Dynamic Combinatorial Chemistry: In Drug Discovery, Bioorganic Chemistry, and Materials Science - Hardcover

Über die Autorin bzw. den Autor

Benjamin L. Miller is an Associate Professor of Dermatology, Biomedical Engineering, and Biochemistry and Biophysics at the University of Rochester. In addition to his academic credentials, Dr. Miller has industry consulting experience as the founder of Adarza BioSystems and Lighthouse Biosciences.

Von der hinteren Coverseite

Effective techniques for applying Dynamic Combinatorial Chemistry

In a relatively short period, Dynamic Combinatorial Chemistry (DCC) has grown from proof-of-concept experiments in a few isolated labs to a broad conceptual framework with applications to an exceptional range of problems in molecular recognition, lead compound identification, catalyst design, nanotechnology, polymer science, and others. Bringing together a group of respected experts, this overview explains how chemists can apply DCC and fragment-based library methods to lead generation for drug discovery and molecular recognition in bioorganic chemistry and materials science.

Chapters cover:

• Basic theory

• Approaches to binding in proteins and nucleic acids

• Molecular recognition

• Self-sorting

• Catalyst discovery

• Materials discovery

• Analytical chemistry challenges

A comprehensive, single-source reference about DCC methods and applications including aspects of fragment-based drug discovery, this is a core reference that will spark the development of new solutions and strategies for chemists building structure libraries and designing compounds and materials.

Aus dem Klappentext

Effective techniques for applying Dynamic Combinatorial Chemistry

In a relatively short period, Dynamic Combinatorial Chemistry (DCC) has grown from proof-of-concept experiments in a few isolated labs to a broad conceptual framework with applications to an exceptional range of problems in molecular recognition, lead compound identification, catalyst design, nanotechnology, polymer science, and others. Bringing together a group of respected experts, this overview explains how chemists can apply DCC and fragment-based library methods to lead generation for drug discovery and molecular recognition in bioorganic chemistry and materials science.

Chapters cover:

• Basic theory

• Approaches to binding in proteins and nucleic acids

• Molecular recognition

• Self-sorting

• Catalyst discovery

• Materials discovery

• Analytical chemistry challenges

A comprehensive, single-source reference about DCC methods and applications including aspects of fragment-based drug discovery, this is a core reference that will spark the development of new solutions and strategies for chemists building structure libraries and designing compounds and materials.