Biomolecular Interactions Research Articles

Competitive SPR chaser assay to study biomolecular interactions with very slow binding dissociation rate constant

Binding kinetics of drug and its target protein is crucial for the efficacy and safety of the drug. Using surface plasmon resonance (SPR) technology, we performed a competitive SPR chaser assay, a method to study biomolecular interactions with very slow dissociation rate constants (kd < 1E-4 s−1). This report described the principle and the experimental setup of the chaser assay, which involves using a competitive probe (chaser) to detect changes in target occupancy by a test molecule over time. We demonstrated the applicability of the chaser assay for both small and large molecules and compared the results with conventional SPR kinetic analysis and other methods. We suggest that the chaser assay is a useful and robust technique to characterize very tight biomolecular interactions, and that it can also be used to study cooperativity in ternary complex formation.

Real-time analysis of the biomolecular interaction between gelsolin and Aβ1-42 monomer and its implication for Alzheimer's disease

Biomolecular interaction acts a pivotal part in understanding the mechanisms underlying the development of Alzheimer's disease (AD). Herein, we built a biosensing platform to explore the interaction between gelsolin (GSN) and different β-amyloid protein 1-42 (Aβ1-42) species, including Aβ1-42 monomer (m-Aβ), Aβ1-42 oligomers with both low and high levels of aggregation (LLo-Aβ and HLo-Aβ) via dual polarization interferometry (DPI). Real-time molecular interaction process and kinetic analysis showed that m-Aβ had the strongest affinity and specificity with GSN compared with LLo-Aβ and HLo-Aβ. The impact of GSN on inhibiting aggregation of Aβ1-42 and solubilizing Aβ1-42 aggregates was evaluated by circular dichroism (CD) spectroscopy. The maintenance of random coil structure of m-Aβ and the reversal of β-sheet structure in HLo-Aβ were observed, demonstrating the beneficial effects of GSN on preventing Aβ from aggregation. In addition, the structure of m-Aβ/GSN complex was analyzed in detail by molecular dynamics (MD) simulation and molecular docking. The specific binding sites and crucial intermolecular forces were identified, which are believed to stabilize m-Aβ in its soluble state and to inhibit the fibrilization of Aβ1-42. Combined theoretical simulations and experiment results, we speculate that the success of GSN sequestration mechanism and the balance of GSN levels in cerebrospinal fluid and plasma of AD subjects may contribute to a delay in AD progression. This research not only unveils the molecular basis of the interaction between GSN and Aβ1-42, but also provides clues to understanding the crucial functions of GSN in AD and drives the development of AD drugs and therapeutic approaches.

Sodium Ion-Induced Structural Transition on the Surface of a DNA-Interacting Protein.

Protein surfaces have pivotal roles in interactions between proteins and other biological molecules. However, the structural dynamics of protein surfaces have rarely been explored and are poorly understood. Here, the surface of a single-stranded DNA (ssDNA) binding protein (SSB) with four DNA binding domains that bind ssDNA in binding site sizes of 35, 56, and 65 nucleotides per tetramer is investigated. Using oligonucleotides as probes to sense the charged surface, NaCl induces a two-state structural transition on the SSB surface even at moderate concentrations. Chelation of sodium ions with charged amino acids alters the network of hydrogen bonds and/or salt bridges on the surface. Such changes are associated with changes in the electrostatic potential landscape and interaction mode. These findings advance the understanding of the molecular mechanism underlying the enigmatic salt-induced transitions between different DNA binding site sizes of SSBs. This work demonstrates that monovalent salt is a key regulator of biomolecular interactions that not only play roles in non-specific electrostatic screening effects as usually assumed but also may configure the surface of proteins to contribute to the effective regulation of biomolecular recognition and other downstream events.

Oligomerization-driven avidity correlates with SARS-CoV-2 cellular binding and inhibition

Cellular processes are controlled by the thermodynamics of the underlying biomolecular interactions. Frequently, structural investigations use one monomeric binding partner, while ensemble measurements of binding affinities generally yield one affinity representative of a 1:1 interaction, despite the majority of the proteome consisting of oligomeric proteins. For example, viral entry and inhibition in SARS-CoV-2 involve a trimeric spike surface protein, a dimeric angiotensin-converting enzyme 2 (ACE2) cell-surface receptor and dimeric antibodies. Here, we reveal that cooperativity correlates with infectivity and inhibition as opposed to 1:1 binding strength. We show that ACE2 oligomerizes spike more strongly for more infectious variants, while exhibiting weaker 1:1 affinity. Furthermore, we find that antibodies use induced oligomerization both as a primary inhibition mechanism and to enhance the effects of receptor-site blocking. Our results suggest that naive affinity measurements are poor predictors of potency, and introduce an antibody-based inhibition mechanism for oligomeric targets. More generally, they point toward a much broader role of induced oligomerization in controlling biomolecular interactions.

Development of a carboxymethyl chitosan functionalized slide for small molecule detection using oblique-incidence reflectivity difference technology.

Label-free optical biosensors have become powerful tools in the study of biomolecular interactions without the need for labels. High throughput and low detection limit are desirable for rapid and accurate biomolecule detection. The oblique-incidence reflectivity difference (OI-RD) technique is capable of detecting thousands of biomolecular interactions in a high-throughput mode, specifically for biomolecules larger than 1000 Da. In order to enhance the detection capability of OI-RD for small molecules (typically < 500 Da), we have developed a three-dimensional biochip that utilized carboxymethyl chitosan (CMCS) functionalized slides. By investigating various factors such as sonication time, protein immobilization time, CMCS molecular weight, and glutaraldehyde (GA) functionalization time, we have achieved a detection limit of 6.8 pM for avidin (68 kDa). Furthermore, accurate detection of D-biotin with a molecular weight of 244 Da has also been achieved. This paper presents an effective solution for achieving both high throughput and low detection limits using the OI-RD technique in the field of biomolecular interaction detection.

Computational screening of the effects of mutations on protein-protein off-rates and dissociation mechanisms by τRAMD

The dissociation rate, or its reciprocal, the residence time (τ), is a crucial parameter for understanding the duration and biological impact of biomolecular interactions. Accurate prediction of τ is essential for understanding protein-protein interactions (PPIs) and identifying potential drug targets or modulators for tackling diseases. Conventional molecular dynamics simulation techniques are inherently constrained by their limited timescales, making it challenging to estimate residence times, which typically range from minutes to hours. Building upon its successful application in protein-small molecule systems, τ-Random Acceleration Molecular Dynamics (τRAMD) is here investigated for estimating dissociation rates of protein-protein complexes. τRAMD enables the observation of unbinding events on the nanosecond timescale, facilitating rapid and efficient computation of relative residence times. We tested this methodology for three protein-protein complexes and their extensive mutant datasets, achieving good agreement between computed and experimental data. By combining τRAMD with MD-IFP (Interaction Fingerprint) analysis, dissociation mechanisms were characterized and their sensitivity to mutations investigated, enabling the identification of molecular hotspots for selective modulation of dissociation kinetics. In conclusion, our findings underscore the versatility of τRAMD as a simple and computationally efficient approach for computing relative protein-protein dissociation rates and investigating dissociation mechanisms, thereby aiding the design of PPI modulators.

Solvation free energy in governing equations for DNA hybridization, protein-ligand binding, and protein folding.

This work examines the thermodynamics of model biomolecular interactions using a governing equation that accounts for the participation of bulk water in the equilibria. In the first example, the binding affinities of two DNA duplexes, one of nine and one of 10 base pairs in length, are measured and characterized by isothermal titration calorimetry (ITC) as a function of concentration. The results indicate that the change in solvation free energy that accompanies duplex formation (ΔGS) is large and unfavorable. The duplex with the larger number of G:C pairings yields the largest change in solvation free energy, ΔGS = +460 kcal·mol-1per base pair at 25 °C. A van't Hoff analysis of the data is complicated by the varying degree of intramolecular base stacking within each DNA strand as a function of temperature. A modeling study reveals how the solvation free energy alters the output of a typical ITC experiment and leads to a good, though misleading, fit to the classical equilibrium equation. The same thermodynamic framework is applied to a model protein-ligand interaction, the binding of ribonuclease A with the nucleotide inhibitor 3'-UMP, and to a conformational equilibrium, the change in tertiary structure of α-lactalbumin in molar guanidinium chloride solutions. The ribonuclease study yields a value of ΔGS = +160 kcal·mol-1, whereas the folding equilibrium yields ΔGS ≈ 0, an apparent characteristic of hydrophobic interactions. These examples provide insight on the role of solvation energy in binding equilibria and suggest a pivot in the fundamental application of thermodynamics to solution chemistry.

Synthesis of novel thiazole derivatives containing 3-methylthiophene carbaldehyde as potent anti α-glucosidase agents: In vitro evaluation, molecular docking, dynamics, MM-GBSA, and DFT studies

Thiazole derivatives bearing thiophene carbaldehyde have been successfully prepared by refluxing 3-methylthiophene carbaldehyde with thiosemicarbazide in absolute ethanol followed by treating the obtained product with different phenacyl bromide to get thiazole products in better yields. These derivatives were confirmed using 1H-, 13C NMR, and EI-MS spectrometry techniques and finally subjected for their α-glucosidase inhibitory potential. Two compounds in the series including 2 g (IC50 = 9.00 ± 0.57 µM) and 2b (IC50 = 13.50 ± 0.20 µM) were found as the most potent α-glucosidase inhibitors better than the standard acarbose. Furthermore, the remaining five compounds attributed significantly to less activity. The studied molecules were calculated on the 6–31++g(d,p) basis set at B3LYP, HF, M062X levels with the help of the Gaussian package program, and their chemical activities were compared. Following that, the molecules' interactions with different α-glucosidase proteins (PDB IDs: 1R47 and 1UAS) were investigated, and their activities were contrasted. The binding free energy of the molecule with the best docking score is computed using MM/GBSA techniques. The comparative molecular dynamics simulations of the 2g-1UAS and 2g-1R47 complexes highlight the intricate balance of forces that govern biomolecular interactions. The findings suggest that while the 2g-1UAS complex forms more stable interactions, as indicated by lower RMSD values, the 2g-1R47 complex maintains its structural integrity through strong hydrogen bonds. Overall, the equilibrium conformations achieved by both complexes suggest they are well-suited for their roles in physiological environments.

AutoFocus: a hierarchical framework to explore multi-omic disease associations spanning multiple scales of biomolecular interaction

Recent advances in high-throughput measurement technologies have enabled the analysis of molecular perturbations associated with disease phenotypes at the multi-omic level. Such perturbations can range in scale from fluctuations of individual molecules to entire biological pathways. Data-driven clustering algorithms have long been used to group interactions into interpretable functional modules; however, these modules are typically constrained to a fixed size or statistical cutoff. Furthermore, modules are often analyzed independently of their broader biological context. Consequently, such clustering approaches limit the ability to explore functional module associations with disease phenotypes across multiple scales. Here, we introduce AutoFocus, a data-driven method that hierarchically organizes biomolecules and tests for phenotype enrichment at every level within the hierarchy. As a result, the method allows disease-associated modules to emerge at any scale. We evaluated this approach using two datasets: First, we explored associations of biomolecules from the multi-omic QMDiab dataset (n = 388) with the well-characterized type 2 diabetes phenotype. Secondly, we utilized the ROS/MAP Alzheimer’s disease dataset (n = 500), consisting of high-throughput measurements of brain tissue to explore modules associated with multiple Alzheimer’s Disease-related phenotypes. Our method identifies modules that are multi-omic, span multiple pathways, and vary in size. We provide an interactive tool to explore this hierarchy at different levels and probe enriched modules, empowering users to examine the full hierarchy, delve into biomolecular drivers of disease phenotype within a module, and incorporate functional annotations.

Real-time detection of Tau-381 protein using liquid crystal-based sensors for Alzheimer's disease diagnosis

Tau is a protein found in the central nervous system (CNS) and is involved in stabilizing microtubules in axons. Given the link between Tau levels in the body and Alzheimer's disease (AD), there is a demand for straightforward and precise strategies to detect Tau in body fluids. In this study, we report liquid crystal (LC)-based sensors for the real-time detection of Tau protein, a well-known AD biomarker. The sensor uses a detection method based on the orientation change of the LC because of the competitive biomolecular interaction between Tau and Tau aptamers with the cationic polymer poly-L-lysine (PLL). Tau and its aptamers form stable complexes through electrostatic interactions. Owing to the consumption of the aptamer, the positively charged PLL fails to interact with the aptamer but binds to the negatively charged 1.2-dioleoyl-sn-glycero-3-phospho-(1′-rac-glycerol) sodium salt (DOPG). The PLL and DOPG complex alters the orientation of the LC to ensure a planar anchoring of the 4-cyano-4′-pentylbiphenyl (5CB)/aqueous interface; this anchoring intensifies with increasing Tau concentration, thus enabling the observation of a bright optical image. Our LC-based sensor demonstrated a low detection limit of 2.77 pg/mL in phosphate buffered saline (PBS) and 10.86 pg/mL and 19.31 pg/mL in human serum and plasma, respectively. Moreover, it is anticipated to be suitable for point-of-care diagnosis of AD because it does not require specialized analytical equipment and only requires microliters of sample.

Evaluation of Co(II) Schiff base complexes: Catalysis, theoretical and biomolecular interaction studies

Two Schiff base ligands, namely H2L1 [3-(2‑hydroxy-phenylimino)-1,3-dihydro-indole-2-one] and H2L2 [3-(2-mercapto-phenylimino)-1,3-dihydro-indole-2–1], were successfully synthesized. Furthermore, the ligands were subsequently complexed with [CoCl2(PPh3)3] to form CoL1 and CoL2, respectively. The synthesized metal complexes were investigated using FTIR, UV–Visible, and NMR spectroscopic techniques. Catalytic efficiency was evaluated for the oxidation of alcohol and C6H5-H5C6Coupling reactions. DFT study verified the structural parameters of the prepared Co2+ complexes were made reliable. The interaction of Co2+ Schiff base complexes with BSA and DNA were studied using an in-silico docking approach.

Aromatic Residues in Proteins: Re-Evaluating the Geometry and Energetics of π-π, Cation-π, and CH-π Interactions.

Aromatic residues can participate in various biomolecular interactions, such as π-π, cation-π, and CH-π interactions, which are essential for protein structure and function. Here, we re-evaluate the geometry and energetics of these interactions using quantum mechanical (QM) calculations, focusing on pairwise interactions involving the aromatic amino acids Phe, Tyr, and Trp and the cationic amino acids Arg and Lys. Our findings reveal that π-π interactions, while energetically favorable, are less abundant in structured proteins than commonly assumed and are often overshadowed by previously underappreciated, yet prevalent, CH-π interactions. Cation-π interactions, particularly those involving Arg, show strong binding energies and a specific geometric preference toward stacked conformations, despite the global QM minimum, suggesting that a rather perpendicular T-shape conformation should be more favorable. Our results support a more nuanced understanding of protein stabilization via interactions involving aromatic residues. On the one hand, our results challenge the traditional emphasis on π-π interactions in structured proteins by showing that CH-π and cation-π interactions contribute significantly to their structure. On the other hand, π-π interactions appear to be key stabilizers in solvated regions and thus may be particularly important to the stabilization of intrinsically disordered proteins.

Membrane-Nanoparticle Interactions: The Impact of Membrane Lipids.

The growing field of nanotechnology presents opportunity for applications across many sectors. Nanostructures, such as nanoparticles, hold distinct properties based on their size, shape, and chemical modifications that allow them to be utilized in both highly specific as well as broad capacities. As the classification of nanoparticles becomes more well-defined and the list of applications grows, it is imperative that their toxicity be investigated. One such cellular system that is of importance are cellular membranes (biomembranes). Membranes present one of the first points of contact for nanoparticles at the cellular level. This review will address current studies aimed at defining the biomolecular interactions of nanoparticles at the level of the cell membrane, with a specific focus of the interactions of nanoparticles with prominent lipid systems.

Exploring Protein S-Palmitoylation: Mechanisms, Detection, and Strategies for Inhibitor Discovery.

S-palmitoylation is a reversible and dynamic process that involves the addition of long-chain fatty acids to proteins. This protein modification regulates various aspects of protein function, including subcellular localization, stability, conformation, and biomolecular interactions. The zinc finger DHHC (ZDHHC) domain-containing protein family is the main group of enzymes responsible for catalyzing protein S-palmitoylation, and 23 members have been identified in mammalian cells. Many proteins that undergo S-palmitoylation have been linked to disease pathogenesis and progression, suggesting that the development of effective inhibitors is a promising therapeutic strategy. Reducing the protein S-palmitoylation level can target either the PATs directly or their substrates. However, there are rare clinically effective S-palmitoylation inhibitors. This review aims to provide an overview of the S-palmitoylation field, including the catalytic mechanism of ZDHHC, S-palmitoylation detection methods, and the functional impact of protein S-palmitoylation. Additionally, this review focuses on current strategies for expanding the chemical toolbox to develop novel and effective inhibitors that can reduce the level of S-palmitoylation of the target protein.

Biomolecular Interactions and Anticancer Mechanisms of Ru(II)-Arene Complexes of Cinnamaldehyde-Derived Thiosemicarbazone Ligands: Analysis Combining In Silico and In Vitro Approaches.

Our study focuses on synthesizing and exploring the potential of three N-(4) substituted thiosemicarbazones derived from cinnamic aldehyde, alongside their Ru(II)-(η6 -p-cymene)/(η6-benzene) complexes. The synthesized compounds were comprehensively characterized using a range of analytical techniques, including FT-IR, UV-visible spectroscopy, NMR (1H, 13C), and HRMS. We investigated their electronic and physicochemical properties via density functional theory (DFT). X-ray crystal structures validated structural differences identified by DFT. Molecular docking predicted promising bioactivities, supported by experimental observations. Notably, docking with EGFR suggested an inhibitory potential against this cancer-related protein. Spectroscopic titrations revealed significant DNA/BSA binding affinities, particularly with DNA intercalation and BSA hydrophobic interactions. RuPCAM displayed the strongest binding affinity with DNA (Kb = 6.23 × 107 M-1) and BSA (Kb = 9.75 × 105 M-1). Assessed the cytotoxicity of the complexes on cervical cancer cells (HeLa), and breast cancer cells (MCF-7 and MDA-MB 231), revealing remarkable potency. Additionally, selectivity was assessed by examining MCF-10a normal cell lines. The active complexes were found to trigger apoptosis, a vital cellular process crucial for evaluating their potential as anticancer agents utilizing staining assays and flow cytometry analysis. Intriguingly, complexation with Ru(II)-arene precursors significantly amplified the bioactivity of thiosemicarbazones, unveiling promising avenues toward the creation of powerful anticancer agents.

High-affinity biomolecular interactions are modulated by low-affinity binders

The strength of molecular interactions is characterized by their dissociation constants (KD). Only high-affinity interactions (KD ≤ 10−8 M) are extensively investigated and support binary on/off switches. However, such analyses have discounted the presence of low-affinity binders (KD > 10−5 M) in the cellular environment. We assess the potential influence of low-affinity binders on high-affinity interactions. By employing Gillespie stochastic simulations and continuous methods, we demonstrate that the presence of low-affinity binders can alter the kinetics and the steady state of high-affinity interactions. We refer to this effect as ‘herd regulation’ and have evaluated its possible impact in two different contexts including sex determination in Drosophila melanogaster and in signalling systems that employ molecular thresholds. We have also suggested experiments to validate herd regulation in vitro. We speculate that low-affinity binders are prevalent in biological contexts where the outcomes depend on molecular thresholds impacting homoeostatic regulation.

Dynamic and large field of view photonic resonator absorption microscopy for ultrasensitive digital resolution detection of nucleic acid and protein biomarkers

In this paper, we describe a biosensing instrument based on our previously developed photonic resonator absorption microscope (PRAM) that incorporates autofocus, digital representation of the gold nanoparticle (AuNP) accumulation, and the ability to gather time-series image sequences of AuNP attachment and detachment from the photonic crystal (PC) surface. The combined capabilities are used to fully automate PRAM image collection during biomolecular assays to enable tiling of PRAM images to provide millimeter-scale field of view. The instrument can also gather PRAM “movies” that enables digital showcasing and dynamic counting AuNPs as they arrive and depart from the PC surface. We utilize the capabilities in the context of two biomolecular assays for detection of protein biomarkers in a conventional AuNP-tagged sandwich format. Utilizing dynamic counting of AuNP attachment and detachment events during the assay we present a detection for microRNA-375 (miRNA-375) down to 1 aM with a 10-min, room temperature, enzyme-free approach, while revealing characteristics of the binding-rate and unbinding-rate of the biomolecular interactions. Our instrument can potentially find broad applications in multiplexed point-of-care diagnostic testing, and as a general-purpose tool for quantitative characterization of biomolecular binding kinetics with single-molecule resolution.

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.

Towards the prediction of general biomolecular interactions with AI.

Towards the prediction of general biomolecular interactions with AI.

MAGPIE: An interactive tool for visualizing and analyzing protein-ligand interactions.

Quantitative tools to compile and analyze biomolecular interactions among chemically diverse binding partners would improve therapeutic design and aid in studying molecular evolution. Here we present Mapping Areas of Genetic Parsimony In Epitopes (MAGPIE), a publicly available software package for simultaneously visualizing and analyzing thousands of interactions between a single protein or small molecule ligand (the "target") and all of its protein binding partners ("binders"). MAGPIE generates an interactive three-dimensional visualization from a set of protein complex structures that share the target ligand, as well as sequence logo-style amino acid frequency graphs that show all the amino acids from the set of protein binders that interact with user-defined target ligand positions or chemical groups. MAGPIE highlights all the salt bridge and hydrogen bond interactions made by the target in the visualization and as separate amino acid frequency graphs. Finally, MAGPIE collates the most common target-binder interactions as a list of "hotspots," which can be used to analyze trends or guide the de novo design of protein binders. As an example of the utility of the program, we used MAGPIE to probe how different antibody fragments bind a viral antigen; how a common metabolite binds diverse protein partners; and how two ligands bind orthologs of a well-conserved glycolytic enzyme for a detailed understanding of evolutionarily conserved interactions involved in its activation and inhibition. MAGPIE is implemented in Python 3 and freely available at https://github.com/glasgowlab/MAGPIE, along with sample datasets, usage examples, and helper scripts to prepare input structures.