Fragment-to-Lead Medicinal Chemistry Publications in 2020

Identification of fragments targeting SMYD3 using highly sensitive kinetic and multiplexed biosensor-based screening

A 1056-membered fragment library has been screened against SMYD3 using a novel multiplexed experimental design implemented in a grating coupled interferometry (GCI)-based biosensor. SMYD3 is a prospective target for anticancer drugs and the focus has initially been on discovery of inhibitors of its lysine methyl transferase activity. However, it has multiple protein interaction partners and several potential roles in carcinogenesis. It therefore remains unclear what mode of action ligands targeting the protein should have. Our goal was therefore to identify new ligands and discriminate hits that interact with the active site and those that interact with other sites. In addition, we were interested in selecting hits based on kinetic features rather than affinity. Screening was done in parallel against SMYD3 alone or SMYD3 with the active site blocked by a tight binding inhibitor. Hit selection was primarily based on dissociation rates. In total, 20 fragments were selected as hits, of which half apparently targeted the active site and half targeted other sites. Twelve of the hits were selected for structural analysis using X-ray crystallography in order to identify binding sites and modes of binding. Four of the hits were successfully identified in crystal structures with SMYD3; the others did not show any electron densities for ligands in the crystals. Although it might be possible to optimize the crystallography approach for a better success rate, it was clear that the sensitivity and time resolution of the biosensor assay was exceptional and enabled kinetic rate constants to be estimated for fragments. Fragments are typically considered to interact too rapidly for such quantification to be possible. This approach consequently represents a paradigm shift. In addition, the multiplexed approach allows ligands targeting different sites to be rationally selected already in the fragment library screening stage.

Site Identification and Next Choice Protocol for Hit-to-Lead Optimization

Time efficiency and cost savings are major challenges in drug discovery and development. In this process, the hit-to-lead stage is expected to improve efficiency because it primarily exploits the trial-and-error approach of medicinal chemists. This study proposes a site identification and next choice (SINCHO) protocol to improve the hit-to-lead efficiency. This protocol selects an anchor atom and growth site pair, which is desirable for a hit-to-lead strategy starting from a 3D complex structure. We developed and fine-tuned the protocol using a training data set and assessed it using a test data set of the preceding hit-to-lead strategy. The protocol was tested for experimentally determined structures and molecular dynamics (MD) ensembles. The protocol had a high prediction accuracy for applying MD ensembles, owing to the consideration of protein flexibility. The SINCHO protocol enables medicinal chemists to visualize and modify functional groups in a hit-to-lead manner.

FragGrow: A Web Server for Structure-Based Drug Design by Fragment Growing within Constraints

Fragment growing is an important ligand design strategy in drug discovery. In this study, we present FragGrow, a web server that facilitates structure-based drug design by fragment growing. FragGrow offers two working modes: one for growing molecules through the direct replacement of hydrogen atoms or substructures and the other for growing via virtual synthesis. FragGrow works by searching for suitable fragments that meet a set of constraints from an indexed 3D fragment database and using them to create new compounds in 3D space. The users can set a range of constraints when searching for their desired fragment, including the fragment's ability to interact with specific protein sites; its size, topology, and physicochemical properties; and the presence of particular heteroatoms and functional groups within the fragment. We hope that FragGrow will serve as a useful tool for medicinal chemists in ligand design. The FragGrow server is freely available to researchers and can be accessed at https://fraggrow.xundrug.cn.

Practical Three-Component Regioselective Synthesis of Drug-Like 3-Aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines as Potential Non-Covalent Multi-Targeting Inhibitors To Combat Neurodegenerative Diseases

Neurodegenerative diseases (NDs) are one of the prominent health challenges facing contemporary society, and many efforts have been made to overcome and (or) control it. In this research paper, we described a practical one-pot two-step three-component reaction between 3,4-dihydronaphthalen-1(2H)-one (1), aryl(or heteroaryl)glyoxal monohydrates (2a-h), and hydrazine monohydrate (NH2NH2•H2O) for the regioselective preparation of some 3-aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnoline derivatives (3a-h). After synthesis and characterization of the mentioned cinnolines (3a-h), the in silico multi-targeting inhibitory properties of these heterocyclic scaffolds have been investigated upon various Homo sapiens-type enzymes, including hMAO-A, hMAO-B, hAChE, hBChE, hBACE-1, hBACE-2, hNQO-1, hNQO-2, hnNOS, hiNOS, hPARP-1, hPARP-2, hLRRK-2(G2019S), hGSK-3β, hp38α MAPK, hJNK-3, hOGA, hNMDA receptor, hnSMase-2, hIDO-1, hCOMT, hLIMK-1, hLIMK-2, hRIPK-1, hUCH-L1, hPARK-7, and hDHODH, which have confirmed their functions and roles in the neurodegenerative diseases (NDs), based on molecular docking studies, and the obtained results were compared with a wide range of approved drugs and well-known (with IC50, EC50, etc.) compounds. In addition, in silico ADMET prediction analysis was performed to examine the prospective drug properties of the synthesized heterocyclic compounds (3a-h). The obtained results from the molecular docking studies and ADMET-related data demonstrated that these series of 3-aryl(or heteroaryl)-5,6-dihydrobenzo[h]cinnolines (3a-h), especially hit ones, can really be turned into the potent core of new drugs for the treatment of neurodegenerative diseases (NDs), and/or due to the having some reactionable locations, they are able to have further organic reactions (such as cross-coupling reactions), and expansion of these compounds (for example, with using other types of aryl(or heteroaryl)glyoxal monohydrates) makes a new avenue for designing novel and efficient drugs for this purpose.

Identification of BACE-1 inhibitors through directed C(sp3)-H activation on 5-oxo-pyrrolidine-3-carboxylic acid derivatives

Convenient synthesis of stereochemically dense 5-oxo-pyrrolidines was obtained from succinic anyhdride and imines by combining the Castagnoli-Cushman reaction with directed Pd-catalyzed C(sp3)-H functionalization, taking advantage of the developing carboxylic group properly derivatized with 8-aminoquinoline as a directing group. These fully substituted 5-oxopyrrolidines were found to be able to inhibit BACE-1 enzyme with sub-micromolar activity, thanks to the interaction of the key aryl appendage introduced by C(sp3)-H activation within BACE-1 S2' subsite.

Fragment-to-Lead Medicinal Chemistry Publications in 2022

This Perspective is the eighth in an annual series that summarizes successful fragment-to-lead (F2L) case studies published each year. A tabulated summary of relevant articles published in 2022 is provided, and features such as target class, screening methods, and ligand efficiency are discussed both for the 2022 examples and for the combined examples over the years 2015-2022. In addition, trends and new developments in the field are summarized. In 2022, 18 publications described successful fragment-to-lead studies, including the development of three clinical compounds (MTRX1719, MK-8189, and BI-823911).

Enabling synthesis in fragment-based drug discovery (FBDD): microscale high-throughput optimisation of the medicinal chemist's toolbox reactions

Miniaturised high-throughput experimentation (HTE) is widely employed in industrial and academic laboratories for rapid reaction optimisation using material-limited, multifactorial reaction condition screening. In fragment-based drug discovery (FBDD), common toolbox reactions such as the Suzuki-Miyaura and Buchwald-Hartwig cross couplings can be hampered by the fragment's intrinsic heteroatom-rich pharmacophore which is required for ligand-protein binding. At Astex, we are using microscale HTE to speed up reaction optimisation and prevent target down-prioritisation. By identifying catalyst/base/solvent combinations which tolerate unprotected heteroatoms we can rapidly optimise key cross-couplings and expedite route design by avoiding superfluous protecting group manipulations. However, HTE requires extensive upfront training, and this modern automated synthesis technique largely differs to the way organic chemists are traditionally trained. To make HTE accessible to all our synthetic chemists we have developed a semi-automated workflow enabled by pre-made 96-well screening kits, rapid analytical methods and in-house software development, which is empowering chemists at Astex to run HTE screens independently with minimal training.

Coumarins as factor XIIa inhibitors: Potency and selectivity improvements using a fragment-based strategy

Previously, we described weak coumarin inhibitors of factor XIIa, a promising target for artificial surface-induced thrombosis and various inflammatory diseases. In this work, we used fragment-based drug discovery approach to improve our coumarin series. First, we screened about 200 fragments for the S1 pocket. The S1 pocket of trypsin-like serine proteases, such as factor XIIa, is highly conserved and is known to drive a major part of the association energy. From the screening, we selected fragments displaying a micromolar activity and studied their selectivity on other serine proteases. Then, these fragments were merged to our coumarin templates, leading to the generation of nanomolar inhibitors. The mechanism of inhibition was further studied by mass spectrometry demonstrating the covalent binding through the formation of an acyl enzyme complex. The most potent compound was tested in plasma to evaluate its stability and efficacy on coagulation assays. It exhibited a plasmatic half-life of 1.9 h and a good selectivity for the intrinsic coagulation pathway over the extrinsic one.

CuII Pyrazolyl-Benzimidazole Dinuclear Complexes with Remarkable Antioxidant Activity

Three dinuclear coordination complexes generated from 1-n-butyl-2-((5-methyl-1H-pyrazole-3-yl)methyl)-1H-benzimidazole (L), have been synthesized and characterized spectroscopically and structurally by single crystal X-ray diffraction analysis. Reaction with iron(II) chloride and then copper(II) nitrate led to a co-crystal containing 78 % of [Cu(NO3 )(μ-Cl)(L')]2 (C1 ) and 22 % of [Cu(NO3 )(μ-NO3 )(L')]2 (C2 ), where L was oxidized to a new ligand L' . A mechanism is provided. Reaction with copper chloride led to the dinuclear complex [Cu(Cl)(μ-Cl)(L)]2 (C3 ). The presence of N-H⋅⋅⋅O and C-H⋅⋅⋅O intermolecular interactions in the crystal structure of C1 and C2 , and C-H⋅⋅⋅N and C-H⋅⋅⋅Cl hydrogen bonding in the crystal structure of C3 led to supramolecular structures that were confirmed by Hirshfeld surface analysis. The ligands and their complexes were tested for free radical scavenging activity and ferric reducing antioxidant power. The complex C1 /C2 shows remarkable antioxidant activities as compared to the ligand L and reference compounds.

TWN-FS method: A novel fragment screening method for drug discovery

Fragment-based drug discovery (FBDD) is a well-established and effective method for generating diverse and novel hits in drug design. Kinases are suitable targets for FBDD due to their well-defined structure. Water molecules contribute to structure and function of proteins and also influence the environment within the binding pocket. Water molecules form a variety of hydrogen-bonded cyclic water-ring networks, collectively known as topological water networks (TWNs). Analyzing the TWNs in protein binding sites can provide valuable insights into potential locations and shapes for fragments within the binding site. Here, we introduce TWN-based fragment screening (TWN-FS) method, a novel screening method that suggests fragments through grouped TWN analysis within the protein binding site. We used this method to screen known CDK2, CHK1, IGF1R and ERBB4 inhibitors. Our findings suggest that TWN-FS method has the potential to effectively screen fragments. The TWN-FS method package is available on GitHub at https://github.com/pkj0421/TWN-FS.

Estimating the hydrophobicity extent of molecular fragments using reversed-phase liquid chromatography

A fast HPLC method was developed to study the hydrophobicity extent of pharmaceutically relevant molecular fragments. By this strategy, the reduced amount of sample available for physico-chemical evaluations in early-phase drug discovery programs does not represent a limiting factor. The sixteen acid fragments investigated were previously synthesized also determining potentiometrically their experimental log D values. For four fragments it was not possible to determine such property since their values were outside of the instrumental working range (2 < pKa  < 12). An RP-HPLC method was therefore optimized. For each scrutinized method, some derived chromatographic indices were calculated, and Pearson's correlation coefficient (r) allowed to select the so-called "φ0 index" as the best correlating with the log D. Thew s p H ${}_w^spH$ was fixed at 3.5 and a modification of some variables [organic modifier (methanol vs. ACN), stationary phase (octyl vs. octadecyl), presence/absence of the additives n-octanol, n-butylamine, and n-octylamine], allowed to select the best correlation conditions, producing a r = 0.94 (p < 0.001). Importantly, the φ0 index enabled the estimation of log D values for four fragments which were unattainable by potentiometric titration. Moreover, a series of molecular descriptors were calculated to identify the chemical characteristics of the fragments explaining the obtained φ0 . The number of hydrogen bond donors and the index of cohesive interaction correlated with the experimental data.

FFLOM: A Flow-Based Autoregressive Model for Fragment-to-Lead Optimization

Recently, deep generative models have been regarded as promising tools in fragment-based drug design (FBDD). Despite the growing interest in these models, they still face challenges in generating molecules with desired properties in low data regimes. In this study, we propose a novel flow-based autoregressive model named FFLOM for linker and R-group design. In a large-scale benchmark evaluation on ZINC, CASF, and PDBbind test sets, FFLOM achieves state-of-the-art performance in terms of validity, uniqueness, novelty, and recovery of the generated molecules and can recover over 92% of the original molecules in the PDBbind test set (with at least five atoms). FFLOM also exhibits excellent potential applicability in several practical scenarios encompassing fragment linking, PROTAC design, R-group growing, and R-group optimization. In all four cases, FFLOM can perfectly reconstruct the ground-truth compounds and generate over 74% of molecules with novel fragments, some of which have higher binding affinity than the ground truth.

Fragment expansion with NUDELs - poised DNA-encoded libraries

Optimisation of the affinity of lead compounds is a critical challenge in the identification of drug candidates and chemical probes and is a process that takes many years. Fragment-based drug discovery has become established as one of the methods of choice for drug discovery starting with small, low affinity compounds. Due to their low affinity, the evolution of fragments to desirable levels of affinity is often a key challenge. The accepted best method for increasing the potency of fragments is by iterative fragment growing, which can be very time consuming and complex. Here, we introduce a paradigm for fragment hit optimisation using poised DNA-encoded chemical libraries (DELs). The synthesis of a poised DEL, a partially constructed library that retains a reactive handle, allows the coupling of any active fragment for a specific target protein, allowing rapid discovery of potent ligands. This is illustrated for bromodomain-containing protein 4 (BRD4), in which a weakly binding fragment was coupled to a 42-member poised DEL via Suzuki-Miyaura cross coupling resulting in the identification of an inhibitor with 51 nM affinity in a single step, representing an increase in potency of several orders of magnitude from an original fragment. The potency of the compound was shown to arise from the synergistic combination of substructures, which would have been very difficult to discover by any other method and was rationalised by X-ray crystallography. The compound showed attractive lead-like properties suitable for further optimisation and demonstrated BRD4-dependent cellular pharmacology. This work demonstrates the power of poised DELs to rapidly optimise fragments, representing an attractive generic approach to drug discovery.

Linkers in fragment-based drug design: an overview of the literature

INTRODUCTION

In fragment-based drug design, fragment linking is a popular strategy where two fragments binding to different sub-pockets of a target are linked together. This attractive method remains challenging especially due to the design of ideal linkers.

AREAS COVERED

The authors review the types of linkers and chemical reactions commonly used to the synthesis of linkers, including those utilized in protein-templated fragment self-assembly, where fragments are directly linked in the presence of the protein. Finally, they detail computational workflows and software including generative models that have been developed for fragment linking.

EXPERT OPINION

The authors believe that fragment linking offers key advantages for compound design, particularly for the design of bivalent inhibitors linking two distinct pockets of the same or different subunits. On the other hand, more studies are needed to increase the potential of protein-templated approaches in FBDD. Important computational tools such as structure-based de novo software are emerging to select suitable linkers. Fragment linking will undoubtedly benefit from developments in computational approaches and machine learning models.

Design and Evaluation of a Low Hydrogen Bond Donor Count Fragment Screening Set to Aid Hit Generation of PROTACs Intended for Oral Delivery

The development of orally bioavailable PROTACs presents a significant challenge due to the inflated physicochemical properties of such heterobifunctional molecules. Molecules occupying this "beyond rule of five" space often demonstrate limited oral bioavailability due to the compounding effects of elevated molecular weight and hydrogen bond donor count (among other properties), but it is possible to achieve sufficient oral bioavailability through physicochemical optimization. Herein, we disclose the design and evaluation of a low hydrogen bond donor count (≤1 HBD) fragment screening set to aid hit generation of PROTACs intended for an oral route of delivery. We demonstrate that application of this library can enhance fragment screens against PROTAC proteins of interest and ubiquitin ligases, yielding fragment hits containing ≤1 HBD suitable for optimizing toward orally bioavailable PROTACs.

Sulfur-fluoride exchange (SuFEx)-enabled lead discovery of AChE inhibitors by fragment linking strategies

SuFEx click chemistry has been a method for the rapid synthesis of functional molecules with desirable properties. Here, we demonstrated a workflow that allows for in situ synthesis of sulfonamide inhibitors based on SuFEx reaction for high-throughput testing of their cholinesterase activity. According to fragment-based drug discovery (FBDD), sulfonyl fluorides [R-SO₂F] with moderate activity were identified as fragment hits, rapidly diversified into 102 analogs in SuFEx reactions, and the sulfonamides were directly screened to yield drug-like inhibitors with 70-fold higher potency (IC₅₀ = 94 nM). Moreover, the improved molecule J8-A34 can ameliorate cognitive function in Aβ_1-42-induced mouse model. Since this SuFEx linkage reaction succeeds on picomole scale for direct screening, this methodology can accelerate the development of robust biological probes and drug candidates.

CMGN: a conditional molecular generation net to design target-specific molecules with desired properties

The rational design of chemical entities with desired properties for a specific target is a long-standing challenge in drug design. Generative neural networks have emerged as a powerful approach to sample novel molecules with specific properties, termed as inverse drug design. However, generating molecules with biological activity against certain targets and predefined drug properties still remains challenging. Here, we propose a conditional molecular generation net (CMGN), the backbone of which is a bidirectional and autoregressive transformer. CMGN applies large-scale pretraining for molecular understanding and navigates the chemical space for specified targets by fine-tuning with corresponding datasets. Additionally, fragments and properties were trained to recover molecules to learn the structure-properties relationships. Our model crisscrosses the chemical space for specific targets and properties that control fragment-growth processes. Case studies demonstrated the advantages and utility of our model in fragment-to-lead processes and multi-objective lead optimization. The results presented in this paper illustrate that CMGN has the potential to accelerate the drug discovery process.

An Automated, Open-Source Workflow for the Generation of (3D) Fragment Libraries

The recent success of fragment-based drug discovery (FBDD) is inextricably linked to adequate library design. To guide the design of our fragment libraries, we have constructed an automated workflow in the open-source KNIME software. The workflow considers chemical diversity and novelty of the fragments, and can also take into account the three-dimensional (3D) character. This design tool can be used to create large and diverse libraries but also to select a small number of representative compounds as a focused set of unique screening compounds to enrich existing fragment libraries. To illustrate the procedures, the design and synthesis of a 10-membered focused library is reported based on the cyclopropane scaffold, which is underrepresented in our existing fragment screening library. Analysis of the focused compound set indicates significant shape diversity and a favorable overall physicochemical profile. By virtue of its modular setup, the workflow can be readily adjusted to design libraries that focus on properties other than 3D shape.

The European Federation for Medicinal Chemistry and Chemical Biology (EFMC) Best Practice Initiative: Hit Generation

Hit generation is a crucial step in drug discovery that will determine the speed and chance of success of identifying drug candidates. Many strategies are now available to identify chemical starting points, or hits, and each biological target warrants a tailored approach. In this set of best practices, we detail the essential approaches for target centric hit generation and the opportunities and challenges they come with. We then provide guidance on how to validate hits to ensure medicinal chemistry is only performed on compounds and scaffolds that engage the target of interest and have the desired mode of action. Finally, we discuss the design of integrated hit generation strategies that combine several approaches to maximize the chance of identifying high quality starting points to ensure a successful drug discovery campaign.

Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

A new reversible transformation of oxindolylidene derivatives of imidazothiazolotriazine into 3-[(imidazotriazin-3-yl)thio]-2-oxoquinoline-4-carboxylates

A simple method for the synthesis of water-soluble potassium 3-[(imidazotriazin-3-yl)thio]-2-oxoquinoline-4-carboxylates was developed based on a new reversible transformation of oxindolylidene derivatives of imidazothiazolotriazine that results from their treatment with potassium hydroxide. The antiproliferative activity of the synthesized compounds was evaluated against 58 cell lines and compared with oxindolylidene derivatives of imidazothiazolotriazine. Quinoline derivatives 3 demonstrated high activity with average GI₅₀ values of <10 μM which are comparable or higher than those of the oxindolylidene imidazothiazolotriazines. Compound 3a, with a pent-3-yl substituent at the nitrogen atom of the quinoline fragment, possessed the highest antiproliferative activity with an average GI₅₀ value of 1.71 μM. The GI₅₀ values of compound 3a against 52 of the 58 cell lines were <1 μM; against the remaining 6 of the 58 cell lines, they were in the range 1.21-39.2 μM.

Green Drug Discovery: Novel Fragment Space from the Biomass-Derived Molecule Dihydrolevoglucosenone (CyreneTM)

Biomass-derived molecules can provide a basis for sustainable drug discovery. However, their full exploration is hampered by the dominance of millions of old-fashioned screening compounds in classical high-throughput screening (HTS) libraries frequently utilized. We propose a fragment-based drug discovery (FBDD) approach as an efficient method to navigate biomass-derived drug space. Here, we perform a proof-of-concept study with dihydrolevoglucosenone (Cyrene^TM), a pyrolysis product of cellulose. Diverse synthetic routes afforded a 100-membered fragment library with a diversity in functional groups appended. The library overall performs well in terms of novelty, physicochemical properties, aqueous solubility, stability, and three-dimensionality. Our study suggests that Cyrene-based fragments are a valuable green addition to the drug discovery toolbox. Our findings can help in paving the way for new hit drug candidates that are based on renewable resources.

Mining the Protein Data Bank to inspire fragment library design

The fragment approach has emerged as a method of choice for drug design, as it allows difficult therapeutic targets to be addressed. Success lies in the choice of the screened chemical library and the biophysical screening method, and also in the quality of the selected fragment and structural information used to develop a drug-like ligand. It has recently been proposed that promiscuous compounds, i.e., those that bind to several proteins, present an advantage for the fragment approach because they are likely to give frequent hits in screening. In this study, we searched the Protein Data Bank for fragments with multiple binding modes and targeting different sites. We identified 203 fragments represented by 90 scaffolds, some of which are not or hardly present in commercial fragment libraries. By contrast to other available fragment libraries, the studied set is enriched in fragments with a marked three-dimensional character (download at 10.5281/zenodo.7554649).

The effect of a methyl group on structure and function: Serine vs. threonine glycosylation and phosphorylation

A variety of glycan structures cover the surface of all cells and are involved in myriad biological processes, including but not limited to, cell adhesion and communication, protein quality control, signal transduction and metabolism, while also being intimately involved in innate and adaptive immune functions. Immune surveillance and responses to foreign carbohydrate antigens, such as capsular polysaccharides on bacteria and surface protein glycosylation of viruses, are the basis of microbial clearance, and most antimicrobial vaccines target these structures. In addition, aberrant glycans on tumors called Tumor-Associated Carbohydrate Antigens (TACAs) elicit immune responses to cancer, and TACAs have been used in the design of many antitumor vaccine constructs. A majority of mammalian TACAs are derived from what are referred to as mucin-type O-linked glycans on cell-surface proteins and are linked to the protein backbone through the hydroxyl group of either serine or threonine residues. A small group of structural studies that have compared mono- and oligosaccharides attached to each of these residues have shown that there are distinct differences in conformational preferences assumed by glycans attached to either "unmethylated" serine or ß-methylated threonine. This suggests that the linkage point of antigenic glycans will affect their presentation to the immune system as well as to various carbohydrate binding molecules (e.g., lectins). This short review, followed by our hypothesis, will examine this possibility and extend the concept to the presentation of glycans on surfaces and in assay systems where recognition of glycans by proteins and other binding partners can be defined by different attachment points that allow for a range of conformational presentations.

Targeted protein degradation as an antiviral approach

Targeted protein degradation (TPD) has emerged as a new modality in drug discovery. In this approach, small molecules are used to drive degradation of the target protein of interest. Whereas most direct-acting antivirals (DAAs) inhibit or derange the activity of their viral protein targets and have occupancy-driven pharmacology, small molecules with a TPD-based mechanism have event-driven pharmacology exerted through their ability to induce target degradation. These contrasting mechanisms can result in significant differences in drug efficacy and pharmacodynamics that may be useful in the development of new classes of antivirals. While now being widely pursued in cancer biology and autoimmune disease, TPD has not yet been widely applied as an antiviral strategy. Here, we briefly review TPD pharmacology along with the current status of tools available for developing small molecules that achieve antiviral activity through a TPD mechanism. We also highlight aspects of TPD that may be especially useful in the development of antivirals and that we hope will motivate pursuit of TPD-based antivirals by the antivirals research community.

Fragment-to-Lead Medicinal Chemistry Publications in 2021

This Perspective is the seventh in an annual series that summarizes successful Fragment-to-Lead (F2L) case studies published in a given year. A tabulated summary of relevant articles published in 2021 is provided, and features such as target class, screening methods, and ligand efficiency are discussed, both for the 2021 examples and for the combined examples over the years 2015-2021. In addition, trends and new developments in the field are summarized. In particular, the use of structural information in fragment-based drug discovery is discussed.

Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 macrodomain of SARS-CoV-2

The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small-molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic, there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high-resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 153 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated conformational changes within the active site, and key inhibitor motifs that will template future drug development against Mac1.

Magnet for the Needle in Haystack: "Crystal Structure First" Fragment Hits Unlock Active Chemical Matter Using Targeted Exploration of Vast Chemical Spaces

Fragment-based drug discovery (FBDD) has successfully led to approved therapeutics for challenging and "undruggable" targets. In the context of FBDD, we introduce a novel, multidisciplinary method to identify active molecules from purchasable chemical space. Starting from four small-molecule fragment complexes of protein kinase A (PKA), a template-based docking screen using Enamine's multibillion REAL Space was performed. A total of 93 molecules out of 106 selected compounds were successfully synthesized. Forty compounds were active in at least one validation assay with the most active follow-up having a 13,500-fold gain in affinity. Crystal structures for six of the most promising binders were rapidly obtained, verifying the binding mode. The overall success rate for this novel fragment-to-hit approach was 40%, accomplished in only 9 weeks. The results challenge the established fragment prescreening paradigm since the standard industrial filters for fragment hit identification in a thermal shift assay would have missed the initial fragments.

The Commoditization of AI for Molecule Design

Anyone involved in designing or finding molecules in the life sciences over the past few years has witnessed a dramatic change in how we now work due to the COVID-19 pandemic. Computational technologies like artificial intelligence (AI) seemed to become ubiquitous in 2020 and have been increasingly applied as scientists worked from home and were separated from the laboratory and their colleagues. This shift may be more permanent as the future of molecule design across different industries will increasingly require machine learning models for design and optimization of molecules as they become "designed by AI". AI and machine learning has essentially become a commodity within the pharmaceutical industry. This perspective will briefly describe our personal opinions of how machine learning has evolved and is being applied to model different molecule properties that crosses industries in their utility and ultimately suggests the potential for tight integration of AI into equipment and automated experimental pipelines. It will also describe how many groups have implemented generative models covering different architectures, for de novo design of molecules. We also highlight some of the companies at the forefront of using AI to demonstrate how machine learning has impacted and influenced our work. Finally, we will peer into the future and suggest some of the areas that represent the most interesting technologies that may shape the future of molecule design, highlighting how we can help increase the efficiency of the design-make-test cycle which is currently a major focus across industries.

Computer- and NMR-Aided Design of Small-Molecule Inhibitors of the Hub1 Protein

By binding to the spliceosomal protein Snu66, the human ubiquitin-like protein Hub1 is a modulator of the spliceosome performance and facilitates alternative splicing. Small molecules that bind to Hub1 would be of interest to study the protein-protein interaction of Hub1/Snu66, which is linked to several human pathologies, such as hypercholesterolemia, premature aging, neurodegenerative diseases, and cancer. To identify small molecule ligands for Hub1, we used the interface analysis, peptide modeling of the Hub1/Snu66 interaction and the fragment-based NMR screening. Fragment-based NMR screening has not proven sufficient to unambiguously search for fragments that bind to the Hub1 protein. This was because the Snu66 binding pocket of Hub1 is occupied by pH-sensitive residues, making it difficult to distinguish between pH-induced NMR shifts and actual binding events. The NMR analyses were therefore verified experimentally by microscale thermophoresis and by NMR pH titration experiments. Our study found two small peptides that showed binding to Hub1. These peptides are the first small-molecule ligands reported to interact with the Hub1 protein.

PAC-FragmentDEL - photoactivated covalent capture of DNA-encoded fragments for hit discovery

We describe a novel approach for screening fragments against a protein that combines the sensitivity of DNA-encoded library technology with the ability of fragments to explore what will bind. Each of the members of the library consists of a fragment which is linked to a photoactivatable diazirine moiety. Split and pool synthesis combines each fragment with a set of linkers with the version of the library reported here containing some 70k different compounds, each with an individual DNA code. Incubation of the library with a protein sample is followed by photoactivation, washing and subsequent PCR and sequencing which allows the individual fragment hits to be identified. We illustrate how the approach allows successful hit fragment identification using only microgram quantities of material for two targets. PAK4 is a kinase for which conventional fragment screening has generated many advance leads. The as yet undrugged target, 2-epimerase, presents a more challenging active site for identification of hit compounds. In both cases, PAC-FragmentDEL identified fragments validated as hits by ligand-observed NMR measurements and crystal structure determination of off-DNA sample binding to the proteins.

Reactivity of Covalent Fragments and Their Role in Fragment Based Drug Discovery

Fragment based drug discovery has long been used for the identification of new ligands and interest in targeted covalent inhibitors has continued to grow in recent years, with high profile drugs such as osimertinib and sotorasib gaining FDA approval. It is therefore unsurprising that covalent fragment-based approaches have become popular and have recently led to the identification of novel targets and binding sites, as well as ligands for targets previously thought to be 'undruggable'. Understanding the properties of such covalent fragments is important, and characterizing and/or predicting reactivity can be highly useful. This review aims to discuss the requirements for an electrophilic fragment library and the importance of differing warhead reactivity. Successful case studies from the world of drug discovery are then be examined.

Fragment-based drug discovery-the importance of high-quality molecule libraries

Fragment-based drug discovery (FBDD) is now established as a complementary approach to high-throughput screening (HTS). Contrary to HTS, where large libraries of drug-like molecules are screened, FBDD screens involve smaller and less complex molecules which, despite a low affinity to protein targets, display more 'atom-efficient' binding interactions than larger molecules. Fragment hits can, therefore, serve as a more efficient start point for subsequent optimisation, particularly for hard-to-drug targets. Since the number of possible molecules increases exponentially with molecular size, small fragment libraries allow for a proportionately greater coverage of their respective 'chemical space' compared with larger HTS libraries comprising larger molecules. However, good library design is essential to ensure optimal chemical and pharmacophore diversity, molecular complexity, and physicochemical characteristics. In this review, we describe our views on fragment library design, and on what constitutes a good fragment from a medicinal and computational chemistry perspective. We highlight emerging chemical and computational technologies in FBDD and discuss strategies for optimising fragment hits. The impact of novel FBDD approaches is already being felt, with the recent approval of the covalent KRAS^G12C inhibitor sotorasib highlighting the utility of FBDD against targets that were long considered undruggable.

Development of Noncovalent Small-Molecule Keap1-Nrf2 Inhibitors by Fragment-Based Drug Discovery

Targeting the protein-protein interaction (PPI) between the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) and its repressor, Kelch-like ECH-associated protein 1 (Keap1), constitutes a promising strategy for treating diseases involving oxidative stress and inflammation. Here, a fragment-based drug discovery (FBDD) campaign resulted in novel, high-affinity (K_i = 280 nM), and cell-active noncovalent small-molecule Keap1-Nrf2 PPI inhibitors. We screened 2500 fragments using orthogonal assays─fluorescence polarization (FP), thermal shift assay (TSA), and surface plasmon resonance (SPR)─and validated the hits by saturation transfer difference (STD) NMR, leading to 28 high-priority hits. Thirteen co-structures showed fragments binding mainly in the P4 and P5 subpockets of Keap1's Kelch domain, and three fluorenone-based fragments featuring a novel binding mode were optimized by structure-based drug discovery. We thereby disclose several fragment hits, including their binding modes, and show how FBDD can be performed to find new small-molecule Keap1-Nrf2 PPI inhibitors.

On drug discovery against infectious diseases and academic medicinal chemistry contributions

This perspective is an attempt to document the problems that medicinal chemists are facing in drug discovery. It is also trying to identify relevant/possible, research areas in which academics can have an impact and should thus be the subject of grant calls. Accordingly, it describes how hit discovery happens, how compounds to be screened are selected from available chemicals and the possible reasons for the recurrent paucity of useful/exploitable results reported. This is followed by the successful hit to lead stories leading to recent and original antibacterials which are, or about to be, used in human medicine. Then, illustrated considerations and suggestions are made on the possible inputs of academic medicinal chemists. This starts with the observation that discovering a “good” hit in the course of a screening campaign still rely on a lot of luck – which is within the reach of academics –, that the hit to lead process requires a lot of chemistry and that if public–private partnerships can be important throughout these stages, they are absolute requirements for clinical trials. Concerning suggestions to improve the current hit success rate, one academic input in organic chemistry would be to identify new and pertinent chemical space, design synthetic accesses to reach these and prepare the corresponding chemical libraries. Concerning hit to lead programs on a given target, if no new hits are available, previously reported leads along with new structural data can be pertinent starting points to design, prepare and assay original analogues. In conclusion, this text is an actual plea illustrating that, in many countries, academic research in medicinal chemistry should be more funded, especially in the therapeutic area neglected by the industry. At the least, such funds would provide the intensive to secure series of hopefully relevant chemical entities which appears to often lack when considering the results of academic as well as industrial screening campaigns.

Think Biologically, Act Chemically

A drug is a sophisticated molecule, purposely evolved, resulting from the accumulation of knowledge learned and exploited from simpler molecules over time. Advanced molecules with increased sophistication and capability are derived from simpler, less sophisticated structures with less capabilities. Medicinal chemists do not find, stumble upon, accidentally discover, screen for, or construct drugs. We purposefully evolve molecules through the use of feedback cycles; we emphasize efficiency and simplicity in pursuit of multiproperty homeostasis; and we design and learn from molecular outliers. This Miniperspective illustrates inspirational themes from nature including evolution, feedback cycles, homeostasis, efficiency, and mutation. These biological themes are then exemplified in modern medicinal chemistry practices, such as design-make-test-analyze cycles (feedback), balancing molecular properties (homeostasis), defining the minimum pharmacophore (simplicity, efficiency), understanding molecular outliers (mutants), and the unifying concept of molecular evolution.

A commentary on the use of pharmacoenhancers in the pharmaceutical industry and the implication for DMPK drug discovery strategies

Paxlovid, a drug combining nirmatrelvir and ritonavir, was designed for the treatment of COVID-19 and its rapid development has led to emergency use approval by the FDA to reduce the impact of COVID-19 infection on patients.In order to overcome potentially suboptimal therapeutic exposures, nirmatrelvir is dosed in combination with ritonavir to boost the pharmacokinetics of the active product.Here we consider examples of drugs co-administered with pharmacoenhancers.Pharmacoenhancers have been adopted for multiple purposes such as ensuring therapeutic exposure of the active product, reducing formation of toxic metabolites, changing the route of administration, and increasing the cost-effectiveness of a therapy.We weigh the benefits and risks of this approach, examining the impact of technology developments on drug design and how enhanced integration between cross-discipline teams can improve the outcome of drug discovery.

Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 Macrodomain of SARS-CoV-2

The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 152 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated protein dynamics within the active site, and key inhibitor motifs that will template future drug development against Mac1.

A fragment-based drug discovery strategy applied to the identification of NDM-1 β-lactamase inhibitors

Hydrolysis of β-lactam drugs, a major class of antibiotics, by serine or metallo-β-lactamases (SBL or MBL) is one of the main mechanisms for antibiotic resistance. New Delhi Metallo-β-lactamase-1 (NDM-1), an acquired metallo-carbapenemase first reported in 2009, is currently considered one of the most clinically relevant targets for the development of β-lactam-β-lactamase inhibitor combinations active on NDM-producing clinical isolates. Identification of scaffolds that could be further rationally pharmacomodulated to design new and efficient NDM-1 inhibitors is thus urgently needed. Fragment-based drug discovery (FBDD) has become of great interest for the development of new drugs for the past few years and combination of several FBDD strategies, such as virtual and NMR screening, can reduce the drawbacks of each of them independently. Our methodology starting from a high throughput virtual screening on NDM-1 of a large library (more than 700,000 compounds) allowed, after slicing the hit molecules into fragments, to build a targeted library. These hit fragments were included in an in-house untargeted library fragments that was screened by Saturation Transfer Difference (STD) Nuclear Magnetic Resonance (NMR). 37 fragments were finally identified and used to establish a pharmacophore. 10 molecules based on these hit fragments were synthesized to validate our strategy. Indenone 89 that combined two identified fragments shows an inhibitory activity on NDM-1 with a K_i value of 4 μM.

Fragment screening yields a small-molecule stabilizer of 14-3-3 dimers that modulates client protein interactions

The development of protein‐protein interaction (PPI) inhibitors has been a successful strategy in drug development. However, the identification of PPI stabilizers has proven much more challenging. Here we report a fragment‐based drug screening approach using the regulatory hub‐protein 14‐3‐3 as a platform for identifying PPI stabilizers. A homogenous time‐resolved FRET assay was used to monitor stabilization of 14‐3‐3/peptide binding using the known interaction partner estrogen receptor alpha. Screening of an in‐house fragment library identified fragment 2 (VUF15640) as a putative PPI stabilizer capable of cooperatively stabilizing 14‐3‐3 PPIs in a cooperative fashion with Fusicoccin‐A. Mechanistically, fragment 2 appears to enhance 14‐3‐3 dimerization leading to increased client‐protein binding. Functionally, fragment 2 enhanced potency of 14‐3‐3 in a cell‐free system inhibiting the enzyme activity of the nitrate reductase. In conclusion, we identified a general PPI stabilizer targeting 14‐3‐3, which could be used as a tool compound for investigating 14‐3‐3 client protein interactions.

Design of a Potent, Selective, and Brain-Penetrant Inhibitor of Wnt-Deactivating Enzyme Notum by Optimization of a Crystallographic Fragment Hit

Notum is a carboxylesterase that suppresses Wnt signaling through deacylation of an essential palmitoleate group on Wnt proteins. There is a growing understanding of the role Notum plays in human diseases such as colorectal cancer and Alzheimer's disease, supporting the need to discover improved inhibitors, especially for use in models of neurodegeneration. Here, we have described the discovery and profile of 8l (ARUK3001185) as a potent, selective, and brain-penetrant inhibitor of Notum activity suitable for oral dosing in rodent models of disease. Crystallographic fragment screening of the Diamond-SGC Poised Library for binding to Notum, supported by a biochemical enzyme assay to rank inhibition activity, identified 6a and 6b as a pair of outstanding hits. Fragment development of 6 delivered 8l that restored Wnt signaling in the presence of Notum in a cell-based reporter assay. Assessment in pharmacology screens showed 8l to be selective against serine hydrolases, kinases, and drug targets.

Scaffold hopping by net photochemical carbon deletion of azaarenes

Discovery chemists routinely identify purpose-tailored molecules through an iterative structural optimization approach, but the preparation of each successive candidate in a compound series can rarely be conducted in a manner matching their thought process. This is because many of the necessary chemical transformations required to modify compound cores in a straightforward fashion are not applicable in complex contexts. We report a method that addresses one facet of this problem by allowing chemists to hop directly between chemically distinct heteroaromatic scaffolds. Specifically, we show that selective photolysis of quinoline N-oxides with 390-nanometer light followed by acid-promoted rearrangement affords N-acylindoles while showing broad compatibility with medicinally relevant functionality. Applications to late-stage skeletal modification of compounds of pharmaceutical interest and more complex transformations involving serial single-atom changes are demonstrated.

A review on cullin neddylation and strategies to identify its inhibitors for cancer therapy

The cullin-RING E3 ligases (CRLs) are the biggest components of the E3 ubiquitin ligase protein family, and they represent an essential role in various diseases that occur because of abnormal activation, particularly in tumors development. Regulation of CRLs needs neddylation, a post-translational modification involving an enzymatic cascade that transfers small, ubiquitin-like NEDD8 protein to CRLs. Many previous studies have confirmed neddylation as an enticing target for anticancer drug discoveries, and few recent studies have also found a significant increase in advancement in protein neddylation, including preclinical and clinical target validation to discover the neddylation inhibitor compound. In the present review, we first presented briefly the essence of CRLs' neddylation and its control, systematic analysis of CRLs, followed by the description of a few recorded chemical inhibitors of CRLs neddylation enzymes with recent examples of preclinical and clinical targets. We have also listed various structure-based pointing of protein-protein dealings in the CRLs' neddylation reaction, and last, the methods available to discover new inhibitors of neddylation are elaborated. This review will offer a concentrated, up-to-date, and detailed description of the discovery of neddylation inhibitors.