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.