Concepts and Core Principles of Fragment-Based Drug Design

In this review, a general introduction to fragment-based drug design and the underlying concepts is given. General considerations and methodologies ranging from library selection/construction over biophysical screening and evaluation methods to in-depth hit qualification and subsequent optimization strategies are discussed. These principles can be generally applied to most classes of drug targets. The examples given for fragment growing, merging, and linking strategies at the end of the review are set in the fields of enzyme-inhibitor design and macromolecule–macromolecule interaction inhibition. Building upon the foundation of fragment-based drug discovery (FBDD) and its methodologies, we also highlight a few new trends in FBDD.

Thermodynamic profiling for fragment-based lead discovery and optimization

Introduction: The enthalpic and entropic components of the ligand-protein binding free energy reflect the type and quality of the interactions and relate to the physicochemical properties of the ligands. These findings have significance in medicinal chemistry optimizations since they suggest that the thermodynamic profiling of the binding may help monitor and control the unfavorable size and hydrophobicity increase typically accompanying affinity improvements and leading to suboptimal pharmacokinetic properties.Areas covered: This review describes the ligand-protein binding event in terms of elementary steps, their associated interactions, and their enthalpic and entropic consequences. The relationships among the breaking and forming interactions, the binding thermodynamic profile, and the physicochemical properties of the ligands are also discussed.Expert opinion: Analysis of the size dependence of available affinity and favorable enthalpy highlights the limitation of the simultaneous optimization of these quantities. Indeed, moderate, rather than very high affinities can be conciliated with favorable physicochemical and pharmacokinetic profiles as it is supported by the affinity range of historical oral drugs. Although thermodynamic quantities are not suitable endpoints for medicinal chemistry optimizations owing to the complexity of the binding thermodynamics, thermodynamic profiling together with structural studies can be advantageously used to understand the details of the binding process and to optimize it.

Chemistry-driven Hit-to-lead Optimization Guided by Structure-based Approaches

For several decades, hit identification for drug discovery has been facilitated by developments in both fragment-based and high-throughput screening technologies. However, a major bottleneck in drug discovery projects continues to be the optimization of primary hits from screening campaigns in order to derive lead compounds. Computational chemistry or molecular modeling can play an important role during this hit-to-lead (H2L) stage by both suggesting putative optimizations and decreasing the number of compounds to be experimentally synthesized and evaluated. However, it is also crucial to consider the feasibility of organically synthesizing these virtually designed compounds. Furthermore, the generated molecules should have reasonable physicochemical properties and be medicinally relevant. This review focuses on chemistry-driven and structure-based computational methods that can be used to tackle the difficult problem of H2L optimization, with emphasis being placed on the strategy developed in our laboratory.

Creation of Novel Cores for β-Secretase (BACE-1) Inhibitors: A Multiparameter Lead Generation Strategy

In order to find optimal core structures as starting points for lead optimization, a multiparameter lead generation workflow was designed with the goal of finding BACE-1 inhibitors as a treatment for Alzheimer's disease. De novo design of core fragments was connected with three predictive in silico models addressing target affinity, permeability, and hERG activity, in order to guide synthesis. Taking advantage of an additive SAR, the prioritized cores were decorated with a few, well-characterized substituents from known BACE-1 inhibitors in order to allow for core-to-core comparisons. Prediction methods and analyses of how physicochemical properties of the core structures correlate to in vitro data are described. The syntheses and in vitro data of the test compounds are reported in a separate paper by Ginman et al. [J. Med. Chem. 2013, 56, 4181-4205]. The affinity predictions are described in detail by Roos et al. [J. Chem. Inf. 2014, DOI: 10.1021/ci400374z].