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Libros sobre el tema "DRUG DISCOVERY TOOLS"

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Autor: Grafiati
Publicado: 11 de septiembre de 2023

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1

Saxena, Anil Kumar, ed. Biophysical and Computational Tools in Drug Discovery. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85281-8.

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2

Rubenstein, Ken. Drug targets from genomics: Evolving tools for discovery. Westborough, MA: D&MD Publications, 2005.

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3

Jürgen, Bajorath, ed. Chemoinformatics: Concepts, methods, and tools for drug discovery. Totowa, N.J: Humana Press, 2004.

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4

K, Ghose Arup y Viswanadhan Vellarkad N. 1954-, eds. Combinatorial library design and evaluation: Principles, software tools, and applications in drug discovery. New York: Marcel Dekker, 2001.

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5

Saxena, Anil Kumar. Biophysical and Computational Tools in Drug Discovery. Springer International Publishing AG, 2021.

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6

Saxena, Anil Kumar. Biophysical and Computational Tools in Drug Discovery. Springer International Publishing AG, 2022.

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7

Egbuna, Chukwuebuka, Mithun Rudrapal y Habibu Tijjani. Phytochemistry, Computational Tools and Databases in Drug Discovery. Elsevier, 2022.

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8

Egbuna, Chukwuebuka, Mithun Rudrapal y Habibu Tijjani. Phytochemistry, Computational Tools and Databases in Drug Discovery. Elsevier, 2022.

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9

Sean, Ekins y Xu Jinghai J, eds. Drug efficacy, safety, and biologics discovery: Emerging technologies and tools. Hoboken, N.J: John Wiley & Sons, 2009.

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10

Ekins, Sean y Jinghai J. Xu. Drug Efficacy, Safety, and Biologics Discovery: Emerging Technologies and Tools. Wiley & Sons, Incorporated, John, 2009.

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11

Ekins, Sean y Jinghai J. Xu. Drug Efficacy, Safety, and Biologics Discovery: Emerging Technologies and Tools. Wiley & Sons, Incorporated, John, 2009.

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12

Translational Neuroimaging Tools For Cns Drug Discovery Development And Treatment. Academic Press, 2012.

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13

Folkers, Gerd, Raimund Mannhold, Hugo Kubinyi y Tomi K. Sawyer. Chemical Biology: Concepts, Methods and Tools for Drug Discovery. Wiley & Sons, Incorporated, John, 2010.

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14

Proteomics: Integrating Protein-Bsed Tools and Applications for Drug Discovery. Gallery Books, 1998.

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15

McArthur, Robert A. Translational Neuroimaging: Tools for CNS Drug Discovery, Development and Treatment. Elsevier Science & Technology Books, 2012.

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16

Fragmentbased Drug Design Tools Practical Approaches And Examples. Academic Press, 2011.

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17

Bajorath, Jürgen. Chemoinformatics: Concepts, Methods, and Tools for Drug Discovery (Methods in Molecular Biology). Humana Press, 2004.

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18

Ghose, Arup y Vellerkad Viswanadhan. Combinatorial Library Design and Evaluation: Principles, Software, Tools, and Applications in Drug Discovery. Taylor & Francis Group, 2019.

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19

Ghose, Arup y Vellerkad Viswanadhan. Combinatorial Library Design and Evaluation: Principles, Software, Tools, and Applications in Drug Discovery. CRC, 2001.

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20

Ghose, Arup y Vellerkad Viswanadhan. Combinatorial Library Design and Evaluation: Principles, Software, Tools, and Applications in Drug Discovery. Taylor & Francis Group, 2001.

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21

Ghose, Arup y Vellerkad Viswanadhan. Combinatorial Library Design and Evaluation: Principles, Software, Tools, and Applications in Drug Discovery. Taylor & Francis Group, 2001.

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22

Sapse, Anne-Marie, ed. Molecular Orbital Calculations for Biological Systems. Oxford University Press, 1998. http://dx.doi.org/10.1093/oso/9780195098730.001.0001.

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Molecular Orbital Calculations for Biological Systems is a hands-on guide to computational quantum chemistry and its applications in organic chemistry, biochemistry, and molecular biology. With improvements in software, molecular modeling techniques are now becoming widely available; they are increasingly used to complement experimental results, saving significant amounts of lab time. Common applications include pharmaceutical research and development; for example, ab initio and semi-empirical methods are playing important roles in peptide investigations and in drug design. The opening chapters provide an introduction for the non-quantum chemist to the basic quantum chemistry methods, ab initio, semi-empirical, and density functionals, as well as to one of the main families of computer programs, the Gaussian series. The second part then describes current research which applies quantum chemistry methods to such biological systems as amino acids, peptides, and anti-cancer drugs. Throughout the authors seek to encourage biochemists to discover aspects of their own research which might benefit from computational work. They also show that the methods are accessible to researchers from a wide range of mathematical backgrounds. Combining concise introductions with practical advice, this volume will be an invaluable tool for research on biological systems.
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