1D and 2D NMR for KRAS:Ligand Binding

Fragment-based screening by ligand-observed 1D NMR and binding interface mapping by protein-observed 2D NMR are popular methods used in drug discovery. These methods allow researchers to detect compound binding over a wide range of affinities and offer a simultaneous assessment of solubility, purity, and chemical formula accuracy of the target compounds and the 15N-labeled protein when examined by 1D and 2D NMR, respectively. These methods can be applied for screening fragment binding to the active (GMPPNP-bound) and inactive (GDP-bound) states of oncogenic KRAS mutants.

A Benchmark Study of Protein-Fragment Complex Structure Calculations with NMR2

Protein-fragment complex structures are particularly sought after in medicinal chemistry to rationally design lead molecules. These structures are usually derived using X-ray crystallography, but the failure rate is non-neglectable. NMR is a possible alternative for the calculation of weakly interacting complexes. Nevertheless, the time-consuming protein signal assignment step remains a barrier to its routine application. NMR Molecular Replacement (NMR2) is a versatile and rapid method that enables the elucidation of a protein-ligand complex structure. It has been successfully applied to peptides, drug-like molecules, and more recently to fragments. Due to the small size of the fragments, ca < 300 Da, solving the structures of the protein-fragment complexes is particularly challenging. Here, we present the expected performances of NMR2 when applied to protein-fragment complexes. The NMR2 approach has been benchmarked with the SERAPhic fragment library to identify the technical challenges in protein-fragment NMR structure calculation. A straightforward strategy is proposed to increase the method's success rate further. The presented work confirms that NMR2 is an alternative method to X-ray crystallography for solving protein-fragment complex structures.

A novel compound to overcome influenza drug resistance in endonuclease inhibitors

Influenza is a seasonal respiratory illness that kills hundreds of thousands of people every year. Currently, neuraminidase inhibitors and endonuclease inhibitors are used in antiviral therapy. However, both drug types have encountered drug-resistant influenza strains in the human body. Fortunately, there is currently no resistance to endonuclease inhibitors in wild strains of influenza. We obtained the molecules with endonuclease inhibitor activity independent of the existing drug-resistant strains through computer-aided drug design, and we hope the obtained results can lay a theoretical foundation for the development of high-activity endonucleases. Combining a traditional fragment-based drug discovery approach with AI-directed fragment growth, we selected and designed a compound that achieved antiviral activity on drug-resistant strains by avoiding mutable residues and drug-resistant residues. We predicted the related properties using an ADMET model. Finally, we obtained a compound similar to baloxavir in terms of binding free energy but not affected by baloxavir resistance.

Fragment merging strategies with known pyrimidine scaffolds targeting dihydrofolate reductase from Mycobacterium tuberculosis

Dihydrofolate reductase (DHFR) is a key enzyme involved in the folate pathway that has been heavily targeted for the development of therapeutics against cancer and bacterial and protozoa infections amongst others. Despite being an essential enzyme for Mycobacterium tuberculosis (Mtb) viability, DHFR remains an underexploited target for tuberculosis (TB) treatment. Herein, we report the preparation and evaluation of a series of compounds against Mtb DHFR (MtbDHFR). The compounds have been designed using a merging strategy of traditional pyrimidine-based antifolates with a previously discovered unique fragment hit against MtbDHFR. In this series, four compounds displayed a high affinity against MtbDHFR, with sub-micromolar affinities. Additionally, we determined the binding mode of six of the best compounds using protein crystallography, which revealed occupation of an underutilised region of the active site.

Efficiently driving protein-based fragment screening and lead discovery using two-dimensional NMR

Fragment-based drug discovery (FBDD) and validation of small molecule binders using NMR spectroscopy is an established and widely used method in the early stages of drug discovery. Starting from a library of small compounds, ligand- or protein-observed NMR methods are employed to detect binders, typically weak, that become the starting points for structure-activity relationships (SAR) by NMR. Unlike the more frequently used ligand-observed 1D NMR techniques, protein-observed 2D ¹H-¹⁵N or ¹H-¹³C heteronuclear correlation (HSQC or HMQC) methods offer insights that include the mechanism of ligand engagement on the target and direct binding affinity measurements in addition to routine screening. We hereby present the development of a set of software tools within the MestReNova (Mnova) package for analyzing 2D NMR for FBDD and hit validation purposes. The package covers three main tasks: (1) unsupervised profiling of raw data to identify outlier data points to exclude in subsequent analyses; (2) batch processing of single-point spectra to identify and rank binders based on chemical shift perturbations or spectral peak intensity changes; and (3) batch processing of multiple titration series to derive binding affinities (K_D) by tracing the changes in peak locations or measuring global spectral changes. Toward this end, we implemented and evaluated a set of algorithms for automated peak tracing, spectral binning, and variance analysis by PCA, and a new tool for spectral data intensity comparison using ECHOS. The accuracy and speed of the tools are demonstrated on 2D NMR binding data collected on ligands used in the development of potential inhibitors of the anti-apoptotic MCL-1 protein.

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.

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).

Genetic validation of Aspergillus fumigatus phosphoglucomutase as a viable therapeutic target in invasive aspergillosis

Aspergillus fumigatus is the causative agent of invasive aspergillosis, an infection with mortality rates of up to 50%. The glucan-rich cell wall of A. fumigatus is a protective structure that is absent from human cells and is a potential target for antifungal treatments. Glucan is synthesized from the donor uridine diphosphate glucose, with the conversion of glucose-6-phosphate to glucose-1-phosphate by the enzyme phosphoglucomutase (PGM) representing a key step in its biosynthesis. Here, we explore the possibility of selectively targeting A. fumigatus PGM (AfPGM) as an antifungal treatment strategy. Using a promoter replacement strategy, we constructed a conditional pgm mutant and revealed that pgm is required for A. fumigatus growth and cell wall integrity. In addition, using a fragment screen, we identified the thiol-reactive compound isothiazolone fragment of PGM as targeting a cysteine residue not conserved in the human ortholog. Furthermore, through scaffold exploration, we synthesized a para-aryl derivative (ISFP10) and demonstrated that it inhibits AfPGM with an IC50 of 2 μM and exhibits 50-fold selectivity over the human enzyme. Taken together, our data provide genetic validation of PGM as a therapeutic target and suggest new avenues for inhibiting AfPGM using covalent inhibitors that could serve as tools for chemical validation.

Identification of Novel GSK-3β Hits Using Competitive Biophysical Assays

Glycogen synthase kinase 3 beta (GSK-3β) is an evolutionarily conserved serine-threonine kinase dysregulated in numerous pathologies, such as Alzheimer’s disease and cancer. Even though GSK-3β is a validated pharmacological target most of its inhibitors have two main limitations: the lack of selectivity due to the high homology that characterizes the ATP binding site of most kinases, and the toxicity that emerges from GSK-3β complete inhibition which translates into the impairment of the plethora of pathways GSK-3β is involved in. Starting from a 1D ¹⁹F NMR fragment screening, we set up several biophysical assays for the identification of GSK-3β inhibitors capable of binding protein hotspots other than the ATP binding pocket or to the ATP binding pocket, but with an affinity able of competing with a reference binder. A phosphorylation activity assay on a panel of several kinases provided selectivity data that were further rationalized and corroborated by structural information on GSK-3β in complex with the hit compounds. In this study, we identified promising fragments, inhibitors of GSK-3β, while proposing an alternative screening workflow that allows facing the flaws that characterize the most common GSK-3β inhibitors through the identification of selective inhibitors and/or inhibitors able to modulate GSK-3β activity without leading to its complete inhibition.

NMR Reporter Assays for the Quantification of Weak-Affinity Receptor-Ligand Interactions

Biophysical methods are widely employed in academia and the pharmaceutical industry to detect and quantify weak molecular interactions. Such methods find broad application in fragment-based drug discovery (FBDD). In an FBDD campaign, a suitable affinity determination method is key to advancing a project beyond the initial screening phase. Protein-observed (PO) nuclear magnetic resonance (NMR) finds widespread use due to its ability to sensitively detect very weak interactions at residue-level resolution. When there are issues precluding the use of PO-NMR, ligand-observed (LO) NMR reporter assays can be a useful alternative. Such assays can measure affinities in a similar range to PO-NMR while offering some distinct advantages, especially with regard to protein consumption and compound throughput. In this paper, we take a closer look at setting up such assays for routine use, with the aim of getting high-quality, accurate data and good throughput. We assess some of the key characteristics of these assays in the mathematical framework established for fluorescence polarization assays with which the readers may be more familiar. We also provide guidance on setting up such assays and compare their performance with other affinity determination methods that are commonly used in drug discovery.

The QSAR Paradigm in Fragment-Based Drug Discovery: From the Virtual Generation of Target Inhibitors to Multi-Scale Modeling

Fragment-Based Drug Design (FBDD) has established itself as a promising approach in modern drug discovery, accelerating and improving lead optimization, while playing a crucial role in diminishing the high attrition rates at all stages in the drug development process. On the other hand, FBDD has benefited from the application of computational methodologies, where the models derived from the Quantitative Structure-Activity Relationships (QSAR) have become consolidated tools. This mini-review focuses on the evolution and main applications of the QSAR paradigm in the context of FBDD in the last five years. This report places particular emphasis on the QSAR models derived from fragment-based topological approaches to extract physicochemical and/or structural information, allowing to design potentially novel mono- or multi-target inhibitors from relatively large and heterogeneous databases. Here, we also discuss the need to apply multi-scale modeling, to exemplify how different datasets based on target inhibition can be simultaneously integrated and predicted together with other relevant endpoints such as the biological activity against non-biomolecular targets, as well as in vitro and in vivo toxicity and pharmacokinetic properties. In this context, seminal papers are briefly analyzed. As huge amounts of data continue to accumulate in the domains of the chemical, biological and biomedical sciences, it has become clear that drug discovery must be viewed as a multi-scale optimization process. An ideal multi-scale approach should integrate diverse chemical and biological data and also serve as a knowledge generator, enabling the design of potentially optimal chemicals that may become therapeutic agents.

A fragment-based approach to assess the ligandability of ArgB, ArgC, ArgD and ArgF in the L-arginine biosynthetic pathway of Mycobacterium tuberculosis

The L-arginine biosynthesis pathway consists of eight enzymes that catalyse the conversion of L-glutamate to L-arginine. Arginine auxotrophs (argB/argF deletion mutants) of Mycobacterium tuberculosis are rapidly sterilised in mice, while inhibition of ArgJ with Pranlukast was found to clear chronic M. tuberculosis infection in a mouse model. Enzymes in the arginine biosynthetic pathway have therefore emerged as promising targets for anti-tuberculosis drug discovery. In this work, the ligandability of four enzymes of the pathway ArgB, ArgC, ArgD and ArgF is assessed using a fragment-based approach. We identify several hits against these enzymes validated with biochemical and biophysical assays, as well as X-ray crystallographic data, which in the case of ArgB were further confirmed to have on-target activity against M. tuberculosis. These results demonstrate the potential for more enzymes in this pathway to be targeted with dedicated drug discovery programmes.

Inspecting the Mechanism of Fragment Hits Binding on SARS-CoV-2 Mpro by Using Supervised Molecular Dynamics (SuMD) Simulations

Computational approaches supporting the early characterization of fragment molecular recognition mechanism represent a valuable complement to more expansive and low‐throughput experimental techniques. In this retrospective study, we have investigated the geometric accuracy with which high‐throughput supervised molecular dynamics simulations (HT‐SuMD) can anticipate the experimental bound state for a set of 23 fragments targeting the SARS‐CoV‐2 main protease. Despite the encouraging results herein reported, in line with those previously described for other MD‐based posing approaches, a high number of incorrect binding modes still complicate HT‐SuMD routine application. To overcome this limitation, fragment pose stability has been investigated and integrated as part of our in‐silico pipeline, allowing us to prioritize only the more reliable predictions.

Insights into newly approved drugs from a medicinal chemistry perspective

The development of new drugs is becoming notably harder each decade. To overcome the present pitfalls in the drug development pipeline, such as those related to potency, selectivity, or absorption, distribution, metabolism, excretion and toxicity properties, medicinal chemistry strategies need to be in continuous evolution and need to become even more multidisciplinary. In this review, we present how structure-based, ligand-based, and fragment-based drug design (SBDD, LBDD, and FBDD, respectively) and their respective techniques were used for the design and optimization of successful cases of new molecular entities (NMEs) approved by the Food and Drug Administration (FDA).

Identifying novel putative ERK1/2 inhibitors via hybrid scaffold hopping -FBDD approach

ERK inhibitors are continuously explored by the researchers due to their clinical significance in resistant tumor cell lines. Though many ERK1/2 inhibitors are reported, there is still need to identify novel hits to increase the number of molecules in clinical trials. Therefore, an urgent need is to examine the existing chemical space for ERK inhibitory potential with an aim to develop novel scaffolds which can act as potent ERKs inhibitors. In this study, Ulixertinib, a known ERK2 inhibitor was selected to perform scaffold hopping to discover new scaffolds with similar binding mode followed by molecular docking analysis of the hits with highest similarity score to determine, both the binding mode and affinity in the catalytic domain of ERK2. The top hit was then subjected to FBDD to identify side chains which could enhance the binding affinity in the catalytic domain of ERK2. Again, docking analysis was performed to validate and determine their binding affinity. Further the top hit identified after docking analysis was subjected to molecular dynamic simulations. Overall, 3 hits (ligand 6, 8 and 10) were found to possess optimum pharmacodynamic and pharmacokinetic profile, in-silico, to be claimed as putative ERK2 inhibitors. This study disclosed new lead molecules with putative ERK2 inhibitory potential which may be further validated via biological evaluation.

Fusion Protein Targeted Antiviral Peptides: Fragment-Based Drug Design (FBDD) Guided Rational Design of Dipeptides Against SARS-CoV-2

Infectious diseases caused by viruses have become a serious public health issue in the recent past, including the current pandemic situation of COVID-19. Enveloped viruses are most commonly known to cause emerging and recurring infectious diseases. Viral and cell membrane fusion is the major key event in the case of enveloped viruses that is required for their entry into the cell. Viral fusion proteins play an important role in the fusion process and in infection establishment. Because of this, the fusion process targeting antivirals become an interest to fight against viral diseases caused by the enveloped virus. Lower respiratory tract infections casing viruses like influenza, respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus (SARS-CoV) are examples of such enveloped viruses that are at the top in public health issues. Here, we summarized the viral fusion protein targeted antiviral peptides along with their mechanism and specific design to combat the viral fusion process. The pandemic COVID-19, severe respiratory syndrome disease is an outbreak worldwide. There are no definitive drugs yet, but few are in on-going trials. Here, an approach of fragmentbased drug design (FBDD) methodology is used to identify the broad spectrum agent target to the conserved region of fusion protein of SARS CoV-2. Three dipeptides (DL, LQ and ID) were chosen from the library and designed by the systematic combination along with their possible modifications of amino acids to the target sites. Designed peptides were docked with targeted fusion protein after energy minimization. Results show strong and significant binding affinity (DL = -60.1 kcal/mol; LQ = - 62.8 kcal/mol; ID= -71.5 kcal/mol) during interaction. Anyone of the active peptides from the developed libraries may help to block the target sites competitively to successfully control COVID-19.

Using NMR Spectroscopy in the Fragment-Based Drug Discovery of Small-Molecule Anticancer Targeted Therapies

Against the challenge of providing personalized cancer care, the development of targeted therapies stands as a promising approach. The discovery of these agents can benefit from fragment-based drug discovery (FBDD) methods that help guide ligand design and provide key structural information on the targets of interest. In particular, nuclear magnetic resonance spectroscopy is a promising biophysical tool in fragment discovery due to its detection capabilities and versatility. This review provides an overview of FBDD, describes the basis of NMR-based fragment screening, summarizes some exciting technical advances reported over the past decades, and closes with a discussion of selected case studies where this technique has been used as part of drug discovery campaigns to produce lead compounds towards the design of anti-cancer targeted therapies.

NMR quality control of fragment libraries for screening

Fragment-based screening has evolved as a remarkable approach within the drug discovery process both in the industry and academia. Fragment screening has become a more structure-based approach to inhibitor development, but also towards development of pathway-specific clinical probes. However, it is often witnessed that the availability, immediate and long-term, of a high quality fragment-screening library is still beyond the reach of most academic laboratories. Within iNEXT (Infrastructure for NMR, EM and X-rays for Translational research), a EU-funded Horizon 2020 program, a collection of 782 fragments were assembled utilizing the concept of "poised fragments" with the aim to facilitate downstream synthesis of ligands with high affinity by fragment ligation. Herein, we describe the analytical procedure to assess the quality of this purchased and assembled fragment library by NMR spectroscopy. This quality assessment requires buffer solubility screening, comparison with LC/MS quality control and is supported by state-of-the-art software for high throughput data acquisition and on-the-fly data analysis. Results from the analysis of the library are presented as a prototype of fragment progression through the quality control process.

CcpNmr AnalysisScreen, a new software programme with dedicated automated analysis tools for fragment-based drug discovery by NMR

Fragment-based drug discovery or FBDD is one of the main methods used by industry and academia for identifying drug-like candidates in early stages of drug discovery. NMR has a significant impact at any stage of the drug discovery process, from primary identification of small molecules to the elucidation of binding modes for guiding optimisations. The essence of NMR as an analytical tool, however, requires the processing and analysis of relatively large amounts of single data items, e.g. spectra, which can be daunting when managed manually. One bottleneck in FBDD by NMR is a lack of adequate and well-integrated resources for NMR data analysis that are freely available to the community. Thus, scientists typically resort to manually inspecting large datasets and relying predominantly on subjective interpretations. In this manuscript, we present CcpNmr AnalysisScreen, a software package that provides computational tools for automated analysis of FBDD data by NMR. We outline how the quality of collected spectra can be evaluated quickly, and how robust workflows can be optimised for reliable and rapid hit identification. With an intuitive graphical user interface and powerful algorithms, AnalysisScreen enables easy analysis of the large datasets needed in the early process of drug discovery by NMR.

Revisiting biomolecular NMR spectroscopy for promoting small-molecule drug discovery

Recently, there has been increasing interest in new modalities such as therapeutic antibodies and gene therapy at a number of pharmaceutical companies. Moreover, in small-molecule drug discovery at such companies, efforts have focused on hard-to-drug targets such as inhibiting protein-protein interactions. Biomolecular NMR spectroscopy has been used in drug discovery in a variety of ways, such as for the reliable detection of binding and providing three-dimensional structural information for structure-based drug design. The advantages of using NMR spectroscopy have been known for decades (Jahnke in J Biomol NMR 39:87-90, (2007); Gossert and Jahnke in Prog Nucl Magn Reson Spectrosc 97:82-125, (2016)). For tackling hard-to-drug targets and increasing the success in discovering drug molecules, in-depth analysis of drug-target protein interactions performed by biophysical methods will be more and more essential. Here, we review the advantages of NMR spectroscopy as a key technology of biophysical methods and also discuss issues such as using cutting-edge NMR spectrometers and increasing the demand of utilizing conformational dynamics information for promoting small-molecule drug discovery.

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.

Applied Biophysical Methods in Fragment-Based Drug Discovery

Fragment-based drug discovery (FBDD) has come of age in the last decade with the FDA approval of four fragment-derived drugs. Biophysical methods are at the heart of hit discovery and validation in FBDD campaigns. The three most commonly used methods, thermal shift, surface plasmon resonance, and nuclear magnetic resonance, can be daunting for the novice user. We aim here to provide the nonexpert user of these methods with a summary of problems and challenges that might be faced, but also highlight the potential gains that each method can contribute to an FBDD project. While our view on FBDD is slightly biased toward enabling structure-guided drug discovery, most of the points we address in this review are also valid for non-structure-focused FBDD.

Identifying Ortholog Selective Fragment Molecules for Bacterial Glutaredoxins by NMR and Affinity Enhancement by Modification with an Acrylamide Warhead

Illustrated here is the development of a new class of antibiotic lead molecules targeted at Pseudomonas aeruginosa glutaredoxin (PaGRX). This lead was produced to (a) circumvent efflux-mediated resistance mechanisms via covalent inhibition while (b) taking advantage of species selectivity to target a fundamental metabolic pathway. This work involved four components: a novel workflow for generating protein specific fragment hits via independent nuclear magnetic resonance (NMR) measurements, NMR-based modeling of the target protein structure, NMR guided docking of hits, and synthetic modification of the fragment hit with a vinyl cysteine trap moiety, i.e., acrylamide warhead, to generate the chimeric lead. Reactivity of the top warhead-fragment lead suggests that the ortholog selectivity observed for a fragment hit can translate into a substantial kinetic advantage in the mature warhead lead, which bodes well for future work to identify potent, species specific drug molecules targeted against proteins heretofore deemed undruggable.

NMR-based fragment screening and lead discovery accelerated by principal component analysis

Protein-based NMR spectroscopy has proven to be a very robust method for finding fragment leads to protein targets. However, one limitation of protein-based NMR is that the data acquisition and analysis can be time consuming. In order to streamline the scoring of protein-based NMR fragment screening data and the determination of ligand affinities using 2D NMR experiments we have developed a data analysis workflow based on principal component analysis (PCA) within the TREND NMR Pro software package. We illustrate this using four different proteins and sets of ligands which interact with these proteins over a range of affinities. Also, these PCA-based methods can be successfully applied even to systems where ligand binding to target proteins is in intermediate or even slow exchange on the NMR time scale. Finally, these methods will work for scoring of fragment binding data using protein spectra that are either highly overlapped or lower in resolution.

Kallikrein 5 inhibitors identified through structure based drug design in search for a treatment for Netherton Syndrome

Netherton syndrome (NS) is a rare and debilitating severe autosomal recessive genetic skin disease with high mortality rates particularly in neonates. NS is caused by loss-of-function SPINK5 mutations leading to unregulated kallikrein 5 (KLK5) and kallikrein 7 (KLK7) activity. Furthermore, KLK5 inhibition has been proposed as a potential therapeutic treatment for NS. Identification of potent and selective KLK5 inhibitors would enable further exploration of the disease biology and could ultimately lead to a treatment for NS. This publication describes how fragmentation of known trypsin-like serine protease (TLSP) inhibitors resulted in the identification of a series of phenolic amidine-based KLK5 inhibitors 1. X-ray crystallography was used to find alternatives to the phenol interaction leading to identification of carbonyl analogues such as lactam 13 and benzimidazole 15. These reversible inhibitors, with selectivity over KLK1 (10-100 fold), provided novel starting points for the guided growth towards suitable tool molecules for the exploration of KLK5 biology.

Fragment-Based Structural Optimization of a Natural Product Itampolin A as a p38α Inhibitor for Lung Cancer

Marine animals and plants provide abundant secondary metabolites with antitumor activity. Itampolin A is a brominated natural tyrosine secondary metabolite that is isolated from the sponge Iotrochota purpurea. Recently, we have achieved the first total synthesis of this brominated tyrosine secondary metabolite, which was found to be a potent p38α inhibitor exhibiting anticancer effects. A fragment-based drug design (FBDD) was carried out to optimize itampolin A. Forty-five brominated tyrosine derivatives were synthesized with interesting biological activities. Then, a QSAR study was carried out to explore the structural determinants responsible for the activity of brominated tyrosine skeleton p38α inhibitors. The lead compound was optimized by a FBDD method, then three series of brominated tyrosine derivatives were synthesized and evaluated for their inhibitory activities against p38α and tumor cells. Compound 6o (IC₅₀ = 0.66 μM) exhibited significant antitumor activity against non-small cell lung A549 cells (A549). This also demonstrated the feasibility of the FBDD method of structural optimization.

Allosteric Small-Molecule Serine/Threonine Kinase Inhibitors

Deregulation of protein kinase activity has been linked to many diseases ranging from cancer to AIDS and neurodegenerative diseases. Not surprisingly, drugging the human kinome - the complete set of kinases encoded by the human genome - has been one of the major drug discovery pipelines. Majority of the approved clinical kinase inhibitors target the ATP binding site of kinases. However, the remarkable sequence and structural similarity of ATP binding pockets of kinases make selective inhibition of kinases a daunting task. To circumvent these issues, allosteric inhibitors that target sites other than the orthosteric ATP binding pocket have been developed. The structural diversity of the allosteric sites allows these inhibitors to have higher selectivity, lower toxicity and improved physiochemical properties and overcome drug resistance associated with the use of conventional kinase inhibitors. In this chapter, we will focus on the allosteric inhibitors of selected serine/threonine kinases, outline the benefits of using these inhibitors and discuss the challenges and future opportunities.

The SGC beyond structural genomics: redefining the role of 3D structures by coupling genomic stratification with fragment-based discovery

The ongoing explosion in genomics data has long since outpaced the capacity of conventional biochemical methodology to verify the large number of hypotheses that emerge from the analysis of such data. In contrast, it is still a gold-standard for early phenotypic validation towards small-molecule drug discovery to use probe molecules (or tool compounds), notwithstanding the difficulty and cost of generating them. Rational structure-based approaches to ligand discovery have long promised the efficiencies needed to close this divergence; in practice, however, this promise remains largely unfulfilled, for a host of well-rehearsed reasons and despite the huge technical advances spearheaded by the structural genomics initiatives of the noughties. Therefore the current, fourth funding phase of the Structural Genomics Consortium (SGC), building on its extensive experience in structural biology of novel targets and design of protein inhibitors, seeks to redefine what it means to do structural biology for drug discovery. We developed the concept of a Target Enabling Package (TEP) that provides, through reagents, assays and data, the missing link between genetic disease linkage and the development of usefully potent compounds. There are multiple prongs to the ambition: rigorously assessing targets' genetic disease linkages through crowdsourcing to a network of collaborating experts; establishing a systematic approach to generate the protocols and data that comprise each target's TEP; developing new, X-ray-based fragment technologies for generating high quality chemical matter quickly and cheaply; and exploiting a stringently open access model to build multidisciplinary partnerships throughout academia and industry. By learning how to scale these approaches, the SGC aims to make structures finally serve genomics, as originally intended, and demonstrate how 3D structures systematically allow new modes of druggability to be discovered for whole classes of targets.

Fragment-based drug discovery as alternative strategy to the drug development for neglected diseases

Neglected diseases (NDs) affect large populations and almost whole continents, representing 12% of the global health burden. In contrast, the treatment available today is limited and sometimes ineffective. Under this scenery, the Fragment-Based Drug Discovery emerged as one of the most promising alternatives to the traditional methods of drug development. This method allows achieving new lead compounds with smaller size of fragment libraries. Even with the wide Fragment-Based Drug Discovery success resulting in new effective therapeutic agents against different diseases, until this moment few studies have been applied this approach for NDs area. In this article, we discuss the basic Fragment-Based Drug Discovery process, brief successful ideas of general applications and show a landscape of its use in NDs, encouraging the implementation of this strategy as an interesting way to optimize the development of new drugs to NDs.

Application of the fragment molecular orbital method analysis to fragment-based drug discovery of BET (bromodomain and extra-terminal proteins) inhibitors

The molecular interactions of inhibitors of bromodomains (BRDs) were investigated. BRDs are protein interaction modules that recognizing ε-N-acetyl-lysine (εAc-Lys) motifs found in histone tails and are promising protein-protein interaction (PPI) targets. First, we analyzed a peptide ligand containing εAc-Lys to evaluate native PPIs. We then analyzed tetrahydroquinazoline-6-yl-benzensulfonamide derivatives found by fragment-based drug design (FBDD) and examined their interactions with the protein compared with the peptide ligand in terms of the inter-fragment interaction energy. In addition, we analyzed benzodiazepine derivatives that are high-affinity ligands for BRDs and examined differences in the CH/π interactions of the amino acid residues. We further surveyed changes in the charges of the amino acid residues among individual ligands, performed pair interaction energy decomposition analysis and estimated the water profile within the ligand binding site. Thus, useful insights for drug design were provided. Through these analyses and considerations, we show that the FMO method is a useful drug design tool to evaluate the process of FBDD and to explore PPI inhibitors.

An NMR-Guided Screening Method for Selective Fragment Docking and Synthesis of a Warhead Inhibitor

Selective hits for the glutaredoxin ortholog of Brucella melitensis are determined using STD NMR and verified by trNOE and (15)N-HSQC titration. The most promising hit, RK207, was docked into the target molecule using a scoring function to compare simulated poses to experimental data. After elucidating possible poses, the hit was further optimized into the lead compound by extension with an electrophilic acrylamide warhead. We believe that focusing on selectivity in this early stage of drug discovery will limit cross-reactivity that might occur with the human ortholog as the lead compound is optimized. Kinetics studies revealed that lead compound 5 modified with an ester group results in higher reactivity than an acrylamide control; however, after modification this compound shows little selectivity for bacterial protein versus the human ortholog. In contrast, hydrolysis of compound 5 to the acid form results in a decrease in the activity of the compound. Together these results suggest that more optimization is warranted for this simple chemical scaffold, and opens the door for discovery of drugs targeted against glutaredoxin proteins-a heretofore untapped reservoir for antibiotic agents.

Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design-Part 2

Methionine aminopeptidase-2 (MetAP2) is an enzyme that cleaves an N-terminal methionine residue from a number of newly synthesized proteins. This step is required before they will fold or function correctly. Pre-clinical and clinical studies with a MetAP2 inhibitor suggest that they could be used as a novel treatment for obesity. Herein we describe the discovery of a series of pyrazolo[4,3-b]indoles as reversible MetAP2 inhibitors. A fragment-based drug discovery (FBDD) approach was used, beginning with the screening of fragment libraries to generate hits with high ligand-efficiency (LE). An indazole core was selected for further elaboration, guided by structural information. SAR from the indazole series led to the design of a pyrazolo[4,3-b]indole core and accelerated knowledge-based fragment growth resulted in potent and efficient MetAP2 inhibitors, which have shown robust and sustainable body weight loss in DIO mice when dosed orally.

Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design-Part 1

Methionine aminopeptidase 2 (MetAP2) is an enzyme that cleaves an N-terminal methionine residue from a number of newly synthesized proteins. Pre-clinical and clinical studies suggest that MetAP2 inhibitors could be used as a novel treatment for obesity. Herein we describe our use of fragment screening methods and structural biology to quickly identify and elaborate an indazole fragment into a series of reversible MetAP2 inhibitors with <10nM potency, excellent selectivity, and favorable in vitro safety profiles.

Fragment-based drug discovery of potent and selective MKK3/6 inhibitors

The MAPK signaling cascade, comprised of several linear and intersecting pathways, propagates signaling into the nucleus resulting in cytokine and chemokine release. The Map Kinase Kinase isoforms 3 and 6 (MKK3 and MKK6) are responsible for the phosphorylation and activation of p38, and are hypothesized to play a key role in regulating this pathway without the redundancy seen in downstream effectors. Using FBDD, we have discovered efficient and selective inhibitors of MKK3 and MKK6 that can serve as tool molecules to help further understand the role of these kinases in MAPK signaling, and the potential impact of inhibiting kinases upstream of p38.

Navigating into the binding pockets of the HER family protein kinases: discovery of novel EGFR inhibitor as antitumor agent

The epidermal growth factor receptor (EGFR) family has been validated as a successful antitumor drug target for decades. Known EGFR inhibitors were exposed to distinct drug resistance against the various EGFR mutants within non-small-cell lung cancer (NSCLC), particularly the T790M mutation. Although so far a number of studies have been reported on the development of third-generation EGFR inhibitors for overcoming the resistance issue, the design procedure largely depends on the intuition of medicinal chemists. Here we retrospectively make a detailed analysis of the 42 EGFR family protein crystal complexes deposited in the Protein Data Bank (PDB). Based on the analysis of inhibitor binding modes in the kinase catalytic cleft, we identified a potent EGFR inhibitor (compound A-10) against drug-resistant EGFR through fragment-based drug design. This compound showed at least 30-fold more potency against EGFR T790M than the two control molecules erlotinib and gefitinib in vitro. Moreover, it could exhibit potent HER2 inhibitory activities as well as tumor growth inhibitory activity. Molecular docking studies revealed a structural basis for the increased potency and mutant selectivity of this compound. Compound A-10 may be selected as a promising candidate in further preclinical studies. In addition, our findings could provide a powerful strategy to identify novel selective kinase inhibitors on the basis of detailed kinase–ligand interaction space in the PDB.

Identification of anthranilamide derivatives as potential factor Xa inhibitors: drug design, synthesis and biological evaluation

The coagulation enzyme factor Xa (fXa) plays a crucial role in the blood coagulation cascade. In this study, three-dimensional fragment based drug design (FBDD) combined with structure-based pharmacophore (SBP) model and structural consensus docking were employed to identify novel fXa inhibitors. After a multi-stage virtual screening (VS) workflow, two hit compounds 3780 and 319 having persistent high performance were identified. Then, these two hit compounds and several analogs were synthesized and screened for in-vitro inhibition of fXa. The experimental data showed that most of the designed compounds displayed significant in vitro potency against fXa. Among them, compound 9b displayed the greatest in vitro potency against fXa with the IC50 value of 23 nM and excellent selectivity versus thrombin (IC50 = 40 μM). Moreover, the prolongation of the prothrombin time (PT) was measured for compound 9b to evaluate its in vitro anticoagulant activity. As a result, compound 9b exhibited pronounced anticoagulant activity with the 2 × PT value of 8.7 μM.

Structure-based drug design for G protein-coupled receptors

Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed.

A Back-to-Front Fragment-Based Drug Design Search Strategy Targeting the DFG-Out Pocket of Protein Tyrosine Kinases

We present a straightforward process for the discovery of novel back pocket-binding fragment molecules against protein tyrosine kinases. The approach begins by screening against the nonphosphorylated target kinase with subsequent counterscreening of hits against the phosphorylated enzyme. Back pocket-binding fragments are inactive against the phosphorylated kinase. Fragment molecules are of insufficient size to span both regions of the ATP binding pocket; thus, the outcome is binary (back pocket-binding or hinge-binding). Next, fragments with the appropriate binding profile are assayed in combination with a known hinge-binding fragment and subsequently with a known back pocket-binding fragment. Confirmation of back pocket-binding by Yonetani-Theorell plot analysis progresses candidate fragments to crystallization trials. The method is exemplified by a fragment screening campaign against vascular endothelial growth factor receptor 2, and a novel back pocket-binding fragment is presented.