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Molecular Informatics

Hongming Chen, Thierry Kogej, Ola Engkvist
Cheminformatics has established itself as a core discipline within large scale drug discovery operations. It would be impossible to handle the amount of data generated today in a small molecule drug discovery project without persons skilled in cheminformatics. In addition, due to increased emphasis on "Big Data", machine learning and artificial intelligence, not only in the society in general, but also in drug discovery, it is expected that the cheminformatics field will be even more important in the future...
May 18, 2018: Molecular Informatics
Hideshi Ooka, Kazuhito Hashimoto, Ryuhei Nakamura
Understanding the design strategy of photosynthetic and respiratory enzymes is important to develop efficient artificial catalysts for oxygen evolution and reduction reactions. Here, based on a bioinformatic analysis of cyanobacterial oxygen evolution and reduction enzymes (photosystem II: PS II and cytochrome c oxidase: COX, respectively), the gene encoding the catalytic D1 subunit of PS II was found to be expressed individually across 38 phylogenetically diverse strains, which is in contrast to the operon structure of the genes encoding major COX subunits...
May 14, 2018: Molecular Informatics
Pavel Sidorov, Elisabeth Davioud-Charvet, Gilles Marcou, Dragos Horvath, Alexandre Varnek
This paper presents the effort of collecting and curating a data set of 15461 molecules tested against the malaria parasite, with robust activity and mode of action annotations. The set is compiled from in-house experimental data and the public ChEMBL database subsets. We illustrate the usefulness of the dataset by building QSAR models for antimalarial activity and QSPR models for modes of actions, as well as by the analysis of the chemical space with the Generative Topographic Mapping method. The GTM models perform well in prediction of both activity and mode of actions, on par with the classical SVM methods...
May 11, 2018: Molecular Informatics
Fuqiang Ban, Kush Dalal, Eric LeBlanc, Hélène Morin, Paul S Rennie, Artem Cherkasov
Androgen receptor (AR) is a master regulator of prostate cancer (PCa), and therefore is a pivotal drug target for the treatment of PCa including its castration-resistance form (CRPC). The development of acquired resistance is a major challenge in the use of the current antiandrogens. The recent advancements in inhibiting AR activity with small molecules specifically designed to target areas distinct from the receptor's androgen binding site are carefully discussed. Our new classes of AR inhibitors of AF2 and BF3 functional sites and DBD domains designed using cheminformatics techniques are promising to circumvent various AR-dependent resistance mechanisms...
May 7, 2018: Molecular Informatics
Shagun Krishna, Sushil Kumar, Deependra Kumar Singh, Amar Deep Lakra, Dibyendu Banerjee, Mohammad Imran Siddiqi
The histone acetyl transferase (HAT) are involved in acetylation of histones that lead to transcription activation in numerous gene regulatory mechanisms. There are very few GCN5 HAT inhibitors reported despite of their role in cancer progression. In this study, we have utilized in-silico virtual screening approaches based on various machine learning algorithm to identify potent inhibitors of GCN5 HAT from commercially available Maybridge library. We have generated predictive chemoinformatics models based on k-Nearest neighbour, naïve Bayesian, Random Forest and Support Vector Machine...
April 23, 2018: Molecular Informatics
Giuseppe Deganutti, Veronica Salmaso, Stefano Moro
One of the most largely accepted concepts in the G protein-coupled receptors (GPCRs) field is that the ligand, either agonist or antagonist, recognizes its receptor with a stoichiometry of 1 : 1. Recent experimental evidence, reporting ternary complexes formed by GPCR:orthosteric: allosteric ligands, has complicated the ligand-receptor 1 : 1 binding scenario. Molecular modeling simulations have been used to retrieve insights on the whole ligand-receptor recognition process, beyond information on the final bound state provided by experimental techniques...
April 19, 2018: Molecular Informatics
Filip Miljković, Jürgen Bajorath
Kinases are among the most heavily investigated drug targets and inhibition of kinases and kinase-dependent signaling has become a paradigm for therapeutic intervention. Kinase inhibitors and associated activity data have increasing 'big data' character, which presents challenges for computational analysis, but also unprecedented opportunities for learning from compound data and for data-driven medicinal chemistry. Herein, publicly available kinase inhibitor data are evaluated and a number of characteristics are discussed...
March 30, 2018: Molecular Informatics
Akbar Ali, Nenad Trinajstić
In the seminal paper [I. Gutman, N. Trinajstić, Chem. Phys. Lett. 1972, 17, 535-538], it was shown that total electron energy (Eπ ) of any alternant hydrocarbon depends on the sum of the squares of the degrees of the corresponding molecular graph. Nowadays, this sum is known as the first Zagreb index. In the same paper, another molecular descriptor was proved to influence Eπ , but that descriptor was never restudied explicitly. We call this descriptor as modified first Zagreb connection index and denote it by ZC1* ...
March 14, 2018: Molecular Informatics
Melaine A Kuenemann, Patricia A Spears, Paul E Orndorff, Denis Fourches
Peptidoglycan walls of gram positive bacteria are functionalized by glycopolymers called wall teichoic acid (WTA). In Listeria monocytogenes, multiple enzymes including the glucose-1-phosphate uridylyltransferase (GalU) were identified as mandatory for WTA galactosylation, so that the inhibition of GalU is associated with a significant attenuation of Listeria virulence. Herein, we report on a series of in silico predicted GalU inhibitors identified using structure-based virtual screening and experimentally validated to be effective in blocking the WTA galactosylation pathway in vitro...
March 8, 2018: Molecular Informatics
Melaine A Kuenemann, Denis Fourches
The With-No-Lysine (WNK) serine/threonine kinase family constitutes a unique and distinctive branch of the kinome. The four proteins of this family (WNK1/2/3/4) are involved in blood pressure regulation, body fluid, and electrolyte homeostasis. Herein, we modeled and analyzed the binding modes of all publicly-available small orthosteric and allosteric binders (including WNK463 and WNK467) experimentally tested towards any of the WNK family member. To do so, we relied on state-of-the-art cheminformatics approaches including structure-based molecular docking and molecular dynamics simulations...
February 23, 2018: Molecular Informatics
Nisha Saroj Devi, Rajasekar Shanmugam, Jayanta Ghorai, Meera Ramanan, Pazhamalai Anbarasan, Mukesh Doble
The single-target drugs against the arachidonic acid inflammatory pathway are associated with serious side effects, hence, as a first step towards multi-target drugs, we have studied the pharmacophoric features common to the inhibitors of 5-lipoxygenase-activating protein (FLAP), microsomal prostaglandin E-synthase 1 (mPGES-1) and leukotriene A4 hydrolase (LTA4H). FLAP and mPGES-1 shared subfamily-specific positions (SSPs) and four mPGES-1 inhibitors binding to them mapped onto the pharmacophore derived from FLAP inhibitors (Ph-FLAP)...
March 2018: Molecular Informatics
Amina Merzoug, Abdelouahab Chikhi, Abderrahmane Bensegueni, Hanane Boucherit, Sezer Okay
The increasing resistance of bacteria to antibacterial therapy poses an enormous health problem, it renders the development of new antibacterial agents with novel mechanism of action an urgent need. Peptide deformylase, a metalloenzyme which catalytically removes N-formyl group from N-terminal methionine of newly synthesized polypeptides, is an important target in antibacterial drug discovery. In this study, we report the structure-based virtual screening of ZINC database in order to discover potential hits as bacterial peptide deformylase enzyme inhibitors with more affinity as compared to GSK1322322, previously known inhibitor...
March 2018: Molecular Informatics
David Barrios, Carlos Prieto
Data visualization techniques provide new methods for the generation of interactive graphs. These graphs allow a better exploration and interpretation of data but their creation requires advanced knowledge of graphical libraries. Recent packages have enabled the integration of interactive graphs in R. However, R provides limited graphical packages that allow the generation of interactive graphs for computational biology applications. The present project has joined the analytical power of R with the interactive graphical features of JavaScript in a new R package (RJSplot)...
March 2018: Molecular Informatics
Hakan Tahtaci, Hatice Karacık, Abdulilah Ece, Mustafa Er, Mine Gül Şeker
In this study, a novel series of phenyl substituted imidazo[2,1-b][1,3,4]thiadiazole derivatives were synthesized, characterized and explored for antibacterial activity against Gram-negative Escherichia coli, Gram-positive Staphylococcus aureus and Bacillus subtilis and antifungal activity against Candida albicans. Most of the synthesized compounds exhibited remarkable antimicrobial activities, some of which being ten times more potent than positive controls. The most promising compound showed excellent activity with MIC value of 0...
March 2018: Molecular Informatics
Giovanna Cardoso Gajo, Daniela Rodrigues Silva, Stephen J Barigye, Elaine Fontes Ferreira da Cunha
Despite recent advances in Computer Aided Drug Discovery and High Throughput Screening, the attrition rates of drug candidates continue to be high, underscoring the inherent complexity of the drug discovery paradigm. Indeed, a compromise between several objectives is often required to obtain successful clinical drugs. The present manuscript details a multi-objective workflow that integrates the 4D-QSAR and molecular docking methods in the simultaneous modeling of the Rho Kinase inhibitory activity and acute toxicity of Benzamide derivatives...
March 2018: Molecular Informatics
Daniel Șterbuleac, Călin Lucian Maniu
The binding modes of many hERG ion channel blockers are well understood, but a notable exception is clofilium, a potent antiarrhythmic agent whose action relies on blocking the current mediated by hERG. From the previously hypothesized binding modes of clofilium to hERG, only two can explain most of the experimental results. In this study, computer simulations are performed in order to analyze the hypothesized binding modes and to identify the consensus one. This is accomplished by employing molecular dynamics (MD) simulations and interaction energy calculations...
February 21, 2018: Molecular Informatics
Yoshifumi Fukunishi, Yasunobu Yamashita, Tadaaki Mashimo, Haruki Nakamura
We used protein-compound docking simulations to develop a structure-based quantitative structure-activity relationship (QSAR) model. The prediction model used docking scores as descriptors. The binding free energy was approximated by a weighted average of docking scores for multiple proteins. This approximation was based on a pharmacophore model of receptor pockets and compounds. The weights of the docking scores were restricted to small values to avoid unrealistic weights by a regularization term. Additional outlier elimination improved the results...
February 14, 2018: Molecular Informatics
Blaž Škrlj, Tanja Kunej, Janez Konc
Many biological phenomena can be represented as complex networks. Using a protein binding site comparison approach, we generated a network of ion binding sites on the scale of all known protein structures from the Protein Data Bank. We found that this ion binding site similarity network is scale-free, indicating a network in which a few ion binding site scaffolds are the network hubs, and these are connected to hundreds of nodes, whereas the vast majority of nodes have only a few neighbors. Enrichment and statistical analysis of the network components and communities yielded insights into underlying processes from the functional and the structural perspective...
February 8, 2018: Molecular Informatics
Junguk Hur, Larson Danes, Jui-Hua Hsieh, Brett McGregor, Dakota Krout, Scott Auerbach
The US Toxicology Testing in the 21st Century (Tox21) program was established to develop more efficient and human-relevant toxicity assessment methods. The Tox21 program screens >10,000 chemicals using quantitative high-throughput screening (qHTS) of assays that measure effects on toxicity pathways. To date, more than 70 assays have yielded >12 million concentration-response curves. The patterns of activity across assays can be used to define similarity between chemicals. Assuming chemicals with similar activity profiles have similar toxicological properties, we may infer toxicological properties based on its neighbourhood...
January 29, 2018: Molecular Informatics
Gisbert Schneider
No abstract text is available yet for this article.
January 2018: Molecular Informatics
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