New Developments in Medicinal Chemistry

The current state of the art for docking and virtual screening methods in drug design have been reviewed, emphasizing their important contribution in aiding drug design and discovery. We summarize our contributions during the last decade, with proposals of novel inhibitors for Cancer, AIDS, Diabetes, Parkinson, Alzheimer and other diseases. Homology, fragment, consensus, bioisosteric, scaffold, pharmacophore, induced fit, chemogenomics and knowledge-based protocols have been described. The basics have been given for binding affinities, molecular dynamics, water and solvation, QM, QM/MM, free energy simulations, molecular shapes and fields. We also discuss virtual screening and comment on hotspots (protein docking, stem cells, workflow pipelines, different types of ligands/targets, cloud, high-performance, grid computing, chemical libraries, evaluations, benchmarks and validations). We describe the procedures of fifty programs that use the protocols reviewed.

Deep knowledge of how the binding processes occur, such as drugreceptor, signal transduction and cellular recognition, is indispensable for a greater understanding 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 state. Thereby, an accurate knowledge about the underlying protein receptor-ligand recognition events at atomic level is fundamental in the process to comprehension, identification and optimization of more potent drug candidates. In this sense, several novel NMR spectroscopic techniques can yield insight into protein-protein interactions in solutions at the molecular level. Resonance signal of the protein or the ligand can be used to identify binding events from a broad range of experiments. For this purpose, changes in NMR spectroscopy parameters such as chemical shifts, relaxation times, diffusion constants, NOEs or exchange of saturation can serve as a measure of binding. In this chapter, the main NMR experimental approaches applied to characterize protein-ligand binding affinity will be discussed. Thus, we hope to provide the reader with a broader and better understanding of how NMR spectroscopy techniques can be applied to a drug discovery process.

Most drug candidate failures during clinical trials occur 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. In silico ADMET predictions comprise various strategies that play a central role when considering the task of profiling lead compounds regarding potential ADMET failures. We will discuss the computational strategies, methods and softwares used, actually, to profile ADMET and how they could 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 idea 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 that can improve the limitations observed for the original lead compound. Bioisosterism can be a useful strategy in order to optimize lead compounds searching for analogs with better selectivity and synthetic accessibility, decreased toxicity, improved pharmacokinetics, enhanced solubility and metabolic stability. This chapter highlights the computational approaches used to identify potential bioisosters, discusses how bioisosterism can be helpful during the design of molecules with better synthetic accessibility, and reviews the scaffold hopping technique, a novel trend of bioisosterism application intended to identify interchangeable scaffolds among pharmaceutical interesting molecules.