An increasing number of drugs introduced to the market and numerous repositories of compounds with confirmed activity have posed the need to revalidate the state-of-the-art rules that determine the ranges of properties the compounds should possess to become future drugs. In this study, we designed a series of two chemotypes of aryl-piperazine hydantoin ligands of 5-HT7R, an attractive target in search for innovative CNS drugs, with higher molecular weight (close to or over 500). Consequently, 14 new compounds were synthesised and screened for their receptor activity accompanied by extensive docking studies to evaluate the observed structure-activity/properties relationships. The ADMET characterisation in terms of the biological membrane permeability, metabolic stability, hepatotoxicity, cardiotoxicity, and protein plasma binding of the obtained compounds was carried out in vitro. The outcome of these studies constituted the basis for the comprehensive challenge of computational tools for ADMET properties prediction. All the compounds possessed high affinity to the 5-HT7R (Ki below 250 nM for all analysed structures) with good selectivity over 5-HT6R and varying affinity towards 5-HT2AR, 5-HT1AR and D2R. For the best compounds of this study, the expression profile of genes associated with neurodegeneration, anti-oxidant response and anti-inflammatory function was determined, and the survival of the cells (SH-SY5Y as an in vitro model of Alzheimer\'s disease) was evaluated. One 5-HT7R agent (32) was characterised by a very promising ADMET profile, i.e. good membrane permeability, low hepatotoxicity and cardiotoxicity, and high metabolic stability with the simultaneous high rate of plasma protein binding and high selectivity over other GPCRs considered, together with satisfying gene expression profile modulations and neural cell survival. Such encouraging properties make it a good candidate for further testing and optimisation as a potential agent in the treatment of CNS-related disorders.

Every year, more than 19 million cancer cases are diagnosed, and this number continues to increase annually. Since standard treatment options have varying success rates for different types of cancer, understanding the biology of an individual\'s tumour becomes crucial, especially for cases that are difficult to treat. Personalised high-throughput profiling, using next-generation sequencing, allows for a comprehensive examination of biopsy specimens. Furthermore, the widespread use of this technology has generated a wealth of information on cancer-specific gene alterations. However, there exists a significant gap between identified alterations and their proven impact on protein function. Here, we present a bioinformatics pipeline that enables fast analysis of a missense mutation\'s effect on stability and function in known oncogenic proteins. This pipeline is coupled with a predictor that summarises the outputs of different tools used throughout the pipeline, providing a single probability score, achieving a balanced accuracy above 86%. The pipeline incorporates a virtual screening method to suggest potential FDA/EMA-approved drugs to be considered for treatment. We showcase three case studies to demonstrate the timely utility of this pipeline. To facilitate access and analysis of cancer-related mutations, we have packaged the pipeline as a web server, which is freely available at https://loschmidt.chemi.muni.cz/predictonco/ .Scientific contributionThis work presents a novel bioinformatics pipeline that integrates multiple computational tools to predict the effects of missense mutations on proteins of oncological interest. The pipeline uniquely combines fast protein modelling, stability prediction, and evolutionary analysis with virtual drug screening, while offering actionable insights for precision oncology. This comprehensive approach surpasses existing tools by automating the interpretation of mutations and suggesting potential treatments, thereby striving to bridge the gap between sequencing data and clinical application.

Organophosphates constitute a major class of pesticides widely employed in agriculture to manage insect pests. Their toxicity is attributed to their ability to inhibit the functioning of acetylcholinesterase (AChE), an essential enzyme for normal nerve transmission. Organophosphates, especially chlorpyrifos, have been a key component of the integrated pest management (IPM) in onions, effectively controlling onion maggot Delia antiqua, a severe pest of onions. However, the growing concerns over the use of this insecticide on human health and the environment compelled the need for an alternative organophosphate and a potential microbial agent for bioremediation to mitigate organophosphate pesticide pollution. In the present study, chloropyrifos along with five other organophosphate insecticides, phosmet, primiphos-methyl, isofenphos, iodofenphos and tribuphos, were screened against the target protein AChE of D. antiqua using molecular modeling and docking techniques. The results revealed that iodofenphos showed the best interaction, while tribuphos had the lowest interaction with the AChE based on comparative binding energy values. Further, protein-protein interaction analysis conducted using the STRING database and Cytoscap software revealed that AChE is linked with a network of 10 different proteins, suggesting that the function of AChE is disrupted through interaction with insecticides, potentially leading to disruption within the network of associated proteins. Additionally, an in silico study was conducted to predict the binding efficiency of two organophosphate degrading enzymes, organophosphohydrolase (OpdA) from Agrobacterium radiobacter and Trichoderma harzianum paraoxonase 1 like (ThPON1-like) protein from Trichoderma harzianum, with the selected insecticides. The analysis revealed their potential to degrade the pesticides, offering a promising alternative before going for cumbersome onsite remediation.

We previously reported on the interaction of 10-chloro-7H-benzo[de]benzo[4,5]imidazo[2,1-a]isoquinolin-7-one (10-Cl-BBQ) with the Aryl hydrocarbon Receptor (AhR) and selective growth inhibition in breast cancer cell lines. We now report on a library of BBQ analogues with substituents on the phenyl and naphthyl rings for biological screening. Herein, we show that absence of the phenyl Cl of 10-Cl-BBQ to produce the simple BBQ molecule substantially enhanced the growth inhibitory effect with GI50 values of 0.001-2.1 μM in select breast cancer cell lines MCF-7, T47D, ZR-75-1, SKBR3, MDA-MB-468, BT20, BT474 cells, while having modest effects of 2.1-7 μM in other cell lines including HT29, U87, SJ-G2, A2780, DU145, BE2-C, MIA, MDA-MB-231 or normal breast cells, MCF10A (3.2 μM). The most potent growth inhibitory effect of BBQ was observed in the triple negative cell line, MDA-MB-468 with a GI50 value of 0.001 μM, presenting a 3,200-fold greater response than in the normal MCF10A breast cells. Additions of Cl, CH3, CN to the phenyl ring and ring expansion from benzoimidazole to dihydroquinazoline hindered the growth inhibitory potency of the BBQ analogues by blocking potential sites of CYP1 oxidative metabolism, while addition of Cl or NO2 to the naphthyl rings restored potency. In a cell-based reporter assay all analogues induced 1.2 to 10-fold AhR transcription activation. Gene expression analysis confirmed the induction of CYP1 oxygenases by BBQ. The CYP1 inhibitor α-naphthoflavone, and the SULT1A1 inhibitor quercetin significantly reduced the growth inhibitory effect of BBQ, confirming the importance of both phase I and II metabolic activation for growth inhibition. Conventional molecular modelling/docking revealed no significant differences between the binding poses of the most and least active analogues. More detailed DFT analysis at the DSD-PBEP86/Def-TZVPP level of theory could not identify significant geometric or electronic changes which would account for this varied AhR activation. Generation of Fukui functions at the same level of theory showed that CYP1 metabolism will primarily occur at the phenyl head group of the analogues, and substituents within this ring lead to lower cytotoxicity.

The comprehension of molecular structure is pivotal in chemistry education. Over the past decade, Mahidol University International College has employed various teaching tools for the introductory chemistry laboratory class. This paper outlines our evolutionary shift from traditional tools, such as plastic and plasticine models, to the integration of computer software, and ultimately to augmented reality (AR) and virtual reality (VR) tools-specifically, MoleculARweb and MolecularWebXR developed by École Polytechnique Fédérale de Lausanne researchers. In this paper, we detail the implementation of these tools in our classes and present the outcomes of student surveys. Our instructional focus encompasses VSEPR, Atomic Orbitals, Molecular Orbitals, Skeletal Formula, and Enantiomers. This paper not only serves as a model for educators in general chemistry at secondary school or university levels to incorporate technology into their classrooms but also showcases a collaborative endeavor between Swiss and Thai researchers.

This study introduces (S)-Opto-prop-2, a second-generation photoswitchable ligand designed for precise modulation of β2-adrenoceptor (β2AR). Synthesised by incorporating an azobenzene moiety with propranolol, (S)-Opto-prop-2 exhibited a high PSScis (photostationary state for cis isomer) percentage (∼90 %) and a favourable half-life (>10 days), facilitating diverse bioassay measurements. In vitro, the cis-isomer displayed substantially higher β2AR binding affinity than the trans-isomer (1000-fold), making (S)-Opto-prop-2 one of the best photoswitchable GPCR (G protein-coupled receptor) ligands reported so far. Molecular docking of (S)-Opto-prop-2 in the X-ray structure of propranolol-bound β2AR followed by site-directed mutagenesis studies, identified D1133.32, N3127.39 and F2896.51 as crucial residues that contribute to ligand-receptor interactions at the molecular level. In vivo efficacy was assessed using a rabbit ocular hypertension model, revealing that the cis isomer mimicked propranolol\'s effects in reducing intraocular pressure, while the trans isomer was inactive. Dynamic optical modulation of β2AR by (S)-Opto-prop-2 was demonstrated in two different cAMP bioassays and using live-cell confocal imaging, indicating reversible and dynamic control of β2AR activity using the new photopharmacology tool. In conclusion, (S)-Opto-prop-2 emerges as a promising photoswitchable ligand for precise and reversible β2AR modulation with light. The new tool shows superior cis-on binding affinity, one of the largest reported differences in affinity (1000-fold) between its two configurations, in vivo efficacy, and dynamic modulation. This study contributes valuable insights into the evolving field of photopharmacology, offering a potential avenue for targeted therapy in β2AR-associated pathologies.

BACKGROUND: HIV-1 produces Tat, a crucial protein for transcription, viral replication, and CNS neurotoxicity. Tat interacts with TAR, enhancing HIV reverse transcription. Subtype C Tat variants (C31S, R57S, Q63E) are associated with reduced transactivation and neurovirulence compared to subtype B. However, their precise impact on Tat-TAR binding is unclear. This study investigates how these substitutions affect Tat-TAR interaction.
METHODS: We utilized molecular modelling techniques, including MODELLER, to produce precise three-dimensional structures of HIV-1 Tat protein variants. We utilized Tat subtype B as the reference or wild type, and generated Tat variants to mirror those amino acid variants found in Tat subtype C. Subtype C-specific amino acid substitutions were selected based on their role in the neuropathogenesis of HIV-1. Subsequently, we conducted molecular docking of each Tat protein variant to TAR using HDOCK, followed by molecular dynamic simulations.
RESULTS: Molecular docking results indicated that Tat subtype B (TatWt) showed the highest affinity for the TAR element (-262.07), followed by TatC31S (-261.61), TatQ63E (-256.43), TatC31S/R57S/Q63E (-238.92), and TatR57S (-222.24). However, binding free energy analysis showed higher affinities for single variants TatQ63E (-349.2 ± 10.4 kcal/mol) and TatR57S (-290.0 ± 9.6 kcal/mol) compared to TatWt (-247.9 ± 27.7 kcal/mol), while TatC31S and TatC31S/R57SQ/63E showed lower values. Interactions over the protein trajectory were also higher for TatQ63E and TatR57S compared to TatWt, TatC31S, and TatC31S/R57SQ/63E, suggesting that modifying amino acids within the Arginine/Glutamine-rich region notably affects TAR interaction. Single amino acid mutations TatR57S and TatQ63E had a significant impact, while TatC31S had minimal effect. Introducing single amino acid variants from TatWt to a more representative Tat subtype C (TatC31S/R57SQ/63E) resulted in lower predicted binding affinity, consistent with previous findings.
CONCLUSIONS: These identified amino acid positions likely contribute significantly to Tat-TAR interaction and the differential pathogenesis and neuropathogenesis observed between subtype B and subtype C. Additional experimental investigations should prioritize exploring the influence of these amino acid signatures on TAR binding to gain a comprehensive understanding of their impact on viral transactivation, potentially identifying them as therapeutic targets.

Occupancy of prostate cancer (PCa) cell androgen receptors (AR) signals proliferation, therefore testosterone biosynthesis inhibitors and AR antagonists are important PCa treatments. Conversely, androgen mimics (e.g., prednisone) used in management of PCa might cause proliferation. The balance between PCa proliferation and inhibition predicts treatment success. We used in silico molecular modelling to explore interactions between ARs, androgens (testosterone, dihydrotestosterone (DHT)) and drugs used to treat (bicalutamide) and manage (dexamethasone, prednisone, hydrocortisone) PCa. We found that hydrogen (H-) bonds between testosterone, DHT and Arg752, Asn705 and Thr877 followed by ligand binding cleft hydrophobic interactions signal proliferation, whereas bicalutamide antagonism is via Phe764 interactions. Hydrocortisone, dexamethasone and prednisone H-bond Asn705 and Thr877, but not Arg752 in the absence of a water molecule. Studies with a bicalutamide agonist AR mutation showed different amino acid interactions, indicating testosterone and DHT would not promote proliferation as effectively as via the native receptor. However, hydrocortisone and bicalutamide form Arg752 and Asn705 H-bonds indicating agonism. Our results suggest that as PCa progresses the resulting mutations will change the proliferative response to androgens and their drug mimics, which have implications for the treatment of prostate cancer.

Peptide-based self-assembly has been used to produce a wide range of nanostructures. While most of these systems involve self-assembly of α-peptides, more recently β-peptides have also been shown to undergo supramolecular self-assembly, and have been used to produce materials for applications in tissue engineering, cell culture and drug delivery. In order to engineer new materials with specific structure and function, theoretical molecular modelling can provide significant insights into the collective balance of non-covalent interactions that drive the self-assembly and determine the structure of the resultant supramolecular materials under different conditions. However, this approach has only recently become feasible for peptide-based self-assembled nanomaterials, particularly those that incorporate non α-amino acids. This perspective provides an overview of the challenges associated with computational modelling of the self-assembly of β-peptides and the recent success using a combination of experimental and computational techniques to provide insights into the self-assembly mechanisms and fully atomistic models of these new biocompatible materials.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome encodes 29 proteins including four structural, 16 nonstructural (nsps), and nine accessory proteins (https://epimedlab.org/sars-cov-2-proteome/). Many of these proteins contain potential targetable sites for the development of antivirals. Despite the widespread use of vaccinations, the emergence of variants necessitates the investigation of new therapeutics and antivirals. Here, the EpiMed Coronabank Chemical Collection (https://epimedlab.org/crl/) was utilized to investigate potential antivirals against the nsp14 exoribonuclease (ExoN) domain. Molecular docking was performed to evaluate the binding characteristics of our chemical library against the nsp14 ExoN site. Based on the initial screen, trisjuglone, ararobinol, corilagin, and naphthofluorescein were identified as potential lead compounds. Molecular dynamics (MD) simulations were subsequently performed, with the results highlighting the stability of the lead compounds in the nsp14 ExoN site. Protein-RNA docking revealed the potential for the lead compounds to disrupt the interaction with RNA when bound to the ExoN site. Moreover, hypericin, cyanidin-3-O-glucoside, and rutin were previously identified as lead compounds targeting the papain-like protease (PLpro) naphthalene binding site. Through performing MD simulations, the stability and interactions of lead compounds with PLpro were further examined. Overall, given the critical role of the exonuclease activity of nsp14 in ensuring viral fidelity and the multifunctional role of PLpro in viral pathobiology and replication, these nsps represent important targets for antiviral drug development. Our databases can be utilized for in silico studies, such as the ones performed here, and this approach can be applied to other potentially druggable SARS-CoV-2 protein targets.