Structure-based Design Research Articles

Utilizing a structure-based virtual screening approach to discover potential LSD1 inhibitors

BackgroundLysine-specific demethylase 1 (LSD1) is highly expressed in a variety of malignant tumors, rendering it a crucial epigenetic target for anti-tumor therapy. Therefore, the inhibition of LSD1 activity has emerged as a promising innovative therapeutic approach for targeted cancer treatment.MethodsIn our study, we employed innovative structure-based drug design methods to meticulously select compounds from the ZINC15 database. Utilizing virtual docking, we evaluated docking scores and binding modes to identify potential inhibitors. To further validate our findings, we harnessed molecular dynamic simulations and conducted meticulous biochemical experiments to deeply analyze the binding interactions between the protein and compounds.ResultsOur results showcased that ZINC10039815 exhibits an exquisite binding mode with LSD1, fitting perfectly into the active pocket and forming robust interactions with multiple critical residues of the protein.ConclusionsWith its significant inhibitory effect on LSD1 activity, ZINC10039815 emerges as a highly promising candidate for the development of novel LSD1 inhibitors.

Leveraging the Fragment Molecular Orbital and MM-GBSA Methods in Virtual Screening for the Discovery of Novel Non-Covalent Inhibitors Targeting the TEAD Lipid Binding Pocket.

The Hippo pathway controls organ size and homeostasis and is linked to numerous diseases, including cancer. The transcriptional enhanced associate domain (TEAD) family of transcription factors acts as a receptor for downstream effectors, namely yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), which binds to various transcription factors and is essential for stimulated gene transcription. YAP/TAZ-TEAD facilitates the upregulation of multiple genes involved in evolutionary cell proliferation and survival. TEAD1-4 overexpression has been observed in different cancers in various tissues, making TEAD an attractive target for drug development. The central drug-accessible pocket of TEAD is crucial because it undergoes a post-translational modification called auto-palmitoylation. Crystal structures of the C-terminal TEAD complex with small molecules are available in the Protein Data Bank, aiding structure-based drug design. In this study, we utilized the fragment molecular orbital (FMO) method, molecular dynamics (MD) simulations, shape-based screening, and molecular mechanics-generalized Born surface area (MM-GBSA) calculations for virtual screening, and we identified a novel non-covalent inhibitor-BC-001-with IC50 = 3.7 μM in a reporter assay. Subsequently, we optimized several analogs of BC-001 and found that the optimized compound BC-011 exhibited an IC50 of 72.43 nM. These findings can be used to design effective TEAD modulators with anticancer therapeutic implications.

Design, synthesis, biological evaluation of novel piperidine-based derivatives as potent poly(ADP-ribose) polymerase-1 (PARP-1) inhibitors

Poly(ADP-ribose) polymerase-1 (PARP-1) is a crucial member of DNA repair enzymes responsible for repairing DNA single-strand breaks. Developing PARP inhibitors based on synthetic lethality strategies is an effective approach for treating breast cancer and other diseases. In this study, a series of novel piperidine-based benzamide derivatives were designed and synthesized using structure-based drug design principles. The anticancer activities of these compounds were evaluated against five human cancer cell lines (MDA-MB-436, CAPAN-1, SW-620, HepG2, SKOV3, and PC3) and the preliminary structure–activity relationships were delineated. Among the compounds, 6a and 15d demonstrated potent antiproliferative effects against MDA-MB-436 cells with IC50 values of 8.56 ± 1.07 μM and 6.99 ± 2.62 μM, respectively. Furthermore, both compounds exhibited excellent inhibitory activity against PARP-1, with IC50 values of 8.33 nM and 12.02 nM, respectively. Mechanistic investigations revealed that 6a and 15d effectively inhibited colony formation and cell migration of HCT116 cells. Moreover, they induced apoptosis by upregulating the expression of Bax and cleaved Caspase-3, while downregulating the expression of Caspase-3 and Bcl-2 in HCT116 cells. Based on its impressive pharmacodynamic data in vitro, we conducted a study to evaluate the efficacy of 15d in a xenograft tumor model in mice when used in combination with cytotoxic agents. Collectively, these findings suggest that 15d could be promising drug candidates worthy of further investigation.

Development of a Fluorescent Assay and Imidazole-Containing Inhibitors by Targeting SARS-CoV-2 Nsp13 Helicase.

Nsp13, a non-structural protein belonging to the coronavirus family 1B (SF1B) helicase, exhibits 5'-3' polarity-dependent DNA or RNA unwinding using NTPs. Crucially, it serves as a key component of the viral replication-transcription complex (RTC), playing an indispensable role in the coronavirus life cycle and thereby making it a promising target for broad-spectrum antiviral therapies. The imidazole scaffold, known for its antiviral potential, has been proposed as a potential scaffold. In this study, a fluorescence-based assay was designed by labeling dsDNA substrates with a commercial fluorophore and monitoring signal changes upon Nsp13 helicase activity. Optimization and high-throughput screening validated the feasibility of this approach. In accordance with the structural characteristics of ADP, we employed a structural-based design strategy to synthesize three classes of imidazole-based compounds through substitution reaction. Through in vitro activity research, pharmacokinetic parameter analysis, and molecular docking simulation, we identified compounds A16 (IC50 = 1.25 μM) and B3 (IC50 = 0.98 μM) as potential lead antiviral compounds for further targeted drug research.

FragGrow: A Web Server for Structure-Based Drug Design by Fragment Growing within Constraints.

Fragment growing is an important ligand design strategy in drug discovery. In this study, we present FragGrow, a web server that facilitates structure-based drug design by fragment growing. FragGrow offers two working modes: one for growing molecules through the direct replacement of hydrogen atoms or substructures and the other for growing via virtual synthesis. FragGrow works by searching for suitable fragments that meet a set of constraints from an indexed 3D fragment database and using them to create new compounds in 3D space. The users can set a range of constraints when searching for their desired fragment, including the fragment's ability to interact with specific protein sites; its size, topology, and physicochemical properties; and the presence of particular heteroatoms and functional groups within the fragment. We hope that FragGrow will serve as a useful tool for medicinal chemists in ligand design. The FragGrow server is freely available to researchers and can be accessed at https://fraggrow.xundrug.cn.

Improving the artificial bee colony algorithm with a proprietary estimation of distribution mechanism for protein–ligand docking

The protein–ligand docking problem plays an essential role in structure-based drug design. The challenge for a protein–ligand docking method is how to execute an efficient conformational search to explore a well-designed scoring function. In this study, we improved the artificial bee colony (ABC) algorithm and proposed an approach called ABC-EDM to solve the protein–ligand docking problem. ABC-EDM employs the scoring function of the classical AutoDock Vina to evaluate a solution during docking simulation. ABC-EDM adopts the search framework of the canonical ABC algorithm to execute conformational search. By further investigating the characteristics of the protein–ligand docking problem, a proprietary search mechanism inspired by estimation of distribution algorithm, i.e., estimation of distribution mechanism (EDM), is designed to enhance the performance of ABC-EDM. To verify the effectiveness of the proposed ABC-EDM, we compare it with three variants of the ABC algorithm, three evolutionary computation algorithms, and AutoDock Vina. The experimental results show that ABC-EDM can effectively solve the protein–ligand docking problem, and it can achieve a success rate 5% higher than AutoDock Vina on the GOLD dataset. This study reveals that taking advantage of problem-specific information about the protein–ligand docking problem to enhance a docking method contributes to solving this problem.

The discovery of a novel pyrrolo[2,3-b]pyridine as a selective CDK8 inhibitor offers a new approach against psoriasis

Currently, the drugs used in clinical to treat psoriasis mainly broadly suppress cellular immunity. However, these drugs can only provide temporary and partial symptom relief, they do not cure the condition and may lead to recurrence or even serious toxic side effects. In this study, we describe the discovery of a novel potent CDK8 inhibitor as a treatment for psoriasis. Through structure-based design, compound 46 was identified as the most promising candidate, exhibiting a strong inhibitory effect on CDK8 (IC50 value of 57 nM) along with favourable inhibition against NF-κB. Additionally, it demonstrated a positive effect in an in vitro psoriasis model induced by TNF-α. Furthermore, this compound enhanced the thermal stability of CDK8 and exerted evident effects on the biological function of CDK8, and it had favourable selectivity across the CDK family and tyrosine kinase. This compound showed no obvious inhibitory effect on CYP450 enzyme. Further studies confirmed that compound 46 exhibited therapeutic effect on IMQ-induced psoriasis, alleviated the inflammatory response in mice, and enhanced the expression of Foxp3 and IL-10 in the dorsal skin in vivo. This discovery provides a new strategy for developing selective CDK8 inhibitors with anti-inflammatory activity for the treatment of psoriasis.

Structure-Based Discovery of Allosteric Inhibitors Targeting a New Druggable Site in the Respiratory Syncytial Virus Polymerase.

Respiratory syncytial virus (RSV) is a major cause of severe lower respiratory infections for which effective treatment options remain limited. Herein, we employed a computational structure-based design strategy aimed at identifying potential targets for a new class of allosteric inhibitors. Our investigation led to the discovery of a previously undisclosed allosteric binding site within the RSV polymerase, the large (L) protein. This discovery was achieved through a combination of virtual screening and molecular dynamics simulations. Subsequently, we identified two inhibitors, 6a and 10b, which both exhibited promising antiviral activity in the low micromolar range. Resistance profiling revealed a distinctive pattern in how RSV evaded treatment with this class of inhibitors. This pattern strongly suggested that this class of small molecules was targeting a new binding site in the RSV L protein, aligning with the computational predictions made in our study. This study paves the way for the development of more potent inhibitors for combating RSV infections by targeting a new druggable pocket within the RdRp which does not overlap with previously known resistance sites.

MzDOCK: A free ready-to-use GUI-based pipeline for molecular docking simulations.

Molecular docking is by far the most preferred approach in structure-based drug design for its effectiveness to predict the scoring and posing of a given bioactive small molecule into the binding site of its pharmacological target. Herein, we present MzDOCK, a new GUI-based pipeline for Windows operating system, designed with the intent of making molecular docking easier to use and higher reproducible even for inexperienced people. By harmonic integration of python and batch scripts, which employs various open source packages such as Smina (docking engine), OpenBabel (file conversion) and PLIP (analysis), MzDOCK includes many practical options such as: binding site configuration based on co-crystallized ligands; generation of enantiomers from SMILES input; application of different force fields (MMFF94, MMFF94s, UFF, GAFF, Ghemical) for energy minimization; retention of selectable ions and cofactors; sidechain flexibility of selectable binding site residues; multiple input file format (SMILES, PDB, SDF, Mol2, Mol); generation of reports and of pictures for interactive visualization. Users can download for free MzDOCK at the following link: https://github.com/Muzatheking12/MzDOCK.

Structure-Based Design of Novel Thiazolone[3,2-a]pyrimidine Derivatives as Potent RNase H Inhibitors for HIV Therapy.

Ribonuclease H (RNase H) was identified as an important target for HIV therapy. Currently, no RNase H inhibitors have reached clinical status. Herein, a series of novel thiazolone[3,2-a]pyrimidine-containing RNase H inhibitors were developed, based on the hit compound 10i, identified from screening our in-house compound library. Some of these derivatives exhibited low micromolar inhibitory activity. Among them, compound 12b was identified as the most potent inhibitor of RNase H (IC50 = 2.98 μM). The experiment of magnesium ion coordination was performed to verify that this ligand could coordinate with magnesium ions, indicating its binding ability to the catalytic site of RNase H. Docking studies revealed the main interactions of this ligand with RNase H. A quantitative structure activity relationship (QSAR) was also conducted to disclose several predictive mathematic models. A molecular dynamics simulation was also conducted to determine the stability of the complex. Taken together, thiazolone[3,2-a]pyrimidine can be regarded as a potential scaffold for the further development of RNase H inhibitors.

Synthesis, molecular dynamics, antimicrobial activity and wound healing application of new methylidene dyes based on pyrrolinone esters

A new methylidene dye based on the direct condensation of an aldehyde derivative with a pyrrolinone ester derivative was successfully prepared as well as its quaternary ammonium salt analogue. The structures of all synthesized dyes were confirmed using NMR, Mass and IR spectra. The absorption and emission spectra of the synthesized dyes were investigated. The synthesized methylidene dye and its cationic form showed high molar absorption coefficients and a significant emission of the cationic dye analogue solution was observed. The antibacterial affinity using the disk diffusion method was investigated for six potential skin infection causing microbial pathogens, including two Gram-negative species (Pseudomonas aeruginosa and Proteus mirabilis), two Gram-positive species (Staphylococcus aureus and Staphylococcus epidermidis), and two fungal species (Candida albicans and Rhizomucor miehei) by recording the inhibition zone as well as studying the killing time effect for the prepared dyes. The in vitro wound healing application and the effect of cationized Dye 2 on the healing progress showed very effective and faster healing at a concentration of 100 µg/mL (IC50). Molecular dynamics simulation studies of Dye 1 and Dye 2 were carried out to compute binding free energies using Generalized Born Surface Area (MM/GBSA) in molecular mechanics. Furthermore, computational studies revealed that Dye 2 showed high affinity toward the active site of DNA gyrase B, which provides a solid framework for new structure-based design initiatives.

Enhancing PET Degrading Enzymes: A Combinatory Approach.

Plastic waste has become a substantial environmental issue. A potential strategy to mitigate this problem is to use enzymatic hydrolysis of plastics to depolymerize post-consumer waste and allow it to be reused. Over the last few decades, the use of enzymatic PET-degrading enzymes has shown promise as a great solution for creating a circular plastic waste economy. PsPETase from Piscinibacter sakaiensis has been identified as an enzyme with tremendous potential for such applications. But to improve its efficiency, enzyme engineering has been applied aiming at enhancing its thermal stability, enzymatic activity, and ease of production. Here, we combine different strategies such as structure-based rational design, ancestral sequence reconstruction and machine learning to engineer a more highly active Combi-PETase variant with a melting temperature of 70 °C and optimal performance at 60 °C. Furthermore, this study demonstrates that these approaches, commonly used in other works of enzyme engineering, are most effective when utilized in combination, enabling the improvement of enzymes for industrial applications.

Computer-Aided Drug Discovery Approaches in the Identification of Anticancer Drugs from Natural Products: A Review.

Natural plant sources are essential in the development of several anticancer drugs, such as vincristine, vinblastine, vinorelbine, docetaxel, paclitaxel, camptothecin, etoposide, and teniposide. However, various chemotherapies fail due to adverse reactions, drug resistance, and target specificity. Researchers are now focusing on developing drugs that use natural compounds to overcome these issues. These drugs can affect multiple targets, have reduced adverse effects, and are effective against several cancer types. Developing a new drug is a highly complex, expensive, and time-consuming process. Traditional drug discovery methods take up to 15 years for a new medicine to enter the market and cost more than one billion USD. However, recent Computer Aided Drug Discovery (CADD) advancements have changed this situation. This paper aims to comprehensively describe the different CADD approaches in identifying anticancer drugs from natural products. Data from various sources, including Science Direct, Elsevier, NCBI, and Web of Science, are used in this review. In-silico techniques and optimization algorithms can provide versatile solutions in drug discovery ventures. The structure-based drug design technique is widely used to understand chemical constituents' molecular-level interactions and identify hit leads. This review will discuss the concept of CADD, in-silico tools, virtual screening in drug discovery, and the concept of natural products as anticancer therapies. Representative examples of molecules identified will also be provided.

Abstract PO3-25-08: Artificial Intelligence-based screening of small molecule inhibitors of phosphoenolpyruvate carboxykinase 2 (PCK2), a novel cancer therapeutic target

Abstract Background: Metabolic rewiring is a hallmark of cancer that is often mediated by alterations in metabolic isozyme expression. Isozymes that are overexpressed in cancer and catalyze rate limiting steps in key metabolic processes are potential therapeutic targets. We previously identified phosphoenolpyruvate carboxykinase 2 (PCK2) as cancer dominant isoform, required for maintaining high metabolic activity and proliferation of lung, prostate, and breast cancer (BC) cells in vitro and in vivo. No PCK2 specific small molecule inhibitors exist. Methods: mRNA expression levels were assessed in the TCGA data. PCK2 MISSION shRNAs (Millipore) were used to knock-down expression of PCK2 in BC cells. Alterations in metabolic flux caused by PCK2 down-regulation were examined via 13C-labeling and mass spectrometry using a SCIEX 5500 QTRAP and SelexION instrument for mobility separation of metabolites. The AtomNetTM (Atomwise Inc.) deep convolutional neural network structure-based drug design software was used to identify candidate small molecule PCK2 inhibitors which were tested in PCK1 and PCK2 in vitro enzyme activity assays. The lead compound was assessed for drug-like properties by QickPropV4.0.001w, and its growth inhibitory activity was tested in MDA-MB-321 and BT-549 cells. Results: Analysis of mRNA levels in TNBC samples revealed a significant decrease in PCK1 expression compared to normal tissues, while PCK2 expression remained elevated or even increased. Quantification of mRNA levels in TNBC cell lines confirmed the higher expression of PCK2 compared to PCK1. To assess functional significance of PCK2 expression, we downregulated PCK2 using shRNA constructs in TNBC cell lines. Western blot analysis confirmed efficient knockdown of PCK2 protein without affecting PCK1 expression. Clonogenic assays demonstrated that PCK2-depleted BT-549 and MDA-MB-231 cells exhibited impaired proliferation, with reduced colony number and size compared to control cells. Metabolic analysis of PCK2-depleted TNBC cells demonstrated decreased levels of glycolytic and TCA intermediates and reduced flux through pyruvate carboxylase, indicating altered metabolic pathways upon PCK2 depletion. To identify potential inhibitors of PCK2, virtual screening was conducted using compound structures. We used a PCK2 protein structure homology model and designated the 3-mercaptopicolinic acid-binding site of the PCK1 structure as the site of interest to perform virtual drug screening of 7 million diverse compounds. The first screen yielded 86 structures to be tested in vitro, of which 5 demonstrated > 16% PCK2 inhibition. The top hit (IC50=2.4µM) was used to refine a second round of in silico screen that yielded 87 second-round candidates that were assessed for PCK2 inhibition in vitro. 3-(3,4-dihydroxyphenyl)-2-hydroxypropanoate emerged as the lead compound. QickProp predicted favorable absorption, distribution, metabolism, and excretion properties, but relatively low cell permeability (apparent Caco-2 and MDCK2 cell permeabilities 18 nm/sec and 8 nm/sec, respectively). The specificity of 3-(3,4-dihydroxyphenyl)-2-hydroxypropanoate was tested in PCK1 and PCK2 enzymatic assays and revealed IC50 of 500nM on PCK1 and an IC50 of 3 nM on PCK2. We next tested the cell growth inhibitory effect of 3-(3,4-dihydroxyphenyl)-2-hydroxypropanoate on parental MDA-MB-231 and BT-549 cells and their PCK2 knockdown clones. Cell growth and viability significantly decreased in the MDA-MD-231 and BT-549 parental cells (the IC50 for MDA-MB-231 was 173 μM) and in shRNA non-targeting control cells, but not in the PCK2 depleted clones, demonstrating PCK2-dependent inhibitory effect. Conclusion: We identified 3-(3,4-dihydroxyphenyl)-2-hydroxypropanoate as a high affinity selective PCK2 enzyme inhibitor. This compound also has significant growth inhibitory activity in BC cell lines in vitro and represents a novel therapeutic lead compound. Citation Format: Alejandro Rios Hoyo, Naing Lin Shan, Hao-Kuen Lin, Gerson Espinoza Campos, Mostafa Ahmed, Sheila Umlauf, Rebecca Cardone, Yulia V. Surovtseva, Vignesh Gunasekharan, Lajos pusztai. Artificial Intelligence-based screening of small molecule inhibitors of phosphoenolpyruvate carboxykinase 2 (PCK2), a novel cancer therapeutic target [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-25-08.

Abstract PO3-26-09: A novel class of RNR inhibitors that induces genomic instability and breast cancer cell death without inducing overt toxicities

Abstract Despite the development of screening techniques and therapies, nearly 30% of breast cancers progress to Stage IV metastatic disease. These advanced cancers are highly proliferative, engaging in ongoing DNA synthesis that requires ribonucleotide reductase (RNR), the rate-limiting enzyme for dNTP synthesis. RRM2, the small subunit of RNR, activates the enzyme, increases deoxynucleotide pools, and is overexpressed in many cancers, including breast cancer. Thus, RNR is an established therapeutic target in advanced breast cancer. Currently, gemcitabine is the only FDA-approved RNR inhibitor used to treat Stage IV disease. As a nucleoside analog, gemcitabine also causes severe dose-limiting toxicities (i.e. myelosuppression and hepatotoxicity) due to off-target DNA replication termination. We hypothesize that a novel, non-nucleoside, RNR inhibitor may overcome these limitations. To address this, we developed TMU27a, a derivative of naphthyl salicylic acyl hydrazone (NSAH), which was identified in an in silico screen for its high-affinity binding to the RNR catalytic site. To measure direct interactions between TMU27a and purified RNR protein, we used surface plasmon resonance, revealing on-target, tight binding (Kd = 150 nM). Unbiased docking and molecular dynamics simulations (using lowest energy calculations) predicted the binding sight of TMU27a to be the catalytic site of RNR, where it is stabilized through extensive interactions formed with conserved residues. Preliminary docking predictions also indicate multiple clash sites between TMU27a and the DNA polymerase lambda nucleotide pocket even in the lowest energy pose (unlike gemcitabine), suggesting that TMU27a inhibits RNR activity through a novel mechanism without significant off-target binding to other nucleotide binding proteins that contribute to toxicity. Demonstrating on-target inhibition, TMU27a reduces dATP levels and induces S and G2/M-phase stalling, leading to significant DNA damage and chromosomal instability. This excessive genomic damage causes growth repression, apoptosis, and senescence in several triple negative breast cancer (TNBC) cell lines. In xenograft mouse models of TNBC, TMU27a fully suppressed tumor growth without impacting mouse weight, suggesting strong drug efficacy in the absence of overt toxicity. Moreover, while short-term exposure to gemcitabine suppresses red and white blood cell populations, TMU27a does not. Together, these data indicate that TMU27a and its potential analogs are novel, non-toxic RNR inhibitors that overcome the limitations of gemcitabine for treating breast cancer. We are currently investigating how and where TMU27a binds human RNR using cryo-electron microscopy with the goal of generating a novel class of RNR inhibitors through structure-based drug design, improving binding affinity and selectivity. Citation Format: Taylor Baker, Kristen Weber-Bonk, Wei Huang, Derek Taylor, Ruth Keri. A novel class of RNR inhibitors that induces genomic instability and breast cancer cell death without inducing overt toxicities [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-26-09.

Rational Design of Drugs Targeting G-Protein-Coupled Receptors: Ligand Search and Screening.

G protein-coupled receptors (GPCRs) are transmembrane proteins that participate in many physiological processes and represent major pharmacological targets. Recent advances in structural biology of GPCRs have enabled the development of drugs based on the receptor structure (structure-based drug design, SBDD). SBDD utilizes information about the receptor-ligand complex to search for suitable compounds, thus expanding the chemical space of possible receptor ligands without the need for experimental screening. The review describes the use of structure-based virtual screening (SBVS) for GPCR ligands and approaches for the functional testing of potential drug compounds, as well as discusses recent advances and successful examples in the application of SBDD for the identification of GPCR ligands.

Synthesis and computational study of metal complex of α-mangostin as an anticancer candidate

Context: The number of breast cancer patients from year to year is increasing, accompanied by an increase in global mortality; the position in Indonesia has reached 60-70% with end-stage conditions. ERα antiproliferative activity exists in α-mangostin compounds, but this compound still has several physicochemical problems, including its solubility. Therefore, efforts are needed to increase the activity of α-mangostin and its affinity as an alpha estrogen receptor antagonist through a structure-based design method. Aims: To obtain new compounds derived from α-mangostin in the form of a metal complex with cobalt (AM-Co), platinum (AM-Pt), and iron (AM-Fe) as medicinal ingredients that can be used as breast cancer therapeutic agents. Methods: The research methods include in silico studies (pharmacokinetic and toxicity prediction, molecular docking, and molecular dynamics), semi-synthesis to form a complex compound, and testing cytotoxic activity against MCF-7 and T-47D human breast cancer cells. Results: From the in vitro test results, it can be seen that the AM-Pt compound showed the best anticancer activity on MCF-7 cells compared to others from IC50 and SI values; this was supported by the results of in silico studies either through molecular docking or molecular dynamics, where this compound was more effective. Conclusions: Furthermore, it can be used as an anticancer candidate; particularly, its activity is predicted to be more potent as an ER antagonist than -mangostin and cisplatin.

Ligand-based drug design against Herpes Simplex Virus-1 capsid protein by modification of limonene through in silico approaches

The pharmacological effects of limonene, especially their derivatives, are currently at the forefront of research for drug development and discovery as well and structure-based drug design using huge chemical libraries are already widespread in the early stages of therapeutic and drug development. Here, various limonene derivatives are studied computationally for their potential utilization against the capsid protein of Herpes Simplex Virus-1. Firstly, limonene derivatives were designed by structural modification followed by conducting a molecular docking experiment against the capsid protein of Herpes Simplex Virus-1. In this research, the obtained molecular docking score exhibited better efficiency against the capsid protein of Herpes Simplex Virus-1 and hence we conducted further in silico investigation including molecular dynamic simulation, quantum calculation, and ADMET analysis. Molecular docking experiment has documented that Ligands 02 and 03 had much better binding affinities (− 7.4 kcal/mol and − 7.1 kcal/mol) to capsid protein of Herpes Simplex Virus-1 than Standard Acyclovir (− 6.5 kcal/mol). Upon further investigation, the binding affinities of primary limonene were observed to be slightly poor. But including the various functional groups also increases the affinities and capacity to prevent viral infection of the capsid protein of Herpes Simplex Virus-1. Then, the molecular dynamic simulation confirmed that the mentioned ligands might be stable during the formation of drug-protein complexes. Finally, the analysis of ADMET was essential in establishing them as safe and human-useable prospective chemicals. According to the present findings, limonene derivatives might be a promising candidate against the capsid protein of Herpes Simplex Virus-1 which ultimately inhibits Herpes Simplex Virus-induced encephalitis that causes interventions in brain inflammation. Our findings suggested further experimental screening to determine their practical value and utility.

Identification and affinity enhancement of T-cell receptor targeting a KRASG12V cancer neoantigen

Neoantigens derived from somatic mutations in Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS), the most frequently mutated oncogene, represent promising targets for cancer immunotherapy. Recent research highlights the potential role of human leukocyte antigen (HLA) allele A*11:01 in presenting these altered KRAS variants to the immune system. In this study, we successfully generate and identify murine T-cell receptors (TCRs) that specifically recognize KRAS8–16G12V from three predicted high affinity peptides. By determining the structure of the tumor-specific 4TCR2 bound to KRASG12V-HLA-A*11:01, we conduct structure-based design to create and evaluate TCR variants with markedly enhanced affinity, up to 15.8-fold. This high-affinity TCR mutant, which involved only two amino acid substitutions, display minimal conformational alterations while maintaining a high degree of specificity for the KRASG12V peptide. Our research unveils the molecular mechanisms governing TCR recognition towards KRASG12V neoantigen and yields a range of affinity-enhanced TCR mutants with significant potential for immunotherapy strategies targeting tumors harboring the KRASG12V mutation.

A Tiny Pocket Packs a Punch: Leveraging Pyridones for the Discovery of CNS-Penetrant Aza-indazole IRAK4 Inhibitors.

We herein report the discovery, synthesis, and evolution of a series of indazoles and azaindazoles as CNS-penetrant IRAK4 inhibitors. Described is the use of structure-based and property-based drug design strategically leveraged to guide the property profile of a key series into a favorable property space while maintaining potency and selectivity. Our rationale that led toward functionalities with potency improvements, CNS-penetration, solubility, and favorable drug-like properties is portrayed. In vivo evaluation of an advanced analogue showed significant, dose-dependent modulation of inflammatory cytokines in a mouse model. In pursuit of incorporating a highly engineered bridged ether that was crucial to metabolic stability in this series, significant synthetic challenges were overcome to enable the preparation of the analogues.