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Molecular Informatics

Neha Tripathi, Naeem Shaikh, Prasad V Bharatam, Prabha Garg
The enzyme human topoisomerase IIα (hTopoIIα) is an important anticancer drug target. Due to the availability of multiple inhibitor-binding sites in this enzyme, the anti-hTopoII agents possess high chemical diversity. Chemoinformatics methods can be used to identify lead compounds from large databases for hTopoII inhibitory activity and classify them. In this work, we report the use of machine learning methods to develop classification models for the identification of possible anti-hTopoIIα agents and to classify them as catalytic inhibitors vs...
September 14, 2018: Molecular Informatics
Viviana Consonni, Roberto Todeschini, Davide Ballabio, Francesca Grisoni
Quantitative Structure - Activity Relationship (QSAR) models play a central role in medicinal chemistry, toxicology and computer-assisted molecular design, as well as a support for regulatory decisions and animal testing reduction. Thus, assessing their predictive ability becomes an essential step for any prospective application. Many metrics have been proposed to estimate the model predictive ability of QSARs, which have created confusion on how models should be evaluated and properly compared. Recently, we showed that the metric QF32 is particularly well-suited for comparing the external predictivity of different models developed on the same training dataset...
August 24, 2018: Molecular Informatics
Marta Glavatskikh, Timur Madzhidov, Dragos Horvath, Ramil Nugmanov, Timur Gimadiev, Daria Malakhova, Gilles Marcou, Alexandre Varnek
This paper reports SVR (Support Vector Regression) and GTM (Generative Topographic Mapping) modeling of three kinetic properties of cycloaddition reactions: rate constant (logk), activation energy (Ea) and pre-exponential factor (logA). A data set of 1849 reactions, comprising (4+2), (3+2) and (2+2) cycloadditions (CA) were studied in different solvents and at different temperatures. The reactions were encoded by the ISIDA fragment descriptors generated for Condensed Graph of Reaction (CGR). For a given reaction, a CGR condenses structures of all the reactants and products into one single molecular graph, described both by conventional chemical bonds and "dynamical" bonds characterizing chemical transformations...
August 22, 2018: Molecular Informatics
Zhibin Du, Akbar Ali
The Wiener polarity index (usually denoted by Wp ) of an alkane is the number of unordered pairs of carbon atoms which are separated by three carbon-carbon bonds. This topological index Wp is useful for predicting the boiling points of alkanes. Deng [MATCH Commun. Math. Comput. Chem. 66 (2011) 305] proved that the maximum Wp value among all alkanes, with n carbon atoms, is 3n-15 . The main purpose of present paper is to find all those alkanes with n carbon atoms, which attain the maximum value of Wp .
August 9, 2018: Molecular Informatics
César R García-Jacas, Lisset Cabrera-Leyva, Yovani Marrero-Ponce, José Suárez-Lezcano, Fernando Cortés-Guzmán, Luis A García-González
A different perspective to compute global weighted definitions of molecular descriptors from the contributions of each atom (LOVIs) or covalent bond (LOEIs) within a molecule is presented, using the generalized ordered weighted averaging - weighted averaging (GOWAWA) aggregation operator. This operator is rather different from the other norm-, mean- and statistic-based operators used up to date for the descriptors calculation from LOVIs/LOEIs. GOWAWA unifies the generalized ordered weighted averaging (GOWA) and the weighted generalized mean (WGM) functions and, in addition, it uses a smoothing parameter to assign different importance values to both functions depending on the problem under study...
August 2, 2018: Molecular Informatics
Alexandre Borges, Rosana Casoti, Marcio Luis Andrade E Silva, Nayane Larissa da Cunha, Ana Paula da Rocha Pissurno, Daniel Fábio Kawano, Rosangela da Silva de Laurentiz
Encouraged by the anti-inflammatory activity of hinokinin in vivo, which is also observed for the analogues dinitrohinokinin and diidrocubebin, herein we used in vitro and in silico methods to assess their selectivity profiles and predict their binding modes with Cyclooxygenases (COX-1 and 2). The in vitro assays demonstrated dinitrohinokinin is about 13 times more selective for COX-2 than for COX-1, a similar profile observed for the drugs celecoxib (selective index ≈9) and meloxicam (selective index ≈11)...
August 1, 2018: Molecular Informatics
Adriano Luchi, Emilio Angelina, Lucrecia Bogado, Stefano Forli, Arthur Olson, Nélida Peruchena
HIV-1 protease (HIV-PR) performs a vital step in the virus life cycle which makes it an excellent target for drug therapy. However, due to the error-prone of HIV reverse transcriptase, mutations in HIV-PR often occur, inducing drug-resistance to inhibitors. Some HIV-PR mutations can make the flaps of the enzyme more flexible thus increasing the flaps opening rate and inhibitor releasing. It has been shown that by targeting novel binding sites on HIV-PR with small molecules, it is possible to alter the equilibrium of flap conformational states...
July 26, 2018: Molecular Informatics
Manikandan Alagumuthu, Vivek Panyam Muralidharan, Monic Andrew, Mohammed Habeeb Ahmed, Sathiyanarayanan Kulathu Iyer, Sivakumar Arumugam
Developing a new antibacterial drug by using (Z/E)-4-(4-substituted-benzylidene)-2-isoquinoline-1,3(2H,4H)-diones (5a-h) via DNA gyrase inhibition mechanism is the main aim of this study. DNA gyrase inhibition assay was executed to confirm the DNA gyrase inhibition potentials of 5a-h. DNA gyrase inhibitory potentials were further validated through molecular docking. Docking study was also intended to get more insight into the binding mode of 5a-h into the active site of DNA gyrase A. Agar well diffusion method antimicrobial activity on Gram-ve bacteria Escherichia coli (MTCC 443), Pseudomonas aeruginosa (MTCC 424), and Gram+ve bacteria (Staphylococcus aureus (MTCC 96) and Streptococcus pyogenes (MTCC 442) was evaluated...
July 26, 2018: Molecular Informatics
Inge Seim, Andrew M Baker, Lisa K Chopin
High-throughput sequencing has revolutionised biology and medicine. Numerous genomes and transcriptome assemblies are now available, and these genomic data sets lend themselves to comparisons between species, strains, and other strata. Researchers often need to rapidly identify changes, in particular amino acid substitutions that could confer biological function in their system of interest. However, we are not aware of an easy-to-use tool that can be used to detect such changes, and researchers currently rely on idiosyncratic computer code...
July 17, 2018: Molecular Informatics
Farahnaz Rezaei Makhouri, Jahan B Ghasemi
Inhibition protein-protein interactions (PPIs) using small molecules, that interfere with the formation of these complexes, modulates critical regulatory pathways and has therapeutic significance. DBF4-dependent kinase CDC7 is the S-phase checkpoint pathway target, which plays an important role for a proper response to DNA damage and replicative stress in multiple organisms. Overexpression of CDC7 and its protein regulator DBF4 is highly neurotoxic and promotes cancer and neurodegeneration. In the present study, virtual screening of inhibitor scaffolds mimicking DBF4 pharmacophoric properties was carried out and evaluation of their potential inhibitory activity toward CDC7 was performed using high-throughput docking and molecular dynamics simulations...
July 9, 2018: Molecular Informatics
Vitaly P Solov'ev, Yuri A Ustynyuk, Nelly I Zhokhova, Kirill V Karpov
Quantum chemical calculations combined with QSPR methodology reveal challenging perspectives for the solution of a number of fundamental and applied problems. In this work, we performed the PM7 and DFT calculations and QSPR modeling of HOMO and LUMO energies for polydentate N-heterocyclic ligands promising for the extraction separation of lanthanides because these values are related to the ligands selectivity in the respect to the target cations. Data for QSPR modeling comprised the PM7 calculated HOMO and LUMO energies of N-donor heterocycles, including several types of both known and virtual undescribed polydentate ligands...
July 4, 2018: Molecular Informatics
Alexandre Varnek
No abstract text is available yet for this article.
September 2018: Molecular Informatics
Laurent Hoffer, Christophe Muller, Philippe Roche, Xavier Morelli
For several decades, hit identification for drug discovery has been facilitated by developments in both fragment-based and high-throughput screening technologies. However, a major bottleneck in drug discovery projects continues to be the optimization of primary hits from screening campaigns in order to derive lead compounds. Computational chemistry or molecular modeling can play an important role during this hit-to-lead (H2L) stage by both suggesting putative optimizations and decreasing the number of compounds to be experimentally synthesized and evaluated...
September 2018: Molecular Informatics
Marta Glavatskikh, Timur Madzhidov, Igor I Baskin, Dragos Horvath, Ramil Nugmanov, Timur Gimadiev, Gilles Marcou, Alexandre Varnek
Generative Topographic Mapping (GTM) approach was successfully used to visualize, analyze and model the equilibrium constants (KT ) of tautomeric transformations as a function of both structure and experimental conditions. The modeling set contained 695 entries corresponding to 350 unique transformations of 10 tautomeric types, for which KT values were measured in different solvents and at different temperatures. Two types of GTM-based classification models were trained: first, a "structural" approach focused on separating tautomeric classes, irrespective of reaction conditions, then a "general" approach accounting for both structure and conditions...
September 2018: Molecular Informatics
Omer Kaspi, Abraham Yosipof, Hanoch Senderowitz
This work describes the integration of several data mining and machine learning tools for researching Photovoltaic (PV) solar cells libraries into a unified workflow embedded within a GUI-supported Decision Support System (DSS), named PV Analyzer. The analyzer's workflow is composed of several data analysis components including basic statistical and visualization methods as well as an algorithm for building predictive machine learning models. The analyzer allows for the identification of interesting trends within the libraries, not easily observable using simple bi-parametric correlations...
September 2018: Molecular Informatics
Christoph Sotriffer
Covalent ligands have recently regained considerable attention in drug discovery. The rational design of such ligands, however, is still faced with particular challenges, mostly related to the fact that covalent bond formation is a quantum mechanical phenomenon which cannot adequately be handled by the force fields or empirical approaches typically used for noncovalent protein-ligand interactions. Although the necessity for quantum chemical approaches is clear, they cannot yet routinely be applied on large data sets of ligands or for a broader exploration of binding modes in docking calculations...
September 2018: Molecular Informatics
Petra Schneider, Gisbert Schneider
Pharmacological drug actions are often caused by multi-target effects. While most of the currently approved synthetic drugs were designed to interact with a single 'on-target', these chemical agents often interact with additional 'off-targets'. Understanding and rationalizing these multiple interactions will be indispensable for the design of future precision medicines. We employed computational predictions of drug-target interactions to analyze functional drug-drug relationships. 900 approved drugs were represented in terms of their predicted activity fingerprints, considering 1158 potential target activities...
September 2018: 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...
September 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...
September 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...
September 2018: Molecular Informatics
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