Molecular Simulation and Statistical Learning Methods Toward Predicting Drug–Polymer Amorphous Solid Dispersion Miscibility, Stability, and Formulation Design
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Development and Validation of Liquid Chromatography-Based Methods to Assess the Lipophilicity of Cytotoxic Platinum(IV) Complexes
Article Development and Validation of Liquid Chromatography-Based Methods to Assess the Lipophilicity of Cytotoxic Platinum(IV) Complexes Matthias H. M. Klose 1,2, Sarah Theiner 3, Hristo P. Varbanov 1,4, Doris Hoefer 1, Verena Pichler 1,5, Markus Galanski 1, Samuel M. Meier-Menches 2,3,* and Bernhard K. Keppler 1,2,* 1 Institute of Inorganic Chemistry, University of Vienna, 1090 Vienna, Austria; [email protected] (M.H.M.K.); [email protected] (D.H.); [email protected] (M.G.) 2 Research Cluster ‘Translational Cancer Therapy Research’, University of Vienna, 1090 Vienna, Austria 3 Department of Analytical Chemistry, University of Vienna, 1090 Vienna, Austria; [email protected] 4 Institute of Chemistry—Inorganic Chemistry, University of Graz, 8010 Graz, Austria; [email protected] (H.P.V.) 5 Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria; [email protected] (V.P.) * Correspondence: [email protected] (S.M.M.-M.); [email protected] (B.K.K.); Tel.: +43-1-4277-52373 (S.M.M.-M.); +43-1-4277-52602 (B.K.K.) Received: 2 October 2018; Accepted: 29 November 2018; Published: 4 December 2018 Abstract: Lipophilicity is a crucial parameter for drug discovery, usually determined by the logarithmic partition coefficient (Log P) between octanol and water. However, the available detection methods have restricted the widespread use of the partition coefficient in inorganic medicinal chemistry, and recent investigations have shifted towards chromatographic lipophilicity parameters, frequently without a conversion to derive Log P. -
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
processes Review Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development Outi M. H. Salo-Ahen 1,2,* , Ida Alanko 1,2, Rajendra Bhadane 1,2 , Alexandre M. J. J. Bonvin 3,* , Rodrigo Vargas Honorato 3, Shakhawath Hossain 4 , André H. Juffer 5 , Aleksei Kabedev 4, Maija Lahtela-Kakkonen 6, Anders Støttrup Larsen 7, Eveline Lescrinier 8 , Parthiban Marimuthu 1,2 , Muhammad Usman Mirza 8 , Ghulam Mustafa 9, Ariane Nunes-Alves 10,11,* , Tatu Pantsar 6,12, Atefeh Saadabadi 1,2 , Kalaimathy Singaravelu 13 and Michiel Vanmeert 8 1 Pharmaceutical Sciences Laboratory (Pharmacy), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland; ida.alanko@abo.fi (I.A.); rajendra.bhadane@abo.fi (R.B.); parthiban.marimuthu@abo.fi (P.M.); atefeh.saadabadi@abo.fi (A.S.) 2 Structural Bioinformatics Laboratory (Biochemistry), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland 3 Faculty of Science-Chemistry, Bijvoet Center for Biomolecular Research, Utrecht University, 3584 CH Utrecht, The Netherlands; [email protected] 4 Swedish Drug Delivery Forum (SDDF), Department of Pharmacy, Uppsala Biomedical Center, Uppsala University, 751 23 Uppsala, Sweden; [email protected] (S.H.); [email protected] (A.K.) 5 Biocenter Oulu & Faculty of Biochemistry and Molecular Medicine, University of Oulu, Aapistie 7 A, FI-90014 Oulu, Finland; andre.juffer@oulu.fi 6 School of Pharmacy, University of Eastern Finland, FI-70210 Kuopio, Finland; maija.lahtela-kakkonen@uef.fi (M.L.-K.); tatu.pantsar@uef.fi -
Lipophilicity (Logd7.4) of N-Aryl Benzo Hydroxamic Acids
Global Journal of Pharmacy & Pharmaceutical Sciences ISSN: 2573-2250 Mini Review Glob J Pharmaceu Sci Volume 4 Issue 5 - february 2018 Copyright © All rights are reserved by Ajita Dixit DOI: 10.19080/GJPPS.2018.04.555648 Lipophilicity (LogD7.4) of N-Aryl Benzo Hydroxamic Acids Ajita Dixit* Pandit Ravishankar Shukla University, India Submission: July 24, 2017; Published: February 21, 2018 *Corresponding author: Ajita Dixit, Pandit Ravishankar Shukla University, India, Email: Abstract Hydroxamic acids are polyfunctional molecules which show a wide spectrum of biological and medicinal activities. Lipophilicity is known to be important for absorption, permeability and in vivo distribution of organic compound. Lipophilicity is also a major structural factor that influences the pharmacokinetic and pharmacodynamic behaviour of compound. Introduction homogeneously but rather, a gradient is formed that varies Lipophilicity is known to be important for absorption, with the composition and geometry of membrane [7]. The high permeability and in vivo distribution of organic compound degree of ordering of solutes in a lipid bi layer compared with a [1]. Since about one century, it is recognized as a meaningful parameter in Structure-activity relationship studies and with and partitioning. Never the less good correlation between the epoch making contributions of Hansch et al. [2] has become bulk liquid phase also significantly changes the thermodynamic the single most informative and successful physico-chemical membrane /buffer and octanol/water two phase’s systems has the partition coefficient of various lipophilic compounds in been observed [8]. property in medicinal chemistry. Lipophilicity is defined for a lipophilic environment.” Lipophilicity is determined Material and Methods “Lipophilicity represents the affinity of a molecule or a moiety valid only for a single chemical species) or as distribution experimentally as partition coefficients (written as logP and In the present investigation partition coefficient or n-Octanol and buffer as solvent. -
Maestro 10.2 User Manual
Maestro User Manual Maestro 10.2 User Manual Schrödinger Press Maestro User Manual Copyright © 2015 Schrödinger, LLC. All rights reserved. While care has been taken in the preparation of this publication, Schrödinger assumes no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein. Canvas, CombiGlide, ConfGen, Epik, Glide, Impact, Jaguar, Liaison, LigPrep, Maestro, Phase, Prime, PrimeX, QikProp, QikFit, QikSim, QSite, SiteMap, Strike, and WaterMap are trademarks of Schrödinger, LLC. Schrödinger, BioLuminate, and MacroModel are registered trademarks of Schrödinger, LLC. MCPRO is a trademark of William L. Jorgensen. DESMOND is a trademark of D. E. Shaw Research, LLC. Desmond is used with the permission of D. E. Shaw Research. All rights reserved. This publication may contain the trademarks of other companies. Schrödinger software includes software and libraries provided by third parties. For details of the copyrights, and terms and conditions associated with such included third party software, use your browser to open third_party_legal.html, which is in the docs folder of your Schrödinger software installation. This publication may refer to other third party software not included in or with Schrödinger software ("such other third party software"), and provide links to third party Web sites ("linked sites"). References to such other third party software or linked sites do not constitute an endorsement by Schrödinger, LLC or its affiliates. Use of such other third party software and linked sites may be subject to third party license agreements and fees. Schrödinger, LLC and its affiliates have no responsibility or liability, directly or indirectly, for such other third party software and linked sites, or for damage resulting from the use thereof. -
Kepler Gpus and NVIDIA's Life and Material Science
LIFE AND MATERIAL SCIENCES Mark Berger; [email protected] Founded 1993 Invented GPU 1999 – Computer Graphics Visual Computing, Supercomputing, Cloud & Mobile Computing NVIDIA - Core Technologies and Brands GPU Mobile Cloud ® ® GeForce Tegra GRID Quadro® , Tesla® Accelerated Computing Multi-core plus Many-cores GPU Accelerator CPU Optimized for Many Optimized for Parallel Tasks Serial Tasks 3-10X+ Comp Thruput 7X Memory Bandwidth 5x Energy Efficiency How GPU Acceleration Works Application Code Compute-Intensive Functions Rest of Sequential 5% of Code CPU Code GPU CPU + GPUs : Two Year Heart Beat 32 Volta Stacked DRAM 16 Maxwell Unified Virtual Memory 8 Kepler Dynamic Parallelism 4 Fermi 2 FP64 DP GFLOPS GFLOPS per DP Watt 1 Tesla 0.5 CUDA 2008 2010 2012 2014 Kepler Features Make GPU Coding Easier Hyper-Q Dynamic Parallelism Speedup Legacy MPI Apps Less Back-Forth, Simpler Code FERMI 1 Work Queue CPU Fermi GPU CPU Kepler GPU KEPLER 32 Concurrent Work Queues Developer Momentum Continues to Grow 100M 430M CUDA –Capable GPUs CUDA-Capable GPUs 150K 1.6M CUDA Downloads CUDA Downloads 1 50 Supercomputer Supercomputers 60 640 University Courses University Courses 4,000 37,000 Academic Papers Academic Papers 2008 2013 Explosive Growth of GPU Accelerated Apps # of Apps Top Scientific Apps 200 61% Increase Molecular AMBER LAMMPS CHARMM NAMD Dynamics GROMACS DL_POLY 150 Quantum QMCPACK Gaussian 40% Increase Quantum Espresso NWChem Chemistry GAMESS-US VASP CAM-SE 100 Climate & COSMO NIM GEOS-5 Weather WRF Chroma GTS 50 Physics Denovo ENZO GTC MILC ANSYS Mechanical ANSYS Fluent 0 CAE MSC Nastran OpenFOAM 2010 2011 2012 SIMULIA Abaqus LS-DYNA Accelerated, In Development NVIDIA GPU Life Science Focus Molecular Dynamics: All codes are available AMBER, CHARMM, DESMOND, DL_POLY, GROMACS, LAMMPS, NAMD Great multi-GPU performance GPU codes: ACEMD, HOOMD-Blue Focus: scaling to large numbers of GPUs Quantum Chemistry: key codes ported or optimizing Active GPU acceleration projects: VASP, NWChem, Gaussian, GAMESS, ABINIT, Quantum Espresso, BigDFT, CP2K, GPAW, etc. -
Lipophilicity As a Central Component of Drug-Like Properties of Chalchones and Flavonoid Derivatives
molecules Article Lipophilicity as a Central Component of Drug-Like Properties of Chalchones and Flavonoid Derivatives Teodora Constantinescu 1, Claudiu Nicolae Lungu 2,* and Ildiko Lung 3 1 Department of Chemistry, Faculty of Pharmacy, Iuliu Hatieganu University, 400012 Cluj-Napoca, Romania; [email protected] 2 Department of Chemistry, Faculty of Chemistry and Chemical Engineering, Babes-Bolyai University, 400028 Cluj-Napoca, Romania 3 National Institute for Research & Development of Isotopic and Molecular Technologies 67-103 Donath street, 400293 Cluj-Napoca, Romania; [email protected] * Correspondence: [email protected]; Tel.: +40-(0)-742-255-099 Received: 11 March 2019; Accepted: 10 April 2019; Published: 17 April 2019 Abstract: Lipophilcity is an important physico-chemical parameter that influences membrane transport and binding ability to action. Migration distance following complete elution of compounds was used to calculate different lipophilicity-related parameters. The aim of this study is to show that lipophilicity is a central component of thiazole chalcones and flavonoid derivatives regarding their drug-like properties. Experimental and computational methods were used. This study considers 44 previously synthesized compounds (thiazole chalcones, flavanones, flavones, 3-hydroxyflavones, and their acetylated derivatives). The concerned compounds have shown antitumoral hallmarks and antibacterial activity in vitro. The experimental method used to determine compounds’ lipophilicity was the reverse-phase thin layer chromatography (RP-TLC). Lipophilicity related 0 parameters—isocratic retention factor (RM), relative lipophily (RM ), slope (b), chromatographic hydrophobic index ('0), scores of principal components (PC1/RM)—were determined based on reverse-phase chromatography results. Keywords: lipophilicity; retention factor; chalcones; QSAR; chromatography; drug design 1. Introduction Lipophilicity is an important feature of molecules in pharmaceutical, biochemical, and medical chemistry fields. -
Trends in Atomistic Simulation Software Usage [1.3]
A LiveCoMS Perpetual Review Trends in atomistic simulation software usage [1.3] Leopold Talirz1,2,3*, Luca M. Ghiringhelli4, Berend Smit1,3 1Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingenierie Chimiques, Valais, École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland; 2Theory and Simulation of Materials (THEOS), Faculté des Sciences et Techniques de l’Ingénieur, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 3National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 4The NOMAD Laboratory at the Fritz Haber Institute of the Max Planck Society and Humboldt University, Berlin, Germany This LiveCoMS document is Abstract Driven by the unprecedented computational power available to scientific research, the maintained online on GitHub at https: use of computers in solid-state physics, chemistry and materials science has been on a continuous //github.com/ltalirz/ rise. This review focuses on the software used for the simulation of matter at the atomic scale. We livecoms-atomistic-software; provide a comprehensive overview of major codes in the field, and analyze how citations to these to provide feedback, suggestions, or help codes in the academic literature have evolved since 2010. An interactive version of the underlying improve it, please visit the data set is available at https://atomistic.software. GitHub repository and participate via the issue tracker. This version dated August *For correspondence: 30, 2021 [email protected] (LT) 1 Introduction Gaussian [2], were already released in the 1970s, followed Scientists today have unprecedented access to computa- by force-field codes, such as GROMOS [3], and periodic tional power. -
Solvent Effect Modelling of Isocyanuric Products Synthesis by Chemometric Methods
Journal of Automated Methods & Management in Chemistry Vol. 24, No. 4 (July–August 2002) pp. 111–119 Solvent e´ ect modelling of isocyanuric products synthesis by chemometric methods Jean-Louis Havet, Myriam Billiau-Loreau, electric constant) or by empirical parameters (Dimroth± Catherine Porte* and Alain Delacroix Reichardt constant, Kosower constant). These data can Laboratoire de Chimie Industrielle et Geè nie des Proceè deè s, Conservatoire National be considered as good but partial indicators of polarity. des Arts et Meè tiers, 2 rue Conteè , F-75003 Paris, France Furthermore, the accumulation of empirical values shows that none of these de® nitions is totally convenient. The Chemometric tools were used to generate the modelling of solvent use of several parameters that are not independent in N e¡ects on the -alkylation of an isocyanuric acid salt. The method multiparametric equations allows one to improve the proceeded from a central composite design applied on the Carlson quanti® cation of polarity, but it remains insuæ cient to solvent classi¢cation using principal components analysis. The have a general classi® cation of solvents [3]. selectivity of the reaction was studied from the production of di¡erent substituted isocyanuric derivatives. Response graphs were The most ambitious approach for a general classi® cation obtained for each compound and used to devise a strategy for of solvents uses multivariate statistical methods [4, 5]. solvent selection. The prediction models were validated and used to The compilation of the physicochemical constants of search for the best selectivity for the reaction system. The solvent solvents allows one to take diå erent properties simulta- most often selected as the best for the reaction is the N,N- neously into account. -
In Silico Strategy for Targeting the Mtor Kinase at Rapamycin Binding Site by Small Molecules
molecules Article In Silico Strategy for Targeting the mTOR Kinase at Rapamycin Binding Site by Small Molecules Serena Vittorio 1 , Rosaria Gitto 1 , Ilenia Adornato 1, Emilio Russo 2 and Laura De Luca 1,* 1 Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Viale Palatucci 13, I-98168 Messina, Italy; [email protected] (S.V.); [email protected] (R.G.); [email protected] (I.A.) 2 Science of Health Department, School of Medicine, University “Magna Graecia” of Catanzaro, Viale Europa e Germaneto, I-88100 Catanzaro, Italy; [email protected] * Correspondence: [email protected] or [email protected]; Tel.: +39-090-676-6410 Abstract: Computer aided drug-design methods proved to be powerful tools for the identification of new therapeutic agents. We employed a structure-based workflow to identify new inhibitors targeting mTOR kinase at rapamycin binding site. By combining molecular dynamics (MD) simulation and pharmacophore modelling, a simplified structure-based pharmacophore hypothesis was built starting from the FKBP12-rapamycin-FRB ternary complex retrieved from RCSB Protein Data Bank (PDB code 1FAP). Then, the obtained model was used as filter to screen the ZINC biogenic compounds library, containing molecules derived from natural sources or natural-inspired compounds. The resulting hits were clustered according to their similarity; moreover, compounds showing the highest pharmacophore fit-score were chosen from each cluster. The selected molecules were subjected to docking studies to clarify their putative binding mode. The binding free energy of the obtained complexes was calculated by MM/GBSA method and the hits characterized by the lowest DGbind Citation: Vittorio, S.; Gitto, R.; values were identified as potential mTOR inhibitors. -
AP42 Chapter 9 Reference
Background Report Reference AP-42 Section Number: 9.2.2 Background Chapter: 4 Reference Number: 22 Title: "Critical Review of Henry's Law Constants fro Pesticides" in Reviews of Environmental Contamination and Toxicology L.R. Suntio 1988 AP-42 Section 9! Reference Report Sect. 3c L2% Critical Review of Henry's Law Constants Reference for Pesticides L.R. Sunti0,'W.Y. Shiu,* D. Mackay,* J.N. Seiber,** and D. Glotfelty*** Contents ......... ........... ........... ............. IV. Data Analysis ........ ........... ......... I V. Discussion .......... ........... .......... 41 ............. so .......... ............ I. Introduction Pesticides play an important role in maintaining agricultural productivity, but they may also be causes of contamination of air, water, soil, and food, with possible adverse effects on human and animal health. The proper use of pesticide chemicals must be based on an understanding of the behavior of the chemicals as they interact with air, water, soil, and biota, react or degrade, and migrate. This behavior is strongly influenced by the chemicals' physical- chemical properties of solubility in water, vapor pressure or volatility, and tendency to sorb to organic and mineral matter in the soil. Reviews of such physical-chemical properties have been compiled by Kenaga (1980), Kenaga and Goring (1980), Briggs (1981), and Bowman and Sans (1983) for aqueous solubility, octanol-water partition coefficient, bio- accumulation, and soil sorption; Spencer and Cliath (1970, 1973. 1983). and Spencer (1976) for vapor pressure and volatilization from soil. In this chapter we compile and discuss data for Henry's Law constant H (which is the ratio of solute partial pressure in the air to the equilibrium water concentration and thus has units of Pa m3/mol) or the air-water partition 'Department ofchemical Engineering and Applied Chemistry. -
Lawrence Berkeley National Laboratory Recent Work
Lawrence Berkeley National Laboratory Recent Work Title From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape. Permalink https://escholarship.org/uc/item/4sm897jh Journal Chemical reviews, 121(8) ISSN 0009-2665 Authors Kowalski, Karol Bair, Raymond Bauman, Nicholas P et al. Publication Date 2021-04-01 DOI 10.1021/acs.chemrev.0c00998 Peer reviewed eScholarship.org Powered by the California Digital Library University of California From NWChem to NWChemEx: Evolving with the computational chemistry landscape Karol Kowalski,y Raymond Bair,z Nicholas P. Bauman,y Jeffery S. Boschen,{ Eric J. Bylaska,y Jeff Daily,y Wibe A. de Jong,x Thom Dunning, Jr,y Niranjan Govind,y Robert J. Harrison,k Murat Keçeli,z Kristopher Keipert,? Sriram Krishnamoorthy,y Suraj Kumar,y Erdal Mutlu,y Bruce Palmer,y Ajay Panyala,y Bo Peng,y Ryan M. Richard,{ T. P. Straatsma,# Peter Sushko,y Edward F. Valeev,@ Marat Valiev,y Hubertus J. J. van Dam,4 Jonathan M. Waldrop,{ David B. Williams-Young,x Chao Yang,x Marcin Zalewski,y and Theresa L. Windus*,r yPacific Northwest National Laboratory, Richland, WA 99352 zArgonne National Laboratory, Lemont, IL 60439 {Ames Laboratory, Ames, IA 50011 xLawrence Berkeley National Laboratory, Berkeley, 94720 kInstitute for Advanced Computational Science, Stony Brook University, Stony Brook, NY 11794 ?NVIDIA Inc, previously Argonne National Laboratory, Lemont, IL 60439 #National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6373 @Department of Chemistry, Virginia Tech, Blacksburg, VA 24061 4Brookhaven National Laboratory, Upton, NY 11973 rDepartment of Chemistry, Iowa State University and Ames Laboratory, Ames, IA 50011 E-mail: [email protected] 1 Abstract Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. -
Elucidating Binding Sites and Affinities of Erα Agonist and Antagonist to Human Alpha-Fetoprotein by in Silico Modeling and Point Mutagenesis Nurbubu T
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 29 December 2019 doi:10.20944/preprints201912.0374.v1 Peer-reviewed version available at Int. J. Mol. Sci. 2020, 21, 893; doi:10.3390/ijms21030893 Elucidating Binding Sites and Affinities of ERα Agonist and Antagonist to Human Alpha-Fetoprotein by in silico Modeling and Point Mutagenesis Nurbubu T. Moldogazieva1*, Daria S. Ostroverkhova1,2, Nikolai N. Kuzmich1,3, Vladimir V. Kadochnikov4, Alexander A. Terentiev5, Yuri B. Porozov1,4 1 Laboratory of Bioinformatics, I.M. Sechenov First Moscow State Medical University (Sechenov University); Moscow, Russia; 2Department of Bioengineering, M.V. Lomonosov Moscow State University; Moscow, Russia; 3Department of Drug Safety, I.M. Smorodintsev Research Institute of Influenza, WHO National Influenza Centre of Russia; Saint Petersburg, Russia 4Department of Information and Communication Technologies, Saint Petersburg National Research University of Information Technologies, Mechanics and Optics; Saint Petersburg, Russia 5Deparment of Biochemistry and Molecular Biology, N.I. Pirogov Russian National Research Medical University; Moscow Russia *Corresponding author: Nurbubu T. Moldogazieva, e-mail: [email protected] (NM) ¶ These authors contributed equally to this work Short title: Binding of ERα ligands to human alpha-fetoprotein Key words: alpha-fetoprotein, estrogens, selective estrogen receptor modulators, homology-based modeling, molecular docking, protein-ligand interaction, amino acid substitutions. Abbreviations: HAFP, human alpha-fetoprotein; HSA, human serum albumin; E2, 17β-estradiol; DES, diethylstilbestrol. Author contribution: Conceptualization, Nurbubu T. Moldogazieva, Alexander A. Terentiev and Yuri B. Porozov; Data curation, Nurbubu T. Moldogazieva; Formal analysis, Nurbubu T. Moldogazieva and Nikolai N. Kuzmich; Investigation, Daria S. Ostroverkhova and Vladimir V. Kadochnikov; Methodology, Nikolai N. Kuzmich; Supervision, Alexander A.