaterials (ENMs) are increasingly infiltrating our lives due to their applications across multiple fields. However, ENM formulations may result in the modulation of pathways and mechanisms of toxic action that endanger human health and the environment. Alternative testing methods such as in silico approaches are becoming increasingly popular for assessing the safety of ENMs as they are cost- and time- effective. Additionally, computational approaches support the industrial safer-by-design challenge and the REACH legislation objective of reducing animal testing...
August 16, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28763207/inhibition-of-human-enhancer-of-zeste-homolog-2-with-tambjamine-analogs
#4
Martin Kotev, Pilar Manuel-Manresa, Elsa Hernando, Vanessa Soto-Cerrato, Modesto Orozco, Roberto Quesada, Ricardo Pérez-Tomás, Victor Guallar
Combining computational modeling, de novo compound synthesis, and in vitro and cellular assays, we have performed an inhibition study against the enhancer of zeste homolog 2 (EZH2) histone-lysine N-methyltransferase. This enzyme is an important catalytic component of the PRC2 complex whose alterations have been associated with different cancers. We introduce here several tambjamine-inspired derivatives with low micromolar in vitro activity that produce a significant decrease in histone 3 trimethylation levels in cancer cells...
August 16, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28753003/site-of-tagging-influences-the-ochratoxin-recognition-by-peptide-nfo4-a-molecular-dynamics-study
#5
Aby A Thyparambil, Tigran M Abramyan, Ingrid Bazin, Anthony Guiseppi-Elie
Molecular recognition by synthetic peptides is growing in importance in the design of biosensing elements used in the detection and monitoring of a wide variety of hapten bioanlaytes. Conferring specificity via bioimmobilization and subsequent recovery and purification of such sensing elements are aided by the use of affinity tags. However, the tag and its site of placement can potentially compromise the hapten recognition capabilities of the peptide, necessitating a detailed experimental characterization and optimization of the tagged molecular recognition entity...
August 16, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28810126/combined-virtual-screening-and-substructure-search-for-discovery-of-novel-fabp4-inhibitors
#6
Haiyan Cai, Ting Wang, Zhuo Yang, Zhijian Xu, Guimin Wang, Heyao Wang, Weiliang Zhu, Kaixian Chen
Fatty acid-binding protein 4 (FABP4, AFABP) is a potential drug target for diabetes and atherosclerosis. In this study, a series of novel FABP4 inhibitors were discovered through combining virtual screening and substructure search. Seventeen compounds exhibited FABP4 inhibitory activities with IC50 <10 μM, among which eleven compounds showed high selectivity against FABP3. The best compound 36b displayed an IC50 value of 1.5 μM. Molecular docking and point mutation studies revealed that Gln95, Arg126 and Tyr128 play key roles for these compounds binding with FABP4...
August 15, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28810125/cheminformatic-analysis-of-anti-malarial-chemical-space-illuminates-therapeutic-mechanisms-and-offers-strategies-for-therapy-development
#7
Julia Nogueira Varela, María Fernanda Fernanda Lammoglia Cobo, Sandip V Pawar, Vikramaditya G Yadav
The clear and present danger of malaria, which has been amplified in recent years by climate change, and the progressive thinning of our drug arsenal over the past two decades raise uncomfortable questions about the current state and future of anti-malarial drug development. Besides suffering from many of the same technical challenges that affect drug development in other disease areas, the quest for new anti-malarial therapies is also hindered by the complex, dynamic life cycle of the malaria parasite, P. falciparum, in its mosquito and human hosts, and its role thereof in the elicitation of drug resistance...
August 15, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28809487/maximum-likelihood-calibration-of-the-unres-force-field-for-simulation-of-protein-structure-and-dynamics
#8
Pawel Krupa, Anna Halabis, Wioletta Zmudzinska, Stanislaw Oldziej, Harold Abraham Scheraga, Adam Liwo
By using the maximum likelihood method for force-field calibration recently developed in our laboratory, which is aimed at achieving the agreement between the simulated conformational ensembles of selected training proteins and the corresponding ensembles determined experimentally at various temperatures, the physics-based coarse-grained UNRES force field for simulations of protein structure and dynamics was optimized with seven small training proteins exhibiting a variety of secondary and tertiary structures...
August 15, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28805387/polymyxin-binding-to-the-bacterial-outer-membrane-reveals-cation-displacement-and-increasing-membrane-curvature-in-susceptible-but-not-in-resistant-lps-chemotypes
#9
Denys Ewerton da Silva Santos, Laércio Pol-Fachin, Roberto D Lins, Thereza A Soares
Lipid-A is the causative agent of Gram-negative sepsis and responsible for increasingly high mortality rate among hospitalized patients. Compounds that bind Lipid-A can limit this inflammatory process. The cationic antimicrobial peptide polymyxin B (Pmx-B) is one of the simplest molecules capable of selectively bind to Lipid-A, and may serve as a model for further development of Lipid-A binding agents. Gram-negative bacteria resistance to Pmx-B relies on the upregulation of a number of regulatory systems, which promote chemical modifications of the LPS structure, and leads to major changes in the physical-chemical properties of the outer membrane...
August 14, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28805377/intrinsic-dynamics-of-binding-rail-and-its-allosteric-effect-in-the-class-i-hdacs
#10
Jingwei Zhou, Yue Huang, Chunyan Cheng, Kai Wang, Ruibo Wu
The development of novel isoform/class-selective inhibitor is still of great biological and medical significance to conquer the continuously reported side effects for the histone deacetylases (HDACs) drugs. The first potent HDAC allosteric inhibitor was discovered last year and this allosteric inhibitor design is thought to be a promising strategy to overcome the current challenges in HDAC inhibitor design. However, the detailed allosteric mechanisms and its remote regulation effects on the catalytic/inhibitor activity of HDAC are still unclear...
August 14, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28796507/molecular-dynamics-study-to-investigate-the-dimeric-structure-of-the-full-length-%C3%AE-synuclein-in-aqueous-solution
#11
Tingting Zhang, Yuanxin Tian, Zhonghuang Li, Siming Liu, Xiang Hu, Zichao Yang, Xiaotong Ling, Shu-Wen Liu, Jiajie Zhang
The mechanisms of dimerization of α-Synuclein from full-length monomers and the structural features have been investigated through molecular dynamics simulations in this study. The dimerization of α-Syn plays a critical role in the fibrillogenesis mechanism and could initiate and trigger α-Syn to aggregate by conformational transforming. According to the alignment between three regions of α-Syn monomer, 8 diverse starting structures have been constructed. However, only 5 configurations show the dimeric structures and the detailed properties of 3 dimers of them are discussed...
August 10, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28796500/molecular-structure-based-large-scale-prediction-of-chemical-induced-gene-expression-changes
#12
Ruifeng Liu, Mohamed Diwan M AbdulHameed, Anders Wallqvist
The quantitative structure-activity relationship (QSAR) approach has been used to model a wide range of chemical-induced biological responses. However, it had not been utilized to model chemical-induced genome-wide gene expression changes until very recently, owing to the complexity of training and evaluating a very large number of models. To address this issue, we examined the performance of a variable nearest neighbor (v-NN) method that uses information of near neighbors conforming to the principle that similar structures have similar activities...
August 10, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28792217/kinase-crystal-miner-a-powerful-approach-to-repurposing-3d-hinge-binding-fragments-and-its-application-to-finding-novel-bruton-tyrosine-kinase-inhibitors
#13
Prasenjit Mukherjee, Joerg Bentzien, Todd Bosanac, Wang Mao, Michael Burke, Ingo Muegge
Protein kinases represent an important target class for drug discovery because of their role in signaling pathways involved in disease areas such as oncology and immunology. A key element of many ATP-competitive kinase inhibitors is their hinge-binding motif. Here we describe Kinase Crystal Miner (KCM) - a new approach developed at Boehringer Ingelheim (BI) that harvests the existing crystallographic information of kinase-inhibitor co-crystal structures from internal and external databases. About one thousand unique three-dimensional kinase inhibitor hinge binding motifs have been extracted from structures covering more than 180 different protein kinases...
August 9, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28715190/chemical-topic-modeling-exploring-molecular-data-sets-using-a-common-text-mining-approach
#14
Nadine Schneider, Nikolas Fechner, Gregory A Landrum, Nikolaus Stiefl
Big data is one of the key transformative factors which increasingly influences 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...
August 9, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28786670/a-statistical-analysis-on-the-performance-of-mmpbsa-versus-absolute-binding-free-energy-calculations-bromodomains-as-a-case-study
#15
Matteo Aldeghi, Michael J Bodkin, Stefan Knapp, Philip C Biggin
Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. While relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative...
August 8, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28786669/grid-based-surface-generalized-born-model-for-calculation-of-electrostatic-binding-free-energies
#16
Negin Forouzesh, Saeed Izadi, Alexey V Onufriev
Fast and accurate calculation of solvation free energies is central to many applications, such as rational drug design. In this study, we present a grid-based molecular surface implementation of an "R6" flavor of the generalized Born (GB) implicit solvent model, named GBNSR6. The speed, accuracy relative to numerical Poisson-Boltzmann treatment, and sensitivity to grid surface parameters are tested on a set of 15 small protein-ligand complexes, and a set of biomolecules in the range of 268 to 25099 atoms. Our results demonstrate that the proposed model provides a relatively successful compromise between the speed and accuracy of computing polar components of the solvation free energies (ΔGpol) , and binding free energies (ΔΔGpol)...
August 8, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28737911/platform-for-unified-molecular-analysis-puma
#17
Mariana González-Medina, José L Medina-Franco
We introduce a free platform for chemoinformatic-based diversity analysis and visualization of chemical space of user supplied data sets. Platform for Unified Molecular Analysis (PUMA) integrates metrics used to characterize compound databases including visualization of chemical space, scaffold content, and analysis of chemical diversity. The user's input is a file with SMILES, database names, and compound IDs. PUMA computes molecular properties of pharmaceutical relevance, Murcko scaffolds, and diversity analysis...
August 8, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28727915/improving-accuracy-diversity-and-speed-with-prime-macrocycle-conformational-sampling
#18
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 data set of 208 macrocycles which was curated for diversity from the Cambridge Structural Database, the Protein Data Bank, 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...
August 8, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28782945/fame-2-simple-and-effective-machine-learning-model-of-cytochrome-p450-regioselectivity
#19
Martin Šícho, Christina de Bruyn Kops, Conrad Stork, Daniel Svozil, Johannes Kirchmair
We report on the further development of FAst MEtabolizer (FAME; J. Chem. Inf. MODEL: 2013, 53, 2896-2907), a collection of random forest models for the prediction of sites of metabolism (SoMs) of xenobiotics. A broad set of descriptors was explored, from simple 2D descriptors such as those used in FAME, to quantum chemical descriptors employed in some of the most accurate models for SoM prediction currently available. In line with the original FAME approach, our objective was to keep things simple and to come up with accurate and robust models that are based on a small number of 2D descriptors...
August 7, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28727421/shallow-representation-learning-via-kernel-pca-improves-qsar-modelability
#20
Stefano E Rensi, Russ B Altman
Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure-activity relationships (QSARs) but have been eclipsed in performance by nonlinear 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...
August 7, 2017: Journal of Chemical Information and Modeling
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