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      Novel Potent Muscarinic Receptor Antagonists: Investigation on the Nature of Lipophilic Substituents in the 5- and/or 6-Positions of the 1,4-Dioxane Nucleus

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          Abstract

          A series of novel 1,4-dioxane analogues of the muscarinic acetylcholine receptor (mAChR) antagonist 2 was synthesized and studied for their affinity at M 1–M 5 mAChRs. The 6-cyclohexyl-6-phenyl derivative 3b, with a cis configuration between the CH 2N +(CH 3) 3 chain in the 2-position and the cyclohexyl moiety in the 6-position, showed p K i values for mAChRs higher than those of 2 and a selectivity profile analogous to that of the clinically approved drug oxybutynin. The study of the enantiomers of 3b and the corresponding tertiary amine 33b revealed that the eutomers are (2 S,6 S)-(−)- 3b and (2 S,6 S)-(−)- 33b, respectively. Docking simulations on the M 3 mAChR-resolved structure rationalized the experimental observations. The quaternary ammonium function, which should prevent the crossing of the blood–brain barrier, and the high M 3/M 2 selectivity, which might limit cardiovascular side effects, make 3b a valuable starting point for the design of novel antagonists potentially useful in peripheral diseases in which M 3 receptors are involved.

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          SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules

          To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.
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            Scalable molecular dynamics with NAMD.

            NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu. (c) 2005 Wiley Periodicals, Inc.
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              Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters

              Modern semiempirical methods are of sufficient accuracy when used in the modeling of molecules of the same type as used as reference data in the parameterization. Outside that subset, however, there is an abundance of evidence that these methods are of very limited utility. In an attempt to expand the range of applicability, a new method called PM7 has been developed. PM7 was parameterized using experimental and high-level ab initio reference data, augmented by a new type of reference data intended to better define the structure of parameter space. The resulting method was tested by modeling crystal structures and heats of formation of solids. Two changes were made to the set of approximations: a modification was made to improve the description of noncovalent interactions, and two minor errors in the NDDO formalism were rectified. Average unsigned errors (AUEs) in geometry and ΔH f for PM7 were reduced relative to PM6; for simple gas-phase organic systems, the AUE in bond lengths decreased by about 5 % and the AUE in ΔH f decreased by about 10 %; for organic solids, the AUE in ΔH f dropped by 60 % and the reduction was 33.3 % for geometries. A two-step process (PM7-TS) for calculating the heights of activation barriers has been developed. Using PM7-TS, the AUE in the barrier heights for simple organic reactions was decreased from values of 12.6 kcal/mol-1 in PM6 and 10.8 kcal/mol-1 in PM7 to 3.8 kcal/mol-1. The origins of the errors in NDDO methods have been examined, and were found to be attributable to inadequate and inaccurate reference data. This conclusion provides insight into how these methods can be improved. Electronic supplementary material The online version of this article (doi:10.1007/s00894-012-1667-x) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                J Med Chem
                J Med Chem
                jm
                jmcmar
                Journal of Medicinal Chemistry
                American Chemical Society
                0022-2623
                1520-4804
                06 May 2020
                11 June 2020
                : 63
                : 11
                : 5763-5782
                Affiliations
                []Scuola di Scienze del Farmaco e dei Prodotti della Salute, Università di Camerino , Via S. Agostino 1, 62032 Camerino, Italy
                []Scuola di Bioscienze e Medicina Veterinaria, Università di Camerino , Via Gentile III da Varano, 62032 Camerino, Italy
                [§ ]Istituto di Cristallografia IC-CNR , Via Amendola 122/o, 70126 Bari, Italy
                []Dipartimento di Farmacia-Scienze del Farmaco, Università di Bari “A. Moro” , Consorzio C.I.N.M.P.I.S., Via E. Orabona 4, I-70125 Bari, Italy
                []Dipartimento di Neuroscienze, Psicologia, Area del Farmaco e Salute del Bambino (NEUROFARBA), Sezione di Farmacologia e Tossicologia, Università degli Studi di Firenze , Viale Pieraccini 6, 50139 Firenze, Italy
                [# ]Dipartimento di Chimica e Chimica Industriale, Università di Pisa , Via Moruzzi 13, 56124 Pisa, Italy
                []Institute of Organic Chemistry, Polish Academy of Sciences , Kasprzaka 44/52 Street, 01-224 Warsaw, Poland
                []Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano , Via Mangiagalli 25, 20133 Milano, Italy
                Author notes
                [* ]Email: alessandro.piergentili@ 123456unicam.it . Phone: +390737402235. Fax: +390737637345.
                Article
                10.1021/acs.jmedchem.9b02100
                8007111
                32374602
                3dfd50b6-fc83-47fb-8c38-d83b64f24734

                Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 17 December 2019
                Categories
                Article
                Custom metadata
                jm9b02100
                jm9b02100

                Pharmaceutical chemistry
                Pharmaceutical chemistry

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