Denaturing for Nanoarchitectonics: Local and Periodic UV-Laser Photodeactivation of Protein Biolayers to Create Functional Patterns for Biosensing

The nanostructuration of biolayers has become a paradigm for exploiting nanoscopic light-matter phenomena for biosensing, among other biomedical purposes. In this work, we present a photopatterning method to create periodic structures of biomacromolecules based on a local and periodic mild denaturation of protein biolayers mediated by UV-laser irradiation. These nanostructures are constituted by a periodic modulation of the protein activity, so they are free of topographic and compositional changes along the pattern. Herein, we introduce the approach, explore the patterning parameters, characterize the resulting structures, and assess their overall homogeneity. This UV-based patterning principle has proven to be an easy, cost-effective, and fast way to fabricate large areas of homogeneous one-dimensional protein patterns (2 min, 15 × 1.2 mm, relative standard deviation ≃ 16%). This work also investigates the implementation of these protein patterns as transducers for diffractive biosensing. Using a model immunoassay, these patterns have demonstrated negligible signal contributions from non-specific bindings and comparable experimental limits of detection in buffer media and in human serum (53 and 36 ng·mL^-1 of unlabeled IgG, respectively).

Teaching Essential EMG Theory to Kinesiologists and Physical Therapists Using Analogies Visual Descriptions, and Qualitative Analysis of Biophysical Concepts

Electromyography (EMG) is a multidisciplinary field that brings together allied health (kinesiology and physical therapy) and the engineering sciences (biomedical and electrical). Since the physical sciences are used in the measurement of a biological process, the presentation of the theoretical foundations of EMG is most conveniently conducted using math and physics. However, given the multidisciplinary nature of EMG, a course will most likely include students from diverse backgrounds, with varying levels of math and physics. This is a pedagogical paper that outlines an approach for teaching foundational concepts in EMG to kinesiologists and physical therapists that uses a combination of analogies, visual descriptions, and qualitative analysis of biophysical concepts to develop an intuitive understanding for those who are new to surface EMG. The approach focuses on muscle fiber action potentials (MFAPs), motor unit action potentials (MUAPs), and compound muscle action potentials (CMAPs) because changes in these waveforms are much easier to identify and describe in comparison to the surface EMG interference pattern (IP).

Effect of Protein–Protein Interactions on Translational Diffusion of Spheroidal Proteins

One of the commonly accepted approaches to estimate protein–protein interactions (PPI) in aqueous solutions is the analysis of their translational diffusion. The present review article observes a phenomenological approach to analyze PPI effects via concentration dependencies of self- and collective translational diffusion coefficient for several spheroidal proteins derived from the pulsed field gradient NMR (PFG NMR) and dynamic light scattering (DLS), respectively. These proteins are rigid globular α-chymotrypsin (ChTr) and human serum albumin (HSA), and partly disordered α-casein (α-CN) and β-lactoglobulin (β-Lg). The PPI analysis enabled us to reveal the dominance of intermolecular repulsion at low ionic strength of solution (0.003–0.01 M) for all studied proteins. The increase in the ionic strength to 0.1–1.0 M leads to the screening of protein charges, resulting in the decrease of the protein electrostatic potential. The increase of the van der Waals potential for ChTr and α-CN characterizes their propensity towards unstable weak attractive interactions. The decrease of van der Waals interactions for β-Lg is probably associated with the formation of stable oligomers by this protein. The PPI, estimated with the help of interaction potential and idealized spherical molecular geometry, are in good agreement with experimental data.

Review of historic article: Huxley 1957 Muscle Structure and theories of contraction. Progress in Biophysics and biophysical chemistry, 7, 255-318

The article by Andrew Huxley in this journal in 1957, "Muscle Structure and theories of Contraction" is much more than a standard review of a field. It is itself a major theoretical modelling achievement: the first mathematical model of the contractile process in skeletal muscle. That model was based on careful microscopic analysis of the striation patterns in skeletal muscles. Cited 4456 times, it holds the record for this journal.

Biophysical properties of hydrogels for mimicking tumor extracellular matrix

The extracellular matrix (ECM) is an essential component of the tumor microenvironment. It plays a critical role in regulating cell-cell and cell-matrix interactions. However, there is lack of systematic and comparative studies on different widely-used ECM mimicking hydrogels and their properties, making the selection of suitable hydrogels for mimicking different in vivo conditions quite random. This study systematically evaluates the biophysical attributes of three widely used natural hydrogels (Matrigel, collagen gel and agarose gel) including complex modulus, loss tangent, diffusive permeability and pore size. A new and facile method was developed combining Critical Point Drying, Scanning Electron Microscopy imaging and a MATLAB image processing program (CSM method) for the characterization of hydrogel microstructures. This CSM method allows accurate measurement of the hydrogel pore size down to nanometer resolution. Furthermore, a microfluidic device was implemented to measure the hydrogel permeability (P_d) as a function of particle size and gel concentration. Among the three gels, collagen gel has the lowest complex modulus, medium pore size, and the highest loss tangent. Agarose gel exhibits the highest complex modulus, the lowest loss tangent and the smallest pore size. Collagen gel and Matrigel produced complex moduli close to that estimated for cancer ECM. The P_d of these hydrogels decreases significantly with the increase of particle size. By assessing different hydrogels' biophysical characteristics, this study provides valuable insights for tailoring their properties for various three-dimensional cancer models.

G-Quadruplex-Binding Proteins: Promising Targets for Drug Design

G-quadruplexes (G4s) are non-canonical secondary nucleic acid structures. Sequences with the potential to form G4s are abundant in regulatory regions of the genome including telomeres, promoters and 5′ non-coding regions, indicating they fulfill important genome regulatory functions. Generally, G4s perform various biological functions by interacting with proteins. In recent years, an increasing number of G-quadruplex-binding proteins have been identified with biochemical experiments. G4-binding proteins are involved in vital cellular processes such as telomere maintenance, DNA replication, gene transcription, mRNA processing. Therefore, G4-binding proteins are also associated with various human diseases. An intensive study of G4-protein interactions provides an attractive approach for potential therapeutics and these proteins can be considered as drug targets for novel medical treatment. In this review, we present biological functions and structural properties of G4-binding proteins, and discuss how to exploit G4-protein interactions to develop new therapeutic targets.

Membrane Cargo Density-Dependent Interaction between Protein and Lipid Domains on the Giant Unilamellar Vesicles

Protein cargos anchored on the lipid membrane can be segregated by fluidic domain phase separation. Lipid membranes at certain compositions may separate into lipid domains to segregate cargos, and protein cargos themselves may be involved in protein condensate domain formation with multivalent binding proteins to segregate cargos. Recent studies suggest that these two driving forces of phase separation closely interact on the lipid membranes to promote codomain formation. In this report, we studied the effect of cargo density on the outcome of the cargo phase separation on giant unilamellar vesicles. Proteins and lipids are connected only by the anchored cargos, so it was originally hypothesized that higher cargo density would increase the degree of interaction between the lipid and protein domains, promoting more phase separation. However, fluorescence image analysis on different cargo densities showed that the cooperative domain formation and steric pressure are at a tug of war opposing each other. Cooperative domain formation is dominant under lower anchor density conditions, and above a threshold density, steric pressure was dominant opposing the domain formation. The result suggests that the cargo density is a key parameter affecting the outcome of cargo organization on the lipid membranes by phase separation.

Physical constraints on thermoregulation and flight drive morphological evolution in bats

Body size and shape fundamentally determine organismal energy requirements by modulating heat and mass exchange with the environment and the costs of locomotion, thermoregulation, and maintenance. Ecologists have long used the physical linkage between morphology and energy balance to explain why the body size and shape of many organisms vary across climatic gradients, e.g., why larger endotherms are more common in colder regions. However, few modeling exercises have aimed at investigating this link from first principles. Body size evolution in bats contrasts with the patterns observed in other endotherms, probably because physical constraints on flight limit morphological adaptations. Here, we develop a biophysical model based on heat transfer and aerodynamic principles to investigate energy constraints on morphological evolution in bats. Our biophysical model predicts that the energy costs of thermoregulation and flight, respectively, impose upper and lower limits on the relationship of wing surface area to body mass (S-MR), giving rise to an optimal S-MR at which both energy costs are minimized. A comparative analysis of 278 species of bats supports the model’s prediction that S-MR evolves toward an optimal shape and that the strength of selection is higher among species experiencing greater energy demands for thermoregulation in cold climates. Our study suggests that energy costs modulate the mode of morphological evolution in bats—hence shedding light on a long-standing debate over bats’ conformity to ecogeographical patterns observed in other mammals—and offers a procedure for investigating complex macroecological patterns from first principles.

Calcium selective channel TRPV6: Structure, function, and implications in health and disease

Calcium-selective channel TRPV6 (Transient Receptor Potential channel family, Vanilloid subfamily member 6) belongs to the TRP family of cation channels and plays critical roles in transcellular calcium (Ca2+) transport, reuptake of Ca2+ into cells, and maintaining a local low Ca2+ environment for certain biological processes. Recent crystal and cryo-electron microscopy-based structures of TRPV6 have revealed mechanistic insights on how the protein achieves Ca2+ selectivity, permeation, and inactivation by calmodulin. The TRPV6 protein is expressed in a range of epithelial tissues such as the intestine, kidney, placenta, epididymis, and exocrine glands such as the pancreas, prostate and salivary, sweat, and mammary glands. The TRPV6 gene is a direct transcriptional target of the active form of vitamin D and is efficiently regulated to meet the body's need for Ca2+ demand. In addition, TRPV6 is also regulated by the level of dietary Ca2+ and under physiological conditions such as pregnancy and lactation. Genetic models of loss of function in TRPV6 display hypercalciuria, decreased bone marrow density, deficient weight gain, reduced fertility, and in some cases alopecia. The models also reveal that the channel plays an indispensable role in maintaining maternal-fetal Ca2+ transport and low Ca2+ environment in the epididymal lumen that is critical for male fertility. Most recently, loss of function mutations in TRPV6 gene is linked to transient neonatal hyperparathyroidism and early onset chronic pancreatitis. TRPV6 is overexpressed in a wide range of human malignancies and its upregulation is strongly correlated to tumor aggressiveness, metastasis, and poor survival in selected cancers. This review summarizes the current state of knowledge on the expression, structure, biophysical properties, function, polymorphisms, and regulation of TRPV6. The aberrant expression, polymorphisms, and dysfunction of this protein linked to human diseases are also discussed.

Kinetic interplay between droplet maturation and coalescence modulates shape of aged protein condensates

Biomolecular condensates formed by the process of liquid-liquid phase separation (LLPS) play diverse roles inside cells, from spatiotemporal compartmentalisation to speeding up chemical reactions. Upon maturation, the liquid-like properties of condensates, which underpin their functions, are gradually lost, eventually giving rise to solid-like states with potential pathological implications. Enhancement of inter-protein interactions is one of the main mechanisms suggested to trigger the formation of solid-like condensates. To gain a molecular-level understanding of how the accumulation of stronger interactions among proteins inside condensates affect the kinetic and thermodynamic properties of biomolecular condensates, and their shapes over time, we develop a tailored coarse-grained model of proteins that transition from establishing weak to stronger inter-protein interactions inside condensates. Our simulations reveal that the fast accumulation of strongly binding proteins during the nucleation and growth stages of condensate formation results in aspherical solid-like condensates. In contrast, when strong inter-protein interactions appear only after the equilibrium condensate has been formed, or when they accumulate slowly over time with respect to the time needed for droplets to fuse and grow, spherical solid-like droplets emerge. By conducting atomistic potential-of-mean-force simulations of NUP-98 peptides-prone to forming inter-protein [Formula: see text]-sheets-we observe that formation of inter-peptide [Formula: see text]-sheets increases the strength of the interactions consistently with the loss of liquid-like condensate properties we observe at the coarse-grained level. Overall, our work aids in elucidating fundamental molecular, kinetic, and thermodynamic mechanisms linking the rate of change in protein interaction strength to condensate shape and maturation during ageing.

A Micropatterning Assay for Measuring Cell Chirality

Chirality is an intrinsic cellular property, which depicts the asymmetry in terms of polarization along the left-right axis of the cell. As this unique property attracts increasing attention due to its important roles in both development and disease, a standardized quantification method for characterizing cell chirality would advance research and potential applications. In this protocol, we describe a multicellular chirality characterization assay that utilizes micropatterned arrays of cells. Cellular micropatterns are fabricated on titanium/gold-coated glass slides via microcontact printing. After seeding on the geometrically defined (e.g., ring-shaped), protein-coated islands, cells directionally migrate and form a biased alignment toward either the clockwise or the counterclockwise direction, which can be automatically analyzed and quantified by a custom-written MATLAB program. Here we describe in detail the fabrication of micropatterned substrates, cell seeding, image collection, and data analysis and show representative results obtained using the NIH/3T3 cells. This protocol has previously been validated in multiple published studies and is an efficient and reliable tool for studying cell chirality in vitro.

Protein assembly and crowding simulations

Proteins encounter frequent molecular interactions in biological environments. Computer simulations have become an increasingly important tool in providing mechanistic insights into how such interactions in vivo relate to their biological function. The review here focuses on simulations describing protein assembly and molecular crowding effects as two important aspects that are distinguished mainly by how specific and long-lived protein contacts are. On the topic of crowding, recent simulations have provided new insights into how crowding affects protein folding and stability, modulates enzyme activity, and affects diffusive properties. Recent studies of assembly processes focus on assembly pathways, especially for virus capsids, amyloid aggregation pathways, and the role of multivalent interactions leading to phase separation. Also, discussed are technical challenges in achieving increasingly realistic simulations of interactions in cellular environments.

Transport of a self-propelled tracer through a hairy cylindrical channel: interplay of stickiness and activity

Active transport of biomolecules assisted by motor proteins is imperative for the proper functioning of cellular activities. Inspired by the diffusion of active agents in crowded cellular channels, we computationally investigate the transport of an active tracer through a polymer grafted cylindrical channel by varying the activity of the tracer and stickiness of the tracer to the polymers. Our results reveal that the passive tracer exhibits profound subdiffusion with increasing stickiness by exploring deep into the grafted polymeric zone, while purely repulsive one prefers to diffuse through the pore-like space created along the cylindrical axis of the channel. In contrast, the active tracer shows faster dynamics and intermediate superdiffusion even though the tracer preferentially stays close to the dense polymeric region. This observation is further supported by the sharp peaks in the density profile of the probability of radial displacement of the tracer. We discover that the activity plays an important role in deciding the pathway that the tracer takes through the narrow channel. Interestingly, increasing the activity washes out the effect of stickiness. Adding to this, van-Hove functions manifest that the active tracer dynamics deviates from Gaussianity, and the degree of deviation grows with the activity. Our work has direct implications on how effective transportation and delivery of cargo can be achieved through a confined medium where activity, interactions, and crowding are interplaying. Looking ahead, these factors will be crucial for understanding the mechanism of artificial self-powered machines navigating through the cellular channels and performing in vivo challenging tasks.

RNA length has a non-trivial effect in the stability of biomolecular condensates formed by RNA-binding proteins

Biomolecular condensates formed via liquid-liquid phase separation (LLPS) play a crucial role in the spatiotemporal organization of the cell material. Nucleic acids can act as critical modulators in the stability of these protein condensates. To unveil the role of RNA length in regulating the stability of RNA binding protein (RBP) condensates, we present a multiscale computational strategy that exploits the advantages of a sequence-dependent coarse-grained representation of proteins and a minimal coarse-grained model wherein proteins are described as patchy colloids. We find that for a constant nucleotide/protein ratio, the protein fused in sarcoma (FUS), which can phase separate on its own-i.e., via homotypic interactions-only exhibits a mild dependency on the RNA strand length. In contrast, the 25-repeat proline-arginine peptide (PR25), which does not undergo LLPS on its own at physiological conditions but instead exhibits complex coacervation with RNA-i.e., via heterotypic interactions-shows a strong dependence on the length of the RNA strands. Our minimal patchy particle simulations suggest that the strikingly different effect of RNA length on homotypic LLPS versus RBP-RNA complex coacervation is general. Phase separation is RNA-length dependent whenever the relative contribution of heterotypic interactions sustaining LLPS is comparable or higher than those stemming from protein homotypic interactions. Taken together, our results contribute to illuminate the intricate physicochemical mechanisms that influence the stability of RBP condensates through RNA inclusion.

Bicontinuous inverted cubic phase stabilization as an index of antimicrobial and membrane fusion peptide activity

Some antimicrobial peptides (AMPs) and membrane fusion-catalyzing peptides (FPs) stabilize bicontinuous inverted cubic (QII) phases. Previous authors proposed a topological rationale: since AMP-induced pores, fusion intermediates, and QII phases all have negative Gaussian curvature (NGC), peptides which produce NGC in one structure also do it in another. This assumes that peptides change the curvature energy of the lipid membranes. Here I test this with a Helfrich curvature energy model. First, experimentally, I show that lipid systems often used to study peptide NGC have NGC without peptides at higher temperatures. To determine the net effect of an AMP on NGC, the equilibrium phase behavior of the host lipids must be determined. Second, the model shows that AMPs must make large changes in the curvature energy to stabilize AMP-induced pores. Peptide-induced changes in elastic constants affect pores and QII phase differently. Changes in spontaneous curvature affect them in opposite ways. The observed correlation between QII phase stabilization and AMP activity doesn't show that AMPs act by lowering pore curvature energy. A different rationale is proposed. In theory, AMPs could simultaneously stabilize QII phase and pores by drastically changing two particular elastic constants. This could be tested by measuring AMP effects on the individual constants. I propose experiments to do that. Unlike AMPs, FPs must make only small changes in the curvature energy to catalyze fusion. It they act in this way, their fusion activity should correlate with their ability to stabilize QII phases.

Structural modeling of Omicron spike protein and its complex with human ACE-2 receptor: Molecular basis for high transmissibility of the virus

Omicron is a new variant of SARS-CoV-2, which is currently infecting people around the world. Spike glycoprotein, an important molecule in pathogenesis of infection has been modeled and the interaction of its Receptor Binding Domain with human ACE-receptor has been analysed by simulation studies. Structural analysis of Omicron spike glycoprotein shows the 30 mutations to be distributed over all domains of the trimeric protein, wherein the mutant residues are seen to be participating in higher number of intra-molecular interactions including two salt bridges emanating from mutant residues thereby stabilizing their conformation, as compared to wild type. Complex of Receptor Binding Domain (RBD) with human ACE-2 receptor shows seven mutations at interacting interface comprising of two ionic interactions, eight hydrogen bonds and seven Van der Waals interactions. The number and quality of these interactions along with other binding biophysical parameters suggests more potency of RBD domain to the receptor as compared to the wild type counterpart. Results of this study explains the high transmissibility of Omicron variant of SARS-CoV-2 that is currently observed across the world.

A multiscale biophysical model gives quantized metachronal waves in a lattice of beating cilia

Motile cilia are slender, hair-like cellular appendages that spontaneously oscillate under the action of internal molecular motors and are typically found in dense arrays. These active filaments coordinate their beating to generate metachronal waves that drive long-range fluid transport and locomotion. Until now, our understanding of their collective behavior largely comes from the study of minimal models that coarse grain the relevant biophysics and the hydrodynamics of slender structures. Here we build on a detailed biophysical model to elucidate the emergence of metachronal waves on millimeter scales from nanometer-scale motor activity inside individual cilia. Our study of a one-dimensional lattice of cilia in the presence of hydrodynamic and steric interactions reveals how metachronal waves are formed and maintained. We find that, in homogeneous beds of cilia, these interactions lead to multiple attracting states, all of which are characterized by an integer charge that is conserved. This even allows us to design initial conditions that lead to predictable emergent states. Finally, and very importantly, we show that, in nonuniform ciliary tissues, boundaries and inhomogeneities provide a robust route to metachronal waves.

Nonequilibrium Self-Organization of Lipids into Hierarchically Ordered and Compositionally Graded Cylindrical Smectics

When a dry mass of certain amphiphiles encounters water, a spectacular interfacial instability ensues: It gives rise to the formation of ensembles of fingerlike tubular protrusions called myelin figures─tens of micrometers wide and tens to hundreds of micrometers long─representing a novel class of nonequilibrium higher-order self-organization. Here, we report that when phase-separating mixtures of unsaturated lipid, cholesterol, and sphingomyelin are hydrated, the resulting myelins break symmetry and couple their compositional degrees of freedom with the extended myelinic morphology: They produce complementary, interlamellar radial gradients of concentrations of cholesterol (and sphingomyelin) and unsaturated lipid, which stands in stark contrast to interlamellar, lateral phase separation in equilibrated morphologies. Furthermore, the corresponding gradients of molecule-specific chemistries (i.e., cholesterol extraction by methyl-β-cyclodextrin and GM₁ binding by cholera toxin) produce unusual morphologies comprising compositionally graded vesicles and buckled tubes. We propose that kinetic differences in the information processing of hydration characteristics of individual molecules while expending energy dictate this novel behavior of lipid mixtures undergoing hydration.

Stoichiometry Controls the Dynamics of Liquid Condensates of Associative Proteins

Multivalent associative proteins with strong complementary interactions play a crucial role in phase separation of intracellular liquid condensates. We study the internal dynamics of such "bond-network" condensates comprising two complementary proteins via scaling analysis and molecular dynamics. We find that when stoichiometry is balanced, relaxation slows down dramatically due to a scarcity of alternative binding partners following bond breakage. This microscopic slow-down strongly affects the bulk diffusivity, viscosity, and mixing, which provides a means to experimentally test this prediction.

Conformational Freedom and Topological Confinement of Proteins in Biomolecular Condensates

The emergence of biomolecular condensation and liquid-liquid phase separation (LLPS) introduces a new layer of complexity into our understanding of cell and molecular biology. Evidence steadily grows indicating that condensates are not only implicated in physiology but also human disease. Macro- and mesoscale characterization of condensates as a whole have been instrumental in understanding their biological functions and dysfunctions. By contrast, the molecular level characterization of condensates and how condensates modify the properties of the molecules that constitute them thus far remain comparably scarce. In this minireview we summarize and discuss the findings of several recent studies that have focused on structure, dynamics, and interactions of proteins undergoing condensation. The mechanistic insights they provide help us identify the relevant properties nature and scientists can leverage to modulate the behavior of condensate systems. We also discuss the unique environment of the droplet surface and speculate on effects of topological constraints and physical exclusion on condensate properties.

Probing membrane protein interactions and signaling molecule homeostasis in plants by Förster resonance energy transfer analysis

Membrane proteins have key functions in signal transduction, transport, and metabolism. Therefore, deciphering the interactions between membrane proteins provides crucial information on signal transduction and the spatiotemporal organization of protein complexes. However, detecting the interactions and behaviors of membrane proteins in their native environments remains difficult. Förster resonance energy transfer (FRET) is a powerful tool for quantifying the dynamic interactions and assembly of membrane proteins without disrupting their local environment, supplying nanometer-scale spatial information and nanosecond-scale temporal information. In this review, we briefly introduce the basic principles of FRET and assess the current state of progress in the development of new FRET techniques (such as FRET-FLIM, homo-FRET, and smFRET) for the analysis of plant membrane proteins. We also describe the various FRET-based biosensors used to quantify the homeostasis of signaling molecules and the active state of kinases. Furthermore, we summarize recent applications of these advanced FRET sensors in probing membrane protein interactions, stoichiometry, and protein clustering, which have shed light on the complex biological functions of membrane proteins in living plant cells.

Homo-FRET Imaging to Study Protein-Protein Interaction and Complex Formation in Plants

Protein-protein interactions in living plant cells can be measured by changes in fluorescence anisotropy due to homo-FRET (Förster Resonance Energy Transfer). Here, the energy transfer between identical fluorophores, e.g., enhanced green fluorescent protein (EGFP) fused to a protein of interest, serves as a read-out for protein interaction and clustering. By applying homo-FRET imaging, not only dimeric complexes, but also bigger homomeric complex formation can be followed in vivo at high spatial and temporal resolution. Therefore, this method provides a powerful tool to investigate changes in complex formation over time in their natural environment with high precision at a subcellular level. Here, we describe the necessary theoretical background and how homo-FRET imaging is practically carried out. We also discuss potential pitfalls and points of consideration.

Single-Molecule Optical Tweezers Study of Protein-Membrane Interactions

Numerous proteins directly or indirectly bind membranes to exert their roles in a wide variety of biological processes. Such membrane binding often occurs in the presence of an external mechanical force. It remains challenging to quantify these interactions using traditional experimental approaches based on a large number of molecules, due to ensemble averaging or the lack of mechanical force. Here we described a new single-molecule approach based on high-resolution optical tweezers to characterize protein-membrane interactions. A single membrane binding protein is attached to the lipid bilayer coated on a silica bead via a flexible polypeptide linker, tethered to another bead via a long DNA handle, and pulled away from the bilayer using optical tweezers. Dynamic protein binding and unbinding is detected by the corresponding changes in the extension of the protein-DNA tether with high spatiotemporal resolution, which reveals the membrane binding affinity, kinetics, and intermediates. We demonstrated the method using C2 domains of extended synaptotagmin 2 (E-Syt2) with a detailed protocol. The method can be widely applied to investigate complex protein-membrane interactions under well-controlled experimental conditions.

Identifying Specific Small Molecule-Protein Interactions Using Target Abundance-Based Fitness Screening (TAFiS)

Traditional small molecule antifungal discovery efforts often utilize high-throughput (HTP) biochemical or whole-cell phenotypic screens to identify novel candidates. However, both methods have limitations which hinder the rapid identification of physiologically active compounds that act via a defined mechanism of action. The method described herein is an efficient, sensitive, and HTP compatible approach that utilizes the principles of competitive fitness to rapidly identify small molecules that functionally interact with a specific target protein within whole cells.

Charge Sensitive Optical Detection for Measurement of Small-Molecule Binding Kinetics

Charge sensitive optical detection (CSOD) technique is a label-free method for real-time measurement of molecular interactions. Traditional label-free optical detection techniques mostly measure the mass of a molecule, and they are less sensitive to small molecules. In contrast, CSOD detects the charge of a molecule, where the signal does not diminish with the size of the molecule, thus capable for studying small molecules. In addition, CSOD is compatible with the standard microplate platform, making it suitable for high-throughput screening of drug candidates. In CSOD, an optical fiber functionalized with the probe molecule is dipped into a well of a microplate where an alternate perpendicular electrical field is applied to the fiber, which drives the fiber into oscillation because of the presence of surface charge on the fiber. The binding of the target molecules changes the charge of the fiber, and thus the amplitude and phase of the oscillating fiber, which are precisely measured through tracking of the optical images of the fiber tip.