A small nonrule of 3 compatible fragment library provides high hit rate of endothiapepsin crystal structures with various fragment chemotypes

Assessment of fragment docking and scoring with the endothiapepsin model system

Fragment-based screening has become indispensable in drug discovery. Yet, the weak binding affinities of these small molecules still represent a challenge for the reliable detection of fragment hits. The extent of this issue was illustrated in the literature for the aspartic protease endothiapepsin: When seven biochemical and biophysical in vitro screening methods were applied to screen a library of 361 fragments, very poor overlap was observed between the hit fragments identified by the individual approaches, resulting in high levels of false positive and/or false negative results depending on the mutually compared methods. Here, the reported in vitro findings are juxtaposed with the results from in silico docking and scoring approaches. The docking programs GOLD and Glide were considered with the scoring functions ASP, ChemScore, ChemPLP, GoldScore, DSXCSD, and GlideScore. First, the ranking power and scoring power were assessed for the named scoring functions. Second, the capability of reproducing the crystallized fragment binding modes was tested in a structure-based redocking approach. The redocking success notably depended on the ligand efficiency of the considered fragments. Third, a blinded virtual screening approach was employed to evaluate whether in silico screening can compete with in vitro methods in the enrichment of fragment databases.

Extracting binding energies and binding modes from biomolecular simulations of fragment binding to endothiapepsin

Fragment-based drug discovery (FBDD) aims to discover a set of small binding fragments that may be subsequently linked together. Therefore, in-depth knowledge of the individual fragments' structural and energetic binding properties is essential. In addition to experimental techniques, the direct simulation of fragment binding by molecular dynamics (MD) simulations became popular to characterize fragment binding. However, former studies showed that long simulation times and high computational demands per fragment are needed, which limits applicability in FBDD. Here, we performed short, unbiased MD simulations of direct fragment binding to endothiapepsin, a well-characterized model system of pepsin-like aspartic proteases. To evaluate the strengths and limitations of short MD simulations for the structural and energetic characterization of fragment binding, we predicted the fragments' absolute free energies and binding poses based on the direct simulations of fragment binding and compared the predictions to experimental data. The predicted absolute free energies are in fair agreement with the experiment. Combining the MD data with binding mode predictions from molecular docking approaches helped to correctly identify the most promising fragments for further chemical optimization. Importantly, all computations and predictions were done within 5 days, suggesting that MD simulations may become a viable tool in FBDD projects.

Unravelling driver genes as potential therapeutic targets in ovarian cancer via integrated bioinformatics approach

Target-driven cancer therapy is a notable advancement in precision oncology that has been accompanied by substantial medical accomplishments. Ovarian cancer is a highly frequent neoplasm in women and exhibits significant genomic and clinical heterogeneity. In a previous publication, we presented an extensive bioinformatics study aimed at identifying specific biomarkers associated with ovarian cancer. The findings of the network analysis indicate the presence of a cluster of nine dysregulated hub genes that exhibited significance in the underlying biological processes and contributed to the initiation of ovarian cancer. Here in this research article, we are proceeding our previous research by taking all hub genes into consideration for further analysis. GEPIA2 was used to identify patterns in the expression of critical genes. The KM plotter analysis indicated that the out of all genes 5 genes are statistically significant. The cBioPortal platform was further used to investigate the frequency of genetic mutations across the board and how they affected the survival of the patients. Maximum mutation was reported by ELAVL2. In order to discover viable therapeutic candidates after competitive inhibition of ELAVL2 with small molecular drug complex, high throughput screening and docking studies were used. Five compounds were identified. Overall, our results suggest that the ELAV-like protein 2-ZINC03830554 complex was relatively stable during the molecular dynamic simulation. The five compounds that have been found can also be further examined as potential therapeutic possibilities. The combined findings suggest that ELAVL2, together with their genetic changes, can be investigated in therapeutic interventions for precision oncology, leveraging early diagnostics and target-driven therapy.

Covalent fragment libraries in drug discovery-Design, synthesis, and screening methods

As the development of drugs with a covalent mode of action is becoming increasingly popular, well-validated covalent fragment-based drug discovery (FBDD) methods have been comparatively slow to keep up with the demand. In this chapter the principles of covalent fragment reactivity, library design, synthesis, and screening methods are explored in depth, focussing on literature examples with direct applications to practical covalent fragment library design and screening. Further, questions about the future of the field are explored and potential useful advances are proposed.

Fragtory: Pharmacophore-Focused Design, Synthesis, and Evaluation of an sp3-Enriched Fragment Library

Fragment-based drug discovery has played an important role in medicinal chemistry and pharmaceutical research. Despite numerous demonstrated successes, the limited diversity and overrepresentation of planar, sp²-rich structures in commercial libraries often hamper the full potential of this approach. Hence, the thorough design of screening libraries inevitably determines the probability for meaningful hits and subsequent structural elaboration. Against this background, we present the generation of an exclusive fragment library based on iterative entry nomination by a specifically designed computational workflow: "Fragtory". Following a pharmacophore diversity-driven approach, we used Fragtory in an interdisciplinary academic setting to guide both tailored synthesis efforts and the implementation of in-house compounds to build a curated 288-member library of sp³-enriched fragments. Subsequent NMR screens against a model protein and hit validation by protein crystallography led to the identification of structurally novel ligands that were further characterized by isothermal titration calorimetry, demonstrating the applicability of our experimental approach.

Unprecedented Combination of Polyketide Natural Product Fragments Identifies the New Hedgehog Signaling Pathway Inhibitor Grismonone

Pseudo-natural products (pseudo-NPs) are de novo combinations of natural product (NP) fragments that define novel bioactive chemotypes. For their discovery, new design principles are being sought. Previously, pseudo-NPs were synthesized by the combination of fragments originating from biosynthetically unrelated NPs to guarantee structural novelty and novel bioactivity. We report the combination of fragments from biosynthetically related NPs in novel arrangements to yield a novel chemotype with activity not shared by the guiding fragments. We describe the synthesis of the polyketide pseudo-NP grismonone and identify it as a structurally novel and potent inhibitor of Hedgehog signaling. The insight that the de novo combination of fragments derived from biosynthetically related NPs may also yield new biologically relevant compound classes with unexpected bioactivity may be considered a chemical extension or diversion of existing biosynthetic pathways and greatly expands the opportunities for exploration of biologically relevant chemical space by means of the pseudo-NP principle.

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.

Identification of PARP12 Inhibitors By Virtual Screening and Molecular Dynamics Simulations

Poly [adenosine diphosphate (ADP)-ribose] polymerases (PARPs) are members of a family of 17 enzymes that performs several fundamental cellular processes. Aberrant activity (mutation) in PARP12 has been linked to various diseases including inflammation, cardiovascular disease, and cancer. Herein, a large library of compounds (ZINC-FDA database) has been screened virtually to identify potential PARP12 inhibitor(s). The best compounds were selected on the basis of binding affinity scores and poses. Molecular dynamics (MD) simulation and binding free energy calculation (MMGBSA) were carried out to delineate the stability and dynamics of the resulting complexes. To this end, root means deviations, relative fluctuation, atomic gyration, compactness, covariance, residue-residue contact map, and free energy landscapes were studied. These studies have revealed that compounds ZINC03830332, ZINC03830554, and ZINC03831186 are promising agents against mutated PARP12.

Probing ligand binding of endothiapepsin by `temperature-resolved' macromolecular crystallography

A room-temperature X-ray crystallographic method using temperature as a trigger to record movie-like structural snapshots has been developed and applied to study ligand binding and protein plasticity.

Continuous developments in cryogenic X-ray crystallography have provided most of our knowledge of 3D protein structures, which has recently been further augmented by revolutionary advances in cryoEM. However, a single structural conformation identified at cryogenic temperatures may introduce a fictitious structure as a result of cryogenic cooling artefacts, limiting the overview of inherent protein physiological dynamics, which play a critical role in the biological functions of proteins. Here, a room-temperature X-ray crystallo­graphic method using temperature as a trigger to record movie-like structural snapshots has been developed. The method has been used to show how TL00150, a 175.15 Da fragment, undergoes binding-mode changes in endothiapepsin. A surprising fragment-binding discrepancy was observed between the cryo-cooled and physiological temperature structures, and multiple binding poses and their interplay with DMSO were captured. The observations here open up new promising prospects for structure determination and interpretation at physiological temperatures with implications for structure-based drug discovery.

FGDB: a comprehensive graph database of ligand fragments from the Protein Data Bank

This work presents Fragment Graph DataBase (FGDB), a graph database of ligand fragments extracted and generated from the protein entries available in the Protein Data Bank (PDB). FGDB is meant to support and elicit campaigns of fragment-based drug design, by enabling users to query it in order to construct ad hoc, target-specific libraries. In this regard, the database features more than 17 000 fragments, typically small, highly soluble and chemically stable molecules expressed via their canonical Simplified Molecular Input Line Entry System (SMILES) representation. For these fragments, the database provides information related to their contact frequencies with the amino acids, the ligands they are contained in and the proteins the latter bind to. The graph database can be queried via standard web forms and textual searches by a number of identifiers (SMILES, ligand and protein PDB ids) as well as via graphical queries that can be performed against the graph itself, providing users with an intuitive and effective view upon the underlying biological entities. Further search mechanisms via advanced conjunctive/disjunctive/negated textual queries are also possible, in order to allow scientists to look for specific relationships and export their results for further studies. This work also presents two sample use cases where maternal embryonic leucine zipper kinase and mesotrypsin are used as a target, being proteins of high biomedical relevance for the development of cancer therapies.

Database URL: http://biochimica3.bio.uniroma3.it/fragments-web/

Fragment hopping protocol for the design of small-molecule protein-protein interaction inhibitors

Fragment-based ligand discovery (FBLD) is one of the most successful approaches to designing small-molecule protein-protein interaction (PPI) inhibitors. The incorporation of computational tools to FBLD allows the exploration of chemical space in a time- and cost-efficient manner. Herein, a computational protocol for the development of small-molecule PPI inhibitors using fragment hopping, a fragment-based de novo design approach, is described and a case study is presented to illustrate the efficiency of this protocol. Fragment hopping facilitates the design of PPI inhibitors from scratch solely based on key binding features in the PPI complex structure. This approach is an open system that enables the inclusion of different state-of-the-art programs and softwares to improve its performances.

Human Estrogen Receptor Alpha Antagonists, Part 3: 3-D Pharmacophore and 3-D QSAR Guided Brefeldin A Hit-to-Lead Optimization toward New Breast Cancer Suppressants

The estrogen receptor α (ERα) is an important biological target mediating 17β-estradiol driven breast cancer (BC) development. Aiming to develop innovative drugs against BC, either wild-type or mutated ligand-ERα complexes were used as source data to build structure-based 3-D pharmacophore and 3-D QSAR models, afterward used as tools for the virtual screening of National Cancer Institute datasets and hit-to-lead optimization. The procedure identified Brefeldin A (BFA) as hit, then structurally optimized toward twelve new derivatives whose anticancer activity was confirmed both in vitro and in vivo. Compounds as SERMs showed picomolar to low nanomolar potencies against ERα and were then investigated as antiproliferative agents against BC cell lines, as stimulators of p53 expression, as well as BC cell cycle arrest agents. Most active leads were finally profiled upon administration to female Wistar rats with pre-induced BC, after which 3DPQ-12, 3DPQ-3, 3DPQ-9, 3DPQ-4, 3DPQ-2, and 3DPQ-1 represent potential candidates for BC therapy.

Puckering the planar landscape of fragments: design and synthesis of a 3D cyclobutane fragment library

Fragment‐based drug discovery (FBDD) has a growing need for unique screening libraries. The cyclobutane moiety was identified as an underrepresented yet attractive three‐dimensional (3D) scaffold. Synthetic strategies were developed via a key 3‐azido‐cyclobutanone intermediate, giving potential access to a range of functional groups with accessible growth vectors. A focused set of 33 novel 3D cyclobutane fragments was synthesised, comprising three functionalities: secondary amines, amides, and sulfonamides. This library was designed using Principal Component Analysis (PCA) and an expanded version of the rule of three (RO3), followed by Principal Moment of Inertia (PMI) analysis to achieve both chemical diversity and high 3D character. Cis and trans ring isomers of library members were generated to maximise the shape diversity obtained, while limiting molecular complexity through avoiding enantiomers. Property analyses of the cyclobutane library indicated that it fares favourably against existing synthetic 3D fragment libraries in terms of shape and physicochemical properties.

Chemical Evolution of Natural Product Structure

Natural products are the result of Nature’s exploration of biologically relevant chemical space through evolution and an invaluable source of bioactive small molecules for chemical biology and medicinal chemistry. Novel concepts for the discovery of new bioactive compound classes based on natural product structure may enable exploration of wider biologically relevant chemical space. The pseudo-natural product concept merges the relevance of natural product structure with efficient exploration of chemical space by means of fragment-based compound development to inspire the discovery of new bioactive chemical matter through de novo combination of natural product fragments in unprecedented arrangements. The novel scaffolds retain the biological relevance of natural products but are not obtainable through known biosynthetic pathways which can lead to new chemotypes that may have unexpected or unprecedented bioactivities. Herein, we cover the workflow of pseudo-natural product design and development, highlight recent examples, and discuss a cheminformatic analysis in which a significant portion of biologically active synthetic compounds were found to be pseudo-natural products. We compare the concept to natural evolution and discuss pseudo-natural products as the human-made equivalent, i.e. the chemical evolution of natural product structure.

Fast fragment- and compound-screening pipeline at the Swiss Light Source

Over the last two decades, fragment-based drug discovery (FBDD) has emerged as an effective and efficient method to identify new chemical scaffolds for the development of lead compounds. X-ray crystallography can be used in FBDD as a tool to validate and develop fragments identified as binders by other methods. However, it is also often used with great success as a primary screening technique. In recent years, technological advances at macromolecular crystallography beamlines in terms of instrumentation, beam intensity and robotics have enabled the development of dedicated platforms at synchrotron sources for FBDD using X-ray crystallography. Here, the development of the Fast Fragment and Compound Screening (FFCS) platform, an integrated next-generation pipeline for crystal soaking, handling and data collection which allows crystallography-based screening of protein crystals against hundreds of fragments and compounds, at the Swiss Light Source is reported.

Frag4Lead: growing crystallographic fragment hits by catalog using fragment-guided template docking

In recent years, crystallographic fragment screening has matured into an almost routine experiment at several modern synchrotron sites. The hits of the screening experiment, i.e. small molecules or fragments binding to the target protein, are revealed along with their 3D structural information. Therefore, they can serve as useful starting points for further structure-based hit-to-lead development. However, the progression of fragment hits to tool compounds or even leads is often hampered by a lack of chemical feasibility. As an attractive alternative, compound analogs that embed the fragment hit structurally may be obtained from commercial catalogs. Here, a workflow is reported based on filtering and assessing such potential follow-up compounds by template docking. This means that the crystallographic binding pose was integrated into the docking calculations as a central starting parameter. Subsequently, the candidates are scored on their interactions within the binding pocket. In an initial proof-of-concept study using five starting fragments known to bind to the aspartic protease endothiapepsin, 28 follow-up compounds were selected using the designed workflow and their binding was assessed by crystallography. Ten of these compounds bound to the active site and five of them showed significantly increased affinity in isothermal titration calorimetry of up to single-digit micromolar affinity. Taken together, this strategy is capable of efficiently evolving the initial fragment hits without major synthesis efforts and with full control by X-ray crystallography.

Non-Extensive Fragmentation of Natural Products and Pharmacophore-Based Virtual Screening as a Practical Approach to Identify Novel Promising Chemical Scaffolds

Fragment-based drug design (FBDD) and pharmacophore modeling have proven to be efficient tools to discover novel drugs. However, these approaches may become limited if the collection of fragments is highly repetitive, poorly diverse, or excessively simple. In this article, combining pharmacophore modeling and a non-classical type of fragmentation (herein called non-extensive) to screen a natural product (NP) library may provide fragments predicted as potent, diverse, and developable. Initially, we applied retrosynthetic combinatorial analysis procedure (RECAP) rules in two versions, extensive and non-extensive, in order to deconstruct a virtual library of NPs formed by the databases Traditional Chinese Medicine (TCM), AfroDb (African Medicinal Plants database), NuBBE (Nuclei of Bioassays, Biosynthesis, and Ecophysiology of Natural Products), and UEFS (Universidade Estadual de Feira de Santana). We then developed a virtual screening (VS) using two groups of natural-product-derived fragments (extensive and non-extensive NPDFs) and two overlapping pharmacophore models for each of 20 different proteins of therapeutic interest. Molecular weight, lipophilicity, and molecular complexity were estimated and compared for both types of NPDFs (and their original NPs) before and after the VS proceedings. As a result, we found that non-extensive NPDFs exhibited a much higher number of chemical entities compared to extensive NPDFs (45,355 vs. 11,525 compounds), accounting for the larger part of the hits recovered and being far less repetitive than extensive NPDFs. The structural diversity of both types of NPDFs and the NPs was shown to diminish slightly after VS procedures. Finally, and most interestingly, the pharmacophore fit score of the non-extensive NPDFs proved to be not only higher, on average, than extensive NPDFs (56% of cases) but also higher than their original NPs (69% of cases) when all of them were also recognized as hits after the VS. The findings obtained in this study indicated that the proposed cascade approach was useful to enhance the probability of identifying innovative chemical scaffolds, which deserve further development to become drug-sized candidate compounds. We consider that the knowledge about the deconstruction degree required to produce NPDFs of interest represents a good starting point for eventual synthesis, characterization, and biological activity studies.

Molecular docking studies, molecular dynamics and ADME/tox reveal therapeutic potentials of STOCK1N-69160 against papain-like protease of SARS-CoV-2

SARS-CoV-2 is a new strain of Coronavirus that caused the pneumonia outbreak in Wuhan, China and has spread to over 200 countries of the world. It has received worldwide attention due to its virulence and high rate of infection. So far, several drugs have experimented against SARS-CoV-2, but the failure of these drugs to specifically interact with the viral protease necessitates urgent measure to boost up researches for the development of effective therapeutics against SARS-CoV-2. Papain-like protease (PLpro) of the viral polyproteins is essential for maturation and infectivity of the virus, making it one of the prime targets explored for SARS-CoV-2 drug design. This study was conducted to evaluate the efficacy of ~ 50,000 natural compounds retrieved from IBS database against COVID-19 PLpro using computer-aided drug design. Based on molecular dock scores, molecular interaction with active catalytic residues and molecular dynamics (MD) simulations studies, STOCK1N-69160 [(S)-2-((R)-4-((R)-2-amino-3-methylbutanamido)-3-(4-chlorophenyl) butanamido) propanoic acid hydrochloride] has been proposed as a novel inhibitor against COVID-19 PLpro. It demonstrated favourable docking score, the free energy of binding, interacted with key amino acid residues necessary for PLpro inhibition and also showed significant moderation for parameters investigated for ADME/tox (Adsorption, distribution, metabolism, excretion and toxicological) properties. The edge of the compound was further established by its stability in MD simulation conducted for 30 ns employing GROMACS software. We propose that STOCK1N-69160 is worth further investigation for preventing SARS-CoV-2.

Synthesis and in Vitro Evaluation of Novel 5-Nitroindole Derivatives as c-Myc G-Quadruplex Binders with Anticancer Activity

Lead-optimization strategies for compounds targeting c-Myc G-quadruplex (G4) DNA are being pursued to develop anticancer drugs. Here, we investigate the structure-activity- relationship (SAR) of a newly synthesized series of molecules based on the pyrrolidine-substituted 5-nitro indole scaffold to target G4 DNA. Our synthesized series allows modulation of flexible elements with a structurally preserved scaffold. Biological and biophysical analyses illustrate that substituted 5-nitroindole scaffolds bind to the c-Myc promoter G-quadruplex. These compounds downregulate c-Myc expression and induce cell-cycle arrest in the sub-G1/G1 phase in cancer cells. They further increase the concentration of intracellular reactive oxygen species. NMR spectra show that three of the newly synthesized compounds interact with the terminal G-quartets (5'- and 3'-ends) in a 2 : 1 stoichiometry.

Natural product fragment combination to performance-diverse pseudo-natural products

Natural product structure and fragment-based compound development inspire pseudo-natural product design through different combinations of a given natural product fragment set to compound classes expected to be chemically and biologically diverse. We describe the synthetic combination of the fragment-sized natural products quinine, quinidine, sinomenine, and griseofulvin with chromanone or indole-containing fragments to provide a 244-member pseudo-natural product collection. Cheminformatic analyses reveal that the resulting eight pseudo-natural product classes are chemically diverse and share both drug- and natural product-like properties. Unbiased biological evaluation by cell painting demonstrates that bioactivity of pseudo-natural products, guiding natural products, and fragments differ and that combination of different fragments dominates establishment of unique bioactivity. Identification of phenotypic fragment dominance enables design of compound classes with correctly predicted bioactivity. The results demonstrate that fusion of natural product fragments in different combinations and arrangements can provide chemically and biologically diverse pseudo-natural product classes for wider exploration of biologically relevant chemical space.

Escape from planarity in fragment-based drug discovery: A physicochemical and 3D property analysis of synthetic 3D fragment libraries

Fragment-based drug discovery (FBDD) has grown into a well-established approach in the pursuit of new therapeutics. Key to the success of FBDD is the low molecular complexity of the initial hits and this has resulted in fragment libraries that mainly contain compounds with a two-dimensional (2D) shape. In an effort to increase the chemical diversity and explore the impact of increased molecular complexity on the hit rate of fragment library screening, several academic and industrial groups have designed and synthesised novel fragments with a three-dimensional (3D) shape. This review provides an overview of 25 synthetic 3D fragment libraries from the recent literature. We calculate and compare physicochemical properties and descriptors that are typically used to measure molecular three-dimensionality such as fraction sp³ (Fsp³), plane of best fit (PBF) scores and principal moment of inertia (PMI) plots. Although the libraries vary widely in structure and properties, some key common features can be identified which may have utility in designing the next generation of 3D fragment libraries.

F2X-Universal and F2X-Entry: Structurally Diverse Compound Libraries for Crystallographic Fragment Screening

Crystallographic fragment screening (CFS) provides excellent starting points for projects concerned with drug discovery or biochemical tool compound development. One of the fundamental prerequisites for effective CFS is the availability of a versatile fragment library. Here, we report on the assembly of the 1,103-compound F2X-Universal Library and its 96-compound sub-selection, the F2X-Entry Screen. Both represent the available fragment chemistry and are highly diverse in terms of their 3D-pharmacophore variations. Validation of the F2X-Entry Screen in CFS campaigns using endothiapepsin and the Aar2/RNaseH complex yielded hit rates of 30% and 21%, respectively, and revealed versatile binding sites. Dry presentation of the libraries allows CFS campaigns to be carried out with or without the co-solvent DMSO present. Most of the hits in our validation campaigns could be reproduced also in the absence of DMSO. Consequently, CFS can be carried out more efficiently and for a wider range of conditions and targets.

A Proof-of-Concept Fragment Screening of a Hit-Validated 96-Compounds Library against Human Carbonic Anhydrase II

Fragment screening is a powerful tool to identify and characterize binding pockets in proteins. We herein present the results of a proof-of-concept screening campaign of a versatile 96-entry fragment library from our laboratory against the drug target and model protein human carbonic anhydrase II. The screening revealed a novel chemotype for carbonic anhydrase inhibition, as well as less common non-covalent interaction types and unexpected covalent linkages. Lastly, different runs of the PanDDA tool reveal a practical hint for its application.

Fragments as Novel Starting Points for tRNA-Guanine Transglycosylase Inhibitors Found by Alternative Screening Strategies

Crystallography provides structural information crucial for fragment optimization, however several criteria must be met to screen directly on protein crystals as soakable, well-diffracting specimen must be available. We screened a 96-fragment library against the tRNA-modifying enzyme TGT using crystallography. Eight hits, some with surprising binding poses, were detected. However, the amount of data collection, reduction and refinement is assumed substantial. Therefore, having a reliable cascade of fast and cost-efficient methods available for pre-screening before embarking to elaborate crystallographic screening appears beneficial. This allows filtering of compounds to the most promising hits, available to rapidly progress from hit-to-lead. But how to ensure that this workflow is reliable? To answer this question, we also applied SPR and NMR to the same screening sample to study whether identical hits are retrieved. Upon hit-list comparisons, crystallography shows with NMR and SPR, only one overlapping hit and all three methods shared no common hits. This questions a cascade-type screening protocol at least in the current example. Compared to crystallography, SPR and NMR detected higher percentages of non-active-site binders suggesting the importance of running reporter ligand-based competitive screens in SPR and NMR, a requirement not needed in crystallography. Although not specific, NMR proved a more sensitive method relative to SPR and crystallography, as it picked up the highest numbers of binders.

Guided by evolution: from biology oriented synthesis to pseudo natural products

This review provides an overview and historical context to two concepts for the design of natural product-inspired compound libraries and highlights the used synthetic methodologies.

Kinetic Target-Guided Synthesis: Reaching the Age of Maturity

Kinetic target-guided synthesis (KTGS) is an original discovery strategy allowing a target to catalyze the irreversible synthesis of its own ligands from a pool of reagents. Although pioneered almost two decades ago, it only recently proved its usefulness in medicinal chemistry, as exemplified by the increasing number of protein targets used, the wider range of target and pocket types, and the diversity of therapeutic areas explored. In recent years, two new leads for in vivo studies were released. Amidations and multicomponent reactions expanded the armamentarium of reactions beyond triazole formation and two new examples of in cellulo KTGS were also disclosed. Herein, we analyze the origins and the chemical space of both KTGS ligands and warhead-bearing reagents. We review the KTGS timeline focusing on recent cases in order to give medicinal chemists the full scope of this strategy which has great potential for hit discovery and hit or lead optimization.

Fragment Hits: What do They Look Like and How do They Bind?

A “fragment hit”, a molecule of low molecular weight that has been validated to bind to a target protein, can be an effective chemical starting point for a drug discovery project. Our ability to find and progress fragment hits could potentially be improved by enhancing our understanding of their binding properties, which to date has largely been based on tacit knowledge and reports from individual projects. In the work reported here, we systematically analyzed the molecular and binding properties of fragment hits using 489 published protein–fragment complexes. We identified a number of notable features that these hits tend to have in common, including preferences in buried surface area upon binding, hydrogen bonding and other directional interactions with the protein targets, structural topology, functional-group occurrence, and degree of carbon saturation. In the future, taking account of these preferences in designing and selecting fragments to screen against protein targets may increase the chances of success in fragment screening campaigns.

The nature of ligand efficiency

Ligand efficiency is a widely used design parameter in drug discovery. It is calculated by scaling affinity by molecular size and has a nontrivial dependency on the concentration unit used to express affinity that stems from the inability of the logarithm function to take dimensioned arguments. Consequently, perception of efficiency varies with the choice of concentration unit and it is argued that the ligand efficiency metric is not physically meaningful nor should it be considered to be a metric. The dependence of ligand efficiency on the concentration unit can be eliminated by defining efficiency in terms of sensitivity of affinity to molecular size and this is illustrated with reference to fragment-to-lead optimizations. Group efficiency and fit quality are also examined in detail from a physicochemical perspective. The importance of examining relationships between affinity and molecular size directly is stressed throughout this study and an alternative to ligand efficiency for normalization of affinity with respect to molecular size is presented.

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

Molecular property diagnostic suite (MPDS): Development of disease-specific open source web portals for drug discovery

Molecular property diagnostic suite (MPDS) is a Galaxy-based open source drug discovery and development platform. MPDS web portals are designed for several diseases, such as tuberculosis, diabetes mellitus, and other metabolic disorders, specifically aimed to evaluate and estimate the drug-likeness of a given molecule. MPDS consists of three modules, namely data libraries, data processing, and data analysis tools which are configured and interconnected to assist drug discovery for specific diseases. The data library module encompasses vast information on chemical space, wherein the MPDS compound library comprises 110.31 million unique molecules generated from public domain databases. Every molecule is assigned with a unique ID and card, which provides complete information for the molecule. Some of the modules in the MPDS are specific to the diseases, while others are non-specific. Importantly, a suitably altered protocol can be effectively generated for another disease-specific MPDS web portal by modifying some of the modules. Thus, the MPDS suite of web portals shows great promise to emerge as disease-specific portals of great value, integrating chemoinformatics, bioinformatics, molecular modelling, and structure- and analogue-based drug discovery approaches.

Do Fragments and Crystallization Additives Bind Similarly to Drug-like Ligands?

The success of fragment-based drug design (FBDD) hinges upon the optimization of low-molecular-weight compounds (MW < 300 Da) with weak binding affinities to lead compounds with high affinity and selectivity. Usually, structural information from fragment-protein complexes is used to develop ideas about the binding mode of similar but drug-like molecules. In this regard, crystallization additives such as cryoprotectants or buffer components, which are highly abundant in crystal structures, are frequently ignored. Thus, the aim of this study was to investigate the information present in protein complexes with fragments as well as those with additives and how they relate to the binding modes of their drug-like counterparts. We present a thorough analysis of the binding modes of crystallographic additives, fragments, and drug-like ligands bound to four diverse targets of wide interest in drug discovery and highly represented in the Protein Data Bank: cyclin-dependent kinase 2, β-secretase 1, carbonic anhydrase 2, and trypsin. We identified a total of 630 unique molecules bound to the catalytic binding sites, among them 31 additives, 222 fragments, and 377 drug-like ligands. In general, we observed that, independent of the target, protein-fragment interaction patterns are highly similar to those of drug-like ligands and mostly cover the residues crucial for binding. Crystallographic additives are also able to show conserved binding modes and recover the residues important for binding in some of the cases. Moreover, we show evidence that the information from fragments and drug-like ligands can be applied to rescore docking poses in order to improve the prediction of binding modes.

Active Site Mapping of an Aspartic Protease by Multiple Fragment Crystal Structures: Versatile Warheads To Address a Catalytic Dyad

Crystallography is frequently used as follow-up method to validate hits identified by biophysical screening cascades. The capacity of crystallography to directly screen fragment libraries is often underestimated, due to its supposed low-throughput and need for high-quality crystals. We applied crystallographic fragment screening to map the protein-binding site of the aspartic protease endothiapepsin by individual soaking experiments. Here, we report on 41 fragments binding to the catalytic dyad and adjacent specificity pockets. The analysis identifies already known warheads but also reveals hydrazide, pyrazole, or carboxylic acid fragments as novel functional groups binding to the dyad. A remarkable swapping of the S1 and S1' pocket between structurally related fragments is explained by either steric demand, required displacement of a well-bound water molecule, or changes of trigonal-planar to tetrahedral geometry of an oxygen functional group in a side chain. Some warheads simultaneously occupying both S1 and S1' are promising starting points for fragment-growing strategies.

Fragment-Based Drug Design Facilitated by Protein-Templated Click Chemistry: Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin

There is an urgent need for the development of efficient methodologies that accelerate drug discovery. We demonstrate that the strategic combination of fragment linking/optimization and protein-templated click chemistry is an efficient and powerful method that accelerates the hit-identification process for the aspartic protease endothiapepsin. The best binder, which inhibits endothiapepsin with an IC50 value of 43 μm, represents the first example of triazole-based inhibitors of endothiapepsin. Our strategy could find application on a whole range of drug targets.

Experimental Active-Site Mapping by Fragments: Hot Spots Remote from the Catalytic Center of Endothiapepsin

Successful optimization of a given lead scaffold requires thorough binding-site mapping of the target protein particular in regions remote from the catalytic center where high conservation across protein families is given. We screened a 361-entry fragment library for binding to the aspartic protease endothiapepsin by crystallography. This enzyme is frequently used as a surrogate for the design of renin and β-secretase inhibitors. A hit rate of 20% was achieved, providing 71 crystal structures. Here, we discuss 45 binding poses of fragments accommodated in pockets remote from the catalytic dyad. Three major hot spots are discovered in remote binding areas: Asp81, Asp119, and Phe291. Compared to the dyad binders, bulkier fragments occupy these regions. Many of the discovered fragments suggest an optimization concept on how to grow them into larger ligands occupying adjacent binding pockets that will possibly endow them with the desired selectivity for one given member of a protein family.

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment-Based Drug Design Facilitated by Dynamic Combinatorial Chemistry

Fragment-based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit-identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X-ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis-acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240-fold improvement in potency compared to the parent hits. Subsequent X-ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit-identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit-to-lead optimization.

High-Throughput Crystallography: Reliable and Efficient Identification of Fragment Hits

Today the identification of lead structures for drug development often starts from small fragment-like molecules raising the chances to find compounds that successfully pass clinical trials. At the heart of the screening for fragments binding to a specific target, crystallography delivers structural information essential for subsequent drug design. While it is common to search for bound ligands in electron densities calculated directly after an initial refinement cycle, we raise the important question whether this strategy is viable for fragments characterized by low affinities. Here, we describe and provide a collection of high-quality diffraction data obtained from 364 protein crystals treated with diverse fragments. Subsequent data analysis showed that ∼25% of all hits would have been missed without further refining the resulting structures. To enable fast and reliable hit identification, we have designed an automated refinement pipeline that will inspire the development of optimized tools facilitating the successful application of fragment-based methods.

Six Biophysical Screening Methods Miss a Large Proportion of Crystallographically Discovered Fragment Hits: A Case Study

Fragment-based lead discovery (FBLD) has become a pillar in drug development. Typical applications of this method comprise at least two biophysical screens as prefilter and a follow-up crystallographic experiment on a subset of fragments. Clearly, structural information is pivotal in FBLD, but a key question is whether such a screening cascade strategy will retrieve the majority of fragment-bound structures. We therefore set out to screen 361 fragments for binding to endothiapepsin, a representative of the challenging group of aspartic proteases, employing six screening techniques and crystallography in parallel. Crystallography resulted in the very high number of 71 structures. Yet alarmingly, 44% of these hits were not detected by any biophysical screening approach. Moreover, any screening cascade, building on the results from two or more screening methods, would have failed to predict at least 73% of these hits. We thus conclude that, at least in the present case, the frequently applied biophysical prescreening filters deteriorate the number of possible X-ray hits while only the immediate use of crystallography enables exhaustive retrieval of a maximum of fragment structures, which represent a rich source guiding hit-to-lead-to-drug evolution.

Structures of endothiapepsin-fragment complexes from crystallographic fragment screening using a novel, diverse and affordable 96-compound fragment library

Crystallographic screening of the binding of small organic compounds (termed fragments) to proteins is increasingly important for medicinal chemistry-oriented drug discovery. To enable such experiments in a widespread manner, an affordable 96-compound library has been assembled for fragment screening in both academia and industry. The library is selected from already existing protein-ligand structures and is characterized by a broad ligand diversity, including buffer ingredients, carbohydrates, nucleotides, amino acids, peptide-like fragments and various drug-like organic compounds. When applied to the model protease endothiapepsin in a crystallographic screening experiment, a hit rate of nearly 10% was obtained. In comparison to other fragment libraries and considering that no pre-screening was performed, this hit rate is remarkably high. This demonstrates the general suitability of the selected compounds for an initial fragment-screening campaign. The library composition, experimental considerations and time requirements for a complete crystallographic fragment-screening campaign are discussed as well as the nine fully refined obtained endothiapepsin-fragment structures. While most of the fragments bind close to the catalytic centre of endothiapepsin in poses that have been observed previously, two fragments address new sites on the protein surface. ITC measurements show that the fragments bind to endothiapepsin with millimolar affinity.

XDSAPP2.0

XDSAPPis an expert system and graphical user interface (GUI) for the automated processing of diffraction images using theXDSprogram suite and other programs. The latest major update and the extension of the program are presented here. The update includes new features, as well as improvements in the GUI and the underlying decision-making system.XDSAPPis freely available for academic users.

Charting a Path to Success in Virtual Screening

Docking is commonly applied to drug design efforts, especially high-throughput virtual screenings of small molecules, to identify new compounds that bind to a given target. Despite great advances and successful applications in recent years, a number of issues remain unsolved. Most of the challenges and problems faced when running docking experiments are independent of the specific software used, and can be ascribed to either improper input preparation or to the simplified approaches applied to achieve high-throughput speed. Being aware of approximations and limitations of such methods is essential to prevent errors, deal with misleading results, and increase the success rate of virtual screening campaigns. In this review, best practices and most common issues of docking and virtual screening will be discussed, covering the journey from the design of the virtual experiment to the hit identification.

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.