Computational Toxicology Methods in Chemical Library Design and High-Throughput Screening Hit Validation.

The discovery of molecular toxicity in a clinical drug candidate can have a significant impact on both the cost and timeline of the drug discovery process. Early identification of potentially toxic compounds during screening library preparation or, alternatively, during the hit validation process is critical to ensure that valuable time and resources are not spent pursuing compounds that may possess a high propensity for human toxicity. This report focuses on the application of computational molecular filters, applied either pre- or post-screening, to identify and remove known reactive and/or potentially toxic compounds from consideration in drug discovery campaigns.

In Vitro Cell-Based MTT and Crystal Violet Assays for Drug Toxicity Screening.

The development of novel drug candidates is a current challenge in pharmacology where therapeutic benefits must exceed side effects. Toxicology testing is therefore a fundamental step in drug discovery research. Herein, we describe the first line of toxicology testing program, consisting in cell-based high-throughput screening assays, which have the advantage of being easy, rapid, cheap, and reproducible while providing quantitative information. We illustrate MTT and Crystal Violet assays, two common colorimetric tests able to assess both cytostatic and cytotoxic effects, respectively, of a drug candidate. MTT assay allows evaluation of cellular metabolic activity, by which cell viability can be inferred; Crystal Violet staining is directly correlated with attached viable cells, thus allowing direct assessment of cell survival and death. Therefore, combination of the two methodologies represents a useful tool for predicting drug sensitivity and efficacy, the first milestones in pre-clinical toxicology workflow.

Partition coefficient screening - An effective approach for finding the best conditions for byproduct removal as demonstrated by a bispecific antibody purification case.

In recombinant protein purification, differences in isoelectric point (pI)/surface charge and hydrophobicity between the product and byproducts generally form the basis for separation. For bispecific antibodies (bsAbs), in many cases the physicochemical difference between product and byproducts is subtle, making byproduct removal considerably challenging. In a previous report, with a bsAb case study, we showed that partition coefficient (Kp) screening for the product and byproducts under various conditions facilitated finding conditions under which effective separation of two difficult-to-remove byproducts was achieved by anion exchange (AEX) chromatography. In the current work, as a follow-up study, we demonstrated that the same approach enabled identification of conditions allowing equally good byproduct removal by mixed-mode chromatography with remarkably improved yield. Results from the current and previous studies proved that separation factor determination based on Kp screening for product and byproduct is an effective approach for finding conditions enabling efficient and maximum byproduct removal, especially in challenging cases.

Findings from the individualized management of a patient with Acyl-CoA Oxidase-1 (ACOX1) deficiency: A bedside-to-bench-to-bedside strategy.

Acyl-CoA Oxidase-1 (ACOX1) deficiency (MIM 264470) is an autosomal recessive disease characterized by impairments in the desaturation of acyl-CoAs to 2-trans-enoyl-CoAs, which is the first step in the catalysis of the ß-oxidative breakdown of very long chain fatty acids (VLCFA) occuring in peroxisomes. The deleterious accumulation of VLCFA in several organs, including the brain, is a key biochemical feature of this disease which has devastating neurological consequences. ACOX1 deficiency is ultra-rare; as such, few studies have been conducted to determine the leading causes of symptoms or uncover new therapeutics. When confronted with one such case, we decided to bring drug discovery tools to the patient's bedside in an attempt to identify a cure. A skin biopsy was performed on a young patient with ACOX1 deficiency, following which screening technologies and mass spectrometry analysis techniques were applied to design a cellular assay that enabled the direct measurement of the effect of small molecules on the patient's primary fibroblasts. This approach is particularly well adapted to inherited metabolic disorders such as ACOX1 deficiency. Through the evaluation of a proprietary library of repurposable drugs, we found that the anthelmintic drug niclosamide led to a significant reduction in VLCFA in vitro. This drug was subsequently administered to the patient for more than six years. This study outlines the screening and drug selection processes. Additionally, we present our comprehensive clinical and biochemical findings that aided in understanding the patient's natural history and analysis of the progression of the patient's symptoms throughout the treatment period. Although the patient's overall lifespan was extended compared to the average age at death in severe early onset cases of ACOX1 deficiency, we did not observe any definitive evidence of clinical or biochemical improvement during niclosamide treatment. Nonetheless, our study shows a good safety profile of long-term niclosamide administration in a child with a rare neurodegenerative disease, and illustrates the potential of individualized therapeutic strategies in the management of inherited metabolic disorders, which could benefit both patients and the broader scientific and medical communities.

Standardisation of high throughput microdilution antifungal susceptibility testing for Candida albicans and Cryptococcus neoformans.

The Clinical and Laboratory Standards Institute (CLSI) M27 guidelines are the recommended and most commonly used protocols for broth microdilution antifungal susceptibility testing of yeasts. However, these guidelines are limited to the use of 96-well assay plates, limiting assay capacity. With the increased risk of fungal resistance emerging in the community, it is important to have alternative protocols available, that offer higher throughput and can screen more than eight to ten potential antifungal compounds per plate. This study presents an optimised broth microdilution minimum inhibitory concentration (MIC) method for testing the susceptibility of yeasts in an efficient high throughput screening setup, with minimal growth variability and maximum reproducibility. We extend the M27 guidelines and optimise the conditions for 384-well plates. Validation of the assay was performed with ten clinically used antifungals (fluconazole, amphotericin B, 5-fluorocytosine, posaconazole, voriconazole, ketoconazole, itraconazole, caspofungin diacetate, anidulafungin and micafungin) against Candida albicans and Cryptococcus neoformans.

Exploring "dark-matter" protein folds using deep learning.

De novo protein design explores uncharted sequence and structure space to generate novel proteins not sampled by evolution. A main challenge in de novo design involves crafting "designable" structural templates to guide the sequence searches toward adopting target structures. We present a convolutional variational autoencoder that learns patterns of protein structure, dubbed Genesis. We coupled Genesis with trRosetta to design sequences for a set of protein folds and found that Genesis is capable of reconstructing native-like distance and angle distributions for five native folds and three novel, the so-called "dark-matter" folds as a demonstration of generalizability. We used a high-throughput assay to characterize the stability of the designs through protease resistance, obtaining encouraging success rates for folded proteins. Genesis enables exploration of the protein fold space within minutes, unrestricted by protein topologies. Our approach addresses the backbone designability problem, showing that small neural networks can efficiently learn structural patterns in proteins. A record of this paper's transparent peer review process is included in the supplemental information.

Unlocking the Chemical and Structural Complexity of Aluminum Hydroxy Acetates: from Commodity Chemicals to Porous Materials.

Aluminum acetates have been in use for more than a century, but despite their widespread commercial applications, essential scientific knowledge of their synthesis-structure-property relationships is lacking. High-throughput screening, followed by fine tuning and extensive optimization of reaction conditions using Al3+, OH- and CH3COO- ions, has unraveled their complex synthetic chemistry, yielding for the first time the four phase pure products Al(OH)(O2CCH3) ⋅ x H2O (x = 0, 2) (1A and CAU-65, 1B), Al3O(HO2CCH3)(O2CCH3)7 (2), and the porous aluminum salt [Al24(OH)56(CH3COO)12](OH)4 (CAU-55-OH, 3). Structure determination by electron and X-ray diffraction was carried out and the data suggested porosity for 1B and 3, which was confirmed by physisorption experiments. Even the scale-up to the 10 L scale was accomplished for 1A, 1B and 3 with yields of up to 1.1 kg (99%). This study of a seemingly simple chemical system provides important information on both fundamental inorganic chemistry and porous materials.

Machine Learning Elucidates Design Features of Plasmid Deoxyribonucleic Acid Lipid Nanoparticles for Cell Type-Preferential Transfection.

To broaden the accessibility of cell and gene therapies, it is essential to develop and optimize nonviral, cell type-preferential gene carriers such as lipid nanoparticles (LNPs). While high-throughput screening (HTS) approaches have proven effective in accelerating LNP discovery, they are often costly, labor-intensive, and do not consistently yield actionable design rules that direct screening efforts toward the most relevant chemical and formulation parameters. In this study, we employed a machine learning (ML) workflow, utilizing well-curated plasmid DNA LNP transfection data sets across six cell types, to extract compositional and chemical insights from HTS studies. Our approach achieved prediction errors averaging between 5 and 10%, depending on the cell type. By applying SHapley Additive exPlanations to our ML models, we uncovered key composition-function relationships that govern cell type-preferential LNP transfection efficiency. Notably, we identified consistent LNP composition parameters that enhance in vitro transfection efficiency across diverse cell types, including a helper lipid molar percentage of charged lipids between 9 and 50% and the inclusion of cationic/zwitterionic helper lipids. Additionally, several parameters were found to modulate cell type-preferentiality, such as the total molar percentage of ionizable and helper lipids, N/P ratio, PEGylated lipid molar percentage of uncharged lipids, and hydrophobicity of the helper lipid. This study leverages HTS of compositionally diverse LNP libraries combined with ML analysis to elucidate the interactions between lipid components in LNP formulations, providing insights that contribute to the design of LNP compositions tailored for cell type-preferential transfection.

Clear zone formation in microdroplets for high-throughput screening for lactic acid bacteria.

Droplet microfluidic-based technology is a powerful tool for biotechnology, and it is also expected that it will be applied to culturing and screening methods. Using this technology, a new high-throughput screening method for lactic acid bacteria was developed. In this study, the conventional culture of lactic acid bacteria that form clear zones on an agar medium was reproduced in water-in-oil droplets, and only the droplets in which lactic acid bacteria grew were collected one by one. Using this method, the specific recovery of Lactiplantibacillus plantarum from a mixture of L. plantarum and Escherichia coli and the acquirement of lactic acid bacteria from an environmental sample were successful. This method could be applied to various conventional screening methods using the clear zone as a microbial growth indicator. This has expanded the possibilities of applying droplet microfluidic-based technology to microbial cultivations.

High-Throughput Assessment of Metabolism-Mediated Neurotoxicity by Co-Culture of Neurospheres and Liver Spheroids.

The liver's role in the biotransformation of chemicals is critical for both augmented toxicity and detoxification. However, there has been a significant lack of effort to integrate biotransformation into in vitro neurotoxicity testing. Traditional in vitro neurotoxicity testing systems are unable to assess the qualitative and quantitative differences between parent chemicals and their metabolites as they would occur in the human body. As a result, traditional in vitro toxicity screening systems cannot incorporate hepatic biotransformation to predict the neurotoxic potential of chemical metabolites. To bridge this gap, a high-throughput, metabolism-mediated neurotoxicity testing system has been developed, which combines metabolically competent HepaRG cell spheroids with a three-dimensional (3D) culture of ReNcell VM human neural progenitor cell line. The article outlines protocols for generating HepaRG cell spheroids using an ultralow attachment (ULA) 384-well plate and for cultivating ReNcell VM in 3D on a 384-pillar plate with sidewalls and slits (384PillarPlate). Metabolically sensitive test compounds are introduced into the ULA 384-well plate containing HepaRG spheroids and then tested with 3D-cultured ReNcell VM on the 384PillarPlate. This configuration permits the in situ generation of metabolites by HepaRG cells and their subsequent testing on neurospheres. By analyzing cell viability data, researchers can determine the IC50 values for each compound, thus evaluating metabolism-mediated neurotoxicity. © 2024 Wiley Periodicals LLC. Basic Protocol 1: HepaRG spheroid culture in an ultralow attachment (ULA) 384-well plate and the assessment of drug-metabolizing enzyme (DME) activities Basic Protocol 2: 3D neural stem cell (NSC) culture on a 384PillarPlate and compound treatment for the assessment of metabolism-mediated neurotoxicity Basic Protocol 3: Image acquisition, processing, and data analysis.

High-throughput screening for small-molecule stabilizers of misfolded glucocerebrosidase in Gaucher disease and Parkinson's disease.

Glucocerebrosidase (GCase) is implicated in both a rare, monogenic disorder (Gaucher disease, GD) and a common, multifactorial condition (Parkinson's disease, PD); hence, it is an urgent therapeutic target. To identify correctors of severe protein misfolding and trafficking obstruction manifested by the pathogenic L444P-variant of GCase, we developed a suite of quantitative, high-throughput, cell-based assays. First, we labeled GCase with a small proluminescent HiBiT peptide reporter tag, enabling quantitation of protein stabilization in cells while faithfully maintaining target biology. TALEN-based gene editing allowed for stable integration of a single HiBiT-GBA1 transgene into an intragenic safe-harbor locus in GBA1-knockout H4 (neuroglioma) cells. This GD cell model was amenable to lead discovery via titration-based quantitative high-throughput screening and lead optimization via structure-activity relationships. A primary screen of 10,779 compounds from the NCATS bioactive collections identified 140 stabilizers of HiBiT-GCase-L444P, including both pharmacological chaperones (ambroxol and noninhibitory chaperone NCGC326) and proteostasis regulators (panobinostat, trans-ISRIB, and pladienolide B). Two complementary high-content imaging-based assays were deployed to triage hits: The fluorescence-quenched substrate LysoFix-GBA captured functional lysosomal GCase activity, while an immunofluorescence assay featuring antibody hGCase-1/23 directly visualized GCase lysosomal translocation. NCGC326 was active in both secondary assays and completely reversed pathological glucosylsphingosine accumulation. Finally, we tested the concept of combination therapy by demonstrating synergistic actions of NCGC326 with proteostasis regulators in enhancing GCase-L444P levels. Looking forward, these physiologically relevant assays can facilitate the identification, pharmacological validation, and medicinal chemistry optimization of small molecules targeting GCase, ultimately leading to a viable therapeutic for GD and PD.

Large-Scale Construction and Analysis of Amorphous Porous Polymer Network Materials.

In recent decades, data-driven methodologies have emerged as irreplaceable tools in materials science, particularly for elucidating structure-property relationships and facilitating the discovery of novel materials. However, despite the rapid development witnessed in other domains, amorphous materials have received relatively less attention in this context. The disordered atomic structure of amorphous materials resulting from irreversible reactions between building blocks has posed a difficulty in structural modeling, leading to a lack of databases that accurately reflect the amorphous nature of these materials. In this work, a database composed of 10,237 porous polymer networks (PPNs) was constructed from self-assembly simulations, resulting in the largest database of PPNs considering their amorphous characteristics. Through the distinct differences observed in comparison with existing databases, we emphasize that carefully considering the structural disorder of PPNs is essential for accurately characterizing their chemical behaviors. Machine learning models trained on the constructed database have confirmed that the macroscopic properties of amorphous PPNs can be predicted solely from the atomic structures of their monomers, implying that the characteristics of previously unseen PPNs can be assessed without the need for additional self-assembly simulations.

Protocol for modeling acquired resistance to targeted therapeutics in adherent and suspension cancer cell lines via in situ resistance assay.

Acquired resistance to oncogene-targeted therapies is the major driver of mortality for patients with cancer. Here, we present a 6-to-16-week assay to model the development of acquired resistance in adherent and suspension cancer cell lines. We describe steps for determining therapeutic dose, assaying acquired resistance, and testing combination therapies. This protocol is a high-throughput, cost-effective, and scalable method to model acquired drug resistance to established and newly developed therapies. For complete details on the use and execution of this protocol, please refer to Sealover et al.1 and Theard et al.2.

RADD: A real-time FRET-based biochemical assay for DNA deaminase studies.

In recent years, the connection between APOBEC3 cytosine deaminases and cancer mutagenesis has become ever more apparent. This growing awareness and lack of inhibitory drugs has created a distinct need for biochemical tools that can be used to identify and characterize potential inhibitors of this family of enzymes. In response to this challenge, we have developed a Real-time APOBEC3-mediated DNA Deamination (RADD) assay. The RADD assay provides a rapid, real-time fluorescence readout of APOBEC3 DNA deamination and serves as a crucial addition to the existing APOBEC3 biochemical and cellular toolkit. This method improves upon contemporary DNA deamination assays by offering a more rapid and quantifiable readout as well as providing a platform that is readily adaptable to a high-throughput format for inhibitor discovery. In this chapter we provide a detailed guide for the usage of the RADD assay for the characterization of APOBEC3 enzymes and potential inhibitors.

Construction of HEK293T cell line stably expressing TRPM2 channel based on PiggyBac transposition system and its application in drug screening for cerebral ischemia and other diseases. / 基于PiggyBac转座子优化稳定表达细胞系的新型瞬时受体电位M2通道抑制剂筛选.

OBJECTIVES: To establish a cell line stably expressing the TRPM2 channel for screening TRPM2 inhibitors based on PiggyBac transposition system. METHODS: A pPB-hTRPM2 eukaryotic expression vector was constructed using PiggyBac transposition system. The constructed plasmid and helper plasmid were contransfected into HEK293T cells to express TRPM2, which was identified by fluorescence and patch-clamp assay. The high throughput screening was assessed with the Z ´ factor. Calcium imaging and patch clamp techniques were employed to assess the initial activity of the eleven compound molecules, confirming the inhibitory effects of the primary molecule on TRPM2. The protective impact of screened compounds on damaged cells was validated using the oxygen-glucose deprivation reperfusion (OGD/R) model and CCK-8 kit. The level of cellular reactive oxygen species (ROS) was detected by flow cytometry. The neuroprotective effects of the compounds were evaluated using a transient middle cerebral artery occlusion (tMCAO) mouse model. RESULTS: The HEK293T cells transfected with pPB-hTRPM2-EGFP showed high TRPM2 expression. Puromycin-resistant cells, selected through screening, exhibited robust fluorescence. Whole-cell patch results revealed that induced cells displayed classical TRPM2 current characteristics comparable to the control group, showing no significant differences (P>0.05). With a Z ´ factor of 0.5416 in calcium imaging (Z ´>0.5), the model demonstrated suitability for high-throughput screening of TRPM2 inhibitors. Calcium imaging and electrophysiological experiments indicated that compound 6 significantly inhibited the TRPM2 channel. Further experiments showed that 1 µmol/L of compound 6 enhanced the cell viability (P<0.05) and reduced the level of ROS (P<0.05) of SH-SY5Y under OGD/R-induced injury, 0.3 and 1 mg/kg of compound 6 reduced the cerebral infarction volume in tMCAO mice (both P<0.05). CONCLUSIONS: A stably TRPM2 gene expressing cell line has been successfully established using PiggyBac gene editing in this study. TRPM2 channel inhibitors were screened through calcium imaging and patch clamp techniques, an inhibitor compound 6 has been identified, which can alleviate cell damage after OGD/R by reducing cellular ROS levels, and has a protective effect against cerebral ischemia-reperfusion injury in mice.

Innovative Strategies in Drug Repurposing to Tackle Intracellular Bacterial Pathogens.

Intracellular bacterial pathogens pose significant public health challenges due to their ability to evade immune defenses and conventional antibiotics. Drug repurposing has recently been explored as a strategy to discover new therapeutic uses for established drugs to combat these infections. Utilizing high-throughput screening, bioinformatics, and systems biology, several existing drugs have been identified with potential efficacy against intracellular bacteria. For instance, neuroleptic agents like thioridazine and antipsychotic drugs such as chlorpromazine have shown effectiveness against Staphylococcus aureus and Listeria monocytogenes. Furthermore, anticancer drugs including tamoxifen and imatinib have been repurposed to induce autophagy and inhibit bacterial growth within host cells. Statins and anti-inflammatory drugs have also demonstrated the ability to enhance host immune responses against Mycobacterium tuberculosis. The review highlights the complex mechanisms these pathogens use to resist conventional treatments, showcases successful examples of drug repurposing, and discusses the methodologies used to identify and validate these drugs. Overall, drug repurposing offers a promising approach for developing new treatments for bacterial infections, addressing the urgent need for effective antimicrobial therapies.

Development of a FUT8 Inhibitor with Cellular Inhibitory Properties.

Core fucosylation is catalyzed by α-1,6-fucosyltransferase (FUT8), which fucosylates the innermost GlcNAc of N-glycans. Given the association of FUT8 with various diseases including cancer, selective FUT8 inhibitors applicable to in vivo or cell-based systems are highly sought-after. Here, we report the discovery of a compound that selectively inhibits FUT8 in cell-based assays. High-throughput screening revealed a FUT8-inhibiting pharmacophore, and further structural optimization yielded an inhibitor with a KD of 49 nM. Notably, this binding occurs only in the presence of GDP (a product of the enzymatic reaction catalyzed by FUT8). Mechanistic studies suggested that this inhibitor generates a highly reactive naphthoquinone methide derivative at the binding site in FUT8, which subsequently reacts with FUT8. Furthermore, prodrug derivatization of this inhibitor improved its stability, enabling suppression of core fucose expression and subsequent EGFR and T-cell signaling in cell-based assays, paving the way for the development of drugs targeting core fucosylation.

A High-Throughput Visual Screen for the Directed Evolution of C ß -stereoselectivity of L-threonine Aldolase.

L-Threonine aldolase (L-TA) is a pyridoxal phosphate-dependent enzyme that catalyzes the reversible condensation of glycine and aldehydes to form ß-hydroxy-α-amino acids. The combination of directed evolution and efficient high-throughput screening methods is an effective strategy for enhancing the enzyme's catalytic performance. However, few feasible high-throughput methods exist for engineering the Cß-stereoselectivity of L-TAs. Here, we present a novel method of screening for variants with improved Cß-stereoselectivity; this method couples an L-threo-phenylserine dehydrogenase, which catalyzes the specific oxidation of L-threo-4-methylsulfonylphenylserine (L-threo-MTPS), with the concurrent synthesis of NADPH, which is easily detectable via 340-nm UV absorption. This enables the visual detection of L-threo-MTPS produced by L-TA through the measurement of generated NADPH. Using this method, we discover an L-TA variant with significantly higher diastereoselectivity, increasing from 0.98% de (for the wild-type) to 71.9% de.

Anti-cancer agent 5-fluorouracil reverses meropenem resistance in carbapenem-resistant Gram-negative pathogens.

The global increasing incidence of clinical infections caused by carbapenem-resistant Gram-negative pathogens demands urgent and effective treatment strategies. Antibiotic adjuvants represent a promising approach to enhance the efficacy of meropenem against carbapenem-resistant bacteria. Herein, we identified the anticancer agent 5-fluorouracil (5-FU, 50 µM) significantly reduced the minimal inhibitory concentration of meropenem against blaNDM-5 positive Escherichia coli by 32-fold through cell-based high-throughput screening. Further pharmacological studies indicated that 5-FU exhibited the potentiation effects on carbapenem antibiotics against 42 Gram-negative bacteria producing either metallo-ß-lactamases (MBLs), such as NDM and IMP, or serine ß-lactamases (Ser-BLs), like KPC and OXA. These bacteria included E. coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter spp., with 32 of them obtained from human clinical samples. Mechanistic investigations revealed that 5-FU inhibited the transcriptional and expressional level of the blaNDM-5 gene. Additionally, the 5-FU combined with meropenem can enhance bacterial metabolism, and stimulate the production of Reactive Oxygen Species (ROS), thereby rendering bacteria more susceptible to meropenem. This drug combination could effectively elevate the survival rate from 16.7% to 83.3% compared to meropenem monotherapy, and reduce bacteria loads in tissues in a mouse systemic infection model. Collectively, these findings reveal that the potential of 5-FU as a novel meropenem adjuvant to improve treatment outcomes against carbapenem-resistant bacteria infections.

Probing Nanotopography-Mediated Macrophage Polarization via Integrated Machine Learning and Combinatorial Biophysical Cue Mapping.

Inflammatory responses, leading to fibrosis and potential host rejection, significantly hinder the long-term success and widespread adoption of biomedical implants. The ability to control and investigated macrophage inflammatory responses at the implant-macrophage interface would be critical for reducing chronic inflammation and improving tissue integration. Nonetheless, the systematic investigation of how surface topography affects macrophage polarization is typically complicated by the restricted complexity of accessible nanostructures, difficulties in achieving exact control, and biased preselection of experimental parameters. In response to these problems, we developed a large-scale, high-content combinatorial biophysical cue (CBC) array for enabling high-throughput screening (HTS) of the effects of nanotopography on macrophage polarization and subsequent inflammatory processes. Our CBC array, created utilizing the dynamic laser interference lithography (DLIL) technology, contains over 1 million nanotopographies, ranging from nanolines and nanogrids to intricate hierarchical structures with dimensions ranging from 100 nm to several microns. Using machine learning (ML) based on the Gaussian process regression algorithm, we successfully identified certain topographical signals that either repress (pro-M2) or stimulate (pro-M1) macrophage polarization. The upscaling of these nanotopographies for further examination has shown mechanisms such as cytoskeletal remodeling and ROCK-dependent epigenetic activation to be critical to the mechanotransduction pathways regulating macrophage fate. Thus, we have also developed a platform combining advanced DLIL nanofabrication techniques, HTS, ML-driven prediction of nanobio interactions, and mechanotransduction pathway evaluation. In short, our developed platform technology not only improves our ability to investigate and understand nanotopography-regulated macrophage inflammatory responses but also holds great potential for guiding the design of nanostructured coatings for therapeutic biomaterials and biomedical implants.