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

Targeting the nucleic acid oxidative damage repair enzyme MTH1: a promising therapeutic option

The accumulation of reactive oxygen species (ROS) plays a pivotal role in the development of various diseases, including cancer. Elevated ROS levels cause oxidative stress, resulting in detrimental effects on organisms and enabling tumors to develop adaptive responses. Targeting these enhanced oxidative stress protection mechanisms could offer therapeutic benefits with high specificity, as normal cells exhibit lower dependency on these pathways. MTH1 (mutT homolog 1), a homolog of Escherichia coli's MutT, is crucial in this context. It sanitizes the nucleotide pool, preventing incorporation of oxidized nucleotides, thus safeguarding DNA integrity. This study explores MTH1's potential as a therapeutic target, particularly in cancer treatment, providing insights into its structure, function, and role in disease progression.

Structure-based discovery of nonopioid analgesics acting through the α2A-adrenergic receptor

Because nonopioid analgesics are much sought after, we computationally docked more than 301 million virtual molecules against a validated pain target, the α2A-adrenergic receptor (α2AAR), seeking new α2AAR agonists chemotypes that lack the sedation conferred by known α2AAR drugs, such as dexmedetomidine. We identified 17 ligands with potencies as low as 12 nanomolar, many with partial agonism and preferential Gi and Go signaling. Experimental structures of α2AAR complexed with two of these agonists confirmed the docking predictions and templated further optimization. Several compounds, including the initial docking hit '9087 [mean effective concentration (EC50) of 52 nanomolar] and two analogs, '7075 and PS75 (EC50 4.1 and 4.8 nanomolar), exerted on-target analgesic activity in multiple in vivo pain models without sedation. These newly discovered agonists are interesting as therapeutic leads that lack the liabilities of opioids and the sedation of dexmedetomidine.

Enhancing Repair of Oxidative DNA Damage with Small-Molecule Activators of MTH1

Impaired DNA repair activity has been shown to greatly increase rates of cancer clinically. It has been hypothesized that upregulating repair activity in susceptible individuals may be a useful strategy for inhibiting tumorigenesis. Here, we report that selected tyrosine kinase (TK) inhibitors including nilotinib, employed clinically in the treatment of chronic myeloid leukemia, are activators of the repair enzyme Human MutT Homolog 1 (MTH1). MTH1 cleanses the oxidatively damaged cellular nucleotide pool by hydrolyzing the oxidized nucleotide 8-oxo-2'-deoxyguanosine (8-oxo-dG)TP, which is a highly mutagenic lesion when incorporated into DNA. Structural optimization of analogues of TK inhibitors resulted in compounds such as SU0448, which induces 1000 ± 100% activation of MTH1 at 10 μM and 410 ± 60% at 5 μM. The compounds are found to increase the activity of the endogenous enzyme, and at least one (SU0448) decreases levels of 8-oxo-dG in cellular DNA. The results suggest the possibility of using MTH1 activators to decrease the frequency of mutagenic nucleotides entering DNA, which may be a promising strategy to suppress tumorigenesis in individuals with elevated cancer risks.

Ultralarge Virtual Screening Identifies SARS-CoV-2 Main Protease Inhibitors with Broad-Spectrum Activity against Coronaviruses

Drugs targeting SARS-CoV-2 could have saved millions of lives during the COVID-19 pandemic, and it is now crucial to develop inhibitors of coronavirus replication in preparation for future outbreaks. We explored two virtual screening strategies to find inhibitors of the SARS-CoV-2 main protease in ultralarge chemical libraries. First, structure-based docking was used to screen a diverse library of 235 million virtual compounds against the active site. One hundred top-ranked compounds were tested in binding and enzymatic assays. Second, a fragment discovered by crystallographic screening was optimized guided by docking of millions of elaborated molecules and experimental testing of 93 compounds. Three inhibitors were identified in the first library screen, and five of the selected fragment elaborations showed inhibitory effects. Crystal structures of target-inhibitor complexes confirmed docking predictions and guided hit-to-lead optimization, resulting in a noncovalent main protease inhibitor with nanomolar affinity, a promising in vitro pharmacokinetic profile, and broad-spectrum antiviral effect in infected cells.

Fragment-to-lead tailored in silico design

Fragment-based drug discovery (FBDD) emerged as a disruptive technology and became established during the last two decades. Its rationality and low entry costs make it appealing, and the numerous examples of approved drugs discovered through FBDD validate the approach. However, FBDD still faces numerous challenges. Perhaps the most important one is the transformation of the initial fragment hits into viable leads. Fragment-to-lead (F2L) optimization is resource-intensive and is therefore limited in the possibilities that can be actively pursued. In silico strategies play an important role in F2L, as they can perform a deeper exploration of chemical space, prioritize molecules with high probabilities of being active and generate non-obvious ideas. Here we provide a critical overview of current in silico strategies in F2L optimization and highlight their remarkable impact. While very effective, most solutions are target- or fragment- specific. We propose that fully integrated in silico strategies, capable of automatically and systematically exploring the fast-growing available chemical space can have a significant impact on accelerating the release of fragment originated drugs.

Specific Inhibitor of Placental Alkaline Phosphatase Isolated from a DNA-Encoded Chemical Library Targets Tumor of the Female Reproductive Tract

Placental alkaline phosphatase (PLAP) is an abundant surface antigen in the malignancies of the female reproductive tract. Nevertheless, the discovery of PLAP-specific small organic ligands for targeting applications has been hindered by ligand cross-reactivity with the ubiquitous tissue non-specific alkaline phosphatase (TNAP). In this study, we used DNA-encoded chemical libraries to discover a potent (IC₅₀ = 32 nM) and selective PLAP inhibitor, with no detectable inhibition of TNAP activity. Subsequently, the PLAP ligand was conjugated to fluorescein; it specifically bound to PLAP-positive tumors in vitro and targeted cervical cancer in vivo in a mouse model of the disease. Ultimately, the fluorescent derivative of the PLAP inhibitor functioned as a bispecific engager redirecting the killing of chimeric antigen receptor-T cells specific to fluorescein on PLAP-positive tumor cells.

Fragment-based in silico design of SARS-CoV-2 main protease inhibitors

3CLpro is essential for SARS-CoV-2 replication and infection; its inhibition using small molecules is a potential therapeutic strategy. In this study, a comprehensive crystallography-guided fragment-based drug discovery approach was employed to design new inhibitors for SARS-CoV-2 3CLpro. All small molecules co-crystallized with SARS-CoV-2 3CLpro with structures deposited in the Protein Data Bank were used as inputs. Fragments sitting in the binding pocket (87) were grouped into eight geographical types. They were interactively coupled using various synthetically reasonable linkers to generate larger molecules with divalent binding modes taking advantage of two different fragments' interactions. In total, 1,251 compounds were proposed, and 7,158 stereoisomers were screened using Glide (standard precision and extra precision), AutoDock Vina, and Prime MMGBSA. The top 22 hits having conformations approaching the linear combination of their constituent fragments were selected for MD simulation on Desmond. MD simulation suggested 15 of these did adopt conformations very close to their constituent pieces with far higher binding affinity than either constituent domain alone. These structures could provide a starting point for the further design of SARS-CoV-2 3CLpro inhibitors with improved binding, and structures are provided.

Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence

Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.

Decision Making in Structure-Based Drug Discovery: Visual Inspection of Docking Results

Molecular docking is a computational method widely used in drug discovery. Due to the inherent inaccuracies of molecular docking, visual inspection of binding modes is a crucial routine in the decision making process of computational medicinal chemists. Despite its apparent importance for medicinal chemistry projects, guidelines for the visual docking pose assessment have been hardly discussed in the literature. Here, we review the medicinal chemistry literature with the aim of identifying consistent principles for visual inspection, highlighting cases of its successful application, and discussing its limitations. In this context, we conducted a survey reaching experts in both academia and the pharmaceutical industry, which also included a challenge to distinguish native from incorrect poses. We were able to collect 93 expert opinions that offer valuable insights into visually supported decision-making processes. This perspective shall motivate discussions among experienced computational medicinal chemists and guide young scientists new to the field to stratify their compounds.

Targeting human MutT homolog 1 (MTH1) for cancer eradication: current progress and perspectives

Since accelerated metabolism produces much higher levels of reactive oxygen species (ROS) in cancer cells compared to ROS levels found in normal cells, human MutT homolog 1 (MTH1), which sanitizes oxidized nucleotide pools, was recently demonstrated to be crucial for the survival of cancer cells, but not required for the proliferation of normal cells. Therefore, dozens of MTH1 inhibitors have been developed with the aim of suppressing cancer growth by accumulating oxidative damage in cancer cells. While several inhibitors were indeed confirmed to be effective, some inhibitors failed to kill cancer cells, complicating MTH1 as a viable target for cancer eradication. In this review, we summarize the current status of developing MTH1 inhibitors as drug candidates, classify the MTH1 inhibitors based on their structures, and offer our perspectives toward the therapeutic potential against cancer through the targeting of MTH1.

In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery

Fragment-based drug (or lead) discovery (FBDD or FBLD) has developed in the last two decades to become a successful key technology in the pharmaceutical industry for early stage drug discovery and development. The FBDD strategy consists of screening low molecular weight compounds against macromolecular targets (usually proteins) of clinical relevance. These small molecular fragments can bind at one or more sites on the target and act as starting points for the development of lead compounds. In developing the fragments attractive features that can translate into compounds with favorable physical, pharmacokinetics and toxicity (ADMET-absorption, distribution, metabolism, excretion, and toxicity) properties can be integrated. Structure-enabled fragment screening campaigns use a combination of screening by a range of biophysical techniques, such as differential scanning fluorimetry, surface plasmon resonance, and thermophoresis, followed by structural characterization of fragment binding using NMR or X-ray crystallography. Structural characterization is also used in subsequent analysis for growing fragments of selected screening hits. The latest iteration of the FBDD workflow employs a high-throughput methodology of massively parallel screening by X-ray crystallography of individually soaked fragments. In this review we will outline the FBDD strategies and explore a variety of in silico approaches to support the follow-up fragment-to-lead optimization of either: growing, linking, and merging. These fragment expansion strategies include hot spot analysis, druggability prediction, SAR (structure-activity relationships) by catalog methods, application of machine learning/deep learning models for virtual screening and several de novo design methods for proposing synthesizable new compounds. Finally, we will highlight recent case studies in fragment-based drug discovery where in silico methods have successfully contributed to the development of lead compounds.

Dual Inhibitors of 8-Oxoguanine Surveillance by OGG1 and NUDT1

Oxidative damage in DNA is one of the primary sources of mutations in the cell. The activities of repair enzymes 8-oxoguanine DNA glycosylase (OGG1) and human MutT Homologue 1 (NUDT1 or MTH1), which work together to ameliorate this damage, are closely linked to mutagenesis, genotoxicity, cancer, and inflammation. Here we have undertaken the development of small-molecule dual inhibitors of the two enzymes as tools to test the relationships between these pathways and disease. The compounds preserve key structural elements of known inhibitors of the two enzymes, and they were synthesized and assayed with recently developed luminescence assays of the enzymes. Further structural refinement of initial lead molecules yielded compound 5 (SU0383) with IC50(NUDT1) = 0.034 μM and IC50(OGG1) = 0.49 μM. The compound SU0383 displayed low toxicity in two human cell lines at 10 μM. Experiments confirm the ability of SU0383 to increase sensitivity of tumor cells to oxidative stress. Dual inhibitors of these two enzymes are expected to be useful in testing multiple hypotheses regarding the roles of 8-oxo-dG in multiple disease states.

Key Topics in Molecular Docking for Drug Design

Molecular docking has been widely employed as a fast and inexpensive technique in the past decades, both in academic and industrial settings. Although this discipline has now had enough time to consolidate, many aspects remain challenging and there is still not a straightforward and accurate route to readily pinpoint true ligands among a set of molecules, nor to identify with precision the correct ligand conformation within the binding pocket of a given target molecule. Nevertheless, new approaches continue to be developed and the volume of published works grows at a rapid pace. In this review, we present an overview of the method and attempt to summarise recent developments regarding four main aspects of molecular docking approaches: (i) the available benchmarking sets, highlighting their advantages and caveats, (ii) the advances in consensus methods, (iii) recent algorithms and applications using fragment-based approaches, and (iv) the use of machine learning algorithms in molecular docking. These recent developments incrementally contribute to an increase in accuracy and are expected, given time, and together with advances in computing power and hardware capability, to eventually accomplish the full potential of this area.

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

Binding mode information improves fragment docking

Docking is commonly used in drug discovery to predict how ligand binds to protein target. Best programs are generally able to generate a correct solution, yet often fail to identify it. In the case of drug-like molecules, the correct and incorrect poses can be sorted by similarity to the crystallographic structure of the protein in complex with reference ligands. Fragments are particularly sensitive to scoring problems because they are weak ligands which form few interactions with protein. In the present study, we assessed the utility of binding mode information in fragment pose prediction. We compared three approaches: interaction fingerprints, 3D-matching of interaction patterns and 3D-matching of shapes. We prepared a test set composed of high-quality structures of the Protein Data Bank. We generated and evaluated the docking poses of 586 fragment/protein complexes. We observed that the best approach is twice as accurate as the native scoring function, and that post-processing is less effective for smaller fragments. Interestingly, fragments and drug-like molecules both proved to be useful references. In the discussion, we suggest the best conditions for a successful pose prediction with the three approaches.

Mechanisms of MTH1 inhibition-induced DNA strand breaks: The slippery slope from the oxidized nucleotide pool to genotoxic damage

Unlike normal tissues, tumor cells possess a propensity for genomic instability, resulting from elevated oxidant levels produced by oncogenic signaling and aberrant cellular metabolism. Thus, targeting mechanisms that protect cancer cells from the tumor-inhibitory consequences of their redox imbalance and spontaneous DNA-damaging events is expected to have broad-spectrum efficacy and a high therapeutic index. One critical mechanism for tumor cell protection from oxidant stress is the hydrolysis of oxidized nucleotides. Human MutT homolog 1 (MTH1), the mammalian nudix (nucleoside diphosphate X) pyrophosphatase (NUDT1), protects tumor cells from oxidative stress-induced genomic DNA damage by cleansing the nucleotide pool of oxidized purine nucleotides. Depletion or pharmacologic inhibition of MTH1 results in genomic DNA strand breaks in many cancer cells. However, the mechanisms underlying how oxidized nucleotides, thought mainly to be mutagenic rather than genotoxic, induce DNA strand breaks are largely unknown. Given the recent therapeutic interest in targeting MTH1, a better understanding of such mechanisms is crucial to its successful translation into the clinic and in identifying the molecular contexts under which its inhibition is likely to be beneficial. Here we provide a comprehensive perspective on MTH1 function and its importance in protecting genome integrity, in the context of tumor-associated oxidative stress and the mechanisms that likely lead to irreparable DNA strand breaks as a result of MTH1 inhibition.

Fragment-to-Lead Medicinal Chemistry Publications in 2017

This Miniperspective is the third in a series reviewing fragment-to-lead publications from a given year. Following our reviews for 2015 and 2016, this Miniperspective provides tabulated summaries of relevant articles published in 2017 along with some general observations. In addition, we discuss insights obtained from analysis of the combined data set of 85 examples from all three years of publications.

Fragment-Based Drug Discovery: Advancing Fragments in the Absence of Crystal Structures

Fragment-based drug discovery typically requires an interplay between screening methods, structural methods, and medicinal chemistry. X-ray crystallography is generally the method of choice to obtain three-dimensional structures of the bound ligand/protein complex, but this can sometimes be difficult, particularly for early, low-affinity fragment hits. In this Perspective, we discuss strategies to advance and evolve fragments in the absence of crystal structures of protein-fragment complexes, although the structure of the unliganded protein may be available. The strategies can involve other structural techniques, such as NMR spectroscopy, molecular modeling, or a variety of chemical approaches. Often, these strategies are aimed at guiding evolution of initial fragment hits to a stage where crystal structures can be obtained for further structure-based optimization.

Synthesis, crystal structure and cytotoxic activity of novel 5-methyl-4-thiopyrimidine derivatives

This article presents the synthesis of three new 4-thiopyrimidine derivatives obtained from ethyl 4-methyl-2-phenyl-6-sulfanylpyrimidine-5-carboxylate as the starting material, namely, ethyl 4-[(4-chlorobenzyl)sulfanyl]-6-methyl-2-phenylpyrimidine-5-carboxylate, C₂₁H₁₉ClN₂O₂S, (2), {4-[(4-chlorobenzyl)sulfanyl]-6-methyl-2-phenylpyrimidin-5-yl}methanol, C₁₉H₁₇ClN₂OS, (3), and 4-[(4-chlorobenzyl)sulfanyl]-5,6-dimethyl-2-phenylpyrimidine, C₁₉H₁₇ClN₂S, (4), which vary in the substituent at the 5-position of the pyrimidine ring. The compounds were characterized by ¹H NMR, ¹³C NMR, IR and mass spectroscopies, and also elemental analysis. The molecular structures were further studied by single-crystal X-ray diffraction. Compound (2) crystallizes in the space group P-1 with one molecule in the asymmetric unit, whereas compounds (3) and (4) crystallize in the space group P2₁/c with two and one molecule, respectively, in their asymmetric units. The conformation of each molecule is best defined by the dihedral angles formed between the pyrimidine ring and the planes of the two aryl substituents attached at the 2- and 4-positions. The only structural difference between the three compounds is the substituent at the 5-position of the pyrimidine ring, but they present significantly different features in the hydrogen-bond interactions. Compound (2) displays a one-dimensional chain formed by hydrogen bonds and the chains are further extended into a two-dimensional network. Molecules of (3) and (4) generate one-dimensional chains formed through intermolecular interactions. The study examines the cytotoxicity of compounds (3) and (4) against Human umbilical vein endothelial cells (HUVEC) and HeLa, K562 and CFPAC cancer cell lines. The presence of the hydroxymethyl and methyl groups in (3) and (4), respectively, offers an interesting new insight into the structures and behaviour of these derivatives. Compound (4) was found to be nontoxic against CFPAC and HUVEC; however, it shows weak activity against the HeLa and K563 cell lines. The presence of a hydroxy group in (3) significantly increases its cytotoxicity towards both, i.e. the cancer (HeLa, K562 and CFPAC) and normal (HUVEC) cell lines.

The influence of residue in the position of 116 on the inhibitory potency of TH588 for MTH1

As one of the first-in-class inhibitor, TH588 was found to be efficient in the suppression of MutT homolog1 (MTH1). A recent work shows that the inhibitory potency of TH588 against human MTH1 (hsMTH1) is approximately 20-fold over that of mouse MTH1 (mmMTH1) and identifies residue in position 116 in MTH1 has an important contribution to TH588 affinity. But the effect of residue Leu or Met in position 116 on the binding affinity remains unclear. In this study, molecular dynamics (MD) simulations and free energy calculations were used to elucidate the mechanism about the effect of residue 116 to the different inhibitory potency of TH588 against MTH1. The binding free energy of TH588 in M116 complexes predicated by the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) is much lower than that in L116 complexes, which is consistent with the experiment results. The analysis of the individual energy terms suggests that the non-polar interactions are important for distinguishing the binding of TH588. The MD results show that the Leu116 disrupts the interactions between Asn33 and TH588, thus induces the conformational changes of Asn33 as well as TH588. The altered interactions between TH588 and mmMTH1 change the flexibility of TH588, which could induce the remarkable conformational fluctuation of mmMTH1. The conformations of the two loops covering the binding pocket have obvious influence on the opening or closure of the active site. The more open binding site may explain the lower inhibitor potency of TH588 against mmMTH1 than hsMTH1. Our results provide mechanistic insight into the effect of different residue Leu or Met in position 116 on the binding affinity of TH588 for MTH1, which is expected to contribute to the further rational design of more potent inhibitors.