How Are Fragments Optimized? A Retrospective Analysis of 145 Fragment Optimizations

Fragment screening using biolayer interferometry reveals ligands targeting the SHP-motif binding site of the AAA+ ATPase p97

Biosensor techniques have become increasingly important for fragment-based drug discovery during the last years. The AAA+ ATPase p97 is an essential protein with key roles in protein homeostasis and a possible target for cancer chemotherapy. Currently available p97 inhibitors address its ATPase activity and globally impair p97-mediated processes. In contrast, inhibition of cofactor binding to the N-domain by a protein-protein-interaction inhibitor would enable the selective targeting of specific p97 functions. Here, we describe a biolayer interferometry-based fragment screen targeting the N-domain of p97 and demonstrate that a region known as SHP-motif binding site can be targeted with small molecules. Guided by molecular dynamics simulations, the binding sites of selected screening hits were postulated and experimentally validated using protein- and ligand-based NMR techniques, as well as X-ray crystallography, ultimately resulting in the first structure of a small molecule in complex with the N-domain of p97. The identified fragments provide insights into how this region could be targeted and present first chemical starting points for the development of a protein-protein interaction inhibitor preventing the binding of selected cofactors to p97.

Cosolvent Simulations with Fragment-Bound Proteins Identify Hot Spots to Direct Lead Growth

In drug design, chemical groups are sequentially added to improve a weak-binding fragment into a tight-binding lead molecule. Often, the direction to make these additions is unclear, and there are numerous chemical modifications to choose. Lead development can be guided by crystal structures of the fragment-bound protein, but this alone is unable to capture structural changes like closing or opening of the binding site and any side-chain movements. Accounting for adaptation of the site requires a dynamic approach. Here, we use molecular dynamics calculations of small organic solvents with protein-fragment pairs to reveal the nearest "hot spots". These close hot spots show the direction to make appropriate additions and suggest types of chemical modifications that could improve binding affinity. Mixed-solvent molecular dynamics (MixMD) is a cosolvent simulation technique that is well established for finding binding "hot spots" in active sites and allosteric sites of proteins. We simulated 20 fragment-bound and apo forms of key pharmaceutical targets to map out hot spots for potential lead space. Furthermore, we analyzed whether the presence of a fragment facilitates the probes' binding in the lead space, a type of binding cooperativity. To the best of our knowledge, this is the first use of cosolvent MD conducted with bound inhibitors in the simulation. Our work provides a general framework to extract molecular features of binding sites to choose chemical groups for growing lead molecules. Of the 20 systems, 17 systems were well mapped by MixMD. For the three not-mapped systems, two had lead growth out into solution away from the protein, and the third had very small modifications which indicated no nearby hot spots. Therefore, our lack of mapping in three systems was appropriate given the experimental data (true-negative cases). The simulations are run for very short time scales, making this method tractable for use in the pharmaceutical industry.

Identification of isoform/domain-selective fragments from the selection of DNA-encoded dynamic library

DNA-encoded chemical library (DEL) has emerged to be a powerful ligand screening technology in drug discovery. Recently, we reported a DNA-encoded dynamic library (DEDL) approach that combines the principle of traditional dynamic combinatorial library (DCL) with DEL. DEDL has shown excellent potential in fragment-based ligand discovery with a variety of protein targets. Here, we further tested the utility of DEDL in identifying low molecular weight fragments that are selective for different isoforms or domains of the same protein family. A 10,000-member DEDL was selected against sirtuin-1, 2, and 5 (SIRT1, 2, 5) and the BD1 and BD2 domains of bromodomain 4 (BRD4), respectively. Albeit with modest potency, a series of isoform/domain-selective fragments were identified and the corresponding inhibitors were derived by fragment linking.

AlphaSpace 2.0: Representing Concave Biomolecular Surfaces Using β-Clusters

Modern rational modulator design and structure-function characterization often concentrate on concave regions of biomolecular surfaces, ranging from well-defined small-molecule binding sites to large protein-protein interaction interfaces. Here, we introduce a β-cluster as a pseudomolecular representation of fragment-centric pockets detected by AlphaSpace [J. Chem. Inf. Model. 2015, 55, 1585], a recently developed computational analysis tool for topographical mapping of biomolecular concavities. By mimicking the shape as well as atomic details of potential molecular binders, this new β-cluster representation allows direct pocket-to-ligand shape comparison and can be used to guide ligand optimization. Furthermore, we defined the β-score, the optimal Vina score of the β-cluster, as an indicator of pocket ligandability and developed an ensemble β-cluster approach, which allows one-to-one pocket mapping and comparison among aligned protein structures. We demonstrated the utility of β-cluster representation by applying the approach to a wide variety of problems including binding site detection and comparison, characterization of protein-protein interactions, and fragment-based ligand optimization. These new β-cluster functionalities have been implemented in AlphaSpace 2.0, which is freely available on the web at http://www.nyu.edu/projects/yzhang/AlphaSpace2.

Fragment Binding Pose Predictions Using Unbiased Simulations and Markov-State Models

Predicting the costructure of small-molecule ligands and their respective target proteins has been a long-standing problem in drug discovery. For weak binding compounds typically identified in fragment-based screening (FBS) campaigns, determination of the correct binding site and correct binding mode is usually done experimentally via X-ray crystallography. For many targets of pharmaceutical interest, however, establishing an X-ray system which allows for sufficient throughput to support a drug discovery project is not possible. In this case, exploration of fragment hits becomes a very laborious and consequently slow process with the generation of protein/ligand cocrystal structures as the bottleneck of the entire process. In this work, we introduce a computational method which is able to reliably predict binding sites and binding modes of fragment-like small molecules using solely the structure of the apoprotein and the ligand's chemical structure as input information. The method is based on molecular dynamics simulations and Markov-state models and can be run as a fully automated protocol requiring minimal human intervention. We describe the application of the method to a representative subset of different target classes and fragments from historical FBS efforts at Boehringer Ingelheim and discuss its potential integration into the overall fragment-based drug discovery workflow.

Fragment Based Optimization of Metabotropic Glutamate Receptor 2 (mGluR2) Positive Allosteric Modulators in the Absence of Structural Information

Metabotropic glutamate receptor 2 (mGluR2) positive allosteric modulators (PAMs) have been implicated as potential pharmacotherapy for psychiatric conditions. Screening our corporate compound deck, we identified a benzotriazole fragment (4) that was rapidly optimized to a potent and metabolically stable early lead (16). The highly lipophilic character of 16, together with its limited solubility, permeability, and high protein binding, however, did not allow reaching of the proof of concept in vivo. Since further attempts on the optimization of druglike properties were unsuccessful, the original hit 4 has been revisited and was optimized following the principles of fragment based drug discovery (FBDD). Lacking structural information on the receptor-ligand complex, we implemented a group efficiency (GE) based strategy and identified a new fragment like lead (60) with more balanced profile. Significant improvement achieved on the druglike properties nominated the compound for in vivo proof of concept studies that revealed the chemotype being a promising PAM lead targeting mGluR2 receptors.

Molecular-Simulation-Driven Fragment Screening for the Discovery of New CXCL12 Inhibitors

Fragment-based drug discovery (FBDD) has become a mainstream approach in drug design because it allows the reduction of the chemical space and screening libraries while identifying fragments with high protein-ligand efficiency interactions that can later be grown into drug-like leads. In this work, we leverage high-throughput molecular dynamics (MD) simulations to screen a library of 129 fragments for a total of 5.85 ms against the CXCL12 monomer, a chemokine involved in inflammation and diseases such as cancer. Our in silico binding assay was able to recover binding poses, affinities, and kinetics for the selected library and was able to predict 8 mM-affinity fragments with ligand efficiencies higher than 0.3. All of the fragment hits present a similar chemical structure, with a hydrophobic core and a positively charged group, and bind to either sY7 or H1S68 pockets, where they share pharmacophoric properties with experimentally resolved natural binders. This work presents a large-scale screening assay using an exclusive combination of thousands of short MD adaptive simulations analyzed with a Markov state model (MSM) framework.

Fragment-Based Discovery and Optimization of Enzyme Inhibitors by Docking of Commercial Chemical Space

Fragment-based lead discovery has emerged as a leading drug development strategy for novel therapeutic targets. Although fragment-based drug discovery benefits immensely from access to atomic-resolution information, structure-based virtual screening has rarely been used to drive fragment discovery and optimization. Here, molecular docking of 0.3 million fragments to a crystal structure of cancer target MTH1 was performed. Twenty-two predicted fragment ligands, for which analogs could be acquired commercially, were experimentally evaluated. Five fragments inhibited MTH1 with IC₅₀ values ranging from 6 to 79 μM. Structure-based optimization guided by predicted binding modes and analogs from commercial chemical libraries yielded nanomolar inhibitors. Subsequently solved crystal structures confirmed binding modes predicted by docking for three scaffolds. Structure-guided exploration of commercial chemical space using molecular docking gives access to fragment libraries that are several orders of magnitude larger than those screened experimentally and can enable efficient optimization of hits to potent leads.

Fragment library screening identifies hits that bind to the non-catalytic surface of Pseudomonas aeruginosa DsbA1

At a time when the antibiotic drug discovery pipeline has stalled, antibiotic resistance is accelerating with catastrophic implications for our ability to treat bacterial infections. Globally we face the prospect of a future when common infections can once again kill. Anti-virulence approaches that target the capacity of the bacterium to cause disease rather than the growth or survival of the bacterium itself offer a tantalizing prospect of novel antimicrobials. They may also reduce the propensity to induce resistance by removing the strong selection pressure imparted by bactericidal or bacteriostatic agents. In the human pathogen Pseudomonas aeruginosa, disulfide bond protein A (PaDsbA1) plays a central role in the oxidative folding of virulence factors and is therefore an attractive target for the development of new anti-virulence antimicrobials. Using a fragment-based approach we have identified small molecules that bind to PaDsbA1. The fragment hits show selective binding to PaDsbA1 over the DsbA protein from Escherichia coli, suggesting that developing species-specific narrow-spectrum inhibitors of DsbA enzymes may be feasible. Structures of a co-complex of PaDsbA1 with the highest affinity fragment identified in the screen reveal that the fragment binds on the non-catalytic surface of the protein at a domain interface. This biophysical and structural data represent a starting point in the development of higher affinity compounds, which will be assessed for their potential as selective PaDsbA1 inhibitors.

Fragment-to-Lead Medicinal Chemistry Publications in 2015

Fragment-based drug discovery (FBDD) is now well-established as a technology for generating new chemical leads and drugs. This Miniperspective provides a tabulated overview of the fragment-to-lead literature published in the year 2015, together with a commentary on trends observed across the FBDD field during this time. It is hoped that this tabulated summary will provide a useful point of reference for both FBDD practitioners and the wider medicinal chemistry community.

Twenty years on: the impact of fragments on drug discovery

After 20 years of sometimes quiet growth, fragment-based drug discovery (FBDD) has become mainstream. More than 30 drug candidates derived from fragments have entered the clinic, with two approved and several more in advanced trials. FBDD has been widely applied in both academia and industry, as evidenced by the large number of papers from universities, non-profit research institutions, biotechnology companies and pharmaceutical companies. Moreover, FBDD draws on a diverse range of disciplines, from biochemistry and biophysics to computational and medicinal chemistry. As the promise of FBDD strategies becomes increasingly realized, now is an opportune time to draw lessons and point the way to the future. This Review briefly discusses how to design fragment libraries, how to select screening techniques and how to make the most of information gleaned from them. It also shows how concepts from FBDD have permeated and enhanced drug discovery efforts.

The analysis of the market success of FDA approvals by probing top 100 bestselling drugs

Target-oriented drug discovery is the main research paradigm of contemporary drug discovery. In target-oriented approaches, we attempt to maximize in vitro drug potency by finding the optimal fit to the target. This can result in a higher molecular complexity, in particular, the higher molecular weight (MW) of the drugs. However, a comparison of the successful developments of pharmaceuticals with the general trends that can be observed in medicinal chemistry resulted in the conclusion that the so-called molecular obesity is an important reason for the attrition rate of drugs. When analyzing the list of top 100 drug bestsellers versus all of the FDA approvals, we discovered that on average lower-complexity (MW, ADMET score) drugs are winners of the top 100 list in terms of numbers but that, especially, up to some optimal MW value, a higher molecular complexity can pay off with higher incomes. This indicates that slim drugs are doing better but that fat drugs are bigger fishes to catch.

Fragment-based approaches to anti-HIV drug discovery: state of the art and future opportunities

INTRODUCTION

The search for additional drugs to treat HIV infection is a continuing effort due to the emergence and spread of HIV strains resistant to nearly all current drugs. The recent literature reveals that fragment-based drug design/discovery (FBDD) has become an effective alternative to conventional high-throughput screening strategies for drug discovery.

AREAS COVERED

In this critical review, the authors describe the state of the art in FBDD strategies for the discovery of anti-HIV drug-like compounds. The article focuses on fragment screening techniques, direct fragment-based design and early hit-to-lead progress.

EXPERT OPINION

Rapid progress in biophysical detection and in silico techniques has greatly aided the application of FBDD to discover candidate agents directed at a variety of anti-HIV targets. Growing evidence suggests that structural insights on key proteins in the HIV life cycle can be applied in the early phase of drug discovery campaigns, providing valuable information on the binding modes and efficiently prompting fragment hit-to-lead progression. The combination of structural insights with improved methodologies for FBDD, including the privileged fragment-based reconstruction approach, fragment hybridization based on crystallographic overlays, fragment growth exploiting dynamic combinatorial chemistry, and high-speed fragment assembly via diversity-oriented synthesis followed by in situ screening, offers the possibility of more efficient and rapid discovery of novel drugs for HIV-1 prevention or treatment. Though the use of FBDD in anti-HIV drug discovery is still in its infancy, it is anticipated that anti-HIV agents developed via fragment-based strategies will be introduced into the clinic in the future.

Fragment Binding Can Be Either More Enthalpy-Driven or Entropy-Driven: Crystal Structures and Residual Hydration Patterns Suggest Why

In lead optimization, small, enthalpically advantaged fragments have been suggested to be superior, as an entropic component will be added inevitably during late-stage optimization. Determination of thermodynamic signatures of weak-binding fragments is essential to support the decision-making process, to decide which fragment to take to further optimization. High-resolution crystal structures of six fragments binding to the S1 pocket of thrombin were determined and analyzed with respect to their thermodynamic profile. The two most potent fragments exhibiting an amidine-type scaffold are not the most enthalpic binders; instead a chloro-thiophene fragment binds more enthalpically. Two chemically very similar chloro-aromatic fragments differ strongly in their potency (430 μM vs 10 mM); their binding modes are related, but the surrounding residual water network differs. The more potent one recruits a water molecule and involves Glu192 in binding, thus succeeding in firmly capping the S1 pocket. Fragments exhibiting a rather perfect solvation pattern in their binding mode also experience the highest potency.

Fragment and Structure-Based Drug Discovery for a Class C GPCR: Discovery of the mGlu5 Negative Allosteric Modulator HTL14242 (3-Chloro-5-[6-(5-fluoropyridin-2-yl)pyrimidin-4-yl]benzonitrile)

Fragment screening of a thermostabilized mGlu5 receptor using a high-concentration radioligand binding assay enabled the identification of moderate affinity, high ligand efficiency (LE) pyrimidine hit 5. Subsequent optimization using structure-based drug discovery methods led to the selection of 25, HTL14242, as an advanced lead compound for further development. Structures of the stabilized mGlu5 receptor complexed with 25 and another molecule in the series, 14, were determined at resolutions of 2.6 and 3.1 Å, respectively.

The impact of binding thermodynamics on medicinal chemistry optimizations

Ligand binding thermodynamics has been attracted considerable interest in the past decade owing to the recognized relation between binding thermodynamic profile and the physicochemical and druglike properties of compounds. In this review, the relation between optimization strategies and ligand properties is presented based on the structural and thermodynamic analysis of ligand–protein complex formation. The control of the binding thermodynamic profile is beneficial for the balanced affinity and physicochemical properties of drug candidates, and early phase optimization gives more opportunity to this control.

Cell-based and virtual fragment screening for adrenergic α2C receptor agonists

Fragment-based drug discovery has emerged as an alternative to conventional lead identification and optimization strategies generally supported by biophysical detection techniques. Membrane targets like G protein-coupled receptors (GPCRs), however, offer challenges in lack of generic immobilization or stabilization methods for the dynamic, membrane-bound supramolecular complexes. Also modeling of different functional states of GPCRs proved to be a challenging task. Here we report a functional cell-based high concentration screening campaign for the identification of adrenergic α2C receptor agonists compared with the virtual screening of the same ligand set against an active-like homology model of the α2C receptor. The conventional calcium mobilization-based assay identified active fragments with a similar incidence to several other reported fragment screens on GPCRs. 16 out of 3071 screened fragments turned out as specific ligands of α2C, two of which were identified by virtual screening as well and several of the hits possessed surprisingly high affinity and ligand efficiency. Our results indicate that in vitro biological assays can be utilized in the fragment hit identification process for GPCR targets.

Fragment-based identification and optimization of a class of potent pyrrolo[2,1-f][1,2,4]triazine MAP4K4 inhibitors

MAP4K4 has been shown to regulate key cellular processes that are tied to disease pathogenesis. In an effort to generate small molecule MAP4K4 inhibitors, a fragment-based screen was carried out and a pyrrolotriazine fragment with excellent ligand efficiency was identified. Further modification of this fragment guided by X-ray crystal structures and molecular modeling led to the discovery of a series of promising compounds with good structural diversity and physicochemical properties. These compounds exhibited single digit nanomolar potency and compounds 35 and 44 achieved good in vivo exposure.

The importance of hydration thermodynamics in fragment-to-lead optimization

Using a computational approach to assess changes in solvation thermodynamics upon ligand binding, we investigated the effects of water molecules on the binding energetics of over 20 fragment hits and their corresponding optimized lead compounds. Binding activity and X-ray crystallographic data of published fragment-to-lead optimization studies from various therapeutically relevant targets were studied. The analysis reveals a distinct difference between the thermodynamic profile of water molecules displaced by fragment hits and those displaced by the corresponding optimized lead compounds. Specifically, fragment hits tend to displace water molecules with notably unfavorable excess entropies-configurationally constrained water molecules-relative to those displaced by the newly added moieties of the lead compound during the course of fragment-to-lead optimization. Herein we describe the details of this analysis with the goal of providing practical guidelines for exploiting thermodynamic signatures of binding site water molecules in the context of fragment-to-lead optimization.

The essential roles of chemistry in high-throughput screening triage

It is increasingly clear that academic high-throughput screening (HTS) and virtual HTS triage suffers from a lack of scientists trained in the art and science of early drug discovery chemistry. Many recent publications report the discovery of compounds by screening that are most likely artifacts or promiscuous bioactive compounds, and these results are not placed into the context of previous studies. For HTS to be most successful, it is our contention that there must exist an early partnership between biologists and medicinal chemists. Their combined skill sets are necessary to design robust assays and efficient workflows that will weed out assay artifacts, false positives, promiscuous bioactive compounds and intractable screening hits, efforts that ultimately give projects a better chance at identifying truly useful chemical matter. Expertise in medicinal chemistry, cheminformatics and purification sciences (analytical chemistry) can enhance the post-HTS triage process by quickly removing these problematic chemotypes from consideration, while simultaneously prioritizing the more promising chemical matter for follow-up testing. It is only when biologists and chemists collaborate effectively that HTS can manifest its full promise.

Virtual fragment screening on GPCRs: a case study on dopamine D3 and histamine H4 receptors

Prospective structure based virtual fragment screening methodologies on two GPCR targets namely the dopamine D3 and the histamine H4 receptors with a library of 12,905 fragments were evaluated. Fragments were docked to the X-ray structure and the homology model of the D3 and H4 receptors, respectively. Representative receptor conformations for ensemble docking were obtained from molecular dynamics trajectories. In vitro confirmed hit rates ranged from 16% to 32%. Hits had high ligand efficiency (LE) values in the range of 0.31-0.74 and also acceptable lipophilic efficiency. The X-ray structure, the homology model and structural ensembles were all found suitable for docking based virtual screening of fragments against these GPCRs. However, there was little overlap among different hit sets and methodologies were thus complementary to each other.

Efficient search of chemical space: navigating from fragments to structurally diverse chemotypes

We introduce a novel strategy to sample bioactive chemical space, which follows-up on hits from fragment campaigns without the need for a crystal structure. Our results strongly suggest that screening a few hundred or thousand fragments can substantially improve the selection of small-molecule screening subsets. By combining fragment-based screening with virtual fragment linking and HTS fingerprints, we have developed an effective strategy not only to expand from low-affinity hits to potent compounds but also to hop in chemical space to substantially novel chemotypes. In benchmark calculations, our approach accessed subsets of compounds that were substantially enriched in chemically diverse hit compounds for various activity classes. Overall, half of the hits in the screening collection were found by screening only 10% of the library. Furthermore, a prospective application led to the discovery of two structurally novel histone deacetylase 4 inhibitors.

Setting expectations in molecular optimizations: Strengths and limitations of commonly used composite parameters

Over the past 15years there have been extensive efforts to understand and reduce the high attrition rates of drug candidates with an increased focus on physicochemical properties. The fruits of this labor have been the generation of numerous efficiency indices, metric-based rules and visualization tools to help guide medicinal chemists in the design of new compounds with more favorable properties. This deluge of information may have had the unintended consequence of further obfuscating molecular optimizations by the inability of these scoring functions, rules and guides to reach a consensus on when a particular transformation is identified as beneficial. In this manuscript, several composite parameters, or efficiency indices, are examined utilizing theoretical and experimental matched molecular pair analyses in order to understand the basis for how each will perform under varying scenarios of molecular optimizations. In contrast to empirically derived composite parameters based on heavy atom count, lipophilic efficiency (LipE) sets consistent expectations regardless of molecular weight or relative potency and can be used to generate consistent expectations for any matched molecular pair.

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

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