Discovery and biological evaluation of 6-aryl-4-(3,4,5-trimethoxyphenyl)quinoline derivatives with promising antitumor activities as novel colchicine-binding site inhibitors

Tubulin, as the fundamental unit of microtubules, is a crucial target in the investigation of anticarcinogens. The synthesis and assessment of small-molecule tubulin polymerization inhibitors remains a promising avenue for the development of novel cancer therapeutics. Through an analysis of reported colchicine-binding site inhibitors (CBSIs) and tubulin binding models, a set of 6-aryl-4-(3,4,5-trimethoxyphenyl)quinoline derivatives were meticulously crafted as potential CBSIs. Notably, compound 14u exhibited potent anti-proliferative efficacy, displaying IC50 values ranging from 0.03 to 0.18 μM against three human cancer cell lines (Huh7, MCF-7, and SGC-7901). Mechanistic investigations revealed that compound 14u could disrupt tubulin polymerization, dismantle the microtubule architecture, arrest the cell cycle at G2/M phase, and induce apoptosis in cancer cells. Furthermore, compound 14u demonstrated significant inhibition of tumor proliferation in vivo with no discernible toxicity in the Huh7 orthotopic tumor model mice. Additionally, physicochemical property predictions indicated that compound 14u adhered well to Lipinski's rule of five. These findings collectively suggest that compound 14u holds promise as an antitumor agent targeting the colchicine-binding site on tubulin and warrants further investigation.

An in-silico approach to target multiple proteins involved in anti-microbial resistance using natural compounds produced by wild mushrooms

Bacterial resistance to antibiotics and the number of patients infected by multi-drug-resistant bacteria have increased significantly over the past decade. This study follows a computational approach to identify potential antibacterial compounds from wild mushrooms. Twenty-six known compounds produced by wild mushrooms were docked to assess their affinity with drug targets of antibiotics such as penicillin-binding protein-1a (PBP1a), DNA gyrase, and isoleucyl-tRNA synthetase (ILERS). Docking scores were further validated by multiple receptor conformer (MRC)-based docking studies. Based on the MRC-based docking results, eight molecules were shortlisted for ADMET analysis. Molecular dynamics (MD) simulations were further performed to evaluate the conformational stability of the ligand-protein complexes. Binding energies were computed by the gmx_MMPBSA method. The data were obtained in terms of root-mean square deviation, and root-mean square fluctuation justified the stability of Austrocortilutein A, Austrocortirubin, and Confluentin in complex with several proteins under physiological conditions. Among these, Austrocortilutein A displayed better binding affinity with PBP1a and ILERS when compared with their respective reference ligands. This study is preliminary and aims to help drive the search for compounds that have the capacity to overcome the anti-microbial resistance of prevalent bacteria, using natural compounds produced by wild mushrooms. Further experimental validation is required to justify the clinical use of the studied compounds.

Design, synthesis, and evaluation of novel stilbene derivatives that degrade acidic nucleoplasmic DNA-binding protein 1 (And1) and synergize with PARP1 inhibitor in NSCLC cells

Specifically inducing the degradation of acidic nucleoplasmic DNA-binding protein 1 (And1) is a promising antitumor strategy. Our previous study identified Bazedoxifene (BZA) and CH3 as specific And1 degraders and validated their activity in reversing radiotherapy resistance in vitro and in vivo. However, unelucidated structure-activity relationships and moderate activity have limited their application. In this study, 27 novel CH3 derivatives were designed and synthesised based on the cavity topology of the WD40 domain of And1. Among them, A15 with a "V" conformation significantly induced And1 degradation in NSCLC cells. In addition, this study demonstrated a potential synthetic lethal effect of And1 degraders and PARP1 inhibitors. 1 µM of Olaparib in combination with 5 µM of A15 significantly inhibited the proliferation of A549 and H460 cells. Overall, these compounds are valuable tools for elucidating And1 biology, and their special spatial conformation make them promising candidates for future optimisation studies.

An update on small molecule compounds targeting synthetic lethality for cancer therapy

Targeting cancer-specific vulnerabilities through synthetic lethality (SL) is an emerging paradigm in precision oncology. A SL strategy based on PARP inhibitors has demonstrated clinical efficacy. Advances in DNA damage response (DDR) uncover novel SL gene pairs. Beyond BRCA-PARP, emerging SL targets like ATR, ATM, DNA-PK, CHK1, WEE1, CDK12, RAD51, and RAD52 show clinical promise. Selective and bioavailable small molecule inhibitors have been developed to induce SL, but optimization for potency, specificity, and drug-like properties remains challenging. This article illuminated recent progress in the field of medicinal chemistry centered on the rational design of agents capable of eliciting SL specifically in neoplastic cells. It is envisioned that innovative strategies harnessing SL for small molecule design may unlock novel prospects for targeted cancer therapeutics going forward.

Revealing binding mechanism of β-casein to chrysin, apigenin, and luteolin and locating its binding pockets by molecular docking and molecular dynamics

Revealing the interaction mechanism of proteins with bioactive molecules and the location of their binding pockets is crucial for predicting the structure-function relationship of proteins in drug discovery and design. Despite some published papers on the interaction of β-casein with small bioactive molecules, the ambiguity of the location and constituent amino acids of β-casein binding pockets prompted us to identify them by in silico simulation of its interaction with three polyphenols, chrysin, apigenin, and luteolin. Molecular docking revealed that the primary β-casein binding pocket for chrysin consists of five nonpolar amino acids (Leu73, Phe77, Pro80, Ile89, and Pro196), three polar neutral amino acids (Ser137, Gln138, and Gln197), and two polar charged amino acids (Glu136, and Arg198). For β-casein/apigenin and β-casein/luteolin complexes, Asn83 also contributes to forming the pocket. Molecular dynamics provided more details, such as the relative contribution of determinative amino acids and the role of various forces. For example, we found that Glu210, Glu132, and Glu35 are the most destructive residues in the binding of chrysin, apigenin, and luteolin to β-casein, respectively. Also, we observed that hydrophobic forces mainly stabilize β-casein/chrysin and β-casein/apigenin, and polar solvation (including hydrogen bonds) stabilizes β-casein/luteolin, all by spontaneous processes.

In silico discovery of druggable targets in Citrobacter koseri using echinoderm metabolites and molecular dynamics simulation

Citrobacter koseri causes infection in people who are immunocompromised. Without effective antibiotics, these infections can become severe and life-threatening, so effective drugs are essential to treat these infections. Utilizing subtractive genomics, 2699 ORFs were predicted and translated into amino acid sequences. Metabolic pathway analysis and subcellular localization helped define the roles of key bacterial proteins. Two druggable proteins, WP_012000829.1 and WP_275157394.1, were discovered as promising targets. Alpha Fold provided 3D structures, and a library of 1600 echinoderm metabolites was docked against these proteins, with Ampicillin, Levofloxacin, and Doxycycline as controls. Notably, CMNPD13085 and CMNPD15632 exhibited the highest binding affinities for WP_012000829.1 and WP_275157394.1, respectively. Molecular dynamics simulations and MM-GBSA binding free energy complemented docking results. However, acknowledging the reliance on computational validations, the study emphasizes the need for essential in-vitro research to transform these potential inhibitors into therapeutic drugs.

A molecular dynamics simulations analysis of repurposing drugs for COVID-19 using bioinformatics methods

A number of multidisciplinary methods have piqued the interest of researchers as means to accelerate and lower the cost of medication creation. The goal of this research was to find target proteins and then select a lead drug against SARS-CoV-2. The three-dimensional structure is taken from the RCSB PDB using its specific PDB ID 6lu7. Virtual screening based on pharmacophores is performed using Molecular Operating Environment software. We looked for a potent inhibitor in the FDA-approved database. For docking, AutoDock Vina uses Pyrx. The compound-target protein binding interactions were tested using BIOVIA Discovery Studio. The stability of protein and inhibitor complexes in a physiological setting was investigated using Desmond's Molecular Dynamics Simulation (MD simulation). According to our findings, we repurpose the FDA-approved drugs ZINC000169677008 and ZINC000169289767, which inhibit the activity of the virus's main protease (6lu7). The scientific community will gain from this finding, which might create new medicine. The novel repurposed chemicals were promising inhibitors with increased efficacy and fewer side effects.Communicated by Ramaswamy H. Sarma.

Copper-assisted anticancer activity of hydroxycinnamic acid terpyridine conjugates on triple-negative breast cancer

The development of active therapeutic agents to treat highly metastatic cancer while minimizing damage to healthy cells is of utmost importance. Due to potential antioxidant properties, hydroxycinnamic acid derivatives (caffeic acid and p-coumaric acids) were found to inhibit highly metastatic breast cancer cell growth both in vitro and in vivo without much effect on normal cells. Especially due to the structure-activity relationships, ester and amide derivatives of hydroxycinnamic acids are reported to gain much higher radical scavenging ability than their naked hydroxycinnamic acid analogs like caffeic acid and p-coumaric acid. These results prompted us to design a set of ligands by incorporating an amide moiety on caffeic acid and p-coumaric acid to achieve the least toxicity towards healthy cell lines. Further, the Cu(II) complexes of amide-coupled caffeic acid and p-coumaric acid ligands have been explored for their therapeutic activity on triple-negative breast cancer and other cancer cells like colon, and prostate cancer. The Cu(II) complexes (4 & 5) were characterized by UV-Vis spectroscopy, FTIR, and X-band EPR spectroscopy. The trigonal bipyramidal geometry of complexes was confirmed by the X-band EPR spectra recorded in solution state at liquid N2 temperature. The purity of the complexes was determined by elemental analysis and HPLC traces. Initially, Calf thymus DNA (ct-DNA) binding studies with the complexes were explored. The results suggested the complexes (4 & 5) bind majorly through an intercalative mode of binding with ct-DNA, whereas no significant binding was observed for the bare organic ligands (2 & 3). The intercalation binding modes of 4 and 5 were further supported by UV-visible spectroscopy, ct-DNA melting point analysis, and CD spectroscopy. Moreover, these complexes showed better activity towards cisplatin-resistant TNBC cell lines (4T1, a TNBC cell line derived from the mammary gland tissue of a mouse). The combination of antioxidants and Cu(II) as the metal center made the complexes more cytotoxic toward cancer cell lines (4T1) (IC50 ∼ 3.5 ± 2.5 μM) and the least toxic toward healthy cells (L929) (IC50 ∼ 15 ± 5 μM). Finally, the mechanism of cell death was studied using JC-1 staining and a cell colony formation assay. These studies might help in designing safer anticancer drugs for treating more aggressive types of cancer.

Effect of isoproterenol, a β-adrenergic agonist, on the differentiation of insulin-producing pancreatic β cells derived from human pluripotent stem cells

Research on islet replacement through the differentiation of functionally matured insulin-producing β-like cells for the treatment of diabetes presents a significant challenge. Neural signals in β cell differentiation significantly impact the pancreatic microenvironment in glucose metabolism, but they are not fully understood. In this study, isoproterenol, a β adrenoreceptor agonist, was introduced into pancreatic progenitor cells, derived from human pluripotent stem cells in vitro, undergoing endocrine differentiation, using 2-dimensional (2D) and 3-dimensional (3D) differentiation protocols. This resulted in increased insulin and C-peptide secretion, along with elevated expression of key pancreatic beta cell transcription factors, including PDX-1, NKX6.1, and MAFA, and improved function, demonstrated by increased responsiveness to glucose determined via a glucose-stimulated insulin secretion test. Moreover, RNA transcriptome analysis of isoproterenol-treated endocrine progenitors facilitated the identification of biological pathways and genes that contribute to mature beta cell differentiation efficiency correlated with neural signals, such as adrenoceptor beta 1, calcium/calmodulin dependent protein kinase II alpha, phospholipase C delta 4, and neurotrophic receptor tyrosine kinase 1. Among those genes, calcium/calmodulin dependent protein kinase II alpha was suggested as the most notable gene involved in the isoproterenol mechanism through inhibitor assays. This study illustrates that isoproterenol significantly enhances endocrine differentiation and underscores its effects on stem cell-derived beta cell maturation, emphasizing its therapeutic potential for the treatment of diabetes.

Discovery of novel quinazoline derivatives as tubulin polymerization inhibitors targeting the colchicine binding site with potential anti-colon cancer effects

Tubulin is a critical target for cancer therapy, with colchicine binding site inhibitors (CBSIs) being the most extensively researched. A series of quinazoline derivatives designed to target the colchicine binding site of tubulin were synthesized and evaluated for their biological activities. The antiproliferative effects of these compounds were tested against six human cancer cell lines, and compound Q19 demonstrated potent antiproliferative activity against the HT-29 cell line, with an IC50 value of 51 nM. Additionally, further investigation revealed that Q19 effectively inhibited microtubule polymerization by binding to the colchicine binding site on tubulin. Furthermore, compound Q19 arrested the HT-29 cell cycle at the G2/M phase, induced apoptosis in these cells, and disrupted angiogenesis. Finally, compound Q19 exhibited potent inhibitory effects on tumor growth in HT-29 xenografted mice while demonstrating minimal toxic side effects and acceptable pharmacokinetic properties. These findings suggested that Q19 hold promise as a potential candidate for colon cancer therapy targeting tubulin.

Discovery of Tetrahydro Tanshinone I as a Naturally Occurring Covalent Pan-Inhibitor Against Gut Microbial Bile Salt Hydrolases

Gut microbial bile salt hydrolases (gmBSHs), an important class of bacteria-produced cysteine hydrolases, play a crucial role in bile acid metabolism. Modulating the total gmBSH activity is a feasible way for ameliorating some metabolic diseases including colorectal cancer, type 2 diabetes, and obesity. This study reported the discovery and characterization of a botanical compound as a covalent pan-inhibitor of gmBSHs. Following the screening of more than 100 botanical compounds, tanshinones were found with strong time-dependent anti-EfBSH effects. After that, a total of 17 naturally occurring tanshinones were collected, and their anti-EfBSH potentials were tested. Among all tested tanshinones, tetrahydro tanshinone I (THTI) exhibited the most potent inhibitory effects against five gmBSHs (EfBSH, LsBSH, BtBSH, CpBSH, and BlBSH), showing the IC50 values ranging from 0.28 ± 0.05 μM to 1.62 ± 0.07 μM. Further investigations showed that THTI could covalently modify the conserved catalytic cysteine (Cys2) of all tested gmBSHs, while this agent could strongly inhibit the total gmBSHs activity in live microorganisms and murine gut luminal content. Collectively, THTI is identified as a naturally occurring covalent pan-inhibitor of gmBSHs, which offers a promising lead compound to develop more efficacious gmBSHs inhibitors for the management of bile acid metabolism and related metabolic disorders.

Identification of novel brain penetrant GSK-3β inhibitors toward Alzheimer's disease therapy by virtual screening, molecular docking, dynamic simulation, and MMPBSA analysis

One of the significant therapeutic targets for Alzheimer's disease (AD) is Glycogen Synthase Kinase-3β (GSK-3β). Inhibition of GSK-3β can prevent hyperphosphorylation of tau, and thus prevent formation and accumulation of neurofibrillary tangles and neuropil threads that block intracellular transport, trigger unfolded protein response, and increase oxidative stress, cumulatively leading to neurodegeneration. In this study, we have performed structure-based virtual screening of two small-molecule libraries from ChemDiv CNS databases using AutoDock Vina to identify hit molecules based on their binding affinities compared to that of an established GSK-3β inhibitor, indirubin-3'-monoxime (IMO). Pharmacoinformatic screening on SwissADME and pkCSM servers enabled identification of lead molecules with favorable pharmacoinformatic properties for drug likeliness, including blood brain barrier (BBB) permeability. Further, molecular dynamic simulations identified six candidate lead molecules that show stable complex formation with GSK-3β in dynamic state under physiological conditions. Principal component analysis of the dynamic state was used to plot Free Energy Landscapes (FELs) of GSK-3β-ligand complexes. STRIDE secondary structure analysis of the lowest energy conformations identified from FEL plots, and binding free energy calculations by Molecular Mechanics Poisson-Boltzmann Surface Area ((ΔGbind)MM-PBSA) of the simulation trajectories led to the identification of two ligands as potential lead molecules having favorable free energy landscape profiles as well as significantly lower (ΔGbind)MM-PBSA in dynamic state compared to that of reference inhibitor IMO. Hence, this study identifies two novel brain penetrant GSK-3β inhibitors that are likely to have therapeutic potential against Alzheimer's disease.

Integrating ADMET, enrichment analysis, and molecular docking approach to elucidate the mechanism of Artemisia herba alba for the treatment of inflammatory bowel disease-associated arthritis

Inflammatory Bowel Disease-Associated Arthritis (IBD-associated arthritis) poses a significant challenge, intertwining the complexities of both inflammatory bowel disease (IBD) and arthritis, significantly compromising patient quality of life. While existing medications offer relief, these drugs often initiate adverse effects, necessitating the requirement for safer therapeutic alternatives. Artemisia herba-alba, a traditional medicinal plant known for its anti-inflammatory properties, emerges as a potential candidate. Our computational study focused on examining 20 bioactive compounds derived from A. herba-alba for potential treatment of IBD-associated arthritis. These compounds detected in A. herba-alba include camphor, alpha-thujone, eucalyptol, cis-chrysanthenyl acetate, vicenin-2, 4,5-di-O-caffeoylquinic acid, chlorogenic acid, hispidulin, isoschaftoside, isovitexin, patuletin-3-glucoside, vanillic acid, rutin, schaftoside, lopinavir, nelfinavir, quercetin, artemisinin, gallic acid, and cinnamic acid. Following rigorous analysis encompassing pharmacokinetics, toxicity profiles, and therapeutic targets, compounds with favorable, beneficial characteristics were identified. In addition, comparative analysis with disease-gene associations demonstrated the interconnectedness of inflammatory pathways across diseases. Molecular docking studies provided mechanistic insights indicating this natural plant components potential to modulate critical inflammatory pathways. Overall, our findings indicate that A. herba-alba-derived compounds may be considered as therapeutic agents for IBD-associated arthritis, warranting further experimental validation and clinical exploration.

Synthesis and evaluation of tetrahydropyrrolo[1,2-a]quinolin-1(2H)-ones as new tubulin polymerization inhibitors

Here we explored new 1,5-disubstituted pyrrolidin-2-ones 1, 2 and 5-aryl-3,3a,4,5-tetrahydropyrrolo[1,2-a]quinoline-1(2H)-ones 3 as inhibitors of tubulin polymerization. We evaluated their effects on microtubule dynamics in vitro and on the proliferation of A549 cells, using flow cytometry-based cell cycle analysis. The results were verified with phase-contrast microscopy in three cancer cell lines: A549, HeLa and MCF-7. Guided by molecular modeling of the interactions between tubulin and the most active of the identified compounds, we designed, synthesized, and tested the 3-hydroxyphenyl-substituted compound 3c. This compound was further shown to bind to the colchicine site of tubulin and reduce microtubule growth rates in vitro. Moreover, compound 3c arrested division of the A549 cells in the low micromolar range (IC50 = 5.9 μM) and exhibited cytotoxicity against four different cell lines in the MTT assay for cell proliferation. Our findings demonstrate that 5-aryltetrahydropyrrolo[1,2-a]quinoline-1(2H)-one is a promising scaffold for the development of novel tubulin polymerization inhibitors.

Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery

Computational methods constitute efficient strategies for screening and optimizing potential drug molecules. A critical factor in this process is the binding affinity between candidate molecules and targets, quantified as binding free energy. Among various estimation methods, alchemical transformation methods stand out for their theoretical rigor. Despite challenges in force field accuracy and sampling efficiency, advancements in algorithms, software, and hardware have increased the application of free energy perturbation (FEP) calculations in the pharmaceutical industry. Here, we review the practical applications of FEP in drug discovery projects since 2018, covering both ligand-centric and residue-centric transformations. We show that relative binding free energy calculations have steadily achieved chemical accuracy in real-world applications. In addition, we discuss alternative physics-based simulation methods and the incorporation of deep learning into free energy calculations.

Recent advances from computer-aided drug design to artificial intelligence drug design

Computer-aided drug design (CADD), a cornerstone of modern drug discovery, can predict how a molecular structure relates to its activity and interacts with its target using structure-based and ligand-based methods. Fueled by ever-increasing data availability and continuous model optimization, artificial intelligence drug design (AIDD), as an enhanced iteration of CADD, has thrived in the past decade. AIDD demonstrates unprecedented opportunities in protein folding, property prediction, and molecular generation. It can also facilitate target identification, high-throughput screening (HTS), and synthetic route prediction. With AIDD involved, the process of drug discovery is greatly accelerated. Notably, AIDD offers the potential to explore uncharted territories of chemical space beyond current knowledge. In this perspective, we began by briefly outlining the main workflows and components of CADD. Then through showcasing exemplary cases driven by AIDD in recent years, we describe the evolving role of artificial intelligence (AI) in drug discovery from three distinct stages, that is, chemical library screening, linker generation, and de novo molecular generation. In this process, we attempted to draw comparisons between the features of CADD and AIDD.

Self-organizing maps of unbiased ligand-target binding pathways and kinetics

The interpretation of ligand-target interactions at atomistic resolution is central to most efforts in computational drug discovery and optimization. However, the highly dynamic nature of protein targets, as well as possible induced fit effects, makes difficult to sample many interactions effectively with docking studies or even with large-scale molecular dynamics (MD) simulations. We propose a novel application of Self-Organizing Maps (SOMs) to address the sampling and dynamic mapping tasks, particularly in cases involving ligand flexibility and induced fit. The SOM approach offers a data-driven strategy to create a map of the interaction process and pathways based on unbiased MD. Furthermore, we show how the preliminary SOM mapping is complementary to kinetic analysis, with the employment of both network-based approaches and Markov state models. We demonstrate the method by comprehensively mapping a large dataset of 640 μs of unbiased trajectories sampling the recognition process between the phosphorylated YEEI peptide and its high-specificity target lck-SH2. The integration of SOM into unbiased simulation protocols significantly advances our understanding of the ligand binding mechanism. This approach serves as a potent tool for mapping intricate ligand-target interactions with unprecedented detail, thereby enhancing the characterization of kinetic properties crucial to drug design.

Discovery and mechanistic insights into thieno[3,2-d]pyrimidine and heterocyclic fused pyrimidines inhibitors targeting tubulin for cancer therapy

Guided by the X-ray cocrystal structure of the lead compound 4a, we developed a series of thieno[3,2-d]pyrimidine and heterocyclic fused pyrimidines demonstrating potent antiproliferative activity against four tumor cell lines. Two analogs, 13 and 25d, exhibited IC50 values around 1 nM and overcame P-glycoprotein (P-gp)-mediated multidrug resistance (MDR). At low concentrations, 13 and 25d inhibited both the colony formation of SKOV3 cells in vitro and tubulin polymerization. Furthermore, mechanistic studies showed that 13 and 25d induced G2/M phase arrest and apoptosis in SKOV3 cells, as well as dose-dependent inhibition of tumor cell migration and invasion at low concentrations. Most notably, the X-ray cocrystal structures of compounds 4a, 25a, and the optimal molecule 13 in complex with tubulin were elucidated. This study identifies thieno[3,2-d]pyrimidine and heterocyclic fused pyrimidines as representatives of colchicine-binding site inhibitors (CBSIs) with potent antiproliferative activity.

Exploring the ability of the MD+FoldX method to predict SARS-CoV-2 antibody escape mutations using large-scale data

Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain. Our results show a positive correlation between predicted and experimental data, indicating that mutations with reduced predicted binding affinity correlate moderately with higher experimental escape fractions. We also demonstrate that higher precision can be achieved using affinity cutoffs tailored to distinct SARS-CoV-2 antibodies from four different classes rather than a one-size-fits-all approach. Further, we suggest that the quartile values of optimized cutoffs reported for each class in this study can serve as a valuable guide for future work on escape mutation predictions. We find that 70% of the systems surpass the 50% precision mark, and demonstrate success in identifying mutations present in significant variants of concern and variants of interest. Despite promising results for some systems, our study highlights the challenges in comparing predicted and experimental values. It also emphasizes the need for new binding affinity methods with improved accuracy that are fast enough to estimate hundreds to thousands of antibody-antigen binding affinities.

Structure-based approaches in synthetic lethality strategies

Evolution has fostered robust DNA damage response (DDR) mechanisms to combat DNA lesions. However, disruptions in this intricate machinery can render cells overly reliant on the remaining functional but often less accurate DNA repair pathways. This increased dependence on error-prone pathways may result in improper repair and the accumulation of mutations, fostering genomic instability and facilitating the uncontrolled cell proliferation characteristic of cancer initiation and progression. Strategies based on the concept of synthetic lethality (SL) leverage the inherent genomic instability of cancer cells by targeting alternative pathways, thereby inducing selective death of cancer cells. This review emphasizes recent advancements in structural investigations of pivotal SL targets. The significant contribution of structure-based methodologies to SL research underscores their potential impact in characterizing the growing number of SL targets, largely due to advances in next-generation sequencing. Harnessing these approaches is essential for advancing the development of precise and personalized SL therapeutic strategies.

The roles of G protein-coupled receptor kinase 2 in renal diseases

G protein-coupled receptor (GPCR) kinase 2 (GRK2) is an integrative node in many signalling network cascades. An emerging study indicates that GRK2 can interact with GPCRs and non-GPCR substrates in both kinase-dependent and -independent modes. Alterations in the functional levels of GRK2 have been found in a variety of renal diseases, such as hypertension-related kidney injury, sepsis-associated acute kidney injury (S-AKI), cardiorenal syndrome (CRS), acute kidney injury (AKI), age-related kidney injury or hyperglycemia-related kidney injury. Abnormal GRK2 expression contribute to the development of renal diseases, making them promising molecular targets for treating renal diseases. Blocking the prostaglandin E2 (PGE2)-EP1-Gaq-Ca2+ signal pathway in glomerular mesangial cells (GMCs) by internalizing prostaglandin E2 receptor 1 (EP1) with GRK2 may be a potential treatment for diabetic nephropathy (DN). In addition, GRK2 inhibition may have therapeutic effects in a variety of renal diseases, such as SLE-related kidney injury, DN, age-related kidney injury, hypertension-related kidney injury, and CRS. However, there is still a long way to go for the large-scale application of GRK2 inhibition in the field of renal diseases. In this review, we discuss recent updates in understanding the role of GRK2 in kidney dysfunction. Furthermore, we explore the potential of GRK2 as a possible therapeutic target for renal pathologies. We believe it will shed light on the future development of small-molecule inhibitors of GRK, as well as the clinical applications in renal diseases.

Alisol C 23-acetate might be a lead compound of potential lipase inhibitor from Alismatis Rhizoma: Screening, identification and molecular dynamics simulation

Alismatis Rhizoma (AR), a traditional Chinese medicine for treating obesity in traditional Chinese medicine clinic, is recognized as a promising source of lead compounds of lipase inhibitors. Ultrafiltration centrifugal combined with liquid chromatography-mass spectrometry (UF-LC-MS) was used for screening potential lipase inhibitors from AR, and the result indicated the binding capacity between compound 7 and lipase (92.3 ± 1.28 %) was significantly higher than other triterpenoids, and was identified as alisol C 23-acetate. It exhibited a mixed-type inhibitory behavior with an IC50 value of 84.88 ± 1.03 μM. Subsequently, the binding pockets of alisol C 23-acetate to lipase were predicted, and their binding mechanism was explored with molecular simulation. Pocket 1 (active center) and pocket 4 might be the orthosteric and allosteric binding sites of alisol C 23-acetate to lipase, respectively. The interaction between alisol C 23-acetate and lipase was identified to involve key amino acid residues such as GLY-77, PHE-78, TYR-115, LEU-154, PRO-181, PHE-216, LEU-264, ASP-278, GLN-306, ARG-313, and VAL-426. Meanwhile, alisol C 23-acetate remained stable during the intestinal digestive but degraded in the gastric digestion. Overall, alisol C 23-acetate is expected to be the lead compound of lipase inhibitors for treating obesity.

Improvements in Precision of Relative Binding Free Energy Calculations Afforded by the Alchemical Enhanced Sampling (ACES) Approach

Accurate in silico predictions of how strongly small molecules bind to proteins, such as those afforded by relative binding free energy (RBFE) calculations, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. The success of such calculations, however, relies heavily on their precision. Here, we show that a recently developed alchemical enhanced sampling (ACES) approach can consistently improve the precision of RBFE calculations on a large and diverse set of proteins and small molecule ligands. The addition of ACES to conventional RBFE calculations lowered the average hysteresis by over 35% (0.3-0.4 kcal/mol) and the average replicate spread by over 25% (0.2-0.3 kcal/mol) across a set of 10 protein targets and 213 small molecules while maintaining similar or improved accuracy. We show in atomic detail how ACES improved convergence of several representative RBFE calculations through enhancing the sampling of important slowly transitioning ligand degrees of freedom.

Exploring high hydrostatic pressure effects on anthocyanin binding to serum albumin and food-derived transferrins

This study investigated the effects of high hydrostatic pressure (HHP) on the binding interactions of cyanindin-3-O-glucoside (C3G) to bovine serum albumin, human serum albumin (HSA), bovine lactoferrin, and ovotransferrin. Fluorescence quenching revealed that HHP reduced C3G-binding affinity to HSA, while having a largely unaffected role for the other proteins. Notably, pretreating HSA at 500 MPa significantly increased its dissociation constant with C3G from 24.7 to 34.3 μM. Spectroscopic techniques suggested that HSA underwent relatively pronounced tertiary structural alterations after HHP treatments. The C3G-HSA binding mechanisms under pressure were further analyzed through molecular dynamics simulation. The localized structural changes in HSA under pressure might weaken its interaction with C3G, particularly polar interactions such as hydrogen bonds and electrostatic forces, consequently leading to a decreased binding affinity. Overall, the importance of pressure-induced structural alterations in proteins influencing their binding with anthocyanins was highlighted, contributing to optimizing HHP processing for anthocyanin-based products.

Wee1 inhibitor PD0166285 sensitized TP53 mutant lung squamous cell carcinoma to cisplatin via STAT1

BACKGROUND

Lung squamous cell carcinoma (LUSCs) is associated with high mortality (20-30%) and lacks of effective treatments. Almost all LUSC exhibit somatic mutations in TP53. Wee1, a tyrosine kinase, regulates the cell cycle at the G2/M checkpoint. In TP53-deficient cells, the dependence on G2/M checkpoints increases. PD0166285 is the first reported drug with inhibitory activity against both Wee1 and PKMYT1.

METHODS

Protein expression was determined by Western blot analysis. Cell proliferation was assessed using cell colony formation and CCK-8 assays. Cell cycle was performed by PI staining with flow cytometry. Apoptosis was evaluated using Annexin V-Phycoerythrin double staining and flow cytometry. DNA damage was detected through comet assay and immunofluorescence assay. In vivo, apoptosis and anti-tumor effects were assessed using the TUNEL assay, a nude mouse model, and immunohistochemistry (IHC). Co-immunoprecipitation assay was used to detect protein-protein interactions. We analyzed Wee1, PKMYT1, and Stat1 expression in pan-cancer studies using the Ualcan public database and assessed their prognostic implications with Kaplan-Meier curves.

RESULT

PD0166285, a Wee1 inhibitor, effectively inhibits Wee1 activity, promoting cell entry into a mitotic crisis. Moreover, PD0166285 sensitizes cells to cisplatin, enhancing clinical outcomes. Our study demonstrated that PD016628 regulates the cell cycle through Rad51 and results in cell cycle arrest at the G2/M phase. We observed increased apoptosis in tumor cells treated with PD0166285, particularly when combined with cisplatin, indicating an enhanced apoptotic response. The upregulation of γ-H2AX serves as an indicator of mitotic catastrophe. Co-immunoprecipitation and data analysis revealed that apoptosis in LUSC is mediated through the Stat1 pathway, accompanied by decreased levels of Socs3. Furthermore, IHC staining confirmed significant differences in the expression of Phospho-CDK1 and γ-H2AX in LUSCs, suggesting involvement in DNA damage.

CONCLUSIONS

In summary, our study suggests that PD0166285, an inhibitor of Wee1, sensitizes LUSC cells to cisplatin and modulates DNA damage and apoptosis pathways through Rad51 and Stat1, respectively. These findings highlight the combination of PD0166285 and cisplatin as a promising therapeutic approach for treating LUSC.

Elucidating the Selective Mechanism of Drugs Targeting Cyclin-Dependent Kinases with Integrated MetaD-US Simulation

Cyclin-dependent kinases (CDKs), including CDK12 and CDK13, play crucial roles in regulating the cell cycle and RNA polymerase II activity, making them vital targets for cancer therapies. SR4835 is a selective inhibitor of CDK12/13, showing significant potential for treating triple-negative breast cancer. To elucidate the selective mechanism of SR4835 among three CDKs (CDK13/12/9), we developed an innovative enhanced sampling method, integrated well-tempered metadynamics-umbrella sampling (IMUS). IMUS synergistically combines the comprehensive pathway exploration capability of well-tempered metadynamics (WT-MetaD) with the precise free energy calculation capability of umbrella sampling, enabling the efficient and accurate characterization of drug-target interactions. The accurate calculation of binding free energy and the detailed analysis of the kinetic mechanism of the drug-target interaction using IMUS successfully elucidate the drug selectivity mechanism targeting the three CDKs, showing that the selectivity is primarily arising from differences in the stability of H-bonds within the Hinge region of the kinases and the interaction patterns during the protein-ligand recognition process. These findings also underscore the utility of IMUS in efficiently and accurately capturing drug-target interaction processes with clear mechanisms.

Discovery of Indole-Thiourea Derivatives as Tyrosinase Inhibitors: Synthesis, Biological Evaluation, Kinetic Studies, and In Silico Analysis

Tyrosinase, a key enzyme in melanin synthesis, represents a crucial therapeutic target for hyperpigmentation disorders due to excessive melanin production. This study aimed to design and evaluate a series of indole-thiourea derivatives by conjugating thiosemicarbazones with strong tyrosinase inhibitory activity to indole. Among these derivatives, compound 4b demonstrated tyrosinase inhibitory activity with an IC50 of 5.9 ± 2.47 μM, outperforming kojic acid (IC50 = 16.4 ± 3.53 μM). Kinetic studies using Lineweaver-Burk plots confirmed competitive inhibition by compound 4b. Its favorable ADMET and drug-likeness properties make compound 4b a promising therapeutic candidate with a reduced risk of toxicity. Molecular docking revealed that the compounds bind strongly to mushroom tyrosinase (mTYR) and human tyrosinase-related protein 1 (TYRP1), with compound 4b showing superior binding energies of -7.0 kcal/mol (mTYR) and -6.5 kcal/mol (TYRP1), surpassing both kojic acid and tropolone. Molecular dynamics simulations demonstrated the stability of the mTYR-4b complex with low RMSD and RMSF and consistent Rg and SASA values. Persistent strong hydrogen bonds with mTYR, along with favorable Gibbs free energy and MM/PBSA calculations (-19.37 kcal/mol), further support stable protein-ligand interactions. Overall, compound 4b demonstrated strong tyrosinase inhibition and favorable pharmacokinetics, highlighting its potential for treating pigmentary disorders.

Synthesis and biological evaluation of 4-phenyl-5-quinolinyl substituted isoxazole analogues as potent cytotoxic and tubulin polymerization inhibitors against ESCC

The identification of chemically different inhibitors that target the colchicine site of tubulin is still of great value for cancer treatment. Combretastatin A-4(CA-4), a naturally occurring colchicine-site binder characterized by its structural simplicity and biological activity, has served as a structural blueprint for the development of novel analogues with improved safety and therapeutic efficacy. In this study, a library of forty-eight 4-phenyl-5-quinolinyl substituted triazole, pyrazole or isoxazole analouges of CA-4, were synthesized and evaluated for their cytotoxicity against Esophageal Squamous Cell Carcinoma (ESCC) cell lines. Compound C11, which features a 2-methyl substitution at the quinoline and carries an isoxazole ring, emerged as the most promising, with 48 h IC50s of less than 20 nmol/L against two ESCC cell lines. The findings from EBI competitive assay, CETA, and in vitro tubulin polymerization assay of C11 are consistent with those of the positive control colchicine, demonstrating the clear affinity of compound C11 to the colchicine binding site. The subsequent cellular-based mechanism studies revealed that C11 significantly inhibited ESCC cell proliferation, arrested cell cycle at the M phase, induced apoptosis, and impeded migration. Experiments conducted in vivo further confirmed that C11 effectively suppressed the growth of ESCC without showing any toxicity towards the selected animal species. Overall, our research suggests that the tubulin polymerization inhibitor incorporating quinoline and the isoxazole ring may deserve consideration for cancer therapy.

A Chronicle Review of In-Silico Approaches for Discovering Novel Antimicrobial Agents to Combat Antimicrobial Resistance

Antimicrobial resistance (AMR) poses a foremost threat to global health, necessitating innovative strategies for discovering antimicrobial agents. This review explores the role and recent advances of in-silico techniques in identifying novel antimicrobial agents and combating AMR giving few briefings of recent case studies of AMR. In-silico techniques, such as homology modeling, virtual screening, molecular docking, pharmacophore modeling, molecular dynamics simulation, density functional theory, integrated machine learning, and artificial intelligence, are systematically reviewed for their utility in discovering antimicrobial agents. These computational methods enable the rapid screening of large compound libraries, prediction of drug-target interactions, and optimization of drug candidates. The review discusses integrating in-silico approaches with traditional experimental methods and highlights their potential to accelerate the discovery of new antimicrobial agents. Furthermore, it emphasizes the significance of interdisciplinary collaboration and data-sharing initiatives in advancing antimicrobial research. Through a comprehensive discussion of the latest developments in in-silico techniques, this review provides valuable insights into the future of antimicrobial research and the fight against AMR.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s12088-024-01355-x.

A glimpse into the hidden world of the flexible C-terminal protein binding domains of human RAD52

Human RAD52 protein binds DNA and is involved in genomic stability maintenance and several forms of DNA repair, including homologous recombination and single-strand annealing. Despite its importance, there are very few structural details about the variability of the RAD52 ring size and the RAD52 C-terminal protein-protein interaction domains. Even recent attempts to employ cryogenic electron microscopy (cryoEM) methods on full-length yeast and human RAD52 do not reveal interpretable structures for the C-terminal half that contains the replication protein A (RPA) and RAD51 binding domains. In this study, we employed the monodisperse purification of two RAD52 deletion constructs and small angle X-ray scattering (SAXS) to construct a structural model that includes RAD52's RPA binding domain. This model is of interest to DNA repair specialists as well as for drug development against HR-deficient cancers.

Development and therapeutic potential of DNA-dependent protein kinase inhibitors

The deployment of DNA damage response (DDR) combats various forms of DNA damage, ensuring genomic stability. Cancer cells' propensity for genomic instability offers therapeutic opportunities to selectively kill cancer cells by suppressing the DDR pathway. DNA-dependent protein kinase (DNA-PK), a nuclear serine/threonine kinase, is crucial for the non-homologous end joining (NHEJ) pathway in the repair of DNA double-strand breaks (DSBs). Therefore, targeting DNA-PK is a promising cancer treatment strategy. This review elaborates on the structures of DNA-PK and its related large protein, as well as the development process of DNA-PK inhibitors, and recent advancements in their clinical application. We emphasize our analysis of the development process and structure-activity relationships (SARs) of DNA-PK inhibitors based on different scaffolds. We hope this review will provide practical information for researchers seeking to develop novel DNA-PK inhibitors in the future.

FYN as an emerging biological biomarker for prognosis and potential therapeutic target in LGG

OBJECTIVES

This study aimed to explore the expression, clinical significance, and functional mechanism of FYN in lower-grade gliomas (LGG).

METHODS

The mRNA and protein expression of FYN in LGG tissues were detected using databases including OncoLnc, GEPIA, and Human protein atlas (HPA). The UCSC Xena browser, TIMER, STRING and Metascape databases were used to investigate Kaplan-Meier survival curves, correlations between FYN expression and various types of immune cell infiltration, protein interaction network and possible functional mechanism.

RESULTS

FYN expression in LGG, IDH mutation or 1p19q co-deletion subgroup was significantly higher than in corresponding control groups (p < 0.05). Patients with higher FYN expression had longer overall survival (p < 0.05). Male or no 1p19q co-deletion groups with higher FYN expression also had longer overall survival (p < 0.05). FYN expression had close correlation with infiltrating levels of cell purity, CD4+T cells, macrophages, and CD8+T cells (p < 0.05). Protein interaction network result showed correlation among FYN, SH2D1A, LCK, CAV1, SRC, CBL and PTK2. Functional enrichment analysis revealed that FYN and its related genes mainly participated in bacterial invasion of epithelial cells and natural killer cell mediated cytotoxicity. Peptidyl-tyrosine phosphorylation, negative regulation of anoikis, immune effector process, transmembrane receptor protein tyrosine kinase signaling pathway, epidermal growth factor receptor signaling pathway, and negative regulation of protein modification process may be the critical biological process.

CONCLUSIONS

FYN is up-expressed in LGG and related to its good prognosis. It participated in tumor pathophysiological processes and may be a therapeutic target for LGG.

Single-residue effects on the behavior of a nascent polypeptide chain inside the ribosome exit tunnel

Nascent polypeptide chains (NCs) are extruded from the ribosome through an exit tunnel (ET) traversing the large ribosomal subunit. The ET's irregular and chemically complex wall allows for various NC-ET interactions. Translational arrest peptides (APs) bind in the ET to induce translational arrest, a property that can be exploited to study NC-ET interactions by Force Profile Analysis (FPA). We employed FPA and molecular dynamics (MD) simulations to investigate how individual residues placed in a glycine-serine repeat segment within an AP-stalled NC interact with the ET to exert a pulling force on the AP and release stalling. Our results indicate that large and hydrophobic residues generate a pulling force on the NC when placed ≳10 residues away from the peptidyl transfer center (PTC). Moreover, an asparagine placed 12 residues from the PTC makes a specific stabilizing interaction with the tip of ribosomal protein uL22 that reduces the pulling force on the NC, while a lysine or leucine residue in the same position increases the pulling force. Finally, the MD simulations suggest how the Mannheimia succiniproducens SecM AP interacts with the ET to promote translational stalling.

All-atom modeling of methacrylate-based multi-modal chromatography resins for Langmuir constant prediction of peptides

In downstream processing, the intricate nature of the interactions between biomolecules and adsorbent materials presents a significant challenge in the prediction of their binding and elution behaviors. This complexity is further heightened in multi-modal chromatography (MMC), which employs two distinct binding mechanisms. To gain a deeper understanding of the involved interactions, simulating the adsorption of biomolecules on resin surfaces is a focal point of ongoing research. However, previous studies often simplified the adsorbent surface, modeling it as a flat or slightly curved plane without including a realistic backbone structure. Here, we introduce and validate two novel workflows aimed at predicting peptide binding behaviors in MMC, specifically targeting methacrylate-based resins. Our first achievement was the development of an all-atom model of a commercial MMC resin surface, incorporating its polymethacrylic backbone. Furthermore, we established and tested a workflow for rapid calculations of binding free energies (ΔG) with 10 linear peptides as target molecules. These ΔG calculations were effectively used to predict Langmuir constants, achieving a high coefficient of determination (R²) of 0.96. In subsequent benchmarking tests, our model outperformed established, simpler resin surface models in terms of predictive capabilities.

Expression Pattern of RpCSP6 from Rhopalosiphum padi and Its Binding Mechanism with Deltamethrin: Insights into Chemosensory Protein-Mediated Insecticide Resistance

The mechanisms of insecticide resistance are complex. Recent studies have revealed a novel mechanism involving the chemosensory system in insecticide resistance. However, the specific binding mechanism between olfactory-related genes and insecticides needs to be clarified. In this study, the binding mechanism between pyrethroid insecticide deltamethrin and RpCSP6 from Rhopalosiphum padi was investigated by using computational and multiple experimental methods. RpCSP6 was expressed in different tissues and developmental stages of R. padi and can be induced by deltamethrin. Knockdown of RpCSP6 significantly increased the susceptibility of R. padi to deltamethrin. The binding affinity of RpCSP6 to 24 commonly used insecticides was measured. Seven key residues were found to steadily interact with deltamethrin, indicating their significance in the binding affinity to the insecticide. Our research provided insights for effectively analyzing the binding mechanism of insect CSPs with insecticides, facilitating the development of new and effective insecticides that target insect CSPs.

Reporting the anti-neuroinflammatory potential of selected spondias mombin flavonoids through network pharmacology and molecular dynamics simulations

Neuroinflammation plays a pivotal role in the development and progression of neurodegenerative diseases, with a complex interplay between immune responses and brain activity. Understanding this interaction is crucial for identifying therapeutic targets and developing effective treatments. This study aimed to explore the neuroprotective properties of flavonoid compounds from Spondias mombin via the modulation of neuroinflammatory pathway using a comprehensive in-silico approach, including network pharmacology, molecular docking, and dynamic simulations. Active flavonoid ingredients from S. mombin were identified, and their potential protein targets were predicted through Network Pharmacology. Molecular docking was conducted to determine the binding affinities of these compounds against targets obtained from network pharmacology, prioritizing docking scores ≥ - 8.0 kcal/mol. Molecular dynamic simulations (MDS) assessed the stability and interaction profiles of these ligand-protein complexes. The docking study highlighted ≥ - 8.0 kcal/mol for the ligands (catechin and epicatechin) against FYN kinase as a significant target. However, these compounds failed the blood-brain barrier (BBB) permeability test. MDS confirmed the stability of catechin and the reference ligand at the FYN kinase active site, with notable interactions involving hydrogen bonds, hydrophobic contacts, and water bridges. GLU54 emerged as a key residue in the catechin-FYN complex stability due to its prolonged hydrogen bond interaction. The findings underscore the potential of S. mombin flavonoids as therapeutic agents against neuroinflammation, though optimization and nanotechnology-based delivery methods are suggested to enhance drug efficacy and overcome BBB limitations.

Graphical abstract

Hit-to-Lead Optimization of Heterocyclic Carbonyloxycarboximidamides as Selective Antagonists at Human Adenosine A3 Receptor

Antagonism of the human adenosine A3 receptor (hA3R) has potential therapeutic application. Alchemical relative binding free energy calculations of K18 and K32 suggested that the combination of a 3-(2,6-dichlorophenyl)-isoxazolyl group with 2-pyridinyl at the ends of a carbonyloxycarboximidamide group should improve hA3R affinity. Of the 25 new analogues synthesized, 37 and 74 showed improved hA3R affinity compared to K18 (and K32). This was further improved through the addition of a bromine group to the 2-pyridinyl at the 5-position, generating compound 39. Alchemical relative binding free energy calculations, mutagenesis studies and MD simulations supported the compounds' binding pattern while suggesting that the bromine of 39 inserts deep into the hA3R orthosteric pocket, so highlighting the importance of rigidification of the carbonyloxycarboximidamide moiety. MD simulations highlighted the importance of rigidification of the carbonyloxycarboximidamide, while suggesting that the bromine of 39 inserts deep into the hA3R orthosteric pocket, which was supported through mutagenesis studies 39 also selectively antagonized endogenously expressed hA3R in nonsmall cell lung carcinoma cells, while pharmacokinetic studies indicated low toxicity enabling in vivo evaluation. We therefore suggest that 39 has potential for further development as a high-affinity hA3R antagonist.

An integrative structural study of the human full-length RAD52 at 2.2 Å resolution

Human RAD52 (RAD52) is a DNA-binding protein involved in many DNA repair mechanisms and genomic stability maintenance. In the last few years, this protein was discovered to be a promising novel pharmacological target for anticancer strategies. Although the interest in RAD52 has exponentially grown in the previous decade, most information about its structure and mechanism still needs to be elucidated. Here, we report the 2.2 Å resolution cryo-EM reconstruction of the full-length RAD52 (FL-RAD52) protein. This allows us to describe the hydration shell of the N-terminal region of FL-RAD52, which is structured in an undecamer ring. Water molecules coordinate with protein residues to promote stabilization inside and among the protomers and within the inner DNA binding cleft to drive protein-DNA recognition. Additionally, through a multidisciplinary approach involving SEC-SAXS and computational methods, we comprehensively describe the highly flexible and dynamic organization of the C-terminal portion of FL-RAD52. This work discloses unprecedented structural details on the FL-RAD52, which will be critical for characterizing its mechanism of action and inhibitor development, particularly in the context of novel approaches to synthetic lethality and anticancer drug discovery.

Enhancing SILCS-MC via GPU Acceleration and Ligand Conformational Optimization with Genetic and Parallel Tempering Algorithms

In the domain of computer-aided drug design, achieving precise and accurate estimates of ligand-protein binding is paramount in the context of screening extensive drug libraries and performing ligand optimization. A fundamental aspect of the SILCS (site identification by ligand competitive saturation) methodology lies in the generation of comprehensive 3D free-energy functional group affinity maps (FragMaps), encompassing the entirety of the target molecule structure. These FragMaps offer an intricate landscape of functional group affinities across the protein, bilayer, or RNA, acting as the basis for subsequent SILCS-Monte Carlo (MC) simulations wherein ligands are docked to the target molecule. To augment the efficiency and breadth of ligand sampling capabilities, we implemented an improved SILCS-MC methodology. By harnessing the parallel computing capability of GPUs, our approach facilitates concurrent calculations over multiple ligands and binding sites, markedly enhancing the computational efficiency. Moreover, the integration of a genetic algorithm (GA) with MC allows us to employ an evolutionary approach to perform ligand sampling, assuring enhanced convergence characteristics. In addition, the potential utility of parallel tempering (PT) to improve sampling was investigated. Implementation of SILCS-MC on GPU architecture is shown to accelerate the speed of SILCS-MC calculations by over 2-orders of magnitude. Use of GA and PT yield improvements over Markov-chain MC, increasing the precision of the resultant docked orientations and binding free energies, though the extent of improvements is relatively small. Accordingly, significant improvements in speed are obtained through the GPU implementation with minor improvements in the precision of the docking obtained via the tested GA and PT algorithms.

Natural compounds from herbs and nutraceuticals as glycogen synthase kinase-3β inhibitors in Alzheimer's disease treatment

BACKGROUND

Alzheimer's disease (AD) pathogenesis is complex. The pathophysiology is not fully understood, and safe and effective treatments are needed. Glycogen synthase kinase 3β (GSK-3β) mediates AD progression through several signaling pathways. Recently, several studies have found that various natural compounds from herbs and nutraceuticals can significantly improve AD symptoms.

AIMS

This review aims to provide a comprehensive summary of the potential neuroprotective impacts of natural compounds as inhibitors of GSK-3β in the treatment of AD.

MATERIALS AND METHODS

We conducted a systematic literature search on PubMed, ScienceDirect, Web of Science, and Google Scholar, focusing on in vitro and in vivo studies that investigated natural compounds as inhibitors of GSK-3β in the treatment of AD.

RESULTS

The mechanism may be related to GSK-3β activation inhibition to regulate amyloid beta production, tau protein hyperphosphorylation, cell apoptosis, and cellular inflammation. By reviewing recent studies on GSK-3β inhibition in phytochemicals and AD intervention, flavonoids including oxyphylla A, quercetin, morin, icariin, linarin, genipin, and isoorientin were reported as potent GSK-3β inhibitors for AD treatment. Polyphenols such as schisandrin B, magnolol, and dieckol have inhibitory effects on GSK-3β in AD models, including in vivo models. Sulforaphene, ginsenoside Rd, gypenoside XVII, falcarindiol, epibrassinolides, 1,8-Cineole, and andrographolide are promising GSK-3β inhibitors.

CONCLUSIONS

Natural compounds from herbs and nutraceuticals are potential candidates for AD treatment. They may qualify as derivatives for development as promising compounds that provide enhanced pharmacological characteristics.

Active and allosteric site binding MM-QM studies of Methylidene tetracyclo derivative in PCSK9 protein intended to make a safe antilipidemic agent

Interaction of low-density lipoprotein receptors with proprotein convertase subtilisin/kexin type 9 (PCSK9) plays a vital part in causing atherosclerosis. It is the hidden precursor of clinical myocardial infarction (MI), stroke, CVD and estimates 60% of deaths worldwide. The current need is to design small molecules to prevent the interaction between PCSK9 and LDL receptors. This study aims to evaluate the interaction between Methylidene tetracyclo derivative and PCSK9 protein through conceptual studies and compare the same with the interaction of the standard atorvastatin. Also, a comparative study was performed to analyze the interaction of molecules inside the active and allosteric sites of PCSK9. The RCSB downloaded pdb file 7S5H and the above said ligands were optimized to the level of local minima energy and configured inside the active and allosteric sites. The stability of non-bonded interactions of the complexes were analyzed using Desmond MD simulation studies. The results of docking showed that the Methylidene tetracyclo molecule possesses a two-fold higher affinity of -10.894 kcal/mol in the active site and -10.884 kcal/mol in the allosteric site. The Phe379 amino acid enabled the Methylidene tetracyclo molecule to orient inside the active site. Nine H-bonds with 6 amino acids of allosteric site increased the binding affinity compared to Atorvastatin. The MD simulation studies confirmed the stability of the nonbonded interaction of Methylidene tetracyclo molecule throughout 100 ns. This confirms that the Methylidene tetracyclo molecule will be the better hit as well as the lead molecule to modulate the behavior of PCSK9 protein.Communicated by Ramaswamy H. Sarma.

Increased throughput in methods for simulating protein ligand binding and unbinding

By incorporating full flexibility and enabling the quantification of crucial parameters such as binding free energies and residence times, methods for investigating protein-ligand binding and unbinding via molecular dynamics provide details on the involved mechanisms at the molecular level. While these advancements hold promise for impacting drug discovery, a notable drawback persists: their relatively time-consuming nature limits throughput. Herein, we survey recent implementations which, employing a blend of enhanced sampling techniques, a clever choice of collective variables, and often machine learning, strive to enhance the efficiency of new and previously reported methods without compromising accuracy. Particularly noteworthy is the validation of these methods that was often performed on systems mirroring real-world drug discovery scenarios.

Structure-based discovery and rational design of microtubule-targeting agents

Microtubule-targeting agents (MTAs) have demonstrated remarkable efficacy as antitumor, antifungal, antiparasitic, and herbicidal agents, finding applications in the clinical, veterinary, and agrochemical industry. Recent advances in tubulin and microtubule structural biology have provided powerful tools that pave the way for the rational design of innovative small-molecule MTAs for future basic and applied life science applications. In this mini-review, we present the current status of the tubulin and microtubule structural biology field, the recent impact it had on the discovery and rational design of MTAs, and exciting avenues for future MTA research.

Design, synthesis, molecular modeling, in vitro evaluation of novel piperidine-containing hydrazone derivatives as cholinesterase inhibitors

In an effort to develop new and effective therapeutic agents for Alzheimer's disease, a series of hydrazone derivatives bearing piperidine rings have been designed and synthesized. The chemical structures of the compounds were characterized by various spectroscopic techniques. In vitro antioxidant and cholinesterase activities of the compounds were evaluated. Among the compounds, N12 exhibited the most antioxidant activity in all methods (CUPRAC, FRAP, DPPH, ABTS). In vitro acetylcholinesterase (AChE) activity results of the compounds showed good IC50 values between 14.124 ± 0.084 and 49.680 ± 0.110 µM were obtained (IC50 = 38.842 ± 0.053 µM for Donepezil). Among the compounds, N7 and N6 are much more effective derivatives than the standard compound donepezil with IC50 values of 14.124 ± 0.084 and 17.968 ± 0.072 µM, respectively. In vitro, butyrylcholinesterase (BChE) inhibition values of the compounds were between 13.505 ± 0.025 and 52.230 ± 0.027 μm. Among the compounds, N6 has the highest BChE inhibition with an IC50 value of 13.505 μm in the series. The cytotoxicity and AChE inhibitory activity of the compounds on SH-SY5Y cell lines were also evaluated. Kinetic studies were also performed to determine the behavior of the compounds as competitive or noncompetitive inhibitors. The binding modes of N6, which was determined to be highly effective according to in vitro analyses, with AChE and BChE were investigated using molecular docking studies, and the stability of the complexes was determined by molecular dynamics simulations. These findings indicated that AChE and BChE enzymes maintained their overall structural stability and compactness during interactions with compound N6.

New Horizons of Synthetic Lethality in Cancer: Current Development and Future Perspectives

In recent years, synthetic lethality has been recognized as a solid paradigm for anticancer therapies. The discovery of a growing number of synthetic lethal targets has led to a significant expansion in the use of synthetic lethality, far beyond poly(ADP-ribose) polymerase inhibitors used to treat BRCA1/2-defective tumors. In particular, molecular targets within DNA damage response have provided a source of inhibitors that have rapidly reached clinical trials. This Perspective focuses on the most recent progress in synthetic lethal targets and their inhibitors, within and beyond the DNA damage response, describing their design and associated therapeutic strategies. We will conclude by discussing the current challenges and new opportunities for this promising field of research, to stimulate discussion in the medicinal chemistry community, allowing the investigation of synthetic lethality to reach its full potential.

A Robust Induced Fit Docking Approach with the Combination of the Hybrid All-Atom/United-Atom/Coarse-Grained Model and Simulated Annealing

Molecular docking remains an indispensable tool in computational biology and structure-based drug discovery. However, the correct prediction of binding poses remains a major challenge for molecular docking, especially for target proteins where a substrate binding induces significant reorganization of the active site. Here, we introduce an Induced Fit Docking (IFD) approach named AA/UA/CG-SA-IFD, which combines a hybrid All-Atom/United-Atom/Coarse-Grained model with Simulated Annealing. In this approach, the core region is represented by the All-Atom(AA) model, while the protein environment beyond the core region and the solvent are treated with either the United-Atom (UA) or the Coarse-Grained (CG) model. By combining the Elastic Network Model (ENM) for the CG region, the hybrid model ensures a reasonable description of ligand binding and the environmental effects of the protein, facilitating highly efficient and reliable sampling of ligand binding through Simulated Annealing (SA) at a high temperature. Upon validation with two testing sets, the AA/UA/CG-SA-IFD approach demonstrates remarkable accuracy and efficiency in induced fit docking, even for challenging cases where the docked poses significantly deviate from crystal structures.

Incorporating Prior Knowledge in the Seeds of Adaptive Sampling Molecular Dynamics Simulations of Ligand Transport in Enzymes with Buried Active Sites

Because most proteins have buried active sites, protein tunnels or channels play a crucial role in the transport of small molecules into buried cavities for enzymatic catalysis. Tunnels can critically modulate the biological process of protein-ligand recognition. Various molecular dynamics methods have been developed for exploring and exploiting the protein-ligand conformational space to extract high-resolution details of the binding processes, a recent example being energetically unbiased high-throughput adaptive sampling simulations. The current study systematically contrasted the role of integrating prior knowledge while generating useful initial protein-ligand configurations, called seeds, for these simulations. Using a nontrivial system of a haloalkane dehalogenase mutant with multiple transport tunnels leading to a deeply buried active site, simulations were employed to derive kinetic models describing the process of association and dissociation of the substrate molecule. The most knowledge-based seed generation enabled high-throughput simulations that could more consistently capture the entire transport process, explore the complex network of transport tunnels, and predict equilibrium dissociation constants, koff/kon, on the same order of magnitude as experimental measurements. Overall, the infusion of more knowledge into the initial seeds of adaptive sampling simulations could render analyses of transport mechanisms in enzymes more consistent even for very complex biomolecular systems, thereby promoting drug development efforts and the rational design of enzymes with buried active sites.

Pseudoirreversible inhibition elicits persistent efficacy of a sphingosine 1-phosphate receptor 1 antagonist

Sphingosine 1-phosphate receptor 1 (S1PR1), a G protein-coupled receptor, is required for lymphocyte trafficking, and is a promising therapeutic target in inflammatory diseases. Here, we synthesize a competitive S1PR1 antagonist, KSI-6666, that effectively suppresses pathogenic inflammation. Metadynamics simulations suggest that the interaction of KSI-6666 with a methionine residue Met124 in the ligand-binding pocket of S1PR1 may inhibit the dissociation of KSI-6666 from S1PR1. Consistently, in vitro functional and mutational analyses reveal that KSI-6666 causes pseudoirreversible inhibition of S1PR1, dependent on the Met124 of the protein and substituents on the distal benzene ring of KSI-6666. Moreover, in vivo study suggests that this pseudoirreversible inhibition is responsible for the persistent activity of KSI-6666.

Synthesis and Biological Evaluation of Novel 2-Aroyl Benzofuran-Based Hydroxamic Acids as Antimicrotubule Agents

Because of synergism between tubulin and HDAC inhibitors, we used the pharmacophore fusion strategy to generate potential tubulin-HDAC dual inhibitors. Drug design was based on the introduction of a N-hydroxyacrylamide or a N-hydroxypropiolamide at the 5-position of the 2-aroylbenzo[b]furan skeleton, to produce compounds 6a-i and 11a-h, respectively. Among the synthesized compounds, derivatives 6a, 6c, 6e, 6g, 11a, and 11c showed excellent antiproliferative activity, with IC50 values at single- or double-digit nanomolar levels, against the A549, HT-29, and MCF-7 cells resistant towards the control compound combretastatin A-4 (CA-4). Compounds 11a and 6g were also 10-fold more active than CA-4 against the Hela cell line. When comparing the inhibition of tubulin polymerization versus the HDAC6 inhibitory activity, we found that 6a-g, 6i, 11a, 11c, and 11e, although very potent as inhibitors of tubulin assembly, did not have significant inhibitory activity against HDAC6.

Dataset for quantum-mechanical exploration of conformers and solvent effects in large drug-like molecules

We here introduce the Aquamarine (AQM) dataset, an extensive quantum-mechanical (QM) dataset that contains the structural and electronic information of 59,783 low-and high-energy conformers of 1,653 molecules with a total number of atoms ranging from 2 to 92 (mean: 50.9), and containing up to 54 (mean: 28.2) non-hydrogen atoms. To gain insights into the solvent effects as well as collective dispersion interactions for drug-like molecules, we have performed QM calculations supplemented with a treatment of many-body dispersion (MBD) interactions of structures and properties in the gas phase and implicit water. Thus, AQM contains over 40 global and local physicochemical properties (including ground-state and response properties) per conformer computed at the tightly converged PBE0+MBD level of theory for gas-phase molecules, whereas PBE0+MBD with the modified Poisson-Boltzmann (MPB) model of water was used for solvated molecules. By addressing both molecule-solvent and dispersion interactions, AQM dataset can serve as a challenging benchmark for state-of-the-art machine learning methods for property modeling and de novo generation of large (solvated) molecules with pharmaceutical and biological relevance.