Fragment library design: efficiently hunting drugs in chemical space

Critical Assessment of a Structure-Based Screening Campaign for IDO1 Inhibitors: Tips and Pitfalls

Over the last two decades, indoleamine 2,3-dioxygenase 1 (IDO1) has attracted wide interest as a key player in immune regulation, fostering the design and development of small molecule inhibitors to restore immune response in tumor immunity. In this framework, biochemical, structural, and pharmacological studies have unveiled peculiar structural plasticity of IDO1, with different conformations and functional states that are coupled to fine regulation of its catalytic activity and non-enzymic functions. The large plasticity of IDO1 may affect its ligand recognition process, generating bias in structure-based drug design campaigns. In this work, we report a screening campaign of a fragment library of compounds, grounding on the use of three distinct conformations of IDO1 that recapitulate its structural plasticity to some extent. Results are instrumental to discuss tips and pitfalls that, due to the large plasticity of the enzyme, may influence the identification of novel and differentiated chemical scaffolds of IDO1 ligands in structure-based screening campaigns.

Novel drug design and bioinformatics: an introduction

In the current era of high-throughput technology, where enormous amounts of biological data are generated day by day via various sequencing projects, thereby the staggering volume of biological targets deciphered. The discovery of new chemical entities and bioisosteres of relatively low molecular weight has been gaining high momentum in the pharmacopoeia, and traditional combinatorial design wherein chemical structure is used as an initial template for enhancing efficacy pharmacokinetic selectivity properties. Once the compound is identified, it undergoes ADMET filtration to ensure whether it has toxic and mutagenic properties or not. If the compound has no toxicity and mutagenicity is either considered a potential lead molecule. Understanding the mechanism of lead molecules with various biological targets is imperative to advance related functions for drug discovery and development. Notwithstanding, a tedious and costly process, taking around 10–15 years and costing around $4 billion, cascaded approached of Bioinformatics and Computational biology viz., structure-based drug design (SBDD) and cognate ligand-based drug design (LBDD) respectively rely on the availability of 3D structure of target biomacromolecules and vice versa has made this process easy and approachable. SBDD encompasses homology modelling, ligand docking, fragment-based drug design and molecular dynamics, while LBDD deals with pharmacophore mapping, QSAR, and similarity search. All the computational methods discussed herein, whether for target identification or novel ligand discovery, continuously evolve and facilitate cost-effective and reliable outcomes in an era of overwhelming data.

Fragment- and structure-based drug discovery for developing therapeutic agents targeting the DNA Damage Response

Cancer will directly affect the lives of over one-third of the population. The DNA Damage Response (DDR) is an intricate system involving damage recognition, cell cycle regulation, DNA repair, and ultimately cell fate determination, playing a central role in cancer etiology and therapy. Two primary therapeutic approaches involving DDR targeting include: combinatorial treatments employing anticancer genotoxic agents; and synthetic lethality, exploiting a sporadic DDR defect as a mechanism for cancer-specific therapy. Whereas, many DDR proteins have proven "undruggable", Fragment- and Structure-Based Drug Discovery (FBDD, SBDD) have advanced therapeutic agent identification and development. FBDD has led to 4 (with ∼50 more drugs under preclinical and clinical development), while SBDD is estimated to have contributed to the development of >200, FDA-approved medicines. Protein X-ray crystallography-based fragment library screening, especially for elusive or "undruggable" targets, allows for simultaneous generation of hits plus details of protein-ligand interactions and binding sites (orthosteric or allosteric) that inform chemical tractability, downstream biology, and intellectual property. Using a novel high-throughput crystallography-based fragment library screening platform, we screened five diverse proteins, yielding hit rates of ∼2-8% and crystal structures from ∼1.8 to 3.2 Å. We consider current FBDD/SBDD methods and some exemplary results of efforts to design inhibitors against the DDR nucleases meiotic recombination 11 (MRE11, a.k.a., MRE11A), apurinic/apyrimidinic endonuclease 1 (APE1, a.k.a., APEX1), and flap endonuclease 1 (FEN1).

Fragment-Based Design of a Potent MAT2a Inhibitor and in Vivo Evaluation in an MTAP Null Xenograft Model

MAT2a is a methionine adenosyltransferase that synthesizes the essential metabolite S-adenosylmethionine (SAM) from methionine and ATP. Tumors bearing the co-deletion of p16 and MTAP genes have been shown to be sensitive to MAT2a inhibition, making it an attractive target for treatment of MTAP-deleted cancers. A fragment-based lead generation campaign identified weak but efficient hits binding in a known allosteric site. By use of structure-guided design and systematic SAR exploration, the hits were elaborated through a merging and growing strategy into an arylquinazolinone series of potent MAT2a inhibitors. The selected in vivo tool compound 28 reduced SAM-dependent methylation events in cells and inhibited proliferation of MTAP-null cells in vitro. In vivo studies showed that 28 was able to induce antitumor response in an MTAP knockout HCT116 xenograft model.

Chespa: Streamlining Expansive Chemical Space Evaluation of Molecular Sets

Thousands of chemical properties can be calculated for small molecules, which can be used to place the molecules within the context of a broader "chemical space." These definitions vary based on compounds of interest and the goals for the given chemical space definition. Here, we introduce a customizable Python module, chespa, built to easily assess different chemical space definitions through clustering of compounds in these spaces and visualizing trends of these clusters. To demonstrate this, chespa currently streamlines prediction of various molecular descriptors (predicted chemical properties, molecular substructures, AI-based chemical space, and chemical class ontology) in order to test six different chemical space definitions. Furthermore, we investigated how these varying definitions trend with mass spectrometry (MS)-based observability, that is, the ability of a molecule to be observed with MS (e.g., as a function of the molecule ionizability), using an example data set from the U.S. EPA's nontargeted analysis collaborative trial, where blinded samples had been analyzed previously, providing 1398 data points. Improved understanding of observability would offer many advantages in small-molecule identification, such as (i) a priori selection of experimental conditions based on suspected sample composition, (ii) the ability to reduce the number of candidate structures during compound identification by removing those less likely to ionize, and, in turn, (iii) a reduced false discovery rate and increased confidence in identifications. Factors controlling observability are not fully understood, making prediction of this property nontrivial and a prime candidate for chemical space analysis. Chespa is available at github.com/pnnl/chespa.

The Symbiotic Relationship Between Drug Discovery and Organic Chemistry

All pharmaceutical products contain organic molecules; the source may be a natural product or a fully synthetic molecule, or a combination of both. Thus, it follows that organic chemistry underpins both existing and upcoming pharmaceutical products. The reverse relationship has also affected organic synthesis, changing its landscape towards increasingly complex targets. This Review article sets out to give a concise appraisal of this symbiotic relationship between organic chemistry and drug discovery, along with a discussion of the design concepts and highlighting key milestones along the journey. In particular, criteria for a high-quality compound library design enabling efficient virtual navigation of chemical space, as well as rise and fall of concepts for its synthetic exploration (such as combinatorial chemistry; diversity-, biology-, lead-, or fragment-oriented syntheses; and DNA-encoded libraries) are critically surveyed.

Harnessing the Properties of Natural Products

Natural products (NPs) have been used as traditional medicines since antiquity. With more than 10⁶⁰ estimated compounds with molecular weights less than 500 Da representing chemical space, NPs occupy a very small percentage; however, they are significantly overrepresented in biologically relevant chemical space. The classical approach concentrates on identifying one or more NPs with biological activity from a source organism. There is much more to be learned from NPs than we can discover this narrow view. In this review, we discuss ways to harness the global properties of NPs.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

High throughput screening using acoustic droplet ejection to combine protein crystals and chemical libraries on crystallization plates at high density

We describe a high throughput method for screening up to 1728 distinct chemicals with protein crystals on a single microplate. Acoustic droplet ejection (ADE) was used to co-position 2.5nL of protein, precipitant, and chemicals on a MiTeGen in situ-1 crystallization plate™ for screening by co-crystallization or soaking. ADE-transferred droplets follow a precise trajectory which allows all components to be transferred through small apertures in the microplate lid. The apertures were large enough for 2.5nL droplets to pass through them, but small enough so that they did not disrupt the internal environment created by the mother liquor. Using this system, thermolysin and trypsin crystals were efficiently screened for binding to a heavy-metal mini-library. Fluorescence and X-ray diffraction were used to confirm that each chemical in the heavy-metal library was correctly paired with the intended protein crystal. A fragment mini-library was screened to observe two known lysozyme ligands using both co-crystallization and soaking. A similar approach was used to identify multiple, novel thaumatin binding sites for ascorbic acid. This technology pushes towards a faster, automated, and more flexible strategy for high throughput screening of chemical libraries (such as fragment libraries) using as little as 2.5nL of each component.

Structure-based virtual screening for fragment-like ligands of the G protein-coupled histamine H4 receptor

Structure-based virtual screening using H₁R- and β₂R-based histamine H₄R homology models identified 9 fragments with an affinity ranging from 0.14 to 6.3 μm for H₄R.

Hitting the target: fragment screening with acoustic in situ co-crystallization of proteins plus fragment libraries on pin-mounted data-collection micromeshes

Acoustic droplet ejection (ADE) is a powerful technology that supports crystallographic applications such as growing, improving and manipulating protein crystals. A fragment-screening strategy is described that uses ADE to co-crystallize proteins with fragment libraries directly on MiTeGen MicroMeshes. Co-crystallization trials can be prepared rapidly and economically. The high speed of specimen preparation and the low consumption of fragment and protein allow the use of individual rather than pooled fragments. The Echo 550 liquid-handling instrument (Labcyte Inc., Sunnyvale, California, USA) generates droplets with accurate trajectories, which allows multiple co-crystallization experiments to be discretely positioned on a single data-collection micromesh. This accuracy also allows all components to be transferred through small apertures. Consequently, the crystallization tray is in equilibrium with the reservoir before, during and after the transfer of protein, precipitant and fragment to the micromesh on which crystallization will occur. This strict control of the specimen environment means that the crystallography experiments remain identical as the working volumes are decreased from the few microlitres level to the few nanolitres level. Using this system, lysozyme, thermolysin, trypsin and stachydrine demethylase crystals were co-crystallized with a small 33-compound mini-library to search for fragment hits. This technology pushes towards a much faster, more automated and more flexible strategy for structure-based drug discovery using as little as 2.5 nl of each major component.

Assembly of a π-π stack of ligands in the binding site of an acetylcholine-binding protein

Acetylcholine-binding protein is a water-soluble homologue of the extracellular ligand-binding domain of cys-loop receptors. It is used as a structurally accessible prototype for studying ligand binding to these pharmaceutically important pentameric ion channels, in particular to nicotinic acetylcholine receptors, due to conserved binding site residues present at the interface between two subunits. Here we report that an aromatic conjugated small molecule binds acetylcholine-binding protein in an ordered π-π stack of three identical molecules per binding site, two parallel and one antiparallel. Acetylcholine-binding protein stabilizes the assembly of the stack by aromatic contacts. Thanks to the plasticity of its ligand-binding site, acetylcholine-binding protein can accommodate the formation of aromatic stacks of different size by simple loop repositioning and minimal adjustment of the interactions. This type of supramolecular binding provides a novel paradigm in drug design.

Design and Evaluation of the Performance of an NMR Screening Fragment Library

The design of a suitable library is an essential prerequisite to establish a fragment-based screening capability. Several pharmaceutical companies have described their approaches to establishing fragment libraries; however there are few detailed reports of both design and analysis of performance for a fragment library maintained in an academic setting. Here we report our efforts towards the design of a fragment library for nuclear magnetic resonance spectroscopy-based screening, demonstrate the performance of the library through analysis of 14 screens, and present a comparison to previously reported fragment libraries.

Construction of the CSIRO Fragment Library

A fundamental component of a successful fragment screening program is a productive fragment library, one that delivers hit fragments with potential for pharmaceutical development. A proprietary fragment library was developed by identifying and extracting subsets of CSIRO’s Compound Collection using two complimentary approaches. Over time, the use of surface plasmon resonance as a front-line screening tool has enabled identification and exclusion of problematic compounds and led to a more reliable fragment screening library.

Small and colorful stones make beautiful mosaics: fragment-based chemogenomics

Smaller stones with a wide variety of colors make a higher resolution mosaic. In much the same way, smaller chemical entities that are structurally diverse are better able to interrogate protein binding sites. This feature article describes the construction of a diverse fragment library and an analysis of the screening of six representative protein targets belonging to three diverse target classes (G protein-coupled receptors ADRB2, H1R, H3R, and H4R, the ligand-gated ion channel 5-HT3R, and the kinase PKA) using chemogenomics approaches. The integration of experimentally determined bioaffinity profiles across related and unrelated protein targets and chemogenomics analysis of fragment binding and protein structure allow the identification of: (i) unexpected similarities and differences in ligand binding properties, and (ii) subtle ligand affinity and selectivity cliffs. With a wealth of fragment screening data being generated in industry and academia, such approaches will contribute to a more detailed structural understanding of ligand-protein interactions.

The role of fragment-based and computational methods in polypharmacology

Polypharmacology-based strategies are gaining increased attention as a novel approach to obtaining potentially innovative medicines for multifactorial diseases. However, some within the pharmaceutical community have resisted these strategies because they can be resource-hungry in the early stages of the drug discovery process. Here, we report on fragment-based and computational methods that might accelerate and optimize the discovery of multitarget drugs. In particular, we illustrate that fragment-based approaches can be particularly suited for polypharmacology, owing to the inherent promiscuous nature of fragments. In parallel, we explain how computer-assisted protocols can provide invaluable insights into how to unveil compounds theoretically able to bind to more than one protein. Furthermore, several pragmatic aspects related to the use of these approaches are covered, thus offering the reader practical insights on multitarget-oriented drug discovery projects.