AncPhore: A versatile tool for anchor pharmacophore steered drug discovery with applications in discovery of new inhibitors targeting metallo-β-lactamases and indoleamine/tryptophan 2,3-dioxygenases

Knowledge-guided diffusion model for 3D ligand-pharmacophore mapping

Pharmacophores are abstractions of essential chemical interaction patterns, holding an irreplaceable position in drug discovery. Despite the availability of many pharmacophore tools, the adoption of deep learning for pharmacophore-guided drug discovery remains relatively rare. We herein propose a knowledge-guided diffusion framework for 'on-the-fly' 3D ligand-pharmacophore mapping, named DiffPhore. It leverages ligand-pharmacophore matching knowledge to guide ligand conformation generation, meanwhile utilizing calibrated sampling to mitigate the exposure bias of the iterative conformation search process. By training on two self-established datasets of 3D ligand-pharmacophore pairs, DiffPhore achieves state-of-the-art performance in predicting ligand binding conformations, surpassing traditional pharmacophore tools and several advanced docking methods. It also manifests superior virtual screening power for lead discovery and target fishing. Using DiffPhore, we successfully identify structurally distinct inhibitors for human glutaminyl cyclases, and their binding modes are further validated through co-crystallographic analysis. We believe this work will advance the AI-enabled pharmacophore-guided drug discovery techniques.

Computational study on the mechanism of small molecules inhibiting NLRP3 with ensemble docking and molecular dynamic simulations

NLRP3 (Nucleotide-binding oligomerization domain, LRR and pyrin domain-containing protein 3) is a pivotal regulator of inflammation, with strong implications in gout, neurodegenerative diseases, and various inflammatory conditions. Consequently, the exploration of NLRP3 inhibitors is of great significance for the treatment of diseases. MCC950, NP3-146, compound (3), and YQ128 are four highly bioactive NLRP3 inhibitors that show great potential; however, their mechanism of action is currently limited to targeting the ATP binding region (NACHT site) of the NLRP3 protein. To gain deeper insights into the defining features of NLRP3 inhibitors and to develop more potent inhibitors, it is imperative to elucidate the interaction mechanism between NLRP3 and these inhibitors. In this study, we employ a comprehensive computational approach to investigate the binding mechanism between NLRP3 and representative inhibitors. Utilizing the molecular mechanics/generalized Born surface area (MM/GBSA) method, we calculate the binding free energy and pinpoint the key residues involved in the binding of the four inhibitors to NLRP3. The decomposition of binding free energy by the MM/GBSA method reveals that the residues Val71, Arg195, Ile255, Phe419, Arg422, and Met505, situated around the binding pocket, play a crucial role in conferring the high bioactivity of NLRP3 inhibitors. Furthermore, pharmacophore analysis of the four NLRP3 complexes indicates that the primary interaction between the inhibitors and NLRP3 was mainly hydrophobic interaction. Our study provides a profound understanding of the interaction mechanism between NLRP3 and its inhibitors, identifies the key residues involved, and provides theoretical guidance for the design of more efficient NLRP3 inhibitors.

CovalentInDB 2.0: an updated comprehensive database for structure-based and ligand-based covalent inhibitor design and screening

The rational design of targeted covalent inhibitors (TCIs) has emerged as a powerful strategy in drug discovery, known for its ability to achieve strong binding affinity and prolonged target engagement. However, the development of covalent drugs is often challenged by the need to optimize both covalent warhead and non-covalent interactions, alongside the limitations of existing compound libraries. To address these challenges, we present CovalentInDB 2.0, an updated online database designed to support covalent drug discovery. This updated version includes 8303 inhibitors and 368 targets, supplemented by 3445 newly added cocrystal structures, providing detailed analyses of non-covalent interactions. Furthermore, we have employed an AI-based model to profile the ligandability of 144 864 cysteines across the human proteome. CovalentInDB 2.0 also features the largest covalent virtual screening library with 2 030 192 commercially available compounds and a natural product library with 105 901 molecules, crucial for covalent drug screening and discovery. To enhance the utility of these compounds, we performed structural similarity analysis and drug-likeness predictions. Additionally, a new user data upload feature enables efficient data contribution and continuous updates. CovalentInDB 2.0 is freely accessible at http://cadd.zju.edu.cn/cidb/.

Elucidation of critical chemical moieties of metallo-β-lactamase inhibitors and prioritisation of target metallo-β-lactamases

The urgent demand for effective countermeasures against metallo-β-lactamases (MBLs) necessitates development of novel metallo-β-lactamase inhibitors (MBLIs). This study is dedicated to identifying critical chemical moieties within previously developed MBLIs, and critical MBLs should serve as the target in MBLI evaluations. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), a systematic literature analysis was conducted, and the NCBI RefSeq genome database was exploited to access the abundance profile and taxonomic distribution of MBLs and their variant types. Through the implementation of two distinct systematic approaches, we elucidated critical chemical moieties of MBLIs, providing pivotal information for rational drug design. We also prioritised MBLs and their variant types, highlighting the imperative need for comprehensive testing to ensure the potency and efficacy of the newly developed MBLIs. This approach contributes valuable information to advance the field of antimicrobial drug discovery.

Discovering New Metallo-Deubiquitinase CSN5 Inhibitors by a Non-Catalytic Activity Assay Platform

COP9 signalosome catalytic subunit CSN5 plays a key role in tumorigenesis and tumor immunity, showing potential as an anticancer target. Currently, only a few CSN5 inhibitors have been reported, at least partially, due to the challenges in establishing assays for CSN5 deubiquitinase activity. Here, we present the establishment and validation of a simple and reliable non-catalytic activity assay platform for identifying CSN5 inhibitors utilizing a new fluorescent probe, CFP-1, that exhibits enhanced fluorescence and fluorescence polarization features upon binding to CSN5. By using this platform, we identified 2-aminothiazole-4-carboxylic acids as new CSN5 inhibitors, which inhibited CSN5 but slightly downregulated PD-L1 in cancer cells. Furthermore, through the integration of deep learning-enabled virtual screening, we discovered that shikonins are nanomolar CSN5 inhibitors, which can upregulate PD-L1 in HCT116 cells. The binding modes of these structurally distinct inhibitors with CSN5 were explored by using microsecond-scale molecular dynamics simulations and tryptophan quenching assays.

A computational odyssey: uncovering classical β-lactamase inhibitors in dry fruits

In the antibacterial arsenal, β-lactams have held a prominent position, but increasing resistance due to unauthorized use and genetic factors requires new strategies. Combining β-lactamase inhibitors with broad-spectrum β-lactams proves effective in combating this resistance. ESBL producers demand new inhibitors, leading to the exploration of plant-derived secondary metabolites for potent β-lactam antibiotics or alternative inhibitors. Using virtual screening, molecular docking, ADMET analysis, and molecular dynamic simulation, this study actively analyzed the inhibitory activity of figs, cashews, walnuts, and peanuts against SHV-1, NDM-1, KPC-2, and OXA-48 β-lactamases. Using AutoDock Vina, the docking affinities of various compounds for target enzymes were initially screened, revealing 12 bioactive compounds with higher affinities for the target enzymes compared to Avibactam and Tazobactam. Top-scoring metabolites, including Oleanolic acid, Protocatechuic acid, and Tannin, were subjected to MD simulation studies to further analyze the stability of the docked complexes using WebGro. The simulation coordinates, in terms of RMSD, RMSF, SASA, Rg, and hydrogen bonds formed, showed that these phytocompounds are stable enough to retain in the active sites at various orientations. The PCA and FEL analysis also showed the stability of the dynamic motion of Cα residues of phytochemical-bound enzymes. The pharmacokinetic analysis of the top phytochemicals was performed to analyze their bioavailability and toxicity. This study provides new insights into the therapeutic potential of phytochemicals of selected dry fruits and contributes to future experimental studies to identify βL inhibitors from plants.Communicated by Ramaswamy H. Sarma.

On the hunt for metalloenzyme inhibitors: Investigating the presence of metal-coordinating compounds in screening libraries and chemical spaces

Metalloenzymes play vital roles in various biological processes, requiring the search for inhibitors to develop treatment options for diverse diseases. While compound library screening is a conventional approach, the exploration of virtual chemical spaces housing trillions of compounds has emerged as an alternative strategy. In this study, we investigated the suitability of selected screening libraries and chemical spaces for discovering inhibitors of metalloenzymes featuring common ions (Mg2+, Mn2+, and Zn2+). First, metal-coordinating groups from ligands interacting with ions in the Protein Data Bank were extracted. Subsequently, the prevalence of these groups in two focused screening libraries (Life Chemicals' chelator library, comprising 6,428 compounds, and Otava's chelator fragment library, with 1,784 fragments) as well as two chemical spaces (GalaXi and REAL space, containing billions of virtual products) was investigated. In total, 1,223 metal-coordinating groups were identified, with about a quarter of these groups found within the examined libraries and spaces. Our results indicate that these can serve as valuable starting points for drug discovery targeting metalloenzymes. In addition, this study suggests ways to improve libraries and spaces for better success in finding potential inhibitors for metalloenzymes.

Worldwide trend discovery of structural and functional relationship of metallo-β-lactamase for structure-based drug design: A bibliometric evaluation and patent analysis

Metallo-β-lactamase (MBL) is an enzyme produced by clinically important bacteria that can inactivate many commonly used antibiotics, making them a significant concern in treating bacterial infections and the risk of having high antibiotic resistance issues among the community. This review presents a bibliometric and patent analysis of MBL worldwide research trend based on the Scopus and World Intellectual Property Organization databases in 2013-2022. Based on the keywords related to MBL in the article title, abstract, and keywords, 592 research articles were retrieved for further analysis using various tools such as Microsoft Excel to determine the frequency analysis, VOSviewer for bibliometric networks visualization, and Harzing's Publish or Perish for citation metrics analysis. Standard bibliometric parameters were analysed to evaluate the field's research trend, such as the growth of publications, topographical distribution, top subject area, most relevant journal, top cited documents, most relevant authors, and keyword trend analysis. Within 10 years, MBL discovery has shown a steady and continuous growth of interest among the community of researchers. United States of America, China, and the United Kingdom are the top 3 countries contribute high productivity to the field. The patent analysis also shows several impactful filed patents, indicating the significance of development research on the structural and functional relationship of MBL for an effective structure-based drug design (SBDD). Developing new MBL inhibitors using SBDD could help address the research gap and provide new successful therapeutic options for treating MBL-producing bacterial infections.

Combination of QSAR Modeling and Hybrid-Based Consensus Scoring to Identify Dual-Targeting Inhibitors of PLK1 and p38γ

Polo-like kinase 1 (PLK1) and p38γ mitogen-activated protein kinase (p38γ) play important roles in cancer pathogenesis by controlling cell cycle progression and are therefore attractive cancer targets. The design of multitarget inhibitors may offer synergistic inhibition of distinct targets and reduce the risk of drug-drug interactions to improve the balance between therapeutic efficacy and safety. We combined deep-learning-based quantitative structure-activity relationship (QSAR) modeling and hybrid-based consensus scoring to screen for inhibitors with potential activity against the targeted proteins. Using this combination strategy, we identified a potent PLK1 inhibitor (compound 4) that inhibited PLK1 activity and liver cancer cell growth in the nanomolar range. Next, we deployed both our QSAR models for PLK1 and p38γ on the Enamine compound library to identify dual-targeting inhibitors against PLK1 and p38γ. Likewise, the identified hits were subsequently subjected to hybrid-based consensus scoring. Using this method, we identified a promising compound (compound 14) that could inhibit both PLK1 and p38γ activities. At nanomolar concentrations, compound 14 inhibited the growth of human hepatocellular carcinoma and hepatoblastoma cells in vitro. This study demonstrates the combined screening strategy to identify novel potential inhibitors for existing targets.

Discovery of 2-Aminothiazole-4-carboxylic Acids as Broad-Spectrum Metallo-β-lactamase Inhibitors by Mimicking Carbapenem Hydrolysate Binding

Metallo-β-lactamases (MBLs) are zinc-dependent enzymes capable of hydrolyzing all bicyclic β-lactam antibiotics, posing a great threat to public health. However, there are currently no clinically approved MBL inhibitors. Despite variations in their active sites, MBLs share a common catalytic mechanism with carbapenems, forming similar reaction species and hydrolysates. We here report the development of 2-aminothiazole-4-carboxylic acids (AtCs) as broad-spectrum MBL inhibitors by mimicking the anchor pharmacophore features of carbapenem hydrolysate binding. Several AtCs manifested potent activity against B1, B2, and B3 MBLs. Crystallographic analyses revealed a common binding mode of AtCs with B1, B2, and B3 MBLs, resembling binding observed in the MBL-carbapenem product complexes. AtCs restored Meropenem activity against MBL-producing isolates. In the murine sepsis model, AtCs exhibited favorable synergistic efficacy with Meropenem, along with acceptable pharmacokinetics and safety profiles. This work offers promising lead compounds and a structural basis for the development of potential drug candidates to combat MBL-mediated antimicrobial resistance.

Metallo-β-lactamase-mediated antimicrobial resistance and progress in inhibitor discovery

Resistance to β-lactam antibiotics is rapidly growing, substantially due to the spread of serine-β-lactamases (SBLs) and metallo-β-lactamases (MBLs), which efficiently catalyse β-lactam hydrolysis. Combinations of a β-lactam antibiotic with an SBL inhibitor have been clinically successful; however, no MBL inhibitors have been developed for clinical use. MBLs are a worrying resistance vector because they catalyse hydrolysis of all β-lactam antibiotic classes, except the monobactams, and they are being disseminated across many bacterial species worldwide. Here we review the classification, structures, substrate profiles, and inhibition mechanisms of MBLs, highlighting current clinical problems due to MBL-mediated resistance and progress in understanding and combating MBL-mediated resistance.

Metal binding pharmacophore click-derived discovery of new broad-spectrum metallo-β-lactamase inhibitors

The emergence of metallo-β-lactamases (MBLs) confers resistance to nearly all the β-lactam antibiotics, including carbapenems. Currently, there is a lack of clinically useful MBL inhibitors, making it crucial to discover new inhibitor chemotypes that can potently target multiple clinically relevant MBLs. Herein we report a strategy that utilizes a metal binding pharmacophore (MBP) click approach to identify new broad-spectrum MBL inhibitors. Our initial investigation identified several MBPs including phthalic acid, phenylboronic acid and benzyl phosphoric acid, which were subjected to structural transformations using azide-alkyne click reactions. Subsequent structure-activity relationship analyses led to the identification of several potent broad-spectrum MBL inhibitors, including 73 that manifested IC₅₀ values ranging from 0.00012 μM to 0.64 μM against multiple MBLs. Co-crystallographic studies demonstrated the importance of MBPs in engaging with the MBL active site anchor pharmacophore features, and revealed the unusual two-molecule binding modes with IMP-1, highlighting the critical role of flexible active site loops in recognizing structurally diverse substrates/inhibitors. Our work provides new chemotypes for MBL inhibition and establishes a MBP click-derived paradigm for inhibitor discovery targeting MBLs as well as other metalloenzymes.

Exploring potential SARS-CoV-2 Mpro non-covalent inhibitors through docking, pharmacophore profile matching, molecular dynamic simulation, and MM-GBSA

CONTEXT

In the replication of SARS-CoV-2, the main protease (Mpro/3CLpro) is significant. It is conserved in a number of novel coronavirus variations, and no known human proteases share its cleavage sites. Therefore, 3CLpro is an ideal target. In the report, we screened five potential inhibitors (1543, 2308, 3717, 5606, and 9000) of SARS-CoV-2 Mpro through a workflow. The calculation of MM-GBSA binding free energy showed that three of the five potential inhibitors (1543, 2308, 5606) had similar inhibitor effects to X77 against Mpro of SARS-CoV-2. In conclusion, the manuscript lays the groundwork for the design of Mpro inhibitors.

METHODS

In the virtual screening phase, we used structure-based virtual screening (Qvina2.1) and ligand-based virtual screening (AncPhore). In the molecular dynamic simulation part, we used the Amber14SB + GAFF force field to perform molecular dynamic simulation of the complex for 100 ns (Gromacs2021.5) and performed MM-GBSA binding free energy calculation according to the simulation trajectory.

MeDBA: the Metalloenzyme Data Bank and Analysis platform

Metalloenzymes are attractive research targets in fields of chemistry, biology, and medicine. Given that metalloenzymes can manifest conservation of metal-coordination and ligand binding modes, the excavation and expansion of metalloenzyme-specific knowledge is of interest in bridging metalloenzyme-related fields. Building on our previous metalloenzyme-ligand association database, MeLAD, we have expanded the scope of metalloenzyme-specific knowledge and services, by forming a versatile platform, termed the Metalloenzyme Data Bank and Analysis (MeDBA). The MeDBA provides: (i) manual curation of metalloenzymes into different categories, that this M-I, M-II and M-III; (ii) comprehensive information on metalloenzyme activities, expression profiles, family and disease links; (iii) structural information on metalloenzymes, in particular metal binding modes; (iv) metalloenzyme substrates and bioactive molecules acting on metalloenzymes; (v) excavated metal-binding pharmacophores and (vi) analysis tools for structure/metal active site comparison and metalloenzyme profiling. The MeDBA is freely available at https://medba.ddtmlab.org.

Design, Synthesis, and Biological Evaluation of New 1H-Imidazole-2-Carboxylic Acid Derivatives as Metallo-β-Lactamase Inhibitors

As one of important mechanisms to β-lactam antimicrobial resistance, metallo-β-lactamases (MBLs) have been receiving increasing worldwide attentions. Ambler subclass B1 MBLs are most clinically relevant, because they can hydrolyze almost all β-lactams with the exception of monobactams. However, it is still lacking of clinically useful drugs to combat MBL-medicated resistance. We previously identified 1H-imidazole-2-carboxylic acid as a core metal-binding pharmacophore (MBP) to target multiple B1 MBLs. Herein, we report structural optimization of 1H-imidazole-2-carboxylic acid and substituents. Structure-activity relationship (SAR) analyses revealed that replacement of 1H-imidazole-2-carboxylic acid with other structurally highly similar MBPs excepting thiazole-4-carboxylic acid resulted in decreased MBL inhibition. Further SAR studies identified more potent inhibitors to MBLs, of which 28 manifested IC₅₀ values of 0.018 µM for both VIM-2 and VIM-5. The microbiological tests demonstrated that the most tested compounds showed improved synergistic effects; some compounds at 1 µg/ml were able to reduce meropenem MIC by at least 16-fold, which will be worth further development of new potent inhibitors particularly targeting VIM-type MBLs.

Dual-target inhibitors of indoleamine 2, 3 dioxygenase 1 (Ido1): A promising direction in cancer immunotherapy

Indoleamine 2, 3-dioxygenase 1 (IDO1) is a rate-limiting enzyme that catalyzes the kynurenine (Kyn) pathway of tryptophan metabolism in the first step, and the kynurenine pathway plays a fundamental role in immunosuppression in the tumor microenvironment. Therefore, researchers are vigorously developing IDO1 inhibitors, hoping to apply them to cancer immunotherapy. Nowadays, there have been 11 kinds of IDO1 inhibitors entering clinical trials, among which many inhibitors have shown good tumor inhibitory effect in phase I/II clinical trials. But the phase III study of the most promising IDO1 inhibitor compound 29 (Epacadostat) failed in 2018, which may be caused by the compensation effect offered by tryptophan 2,3-dioxygenase (TDO), the mismatched drug combination strategies, or other reasons. Luckily, dual-target inhibitors show great potential and advantages in solving these problems. In recent years, many studies have linked IDO1 to popular targets and selected many IDO1 dual-target inhibitors through pharmacophore fusion strategy and library construction, which enhance the tumor inhibitory effect and reduce side effects. Currently, three kinds of IDO1/TDO dual-target inhibitors have entered clinical trials, and extensive studies have been developing on IDO1 dual-target inhibitors. In this review, we summarize the IDO1 dual-target inhibitors developed in recent years and focus on the structure optimization process, structure-activity relationship, and the efficacy of in vitro and in vivo experiments, shedding a light on the pivotal significance of IDO1 dual-target inhibitors in the treatment of cancer, providing inspiration for the development of new IDO1 dual-target inhibitors.

Characterization of Hydrophilic α-Helical Hot Spots on the Protein-Protein Interaction Interfaces for the Design of α-Helix Mimetics

The cooperativity index, K_c, was developed to examine the binding synergy between hot spots of the ligand-protein. For the first time, the convergence of the side-chain spatial arrangements of hydrophilic α-helical hot spots Thr, Tyr, Asp, Asn, Ser, Cys, and His in protein-protein interaction (PPI) complex structures was disclosed and quantified by developing novel clustering models. In-depth analyses revealed the driving force for the protein-protein binding conformation convergence of hydrophilic α-helical hot spots. This observation allows deriving pharmacophore models to design new mimetics for hydrophilic α-helical hot spots. A computational protocol was developed to search amino acid analogues and small-molecule mimetics for each hydrophilic α-helical hot spot. As a pilot study, diverse building blocks of commercially available nonstandard L-type α-amino acids and the phenyl ring-containing small-molecule fragments were obtained, which serve as a fragment collection to mimic hydrophilic α-helical hot spots for the improvement of binding affinity, selectivity, physicochemical properties, and synthesis accessibility of α-helix mimetics.

MeCOM: A Method for Comparing Three-Dimensional Metalloenzyme Active Sites

Since metalloenzymes are a large collection of metal ion(s) dependent enzymes, comparison analyses of metalloenzyme active sites are critical for metalloenzyme de novo design, function investigation, and inhibitor development. Here, we report a method named MeCOM for comparing metalloenzyme active sites. It is characterized by metal ion(s) centric active site recognition and three-dimensional superimposition using α-carbon or pharmacophore features. The test results revealed that for the given metalloenzymes, MeCOM could effectively recognize the active sites, extract active site features, and superimpose the active sites; it also could correctly identify similar active sites, differentiate dissimilar active sites, and evaluate the similarity degree. Moreover, MeCOM showed potential to establish new associations between structurally distinct metalloenzymes by active site comparison. MeCOM is freely available at https://mecom.ddtmlab.org.

Targeting Metalloenzymes by Boron-Containing Metal-Binding Pharmacophores

Metalloenzymes have critical roles in a wide range of biological processes and are directly involved in many human diseases; hence, they are considered as important targets for therapeutic intervention. The specific characteristics of metal ion(s)-containing active sites make exploitation of metal-binding pharmacophores (MBPs) critical to inhibitor development targeting metalloenzymes. This Perspective focuses on boron-containing MBPs, which display unique binding modes with metalloenzyme active sites, particularly via mimicking native substrates or tetrahedral transition states. The design concepts regarding boron-containing MBPs are highlighted through the case analyses on five distinct classes of clinically relevant nucleophilic metalloenzymes from medicinal chemistry perspectives. The challenges (e.g., selectivity) faced by some boron-containing MBPs and possible strategies (e.g., bioisosteres) for metalloenzyme inhibitor transformation are also discussed.

Zinc enzymes in medicinal chemistry

In humans, more than three hundred diverse enzymes that require zinc as an essential cofactor have been identified. These zinc enzymes have demonstrated different and important physiological functions and some of them have been considered as valuable therapeutic targets for drug discovery. Indeed, many drugs targeting a few zinc enzymes have been marketed to treat a variety of diseases. This review discusses drug discovery and drug development based on a dozen of zinc enzymes, including their biological functions and pathogenic roles, their best in class inhibitors (and clinical trial data when available), coordination and binding modes of representative inhibitors, and their implications for further drug design. The opportunities and challenges in developing zinc enzyme inhibitors for the treatment of human disorders are highlighted, too.

ProfKin: A comprehensive web server for structure-based kinase profiling

Protein kinases are central mediators of signal-transduction cascades and attractive drug targets for therapeutic intervention. Since kinases are structurally and mechanistically related to each other, kinase inhibitor selectivity is often investigated by kinase profiling and considered as an important index for drug discovery. We here describe a versatile web server termed ProfKin for structure-based kinase profiling, which is based on a kinase-ligand focused database (KinLigDB). It provides all ready-to-use 3D structure coordinates of 4219 kinase-ligand complex structures covering 297 human kinases and the associated information, particularly including binding site type, binding ligand type, interaction fingerprints, downstream molecules and related human diseases. The web server works via predicting possible binding modes for the query molecule, prioritizing the binding modes guided by an interaction fingerprint analysis method, and giving a list of ranked kinases by a comprehensive index. Users can freely select entire or part of the KinLigDB database, e.g. via subfamily and binding site type, to customize the profiling contents. The superimpositions of the predicted binding poses of the query molecule with reference binding modes can be visually inspected on the website. The additional classification attributes and phylogenetic tree are also given for each top-ranked kinase.

Structure-guided optimization of 1H-imidazole-2-carboxylic acid derivatives affording potent VIM-Type metallo-β-lactamase inhibitors

Production of metallo-β-lactamases (MBLs) in bacterial pathogens is an important cause of resistance to the 'last-resort' carbapenem antibiotics. Development of effective MBL inhibitors to reverse carbapenem resistance in Gram-negative bacteria is still needed. We herein report X-ray structure-guided optimization of 1H-imidazole-2-carboxylic acid (ICA) derivatives by considering how to engage with the active-site flexible loops and improve penetration into Gram-negative bacteria. Structure-activity relationship studies revealed the importance of appropriate substituents at ICA 1-position to achieve potent inhibition to class B1 MBLs, particularly the Verona Integron-encoded MBLs (VIMs), mainly by involving ingenious interactions with the flexible active site loops as observed by crystallographic analyses. Of the tested ICA inhibitors, 55 displayed potent synergistic antibacterial activity with meropenem against engineered Escherichia coli strains and even intractable clinically isolated Pseudomonas aeruginosa producing VIM-2 MBL. The morphologic and internal structural changes of bacterial cells after treatment further demonstrated that 55 crossed the outer membrane and reversed the activity of meropenem. Moreover, 55 showed good pharmacokinetic and safety profile in vivo, which could be a potential candidate for combating VIM-mediated Gram-negative carbapenem resistance.

Deep learning in target prediction and drug repositioning: Recent advances and challenges

Drug repositioning is an attractive strategy for discovering new therapeutic uses for approved or investigational drugs, with potentially shorter development timelines and lower development costs. Various computational methods have been used in drug repositioning, promoting the efficiency and success rates of this approach. Recently, deep learning (DL) has attracted wide attention for its potential in target prediction and drug repositioning. Here, we provide an overview of the basic principles of commonly used DL architectures and their applications in target prediction and drug repositioning, and discuss possible ways of dealing with current challenges to help achieve its expected potential for drug repositioning.

CovPDB: a high-resolution coverage of the covalent protein-ligand interactome

In recent years, the drug discovery paradigm has shifted toward compounds that covalently modify disease-associated target proteins, because they tend to possess high potency, selectivity, and duration of action. The rational design of novel targeted covalent inhibitors (TCIs) typically starts from resolved macromolecular structures of target proteins in their apo or holo forms. However, the existing TCI databases contain only a paucity of covalent protein–ligand (cP–L) complexes. Herein, we report CovPDB, the first database solely dedicated to high-resolution cocrystal structures of biologically relevant cP–L complexes, curated from the Protein Data Bank. For these curated complexes, the chemical structures and warheads of pre-reactive electrophilic ligands as well as the covalent bonding mechanisms to their target proteins were expertly manually annotated. Totally, CovPDB contains 733 proteins and 1,501 ligands, relating to 2,294 cP–L complexes, 93 reactive warheads, 14 targetable residues, and 21 covalent mechanisms. Users are provided with an intuitive and interactive web interface that allows multiple search and browsing options to explore the covalent interactome at a molecular level in order to develop novel TCIs. CovPDB is freely accessible at http://www.pharmbioinf.uni-freiburg.de/covpdb/ and its contents are available for download as flat files of various formats.

X-ray Structure-Guided Discovery of a Potent, Orally Bioavailable, Dual Human Indoleamine/Tryptophan 2,3-Dioxygenase (hIDO/hTDO) Inhibitor That Shows Activity in a Mouse Model of Parkinson's Disease

Human indoleamine 2,3-dioxygenase 1 (hIDO1) and tryptophan 2,3-dioxygenase (hTDO) have been closely linked to the pathogenesis of Parkinson's disease (PD); nevertheless, development of dual hIDO1 and hTDO inhibitors to evaluate their potential efficacy against PD is still lacking. Here, we report biochemical, biophysical, and computational analyses revealing that 1H-indazole-4-amines inhibit both hIDO1 and hTDO by a mechanism involving direct coordination with the heme ferrous and ferric states. Crystal structure-guided optimization led to 23, which manifested IC50 values of 0.64 and 0.04 μM to hIDO1 and hTDO, respectively, and had good pharmacokinetic properties and brain penetration in mice. 23 showed efficacy against the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced mouse motor coordination deficits, comparable to Madopar, an anti-PD medicine. Further studies revealed that different from Madopar, 23 likely has specific anti-PD mechanisms involving lowering IDO1 expression, alleviating dopaminergic neurodegeneration, reducing inflammatory cytokines and quinolinic acid in mouse brain, and increasing kynurenic acid in mouse blood.