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Journal of Chemical Information and Modeling

Hao Sha, Fangqiang Zhu
HIV-1 capsid proteins (CAs) assemble into a capsid that encloses the viral RNA. The binding between a pair of C-terminal domains (CTDs) constitutes a major interface in both the CA dimers and the large CA assemblies. Here we attempt to use a general residue-level coarse-grained model to describe the interaction between two isolated CTDs in Monte Carlo simulations. With the standard parameters that depend only on the residue types, the model predicts a much weaker binding in comparison to the experiments. Detailed analysis reveals that some Lennard-Jones parameters are not compatible with the experimental CTD dimer structure, thus resulting in an unfavorable interaction energy...
April 20, 2017: Journal of Chemical Information and Modeling
Wei Ye, Tianle Qian, Hao Liu, Ray Luo, Hai-Feng Chen
Allosteric autoinhibition exists in many transcription factors. The ERG proteins exhibit autoinhibition on DNA binding by the C-terminal and N-terminal inhibitory domains (CID and NID). However, the autoinhibition mechanism and allosteric pathway of ERG are unknown. In this study we intend to elucidate the residue-level allosteric mechanism and pathway via a combined approach of computational and experimental analyses. Specifically computational residue-level fluctuation correlation data was analyzed to reveal detailed dynamics signatures in the allosteric autoinhibition process...
April 20, 2017: Journal of Chemical Information and Modeling
Si Chen, Zhiwei Feng, Yun Wang, Shifan Ma, Ziheng Hu, Peng Yang, Yifeng Chai, Xiang-Qun Sean Xie
Tumor Necrosis Factor alpha (TNF-α) is overexpressed in various diseases, and it has been a validated therapeutic target for autoimmune diseases. All therapeutics currently used targeting TNF-α are biomacromolecules, and limited numbers of TNF-α chemical inhibitors have been reported, which makes the identification of small molecule alternatives in urgent need. Recent studies mainly focused on identifying small molecules that directly bind to TNF-α or TNF receptor-1 (TNFR1), and/or inhibit the interaction between TNF-α and TNFR1, and/or regulate related signaling pathways...
April 19, 2017: Journal of Chemical Information and Modeling
Silvia Bonomo, Flemming Steen Jørgensen, Lars Olsen
Cytochrome P450 17A1 (CYP17A1) catalyzes C17 hydroxylation of pregnenolone and progesterone and the subsequent C17-C20 bond cleavage (lyase reaction) to form androgen precursors. Compound I (Cpd I) and peroxo anion (POA) are the heme-reactive species underlying the two reactions. We have characterized the reaction path for both the hydroxylase and lyase reactions using density functional theory (DFT) calculations and the enzyme-substrate interactions by molecular dynamics (MD) simulations. Activation barriers for positions subject to hydroxylase reaction have values close to each other and span from 54 to 60 kJ·mol(-1) with a small preference for 17α hydroxylation, in agreement with experimental observations...
April 19, 2017: Journal of Chemical Information and Modeling
Xin Wang, Fu-Quan Bai, Yingtao Liu, Yu Wang, Hong-Xing Zhang, Zhenyang Lin
The purpose of the work described herein is to design highly efficient photosensitizers (PS) for photodynamic therapy (PDT) in theory. A series of expanded Zn porphyrins have been studied as light-activated PS. Their main photophysical properties are systematically calculated by using density functional theory and its time-dependent extension. The mechanisms of PDT are discussed. All the considered candidates exhibit intense absorption in the therapeutic window (600-800 nm), efficient intersystem crossing, and sufficient energy for singlet molecular oxygen production...
April 19, 2017: Journal of Chemical Information and Modeling
Ying Dong, Bingren Xiang, Ding Du
In QSAR/QSPR modeling, the indispensable way to validate the predictability of a model is to perform its statistical external validation. It is common that division algorithm should be used to select training sets from chemical compound libraries or collections prior to external validations. In this study, division method based on the posterior variance of leave-one-out cross-validation (PVLOO) of Gaussian process (GP) has been developed with the goal of producing more predictive models. Four structurally diverse data sets of good quality are collected from the literature and then redeveloped and validated on the basis of training set selection methods, namely: four kinds of PVLOO based training set selection methods with three types of covariance functions (squared exponential, rational quadratic, and neural network covariance function), the Kennard-Stone algorithm and random division...
April 18, 2017: Journal of Chemical Information and Modeling
Tingting Zhang, Gaurav Sharma, Thomas J Paul, Zachary Hoffmann, Rajeev Prabhakar
In this DFT study, activities of 11 different N2O4, N2O3, and NO2 core containing Zr(IV) complexes, 4,13-diaza-18-crown-6 (I'N2O4), 1,4,10-trioxa-7,13-diazacyclopentadecane (I'N2O3), and 2-(2-methoxy)ethanol (I'NO2), respectively, and their analogues in peptide hydrolysis have been investigated. Based on the experimental information, these molecules were created by altering protonation states (singly protonated, doubly protonated, or doubly deprotonated) and number of their ligands. The energetics of the I'N2O4, and I'NO2 and their analogues predicted that both stepwise and concerted mechanisms occurred either with similar barriers, or the latter was more favorable than the former...
April 18, 2017: Journal of Chemical Information and Modeling
Michael González-Durruthy, Luciane Carla Alberici, Zeki Naal, David T Atique-Sawazaki, Carlos Curti, José Manuel Vázquez-Naya, Humbert Gonzalez-Diaz, Cristian Robert Munteanu
The study of selective toxicity of carbon nanotubes (CNT) on mitochondria (CNT-mitotoxicity) is of major interest for future biomedical applications. In the current work, the mitochondrial oxygen consumption (E3) is measured under three experimental conditions by exposure to pristine and oxidized CNTs (hydroxylated and carboxylated). Respiratory functional assays showed that the information of the CNT-Raman spectroscopy could be useful to predict structural parameters of mitotoxicity induced by CNTs. The in vitro functional assays show that the mitochondrial oxidative phosphorylation by ATP-synthase (or state V3 of respiration) was not perturbed in isolated rat-liver mitochondria...
April 17, 2017: Journal of Chemical Information and Modeling
Malgorzata N Drwal, Célien Jacquemard, Carlos Perez, Jérémy Desaphy, Esther Kellenberger
The success of fragment-based drug design (FBDD) hinges upon the optimization of low molecular weight compounds (MW<300) with weak binding affinities to lead compounds with high affinity and selectivity. Usually, structural information from fragment-protein complexes is used to develop ideas about the binding mode of similar, but drug-like molecules. In this regard, crystallization additives such as cryoprotectants or buffer components, highly abundant in crystal structures, are frequently ignored. Thus, the aim of the study was the investigation of the information present in both protein complexes with fragments as well as additives and how they relate to the binding modes of their drug-like counterparts...
April 17, 2017: Journal of Chemical Information and Modeling
Shilva Kayastha, Dragos Horvath, Erik Gilberg, Michael Gütschow, Jürgen Bajorath, Alexandre Varnek
Identification of "privileged structural motifs" associated with specific target families is of particular importance for designing novel bioactive compounds. Here, we demonstrate that they can be extracted from a data distribution represented on a two-dimensional map obtained by Generative Topographic Mapping (GTM) . In GTM, structurally related molecules are grouped together on the map. Zones of the map preferentially populated by target-specific compounds were delineated, which helped to capture common substructures on the basis of which these compounds were grouped together by the GTM...
April 14, 2017: Journal of Chemical Information and Modeling
Yuna Yan, Maoyou Yang, Changge Ji, John Z H Zhang
The theoretical calculation of protein-protein binding free energy is a grand challenge in computational biology. Accurate prediction of critical residues along with their specific and quantitative contributions to protein-protein binding free energy is extremely helpful to reveal binding mechanisms and identify drug-like molecules that alter protein-protein interactions. In this paper, we propose an interaction entropy approach combined with the MM/GBSA method for solvation to compute residue-specific protein-protein binding free energy...
April 13, 2017: Journal of Chemical Information and Modeling
Érica C M Nascimento, Mónica Oliva, Katarzyna Świderek, João B L Martins, Juan Andrés
In the present study, the binding free energy of some classical inhibitors (DMT, DNP, GNT, HUP, THA) with acetylcholinesterase (AChE) is calculated by means of the free energy perturbation (FEP) method based on hybrid quantum mechanics and molecular mechanics (QM/MM) potentials. The results highlight the key role of the van der Waals interaction for the inhibition process, since the contribution of this term to the binding free energy is almost as decisive as the electrostatic one. The analysis of the geometrical parameters and the interaction energy per residue along the QM/MM molecular dynamics (MD) simulations highlights the most relevant interactions in the different AChE-ligand systems, showing that the charged residues with a more prominent contribution to the interaction energy are Asp72 and Glu199, although the relative importance depends on the molecular size of the ligand...
April 13, 2017: Journal of Chemical Information and Modeling
Sereina Riniker
While the use of machine-learning (ML) techniques is well established in cheminformatics for the prediction of physicochemical properties and binding affinities, the training of ML models based on data from molecular dynamics (MD) simulations remains largely unexplored. Here, we present a fingerprint termed MDFP which is constructed from the distributions of properties such as potential-energy components, radius of gyration, and solvent-accessible surface area extracted from MD simulations. The corresponding fingerprint elements are the first two statistical moments of the distributions and the median...
April 12, 2017: Journal of Chemical Information and Modeling
Aleksejs Kontijevskis
The emergence of the DNA-encoded chemical libraries (DEL) field in the past decade has attracted the attention of the pharmaceutical industry as a powerful mechanism for the discovery of novel drug-like hits for various biological targets. Nuevolution Chemetics technology enables DNA-encoded synthesis of billions of chemically diverse drug-like small molecule compounds, and the efficient screening and optimization of these, facilitating effective identification of drug candidates at an unprecedented speed and scale...
April 12, 2017: Journal of Chemical Information and Modeling
Berhane Temelso, Joel M Mabey, Toshiro Kubota, Nana A Appiah-Padi, George C Shields
When assessing the similarity between two isomers whose atoms are ordered identically, one typically translates and rotates their Cartesian coordinates for best alignment and computes the pairwise root mean square deviation (RMSD). However, if the atoms are ordered differently or the molecular axes are switched, it is necessary to find the best ordering of the atoms and check for optimal axes before calculating a meaningful pairwise RMSD. The factorial scaling of finding the best ordering by looking at all permutations is too expensive for any system with more than ten atoms...
April 11, 2017: Journal of Chemical Information and Modeling
Seungryong Heo, Juyong Lee, Keehyoung Joo, Hang-Cheol Shin, Jooyoung Lee
We have developed a protein loop structure prediction method by combining a new energy function, which we call EPLM (Energy for Protein Loop Modeling), with the conformational space annealing (CSA) global optimization algorithm. The energy function includes stereo-chemistry, dynamic fragment assembly, distance-scaled finite ideal-gas reference (DFIRE), and generalized orientation-dependent and distance-dependent terms. For the conformational search of loop structures, the CSA algorithm was used, which has been quite successful in dealing with various hard global optimization problems...
April 11, 2017: Journal of Chemical Information and Modeling
Matthew Ragoza, Joshua Hochuli, Elisa Idrobo, Jocelyn Sunseri, David Ryan Koes
Computational approaches to drug discovery can reduce the time and cost associated with experimental assays and enable the screening of novel chemotypes. Structure-based drug design methods rely on scoring functions to rank and predict binding affinities and poses. The ever-expanding amount of protein-ligand binding and structural data enables the use of deep machine learning techniques for protein-ligand scoring. We describe convolutional neural network (CNN) scoring functions that take as input a comprehensive three-dimensional (3D) representation of a protein-ligand interaction...
April 11, 2017: Journal of Chemical Information and Modeling
Raquel Rodríguez-Pérez, Martin Vogt, Jürgen Bajorath
Support vector machine (SVM) modeling is one of the most popular machine learning approaches in chemoinformatics and drug design. The influence of training set composition and size on predictions currently is an underinvestigated issue in SVM modeling. In this study, we have derived SVM classification and ranking models for a variety of compound activity classes under systematic variation of the number of positive and negative training examples. With increasing numbers of negative training compounds, SVM classification calculations became increasingly accurate and stable...
April 10, 2017: Journal of Chemical Information and Modeling
Shota Uehara, Shigenori Tanaka
Protein flexibility is a major hurdle in current structure-based virtual screening (VS). In spite of the recent advances in high-performance computing, protein-ligand docking methods still demand tremendous computational cost to take into account the full degree of protein flexibility. In this context, ensemble docking has proven its utility and efficiency for VS studies, but it still needs a rational and efficient method to select and/or generate multiple protein conformations. Molecular dynamics (MD) simulations are useful to produce distinct protein conformations without abundant experimental structures...
April 7, 2017: Journal of Chemical Information and Modeling
Zoltan Antal, Janos Szoverfi, Szilard N Fejer
Computational prediction of native protein-protein interfaces still remains a challenging task. In virus capsid proteins, each protein unit is in contact with copies of itself through several interfaces. The relative strength of the different contacts affects the dynamics of the assembly, especially if the process is hierarchical. We investigate the dimerization of the salt stable CCMV capsid protein using a combination of different computational tools. The best predictions of dimer configurations provided by blind docking with ZDOCK are rescored using geometry optimization with the Amber and Rosetta force fields...
April 6, 2017: Journal of Chemical Information and Modeling
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