Structure-activity Relationship Research Articles

The interaction of the azetidine thiazole side chain with the active site loop (ASL) 3 drives the evolution of IMP metallo-β-lactamase against tebipenem.

Imipenemase (IMP) metallo-β-lactamases (MBLs) hydrolyze almost all available β-lactams including carbapenems and are not inhibited by any commercially available β-lactamase inhibitor. Tebipenem (TP) pivoxil is the first orally available carbapenem and possesses a unique bicyclic azetidine thiazole moiety located at the R2 position. TP has potent in vitro activity against Enterobacterales producing extended-spectrum and/or AmpC β-lactamases. Thus far, the activity of TP against IMP-producing strains is understudied. To address this knowledge gap, we explored the structure activity relationships of IMP MBLs by investigating whether IMP-6, IMP-10, IMP-25, and IMP-78 [MBLs with expanded hydrolytic activity against meropenem (MEM)] would demonstrate enhanced activity against TP. Most of the Escherichia coli DH10B strains expressing IMP-1 variants displayed a ≥twofold MIC difference between TP and MEM, while those expressing VIM or NDM variants demonstrated comparable MICs. Catalytic efficiency (kcat/KM) values for the TP hydrolysis by IMP-1, IMP-6, IMP-10, IMP-25, and IMP-78 were significantly lower than those obtained for MEM. Molecular dynamic simulations reveal that V67F and S262G substitutions (found in IMP-78) reposition active site loop 3, ASL-3, to better accommodate the bicyclic azetidine thiazole side chain, allowing microbiological/catalytic activity to approach that of comparison MBLs used in this study. These findings suggest that modifying the R2 side chain of carbapenems can significantly impact hydrolytic stability. Furthermore, changes in conformational dynamics due to single amino acid substitutions should be used to inform drug design of novel carbapenems.

Flavonoid as a Potent Antioxidant: Quantitative Structure-Activity Relationship Analysis, Mechanism Study, and Molecular Design by Synergizing Molecular Simulation and Machine Learning.

In this work, a quantitative structure-antioxidant activity relationship of flavonoids was performed using a machine learning (ML) method. To achieve lipid-soluble, highly antioxidant flavonoids, 398 molecular structures with various substitute groups were designed based on the flavonoid skeleton. The hydrogen dissociation energies (ΔG1, ΔG2, and ΔG3) related to multiple hydrogen atom transfer processes and the solubility parameter (δ) of flavonoids were calculated using molecular simulation. The group decomposition results and the calculated antioxidant parameters constituted the ML data set. The artificial neural network and random forest models were constructed to predict and analyze the contribution of the substitute groups and positions to the antioxidant activity. The results showed the hydroxyl group at positions B4', B5', and B6' and the branched alkyl group at position C3 in the flavonoid skeleton were the optimal choice for improving antioxidant activity and compatibility with apolar organic materials. Compared to the pyrogallol group-grafted flavonoid, the designed potent flavonoid decreased ΔG1 and δ by 2.2 and 15.1%, respectively, while ΔG2 and ΔG3 kept the favorable lower values. These findings suggest that an efficient flavonoid prefers multiple ortho-phenolic hydroxyl groups and suitable sites with hydrophobic groups. The combination of molecular simulation and the ML method may offer a new research approach for the molecular design of novel antioxidants.

Targeted small molecule therapy and inhibitors for lymphoma.

Lymphoma, a blood tumor, has become the ninth most common cancer in the world in 2020. Targeted inhibition is one of the important treatments for lymphoma. At present, there are many kinds of targeted drugs for the treatment of lymphoma. Studies have shown that Histone deacetylase, Bruton's tyrosine kinase and phosphoinositide 3-kinase all play an important role in the occurrence and development of tumors and become important and promising inhibitory targets. This article mainly expounds the important role of these target protein in tumors, and introduces the mechanism of action, structure-activity relationship and clinical research of listed small molecule inhibitors of these targets, hoping to provide new ideas for the treatment of lymphoma.

MDFit: automated molecular simulations workflow enables high throughput assessment of ligands-protein dynamics.

Molecular dynamics (MD) simulation is a powerful tool for characterizing ligand-protein conformational dynamics and offers significant advantages over docking and other rigid structure-based computational methods. However, setting up, running, and analyzing MD simulations continues to be a multi-step process making it cumbersome to assess a library of ligands in a protein binding pocket using MD. We present an automated workflow that streamlines setting up, running, and analyzing Desmond MD simulations for protein-ligand complexes using machine learning (ML) models. The workflow takes a library of pre-docked ligands and a prepared protein structure as input, sets up and runs MD with each protein-ligand complex, and generates simulation fingerprints for each ligand. Simulation fingerprints (SimFP) capture protein-ligand compatibility, including stability of different ligand-pocket interactions and other useful metrics that enable easy rank-ordering of the ligand library for pocket optimization. SimFPs from a ligand library are used to build & deploy ML models that predict binding assay outcomes and automatically infer important interactions. Unlike relative free-energy methods that are constrained to assess ligands with high chemical similarity, ML models based on SimFPs can accommodate diverse ligand sets. We present two case studies on how SimFP helps delineate structure-activity relationship (SAR) trends and explain potency differences across matched-molecular pairs of (1) cyclic peptides targeting PD-L1 and (2) small molecule inhibitors targeting CDK9.

Discovery, Synthesis, and Activity Evaluation of Novel Five-Membered Sulfur-Containing Heterocyclic Nucleosides as Potential Anticancer Agents In Vitro and In Vivo.

A series of novel five-membered sulfur-containing heterocyclic nucleoside derivatives were designed, synthesized, and evaluated for their anticancer activities in vitro and in vivo. The structure-activity relationship studies revealed that some of them showed obvious antitumor activities in several cancer cell lines. Among them, compound 22o exhibited remarkable antiproliferative activity against HeLa cells and was more potent than cisplatin (IC50 = 2.80 vs 7.99 μM). Furthermore, mechanism studies indicated that 22o inhibited cell metastasis, induced cell apoptosis, decreased mitochondrial membrane potential, and activated autophagy through the PI3K-Akt-mTOR signaling pathway. Moreover, drug affinity responsive target stability and the cellular thermal shift assay revealed that 22o targeted RPS6 and inhibited its phosphorylation. Importantly, 22o inhibited the growth of the HeLa xenograft mouse model with a low systemic toxicity. These results indicated that 22o may serve as potent anticancer agents that merit further attention in future anticancer drug discovery.

Photoredox Cascade Catalysts for Solar Hydrogen Production from Sustainable Hydrogen Sources.

Visible-light-driven photocatalytic hydrogen (H2) production has been extensively studied as a clean and sustainable energy resource. Although sacrificial electron donors (SEDs) are commonly used to evaluate photocatalytic activity, their irreversible decomposition forces charge separation, which disrupts the inherent dual productivity of photocatalysis, that is, the formation of both the reduction and oxidation products. To achieve highly efficient photoinduced charge separation without SED decomposition, the layer-by-layer assembly of redox-active photosensitizing dyes and electron mediators through Zr4+-phosphonate bonds has been extensively studied as an artificial mimic of the electron transport chain in natural photosynthesis. This concept paper presents an overview of photoredox cascade catalytic (PRCC) systems comprising multiple Ru(II)-trisbipyridine-type dyes and mediator layers on Pt-loaded TiO2 nanoparticles for H2 production from redox reversible electron donors (RREDs). The PRCC structure-activity relationship for photocatalytic H2 production is briefly discussed in terms of layer thickness, surface structure and modification, and cooperativity with molecular oxidation catalysts. Finally, new insights into the design of efficient dual-production photocatalysts based on the PRCC structure are presented.

Computational screening of metalloporphyrin catalysts for the activation of carbon dioxide

Electrocatalytic CO2 reduction (eCO2R) to value-added chemicals offers a promising route for carbon capture and utilization. Metalloporphyrin (M-POR) is a class of catalysts for eCO2R that has drawn attention due to its tuneable electronic and structural properties. This work presents a computational screening, based on density functional theory calculations, of one of the key steps in the eCO2R: the adsorption of CO2 on 110 M-PORs with varying peripheral ligands, metal centres, and oxidation states, to understand how these factors can influence CO2 activation. A set of criteria was used to shortlist M-PORs based on their ability to lengthen the C–O bond, bend the O–C–O angle, bind CO2, and donate charge from the metal of the M-POR to the carbon of CO2. 16 systems were selected for their potential to activate CO2. These systems predominantly have the electron configuration of the metal centre in the d[6] and d[7] configurations. Natural bond orbital analysis revealed the impact of electron-withdrawing groups in the system, which increases orbital splitting and, consequently, lowers the ability of the M-POR to activate CO2. Second-order perturbation theory analysis confirms that the presence of electron-donating groups in the ligand structure enhances CO2 activation. This work demonstrates the interconnected effect of peripheral ligands, metal centres, and oxidation states in M-PORs on their ability to adsorb and activate CO2, thereby establishing structure-activity relationships within M-PORs.

Discovery of Biphenyl Derivatives to Target Hsp70-Bim Protein-Protein Interaction in Chronic Myeloid Leukemia by Scaffold Hopping Strategy.

Hsp70-Bim protein-protein interaction (PPI) is the most recently identified specific target in chronic myeloid leukemia (CML) therapy. Herein, we developed a new class of Hsp70-Bim PPI inhibitors via scaffold hopping of S1g-10, the most potent Hsp70-Bim PPI inhibitor thus far. Through structure-activity relationship (SAR) study, we obtained a biphenyl scaffold compound JL-15 with a 5.6-fold improvement in Hsp70-Bim PPI suppression (Kd = 123 vs 688 nM) and a 4-fold improvement in water solubility (29.42 vs 7.19 μg/mL) compared to S1g-10. It maintains comparable apoptosis induction capability with S1g-10 against both TKI-sensitive and TKI-resistant CML cell lines in an Hsp70-Bim-dependent manner. Additionally, through SAR, 1H-15N TRSOY-NMR, and molecular docking, we revealed that Lys319 is a "hot spot" in the Hsp70-Bim PPI interface. Collectively, these results provide a novel chemical scaffold and structural insights for the rational design of Hsp70-Bim PPI inhibitors.

Review of the recent advances of pyrazole derivatives as selective COX-2 inhibitors for treating inflammation.

Pyrazole heterocycle is regarded as an extremely significant agent for the therapy of inflammation. Celecoxib, lonazolac, deracoxib, and phenylbutazone are examples of commercially approved pyrazole drugs with COX-2 inhibitory potential for curing inflammation. There have been recently many reviews for the biological significance of pyrazole derivatives. This review talks about pyrazole derivatives with anti-inflammatory activity and also sheds the light on the recent updates on pyrazole research with an emphasis on some synthetic pathways utilized to construct this privileged scaffold and structure activity relationship that accounts for the anti-inflammatory activity in an attempt to pave the opportunity for medicinal chemists to develop novel anti-inflammatory agents with better COX-2 selectivity.

Near-Term Quantum Classification Algorithms Applied to Antimalarial Drug Discovery.

Computational approaches are widely applied in drug discovery to explore properties related to bioactivity, physiochemistry, and toxicology. Over at least the last 20 years, the exploitation of machine learning on molecular data sets has been used to understand the structure-activity relationships that exist between biomolecules and druggable targets. More recently, these methods have also seen application for phenotypic screening data for neglected diseases such as tuberculosis and malaria. Herein, we apply machine learning to build quantum Quantitative Structure Activity Relationship models from antimalarial data sets. There is a continual need for new antimalarials to address drug resistance, and the readily available in vitro data sets could be utilized with newer machine learning approaches as these develop. Furthermore, quantum machine learning is a relatively new method that uses a quantum computer to perform the calculations. First, we present a classical-quantum hybrid computational approach by building a Latent Bernoulli Autoencoder machine learning model for compressing bit-vector descriptors to a size that can be adapted to quantum computers for classification tasks with limited loss of embedded information. Second, we apply our method for feature map compression to quantum classification algorithms, including a completely novel machine learning algorithm with no analogy in classical computers: the Quantum Fourier Transform Classifier. We apply both these approaches to build quantum machine learning models for small-molecule antimalarials with quantum simulation software and then benchmark these quantum models against classical machine learning approaches. While there are many challenges currently facing the development of reliable quantum computers, our results demonstrate that there is potential for the use of this technology in the field of drug discovery.

QSAR, ADMET, molecular docking, and dynamics studies of 1,2,4-triazine-3(2H)-one derivatives as tubulin inhibitors for breast cancer therapy

Breast cancer remains a leading cause of cancer-related deaths among women globally, necessitating the development of more effective therapeutic agents with minimal side effects. This study explores novel 1,2,4-triazine-3(2H)-one derivatives as potential inhibitors of Tubulin, a pivotal protein in cancer cell division, highlighting a targeted approach in cancer therapy. Using an integrated computational approach, we combined quantitative structure–activity relationship (QSAR) modeling, ADMET profiling, molecular docking, and molecular dynamics simulations to evaluate and predict the efficacy and stability of these compounds. Our QSAR models, developed through rigorous statistical analysis, revealed that descriptors such as absolute electronegativity and water solubility significantly influence inhibitory activity, achieving a predictive accuracy (R2) of 0.849. Molecular docking studies identified compounds with high binding affinities, particularly Pred28, which exhibited the best docking score of − 9.6 kcal/mol. Molecular dynamics simulations conducted over 100 ns provided further insights into the stability of these interactions. Pred28 demonstrated notable stability, with the lowest root mean square deviation (RMSD) of 0.29 nm and root mean square fluctuation (RMSF) values indicative of a tightly bound conformation to Tubulin. The novelty of this work lies in its methodological rigor and the integration of multiple advanced computational techniques to pinpoint compounds with promising therapeutic potential. Our findings advance the current understanding of Tubulin inhibitors and open avenues for the synthesis and experimental validation of these compounds, aiming to offer new solutions for breast cancer treatment.

Tailoring Highly Branched Poly(β-amino ester)s for Efficient and Organ-Selective mRNA Delivery.

Development of mRNA therapeutics necessitates targeted delivery technology, while the clinically advanced lipid nanoparticles face difficulty for extrahepatic delivery. Herein, we design highly branched poly(β-amino ester)s (HPAEs) for efficacious organ-selective mRNA delivery through tailoring their chemical compositions and topological structures. Using an "A2+B3+C2" Michael addition platform, a combinatorial library of 219 HPAEs with varied backbone structures, terminal groups, and branching degrees are synthesized. The branched topological structures of HPAEs provide enhanced serum resistance and significantly higher mRNA expression in vivo. The terminal amine structures of HPAEs determine the organ-selectivity of mRNA delivery following systemic administration: morpholine facilitates liver targeting, ethylenediamine favors spleen delivery, while methylpentane enables mRNA delivery to the liver, spleen, and lungs simultaneously. This study represents a comprehensive exploration of the structure-activity relationship governing both the efficiency and organ-selectivity of mRNA delivery by HPAEs, suggesting promising candidates for treating various organ-related diseases.

Structure-Based Design and Discovery of a Potent and Cell-Active LC3A/B Covalent Inhibitor.

Autophagy is a highly conserved cellular homeostasis maintenance mechanism in eukaryotes. Microtubule-associated protein light chain 3 (LC3) plays a crucial role in autophagy. It has multiple pairs of protein-protein interactions (PPIs) with other proteins, and these PPIs have an effect on the regulation of autophagosome formation and the recruitment of autophagic substrates. In our previous work, a small molecule covalent inhibitor DC-LC3in-D5 which could inhibit LC3A/B PPIs was identified, but a detailed study of structure-activity relationships (SARs) was lacking. Herein, a new molecule LC3in-C42 was discovered utilizing the hybridization of advantageous fragments, whose potency (IC50 = 7.6 nM) had been greatly improved compared with that of DC-LC3in-D5. LC3in-C42 inhibits autophagy at the cellular level and its efficacy far exceeds that of DC-LC3in-D5. Thus far, LC3in-C42 stands as the most potent LC3A/B small molecule inhibitor. LC3in-C42 could serve as a powerful tool for LC3A/B protein and autophagy research.

The Unique Structure–Activity Relationship of Porphyrins and Clay Mineral Systems in Modern Applications: A Comprehensive Review

The Unique Structure–Activity Relationship of Porphyrins and Clay Mineral Systems in Modern Applications: A Comprehensive Review

Electrophile Determines Cellular Phenotypes among XPO1-Targeting Small Molecules.

Covalent drug discovery has experienced a renaissance, with numerous electrophilic small molecules recently gaining FDA approval. Many structurally diverse electrophilic small molecules target exportin-1 (XPO1/CRM1) at cysteine 528, including the selective inhibitor of nuclear export (SINE) selinexor, which was FDA-approved as an anticancer agent in 2019. Emerging evidence supports additional pharmacological classes of XPO1 modulators targeting Cys528, including the selective inhibitors of transcriptional activation (SITAs) and probes that induce rapid degradation of XPO1. Here, we analyzed structure-activity relationships across multiple structural series of XPO1 Cys528-targeting probes. We observe that the electrophilic moiety of Cys528-targeting small molecules plays a decisive role in the cellular behavior observed, with subtle changes in electrophile structure being sufficient to convert XPO1-targeting probes to different pharmacological classes. This investigation represents a unique case study in which the electrophile functionality used to target a specific cysteine determines the pharmacological effect among diverse XPO1-targeting small molecules.

Optimization of pyrazolopyridine 4-carboxamides with potent antimalarial activity for which resistance is associated with the P. falciparum transporter ABCI3

Emerging resistance to current antimalarials is reducing their effectiveness and therefore there is a need to develop new antimalarial therapies. Toward this goal, high throughput screens against the P. falciparum asexual parasite identified the pyrazolopyridine 4-carboxamide scaffold. Structure-activity relationship analysis of this chemotype defined that the N1-tert-butyl group and aliphatic foliage in the 3- and 6-positions were necessary for activity, while the inclusion of a 7′-aza-benzomorpholine on the 4-carboxamide motif resulted in potent anti-parasitic activity and increased aqueous solubility. A previous report that resistance to the pyrazolopyridine class is associated with the ABCI3 transporter was confirmed, with pyrazolopyridine 4-carboxamides showing an increase in potency against parasites when the ABCI3 transporter was knocked down. The low metabolic stability intrinsic to the pyrazolopyridine scaffold and the slow rate by which the compounds kill asexual parasites resulted in poor performance in a P. berghei asexual blood stage mouse model. Lowering the risk of resistance and mitigating the metabolic stability and cytochrome P450 inhibition will be challenges in the future development of the pyrazolopyrimidine antimalarial class.

Polymer Microspheres Carrying Schiff-Base Ligands for Metal Ion Adsorption Obtained via Pickering Emulsion Polymerization

Several traditional methods for producing polymer microparticle adsorbents for metal ions exist, such as bulk polymerization followed by milling and crushing the material to micron-size particles, precipitation from organic solvents, and suspension polymerization utilizing surfactants. Alternative methods that are easily scalable and are environmentally friendly are in high demand. This study employs Pickering Emulsion Polymerization Technology (PEmPTech) to synthesize nanostructured polymer microspheres that incorporate Schiff-base ligands, which can be utilized for metal ion adsorption, and specifically Cu(II) ions. Our innovative approach makes use of nanoparticle-stabilized, surfactant-free emulsions/suspensions, enabling the straightforward production of ligand-bearing microspheres while allowing for the precise modulation of the polymer matrix chemistry to maximize adsorption capacities. Through this method, we demonstrate notable enhancements in Cu(II) ion adsorption, which correlates with both the polarity of the monomers used and the concentration of Schiff-base ligands within the microspheres. Notably, our results offer insights into the structure–activity relationships essential for designing tailored adsorbents. This work provides a scalable method to produce high-performance adsorbents and also contributes to sustainable methodologies by excluding harmful surfactants and solvents.

Synthesis of modified Schiff base appended 1,2,4-triazole hybrids scaffolds: elucidating the invitro and in silico α-amylase and α-glucosidase inhibitors potential.

The current study involves the synthesis of Schiff bases based on 1,2,4-triazoles skeleton and assessing their α-amylase and α-glucosidase profile. Furthermore, the precise structures of the synthesized derivatives were elucidated using various spectroscopic methods such as 1H-NMR, 13C-NMR and HREI-MS. Using glimepiride as the reference standard, the invitro α-glucosidase and α-amylase inhibitory activities of the synthesized compounds were evaluated in order to determine their potential anti-diabetic properties. All analogues showed varied range of inhibitory activity having IC50 values ranging from 17.09±0.72 to 45.34±0.03 μM (α-amylase) and 16.35±0.42 to 42.31±0.09 μM (α-glucosidase), respectively. Specifically, the compounds 1, 7 and 8 were found to be significantly active with IC50 values of 17.09±0.72, 19.73±0.42, and 23.01±0.04 μM (against α-amylase) and 16.35±0.42, 18.55±0.26, and 20.07±0.02 μM (against α-glucosidase) respectively. The obtained results were compared with the Glimepiride reference drug having IC50values of 13.02±0.11 μM (for α-glucosidase) and 15.04±0.02 μM (for α-amylase), respectively. The structure-activity relationship (SAR) studies were conducted based on differences in substituent patterns at varying position of aryl rings A and B may cause to alter the inhibitory activities of both α-amylase and α-glucosidase enzymes. Additionally, the molecular docking study was carried out to explore the binding interactions possessed by most active analogues with the active sites of targeted α-amylase and α-glucosidase enzymes.

Customizing pyridinic nitrogen coordination in Ni–N–C for electrocatalytic CO2 reduction towards CO

Nickel anchored N-doped carbon electrocatalysts (Ni–N–C) are rapidly developed for the electrochemical reduction reaction of carbon dioxide (CO2RR). However, the high-performanced Ni–N–C analogues design for CO2RR remains bewilderment, for the reason lacking of definite guidance for its structure-activity relationship. Herein, the correlation between the proportion of nitrogen species derived from various nitrogen sources and the CO2RR activity of Ni–N–C is investigated. The x-ray photoelectron spectroscopy (XPS) spectrum combined with the CO2RR performance results show that pyridinic-N content has a positive correlation with CO2RR activity. Moreover, density functional theory (DFT) demonstrates that pyridinic-N coordinated Ni–N4 sites offers optimized free energy and favorable selectivity towards CO2RR compared with pyrrolic-N. Accordingly, Ni–Na–C with highest pyridinic-N content (ammonia as nitrogen source) performs superior CO2RR activity, with the maximum carbon monoxide faradaic efficiency (FECO) of 99.8% at −0.88 V vs. RHE and the FECO surpassing 95% within potential ranging of −0.88 to −1.38 V vs. RHE. The building of this parameter for CO2RR activity of Ni–N–C give instructive forecast for low-cost and highly active CO2RR electrocatalysts.

TAG‐Assisted Liquid‐Phase Synthesis and Structure Activity Relationship of Macolacin‐Based Side‐to‐Tail Cyclopeptides Antibiotic

<scp>TAG</scp>‐Assisted Liquid‐Phase Synthesis and Structure Activity Relationship of Macolacin‐Based Side‐to‐Tail Cyclopeptides Antibiotic