Binding Affinity Research Articles

The potency of <i>Elaeocarpus grandiflorus </i>Leaf Extract as Anti-obesity: <i>in vivo </i>and <i>in silico</i> Study

The research aims to determine the effect of ethanol extract of Elaeocarpus grandiflorus leaves extract as anti-obesity by in vivo and silico computational models. The pre-and -post-tests were carried out on 20 female Wistar rats, divided into 4 groups. The control group (K) received no treatment and the experimental groups were treated with E. grandiflorus extract of 200 mg/kg BW (P1), 400 mg/kg BW (P2), and 800 mg/kg BW (P3) for 14 days. The body weight, abdominal circumference, and abdominal fat mass were measured on Day 1 and Day 15. The results showed differences in body weight (p=0.02), abdominal circumference (p=0.01), and abdominal fat mass (p=0.00). In silico exploration, bioactive compounds of rutin, orientin, luteolin, vitexin, iso orientin, isovitexin, kaempferol, and quercetin were identified, and targeted ELAVL1, IGF1R, CREB1, AKT1, and PIK3R1 of the AMPK signaling pathway that involved in the anti-obesity mechanism. The high binding affinity values was rutin-EVAL1 (-9.3), orientin-ELAVL1 (-8.3), and quercetin- IGFR1 (-8.2). It can be concluded that the ethanol extract of E. grandiflorus leaves has the potential to be developed as an anti-obesity agent.

Utilization of a Branched Late-Stage Clickable Biotinylated Chassis on the Example of a Pittsburgh B Analogue.

Biotinylation is probably the most frequent and practically useful modification of molecules to facilitate selective and highly affine binding to (strept)avidin for immobilization, enrichment, and purification for further (bio)chemical or (bio)physical investigations. We present a protecting-group-free synthesis of a branched biotin bis-azide that enables dual-payload late-stage functionalization with arbitrary alkynes via click chemistry. Utility of the chassis is briefly showcased on the example of a valuable Pittsburgh B analogue, which binds pathological protein aggregates, commonly found in neurodegenerative diseases.

Enhancing Bioactivity of N,N,N-Chelating Rhodium(III) Complexes with Ionic Liquids: Toward Targeted Cancer Therapy.

This study investigates the potential of using ionic liquids as cosolvents to enhance the solubility and activity of poorly soluble rhodium(III) complexes, particularly those with diene, pyridine derivatives, and camphor-derived bis-pyrazolylpyridine ligands, in relation to 5'-GMP, CT-DNA, and HSA as well as their biological activity. Findings indicate that ionic liquids significantly increase the substitution activity of these complexes toward 5'-GMP while only marginally affecting DNA/HSA binding affinities with molecular docking, further confirming the experimental results. Lipophilicity assessments indicated good lipophilicity. Notably, cytotoxicity studies show that Rh2 is selectively effective against HeLa cancer cells, with IL1 and IL10 modulating the cytotoxic effects. Redox evaluations indicate that rhodium complexes induce oxidative stress in cancerous cells while maintaining redox balance in noncancerous cells. By elucidating the role of ionic liquids in modulating these effects, the study proposes a promising avenue for augmenting the efficacy and selectivity of cancer treatments, thus opening new horizons in cancer therapeutics.

Design, Synthesis and Antitumor Activity of a Novel Class of SHP2 Allosteric Inhibitors with a Furanyl Amide-Based Scaffold.

SHP2 plays a critical role in modulating tumor growth and PD-1-related signaling pathway, thereby serving as an attractive antitumor target. To date, no antitumor drugs targeting SHP2 have been approved, and hence, the search of SHP2 inhibitors with new chemical scaffolds is urgently needed. Herein, we developed a novel SHP2 allosteric inhibitor SDUY038 with a furanyl amide scaffold, demonstrating potent binding affinity (KD = 0.29 μM), enzymatic activity (IC50 = 1.2 μM) and similar binding interactions to SHP099. At the cellular level, SDUY038 exhibited pan-antitumor activity (IC50 = 7-24 μM) by suppressing pERK expression. Furthermore, SDUY038 significantly inhibited tumor growth in both xenograft and organoid models. Additionally, SDUY038 displayed acceptable bioavailability (F = 14%) and half-life time (t1/2 = 3.95 h). Conclusively, this study introduces the furanyl amide scaffold as a novel class of SHP2 allosteric inhibitors, offering promising lead compounds for further development of new antitumor therapies targeting SHP2.

Differential conformational dynamics in two type-A RNA-binding domains drive the double-stranded RNA recognition and binding.

Trans-activation response (TAR) RNA-binding protein (TRBP) has emerged as a key player in the RNA interference pathway, wherein it binds to different pre-microRNAs (miRNAs) and small interfering RNAs (siRNAs), each varying in sequence and/or structure. We hypothesize that TRBP displays dynamic adaptability to accommodate heterogeneity in target RNA structures. Thus, it is crucial to ascertain the role of intrinsic and RNA-induced protein dynamics in RNA recognition and binding. We have previously elucidated the role of intrinsic and RNA-induced conformational exchange in the double-stranded RNA-binding domain 1 (dsRBD1) of TRBP in shape-dependent RNA recognition. The current study delves into the intrinsic and RNA-induced conformational dynamics of the TRBP-dsRBD2 and then compares it with the dsRBD1 study carried out previously. Remarkably, the two domains exhibit differential binding affinity to a 12-bp dsRNA owing to the presence of critical residues and structural plasticity. Furthermore, we report that dsRBD2 depicts constrained conformational plasticity when compared to dsRBD1. Although, in the presence of RNA, dsRBD2 undergoes induced conformational exchange within the designated RNA-binding regions and other residues, the amplitude of the motions remains modest when compared to those observed in dsRBD1. We propose a dynamics-driven model of the two tandem domains of TRBP, substantiating their contributions to the versatility of dsRNA recognition and binding.

Design, synthesis and evaluation of novel norfloxacin analogs as potent anticancer and antioxidant agents.

Aim: To synthesize a novel series of norfloxacin analogs and to evaluate biological activity. Methodology: Novel norfloxacin analogs were synthesized and characterized by NMR and mass spectrometry. Antiproliferative and antioxidant properties were studied. Results: Compound 2f was the most potent against HeLa cell-line with 100% inhibition of cell viability IC50=3.1±0.2μM. All compounds exhibit moderate to excellent antioxidant properties. Docking study demonstrates higher binding affinity of compounds with respective anticancer (B-cell lymphoma-2) and (tyrosinase) antioxidant targets. In silico absorption, distribution, metabolism and excretion profile of compounds proves all synthesized compounds follow Lipinski's rule of drug likeness, non toxic and possess passive gastrointestinal absorption. Conclusion: The biological profile suggest that the synthesized norfloxacin analogs can be a novel scaffold for future anticancer drug development.

(SiFA)SeFe: A Hydrophilic Silicon-Based Fluoride Acceptor Enabling Versatile Peptidic Radiohybrid Tracers.

The radiohybrid (rh) concept to design targeted (and chemically identical) radiotracers for imaging or radionuclide therapy of tumors has gained momentum. For this strategy, a new bifunctional Silicon-based Fluoride Acceptor (SiFA) moiety (SiFA)SeFe was synthesized, endowed with improved hydrophilicity and high versatility of integration into rh-compounds. Preliminary radiolabeling and stability studies under different conditions were conducted using model bioconjugate peptides. Further, three somatostatin receptor 2 (sstR2)-targeted rh-compounds ((SiFA)SeFe-rhTATE1-3, TATE = (Tyr3)-octreotate) were developed. Compound (SiFA)SeFe-rhTATE3, enables labeling with 18F for PET imaging or chelation of 177Lu for therapy. The rh-compounds possess comparable receptor binding affinity and in vitro performance as good as the clinically proven gold standards. SstR2-specificity was further shown for (SiFA)SeFe-rhTATE2 using the chicken chorioallantoic membrane (CAM) model. The biodistribution of two compounds in mice showed high accumulation in tumors and excretion via the kidneys, demonstrating the clinical applicability of the (SiFA)SeFe moiety.

Deciphering GB1's Single Mutational Landscape: Insights from MuMi Analysis.

Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we perform in silico mutational scanning for all possible single mutations, along with 2 μs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. In sum, our findings highlight the potential of MuMi as a reliable and computationally efficient tool for predicting protein fitness landscapes, offering significant advantages over traditional methods. The methodologies and results presented in this study pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.

Engineering a Novel Probiotic Toolkit in Escherichia coli Nissle 1917 for Sensing and Mitigating Gut Inflammatory Diseases.

Inflammatory bowel disease (IBD) is characterized by chronic intestinal inflammation with no cure and limited treatment options that often have systemic side effects. In this study, we developed a target-specific system to potentially treat IBD by engineering the probiotic bacterium Escherichia coli Nissle 1917 (EcN). Our modular system comprises three components: a transcription factor-based sensor (NorR) capable of detecting the inflammation biomarker nitric oxide (NO), a type 1 hemolysin secretion system, and a therapeutic cargo consisting of a library of humanized anti-TNFα nanobodies. Despite a reduction in sensitivity, our system demonstrated a concentration-dependent response to NO, successfully secreting functional nanobodies with binding affinities comparable to the commonly used drug Adalimumab, as confirmed by enzyme-linked immunosorbent assay and in vitro assays. This newly validated nanobody library expands EcN therapeutic capabilities. The adopted secretion system, also characterized for the first time in EcN, can be further adapted as a platform for screening and purifying proteins of interest. Additionally, we provided a mathematical framework to assess critical parameters in engineering probiotic systems, including the production and diffusion of relevant molecules, bacterial colonization rates, and particle interactions. This integrated approach expands the synthetic biology toolbox for EcN-based therapies, providing novel parts, circuits, and a model for tunable responses at inflammatory hotspots.

Lithium chloride selective ion-pair recognition by heteroditopic [2]rotaxanes.

The first heteroditopic [2]rotaxane host systems capable of strong and selective binding of lithium chloride ion-pair species are described. Importantly, a cooperative 'switch on' mechanism was found to operate, in which complexation of a lithium metal cation enhances the halide anion affinity of the rotaxanes via a combination of favourable proximal electrostatic and preorganised allosteric effects. The mechanically bonded rotaxane host design features a macrocycle component possessing a 2,6-dialkoxy pyridyl cation binding motif and an isophthalamide anion binding group, as well as an axle component functionalised with either a halogen bonding (XB) iodotriazole or hydrogen bonding (HB) prototriazole moiety. Extensive quantitative 1H NMR titration studies in CD3CN/CDCl3 solvent mixtures determined enhanced ion-pair binding affinities for lithium halides over the corresponding sodium or potassium halide salts, with the axle prototriazole-containing HB rotaxane in particular demonstrating a marked selectivity for lithium chloride. Solid-state X-ray crystallographic studies and computational DFT investigations provide evidence for a [2]rotaxane host axle-separated ion-pair binding mode, in which complementary cation and anion binding motifs from both the macrocycle and axle components act convergently to recognise each of the charged guest species.

Synthesis of new two 1,2-disubstituted benzimidazole compounds: their in vitro anticancer and in silico molecular docking studies

In this study, two new molecules were synthesized from the reaction of 2-methyl-1H-benzo[d]imidazole with aryl halides in the presence of a strong base. The structures newly of synthesized 1,2-disubstituted benzimidazole compounds were characterized using spectroscopic techniques (FT-IR, 1HNMR, 13CNMR) and chromatographic technique (LC/MS). For discovering an effective anticancer drug, the developed heterocyclic compounds were screened against three different human cancer cell lines (A549, DLD-1, and L929). The results demonstrated that of IC50 values of compound 2a were higher as compared to cisplatin for the A549 and DLD-1 cell lines. The frontier molecular orbital (FMO), and molecular electrostatic potential map (MEP) analyses were studied by using DFT (density functional theory) calculations at B3LYP/6-31G** level of theory. The molecular docking studies of the synthesized compound with lung cancer protein, PDB ID: 1M17, and colon cancer antigen proteins, PDB ID: 2HQ6 were performed to compare with experimental and theoretical data. Compound 2a had shown the best binding affinity with -6.6 kcal/mol. It was observed that the theoretical and experimental studies carried out supported each other.

Unveiling novel insights into human IL-6 − IL-6R interaction sites through 3D computer-guided docking and systematic site mutagenesis

The cytokine interleukin-6 (IL-6) plays a crucial role in autoimmune and inflammatory diseases. Understanding the precise mechanism of IL-6 interaction at the amino acid level is essential to develop IL-6-inhibiting compounds. In this study, we employed computer-guided drug design tools to predict the key residues that are involved in the interaction between IL-6 and its receptor IL-6R. Subsequently, we generated IL-6 mutants and evaluated their binding affinity to IL-6R and the IL-6R − gp130 complex, as well as monitoring their biological activities. Our findings revealed that the R167A mutant exhibited increased affinity for IL-6R, leading to enhanced binding to IL-6R − gp130 complex and subsequently elevated intracellular phosphorylation of STAT3 in effector cells. On the other hand, although E171A reduced its affinity for IL-6R, it displayed stronger binding to the IL-6R − gp130 complex, thereby enhancing its biological activity. Furthermore, we identified the importance of R178 and R181 for the precise recognition of IL-6 by IL-6R. Mutants R181A/V failed to bind to IL-6R, while maintaining an affinity for the IL-6 − gp130 complex. Additionally, deletion of the D helix resulted in complete loss of IL-6 binding affinity for IL-6R. Overall, this study provides valuable insights into the binding mechanism of IL-6 and establishes a solid foundation for future design of novel IL-6 inhibitors.

GalaxyDock-DL: Protein-Ligand Docking by Global Optimization and Neural Network Energy.

With the recent introduction of deep learning techniques into the prediction of biomolecular structures, structure prediction performance has significantly improved, and the potential for biomedical applications has increased considerably. The prediction of protein-ligand complex structures, applicable to the atomistic understanding of biomolecular functions and the effective design of drug molecules, has also improved with the introduction of deep learning. In this paper, it is demonstrated that docking performance can be greatly enhanced by training an energy function that encapsulates physical effects using deep learning within the framework of the traditional protein-ligand docking method. The advantage of this method, called GalaxyDock-DL, lies in its minimal overfitting to the training data compared to several existing deep learning-based protein-ligand docking methods. Unlike some recent deep learning methods, it does not use information about known binding pocket center positions. Instead, the results of this docking method show a systematic dependence on the physical properties of the target protein-ligand complexes such as atomic thermal fluctuations and binding affinity. GalaxyDock-DL utilizes the global optimization technique of the conventional protein-ligand docking method, GalaxyDock, and a neural network energy function trained to stabilize the native state compared to non-native states, just as physical free energy does. This physical principle-based approach suggests directions not only for future structure prediction involving structurally flexible biomolecular complexes but also for predicting binding affinity, thereby providing guidance for the effective design of biofunctional ligands.

Identification of Potential Drug Targets for Myopia Through Mendelian Randomization.

The purpose of this study was to identify potential drug targets for myopia and explore underlying mechanisms. Mendelian randomization (MR) was implemented to assess the effect of 2684 pharmacologically targetable genes in the blood and retina on the risk of myopia from a genomewide association study (GWAS) for age-at-onset of spectacle wearing-inferred mean spherical equivalent (MSE; discovery cohort, N = 287,448, European), which was further validated in a GWAS for autorefraction-measured MSE (replication cohort, N = 95,619, European). The reliability of the identified significant potential targets was strengthened by colocalization analysis. Additionally, enrichment analysis, protein-protein interaction network, and molecular docking were performed to explore the functional roles and the druggability of these targets. This systematic drug target identification has unveiled 6 putative genetically causal targets for myopia-CD34, CD55, Wnt3, LCAT, BTN3A1, and TSSK6-each backed by colocalization evidence in adult blood eQTL datasets. Functional analysis found that dopaminergic neuron differentiation, cell adhesion, Wnt signaling pathway, and plasma lipoprotein-associated pathways may be involved in myopia pathogenesis. Finally, drug prediction and molecular docking corroborated the pharmacological value of these targets with LCAT demonstrating the strongest binding affinity. Our study not only opens new avenues for the development of therapeutic interventions for myopia but may also help to understand the underlying mechanisms of myopia.

In Silico Approach for Assessment of the Anti-tumor Potential of Cannabinoid Compounds by Targeting Glucose-6-phosphate Dehydrogenase Enzyme.

Glucose-6-phosphate dehydrogenase (G6PD) is a pentose phosphate pathway (PPP) enzyme that generates NADPH, which is required for cellular redox equilibrium and reductive biosynthesis. It has been demonstrated that abnormal G6PD activation promotes cancer cell proliferation and metastasis. To date, no G6PD inhibitor has passed clinical testing successfully enough to be launched as a medicine. As a result, in this investigation, cannabinoids were chosen to evaluate their anticancer potential by targeting G6PD. Molecular docking indicated that three molecules, Tetrahydrocannabinolic acid (THCA), Cannabichromenic acid (CBCA), and tetrahydrocannabivarin (THCV), have the highest binding affinities for G6PD of -8.61, - 8.39, and 8.01 Kcal/mol. ADMET analysis found that all of them were safe prospective drug candidates. Molecular dynamics (MD) simulation and MM-PBSA analysis confirm the structural compactness and lower conformational variation of protein-ligand complexes, thereby maintaining structural stability and rigidity. Thus, our in silico investigation exhibited all three cannabinoids as potential competitive inhibitors of G6PD.

Highly Efficient Separation of Intermediate-Sizem-Xylene from Xylenes via a Length-Matched Metal-Organic Framework with Optimal Oxygen Sites Distribution.

Xylene separation is crucial but challenging, especially for the preferential separation of the intermediate-size m-xylene from xylene mixtures. Herein, exploiting the differences in molecular length and alkyl distribution among xylenes, we present a length-matched metal-organic framework, formulated as Al(OH)[O2C-C4H2O-CO2], featuring an effectivepore size corresponding to m-xylene molecular length combined with multiple negative O hydrogen bond donors distribution, can serve as a molecular trap for efficient preferential separation of the intermediate-size m-xylene. Benchmark separation performance was achieved for separating m-xylene from a ternary mixture of m-xylene/o-xylene/p-xylene, with simultaneous record-high m-xylene uptake (1.3 mmol g-1) and m-xylene/p-xylene selectivity (5.3) in the liquid-phase competitive adsorption. Both vapor- and liquid-phase fixed-bed tests confirmed its practical separation capability with benchmark dynamic m-xylene/p-xylene and m-xylene/o-xylene selectivities, as well as excellent regenerability. The selective and strong m-xylene binding affinity among xylene molecules was further elucidated by simulations, validating the effectiveness of such a pore environment for the separation of intermediate-size molecules.

Membrane prewetting by condensates promotes tight-junction belt formation.

Biomolecular condensates enable cell compartmentalization by acting as membraneless organelles1. How cells control the interactions of condensates with other cellular structures such as membranes to drive morphological transitions remains poorly understood. We discovered that formation of a tight-junction belt, which is essential for sealing epithelial tissues, is driven by a wetting phenomenon that promotes the growth of a condensed ZO-1 layer2 around the apical membrane interface. Using temporal proximity proteomics in combination with imaging and thermodynamic theory, we found that the polarity protein PATJ mediates a transition of ZO-1 into a condensed surface layer that elongates around the apical interface. In line with the experimental observations, our theory of condensate growth shows that the speed of elongation depends on the binding affinity of ZO-1 to the apical interface and is constant. Here, using PATJ mutations, we show that ZO-1 interface binding is necessary and sufficient for tight-junction belt formation. Our results demonstrate how cells exploit the collective biophysical properties of protein condensates at membrane interfaces to shape mesoscale structures.

Exploring the Anticancer Potential of Furanpydone A: A Computational Study on its Inhibition of MTHFD2 Across Diverse Cancer Cell Lines.

Cancer poses a significant global health challenge due to its high mortality rate and complex treatment strategies. Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), which is notably overexpressed in various malignancies, represents a promising target for anticancer drug development. Furanpydone A, a new 4-hydroxy-2-pyridone alkaloid isolated from the endophytic fungus Arthrinium sp. GZWMJZ-606, has shown potent inhibitory activity against several cancer cell lines. This study provides the first computational evaluation of furanpydone A, focusing on its potential inhibition of MTHFD2 through molecular docking and 200 ns molecular dynamics (MD) simulations. Molecular docking revealed a binding free energy of -8.08 kcal/mol for furanpydone A, comparable to the control compound DS44960156 (-8.13 kcal/mol), indicating stable interactions with the MTHFD2 active site. MD simulations confirmed the structural stability of the furanpydone A-MTHFD2 complex, with RMSD values ranging from 1.5 to 2.9 Å, RMSF values below 4 Å, and a radius of gyration (Rg) of 26.7 Å. Furanpydone A maintained approximately four consistent hydrogen bonds throughout the simulation. Analysis of furanpydone A binding pose orientations and interactions with the MTHFD2 enzyme at 0 ns, 40 ns, 80 ns, 120 ns, 160 ns, and 200 ns revealed consistent and stable binding. MM-PBSA analysis showed a binding free energy (ΔGbind) of -23.57 ± 0.13 kcal/mol, with electrostatic and van der Waals interactions contributing significantly, suggesting competitive binding affinity to the control compound (-25.32 ± 0.11 kcal/mol). The contribution of individual amino acid residues, including key residues such as ARG43, TYR84, ASN87, LYS88, GLN132, and PRO314, indicated strong interactions that support the stability of the furanpydone A-MTHFD2 complex. ADMET predictions indicated that furanpydone A met key drug-likeness criteria and demonstrated good oral bioavailability, suitable distribution profile, minimal risk of drug-drug interactions, efficient elimination, and low toxicity potential. These findings suggest that furanpydone A is a promising candidate for cancer treatment, warranting further in vitro and in vivo validation, and highlighting its potential impact on the development of new anticancer therapies.

Semisynthetic guanidino lipoglycopeptides with potent in vitro and in vivo antibacterial activity.

Gram-positive bacterial infections present a major clinical challenge, with methicillin- and vancomycin-resistant strains continuing to be a cause for concern. In recent years, semisynthetic vancomycin derivatives have been developed to overcome this problem as exemplified by the clinically used telavancin, which exhibits increased antibacterial potency but has also raised toxicity concerns. Thus, glycopeptide antibiotics with enhanced antibacterial activities and improved safety profiles are still necessary. We describe the development of a class of highly potent semisynthetic glycopeptide antibiotics, the guanidino lipoglycopeptides, which contain a positively charged guanidino moiety bearing a variable lipid group. These glycopeptides exhibited enhanced in vitro activity against a panel of Gram-positive bacteria including clinically relevant methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant strains, showed minimal toxicity toward eukaryotic cells, and had a low propensity for resistance selection. Mechanistically, guanidino lipoglycopeptides engaged with bacterial cell wall precursor lipid II with a higher binding affinity than vancomycin. Binding to both wild-type d-Ala-d-Ala lipid II and the vancomycin-resistant d-Ala-d-Lac variant was confirmed, providing insight into the enhanced activity of guanidino lipoglycopeptides against vancomycin-resistant isolates. The in vivo efficacy of guanidino lipoglycopeptide EVG7 was evaluated in a S. aureus murine thigh infection model and a 7-day sepsis survival study, both of which demonstrated superiority to vancomycin. Moreover, the minimal to mild kidney effects at supratherapeutic doses of EVG7 indicate an improved therapeutic safety profile compared with vancomycin. These findings position guanidino lipoglycopeptides as candidates for further development as antibacterial agents for the treatment of clinically relevant multidrug-resistant Gram-positive infections.

Exploring novel Apalutamide analogues as potential therapeutics for prostate cancer: design, molecular docking investigations and molecular dynamics simulation

Introduction: Prostate cancer (PC) ranks as the second most frequent type of cancer in men and is the fourth largest cause of mortality worldwide. Androgenic hormones such as testosterone and dihydrotestosterone are crucial for the development and progression of the prostate gland. Androgenic hormones bind to androgen receptors (AR) and trigger the synthesis of many genes that stimulate the growth of prostate cells, initiating PC growth. Apalutamide (APL) is a non-steroidal antiandrogen drug used to treat PC; however, it also causes a variety of toxicities and resistance during the treatment.Methods: The purpose of this study was to computationally identify new and safer analogues of APL, focusing on improved pharmacokinetic properties and reduced toxicity. Drug likeness (DL) and drug score (DS) were also calculated. Docking studies on the designed analogues were conducted to predict their binding affinities and compare their orientations with the ligands in the original crystal structure. Molecular dynamics (MD) simulation of docked ligands was done using Schrödinger suite.Results: We generated a total of 1,415 analogues for different groups of APL using the bioisosteric approach. We selected 80 bioisosteres based on pharmacokinetic profiles, DL and DS score predictions, and found that the designed APL bioisosteres were optimal to good compared to APL. Analogues APL19, APL35, APL43, APL76, and APL80, formed hydrogen bonds with protein (PDB ID: 5T8E) which is similar hydrogen bonding to the standard (APL). The MD simulation result confirmed that APL43 and APL80 complexes were stable during the 100 nS run.Discussion: The results suggest that the APL analogues, particularly APL43 and APL80, are predicted to be potential antiandrogen drugs for the treatment of prostate cancer.