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      Combinatorial–computational–chemoinformatics (C 3) approach to finding and analyzing low-energy tautomers

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          Abstract

          Finding the most stable tautomer or a set of low-energy tautomers of molecules is critical in many aspects of molecular modelling or virtual screening experiments. Enumeration of low-energy tautomers of neutral molecules in the gas-phase or typical solvents can be performed by applying available organic chemistry knowledge. This kind of enumeration is implemented in a number of software packages and it is relatively reliable. However, in esoteric cases such as charged molecules in uncommon, non-aqueous solvents there is simply not enough available knowledge to make reliable predictions of low energy tautomers. Over the last few years we have been developing an approach to address the latter problem and we successfully applied it to discover the most stable anionic tautomers of nucleic acid bases that might be involved in the process of DNA damage by low-energy electrons and in charge transfer through DNA. The approach involves three steps: (1) combinatorial generation of a library of tautomers, (2) energy-based screening of the library using electronic structure methods, and (3) analysis of the information generated in step (2). In steps 1–3 we employ combinatorial, computational and chemoinformatics techniques, respectively. Therefore, this hybrid approach is named “Combinatorial*Computational*Chemoinformatics”, or just abbreviated as C 3 (or C-cube) approach. This article summarizes our developments and most interesting methodological aspects of the C 3 approach. It can serve as an example how to identify the most stable tautomers of molecular systems for which common chemical knowledge had not been sufficient to make definite predictions.

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          A post-Hartree-Fock model of intermolecular interactions.

          Intermolecular interactions are of great importance in chemistry but are difficult to model accurately with computational methods. In particular, Hartree-Fock and standard density-functional approximations do not include the physics necessary to properly describe dispersion. These methods are sometimes corrected to account for dispersion by adding a pairwise C6R6 term, with C6 dispersion coefficients dependent on the atoms involved. We present a post-Hartree-Fock model in which C6 coefficients are generated by the instantaneous dipole moment of the exchange hole. This model relies on occupied orbitals only, and involves only one, universal, empirical parameter to limit the dispersion energy at small interatomic separations. The model is extensively tested on isotropic C6 coefficients of 178 intermolecular pairs. It is also applied to the calculation of the geometries and binding energies of 20 intermolecular complexes involving dispersion, dipole-induced dipole, dipole-dipole, and hydrogen-bonding interactions, with remarkably good results.
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            High performance computational chemistry: An overview of NWChem a distributed parallel application

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              Progress in ab initio QM/MM free-energy simulations of electrostatic energies in proteins: accelerated QM/MM studies of pKa, redox reactions and solvation free energies.

              Hybrid quantum mechanical/molecular mechanical (QM/MM) approaches have been used to provide a general scheme for chemical reactions in proteins. However, such approaches still present a major challenge to computational chemists, not only because of the need for very large computer time in order to evaluate the QM energy but also because of the need for proper computational sampling. This review focuses on the sampling issue in QM/MM evaluations of electrostatic energies in proteins. We chose this example since electrostatic energies play a major role in controlling the function of proteins and are key to the structure-function correlation of biological molecules. Thus, the correct treatment of electrostatics is essential for the accurate simulation of biological systems. Although we will be presenting different types of QM/MM calculations of electrostatic energies (and related properties) here, our focus will be on pKa calculations. This reflects the fact that pKa's of ionizable groups in proteins provide one of the most direct benchmarks for the accuracy of electrostatic models of macromolecules. While pKa calculations by semimacroscopic models have given reasonable results in many cases, existing attempts to perform pKa calculations using QM/MM-FEP have led to discrepancies between calculated and experimental values. In this work, we accelerate our QM/MM calculations using an updated mean charge distribution and a classical reference potential. We examine both a surface residue (Asp3) of the bovine pancreatic trypsin inhibitor and a residue buried in a hydrophobic pocket (Lys102) of the T4-lysozyme mutant. We demonstrate that, by using this approach, we are able to reproduce the relevant side chain pKa's with an accuracy of 3 kcal/mol. This is well within the 7 kcal/mol energy difference observed in studies of enzymatic catalysis, and is thus sufficient accuracy to determine the main contributions to the catalytic energies of enzymes. We also provide an overall perspective of the potential of QM/MM calculations in general evaluations of electrostatic free energies, pointing out that our approach should provide a very powerful and accurate tool to predict the electrostatics of not only solution but also enzymatic reactions, as well as the solvation free energies of even larger systems, such as nucleic acid bases incorporated into DNA.
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                Author and article information

                Contributors
                +1-510-4867749 , +1-510-4865812 , mharanczyk@lbl.gov
                Journal
                J Comput Aided Mol Des
                Journal of Computer-Aided Molecular Design
                Springer Netherlands (Dordrecht )
                0920-654X
                1573-4951
                2 April 2010
                2 April 2010
                June 2010
                : 24
                : 6-7
                : 627-638
                Affiliations
                [1 ]Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Mail Stop 50F-1650, Berkeley, CA 94720 USA
                [2 ]Chemistry-School of Engineering and Physical Sciencs, Heriot-Watt University, Edinburgh, EH14 4AS UK
                Article
                9344
                10.1007/s10822-010-9344-6
                2886899
                20361238
                69b8a5c3-438e-4272-8725-de4a06134590
                © The Author(s) 2010
                History
                : 26 January 2010
                : 17 March 2010
                Categories
                Article
                Custom metadata
                © Springer Science+Business Media B.V. 2010

                Biomedical engineering
                electronic structure methods,tautomer,chemoinformatics,combinatorial approach

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