New Developments in Medicinal Chemistry

Volume 2

by

Carlton Anthony Taft, Carlos Henrique Tomich de Paula da Silva

DOI: 10.2174/97816080595461140201
eISBN: 978-1-60805-954-6, 2014
ISBN: 978-1-60805-955-3
ISSN: 2210-9277 (Online)



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Indexed in: EMBASE

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Table of Contents

Foreword

- Pp. i-ii (2)

Ramaswamy Sarma

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Preface

- Pp. iii-iv (2)

Carlton A. Taft

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List of Contributors

- Pp. v-vi (2)

Carlton A. Taft

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Current State-of-the-art for Virtual Screening and Docking Methods

- Pp. 3-169 (167)

Carlton Anthony Taft and Carlos Henrique Tomich de Paula da Silva

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Estimating Protein-Ligand Binding Affinity by NMR

- Pp. 170-191 (22)

Susimaire Pedersoli Mantoani, Peterson de Andrade and Carlos Henrique Tomich de Paula da Silva

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ADME/Tox Predictions in Drug Design

- Pp. 192-212 (21)

Ricardo Pereira Rodrigues, Jonathan Resende de Almeida, Evandro Pizeta Semighini, Flávio Roberto Pinsetta, Susimaire Pedersoli Mantoani, Vinicius Barreto da Silva and Carlos Henrique Tomich de Paula da Silva

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Bioisosteric Replacements in Drug Design

- Pp. 213-238 (26)

Vinicius Barreto da Silva, Daniel Fábio Kawano, Ricardo Pereira Rodrigues, Susimaire Pedersoli Mantoani, Jonathan Resende de Almeida, Evandro Pizeta Semighini and Carlos Henrique Tomich de Paula da Silva

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Index

- Pp. 239-241 (3)

Carlton Anthony Taft and Carlos Henrique Tomich de Paula da Silva

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Foreword

In modern computational medicinal chemistry, docking and virtual screening methods in drug design play important roles in aiding the pharmaceutical industries place new drugs on the market. In the first chapter of this book the authors review (homology, fragment, consensus, bioisosteric, scafffold, pharmacophore, induced fit, chemogenomics, knowledge, similarity)-based models. In addition, binding affinities, scoring functions, molecular dynamics, water and solvation, simulation of free energies, quantum mechanics/molecular mechanics, molecular fields, molecular shape and virtual screening are discussed. Some hotspots are also discussed (protein docking, stem cells, workflow pipelines, different types of ligands/targets/ interactions, (cloud/high performance/grid)-computing, post-processing, chemical libraries, confidence and the future. Docking/virtual screening programs, recent evaluations/validations/benchmarking and selected applications of various models to drug design are also reviewed.

Comprehension of binding processes, such as drug-receptor interactions, signal transduction process, and cellular recognition, are important for a better comprehension of biological functions. Medicinal Chemistry, in the path of drug discovery, has focused on studies, of the molecular interactions, which are involved in the development of severe disease states. Consequently, an accurate knowledge of the underlying protein receptor-ligand recognition events at atomic levels is important in the process of comprehension, identification and optimization of more potent drug candidates. In this sense, novel NMR spectroscopic techniques can be used as tools to gain insight into protein-protein and protein-ligand interactions in solution at the molecular level. Resonance signal of the protein or the ligand can be used to identify binding events from these experiments. In Chapter 2 the authors discuss the main NMR experimental approaches applied to identify and characterize protein-ligand binding affinity, providing a broader and better understanding of how NMR spectroscopy techniques can be employed in a drug discovery process.

Most drug candidate failures that occur during clinical trials are due to inappropriate ADMET properties. In this way, there is a major concern to identify possible ADMET failures during the early stages of drug design projects and optimize such properties in order to reduce time and costs effects. In silico ADMET predictions constitute several strategies that play a central role when considering the task of profiling lead compounds concerning potential ADMET failures. In Chapter 3, authors discuss the computational strategies, methods and softwares currently used to profile ADMET, which can be helpful during drug design.

Bioisosterism is a molecular modification medicinal chemistry strategy applied during drug design projects when a lead compound is available. The concept of bioisisterism is centered at the use of chemical diversity in order to optimize pharmaceutical properties of lead compounds and generate active analogs, replacing problematic substructures inside lead compounds by others with similar physicochemical properties. This can surpass the limitations observed for the original lead compound. Bioisosterism can be a useful strategy in order to optimize lead compounds searching analogs with better selectivity and synthetic accessibility, decreased toxicity, improved pharmacokinetics, enhanced solubility and metabolic stability. In Chapter 4, authors highlight the computational approaches used to identify potential bioisosters, discuss how bioisosterism can be helpful during the design of molecules with better synthetic accessibility, and review the scaffold hopping technique, a novel trend of bioisosterism application intending to identify interchangeable scaffolds among pharmaceutical interesting molecules.

This book thus attempts to convey a few selected topics stimulating the fascination of working in all the multidisciplinary areas, which overlaps knowledge of chemistry, physics, biochemistry, biology and pharmacology, describing some of the theoretical and experimental methods in Medicinal Chemistry.

Ramaswamy Sarma
State University of New York
Albany, NY
USA


Preface

In this book we aim to convey a few selected topics of medicinal chemistry, stimulating the fascination of working in multidisciplinary areas, which overlaps knowledge of chemistry, physics, biology, pharmacology and medicine. It contains 4 chapters, of which 3 are related to theoretical methods in medicinal chemistry and one deals with experimental/mixed methods. Docking and virtual screening methods of computational medicinal chemistry play important roles, via drug design, in aiding the pharmaceutical industries place new drugs on the market. In Chapter one we discuss virtual screening and comment on hotspots including (protein docking, stem cells, different types of ligands/targets/interactions, workflow pipelines, (cloud, high-performance, grid)-computing, chemical libraries/databases, confidence, future trends). Recent evaluations, validations, benchmarking are presented. Fifty virtual screening and docking programs are summarized. Selected applications (our work over the decades) of various models of drug design discussed in the chapter are also presented. We give the basics on binding affinities, scoring functions, molecular dynamics, water and solvation, simulations of free energies, quantum mechanics/molecular mechanics, molecular fields, molecular shapes. We also review (homology, fragment, consensus, bioisosteric, scaffold, pharmacophore, induced fit, chemogenomics, knowledge, similarity)-based models.

In Chapter 2 the main NMR experimental approaches applied to identify and characterize protein-ligand binding affinity are discussed. A good knowledge of drug-receptor, signal transduction process, and cellular recognition processes are required for understanding biological functions. For drug discovery, medicinal chemistry have focused on studies of the molecular interactions which are involved in the development of disease states. Comprehension of the underlying protein receptor-ligand recognition events at atomic levels is fundamental in the process of identification and optimization of more potent drug candidates. Novel NMR spectroscopic techniques can yield insight into protein-protein and proteinlig and interactions in solution at the molecular level. Resonance signal of the protein or the ligand can be used to identify binding events from these experiments. NMR spectroscopy parameters such as chemical shifts, relaxation times, diffusion constants, NOEs and exchange can serve as measures of binding. We have attempted to provide in this chapter an overview of the NMR spectroscopy techniques employed in the drug discovery process.

In chapter 3, we discuss the computational strategies, methods and softwares currently used to profile ADMET and how they can be helpful during drug design. Many drug candidate failures during clinical trials occur due to inappropriate ADMET properties. Consequently, there is a major concern to identify possible ADMET failures during the early stages of drug design projects in order to optimize these properties and reduce time and costs. In silico ADMET predictions involve various strategies that play a central role when considering the task of profiling lead compounds for potential ADMET failures.

The authors highlight in chapter 4 the computational approaches used to identify potential bioisosters and discuss how bioisosterism can be helpful during the design of molecules with better synthetic accessibility. We also review the scaffold hopping technique, a novel trend of bioisosterism applications with the objective of identifying interchangeable scaffolds within pharmaceutical interesting molecules. Bioisosterism is a molecular modification medicinal chemistry strategy applied during drug design projects when a lead compound is available. The idea of this concept is centered at the use of chemical diversity in order to optimize pharmaceutical properties of lead compounds and generate active analogs, replacing problematic substructures inside lead compounds for others with similar physicochemical properties. We can thus surpass the limitations observed for the original lead compound. This strategy can be useful to optimize lead compounds searching analogs with better selectivity and synthetic accessibility, decreased toxicity, improved pharmacokinetics, enhanced solubility and metabolic stability.

Some contents of this book also reflect some of our own ideas and personal experiences, which are presented in selected topics.

Carlton A. Taft
Centro Brasileiro de Pesquisas Físicas
Brazil

List of Contributors

Editor(s):
Carlton Anthony Taft
Brazilian Center for Physics Research
Brazil


Carlos Henrique Tomich de Paula da Silva
University of São Paulo
Brazil




Contributor(s):
Carlton A. Taft
Full Professor, Brazilian Center for Physics Research
Rio de Janeiro
Brazil


Carlos H. T. P. Silva
Associate Professor, School of Pharmaceutical Sciences of Ribeirão Preto
University of São Paulo
Ribeirão Preto
Brazil


Vinícius B. Silva
Assistant Professor, Catholic University of Goiás
Goiânia
Brazil


Daniel Fábio Kawano
Assistant Professor, School of Pharmacy
Federal University of Rio Grande do Sul
Porto Alegre
Rio Grande do Sul
Brasil


Peterson de Andrade
Postdoctoral Researcher, School of Pharmaceutical Sciences of Ribeirão Preto
University of São Paulo
Ribeirão Preto
SP
Brazil


Susimaire P. Mantoani
Postdoctoral Researcher, School of Pharmaceutical Sciences of Ribeirão Preto
University of São Paulo
Ribeirão Preto
SP
Brazil


Flávio R. Pinsetta
Fellow, School of Pharmaceutical Sciences of Ribeirão Preto
University of São Paulo
Ribeirão Preto
SP
Brazil


Evandro P. Semighini
Postdoctoral Researcher, Ribeirão Preto Medical School
University of São Paulo
Ribeirão Preto
SP
Brazil


Ricardo P. Rodrigues
Postdoctoral Researcher, School of Pharmaceutical Sciences of Ribeirão Preto
University of São Paulo
Ribeirão Preto
SP
Brazil


G. R. P. Malpass
Assistant Professor, Federal Institute of Triangulo Mineiro
Ituiutaba
MG
Brazil


Jonathan Resende de Almeida
Fellow, School of Pharmaceutical Sciences of Ribeirão Preto
University of São Paulo
Ribeirão Preto
SP
Brazil




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