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Journal of Chemical Information and Modeling

Zahra Dolatkhah, Shahrzad Javanshir, Ahmad Shahir Sadr, Jaber Hosseini, Soroush Sardari
Series of 4H-chromone-1,2,3,4-tetrahydropyrimidine-5-carboxylates derivatives were synthesized via a three component one-pot condensation of chromone-3-carbaldehyde, alkyl acetoacetate and urea or thiourea, using MCM-41-SO3H as an efficient Nano-catalysts, and evaluated for their anti-cancer activity using a combined in silico docking and molecular dynamics protocol to estimate the binding affinity of the title compounds with the Bcr-Abl oncogene. Two programs, AutoDock 4 and AutoDock Vina software were applied to dock the target protein with synthesized compounds and ATP...
May 19, 2017: Journal of Chemical Information and Modeling
Jaroslaw Polanski, Aleksandra Tkocz
The chemical meaning of the ligand efficiency (LE) metrics is explained in this paper using a large G protein-coupled receptor (GPCR) and kinase structure-activity (IC50, Ki) data set. Although there is a controversy in the literature regarding both the mathematical validity and the performance of LE, it is in common use as an early estimator for drug optimization. Apparently, the numerous con arguments are not convincing enough. We show here for the first time that the main misunderstanding of the chemical meaning of LE is its interpretation as a molecular descriptor connected with a single molecule...
May 19, 2017: Journal of Chemical Information and Modeling
Maho Nakata, Tomomi Shimazaki
Large-scale molecular databases play an essential role in the investigation of various subjects such as the development of organic materials, in silico drug design, and data-driven studies with machine learning. We have developed a large-scale quantum chemistry database based on first-principles methods. Our database currently contains the ground-state electronic structures of 3 million molecules based on density functional theory (DFT) at the B3LYP/6-31G* level, and we successively calculated 10 low-lying excited states of over 2 million molecules via time-dependent DFT with the B3LYP functional and the 6-31+G* basis set...
May 19, 2017: Journal of Chemical Information and Modeling
Melissa Coates Ford, Kerim Babaoglu
The importance of engineering protein stability is well known and has the potential to impact many fields ranging from pharmaceuticals to food sciences. Engineering proteins can be both a time consuming and expensive experimental process. The use of computation is a potential solution to mitigating some of the time and expenses required to engineer a protein. This process has been previously hindered by inaccurate force fields or energy equations and slow computational processors, however improved software and hardware have made this goal much more attainable...
May 18, 2017: Journal of Chemical Information and Modeling
Christina de Bruyn Kops, Nils-Ole Friedrich, Johannes Kirchmair
Prediction of metabolically labile atom positions in a molecule (sites of metabolism) is a key component of the simulation of xenobiotic metabolism as a whole, providing crucial information for the development of safe and effective drugs. In 2008, an exploratory study was published in which sites of metabolism were derived based on molecular shape- and chemical feature-based alignment to a molecule whose site of metabolism (SoM) had been determined by experiments. We present a detailed analysis of the breadth of applicability of alignment-based SoM prediction, including transfer of the approach from a structure- to ligand-based method and extension of the applicability of the models from cytochrome P450 2C9 to all cytochrome P450 isozymes involved in drug metabolism...
May 18, 2017: Journal of Chemical Information and Modeling
Xiuquan Du, Shiwei Sun, Changlin Hu, Yu Yao, Yuanting Yan, Yanping Zhang
The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many proteins variants statistically associated with human disease, nearly all such variants have unknown mechanisms, for example, protein-protein interactions (PPIs). In this study, we address this challenge using a recent machine learning advance-deep neural networks (DNNs). We aim at improving the performance of PPIs prediction and propose a method called DeepPPI (Deep neural networks for Protein-Protein Interactions prediction), which employs deep neural networks to effectively learn the representations of proteins from common protein descriptors...
May 17, 2017: Journal of Chemical Information and Modeling
Benjamin D Sellers, Natalie C James, Alberto Gobbi
Reducing internal strain energy in small molecules is critical for designing potent drugs. Quantum mechanical (QM) and molecular mechanical (MM) methods are often used to estimate these energies. In an effort to determine which methods offer an optimal balance in accuracy and performance, we have carried out torsion scan analyses on 62 fragments. We compared nine QM and four MM methods to reference energies calculated at a higher level of theory: CCSD(T)/CBS single point energies (coupled cluster with single, double, and perturbative triple excitations at the complete basis set limit) calculated on optimized geometries using MP2/6-311+G**...
May 17, 2017: Journal of Chemical Information and Modeling
Jie Xia, Jui-Hua Hsieh, Huabin Hu, Song Wu, Xiang Simon Wang
Structure-based virtual screening (SBVS) has become an indispensable technique for hit identification at the early stage of drug discovery. However, the accuracy of current scoring functions is not high enough to confer success to every targets thus remains to be improved. Precedently, we developed binary pose filter (PF) using knowledge derived from the protein-ligand interface of single X-ray structure of specific target. This novel approach had been validated as an effective way to improve ligand enrichment...
May 16, 2017: Journal of Chemical Information and Modeling
Weilin Zhang, Jianfeng Pei, Luhua Lai
Targeted covalent compounds or drugs have good potency as they can bind to a specific target for a long time with low doses. Most currently known covalent ligands were discovered by chance or by modifying existing non-covalent compounds to make them covalently attached to a nearby reactive residue. Computational methods for novel covalent ligand binding prediction are highly demanded. We performed statistical analysis on protein complexes with covalent ligands attached to cysteine residues. We found that covalent modified cysteine residues have unique features compared to those not attached to covalent ligands, including lower pKa, higher exposure and higher ligand binding affinity...
May 16, 2017: Journal of Chemical Information and Modeling
David Penkler, Ozge Sensoy, Canan Atilgan, Ozlem Tastan Bishop
Hsp70 molecular chaperones play an important role in maintaining cellular homeostasis, and are implicated in a wide array of cellular processes including protein recovery from aggregates, cross membrane protein translocation, and protein biogenesis. Hsp70 consists of two domains, a nucleotide binding domain (NBD) and a substrate binding domain (SBD), each of which communicates via an allosteric mechanism such that the protein interconverts between two functional states, an ATP bound open conformation and an ADP bound closed conformation...
May 15, 2017: Journal of Chemical Information and Modeling
Sheng Tian, Xu Wang, Linlang Li, Xiaohu Zhang, Youyong Li, Feng Zhu, Tingjun Hou, Xuechu Zhen
Among non-dopaminergic strategies for combating Parkinson's disease (PD), antagonism of the A2A adenosine receptor (AR) has emerged to show great potential. In this study, on the basis of two crystal structures of the A2A AR with the best capability to distinguish known antagonists from decoys, docking-based virtual screening (VS) was conducted to identify novel A2A AR antagonists. A total of 63 structurally diverse compounds identified by VS were submitted to experimental testing, and 11 of them exhibited substantial activity against the A2A AR (Ki < 10 μM), including two compounds with Ki below 1 μM (compound 43, 0...
May 15, 2017: Journal of Chemical Information and Modeling
Orkid Coskuner, Vladimir N Uversky
Our recent studies show that the single Tyr residue in the sequence of amyloid-β42 (Aβ42) is reactive toward various ligands, including metals and adenosine trisphospate (see: Coskuner , O. J. Biol. Inorg. Chem. 2016 , 21 , 957 - 973 and Coskuner , O. ; Murray , I. V. J. J. Alzheimer's Dis. 2014 , 41 , 561 - 574 ). However, the exact role of Tyr in the structures of Aβ42 remains unknown. To fill this gap, here we analyzed the role of Tyr and the impact of the Tyr10Ala mutation on the structural ensemble of Aβ42...
May 12, 2017: Journal of Chemical Information and Modeling
Si Chen, Zhiwei Feng, Yun Wang, Shifan Ma, Ziheng Hu, Peng Yang, Yifeng Chai, Xiangqun Xie
Tumor necrosis factor α (TNF-α) is overexpressed in various diseases, and it has been a validated therapeutic target for autoimmune diseases. All therapeutics currently used to target TNF-α are biomacromolecules, and limited numbers of TNF-α chemical inhibitors have been reported, which makes the identification of small-molecule alternatives an urgent need. Recent studies have mainly focused on identifying small molecules that directly bind to TNF-α or TNF receptor-1 (TNFR1), inhibit the interaction between TNF-α and TNFR1, and/or regulate related signaling pathways...
May 11, 2017: Journal of Chemical Information and Modeling
Prashant Joshi, Glen J P McCann, Vinay Sonawane, Ram A Vishwakarma, Bhabatosh Chaudhuri, Sandip B Bharate
Target structure-guided virtual screening (VS) is a versatile, powerful and inexpensive alternative to experimental high-throughput screening (HTS). In order to discover potent CYP1A1 enzyme inhibitors for cancer chemoprevention, a commercially library of 50,000 small molecules was utilized for VS guided by both ligand and structure-based strategies. For experimental validation, 300 ligands were proposed based on combined analysis of fitness scores from ligand based e-pharmacophore screening and docking score, prime MMGB/SA binding affinity and interaction pattern analysis from structure-based VS...
May 10, 2017: Journal of Chemical Information and Modeling
Rodolpho C Braga, Vinicius M Alves, Eugene N Muratov, Judy Strickland, Nicole Kleinstreuer, Alexander Trospsha, Carolina Horta Andrade
Chemically induced skin sensitization is a complex immunological disease with a profound impact on quality of life and working ability. Despite some progress in developing alternative methods for assessing the skin sensitization potential of chemical substances, there is no in vitro test that correlates well with human data. Computational QSAR models provide a rapid screening approach and contribute valuable information for the assessment of chemical toxicity. We describe the development of a freely accessible web-based and mobile application for the identification of potential skin sensitizers...
May 10, 2017: Journal of Chemical Information and Modeling
Yanmin Zhang, Lu Wang, Qing Zhang, Gaoyuan Zhu, Zhimin Zhang, Zhou Xiang, Yadong Chen, Tao Lu, Weifang Tang
While selective BRafV600E inhibitors have been proven effective clinically, acquired resistance rapidly develops through reactivation of MAPK pathway. Simultaneous targeting of multiple nodes in the pathway offers the prospect of enhanced efficacy as well as reduced potential for acquired resistance. Replacement pyridine group of Y-1 by cyclopropyl formamide group afforded I-01 as a novel multi-targeted kinase inhibitor template. I-01 displayed enzyme potency against Pan-Raf and RTKs. Based on the binding mode of I-01, analogues I-02~I-18 were designed and synthesized...
May 9, 2017: Journal of Chemical Information and Modeling
Noureldin Saleh, Passainte Ibrahim, Giorgio Saladino, Francesco Luigi Gervasio, Timothy Clark
A generally applicable metadynamics scheme for predicting the free energy profile of ligand binding to G-protein-coupled receptors (GPCRs) is described. A common and effective collective variable (CV) has been defined using the ideally placed and highly conserved Trp6.48 as a reference point for ligand-GPCR distance measurement and the common orientation of GPCRs in the cell membrane. Using this single CV together with well-tempered multiple-walker metadynamics with a funnel-like boundary allows an efficient exploration of the entire ligand binding path from the extracellular medium to the orthosteric binding site, including vestibule and intermediate sites...
May 8, 2017: Journal of Chemical Information and Modeling
Xinya Han, Xiuyun Zhu, Zongqin Hong, Lin Wei, Yanliang Ren, Fen Wan, Shuaihua Zhu, Hao Peng, Li Guo, Li Rao, Lingling Feng, Jian Wan
Class II fructose-1,6-bisphosphate aldolases (FBA-II) are attractive new targets for the discovery of drugs to combat invasive fungal infection, because they are absent in animals and higher plants. Although several FBA-II inhibitors have been reported, none of these inhibitors exhibit antifungal effect so far. In this study, several novel inhibitors of FBA-II from C. albicans (Ca-FBA-II) with potent antifungal effects were rationally designed by jointly using a specific protocols of molecular docking-based virtual screening, accurate binding-conformation evaluation strategy, synthesis and enzymatic assays...
May 5, 2017: Journal of Chemical Information and Modeling
Jeff Milton, Tianhong Zhang, Claire Bellamy, Eric E Swayze, Christopher E Hart, Markus Weisser, Sabrina Hecht, Sergio Rotstein
HELM Version 2.0 ( Hierarchical Editing Language for Macromolecules ) is a molecular line notation similar to SMILEs but specifically for communicating and managing biopolymer structures. The HELM steering committee, part of the Pistoia Alliance non-profit organization, has been tasked to develop and promote HELM as a global exchange format and recently released version 2.0 of the specification. Here We will describe the specifics of the HELM v2.0 notation along with the large ecosystem of software to support HELM-based structure management...
May 4, 2017: Journal of Chemical Information and Modeling
Jeremy Ash, Denis Fourches
Quantitative Structure-Activity Relationship (QSAR) models typically rely on 2D and 3D molecular descriptors to characterize chemicals and forecast their experimental activities. Previously, we showed that even the most reliable 2D QSAR models and structure-based 3D molecular docking techniques were not capable of accurately ranking a set of known inhibitors for the ERK2 kinase, a key player in various types of cancer. Herein, we calculated and analyzed a series of chemical descriptors computed from the molecular dynamics (MD) trajectories of ERK2-ligand complexes...
May 4, 2017: Journal of Chemical Information and Modeling
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