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Journal of Chemical Information and Modeling

Hubert Li, Manbir Sandhu, Linda H Malkas, Robert J Hickey, Nagarajan Vaidehi
Proliferating cell nuclear antigen (PCNA) is a member of the family of sliding clamp proteins that serves as a clamp during DNA repair, DNA replication, cell cycle control, and multiple forms of chromatin modification. PCNA functions as a homotrimer and complexes with multiple proteins in order to carry out each of these varied functions. PCNA binds to different partner proteins in the same region of its structure, called the " interdomain connecting loop", but with different affinities. This interdomain connecting loop is an intrinsically disordered region that takes different conformations when binding to different partner proteins...
November 17, 2017: Journal of Chemical Information and Modeling
Melanie L Aprahamian, Svetlana B Tikunova, Morgan V Price, Andres F Cuesta, Jonathan P Davis, Steffen Lindert
Calcium-dependent cardiac muscle contraction is regulated by the protein complex troponin. Calcium binds to the N-terminal domain of troponin C (cNTnC) which initiates the process of contraction. Heart failure is a consequence of a disruption of this process. With the prevalence of this condition, a strong need exists to find novel compounds to increase the calcium sensitivity of cNTnC. Desirable are small chemical molecules that bind to the interface between cTnC and the cTnI switch peptide and exhibit calcium sensitizing properties by possibly stabilizing cTnC in an open conformation...
November 16, 2017: Journal of Chemical Information and Modeling
Charles H Reynolds, Ryan C Reynolds
Group additivity is a concept that has been successfully applied to a variety of thermochemical and kinetic properties. This includes drug discovery, where functional group additivity is often assumed in ligand binding. Ligand efficiency can be recast as a special case of group additivity where ΔG/HA is the group equivalent (HA is the number of non-hydrogen atoms in a ligand). Analysis of a large data set of protein-ligand binding affinities (Ki) for diverse targets shows that in general ligand binding is distinctly nonlinear...
November 16, 2017: Journal of Chemical Information and Modeling
Shuang Hou, Ruo-Xu Gu, Dong-Qing Wei
Destabilization of cellular ionic homeostasis by toxic β-amyloid (Aβ) channels/barrels, which is a pathogenic mechanism for Alzheimer's disease (AD), is inhibited by a novel anti-AD drug candidate wgx-50 significantly in our previous biological experiments. In this work, molecular dynamics simulations are conducted to investigate wgx-50-Aβ channels/barrels interactions, as well as the ion conductance inhibition mechanism. Ion influx from the extracellular side to the central pore, which is found in apo-form simulations, is blocked by wgx-50 ligands that bind to the hydrophobic rings at the entrance of the channels/barrels...
November 15, 2017: Journal of Chemical Information and Modeling
Themis Lazaridis, Gerhard Hummer
An important limitation of standard classical molecular dynamics simulations is the inability to make or break chemical bonds. This restricts severely our ability to study processes that involve even the simplest of chemical reactions, the transfer of a proton. Existing approaches for allowing proton transfer in the context of classical mechanics are rather cumbersome and have not achieved widespread use and routine status. Here we reconsider the combination of molecular dynamics with periodic stochastic proton hops...
November 14, 2017: Journal of Chemical Information and Modeling
Stephanie K Ashenden, Thierry Kogej, Ola Engkvist, Andreas Bender
It is well-established that the number of publications of novel small molecule modulators, and their associated targets, has increased over the years. This work focuses on publishing trends over the years with a particular focus on the comparison between patents and scientific literature which is accessible via the ChEMBL and GOSTAR databases. More precisely, the patents and scientific literature associated with bioactive molecules and their target annotations have been compared to identify where novelty (in the meaning of the first modulator of a protein target) originated from...
November 14, 2017: Journal of Chemical Information and Modeling
Ariela Vergara-Jaque, Peying Fong, Jeffrey Comer
Several apical iodide translocation pathways have been proposed for iodide efflux out of thyroid follicular cells, including a pathway mediated by the sodium-coupled monocarboxylate transporter 1 (SMCT1), which remains controversial. Herein, we evaluate structural and functional similarities between SMCT1 and the well-studied sodium-iodide symporter (NIS) that mediates the first step of iodide entry into the thyroid. Free-energy calculations using a force field with electronic polarizability verify the presence of a conserved iodide-binding pocket between the TM2, TM3, and TM7 segments in hNIS, where iodide is coordinated by Phe67, Gln72, Cys91, and Gln94...
November 13, 2017: Journal of Chemical Information and Modeling
Richard Lonsdale, Jonathan Burgess, Nicola Colclough, Nichola L Davies, Eva M Lenz, Alexandra Orton, Richard A Ward
Targeted covalent inhibition is an established approach for increasing the potency and selectivity of potential drug candidates, as well as identifying potent and selective tool compounds for target validation studies. It is evident that identification of reversible recognition elements is essential for selective covalent inhibition, but this must also be achieved with the appropriate level of inherent reactivity of the reactive functionality (or 'warhead'). Structural changes that increase or decrease warhead reactivity, guided by methods to predict the effect of those changes, have the potential to tune warhead reactivity and negate issues related to potency and/or toxicity...
November 13, 2017: Journal of Chemical Information and Modeling
Yeu-Chern Harn, Bo-Han Su, Yuan-Ling Ku, Olivia A Lin, Cheng-Fu Chou, Yufeng Jane Tseng
Identification of the individual chemical constituents of a mixture, especially solutions extracted from medicinal plants, is a time-consuming task. The identification results are often limited by challenges such as the development of separation methods and the availability of known reference standards. A novel structure elucidation system, NP-StructurePredictor, is presented and used to accelerate the process of identifying chemical structures in a mixture based on a branch and bound algorithm combined with a large collection of natural product databases...
November 13, 2017: Journal of Chemical Information and Modeling
Simone Fulle, Samo Turk, Benjamin Merget, Friedrich Rippmann
Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with machine learning (ML) approaches to extrapolate to novel compounds. The here introduced MMP/ML method combines a fragment-based MMP implementation with different machine learning methods to obtain automated SAR decomposition and prediction. To test the prediction capabilities and model transferability, two different compound optimization scenarios were designed: (1) 'new fragments' that occurs when exploring new fragments for a defined compound series, and (2) 'new static core and transformations' that resembles for instance the identification of a new compound series...
November 13, 2017: Journal of Chemical Information and Modeling
Yijie Ding, Jijun Tang, Fei Guo
Identifying protein-ligand binding sites is an important process in drug discovery and structure-based drug design. Traditional experimental methods are expensive and time-consuming for detecting protein-ligand binding sites. Therefore, computational approaches provide many effective strategies to deal with this issue. In recent years, most of computational methods are based on structure information of proteins. However, these methods are limited in the common scenario, where both the sequence of protein target is known and sufficient 3D structure information is available...
November 10, 2017: Journal of Chemical Information and Modeling
Luca Belmonte, Sheref S Mansy
A new R tool is described that rapidly identifies, ranks, and clusters sequence patterns coordinated to metallocofactors. This tool, PdPDB, fills a void because unlike currently available tools, PdPDB searches through sequences with metal coordination as the primary determinant and can identify patterns consisting of amino acids, nucleotides, and small molecule ligands at once. PdPDB was tested by analyzing structures that coordinate Fe2+/3+, [2Fe-2S], [4Fe-4S], Zn2+, and Mg2+ cofactors. PdPDB confirmed previously identified sequence motifs and revealed which residues are enriched, e...
November 8, 2017: Journal of Chemical Information and Modeling
Antoine Marion, Jerzy Góra, Oliver Kracker, Tanja Fröhr, Rafał Latajka, Norbert Sewald, Iris Antes
Peptidomimetics are molecules of particular interest in the context of drug design and development. They are proteolytically and metabolically more stable than their natural peptide counterparts, but still offer high specificity towards their biological targets. In recent years, 1,4- and 1,5-substituted 1,2,3-triazole-based peptidomimetics have emerged as promising lead compounds for design of various inhibitory and tumor-targeting molecules, as well as for synthesis of peptide analogues. The growing popularity of triazole-based peptidomimetics and a constantly broadening range of their application generated a demand for elaborate theoretical investigations by classical molecular dynamics simulations and molecular docking...
November 7, 2017: Journal of Chemical Information and Modeling
Ryuhei Harada, Yasuteru Shigeta
Self-Avoiding Conformational Sampling (SACS) is proposed as an enhanced conformational sampling method for proteins. In SACS, the following conformational resampling is repeated for a given protein: (1) Identifications of newly visited states in a subspace. (2) Conformational resampling with restarting short-time molecular dynamics (MD) simulations from the newly visited states. To identify the newly visited states, a set of history-dependent histograms projected onto the subspace is referred. One is constructed from the trajectories sampled at the current (ith) cycle...
November 7, 2017: Journal of Chemical Information and Modeling
Tomohiro Sato, Noriaki Hashimoto, Teruki Honma
To assist the structural optimization of hit/lead compound during drug discovery, various computational approaches to identify potentially useful bioisosteric conversions have been reported. Here, the preference of chemical fragments to hydrogen bond with specific amino acid residues was used to identify potential bioisosteric conversions. We first compiled a data set of chemical fragments frequently occurring in complex structures contained in Protein Data Bank. We then used a computational approach to determine the amino acids to which these chemical fragments most frequently hydrogen bonded...
November 7, 2017: Journal of Chemical Information and Modeling
Chiduru Watanabe, Hirofumi Watanabe, Kaori Fukuzawa, Lorien J Parker, Yoshio Okiyama, Hitomi Yuki, Shigeyuki Yokoyama, Hirofumi Nakano, Shigenori Tanaka, Teruki Honma
Significant activity changes due to small structural changes (i.e., activity cliffs) of serine/threonine kinase Pim1 inhibitors were studied theoretically using fragment molecular orbital method with molecular mechanics Poisson-Boltzmann surface area (FMO+MM-PBSA) approach. This methodology enabled quantum-chemical calculations for large biomolecules with solvation. In the course of drug discovery targeted Pim1, six benzofuranone-class inhibitors were found to differ only in the position of the indole-ring nitrogen atom...
November 7, 2017: Journal of Chemical Information and Modeling
Li-Na Wang, Shao-Ping Shi, Ping-Ping Wen, Zhi-You Zhou, Jian-Ding Qiu
Identification and systematic analysis of candidates for protein propionylation are crucial steps for understanding its molecular mechanisms and biological functions. Although several proteome-scale methods have been performed to delineate potential propionylated proteins, the majority of lysine-propionylated substrates and their role in pathological physiology still remain largely unknown. By gathering various databases and literatures, experimental prokaryotic propionylation data were collated to be trained in a support vector machine with various features via a three-step feature selection method...
November 7, 2017: Journal of Chemical Information and Modeling
Peter W Kenny
A recent editorial (Aldrich et al. The Ecstasy and Agony of Assay Interference Compounds . J. Chem. Inf. MODEL: 2017 , 57 , 387 - 390 ) is examined critically. When assessing assay hits from screening, it is important to draw a distinction between false positives, that have no effect on target function, and compounds that affect target function through an undesirable mechanism of action. Observation of frequent-hitter behavior for a compound should be regarded as circumstantial evidence, rather than definitive proof, that the compound has interfered with assay readouts or acted through an undesirable mechanism of action...
November 7, 2017: Journal of Chemical Information and Modeling
Kyle V Butler, Ian A MacDonald, Nathaniel A Hathaway, Jian Jin
Small molecule tool compounds have enabled profound advances in life science research. These chemicals are potent, cell active, and selective, and, thus, are suitable for interrogating biological processes. For these chemicals to be useful they must be correctly characterized and researchers must be aware of them. We mined the ChEMBL bioactivity database to identify high quality tool compounds in an unbiased way. We identified 407 best-in-class compounds for 278 protein targets, and these are reported in an annotated data set...
November 2, 2017: Journal of Chemical Information and Modeling
Valentin Goussard, Francois Duprat, Vincent Gerbaud, Jean-Luc Ploix, Gerard Dreyfus, Véronique Nardello-Rataj, Jean Marie Aubry
The efficiency of four modeling approaches, namely group contributions, corresponding-states principle, σ-moment-based neural networks, and graph machines, are compared for the estimation of the surface tension (ST) of 269 pure liquid compounds at 25 °C from their molecular structure. This study focuses on liquids containing only carbon, oxygen, hydrogen or silicon atoms since our purpose is to predict the surface tension of cosmetic oils. Neural network estimations are performed from σ-moment descriptors as defined in the COSMO-RS model, while methods based on group contributions, corresponding-states principle and graph machines use 2D molecular information (SMILES codes)...
November 1, 2017: Journal of Chemical Information and Modeling
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