MMPBSA.py: An Efficient Program for End-State Free Energy Calculations

Theoretical calculation on degradation mechanism of novel copolyesters under CALB enzyme

Poly(butylene succinate-co-furandicarboxylate) (PBSF) and poly(butylene adipate-co-furandicarboxylate) (PBAF) are novel furandicarboxylic acid-based biodegradable copolyesters with great potential to replace fossil-derived terephthalic acid-based copolyesters such as poly(butylene succinate-co-terephthalate) (PBST) and poly(butylene adipate-co-terephthalate) (PBAT). In this study, quantum chemistry techniques after molecular dynamics simulations are employed to investigate the degradation mechanism of PBSF and PBAF catalyzed by Candida antarctica lipase B (CALB). Computational analysis indicates that the catalytic reaction follows a four-step mechanism resembling the ping-pong bibi mechanism, with the initial two steps being acylation reactions and the subsequent two being hydrolysis reactions. Notably, the first step of the hydrolysis is identified as the rate-determining step. Moreover, by introducing single-point mutations to expand the substrate entrance tunnel, the catalytic distance of the first acylation step decreases. Additionally, energy barrier of the rate-determining step is decreased in the PBSF system by site-directed mutations on key residues increasing hydrophobicity of the enzyme's active site. This study unprecedently show the substrate binding pocket and hydrophobicity of the enzyme's active site have the potential to be engineered to enhance the degradation of copolyesters catalyzed by CALB.

Rational design of monomeric IL37 variants guided by stability and dynamical analyses of IL37 dimers

IL37 plays important roles in the regulation of innate immunity and its oligomeric status is critical to these roles. In its monomeric state, IL37 can effectively inhibit the inflammatory response of IL18 by binding to IL18Rα, a capacity lost in its dimeric form, underlining the pivotal role of the oligomeric status of IL37 in its anti-inflammatory action. Until now, two IL37 dimer structures have been deposited in PDB, reflecting a substantial difference in their dimer interfaces. Given this discrepancy, we analyzed the PDB structures of the IL37 dimer (PDB IDs: 6ncu, 5hn1) along with a AF2-multimer prediction by molecular dynamics (MD) simulations. Results showed that the 5hn1 and AF2-predicted dimers have the same interface and stably maintained their conformations throughout simulations, while the recent IL37 dimer (PDB ID: 6ncu) with a different interface did not, proposing a possible issue with the recent IL37 dimer structure (6ncu). Next, focusing on the stable dimer structures, we have identified five critical positions of V71/Y85/I86/E89/S114, three new positions compared to the literature, that would reduce dimer stability without affecting the monomer structure. Two quintuple mutants were tested by MD simulations and showed partial or complete dissociation of the dimer. Overall, the insights gained from this study reinforce the validity of the 5hn1 and AF2 multimer structures, while also advancing our understanding of the IL37 dimer interface through the generation of monomer-locked IL37 variants.

Simulation- and AI-directed optimization of 4,6-substituted 1,3,5-triazin-2(1H)-ones as inhibitors of human DNA topoisomerase IIα

The 4,6-substituted-1,3,5-triazin-2(1H)-ones are promising inhibitors of human DNA topoisomerase IIα. To further develop this chemical class targeting the enzyme´s ATP binding site, the triazin-2(1H)-one substitution position 6 was optimized. Inspired by binding of preclinical substituted 9H-purine derivative, bicyclic substituents were incorporated at position 6 and the utility of this modification was validated by a combination of molecular simulations, dynamic pharmacophores, and free energy calculations. Considering also predictions of Deepfrag, a software developed for structure-based lead optimization based on deep learning, compounds with both bicyclic and monocyclic substitutions were synthesized and investigated for their inhibitory activity. The SAR data showed that the bicyclic substituted compounds exhibited good inhibition of topo IIα, comparable to their mono-substituted counterparts. Further evaluation on a panel of human protein kinases showed selectivity for the inhibition of topo IIα. Mechanistic studies indicated that the compounds acted predominantly as catalytic inhibitors, with some exhibiting topo IIα poison effects at higher concentrations. Integration of STD NMR experiments and molecular simulations, provided insights into the binding model and highlighted the importance of the Asn120 interaction and hydrophobic interactions with substituents at positions 4 and 6. In addition, NCI-60 screening demonstrated cytotoxicity of the compounds with bicyclic substituents and identified sensitive human cancer cell lines, underlining the translational relevance of our findings for further preclinical development of this class of compounds. The study highlights the synergy between simulation and AI-based approaches in efficiently guiding molecular design for drug optimization, which has implications for further preclinical development of this class of compounds.

Anilino-1,4-naphthoquinones as potent mushroom tyrosinase inhibitors: in vitro and in silico studies

Tyrosinase, a pivotal enzyme in melanin synthesis, is a primary target for the development of depigmenting agents. In this work, in vitro and in silico techniques were employed to identify novel tyrosinase inhibitors from a set of 12 anilino-1,4-naphthoquinone derivatives. Results from the mushroom tyrosinase activity assay indicated that, among the 12 derivatives, three compounds (1, 5, and 10) demonstrated the most significant inhibitory activity against mushroom tyrosinase, surpassing the effectiveness of the kojic acid. Molecular docking revealed that all studied derivatives interacted with copper ions and amino acid residues at the enzyme active site. Molecular dynamics simulations provided insights into the stability of enzyme-inhibitor complexes, in which compounds 1, 5, and particularly 10 displayed greater stability, atomic contacts, and structural compactness than kojic acid. Drug likeness prediction further strengthens the potential of anilino-1,4-naphthoquinones as promising candidates for the development of novel tyrosinase inhibitors for the treatment of hyperpigmentation disorders.

Metastatic effects of hydroxy-polycyclic aromatic hydrocarbons on liver cancer cells mediated by estrogen receptor α

Hydroxy-polycyclic aromatic hydrocarbons (OH-PAHs) are a growing worldwide concern because of their persistence, ubiquity, and toxicity. Nonetheless, research on the toxicological mechanisms of OH-PAHs remains sparse, particularly concerning the risk of liver cancer. This study evaluated the effects of OH-PAHs on disrupting estrogen receptor α (ERα) and subsequently facilitating hepatocellular invasion and metastasis. Results revealed that all six OH-PAHs exhibited ERα agonistic activities at noncytotoxic levels, which were partially validated using molecular docking (MD) and molecular dynamics simulations (MDS). Furthermore, OH-PAHs with ERα agonistic properties stimulated a concentration-dependent increase in the migration and invasion of HepG2 cells. In addition, they disturbed the expression of target genes associated with epithelial-mesenchymal transition (EMT) and extracellular matrix (ECM), and the invasion effects were significantly reversed by adding an ERα antagonist. Our results suggest an essential role of ERα in the metastasis of liver cancer cells induced by OH-PAHs and emphasize their potential ecological and health hazards.

Structure based computational RNA design towards MafA transcriptional repressor implicated in multiple myeloma

Multiple myeloma is recognized as the second most common hematological cancer. MafA transcriptional repressor is an established mediator of myelomagenesis. While there are multitude of drugs available for targeting various effectors in multiple myeloma, current literature lacks a candidate RNA based MafA modulator. Thus, using the structure of MafA homodimer-consensus target DNA, a computational effort was implemented to design a novel RNA based chemical modulator against MafA. First, available MafA-consensus DNA structure was employed to generate an RNA library. This library was further subjected to global docking to select the most plausible RNA candidates, preferring to bind DNA binding region of MafA. Following global docking, MD-ready complexes that were prepared via local docking program, were subjected to 500 ns of MD simulations. First, each of these MD simulations were analyzed for relative binding free energy through MM-PBSA method, which pointed towards a strong RNA based MafA binder, RNA1. Second, through a detailed MD analysis, RNA1 was shown to prefer binding to a single monomer of the dimeric DNA binding domain of MafA using higher number of hydrophobic interactions compared with positive control MafA-DNA complex. At the final phase, a principal component analyses was conducted, which led us to identify the actual interaction region of RNA1 and MafA monomer. Overall, to our knowledge, this is the first computational study that presents an RNA molecule capable of potentially targeting MafA protein. Furthermore, limitations of our study together with possible future implications of RNA1 in multiple myeloma were also discussed.

Discovery of novel thiazole derivatives containing pyrazole scaffold as PPAR-γ Agonists, α-Glucosidase, α-Amylase and COX-2 inhibitors; Design, synthesis and in silico study

A novel series of thiazole derivatives with pyrazole scaffold 16a-l as hybrid rosiglitazone/celecoxib analogs was designed, synthesized and tested for its PPAR-γ activation, α-glucosidase, α-amylase and COX-2 inhibitory activities. Regarding the anti-diabetic activity, all compounds were assessed in vitro against PPAR-γ activation, α-glucosidase and α-amylase inhibition in addition to in vivo hypoglycemic activity (one day and 15 days studies). Compounds 16b, 16c, 16e and 16 k showed good PPAR-γ activation (activation % ≈ 72-79 %) compared to that of the reference drug rosiglitazone (74 %). In addition, the same derivatives 16b, 16c, 16e and 16 k showed the highest inhibitory activities against α-glucosidase (IC50 = 0.158, 0.314, 0.305, 0.128 μM, respectively) and against α-amylase (IC50 = 32.46, 23.21, 7.74, 35.85 μM, respectively) compared to the reference drug acarbose (IC50 = 0.161 and 31.46 μM for α-glucosidase and α-amylase, respectively). The most active derivatives 16b, 16c, 16e and 16 k also revealed good in vivo hypoglycemic effect comparable to that of rosiglitazone. In addition, compounds 16b and 16c had the best COX-2 selectivity index (S.I. = 18.7, 31.7, respectively) compared to celecoxib (S.I. = 10.3). In vivo anti-inflammatory activity of the target derivatives 16b, 16c, 16e and 16 k supported the results of in vitro screening as the derivatives 16b and 16c (ED50 = 8.2 and 24 mg/kg, respectively) were more potent than celecoxib (ED50 = 30 mg/kg). In silico docking, ADME, toxicity, and molecular dynamic studies were carried out to explain the interactions of the most active anti-diabetic and anti-inflammatory compounds 16b, 16c, 16e and 16 k with the target enzymes in addition to their physiochemical parameters.

Computational strategies in Klebsiella pneumoniae vaccine design: navigating the landscape of in silico insights

The emergence of multidrug-resistant Klebsiella pneumoniae poses a grave threat to global public health, necessitating urgent strategies for vaccine development. In this context, computational tools have emerged as indispensable assets, offering unprecedented insights into klebsiellal biology and facilitating the design of effective vaccines. Here, a review of the application of computational methods in the development of K. pneumoniae vaccines is presented, elucidating the transformative impact of in silico approaches. Through a systematic exploration of bioinformatics, structural biology, and immunoinformatics techniques, the complex landscape of K. pneumoniae pathogenesis and antigenicity was unravelled. Key insights into virulence factors, antigen discovery, and immune response mechanisms are discussed, highlighting the pivotal role of computational tools in accelerating vaccine development efforts. Advancements in epitope prediction, antigen selection, and vaccine design optimisation are examined, highlighting the potential of in silico approaches to update vaccine development pipelines. Furthermore, challenges and future directions in leveraging computational tools to combat K. pneumoniae are discussed, emphasizing the importance of multidisciplinary collaboration and data integration. This review provides a comprehensive overview of the current state of computational contributions to K. pneumoniae vaccine development, offering insights into innovative strategies for addressing this urgent global health challenge.

In silico analysis of aptamer-RNA conjugate interactions with human transferrin receptor

The human transmembrane protein Transferrin Receptor-1 is regarded as a promising target for the systemic delivery of therapeutic agents, particularly of nucleic acid therapeutics, such as short double stranded RNAs. This ubiquitous receptor is involved in cellular iron uptake, keeping intracellular homeostasis. It is overexpressed in multiple cancer cell types and is internalized via clathrin-mediated endocytosis. In previous studies, a human transferrin receptor-1 RNA aptamer, identified as TR14 ST1-3, was shown to be capable of effectively internalizing into cells in culture and to deliver small, double stranded RNAs in vitro and in vivo, via systemic administration. To understand, at the molecular level, the aptamer binding to the receptor and the impact of conjugation with the therapeutic RNA, a multi-level in silico protocol was employed, including protein-aptamer docking, molecular dynamics simulations and free energy calculations. The competition for the binding pocket, between the aptamer and the natural ligand human Transferrin, was also evaluated. The results show that the aptamer binds to the same region as Transferrin, with residues from the helical domain showing a critical role. Moreover, the conjugation to the therapeutic RNA, was shown not to affect aptamer binding. Overall, this study provides an atomic-level understanding of aptamer association to human Transferrin Receptor-1 and of its conjugation with a short model-therapeutic RNA, providing also important clues for futures studies aiming to deliver other oligonucleotide-based therapeutics via Transferrin Receptor.

Characterizing the Cooperative Effect of PROTAC Systems with End-Point Binding Free Energy Calculation

Proteolytic targeting chimeras (PROTACs), as an emerging type of drug, function by proximity-based modalities that narrow the distance between a target protein and the E3 ubiquitin ligase to facilitate the ubiquitination labeling of the target protein for degradation. Although it is evidenced that the cooperativity of the PROTAC ternary interaction is one of the key factors affecting the degradation rate of a target protein, PROTAC design utilizing this indicator is still challenging because of the complicated/flexible interactions in a target-PROTAC-E3 ternary system. Therefore, developing reliable and practicable computational methods is of great interest for PROTAC design. Hence, in this study, we investigate the feasibility of using the end-point binding free energy calculation method, represented by molecular mechanics/Poisson-Boltzmann (generalized-Born) surface area (MM/PB(GB)SA), for characterizing cooperativity (including the stabilization and hook effects) of the PROTAC systems. The result shows that MM/GBSA is a good predictor in characterizing these effects under a relatively long molecular dynamics adjustment (50-100 ns) and low dielectric constant (εin = 1), with the Pearson correlation coefficient (rp) > 0.5 and 0.6 for the stabilization and hook effect, respectively. This study provides a feasible strategy for characterizing the cooperativity of the PROTAC systems, facilitating the rational design of PROTAC molecules.

Widely-targeted in silico and in vitro evaluation of veratrum alkaloid analogs as FAK inhibitors and dual targeting of FAK and Hh/SMO pathways for cancer therapy: A critical analysis

Focal Adhesive Kinase (FAK), a key player in aggressive cancers, mediates signals crucial for progression, invasion, and metastasis. Despite advances in targeted therapies, drug resistance is still a challenge, and survival rates remain low, particularly for late-stage patients, emphasizing the need for innovative cancer therapeutics. Cyclopamine, a veratrum alkaloid, has shown promising anti-tumor properties, but the search for more potent analogs with enhanced affinity for the biological target continues. This study employs a hybrid virtual screening approach combining pharmacophore model-based virtual screening (PB-VS) and docking-based virtual screening (DB-VS) to identify potential inhibitors of the FAK catalytic domain. PB-VS on the PubChem database yielded a set of hits, which were then docked with the FAK catalytic domain in two stages (1st and 2nd DB-VS). Hits were ranked based on docking scores and interactions with the active site. The top three compounds underwent molecular dynamics simulations, alongside two control compounds (SMO inhibitor(s) and FAK inhibitor(s)), to assess stability through RMSD, RMSF, Rg, and SASA analyses. ADMET properties were evaluated, and compounds were filtered based on drug-likeness criteria. Molecular dynamics simulations demonstrated the stability of compounds when complexed with the FAK catalytic domain. Compounds 16 (-25 kcal/mol), 88 (-27.47 kcal/mol), and 87 (-18.94 kcal/mol) exhibited comparable docking scores, interaction profiles, stability, and binding energies, indicating their potential as lead candidates. However, further validation and optimization through quantitative structure-activity relationship (QSAR) studies are essential to refine their efficacy and therapeutic potential. The in vitro cell-based assay demonstrated that compound 101PF, a FAK inhibitor, significantly inhibited the proliferation and migration of A549 cells. However, the results regarding the combined effects of FAK and SMO inhibitors were inconclusive, highlighting the need for further investigation. This study contributes to developing more effective anti-cancer drugs by improving the understanding of potential cyclopamine-based veratrum alkaloid analogs with enhanced interactions with the FAK catalytic domain.

Molecular insights into human phosphatidylserine synthase 1 reveal its inhibition promotes LDL uptake

In mammalian cells, two phosphatidylserine (PS) synthases drive PS synthesis. Gain-of-function mutations in the Ptdss1 gene lead to heightened PS production, causing Lenz-Majewski syndrome (LMS). Recently, pharmacological inhibition of PSS1 has been shown to suppress tumorigenesis. Here, we report the cryo-EM structures of wild-type human PSS1 (PSS1WT), the LMS-causing Pro269Ser mutant (PSS1P269S), and PSS1WT in complex with its inhibitor DS55980254. PSS1 contains 10 transmembrane helices (TMs), with TMs 4-8 forming a catalytic core in the luminal leaflet. These structures revealed a working mechanism of PSS1 akin to the postulated mechanisms of the membrane-bound O-acyltransferase family. Additionally, we showed that both PS and DS55980254 can allosterically inhibit PSS1 and that inhibition by DS55980254 activates the SREBP pathways, thus enhancing the expression of LDL receptors and increasing cellular LDL uptake. This work uncovers a mechanism of mammalian PS synthesis and suggests that selective PSS1 inhibitors have the potential to lower blood cholesterol levels.

Design and Synthesis of Novel Indole-Derived N-Methylcarbamoylguanidinyl Chitinase Inhibitors with Significantly Improved Insecticidal Activity

Chitinases play an important role in the molting process of insects and are potential targets for the development of green insecticides. Based on the feature that the +1/+2 sites in OfChtI, OfChtII, and OfChi-h have tryptophan residues in mismatch-parallel position, a strategy to introduce indole scaffold into chitinase inhibitors was proposed, and multitarget chitinase inhibitors containing N-methylcarbamoylguanidinyl and indole scaffold were successfully synthesized. The inhibitory activity showed that compound 8u exhibited significant inhibitory activity against OfChtI, OfChtII, and OfChi-h, with IC50 values of 0.7, 0.79, and 0.58 μM, and Ki values of 0.05 ± 0.005, 0.065 ± 0.004, and 0.025 ± 0.006 μM, respectively. In vivo insecticidal activity showed that compounds 8a and 8g exhibited excellent insecticidal activity against Plutella xylostella and Mythimna separata, with LC50 values of 0.79 and 9.17 mg/L against P. xylostella, respectively, and 3.58 and 83.09 mg/L against M. separata, respectively, making them the most potent chitinase inhibitors with in vivo insecticidal activity discovered to date. The inhibition mechanism and binding free energy results suggested that N-methylcarbamoylguanidinyl binds to the -1 catalytic site, while additional interactions acquired by π-π stacking and hydrophobic interactions of the indole scaffold with tryptophan increase the binding affinity of the targets to chitinases. This work provides a new direction for the development of chitinase inhibitors with compounds 8a and 8g potentially serving as promising candidates for pesticide development.

A Small Molecule Impedes the Aβ1-42 Tetramer Neurotoxicity by Preserving Membrane Integrity: Microsecond Multiscale Simulations

Amyloid-β (Aβ1-42) peptides aggregated into plaques deposited in the brain are the main hallmark of Alzheimer's disease (AD), a social and economic burden worldwide. In this context, insoluble Aβ1-42 fibrils are the main components of plaques. The recent trials that used approved AD drugs show that they can remove the fibrils from AD patients' brains, but they did not halt the course of the disease. Mounting evidence envisages that the soluble Aβ1-42 oligomers' interactions with the neuronal membrane trigger higher cell death than Aβ1-42 fibril interactions. Developing a compound that can alleviate the oligomer's toxicity is one of the most demanding tasks for curing the disease. We performed two molecular dynamics (MD) simulations in an explicit solvent model. In the first case, 55-μs of multiscale all-atom (AA)/coarse-grained (CG) MD simulations were carried out to decipher the impact of a previously described small anti-Aβ molecule, termed M30 (2-octahydroisoquinolin-2(1H)-ylethanamine), on an Aβ1-42 tetramer structure in close contact with a DMPC bilayer. In the second case, 15-μs AA/CG MD simulations were performed to rationalize the dynamics between Aβ1-42 and Aβ1-42-M30 tetramer complexes embedded in DMPC. On the membrane bilayer, we found that the Aβ1-42 tetramer penetrates the bilayer surface due to unrestricted conformational flexibility and many contacts with the membrane phosphate groups. In contrast, no Aβ1-42-M30 tetramer penetration was observed during the entire course of the simulation. In the case of the membrane-embedded Aβ1-42 tetramer, the integrity of the bottom bilayer leaflet was severely affected by the interactions between the negatively charged phosphate groups and the positively charged residues of the Aβ1-42 tetramer, resulting in a deep tetramer penetration into the bilayer hydrophobic region. These contacts were not observed in the case of the membrane-embedded Aβ1-42-M30 tetramer. It was noted that M30 molecules bind to Aβ1-42 tetramer through hydrogen bonds, resulting in a conformational stable Aβ1-42-M30 complex. The associated complex has reduced conformational changes and an enhanced rigidity that prevents the tetramer dissociation by interfering with the tetramer-membrane contacts. Our findings suggest that the M30 molecules could bind to Aβ1-42 tetramer resulting in a rigid structure, and that such complexes do not significantly perturb the membrane bilayer organization. These observations support the in vitro and in vivo experimental evidence that the M30 molecules prevent synaptotocity, improving AD-affected mice memory.

Molecular Mechanisms of Methamphetamine-Induced Addiction via TAAR1 Activation

Trace amine-associated receptor 1 (TAAR1), a member of the trace amine receptor family, recognizes various trace amines in the brain, including endogenous β-phenylethylamine (PEA) and methamphetamine (METH). TAAR1 is a novel target for several neurological disorders, including schizophrenia, depression, and substance abuse. Herein, we report the structure of the human TAAR1-Gs protein complex bound to METH. Using functional studies, we reveal the molecular basis of METH recognition by TAAR1, and potential mechanisms underlying the selectivity of TAAR1 for different ligands. Molecular dynamics simulations further elucidated possible mechanisms for the binding of chiral amphetamine (AMPH)-like psychoactive drugs to TAAR1. Additionally, we discovered a hydrophobic core on the transmembrane helices (TM), TM5 and TM6, explaining the unique mechanism of TAAR1 activation. These findings reveal the ligand recognition pattern and activation mechanism of TAAR1, which has important implications for the development of next-generation treatments for substance abuse and various neurological disorders.

Virtual screening, molecular dynamics simulations, and in vitro validation of EGFR inhibitors as breast cancer therapeutics

A high abundance of Epidermal Growth Factor Receptor (EGFR) in malignant cells makes them a prospective therapeutic target for basal breast tumors. Although EGFR inhibitors are in development as anticancer therapeutics, there exists limitations due to the dose-limiting cytotoxicity that limits their clinical utilization, thereby necessitating the advancement of effective inhibitors. In the present study, we have developed common pharmacophore hypotheses using 30 known EGFR inhibitors. The best pharmacophore hypothesis DHRRR_1 was utilized for virtual screening (VS) of the Phase database containing 4.3 × 106 fully prepared compounds. The top 1000 hits were further subjected to ADME filtration followed by structure-based VS and Molecular Dynamics (MD) simulation investigations. Based on pharmacophore hypothesis matching, XP glide score, interactions between ligands and active site residues, ADME properties, and MD simulations, the five best hits (SN-01 through SN-05) were preferred for in-vitro cytotoxicity studies. All the molecules except SN-02 exhibited cytotoxicity in Triple Negative Breast Cancer (TNBC) cells. These potential EGFR inhibitors effectively downregulated the EGF-induced proliferation, migration, in-vitro tumorigenic capability, and EGFR activation (pEGFR) in the TNBCs. Additionally, in combination with doxorubicin, the identified EGFR inhibitors significantly decreased the EGF-induced proliferation. SN-04, and SN-05 in the presence of a lower concentration of doxorubicin markedly increased the apoptotic markers expression in the TNBCs, an effect which was comparable to a higher concentration of doxorubicin treatment, alone. These observations suggest that both SN-04 and/or SN-05 can improve the efficacy of chemotherapeutic drug, doxorubicin at a lower concentration to avert the higher dose of chemotherapeutic-induced side effects during breast cancer treatment.

4D-QSAR, ADMET properties, and molecular dynamics simulations for designing N-substituted urea/thioureas as human glutaminyl cyclase inhibitors

Human glutaminyl cyclase (hQC) inhibitors have great potential to be used as anti- Alzheimer's disease (AD) agents by reducing the toxic pyroform of β-amyloid in the brains of AD patients. The four-dimensional quantitative structure activity relationship (4D-QSAR) model of N-substituted urea/thioureas was established with satisfying predictive ability and statistical reliability (Q2 = 0.521, R2 = 0.933, R2prep = 0.619). By utilizing the developed 4D-QSAR model, a set of new N-substituted urea/thioureas was designed and evaluated for their Absorption Distribution Metabolism Excretion and Toxicity (ADMET) properties. The results of molecular dynamics (MD) simulations, Principal component analysis (PCA), free energy landscape (FEL), dynamic cross-correlation matrix (DCCM) and molecular mechanics generalized Born Poisson-Boltzmann surface area (MM-PBSA) free energy calculations, revealed that the designed compounds were remained stable in protein binding pocket and compounds b ∼ f (-35.1 to -44.55 kcal/mol) showed higher binding free energy than that of compound 14 (-33.51 kcal/mol). The findings of this work will be a theoretical foundation for further research and experimental validation of urea/thiourea derivatives as hQC inhibitors.

Exploring the aroma profile and biomedical applications of Scutellaria nuristanica Rech. F.: A new insight as a natural remedy

BACKGROUND

The Scutellaria genus has promising therapeutic capabilities as an aromatherapy. Based on that and local practices of S. nuristanica Rech. F. The essential oil was studied for the first time for its diverse biomedical applications.

PURPOSE

This study aimed to evaluate and validate their therapeutic capabilities by screening the essential oil ingredients and examining their antimicrobial, antioxidant, carbonic anhydrase, and antidiabetic using further In silico assessment and In vivo anti-inflammatory and analgesic capabilities to devise novel sources as natural remedies alternative to the synthetic drugs.

METHODS

Essential oil was obtained through hydrodistillation, and the constituents were profiled using GC-MS. The antimicrobial assessment was conducted using an agar well diffusion assay. Free radical scavenging capabilities were determined by employing DPPH and ABTS assay. The carbonic anhydrase-II was examined using colorimetric assay, while the antidiabetic significance was performed using α-Glucosidase assay. The anti-inflammatory significance was examined through carrageenan-induced paw edema, and the analgesic features of the essential oil were determined using an acetic acid-induced writhing assay.

RESULTS

Fifty constituents were detected in S. nuristanica essential oil (SNEO), contributing 95.93 % of the total EO, with the predominant constituents being 24-norursa-3,12-diene (10.12 %), 3-oxomanoyl oxide (9.94 %), methyl 7-abieten-18-oate (8.85 %). SNEO presented significance resistance against the Gram-positive bacterial strains (GPBSs), Bacillus atrophaeus and Bacillus subtilis, as compared to the Salmonella typhi and Klebsiella pneumoniae, Gram-negative bacterial strains (GNBSs) as well as two fungal strains Aspergillus parasiticus and Aspergillus niger associated with their respective standards. Considerable free radical scavenging capacity was observed in DPPH compared to the ABTS assay when correlated with ascorbic acid. In addition, when equated with their standards, SNEO offered considerable in vitro carbonic anhydrase II and antidiabetic capabilities. Additionally, the antidiabetic behavior of the 9 dominant compounds of SNEO was tested via In silico techniques, such as molecular docking, which assisted in the assessment of the significance of binding contacts of protein with each chemical compound and pharmacokinetic evaluations to examine the drug-like characteristics. Molecular dynamic simulations at 100 ns and binding free energy evaluations such as PBSA and GBSA models explain the molecular mechanics and stability of molecular complexes. It was also observed that SNEO depicted substantial anti-inflammatory and analgesic capabilities.

CONCLUSION

Hence, it was concluded that the SNEO comprises bioactive ingredients with biomedical significance, such as anti-microbial, antioxidant, CA-II, antidiabetic, anti-inflammatory, and analgesic agents. The computational validation also depicted that SNEO could be a potent source for the discovery of anti-diabetic drugs.

Edaravone N-benzyl pyridinium derivatives: BACE-1 inhibition, kinetics and in silico binding pose determination

BACE-1 plays a pivotal role in the production of β-amyloid (Aβ) peptides, implicated in Alzheimer's Disease (AD) pathology. We previously described edaravone N-benzyl pyridinium derivatives (EBPDs) that exhibited multifunctional activity against multiple AD targets. In this study we explored the EBPDs BACE-1 inhibitory activity to potentially enhance the compounds therapeutic profile. The EBPDs exhibited moderate BACE-1 inhibitory activity (IC50 = 44.10 µM - 123.70 µM) and obtained IC50 values between 2.0 and 5.8-fold greater than resveratrol, a known BACE-1 inhibitor (IC50 = 253.20 µM), in this assay. Compound 3 was the most potent inhibitor with an IC50 of 44.10 µM and a Ki of 19.96 µM and a mixed-type mode of inhibition that favored binding in a competitive manner. Molecular docking identified crucial interactions with BACE-1 active site residues, supported by 100 ns MD simulations. The study highlighted the EBPDs therapeutic potential as BACE-1 inhibitors and multifunctional anti-AD therapeutic agents.

Spermine and spermidine SI-PPCs: Molecular dynamics reveals enhanced biomolecular interactions

In this paper the effects on the interaction of highly positively charged substitution-inert platinum polynuclear complexes (SI-PPCs) with negatively charged DNA and heparin are examined and compared by theoretical chemistry methods. Electrostatic and hydrogen bonding interactions contribute to the overall effects on the biomolecule. Root Mean Square (RMS) deviation, Solvent Accessible Surface, RMS fluctuation, and interaction analysis all confirm similar effects on both biomolecules, dictated predominantly by the total positive charge and total number of hydrogen bonds formed. Especially, changes in structural parameters suggesting condensation and reduction of available surface area will reduce or prevent normal protein recognition and may thus potentially inhibit biological mechanisms related to apoptosis (DNA) or reduced vascularization viability (HEP). Thermodynamic analyses supported these findings with favourable interaction energies. The comparison of DNA and heparin confirms the general intersectionality between the two biomolecules and confirms the intrinsic dual-nature function of this chemotype. The distinction between the two-limiting mode of actions (HS or DNA-centred) could reflect an intriguing balance between extracellular (GAG) and intracellular (DNA) binding and affinities. The results underline the need to fully understand GAG-small molecule interactions and their contribution to drug pharmacology and related therapeutic modalities. This report contributes to that understanding.

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.

Characterization and protein engineering of a novel UDP-glycosyltransferase involved in pseudoginsenoside Rt5 biosynthesis from Panax japonicus

As one of rare high-value ocotillol (OCT)-type ginsenosides, pseudoginsenoside Rt5 has been identified with significant pharmacological activities. UDP-glycosyltransferases (UGTs) play pivotal roles in catalyzing the transfer of a glycosyl moiety from a donor to an acceptor. In this study, the novel UGT, PjUGT10, was screened from the transcriptome database of Panax japonicus and identified with the enzymatic activity of transferring a glucosyl group on OCT to produce Rt5. The catalytic efficiency of PjUGT10 was further enhanced by employing site-directed mutation. Notably, the variant M7 exhibited a remarkable 6.16 × 103-fold increase in kcat/Km towards 20S,24R-ocotillol and a significant 2.02 × 103-fold increase to UDP-glucose, respectively. Moreover, molecular dynamics simulations illustrated a reduced distance between 20S,24R-ocotillol and the catalytic residue His15 or UDP-glucose, favoring conformation interactions between the enzyme and substrates. Subsequently, Rt5 was synthesized in an engineered Escherichia coli strain M7 coupled with a UDP-glucose synthetic system. This study not only shed light on the protein engineering that can enhance the catalytic activity of PjUGT10, but also established a whole-cell approach for the production of Rt5.

Ascorbyl palmitate (ASC16) as a potential inhibitor of toxicity induced by Crotalus durissus terrificus venom

It is well known that C. d. terrificus venom causes pathophysiological effects such as neuropathies, coagulopathies, and even death. Previous studies have reported that ASC16 can interact with monomeric phospholipases A2 from the venom of various snake species (e.g., Vipera russelli and Echis carinatus). As a result, ASC16 has been proposed as an inhibitor of the toxic effects induced by the heterodimeric complex (crotoxin) and other components of the venom of C. d. terrificus. To investigate this further, in silico studies were designed using the crotoxin (CTX) protein complex as a model, and experimental assays were conducted to evaluate the inhibitory effect of ASC16 on CTX, as well as on other venom enzymes such as thrombin-like enzyme (TLE), phosphodiesterase (PDE) and l-aminoxidase (LAAO). For in vitro assays, specific substrates were used, and lethal activity was measured over 48 h using an in vivo murine experimental model (CF01). In silico studies have indicated that the hydrophilic portion of ASC16 adopts a stable conformation while interacting with the catalytic site of crotoxin. At the highest concentrations, ASC16 significantly inhibited the activities of PLA2 (40.89 ± 0.09 %), TLE (11.03 ± 0.69 %), PDE (51.33 ± 2.83 %), and LAAO (56.79 ± 2.91 %). Furthermore, ASC16 neutralized the 2 LD50 lethality of crotalic venom. These findings lay the groundwork for designing promising adjuvants that can facilitate the incorporation of a larger quantity of proteins in immunization schemes. Consequently, this approach aims to achieve higher antibody titers, reduce the number of required immunizations, and minimize local damage in the producer animal.

Exploring the potential of structure-based deep learning approaches for T cell receptor design

Deep learning methods, trained on the increasing set of available protein 3D structures and sequences, have substantially impacted the protein modeling and design field. These advancements have facilitated the creation of novel proteins, or the optimization of existing ones designed for specific functions, such as binding a target protein. Despite the demonstrated potential of such approaches in designing general protein binders, their application in designing immunotherapeutics remains relatively underexplored. A relevant application is the design of T cell receptors (TCRs). Given the crucial role of T cells in mediating immune responses, redirecting these cells to tumor or infected target cells through the engineering of TCRs has shown promising results in treating diseases, especially cancer. However, the computational design of TCR interactions presents challenges for current physics-based methods, particularly due to the unique natural characteristics of these interfaces, such as low affinity and cross-reactivity. For this reason, in this study, we explored the potential of two structure-based deep learning protein design methods, ProteinMPNN and ESM-IF1, in designing fixed-backbone TCRs for binding target antigenic peptides presented by the MHC through different design scenarios. To evaluate TCR designs, we employed a comprehensive set of sequence- and structure-based metrics, highlighting the benefits of these methods in comparison to classical physics-based design methods and identifying deficiencies for improvement.

Probing hot spots of protein-protein interactions mediated by the safety-belt region of REV7

REV7 is a HORMA (Hop1, Rev7, Mad2) family adaptor protein best known as an accessory subunit of the translesion synthesis (TLS) DNA polymerase ζ (Polζ). In this role, REV7 binds REV3, the catalytic subunit of Polζ, by locking REV7-binding motifs (RBMs) in REV3 underneath the REV7 safety-belt loop. The same mechanism is used by REV7 to interact with RBMs from other proteins in DNA damage response (DDR) and mitosis. Because of the importance of REV7 for TLS and other DDR pathways, targeting REV7:RBM protein-protein interactions (PPIs) with small molecules has emerged as a strategy to enhance cancer response to genotoxic chemotherapy. To identify druggable pockets at the REV7:RBM interface, we performed computational analyses of REV7 complexed with several RBM partners. The contributions of different interface regions to REV7:RBM stabilization were corroborated experimentally. These studies provide insights into key intermolecular interactions and establish targetable regions of REV7 for the design of REV7:RBM PPI inhibitors.

Targeting the phosphatidylglycerol lipid: An amphiphilic dendrimer as a promising antibacterial candidate

The rapid emergence and spread of multidrug-resistant bacterial pathogens require the development of antibacterial agents that are robustly effective while inducing no toxicity or resistance development. In this context, we designed and synthesized amphiphilic dendrimers as antibacterial candidates. We report the promising potent antibacterial activity shown by the amphiphilic dendrimer AD1b, composed of a long hydrophobic alkyl chain and a tertiary amine-terminated poly(amidoamine) dendron, against a panel of Gram-negative bacteria, including multidrug-resistant Escherichia coli and Acinetobacter baumannii. AD1b exhibited effective activity against drug-resistant bacterial infections in vivo. Mechanistic studies revealed that AD1b targeted the membrane phospholipids phosphatidylglycerol (PG) and cardiolipin (CL), leading to the disruption of the bacterial membrane and proton motive force, metabolic disturbance, leakage of cellular components, and, ultimately, cell death. Together, AD1b that specifically interacts with PG/CL in bacterial membranes supports the use of small amphiphilic dendrimers as a promising strategy to target drug-resistant bacterial pathogens and addresses the global antibiotic crisis.

The potentiality of isoflavones from Derris robusta (DC.) Benth. against α-glucosidase

The four recently described isoflavones, derrisrobustones A-D, and eight known isoflavones extracted from Derris robusta (DC.) Benth. (Leguminosae) were identified as potential isoflavones for α-glucosidase inhibitory activity. However, the inhibitory ability of each isoflavone was quite different and the structural and dynamical properties of the isoflavones in the binding with α-glucosidase have not been studied. In this study, the molecular dynamics (MD) simulation and the molecular mechanics generalized Born surface area (MM/GBSA) methods were applied to gain insight into isoflavones bound with the α-glucosidase active site. The results found that the isoflavones with a hydroxy substituent could be stabilized in the α-glucosidase active site with low values of the binding free energy, especially derrisrobustone D and derrubone. The isoflavones, except for derrubone, were bound with α-glucosidase by means of electrostatic force effectively.

Development of a machine learning-based target-specific scoring function for structure-based binding affinity prediction for human dihydroorotate dehydrogenase inhibitors

Human dihydroorotate dehydrogenase (hDHODH) is a flavin mononucleotide-dependent enzyme that can limit de novo pyrimidine synthesis, making it a therapeutic target for diseases such as autoimmune disorders and cancer. In this study, using the docking structures of complexes generated by AutoDock Vina, we integrate interaction features and ligand features, and employ support vector regression to develop a target-specific scoring function for hDHODH (TSSF-hDHODH). The Pearson correlation coefficient values of TSSF-hDHODH in the cross-validation and external validation are 0.86 and 0.74, respectively, both of which are far superior to those of classic scoring function AutoDock Vina and random forest (RF) based generic scoring function RF-Score. TSSF-hDHODH is further used for the virtual screening of potential inhibitors in the FDA-Approved & Pharmacopeia Drug Library. In conjunction with the results from molecular dynamics simulations, crizotinib is identified as a candidate for subsequent structural optimization. This study can be useful for the discovery of hDHODH inhibitors and the development of scoring functions for additional targets.

Insight from atomistic molecular dynamics simulations into the supramolecular assembly of the aldo-keto reductase from Trypanosoma cruzi

CONTEXT

Currently, Chagas disease represents an important public health problem affecting more than 8 million people worldwide. The vector of this disease is the Trypanosoma cruzi (Tc) parasite. Our research specifically focuses on the structure and aggregation states of the enzyme aldo-keto reductase of Tc (TcAKR) reported in this parasite. TcAKR belongs to the aldo-keto reductase (AKR) superfamily, enzymes that catalyze redox reactions involved in crucial biological processes. While most AKRs are found in monomeric forms, some have been reported to form dimeric and tetrameric structures. This is the case for some TcAKR. To better understand how TcAKR multimers form and remain stable, we conducted a comprehensive computational analysis using molecular dynamics (MD) simulations. Our approach to elucidating the aggregation states of TcAKR involved two strategies. Initially, we explored the dynamic behaviour of pre-assembled TcAKR dimers. Subsequently, we examined the self-aggregation of eight monomers. This investigation led to the identification of crucial residues that contribute to the stabilization of protein-protein interactions. It was also found that TcAKRs can form stable supramolecular assemblies, with each monomer typically surrounded by three first neighbours. These findings align with experimental reports of tetrameric or more complex supramolecular structures. Our computational studies could guide further experimental investigations aiming at drug development and assist in designing strategies to modulate aggregation.

METHOD

Atomistic molecular dynamics simulations were carried out. The TcAKR 3D model structure was obtained by homology modelling using the Swiss Model for the TcAKR sequence (GenBank accession no. EU558869). Further, we checked the model with Alphafold2 and found a high degree of similarity between models. Several tools were used to build the dimers including CLUSPRO, GRAMM-Docking, Hdock, and Py-dock. Protein superstructures were built using the PACKMOL package. CHARMM-GUI was used to set up the simulation systems. GROMACS version 2020.5 was used to perform the simulations with the CHARMM36 force field for the protein and ions and the TIP3P model for water. Further analyses were performed using VMD, GROMACS, AMBER tools, MDLovoFit, bio3d, and in-house programs.

The RNA-binding protein EIF4A3 promotes axon development by direct control of the cytoskeleton

The exon junction complex (EJC), nucleated by EIF4A3, is indispensable for mRNA fate and function throughout eukaryotes. We discover that EIF4A3 directly controls microtubules, independent of RNA, which is critical for neural wiring. While neuronal survival in the developing mouse cerebral cortex depends upon an intact EJC, axonal tract development requires only Eif4a3. Using human cortical organoids, we show that EIF4A3 disease mutations also impair neuronal growth, highlighting conserved functions relevant for neurodevelopmental pathology. Live imaging of growing neurons shows that EIF4A3 is essential for microtubule dynamics. Employing biochemistry and competition experiments, we demonstrate that EIF4A3 directly binds to microtubules, mutually exclusive of the EJC. Finally, in vitro reconstitution assays and rescue experiments demonstrate that EIF4A3 is sufficient to promote microtubule polymerization and that EIF4A3-microtubule association is a major contributor to axon growth. This reveals a fundamental mechanism by which neurons re-utilize core gene expression machinery to directly control the cytoskeleton.

Network Pharmacology, Molecular Docking, and Molecular Dynamics Study to Explore the Effect of Resveratrol on Type 2 Diabetes

This network pharmacology study represents a significant step in understanding the potential of Resveratrol as an antidiabetic agent and its molecular targets. Targets for Type 2 diabetes were obtained from the MalaCards and DisGeNET databases, while targets for Resveratrol were sourced from the STP and CTD databases. Subsequently, we performed matching to identify common disease-compound targets. The identified genes were analyzed using the ShinGO-0.76.3 database for functional enrichment analysis and KEGG pathway mapping. A protein-protein interaction network was then constructed using Cytoscape software, and hub genes were identified. These hub genes were subjected to molecular docking and dynamic simulations using AutoDock Vina and Gromacs software. According to functional enrichment and KEGG pathway analysis, Resveratrol influences insulin receptors, endoplasmic reticulum functions, and oxidoreductase activity and is involved in the estrogen and HIF-1 pathways. Ten hub genes were identified, including ESR1, PTGS2, SRC, NOS3, MMP9, IGF1R, CYP19A1, MTOR, MMP2, and PIK3CA. The proteins associated with these genes exhibited high interaction with Resveratrol in the molecular docking analysis, and molecular dynamics showed a stable interaction of Resveratrol with ESR1, MMP9, PIK3CA, and PTGS2. In conclusion, our work enhances the understanding of the antidiabetic activity of Resveratrol, which future studies should experimentally corroborate.

Apoptotic Potential of Iloneoside from Gongronema latifolium Benth against Prostate Cancer Cells Using In Vitro and In Silico Approach

Prostate cancer is a major cause of cancer-related mortality in men worldwide. The anti-proliferative activity of Gongronema latifolium leaf extracts on some cancer cells has been reported. Herein, we investigated the growth inhibitory effect of the Gongronema latilolium leaf methanol extract and isolated pregnane (iloneoside) against prostate cancer cell lines using the MTT cell proliferation assay, apoptosis quantification, cell cycle analysis using flow cytometry and computational analysis molecular docking, molecular dynamics simulation (MDs), binding free energy computation and cluster analysis. In addition, UPLC-ESI-TOFMS chemical fingerprinting of previously isolated compounds was performed. The extract inhibited the growth of the cell lines with an IC50 of 49.3 µg/ml and 28.4 µg/ml for 24 h and 48 h, respectively, for PC3; and 43.7 µg/ml and 22.3 µg/ml for 24 h and 48 h, respectively, for DU145. Iloneoside demonstrated low inhibitory activities against PC3 and DU145 (IC50 > 80 μM). Apoptotic quantification and cell cycle analysis further showed that iloneoside induced apoptosis in a few cells at a dose of 200 uM. The ensemble-based molecular docking of the iloneoside to BCL-XL and BCL-2 proteins, and docking to MCL-1, BCL-A1 and BFL-1 proteins, respectively, presented binding energies of -7.22 ± 0.5, -8.12 ± 0.55, -7.1, -7.2 and -6.3 kcal/mol, while the MM/PBSA binding free energy was -25.72 ± 7.22 and -27.76 ± 11.32 kcal/mol for BCL-XL and BCL-2 proteins. Furthermore, iloneoside was stable during the 100 ns MDs analysis, while the clustering of the MDs trajectories showed that the interactions were strongly preserved. Iloneoside, in part, or in synergy with other constituents, may be responsible for the antiproliferative activities of the leaf, subject to further investigation.

Designing of a chimeric multiepitope vaccine against bancroftian lymphatic filariasis through immunoinformatics approaches

The filarial worms of Wuchereria bancrofti are the primary cause of lymphatic filariasis (LF), a mosquito-borne disease among the neglected tropical parasitic diseases. Considering the global endemic consequences of the disease, there is a need to develop a successful vaccine candidate against LF. Using advanced immunoinformatics approaches, we designed two multiepitope vaccines targeting W. bancrofti's glutathione S-transferase and thioredoxin. Therefore, we predicted several MHC-1, MHC-2, and B-cell epitopes from these proteins and mapped two vaccine candidates (V1 and V2). The vaccines were subsequently employed for physicochemical analysis, structural prediction and validation, docking and normal mode analysis, codon optimization, and immune simulation. The selected MHC-1, MHC-2, and B-cell epitopes were antigenic without allergenicity or toxicity. The designed vaccines were expected to be soluble, stable proteins under physiological conditions. Compared to V2, V1's secondary and tertiary structures were simultaneously favorable, with Ramachandran plot analysis revealing 95.6% residues in favored areas. Subsequently, the molecular docking analysis indicated that the V1 had a high binding affinity for the TLR-2, TLR-4 and TLR-5, as suggested by the docking scores of -1248.7, -1038.5 and -1562.8, respectively. The NMA of these complexes further indicated their structural flexibility. Molecular dynamics simulations of V1-TLR complexes revealed V1-TLR-4 as the most stable, with the lowest free energy and minimal fluctuations, indicating the strongest binding affinity. The results of the codon optimization showed high levels of expression, with a favorable CAI score (<1.0). A three-dose vaccination analysis showed significant and persistent immunological responses, including adaptive and innate immune responses. The findings emphasize the potential of the V1 against W. bancrofti, but further validation is required through in vitro, in vivo, and clinical trials.

Cheminformatics-enhanced discovery of therapeutic agents targeting isocitrate lyase in Mycobacterium tuberculosis infections

Tuberculosis (TB) is a global health challenge; therefore, there is an urgent requirement to develop a novel and more effective anti-TB therapeutic. This study targeted the isocitrate lyase (ICL) protein due to its pivotal role in the pathogenicity of Mycobacterium tuberculosis (Mtb). Virtual screening of 8752 bioactive compounds used an ML-based QSAR model and molecular docking. ADMET testing was performed on the top three hits to identify the compound most closely mimicking a drug molecule. The top hits, 648 and 2785758, showed high binding affinity towards ICL with -7.3 and -7 kcal/mol, comparable to the control. These molecules also showed strong binding with the residue Asp108, which plays a vital role in ICL activity. Molecular dynamics simulations showed stability for 648 and 2785758, comparable to the control compound used in this study. It was found that 648 bound to the protein maintained the RMSD constant and consistent at 0.3 nm for a complete 100 ns simulation. 2785758 showed a comparable RMSD trend to the control. Both 648 and 2785758 showed high RMSF for critical residue Asp108. Further, PCA and FEL confirmed the formation of a stable complex. MM/GBSA estimations of binding free energy indicated that compounds 648 had an elevated level of stability (ΔGTOTAL = -28.11 kcal/mol) and 2785758 (ΔGTOTAL = -21.05 kcal/mol). This study suggests that compounds 648 and 2785758 can potentially affect the activity of ICL, leading to its inactivation and ultimately preventing the progression of tuberculosis.Communicated by Ramaswamy H. Sarma.

The potential of Mitragyna speciosa leaves as a natural source of antioxidants for disease prevention

Mitragyna speciosa is famous for its addictive effect. On the other hand, this plant has good potential as an antioxidant agent, and so far, it was not explicitly explained what the most contributing compound in the leaves to that activity is. This study has been conducted using several computational methods to determine which compounds are the most active in interacting with cytochrome P450, myeloperoxidase, and NADPH oxidase proteins. First, virtual screening was carried out based on molecular docking, followed by profiling the properties of adsorption, distribution, metabolism, excretion, and toxicity (ADMET); the second one is the molecular dynamics (MD) simulations for 100 ns. The virtual screening results showed that three compounds acted as inhibitors for each protein: (-)-epicatechin, sitogluside, and corynoxeine. The ADMET profiles of the three compounds exhibit good drug ability and toxicity. The trajectories study from MD simulations predicts that the complexes of these three compounds with their respective target proteins are stable. Furthermore, these compounds identified in this computational study can be a potential guide for future experiments aimed at assessing the antioxidant properties through in vitro testing.

Stabilization of dimeric PYR/PYL/RCAR family members relieves abscisic acid-induced inhibition of seed germination

Abscisic acid (ABA) is the primary preventing factor of seed germination, which is crucial to plant survival and propagation. ABA-induced seed germination inhibition is mainly mediated by the dimeric PYR/PYL/RCAR (PYLs) family members. However, little is known about the relevance between dimeric stability of PYLs and seed germination. Here, we reveal that stabilization of PYL dimer can relieve ABA-induced inhibition of seed germination using chemical genetic approaches. Di-nitrobensulfamide (DBSA), a computationally designed chemical probe, yields around ten-fold improvement in receptor affinity relative to ABA. DBSA reverses ABA-induced inhibition of seed germination mainly through dimeric receptors and recovers the expression of ABA-responsive genes. DBSA maintains PYR1 in dimeric state during protein oligomeric state experiment. X-ray crystallography shows that DBSA targets a pocket in PYL dimer interface and may stabilize PYL dimer by forming hydrogen networks. Our results illustrate the potential of PYL dimer stabilization in preventing ABA-induced seed germination inhibition.

AlphaFold2 Modeling and Molecular Dynamics Simulations of the Conformational Ensembles for the SARS-CoV-2 Spike Omicron JN.1, KP.2 and KP.3 Variants: Mutational Profiling of Binding Energetics Reveals Epistatic Drivers of the ACE2 Affinity and Escape Hotspots of Antibody Resistance

The most recent wave of SARS-CoV-2 Omicron variants descending from BA.2 and BA.2.86 exhibited improved viral growth and fitness due to convergent evolution of functional hotspots. These hotspots operate in tandem to optimize both receptor binding for effective infection and immune evasion efficiency, thereby maintaining overall viral fitness. The lack of molecular details on structure, dynamics and binding energetics of the latest FLiRT and FLuQE variants with the ACE2 receptor and antibodies provides a considerable challenge that is explored in this study. We combined AlphaFold2-based atomistic predictions of structures and conformational ensembles of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the most dominant Omicron variants JN.1, KP.1, KP.2 and KP.3 to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and computations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that protect and restore ACE2-binding affinity while conferring beneficial immune escape. To examine immune escape mechanisms, we performed structure-based mutational profiling of the spike protein binding with several classes of antibodies that displayed impaired neutralization against BA.2.86, JN.1, KP.2 and KP.3. The results confirmed the experimental data that JN.1, KP.2 and KP.3 harboring the L455S and F456L mutations can significantly impair the neutralizing activity of class 1 monoclonal antibodies, while the epistatic effects mediated by F456L can facilitate the subsequent convergence of Q493E changes to rescue ACE2 binding. Structural and energetic analysis provided a rationale to the experimental results showing that BD55-5840 and BD55-5514 antibodies that bind to different binding epitopes can retain neutralizing efficacy against all examined variants BA.2.86, JN.1, KP.2 and KP.3. The results support the notion that evolution of Omicron variants may favor emergence of lineages with beneficial combinations of mutations involving mediators of epistatic couplings that control balance of high ACE2 affinity and immune evasion.

Marine Compound-Carpatamide D as a Potential Inhibitor Against TOP2A and Its Mutant D1021Y in Colorectal Cancer: Insights from DFT, MEP and Molecular Dynamics Simulation

Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, hence there is an urgent need for new and effective therapeutic options. DNA topoisomerase 2A (TOP2A) plays a crucial role in the cell cycle and is involved in CRC progression, making it essential to identify structural and functional relevant alterations. Among the 24 mutations, our findings indicated that mutation D1021Y has the most deleterious effect on the TOP2A protein. Based on virtual screening of 31,561 compounds, we identified three lead candidates: 17683 (nigrospoxydon C), 28461 (carpatamide D), and 28853 (6'-O-acetyl-isohomaarbutin), which showed promising inhibitory effect against TOP2A and its mutant form. These compounds were assessed for their stability using density functional theory (DFT) analysis, where carpatamide D possessed the least energy gap of 4.398 eV showing its high reactivity among all. Further, molecular docking also shows the carpatamide D as the top candidate, which exhibited favourable docking energy against the TOP2A wild type (- 7.47 kcal/mol) and with D1021Y mutant (- 7.62 kcal/mol) as compared to reference compound PK1, which showed - 6.11 kcal/mol TOP2A wild type and - 6.24 kcal/mol against mutant type. The molecular dynamics simulation was performed to analyse the dynamics and stability of complex, which revealed TOP2A_28641 and D1021Y_28641 complexes to be stable with least root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF). Molecular mechanics/Poisson-Boltzmann surface area calculations indicated that TOP2A_28641 and D1021Y_28641 complexes exhibited the lowest binding energy of - 23.55 kcal/mol and - 25.03 kcal/mol, respectively. Our findings suggest carpatamide D as a promising lead compound for the TOP2A_D1021Y targeted cancer therapies, which needs further experimental validation.

Target-Specific De Novo Peptide Binder Design with DiffPepBuilder

Despite the exciting progress in target-specific de novo protein binder design, peptide binder design remains challenging due to the flexibility of peptide structures and the scarcity of protein-peptide complex structure data. In this study, we curated a large synthetic data set, referred to as PepPC-F, from the abundant protein-protein interface data and developed DiffPepBuilder, a de novo target-specific peptide binder generation method that utilizes an SE(3)-equivariant diffusion model trained on PepPC-F to codesign peptide sequences and structures. DiffPepBuilder also introduces disulfide bonds to stabilize the generated peptide structures. We tested DiffPepBuilder on 30 experimentally verified strong peptide binders with available protein-peptide complex structures. DiffPepBuilder was able to effectively recall the native structures and sequences of the peptide ligands and to generate novel peptide binders with improved binding free energy. We subsequently conducted de novo generation case studies on three targets. In both the regeneration test and case studies, DiffPepBuilder outperformed AfDesign and RFdiffusion coupled with ProteinMPNN, in terms of sequence and structure recall, interface quality, and structural diversity. Molecular dynamics simulations confirmed that the introduction of disulfide bonds enhanced the structural rigidity and binding performance of the generated peptides. As a general peptide binder de novo design tool, DiffPepBuilder can be used to design peptide binders for given protein targets with three-dimensional and binding site information.

Rational Design of a Novel 6H-Benzo[c]chromen Series as Selective PI3Kα Inhibitors

The phosphoinositide 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) signaling pathway is a frequently dysregulated pathway in human cancer, and PI3Kα is one of the most frequently mutated kinases in human cancer. A selective PI3Kα inhibitor may provide the opportunity to spare patients the side effects associated with broader inhibition of the class I PI3K family. Here, we describe our efforts to discover a novel series of selective PI3Kα inhibitors using structure-based drug design and molecular docking to inform the design of 6H-benzo[c]chromen inhibitors. XJTU-L453 (21) was identified with PI3Kα inhibitory potency and unique selectivity over other PI3K isoforms and all other kinases tested. Further evaluation of pharmacokinetic properties and in vivo efficacy led to the identification of the preclinical potential of XJTU-L453 (21).

Examining Hemin and its Derivatives: Induction of Heme-Oxygenase-1 Activity and Oxidative Stress in Breast Cancer Cells through Collaborative Experimental Analysis and Molecular Dynamics Simulations

Hemin triggers intracellular reactive oxygen species (ROS) accumulation and enhances heme oxygenase-1 (HOX-1) activity, indicating its potential as an anticancer agent, though precise control of its intracellular levels is crucial. The study explores the impact of hemin and its derivatives, hemin-tyrosine, and hemin-styrene (H-Styr) conjugates on migration, HOX-1 expression, specific apoptosis markers, mitochondrial functions, and ROS generation in breast cancer cells. Molecular docking and dynamics simulations were used to understand the interactions among HOX-1, heme, and the compounds. Hemin outperforms its derivatives in inducing HOX-1 expression, exhibiting pro-oxidative effects and reducing cell migration. Molecular simulations show that heme binds favorably to HOX-1, followed by the other compounds, primarily through van der Waals and electrostatic forces. However, only van der Waals forces determine the H-Styr complexation. These interactions, influenced by metalloporphyrin characteristics, provide insights into HOX-1 regulation and ROS generation, potentially guiding the development of breast cancer therapies targeting oxidative stress.

PNBACE: an ensemble algorithm to predict the effects of mutations on protein-nucleic acid binding affinity

BACKGROUND

Mutations occurring in nucleic acids or proteins may affect the binding affinities of protein-nucleic acid interactions. Although many efforts have been devoted to the impact of protein mutations, few computational studies have addressed the effect of nucleic acid mutations and explored whether the identical methodology could be applied to the prediction of binding affinity changes caused by these two mutation types.

RESULTS

Here, we developed a generalized algorithm named PNBACE for both DNA and protein mutations. We first demonstrated that DNA mutations could induce varying degrees of changes in binding affinity from multiple perspectives. We then designed a group of energy-based topological features based on different energy networks, which were combined with our previous partition-based energy features to construct individual prediction models through feature selections. Furthermore, we created an ensemble model by integrating the outputs of individual models using a differential evolution algorithm. In addition to predicting the impact of single-point mutations, PNBACE could predict the influence of multiple-point mutations and identify mutations significantly reducing binding affinities. Extensive comparisons indicated that PNBACE largely performed better than existing methods on both regression and classification tasks.

CONCLUSIONS

PNBACE is an effective method for estimating the binding affinity changes of protein-nucleic acid complexes induced by DNA or protein mutations, therefore improving our understanding of the interactions between proteins and DNA/RNA.

Understanding the stability and dynamics of influenza a H5N1 polymerase PB2 CAP-Binding domain in complex with natural compounds for antiviral drug discovery

Influenza A virus, particularly the H5N1 strain, poses a significant threat to public health due to its ability to cause severe respiratory illness and its high mortality rate. Traditional antiviral drugs targeting influenza A virus have faced challenges such as drug resistance and limited efficacy. Therefore, new antiviral compounds are needed to be discovered and developed. This study concentrated on examining the stability and behavior of the H5N1 polymerase PB2 CAP-binding domain when interacting with natural compounds, aiming to identify potential candidates for antiviral drug discovery. Through the virtual screening process, four lead compounds, ZINC000096095464, ZINC000044404209, ZINC000001562130, and ZINC000059779788, were selected, and these compounds showed binding energies -9.6, -9.4, -9.3, and -9.2 kcal/mol, respectively. When complexed with PB2, the ligand showed acceptable binding stability due to significant bond formation. However, during the 200ns MD simulation analysis, three (ZINC000096095464, ZINC000044404209, and ZINC000059779788) showed significant stability, which was proven by the trajectory analysis. The Rg-RMSD-based FEL plot showed significant structural stability due to stable conformers. The free-binding energy calculation also validates the stability of these complexes. This study offers valuable insights into the stability and dynamics of the H5N1 polymerase PB2 CAP-binding domain in complexes with natural compounds. These findings highlight the potential of these natural compounds as antiviral agents against the H5N1 influenza virus. Furthermore, this research contributes to the broader field of influenza virus treatment by demonstrating the effectiveness of computational methods in predicting and evaluating the stability and dynamics of potential drug candidates.

Pharmacophore-Based Study: An In Silico Perspective for the Identification of Potential New Delhi Metallo-β-lactamase-1 (NDM-1) Inhibitors

In the ongoing battle against antibiotic-resistant bacteria, New Delhi metallo-β-lactamase-1 (NDM-1) has emerged as a significant therapeutic challenge due to its ability to confer resistance to a broad range of β-lactam antibiotics. This study presents a pharmacophore-based virtual screening, docking, and molecular dynamics simulation approach for the identification of potential inhibitors targeting NDM-1, a critical enzyme associated with antibiotic resistance. Through the generation of a pharmacophore model and subsequent virtual screening of compound libraries, candidate molecules (ZINC29142850 (Z1), ZINC78607001 (Z2), and ZINC94303138 (Z3)) were prioritized based on their similarity to known NDM-1 binder (hydrolyzed oxacillin (0WO)). Molecular docking studies further elucidated the binding modes and affinities of the selected compounds towards the active site of NDM-1. These compounds demonstrated superior binding affinities to the enzyme compared to a control compound (-7.30 kcal/mol), with binding scores of -7.13, -7.92, and -8.10 kcal/mol, respectively. Binding interactions within NDM-1's active site showed significant interactions with critical residues such as His250, Asn220, and Trp93 for these compounds. Subsequent molecular dynamics simulations were conducted to assess the stability of the ligand-enzyme complexes, showing low root mean square deviation (RMSD) values between 0.5 and 0.7 nm for Z1, Z2, which indicate high stability. Z2's compactness in principal component analysis (PCA) suggests that it can stabilize particular protein conformations more efficiently. Z2 displays a very cohesive landscape with a notable deep basin, suggesting a very persistent conformational state induced by the ligand, indicating robust binding and perhaps efficient inhibition. Z2 demonstrates the highest binding affinity among the examined compounds with a binding free energy of -25.68 kcal/mol, suggesting that it could offer effective inhibition of NDM-1. This study highlights the efficacy of computational tools in identifying novel antimicrobial agents against resistant bacteria, accelerating drug discovery processes.

GraphEGFR: Multi-task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcity

The proteins within the human epidermal growth factor receptor (EGFR) family, members of the tyrosine kinase receptor family, play a pivotal role in the molecular mechanisms driving the development of various tumors. Tyrosine kinase inhibitors, key compounds in targeted therapy, encounter challenges in cancer treatment due to emerging drug resistance mutations. Consequently, machine learning has undergone significant evolution to address the challenges of cancer drug discovery related to EGFR family proteins. However, the application of deep learning in this area is hindered by inherent difficulties associated with small-scale data, particularly the risk of overfitting. Moreover, the design of a model architecture that facilitates learning through multi-task and transfer learning, coupled with appropriate molecular representation, poses substantial challenges. In this study, we introduce GraphEGFR, a deep learning regression model designed to enhance molecular representation and model architecture for predicting the bioactivity of inhibitors against both wild-type and mutant EGFR family proteins. GraphEGFR integrates a graph attention mechanism for molecular graphs with deep and convolutional neural networks for molecular fingerprints. We observed that GraphEGFR models employing multi-task and transfer learning strategies generally achieve predictive performance comparable to existing competitive methods. The integration of molecular graphs and fingerprints adeptly captures relationships between atoms and enables both global and local pattern recognition. We further validated potential multi-targeted inhibitors for wild-type and mutant HER1 kinases, exploring key amino acid residues through molecular dynamics simulations to understand molecular interactions. This predictive model offers a robust strategy that could significantly contribute to overcoming the challenges of developing deep learning models for drug discovery with limited data and exploring new frontiers in multi-targeted kinase drug discovery for EGFR family proteins.

Toward Unveiling Putative Binding Sites of Interleukin-33: Insights from Mixed-Solvent Molecular Dynamics Simulations of the Interleukin-1 Family

The interleukin (IL)-1 family is a major proinflammatory cytokine family, ranging from the well-studied IL-1s to the most recently discovered IL-33. As a new focus, IL-33 has attracted extensive research for its crucial immunoregulatory roles, leading to the development of notable monoclonal antibodies as clinical candidates. Efforts to develop small molecules disrupting IL-33/ST2 interaction remain highly desired but encounter challenges due to the shallow and featureless interfaces. The information from relative cytokines has shown that traditional binding site identification methods still struggle in mapping cryptic sites, necessitating dynamic approaches to uncover druggable pockets on IL-33. Here, we employed mixed-solvent molecular dynamics (MixMD) simulations with diverse-property probes to map the hotspots of IL-33 and identify potential binding sites. The protocol was first validated using the known binding sites of two IL-1 family members and then applied to the structure of IL-33. Our simulations revealed several binding sites and proposed side-chain rearrangements essential for the binding of a known inhibitor, aligning well with experimental NMR findings. Further microsecond-time scale simulations of this IL-33-protein complex unveiled distinct binding modes with varying occurrences. These results could facilitate future efforts in developing ligands to target challenging flexible pockets of IL-33 and IL-1 family cytokines in general.

Design, synthesis, pharmacological evaluation, and computational study of benzo[d] isothiazol-based small molecule inhibitors targeting PD-1/PD-l1 interaction

Blockade of the programmed cell death-1 (PD-1)/programmed cell death ligand 1 (PD-L1) pathway is an attractive strategy for immunotherapy, but the clinical application of small molecule PD-1/PD-L1 inhibitors remains unclear. In this work, based on BMS-202 and our previous work YLW-106, a series of compounds with benzo[d]isothiazol structure as scaffold were designed and synthesized. Their inhibitory activity against PD-1/PD-L1 interaction was evaluated by a homogeneous time-resolved fluorescence (HTRF) assay. Among them, LLW-018 (27c) exhibited the most potent inhibitory activity with an IC50 value of 2.61 nM. The cellular level assays demonstrated that LLW-018 exhibited low cytotoxicity against Jurkat T and MDA-MB-231. Further cell-based PD-1/PD-L1 blockade bioassays based on PD-1 NFAT-Luc Jurkat cells and PD-L1 TCR Activator CHO cells indicated that LLW-018 could interrupt PD-1/PD-L1 interaction with an IC50 value of 0.88 μM. Multi-computational methods, including molecular docking, molecular dynamics, MM/GBSA, MM/PBSA, Metadynamics, and QM/MM MD were utilized on PD-L1 dimer complexes, which revealed the binding modes and dissociation process of LLW-018 and C2-symmetric small molecule inhibitor LCH1307. These results suggested that LLW-018 exhibited promising potency as a PD-1/PD-L1 inhibitor for further investigation.

Structure-Aided Computational Design of Triazole-Based Targeted Covalent Inhibitors of Cruzipain

Cruzipain (CZP), the major cysteine protease present in T. cruzi, the ethiological agent of Chagas disease, has attracted particular attention as a therapeutic target for the development of targeted covalent inhibitors (TCI). The vast chemical space associated with the enormous molecular diversity feasible to explore by means of modern synthetic approaches allows the design of CZP inhibitors capable of exhibiting not only an efficient enzyme inhibition but also an adequate translation to anti-T. cruzi activity. In this work, a computer-aided design strategy was developed to combinatorially construct and screen large libraries of 1,4-disubstituted 1,2,3-triazole analogues, further identifying a selected set of candidates for advancement towards synthetic and biological activity evaluation stages. In this way, a virtual molecular library comprising more than 75 thousand diverse and synthetically feasible analogues was studied by means of molecular docking and molecular dynamic simulations in the search of potential TCI of CZP, guiding the synthetic efforts towards a subset of 48 candidates. These were synthesized by applying a Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) centered synthetic scheme, resulting in moderate to good yields and leading to the identification of 12 hits selectively inhibiting CZP activity with IC50 in the low micromolar range. Furthermore, four triazole derivatives showed good anti-T. cruzi inhibition when studied at 50 μM; and Ald-6 excelled for its high antitrypanocidal activity and low cytotoxicity, exhibiting complete in vitro biological activity translation from CZP to T. cruzi. Overall, not only Ald-6 merits further advancement to preclinical in vivo studies, but these findings also shed light on a valuable chemical space where molecular diversity might be explored in the search for efficient triazole-based antichagasic agents.

Modulating the Self-Assembly of a Camptothecin Prodrug with Paclitaxel for Anticancer Combination Therapy: A Molecular Dynamics Approach

Camptothecin (CPT) and paclitaxel (PTX), derived from natural products, are recognized for their significant efficacy in clinical cancer treatments. Despite its therapeutic advantages, CPT is challenged by issues of toxicity and solubility, necessitating its use in conjugation with other compounds for enhanced compatibility. This study delves into the coassembly mechanism of Evans blue-conjugated camptothecin (EB-CPT) with PTX, aiming to elucidate their synergistic potential in combination therapy applications, employing all-atom molecular dynamics simulations. The EB-CPT prodrug is reported to form a self-aggregated cluster. Our findings suggest that increasing the PTX concentration induces a dispersion of EB-CPT clusters, thereby disrupting their inherent self-assembly. This disruption is explained to be facilitated by the coassembly of EB-CPT and PTX. With increasing concentration of PTX, a lengthening of the coassembled structures is observed, supporting the experimental findings of tube-like coassembled structures at higher weight ratios of PTX. Hydrophobic interactions and π-π stacking are the primary forces responsible for the formation of both self- and coassembled structures. Interestingly, the structural analysis reveals that the CPT moiety of EB-CPT is less involved in assemblies due to steric hindrances. Instead, the interaction and coassembly processes are predominantly mediated by the EB derivative component of the prodrug. This research underscores the critical role of the solubilizing agent, EB derivative, in mediating the flexibility and interaction of CPT in combination therapy strategies, particularly with PTX, thus emphasizing the importance of conjugates for therapeutic developments. Furthermore, the molecular insights into the interaction sites and mechanisms facilitating coassembly between EB-CPT and PTX contribute valuable knowledge to the field, highlighting the potential of these nanomedicine combinations in advancing cancer treatment modalities.

Comprehending the Efficacy of Whitlock's Caffeine-Pincered Molecular Tweezer on β-Amyloid Aggregation

Alzheimer's disease (AD) stands as one of the most prevalent neurodegenerative conditions, leading to cognitive impairment, with no cure and preventive measures. Misfolding and aberrant aggregation of amyloid-β (Aβ) peptides are believed to be the underlying cause of AD. These amyloid aggregates culminate in the development of toxic Aβ oligomers and subsequent accumulation of β-amyloid plaques amidst neuronal cells in the brain, marking the hallmarks of AD. Drug development for the potentially curative treatment of Alzheimer's is, therefore, a tremendous challenge for the scientific community. In this study, we investigate the potency of Whitlock's caffeine-armed molecular tweezer in combating the deleterious effects of Aβ aggregation, with special emphasis on the seven residue Aβ16-22 fragment. Extensive all-atom molecular dynamics simulations are conducted to probe the various structural and conformational transitions of the peptides in an aqueous medium in both the presence and absence of tweezers. To explore the specifics of peptide-tweezer interactions, radial distribution functions, contact number calculations, binding free energies, and 2-D kernel density plots depicting the variation of distance-angle between the aromatic planes of the peptide-tweezer pair are computed. The central hydrophobic core, particularly the aromatic Phe residues, is crucial in the development of harmful amyloid oligomers. Notably, all analyses indicate reduced interpeptide interactions in the presence of the tweezer, which is attributed to the tweezer-Phe aromatic interaction. Upon increasing the tweezer concentration, the residues of the peptide are further encased in a hydrophobic environment created by the self-aggregating tweezer cluster, leading to the segregation of the peptide residues. This is further aided by the weakening of interstrand hydrogen bonding between the peptides, thereby impeding their self-aggregation and preventing the formation of neurotoxic β-amyloid. Furthermore, the study also highlights the efficacy of the molecular tweezer in destabilizing preformed amyloid fibrils as well as hindering the aggregation of the full-length Aβ1-42 peptide.