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Binding affinity is a fundamental parameter in drug design, describing the strength of the interaction between a molecule and its target protein. Accurately predicting binding affinity is crucial for the rapid development of novel therapeutics, the prioritization of promising candidates, and the optimization of their properties through rational design strategies. Binding affinity is determined by the mechanism of recognition between proteins and ligands. Various models, including the lock and key, induced fit, and conformational selection, have been proposed to explain this recognition process. However, current computational strategies to predict binding affinity, which are based on these models, have yet to produce satisfactory results. This article explores the connection between binding affinity and these protein-ligand interaction models, highlighting that they offer an incomplete picture of the mechanism governing binding affinity. Specifically, current models primarily center on the binding of the ligand and do not address its dissociation. In this context, the concept of ligand trapping is introduced, which models the mechanisms of dissociation. When combined with the current models, this concept can provide a unified theoretical framework that may allow for the accurate determination of the ligands’ binding affinity.

The Michaelis–Menten equation is usually expressed in terms of k cat and K m values: v = k cat [S]/( K m + [S]). However, it is impossible to interpret K m in the absence of additional information, while the ratio of k cat / K m provides a measure of enzyme specificity and is proportional to enzyme efficiency and proficiency. Moreover, k cat / K m provides a lower limit on the second order rate constant for substrate binding. For these reasons it is better to redefine the Michaelis–Menten equation in terms of k cat and k cat / K m values: v = k SP [S]/(1 + k SP [S]/ k cat ), where the specificity constant, k SP = k cat / K m . In this short review, the rationale for this assertion is explained and it is shown that more accurate measurements of k cat / K m can be derived directly using the modified form of the Michaelis–Menten equation rather than calculated from the ratio of k cat and K m values measured separately. Even greater accuracy is achieved with fitting the raw data directly by numerical integration of the rate equations rather than using analytically derived equations. The importance of fitting to derive k cat and k cat / K m is illustrated by considering the role of conformational changes in enzyme specificity where k cat and k cat / K m can reflect different steps in the pathway. This highlights the pitfalls in attempting to interpret K m , which is best understood as the ratio of k cat divided by k cat / K m .

To our knowledge, this work represents one of the earliest comparative studies on the anion-binding behaviors of carbazole-based structural analogs, demonstrating that a flexible macrocycle markedly improves iodide binding affinity via an induced-fit mechanism. The flexible analog PBG exhibits a 22.78-fold higher fluorescence quenching efficiency upon iodide binding compared to the rigid WDG ( K PBG / K WDG = 22.78), demonstrating its potential as a highly sensitive optical probe and offering a novel strategy for engineering dynamic supramolecular receptors. Two carbazole-based macrocyclic probes, PBG (flexible benzene ring) and WDG (rigid fluorene backbone), were synthesized via Friedel–Crafts reactions. Their iodide (I − ) recognition properties were systematically explored using 1 H NMR, UV–vis absorption, and fluorescence spectroscopy. Quantitative analysis via the Benesi–Hildebrand equation and nonlinear fitting demonstrated that flexible PBG achieves superior I − binding ( K PBG = 1.387 × 10 5 M −1 ) through induced-fit conformational adjustments, whereas rigid WDG ( K WDG = 6.089 × 10 3 M −1 ) is constrained by preorganized cavity geometry, adhering to a conformational selection mechanism. This work elucidates the synergistic interplay between conformational dynamics and localized structural adaptations governing anion recognition. The findings advance the rational design of tunable, high-affinity anion receptors and deepen the understanding of conformational regulation in supramolecular systems.

The 16S rRNA‐binding ribosomal protein S15 is a key component in the assembly of the small ribosomal subunit in bacteria. We have shown that S15 from the extreme thermophile Thermus thermophilus represses the translation of its own mRNA in vitro , by interacting with the leader segment of its mRNA. The S15 mRNA‐binding site was characterized by footprinting experiments, deletion analysis and site‐directed mutagenesis. S15 binding triggers a conformational rearrangement of its mRNA into a fold that mimics the conserved three‐way junction of the S15 rRNA‐binding site. This conformational change masks the ribosome entry site, as demonstrated by direct competition between the ribosomal subunit and S15 for mRNA binding. A comparison of the T.thermophilus and Escherichia coli regulation systems reveals that the two regulatory mRNA targets do not share any similarity and that the mechanisms of translational inhibition are different. Our results highlight an astonishing plasticity of mRNA in its ability to adapt to evolutionary constraints, that contrasts with the extreme conservation of the rRNA‐binding site.

The role of proton tunnelling in biological catalysis is investigated here within the frameworks of quantum information theory and thermodynamics. We consider the quantum correlations generated through two hydrogen bonds between a substrate and a prototypical enzyme that first catalyses the tautomerization of the substrate to move on to a subsequent catalysis, and discuss how the enzyme can derive its catalytic potency from these correlations. In particular, we show that classical changes induced in the binding site of the enzyme spreads the quantum correlations among all of the four hydrogen-bonded atoms thanks to the directionality of hydrogen bonds. If the enzyme rapidly returns to its initial state after the binding stage, the substrate ends in a new transition state corresponding to a quantum superposition. Open quantum system dynamics can then naturally drive the reaction in the forward direction from the major tautomeric form to the minor tautomeric form without needing any additional catalytic activity. We find that in this scenario the enzyme lowers the activation energy so much that there is no energy barrier left in the tautomerization, even if the quantum correlations quickly decay.

SARS-CoV-2 Mpro (Mpro) is the critical cysteine protease in coronavirus viral replication. Tea polyphenols are effective Mpro inhibitors. Therefore, we aim to isolate and synthesize more novel tea polyphenols from Zhenghedabai (ZHDB) white tea methanol-water (MW) extracts that might inhibit COVID-19. Through molecular networking, 33 compounds were identified and divided into 5 clusters. Further, natural products molecular network (MN) analysis showed that MN1 has new phenylpropanoid-substituted ester-catechin (PSEC), and MN5 has the important basic compound type hydroxycinnamoylcatechins (HCCs). Thus, a new PSEC (1, PSEC636) was isolated, which can be further detected in 14 green tea samples. A series of HCCs were synthesized (2–6), including three new acetylated HCCs (3–5). Then we used surface plasmon resonance (SPR) to analyze the equilibrium dissociation constants (KD) for the interaction of 12 catechins and Mpro. The KD values of PSEC636 (1), EGC-C (2), and EC-CDA (3) were 2.25, 2.81, and 2.44 μM, respectively. Moreover, compounds 1, 2, and 3 showed the potential Mpro inhibition with IC50 5.95 ± 0.17, 9.09 ± 0.22, and 23.10 ± 0.69 μM, respectively. Further, we used induced fit docking (IFD), binding pose metadynamics (BPMD), and molecular dynamics (MD) to explore the stable binding pose of Mpro-1, showing that 1 could tightly bond with the amino acid residues THR26, HIS41, CYS44, TYR54, GLU166, and ASP187. The computer modeling studies reveal that the ester, acetyl, and pyrogallol groups could improve inhibitory activity. Our research suggests that these catechins are effective Mpro inhibitors, and might be developed as therapeutics against COVID-19. [Display omitted] •Binding affinities of 12 catechins were tested by surface plasmon resonance technology.•Catechins 1–6 (1, 3–5 are new) were identified as novel inhibitors of SARS-CoV-2 Mpro.•1-Mpro complex were studied by induced-fit docking, binding pose metadynamics, and molecular dynamics.•Benzene ring, hydroxyl, and acetyl groups of substituted p-coumaric acid interact with SARS-CoV-2 Mpro.•THR26, HIS41, CYS44, TYR54, GLU166, and ASP187 residues are the key binding sites.

This paper describes the first detailed NMR analysis of the borylated intermediates and target compounds for a small library of pyrrolidine iminosugars of l-gulose absolute stereochemical configuration. The iminosugars were functionalised via N-alkylation to bear a boronate ester or boronic acid groups. The addition of the organic boron pharmacophore allows to further explore the chemical space around and in the active sites, where the boron atom has the capability to make reversible covalent bonds with enzyme nucleophiles and other nucleophiles. We discuss the concurrent complex equilibrium processes of mutarotation and borarotation as studied by NMR.

The dopamine D3 receptor (D3R) is an important central nervous system target for treating various neurological diseases. D3R antagonists modulate the improvement of psychostimulant addiction and relapse, while D3R agonists can enhance the response to dopaminergic stimulation and have potential applications in treating Parkinson’s disease, which highlights the importance of identifying novel D3R ligands. Therefore, we performed auto dock Vina-based virtual screening and D3R-binding-affinity assays to identify human D3R ligands with diverse structures. All molecules in the ChemDiv library (>1,500,000) were narrowed down to a final set of 37 molecules for the binding assays. Twenty-seven compounds exhibited over 50% inhibition of D3R at a concentration of 10 μM, and 23 compounds exhibited over 70% D3R inhibition at a concentration of 10 μM. Thirteen compounds exhibited over 80% inhibition of D3R at a concentration of 10 μM and the IC50 values were measured. The IC50 values of the five compounds with the highest D3R-inhibition rates ranged from 0.97 μM to 1.49 μM. These hit compounds exhibited good structural diversity, which prompted us to investigate their D3R-binding modes. After trial and error, we combined unbiased molecular dynamics simulation (MD) and molecular mechanics generalized Born surface area (MM/GBSA) binding free-energy calculations with the reported protein–ligand-binding pose prediction method using induced-fit docking (IFD) and binding pose metadynamics (BPMD) simulations into a self-consistent and computationally efficient method for predicting and verifying the binding poses of the hit ligands to D3R. Using this IFD-BPMD-MD-MM/GBSA method, we obtained more accurate and reliable D3R–ligand-binding poses than were obtained using the reported IFD-BPMD method. This IFD-BPMD-MD-MM/GBSA method provides a novel paradigm and reference for predicting and validating other protein–ligand binding poses.

Background: Indicaxanthin, a betaxanthin belonging to the betalain class of compounds, has been recently demonstrated to exert significant antiproliferative effects inducing apoptosis of human melanoma cells through the inhibition of NF-κB as the predominant pathway. Specifically, Indicaxanthin inhibited IκBα degradation in A375 cells. In resting cells, NF-κB is arrested in the cytoplasm by binding to its inhibitor protein IκBα. Upon stimulation, IκBα is phosphorylated by the IKK complex, and degraded by the proteasome, liberating free NF-κB into the nucleus to initiate target gene transcription. Inhibition of the IKK complex leads to the arrest of the NF-κB pathway. Methods: To acquire details at the molecular level of Indicaxanthin’s inhibitory activity against hIKKβ, molecular modeling and simulation techniques including induced-fit docking (IFD), binding pose metadynamics (BPMD), molecular dynamics simulations, and MM-GBSA (molecular mechanics-generalized Born surface area continuum solvation) have been performed. Results: The computational calculations performed on the active and inactive form, and the allosteric binding site of hIKKβ, revealed that Indicaxanthin inhibits prevalently the active form of the hIKKβ. MM-GBSA computations provide further evidence of Indicaxanthin’s stability inside the active binding pocket with a binding free energy of −22.2 ± 4.3 kcal/mol with respect to the inactive binding pocket with a binding free energy of −20.7 ± 4.7 kcal/mol. BPMD and MD simulation revealed that Indicaxanthin is likely not an allosteric inhibitor of hIKKβ. Conclusion: As a whole, these in silico pieces of evidence show that Indicaxanthin can inhibit the active form of the hIKKβ adding novel mechanistic insights on its recently discovered ability to impair NF-κB signaling in melanoma A375 cells. Moreover, our results suggest the phytochemical as a new lead compound for novel, more potent IKKβ inhibitors to be employed in the treatment of cancer and inflammation-related conditions.

New thymol-3,4-disubstitutedthiazole hybrids were synthesised as dual COX-2/5-LOX inhibitors. Compounds , , , and displayed inhibitory activity against COX-2 (IC = 0.037, 0.042, 0.046, and 0.039 µM nearly equal to celecoxib (IC = 0.045 µM . , , and showed SI (379, 341, and 374, respectively) higher than that of celecoxib (327). - elicited 5-LOX inhibitory activity higher than quercetin. - , - , , and possessed inhibition of formalin induced paw edoema higher than celecoxib. , , , - , and showed gastrointestinal safety profile as celecoxib and diclofenac sodium in the population of fasted rats. Induced fit docking and molecular dynamics simulation predicted good fitting of and without changing the packing and globularity of the apo protein. In conclusion, and achieved the target goal as multitarget inhibitors of inflammation.