Three-dimensional Structure Research Articles

Three-dimensional mapping of necrotic lesions for early-stage osteonecrosis of the femoral head

BackgroundThere is a scarcity of evidence regarding the potential relationship between the size and location of necrotic lesions, which must be understood to provide optimal joint-preserving treatment. The purpose of this study was to characterize the distribution patterns of necrotic lesions of varying sizes in early-stage osteonecrosis of femoral head (ONFH) with the use of three-dimensional mapping.MethodsWe retrospectively evaluated clinical CT images of the hips that were performed in the Third Hospital of Hebei Medical University from January 2018 to December 2022 and collected all CT images diagnosed with stage I and II ONFH. Three-dimensional structures that included both necrotic lesions and normal areas of the femoral heads were reconstructed and divided into eight regions to record their size and location. CT images for all lesions were superimposed onto a standard template, and three-dimensional mapping was created to determine the presence of concentrated areas of lesions.ResultsIn a cohort of 143 patients with stage I and II ONFH, a total of 150 hips were reviewed. For lesions with less than 15% of the femoral head volume, necrotic lesions predominantly involve regions I, III, and V, with region I showing concentration. For lesions with volumes ranging from 15 to 30%, necrotic lesions exhibited a wider distribution across regions I, II, III, IV, V, and VII, with significant concentrations in regions I, III, and V. For lesions exceeding 30% of the femoral head volume, the necrotic lesions were extensively distributed across nearly the entire femoral head, with a notable expansion of the concentrated necrotic areas.ConclusionsThe distribution of necrotic lesions varies with lesion size, with smaller lesions primarily concentrated in the anterior and medial regions of the femoral head, particularly in the anterosuperior region, while larger lesions expand to the lateral and inferior regions. These findings enhance existing classification systems and provide crucial insights for guiding hip-preserving surgical planning and approaches.

Subpicosecond Dynamics of Rydberg Excitons Produced from Ultraviolet Excitation of Neutral Cuprite (Cu2O)n Clusters, n < 13.

The ultrafast dynamics of subnanometer neutral cuprite clusters (Cu2O)n, n < 13, are examined with pump probe spectroscopy. Upon absorption of an ultraviolet (400 nm) photon, all clusters exhibit a subpicosecond lifetime that we attribute to carrier recombination. Density functional theory (DFT) shows a change in the structural motif between small planar clusters and three-dimensional structures at n = 4. This transition is accompanied by a change in the excited state relaxation behavior, marking the onset for which lifetimes increase gradually with size. Time-dependent DFT calculations show that the excited state lifetimes align with calculated topological parameters and charge carrier delocalization associated with the formation of Rydberg excitons. Terminal Cu atoms are found to be important for the production of Rydberg excitons at the lowest optically allowed excited state. Upon excitation, the electron resides on terminal Cu atoms and the hole becomes delocalized across the remainder of the cluster.

A lightweight visualization tool for protein unfolding by collision detection and elimination

The experiments involving protein denaturation and refolding serve as the foundation for predicting the three-dimensional spatial structures of proteins based on their amino acid sequences. Despite significant progress in protein structure engineering, exemplified by AlphaFold2 and OmegaFold, there remains a gap in understanding the folding pathways of polypeptide chains leading to their final structures. We developed a lightweight tool for protein unfolding visualization called PUV whose graphics design is mainly implemented by OpenGL. PUV leverages principles from molecular biology and physics, and achieves rapid visual dynamics simulation of protein polypeptide chain unfolding through mechanical force and atom-level collision detection and elimination. After a series of experimental validations, we believe that this method can provide essential support for investigating protein folding mechanisms and pathways.

Mechanical properties and micro-mechanism of seawater cementitious materials reinforced by in-situ polymerization

Understanding the potential mechanism of in-situ polymerization of acrylamide (AM) for modifying seawater cementitious materials is crucial for designing high-strength and durable marine concrete. Herein, the acrylamide (AM) in-situ polymerization was investigated for its effects on the hydration behavior, micro-morphology, and pore structure of cementitious materials mixed with seawater and freshwater through a series of elaborately designed microscopic characterization methods. The results reveal that the hydration process of cementitious materials proceeds simultaneously with in-situ polymerization. However, compared with freshwater mixtures, seawater provides a large number of metal ions and SO42- ions, which can cross-link with the generated polyacrylamide (PAM) during in-situ polymerization to form a three-dimensional network structure. The synergistic effect of the hydration, in-situ polymerization, and cross-linking processes of cementitious materials can improve the pore structure of seawater-mixed paste, enhance erosion resistance, and improve the stability and toughness of microstructure. These findings were further confirmed by comparing infrared spectroscopy results, hydration products, pore size, and micro-morphology analysis as well as flexural performance tests. This is of great significance to guide the design of novel materials in marine infrastructure.

Mass and Heat Exchange in Rotating Compressor Cavities With Variable Cob Separation

Abstract Next generation aeroengines will operate at ever-increasing pressure ratios with smaller cores, where the control of blade-tip clearances across the flight cycle is an emerging design challenge. Such clearances are affected by the thermal expansion of the compressor disks that hold the blades, where acute thermal stresses govern operating life. The cavities formed by corotating disks feature a heated shroud at high radius and cooler cobs at low radius. A three-dimensional, unsteady and unstable flow structure is induced by destabilizing buoyancy forces. The radial distribution of disk temperature is driven by a conjugate heat transfer at Grashof numbers of order 1013. Such flows are further influenced by the heat and mass exchange with an axial throughflow of cooling air at low radius, where the interaction depends on the Rossby number and separation of the disk cobs. This paper is the first to study the effect of cob separation ratio on mass and heat exchange for compressor cavities. A model is developed to predict the cavity-throughflow interaction, and disk and fluid-core temperatures. The judicious use of a physics-based methodology provides reliable, reduced-order solutions to the complex conjugate problem, thereby making it appropriate for practical engine thermo-mechanical design. The model is validated by detailed experimental measurements using the Bath Compressor Cavity Rig, where variable disk cob spacings were investigated over a range of engine-representative conditions. The unsteady pressure measurements collected in the frame of reference of the rotating disks reveal new insight into the fundamentally aperiodic nature of the flow structure. This new understanding of heat transfer informs an expedient reduced-order model and enables more efficient design of future high pressure-ratio aeroengines.

MicroED Structures of Fluticasone Furoate and Fluticasone Propionate Provide New Insights to Their Function.

The detailed understanding of fluticasone, a widely prescribed medicine for allergic rhinitis, asthma, and chronic obstructive pulmonary disease (COPD), has not been complete due to challenges in structural elucidation. The three-dimensional (3D) structure of fluticasone furoate 1 remained undetermined for decades, while the existing structures of fluticasone propionate 2 required refinement against improved data. In this study, we applied microcrystal electron diffraction (MicroED) to determine the 3D structures of 1 and 2 in their drug formulation state. Density functional theory (DFT) calculations were utilized to model solvent effects to determine the preferred geometries in solution. A comparative analysis of structures of 1 and 2 across three states (drug formulation state, in solution, and biologically active state) revealed major conformational changes during the entire transition. Potential energy plots were calculated for the most dynamic bonds, uncovering their rotational barriers. This study underscores the combined use of MicroED and DFT calculations to provide a comprehensive understanding of conformational and energy changes during drug functioning in humans. The quantitative comparison highlights the subtle structural differences that can lead to significant functional changes in pharmaceutical properties.

Validation in Spanish and English of the Transgender Inclusive Behavior Scale.

The Transgender Inclusive Behavior Scale (TIBS) seeks to measure transgender-inclusive behavior, specifically actions and language use that support transgender people. The TIBS was developed in the United States. This study aimed to develop a Spanish version of the TIBS and confirm the structure of the English version to explore the psychometric properties and evaluate the construct validity in new contexts. We examined predictors of transgender-inclusive behavior by conducting a comparative analysis between participants from Spain and the United Kingdom. The study involved 1,110 university students, with 545 participants hailing from Spain (375 women, 162 men, and 8 non-binary individuals) and 565 participants from the United Kingdom (368 women, 178 men, and 19 non-binary individuals). Exploratory and confirmatory factor analysis were conducted to investigate and validate the factorial structure of the TIBS. The factor analysis results for the 15 items on the scale confirmed a three-dimensional structure in both languages. The scale score reliability was excellent with a Cronbach's alpha (α) = .95 in the British sample and with an α = .89 in the Spanish sample. Being a woman, being lesbian, gay, bisexual, trans, queer, intersex, and/or asexual, and being non-religious were the strongest predictors of inclusive behaviors towards transgender people in both countries. The correlations found indicated that people with lower sexual risk behaviors, and lower sexist, homophobic, and transphobic attitudes also presented higher inclusive behaviors towards trans people. These findings support the development of community strategies to increase the social inclusion of transgender people. The TIBS is a useful measure to track their success.

On the three-dimensional structure of instabilities beneath shallow-shoaling internal waves

The stimulation of instability and transport in the bottom boundary layer by internal solitary waves has been documented for over twenty years. However, the challenge of shallow slopes and a disparity of scales between the large-scale wave and the small-scale boundary layer has proven challenging for simulations. We present laboratory scale simulations that resolve the three-dimensionalisation in the boundary layer during the entire shoaling process. We find that the late stage, in which the incoming wave fissions into boluses, provides the most consistent source of three-dimensionalisation. In the early stage of shoaling, three-dimensionalisation occurs not so much due to separation bubble instability, but due to the interaction of vortices shed from the separation bubble with the overlying pycnocline. This interaction overturns the pycnocline, and creates bursts in kinetic energy and viscous dissipation, suggesting that the shed vortices induce turbulent motion and sediment resuspension in the water column above and behind the separation bubble.

Engaging psychologically or behaviourally? A segmentation of the integrated resort customers

Academic studies that highlight the importance of customer engagement for sustaining organisational success have generally assumed that engaged customers are a homogenous market segment. This study provides an alternative scholarly perspective by reconsidering the multidimensionality of customer engagement and uses cognitive, affective, and behavioural elements to segment customers. A cluster analysis with data from 574 integrated resort customers in Macau, China supports the three-dimensional structure, and additional analyses show that customers can be segmented into totally-engaged, shallowly-engaged, potentially-engaged, and non-engaged groups based on their psychological investment (which consists of cognitive and affective engagements) and behavioural engagement. The findings both address the dimensional structure of customer engagement in the market segmentation context and provide some valuable theoretical and market segment-related managerial implications.

N-terminal domain of androgen receptor is a major therapeutic barrier and potential pharmacological target for treating castration resistant prostate cancer: a comprehensive review.

The incidence rate of prostate cancer (PCa) has risen by 3% per year from 2014 through 2019 in the United States. An estimated 34,700 people will die from PCa in 2023, corresponding to 95 deaths per day. Castration resistant prostate cancer (CRPC) is the leading cause of deaths among men with PCa. Androgen receptor (AR) plays a critical role in the development of CRPC. N-terminal domain (NTD) is the essential functional domain for AR transcriptional activation, in which modular activation function-1 (AF-1) is important for gene regulation and protein interactions. Over last 2decades drug discovery against NTD has attracted interest for CRPC treatment. However, NTD is an intrinsically disordered domain without stable three-dimensional structure, which has so far hampered the development of drugs targeting this highly dynamic structure. Employing high throughput cell-based assays, small-molecule NTD inhibitors exhibit a variety of unexpected properties, ranging from specific binding to NTD, blocking AR transactivation, and suppressing oncogenic proliferation, which prompts its evaluation in clinical trials. Furthermore, molecular dynamics simulations reveal that compounds can induce the formation of collapsed helical states. Nevertheless, our knowledge of NTD structure has been limited to the primary sequence of amino acid chain and a few secondary structure motif, acting as a barrier for computational and pharmaceutical analysis to decipher dynamic conformation and drug-target interaction. In this review, we provide an overview on the sequence-structure-function relationships of NTD, including the polymorphism of mono-amino acid repeats, functional elements for transcription regulation, and modeled tertiary structure of NTD. Moreover, we summarize the activities and therapeutic potential of current NTD-targeting inhibitors and outline different experimental methods contributing to screening novel compounds. Finally, we discuss current directions for structure-based drug design and potential breakthroughs for exploring pharmacological motifs and pockets in NTD, which could contribute to the discovery of new NTD inhibitors.

Comprehensive bioinformatics assessments of the ROP34 of Toxoplasma gondii to approach vaccine candidates

IntroductionRhoptries proteins (ROPs) are crucial throughout different stages of the Toxoplasma gondii (T. gondii) lifecycle, playing key roles in both the invasion of host cells and their subsequent survival. ROP34 is particularly noteworthy as it significantly influences host gene expression and aids in the transition from the tachyzoite to the bradyzoite form.Materials and methodsThis research utilized various bioinformatics tools to assess physico-chemical properties, allergenic and antigenic characteristics, sites for post-translational modifications (PTMs) and protein's secondary and three-dimensional structures of the ROP34 protein. Furthermore, the study identified potential B-cell, MHC-binding, and cytotoxic T-lymphocyte (CTL) epitopes within the ROP34 sequence.ResultsThe ROP34 peptide comprised 553 amino acid residues, with a calculated average molecular weight (MW) of 61.60149 kDa, an aliphatic index of 73.98, and a GRAVY score of − 0.554. The antigenicity of the multi-epitope peptide was estimated to be 0.526563 and 0.6025 by the ANTIGENpro and VaxiJen servers, respectively, suggesting ROP34 as an immunogenic protein with no allergenic potential. Secondary structure analysis revealed a composition of 52.80% random coil, 36.17% alpha helix, and 11.03% extended strand. The Ramachandran plot for the refined model depicted that 97.46% of the residues were situated in the favored region.ConclusionThis in silico research serves as a foundation for designing effective immunization tactics to target toxoplasmosis. The present article lays the groundwork for future studies and offers perspectives for the advancement of an appropriate toxoplasmosis vaccine.Graphical

Nanoscale imaging of DNA-RNA identifies transcriptional plasticity at heterochromatin.

The three-dimensional structure of DNA is a biophysical determinant of transcription. The density of chromatin condensation is one determinant of transcriptional output. Chromatin condensation is generally viewed as enforcing transcriptional suppression, and therefore, transcriptional output should be inversely proportional to DNA compaction. We coupled stable isotope tracers with multi-isotope imaging mass spectrometry to quantify and image nanovolumetric relationships between DNA density and newly made RNA within individual nuclei. Proliferative cell lines and cycling cells in the murine small intestine unexpectedly demonstrated no consistent relationship between DNA density and newly made RNA, even though localized examples of this phenomenon were detected at nuclear-cytoplasmic transitions. In contrast, non-dividing hepatocytes demonstrated global reduction in newly made RNA and an inverse relationship between DNA density and transcription, driven by DNA condensates at the nuclear periphery devoid of newly made RNA. Collectively, these data support an evolving model of transcriptional plasticity that extends at least to a subset of chromatin at the extreme of condensation as expected of heterochromatin.

Patterned Ultraslippery Surfaces of Stainless Steel Prepared by Femtosecond Laser Ablation for Directional Manipulation of Liquid Droplets.

Slippery liquid-infused porous surfaces (SLIPS) have promising applications in chip laboratories, nanofriction power generation, and microfluidics due to their excellent properties such as good hydrophobicity and low adhesion. However, the self-driven stability of conventionally lubricated surfaces is not high, and the velocity of liquid droplets is difficult to regulate. This greatly limits the potential applications of SLIPS. A strategy is offered to prepare microporous structures of SLIPS directly on a stainless-steel substrate using femtosecond laser processing technology as the main means to realize exhibiting smoothness to liquids. At the same time, the principle of bionics is utilized, the porous structure of SLIPS is combined with the groove structure of rice leaves, or porous structures are combined with the wedge structure of shorebird beak to prepare the three-dimensional structure of SLIPS. Droplets exhibit significant individual anisotropy on three-dimensional (3D) SLIPS of leaf-like groove stripe structure in rice, enabling the precise control of droplet motion direction. When droplets are transported in wedge-shaped SLIPS with an asymmetric structure, the wedge edge can limit the direction of droplet motion while squeezing the droplet to generate Laplace pressure gradient, which achieves continuous self-driven transport of droplets. In addition, based on the above two processing strategies, an information transfer device is designed: the splicing of the self-driven transport surface with anisotropic topological channels enables the differential drive for liquid transport, which provides the conditions for the information transfer of the droplets. This strategy not only is simple and efficient but also provides new ideas for the effective development of multifunctional SLIPS as well as lab-on-a-chip and microfluidic domains.

Electrospun Nanofiber-Based Biosensors for Foodborne Bacteria Detection.

Food contamination has emerged as a significant global health concern, posing substantial challenges to the food industry. Bacteria are the primary cause of foodborne diseases. Consequently, it is crucial to develop accurate and efficient sensing platforms to detect foodborne bacteria in food products. Among various detection methods, biosensors have emerged as a promising solution due to their portability, affordability, simplicity, selectivity, sensitivity, and rapidity. Electrospun nanofibers have gained increasing popularity in enhancing biosensor performance. These nanofibers possess a distinctive three-dimensional structure, providing a large surface area and ease of preparation. This review provides an overview of the electrospinning technique, nanofibers and nanofiber-based biosensors. It also explores their mechanisms and applications in the detection of foodborne bacteria such as Salmonella, Listeria monocytogenes (L. monocytogenes), Escherichia coli (E. coli), Staphylococcus aureus (S. aureus) and Pseudomonas putida (P. putida).

3D bioprinting technology and equipment based on microvalve control.

3D bioprinting technology is widely used in biomedical fields such as tissue regeneration and constructing pathological model. The prevailing printing technique is extrusion-based bioprinting. In this printing method, the bioink needs to meet both printability and functionality, which are often conflicting requirements. Therefore, this study has developed an innovative microvalve-based equipment, incorporating components such as pressure control, a three-dimensional motion platform, and microvalve. Here, we present a droplet-based method for constructing complex three-dimensional structures. By leveraging the rapid switching characteristics of the microvalve, this equipment can achieve precise printing of bio-materials with viscosities as low as 10mPa·s, significantly expanding the biofabrication window for bioinks. This technology is of great significance for 3D bioprinting in tissue engineering and lays a solid foundation for the construction of complex artificial organ tissues.

Conformational fluidity of intrinsically disordered proteins in crowded environment: a molecular dynamics simulation study.

The class of intrinsically disordered proteins lacks stable three-dimensional structures. Their flexibility allows them to engage in a wide variety of interactions with other biomolecules thus making them biologically relevant and efficient. The intrinsic disorders of these proteins, which undergo binding-induced folding, allow alterations in their topologies while conserving their binding sites. Due to the lack of well-defined three-dimensional structures in the absence of their physiological partners, the folding and the conformational dynamics of these proteins remained poorly understood. Particularly, it is unclear how these proteins exist in the crowded intracellular milieu. In the present study, molecular dynamic simulations of two intrinsically unstructured proteins and two controls (folded proteins) were conducted in the presence and absence of molecular crowders to obtain an in-depth insight into their conformational flexibility. The present study revealed that polymer crowders stabilize the disordered proteins through enthalpic as well as entropic effects that are significantly more than their monomeric counterpart. Taken together, the study delves deep into crowding effects on intrinsically disordered proteins and provides insights into how molecular crowders induce a significantly diverse ensemble of dynamic scaffolds needed to carry out diverse functions.Communicated by Ramaswamy H. Sarma.

MIDF-DMAP: Multimodal information dynamic fusion for drug molecule activity prediction

BackgroundComputer-aided drug development can alleviate limitations in drug research and development processes, such as long cycles, high costs, and limited targeting. Deep learning models can be used to predict the activity of drug compound molecules. However, existing models still need to adequately address semantic redundancy, conflicts, and noise between different data modalities. It results in low accuracy in predicting molecular activity and many false positive results that need further resolution. ObjectiveThis study aims to design a parallel deep learning model for processing multimodal molecular information fusion, dynamically adjusting the weights of different modal features during the fusion process. This approach ensures that high-quality modal information is more significant in molecular activity prediction, improving the model’s predictive accuracy. MethodsFirst, three modal features of drug molecules are extracted: one-dimensional fingerprints, two-dimensional topological structures, and three-dimensional geometric structures. Then, a dynamic weighting mechanism is proposed to fuse these three modal features organically. Finally, the fused features are input into the model classifier to obtain molecular activity prediction results. ResultsExperimental results show that the proposed model improved the Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) value by 29.96% compared to the Weave model and 26.38% compared to the GC model on the BBBP dataset. Compared to the GraphMVP model and the multi-channel substructure graph model MSGG, the ROC-AUC value increased by 20.44% and 15.80%, respectively. This method also achieved good results on imbalanced samples and small molecule datasets. ConclusionThis study provides an effective multimodal dynamic fusion method for virtual drug screening, enriching computer-aided drug development theory and improving drug research and development efficiency.

Copper and nickel hexacyanoferrates/carbon nanotube nanocomposites thin films as high-performance light cathode materials for aqueous sodium-ion batteries

Aqueous rechargeable Na-ion batteries are gaining popularity as an attractive alternative for energy storage systems due to their low cost, wide range of raw material sources, non-flammability, and ultrahigh ionic conductivity. Currently, Because of their three-dimensional open structure, high specific capacity, and inexpensive cost, Prussian blue analogues are being investigated as electrode materials for electrochemistry. In this work, we present an innovative strategy to create novel two-component nanoarchitected thin films that exhibit exceptional performance as cathodes in aqueous sodium-ion batteries (SIBs). By leveraging the versatility of the liquid-liquid interfacial method, we have prepared two distinct transparent nanocomposite films composed of carbon nanotubes and either copper or nickel hexacyanoferrate nanoparticles. The results show that the NiHCF/CNT and CuHCF/CNT deliver a high specific capacity of 152 mA h g−1 and 135 mA h g−1, respectively, at a high current density of 1 A g−1. Moreover, the cells (rGO//NiHCF and rGO//CuHCF) show that the energy density of the battery can reach up to 7.75 Wh kg−1 at a power density of 27.92 W kg−1 for rGO//NiHCF/CNT, while rGO//CuHCF/CNT showed an energy density of 3.67 Wh kg−1 at a power density of 13.21 W kg−1. The results demonstrate that NiHCF/CNT and CuHCF/CNT nanocomposite films provide new insight into the design of high-performance PBA cathodes.

Cyclodextrin grafted chitosan thermosensitive hydrogel using dual gelling agents: Drug delivery and antibacterial materials

In this paper, three kinds of cyclodextrin-grafted-chitosan (CD-g-CS) were synthesized from chitosan (CS) and β-cyclodextrin (β-CD) with different ratios. And a series of hydrogel with good temperature sensitivity and injectability were prepared by using sodium glycerophosphate (GP) and ammonium hydrogen phosphate (AHP) as dual gelling agents. The gelation formation time of hydrogel was short, and the shortest time was 0.75 min. The FTIR spectrum and 1H-NMR spectrum showed the structure of the compounds and intermolecular interactions. The molecular docking technique probed the encapsulation mechanism of the drug with β-CD. The SEM results showed that the hydrogel had a highly interconnected three-dimensional spatial structure. The swelling ratio of hydrogel was not less than 150 % within 1 h and the degradation rate of hydrogel was not less than 75 % within 14 days. The in vitro drug release results showed that the hydrogel had optimal sustained release effect, and the cumulative release ratio was 58.3 % in 34 h. The release kinetics analysis exhibited that the hydrogel conformed to the Riter-Peppas model. The hemocompatibility test and cytotoxicity test proved that the hydrogel had good biocompatibility and biosafety. The antibacterial experiments showed that the hydrogel could inhibit the biological activity of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). Therefore, the CD-g-CS/GP-AHP hydrogel has a broad application prospect in the biological fields of drug delivery and antibacterial materials.

Cheminformatic Identification of Tyrosyl-DNA Phosphodiesterase 1 (Tdp1) Inhibitors: A Comparative Study of SMILES-Based Supervised Machine Learning Models.

Tyrosyl-DNA phosphodiesterase 1 (Tdp1) repairs damages in DNA induced by abortive topoisomerase 1 activity; however, maintenance of genetic integrity may sustain cellular division of neoplastic cells. It follows that Tdp1-targeting chemical inhibitors could synergize well with existing chemotherapy drugs to deny cancer growth; therefore, identification of Tdp1 inhibitors may advance precision medicine in oncology. Current computational research efforts focus primarily on molecular docking simulations, though datasets involving three-dimensional molecular structures are often hard to curate and computationally expensive to store and process. We propose the use of simplified molecular input line entry system (SMILES) chemical representations to train supervised machine learning (ML) models, aiming to predict potential Tdp1 inhibitors. An open-sourced consensus dataset containing the inhibitory activity of numerous chemicals against Tdp1 was obtained from Kaggle. Various ML algorithms were trained, ranging from simple algorithms to ensemble methods and deep neural networks. For algorithms requiring numerical data, SMILES were converted to chemical descriptors using RDKit, an open-sourced Python cheminformatics library. Out of 13 optimized ML models with rigorously tuned hyperparameters, the random forest model gave the best results, yielding a receiver operating characteristics-area under curve of 0.7421, testing accuracy of 0.6815, sensitivity of 0.6444, specificity of 0.7156, precision of 0.6753, and F1 score of 0.6595. Ensemble methods, especially the bootstrap aggregation mechanism adopted by random forest, outperformed other ML algorithms in classifying Tdp1 inhibitors from non-inhibitors using SMILES. The discovery of Tdp1 inhibitors could unlock more treatment regimens for cancer patients, allowing for therapies tailored to the patient's condition.