Site-selective peptide bond hydrolysis and ligation in water by short peptide-based assemblies.

The evolution of complex chemical inventory from Darwin's nutrient-rich warm pond necessitated rudimentary yet efficient catalytic folds. Short peptides and their self-organized microstructures, ranging from spherical colloids to amyloidogenic aggregates might have played a crucial role in the emergence of contemporary catalytic entities. However, the question of how short peptide fragments had functions akin to contemporary complex enzymes to catalyze cleavage and formation of highly stable peptide bonds that constitute the backbone of all proteins remains an unresolved yet fundamentally important question in terms of the origins of enzymes. We report short-peptide-based spherical assemblies that demonstrated residue-specific cleavage and formation of peptide bonds of diverse peptide-based substrates under aqueous environment. Despite the short sequence length, the assemblies utilized the synergistic collaboration of four residues which included the catalytic triad of extant serine proteases with a nonproteinogenic amino acid (quinone moiety), to facilitate proteolysis, ligation, and a three-step (hydrolysis-ligation-hydrolysis) cascade. Such short-peptide-based catalytic assemblies argue for their candidacy as the earliest protein folds and open up avenues for biotechnological applications.

Exact Distribution of the Quantal Content in Synaptic Transmission.

During electrochemical signal transmission through synapses, triggered by an action potential (AP), a stochastic number of synaptic vesicles (SVs), called the "quantal content," release neurotransmitters in the synaptic cleft. It is widely accepted that the quantal content probability distribution is a binomial based on the number of ready-release SVs in the presynaptic terminal. But the latter number itself fluctuates due to its stochastic replenishment, hence the actual distribution of quantal content is unknown. We show that exact distribution of quantal content can be derived for general stochastic AP inputs in the steady state. For fixed interval AP train, we prove that the distribution is a binomial, and corroborate our predictions by comparison with electrophysiological recordings from MNTB-LSO synapses of juvenile mice. For a Poisson train, we show that the distribution is nonbinomial. Moreover, we find exact moments of the quantal content in the Poisson and other general cases, which may be used to obtain the model parameters from experiments.

Emergence of a short peptide based reductase via activation of the model hydride rich cofactor.

In extant biology, large and complex enzymes employ low molecular weight cofactors such as dihydronicotinamides as efficient hydride transfer agents and electron carriers for the regulation of critical metabolic processes. In absence of complex contemporary enzymes, these molecular cofactors are generally inefficient to facilitate any reactions on their own. Herein, we report short peptide-based amyloid nanotubes featuring exposed arrays of cationic and hydrophobic residues that can bind small molecular weak hydride transfer agents (NaBH4) to facilitate efficient reduction of ester substrates in water. In addition, the paracrystalline amyloid phases loaded with borohydrides demonstrate recyclability, substrate selectivity and controlled reduction and surpass the capabilities of standard reducing agent such as LiAlH4. The amyloid microphases and their collaboration with small molecular cofactors foreshadow the important roles that short peptide-based assemblies might have played in the emergence of protometabolism and biopolymer evolution in prebiotic earth.

Estimates of differential toxin expression governing heterogeneous intracellular lifespans of Streptococcus pneumoniae.

Following invasion of the host cell, pore-forming toxins secreted by pathogens compromise vacuole integrity and expose the microbe to diverse intracellular defence mechanisms. However, the quantitative correlation between toxin expression levels and consequent pore dynamics, fostering the intracellular life of pathogens, remains largely unexplored. In this study, using Streptococcus pneumoniae and its secreted pore-forming toxin pneumolysin (Ply) as a model system, we explored various facets of host-pathogen interactions in the host cytosol. Using time-lapse fluorescence imaging, we monitored pore formation dynamics and lifespans of different pneumococcal subpopulations inside host cells. Based on experimental histograms of various event timescales such as pore formation time, vacuolar death or cytosolic escape time and total degradation time, we developed a mathematical model based on first-passage processes that could correlate the event timescales to intravacuolar toxin accumulation. This allowed us to estimate Ply production rate, burst size and threshold Ply quantities that trigger these outcomes. Collectively, we present a general method that illustrates a correlation between toxin expression levels and pore dynamics, dictating intracellular lifespans of pathogens.

Temporal (Dis)Assembly of Peptide Nanostructures Dictated by Native Multistep Catalytic Transformations.

Emergence of complex catalytic machinery via simple building blocks under non-equilibrium conditions can contribute toward the system level understanding of the extant biocatalytic reaction network that fuels metabolism. Herein, we report temporal (dis)assembly of peptide nanostructures in presence of a cofactor dictated by native multistep cascade transformations. The short peptide can form a dynamic covalent bond with the thermodynamically activated substrate and recruit cofactor hemin to access non-equilibrium catalytic nanostructures (positive feedback). The neighboring imidazole and hemin moieties in the assembled state rapidly converted the substrate to product(s) via a two-step cascade reaction (hydrolase-peroxidase like) that subsequently triggered the disassembly of the catalytic nanostructures (negative feedback). The feedback coupled reaction cycle involving intrinsic catalytic prowess of short peptides to realize the advanced trait of two-stage cascade degradation of a thermodynamically activated substrate foreshadows the complex non-equilibrium protometabolic networks that might have preceded the chemical emergence of life.

Exploitation of Catalytic Dyads by Short Peptide-Based Nanotubes for Enantioselective Covalent Catalysis.

Extant enzymes with precisely arranged multiple residues in their three-dimensional binding pockets are capable of exhibiting remarkable stereoselectivity towards a racemic mixture of substrates. However, how early protein folds that possibly featured short peptide fragments facilitated enantioselective catalytic transformations important for the emergence of homochirality still remains an intriguing open question. Herein, enantioselective hydrolysis was shown by short peptide-based nanotubes that could exploit multiple solvent-exposed residues to create chiral binding grooves to covalently interact and subsequently hydrolyse one enantiomer preferentially from a racemic pool. Single or double-site chiral mutations led to opposite but diminished and even complete loss of enantioselectivities, suggesting the critical roles of the binding enthalpies from the precise localization of the active site residues, despite the short sequence lengths. This work underpins the enantioselective catalytic prowess of short peptide-based folds and argues their possible role in the emergence of homochiral chemical inventory.

Temporal Self-Regulation of Mechanical Properties via Catalytic Amyloid Polymers of a Short Peptide.

We report a short peptide that accessed dynamic catalytic polymers to demonstrate four-stage (sol-gel-weak gel-strong gel) temporal self-regulation of its mechanical properties. The peptide exploited its intrinsic catalytic capabilities of manipulating C-C bonds (retro-aldolase-like) that resulted in a nonlinear variation in the catalytic rate. The seven-residue sequence exploited two lysines for binding and cleaving the thermodynamically activated substrate that subsequently led to the self-regulation of the mechanical strengths of the polymerized states as a function of time and reaction progress. Interestingly, the polymerization events were modulated by the different catalytic potentials of the two terminal lysines to cleave the substrate, covalently trap the electrophilic products, and subsequently control the mechanical properties of the system.

Emergence of Photomodulated Protometabolism by Short Peptide-Based Assemblies.

In the early Earth, rudimentary enzymes must have utilized the available light energy source to modulate protometabolic processes. Herein, we report the light-responsive C-C bond manipulation via short peptide-based assemblies bound to the photosensitive molecular cofactor (azo-based photoswitch) where the energy of the light source regulated the binding sites which subsequently modulated the retro-aldolase activity. In the presence of a continual source of high-energy photons, temporal realization of a catalytically more proficient state could be achieved under nonequilibrium conditions. Further, the hydrophobic surface of peptide assemblies facilitated the binding of an orthogonal molecular catalyst that showed augmented activity (promiscuous hydrolytic activity) upon binding. This latent activity was utilized for the in situ generation of light-sensitive cofactor that subsequently modulated the retro-aldolase activity, thus creating a reaction network.

Dual enzyme-powered chemotactic cross ß amyloid based functional nanomotors.

Nanomotor chassis constructed from biological precursors and powered by biocatalytic transformations can offer important applications in the future, specifically in emergent biomedical techniques. Herein, cross ß amyloid peptide-based nanomotors (amylobots) were prepared from short amyloid peptides. Owing to their remarkable binding capabilities, these soft constructs are able to host dedicated enzymes to catalyze orthogonal substrates for motility and navigation. Urease helps in powering the self-diffusiophoretic motion, while cytochrome C helps in providing navigation control. Supported by the simulation model, the design principle demonstrates the utilization of two distinct transport behaviours for two different types of enzymes, firstly enhanced diffusivity of urease with increasing fuel (urea) concentration and secondly, chemotactic motility of cytochrome C towards its substrate (pyrogallol). Dual catalytic engines allow the amylobots to be utilized for enhanced catalysis in organic solvent and can thus complement the technological applications of enzymes.

Emergence of Catalytic Triad by Short Peptide Based Nanofibrillar Assemblies.

Through millions of years of the evolutionary journey, contemporary enzymes observed in extant metabolic pathways have evolved to become specialized, in contrast to their ancestors, which displayed promiscuous activities with wider substrate specificities. However, there remain critical gaps in our understanding of how these early enzymes could show such catalytic versatility despite lacking the complex three-dimensional folds of the existing modern-day enzymes. Herein, we report the emergence of a promiscuous catalytic triad by short amyloid peptide based nanofibers that access paracrystalline folds of ß-sheets to expose three residues (lysine, imidazole, and tyrosine) toward solvent. The ordered folded nanostructures could simultaneously catalyze two metabolically relevant chemical transformations via C-O and C-C bond manipulations, displaying both hydrolase and retro-aldolase-like activities. Further, the latent catalytic capabilities of the short peptide based promiscuous folds also helped in processing a cascade transformation, suggesting the important role they might have played in protometabolism and early evolutionary processes.

Covalent Organic Framework Cladding on Peptide-Amphiphile-Based Biomimetic Catalysts.

Peptide-based biomimetic catalysts are promising materials for efficient catalytic activity in various biochemical transformations. However, their lack of operational stability and fragile nature in non-aqueous media limit their practical applications. In this study, we have developed a cladding technique to stabilize biomimetic catalysts within porous covalent organic framework (COF) scaffolds. This methodology allows for the homogeneous distribution of peptide nanotubes inside the COF (TpAzo and TpDPP) backbone, creating strong noncovalent interactions that prevent leaching. We synthesized two different peptide-amphiphiles, C10FFVK and C10FFVR, with lysine (K) and arginine (R) at the C-termini, respectively, which formed nanotubular morphologies. The C10FFVK peptide-amphiphile nanotubes exhibit enzyme-like behavior and efficiently catalyze C-C bond cleavage in a buffer medium (pH 7.5). We produced nanotubular structures of TpAzo-C10FFVK and TpDPP-C10FFVK through COF cladding by using interfacial crystallization (IC). The peptide nanotubes encased in the COF catalyze C-C bond cleavage in a buffer medium as well as in different organic solvents (such as acetonitrile, acetone, and dichloromethane). The TpAzo-C10FFVK catalyst, being heterogeneous, is easily recoverable, enabling the reaction to be performed for multiple cycles. Additionally, the synthesis of TpAzo-C10FFVK thin films facilitates catalysis in flow. As control, we synthesized another peptide-amphiphile, C10FFVR, which also forms tubular assemblies. By depositing TpAzo COF crystallites on C10FFVR nanotubes through IC, we produced TpAzo-C10FFVR nanotubular structures that expectedly did not show catalysis, suggesting the critical role of the lysines in the TpAzo-C10FFVK.

Unsupervised Data-Driven Reconstruction of Molecular Motifs in Simple to Complex Dynamic Micelles.

The reshuffling mobility of molecular building blocks in self-assembled micelles is a key determinant of many their interesting properties, from emerging morphologies and surface compartmentalization, to dynamic reconfigurability and stimuli-responsiveness. However, the microscopic details of such complex structural dynamics are typically nontrivial to elucidate, especially in multicomponent assemblies. Here we show a machine-learning approach that allows us to reconstruct the structural and dynamic complexity of mono- and bicomponent surfactant micelles from high-dimensional data extracted from equilibrium molecular dynamics simulations. Unsupervised clustering of smooth overlap of atomic position (SOAP) data enables us to identify, in a set of multicomponent surfactant micelles, the dominant local molecular environments that emerge within them and to retrace their dynamics, in terms of exchange probabilities and transition pathways of the constituent building blocks. Tested on a variety of micelles differing in size and in the chemical nature of the constitutive self-assembling units, this approach effectively recognizes the molecular motifs populating them in an exquisitely agnostic and unsupervised way, and allows correlating them to their composition in terms of constitutive surfactant species.

A ~24 kDa protein isolated from protein isolates of Hawaijar, popular fermented soy food of North-East India exhibited promising antidiabetic potential via stimulating PI3K/AKT/GLUT4 signaling pathway of muscle glucose metabolism.

The present study investigated the antidiabetic potential of protein isolates from Hawaijar (HPI), a popular fermented soybean food of North-East India. Treatment with HPI significantly upregulated glucose uptake, glucose utilization, glucose-6-phosphate, and stimulated PI3K/AKT/GLUT4 pathway in high-glucose (HG)-treated myotubes. Signal silencing studies demonstrated that knockdown of insulin-dependent signaling molecule (IR) but not insulin-independent signaling molecule (AMPK) significantly inhibited HPI-induced activation of PI3K/AKT/GLUT4 pathway and glucose uptake in HG-treated myotubes. SDS-PAGE and immunoblotting analyses of HPI showed the reduction and/or absence of various subunits of 7S and 11S globulin protein and appearance of new proteins compared to respective non-fermented soy protein isolates. Using various chromatographic techniques, the present study further isolated a single protein (ISP, ~24 kDa) from HPI as one of the bioactive principles with promising glucose utilization potential via stimulating PI3K/AKT/GLUT4 pathway in HG-treated cells. ISP treatment along with insulin significantly stimulated PI3K/AKT/GLUT4 pathway and glucose uptake compared to either insulin or ISP alone treated cells against HG exposure suggesting the insulin sensitizing effect of ISP. Furthermore, ISP supplementation significantly reduced metabolic markers linked with diabetes in high-fructose high-fat diet-fed animal model of type 2 diabetes. This study demonstrated a novel molecular mechanism underlying the promising antidiabetic potential of HPI.

Nonequilibrium Amyloid Polymers Exploit Dynamic Covalent Linkage to Temporally Control Charge-Selective Catalysis.

Extant proteins exploit thermodynamically activated negatively charged coenzymes and hydrotropes to temporally access mechanistically important conformations that regulate vital biological functions, from metabolic reactions to expression modulation. Herein, we show that a short amyloid peptide can bind to a small molecular coenzyme by exploiting reversible covalent linkage to polymerize and access catalytically proficient nonequilibrium amyloid microphases. Subsequent hydrolysis of the activated coenzyme leads to depolymerization, realizing a variance of the surface charge of the assembly as a function of time. Such temporal change of surface charge dynamically modulates catalytic activities of the transient assemblies as observed in highly evolved modern-day biocatalysts.

Cross ß Amyloid Nanotubes Demonstrate Promiscuous Catalysis in a Chemical Reaction Network via Co-option.

In Darwin's warm pond rich with nutrients, lesser number of early catalytic machineries with modest capabilities were able to demonstrate promiscuity by catalyzing diverse biochemical transformations important for protometabolism. Herein, we report catalytically promiscuous amyloid-based short peptide assemblies that could concomitantly catalyse three metabolically important yet orthogonal reactions. The surface exposed catalytic dyads featuring lysines and imidazoles were utilized for C=N condensation via dynamic covalent linkages and modulation of protonation events, respectively. Further, the peptide assemblies could promiscuously catalyse hydrolysis as well as retro-aldol reactions, that could be co-opted to facilitate C=N bond formation, either by a feedforward-driven reaction network or by replenishing depleted substrates. The catalytic diversity of short peptide based promiscuous ß-sheet folds suggests their possible role in promoting the protometabolic network in early earth.

Short peptide-based cross-ß amyloids exploit dual residues for phosphoesterase like activity.

Herein, we report that short peptides are capable of exploiting their anti-parallel registry to access cross-ß stacks to expose more than one catalytic residue, exhibiting the traits of advanced binding pockets of enzymes. Binding pockets decorated with more than one catalytic residue facilitate substrate binding and process kinetically unfavourable chemical transformations. The solvent-exposed guanidinium and imidazole moieties on the cross-ß microphases synergistically bind to polarise and hydrolyse diverse kinetically stable model substrates of nucleases and phosphatase. Mutation of either histidine or arginine results in a drastic decline in the rate of hydrolysis. These results not only support the argument of short amyloid peptides as the earliest protein folds but also suggest their interactions with nucleic acid congeners, foreshadowing the mutualistic biopolymer relationships that fueled the chemical emergence of life.

A popular fermented soybean food of Northeast India exerted promising antihyperglycemic potential via stimulating PI3K/AKT/AMPK/GLUT4 signaling pathways and regulating muscle glucose metabolism in type 2 diabetes.

This study examined the antidiabetic efficacy of popular fermented soybean foods (FSF) of Northeast (NE) India. Results showed that among different FSF, aqueous extract of Hawaijar (AEH), a traditional FSF of Manipur, NE India, significantly augmented glucose utilization in cultured myotubes treated with high glucose (HG, 25 mM). Furthermore, AEH also upregulated glucose uptake, glucose-6-phosphate level, and phopho-PI3K/phospho-AKT/phospho-AMPK/GLUT4 protein expression in HG-treated myotubes. In vivo studies demonstrated that AEH supplementation (50, 100, or 200 mg/kg body weight/day, oral gavaging, 16 weeks) reduced body weight, fasting blood glucose, glycated hemoglobin, insulin resistance, and glucose intolerance in rats fed with high-fat diet (HFD). AEH supplementation stimulated phopho-PI3K/phospho-AKT/phospho-AMPK/GLUT4 signaling cascades involved in glucose metabolism of muscle tissues in diabetic rats. Chemical profiling of AEH (SDS-PAGE, immunoblotting, and HRMS) suggests the possible role of bioactive proteins/peptides and isoflavones underlying the antihyperglycemic potential AEH. Results from this study will be helpful for developing food-based prophylactics/therapeutics in managing hyperglycemia. PRACTICAL APPLICATIONS: Fermented soybean foods are gaining acceptance due to multiple health benefits. This study for the first time reports the antidiabetic potential of Hawaijar, an indigenous fermented soybean food of North-East India. Higher abundance of bioactive compounds (isoflavones and proteins/peptides) in Hawaijar may be responsible for the alleviation of impaired glucose metabolism associated with diabetes. The findings may be helpful for the development of a novel therapeutic to achieve better control of hyperglycemia and improve the lives of the patient population with diabetes.

First passage in the presence of stochastic resetting and a potential barrier.

Diffusion and first passage in the presence of stochastic resetting and potential bias have been of recent interest. We study a few models, systematically progressing in their complexity, to understand the usefulness of resetting. In the parameter space of the models, there are multiple continuous and discontinuous transitions where the advantage of resetting vanishes. We show these results analytically exactly for a tent potential, and numerically accurately for a quartic potential relevant to a magnetic system at low temperatures. We find that the spatial asymmetry of the potential across the barrier, and the number of absorbing boundaries, play a crucial role in determining the type of transition.

Fluorescent Microswimmers Based on Cross-ß Amyloid Nanotubes and Divergent Cascade Networks.

Shaped through millions of years of evolution, the spatial localization of multiple enzymes in living cells employs extensive cascade reactions to enable highly coordinated multimodal functions. Herein, by utilizing a complex divergent cascade, we exploit the catalytic potential as well as templating abilities of streamlined cross-ß amyloid nanotubes to yield two orthogonal roles simultaneously. The short peptide based paracrystalline nanotube surfaces demonstrated the generation of fluorescence signals within entangled networks loaded with alcohol dehydrogenase (ADH). The nanotubular morphologies were further used to generate cascade-driven microscopic motility through surface entrapment of sarcosine oxidase (SOX) and catalase (Cat). Moreover, a divergent cascade network was initiated by upstream catalysis of the substrate molecules through the surface mutation of catalytic moieties. Notably, the resultant downstream products led to the generation of motile fluorescent microswimmers by utilizing the two sets of orthogonal properties and, thus, mimicked the complex cascade-mediated functionalities of extant biology.

DeepBBBP: High Accuracy Blood-brain-barrier Permeability Prediction with a Mixed Deep Learning Model.

Blood-brain-barrier permeability (BBBP) is an important property that is used to establish the drug-likeness of a molecule, as it establishes whether the molecule can cross the BBB when desired. It also eliminates those molecules which are not supposed to cross the barrier, as doing so would lead to toxicity. BBBP can be measured in vivo, in vitro or in silico. With the advent and subsequent rise of in silico methods for virtual drug screening, quite a bit of work has been done to predict this feature using statistical machine learning (ML) and deep learning (DL) based methods. In this work a mixed DL-based model, consisting of a Multi-layer Perceptron (MLP) and Convolutional Neural Network layers, has been paired with Mol2vec. Mol2vec is a convenient and unsupervised machine learning technique which produces high-dimensional vector representations of molecules and its molecular substructures. These succinct vector representations are utilized as inputs to the mixed DL model that is used for BBBP predictions. Several well-known benchmarks incorporating BBBP data have been used for supervised training and prediction by our mixed DL model which demonstrates superior results when compared to existing ML and DL techniques used for predicting BBBP.